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Holy cow, is this thing exciting. esp32-P4: 👍 Pretty powerful microprocessor. 👍 High speed MIPI 480x800(!!) touchscreen display. 👍 High speed MIPI camera. ☹️ Onboard wifi/BT. 👀 $43!! My new leading candidate for a next-gen MicroPython SeedSigner.

Keith Mukai

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23,681 views • 3 months ago •via X (Twitter)

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This is BLITZ 🏍️ starring myself. I've tested a workflow that combines two of the best AI image editing models right now, Nano Banana and Seedream 4. Using these together feels like a superpower. Seedream 4 for instance generates much more dynamic camera angles BUT Nano Banana does a better job with overall consistency, so utilizing both is super beneficial. I wanted to create a sequence where I'm riding a Cyberbike with an electric booster that overclocks the motor to deliver short, high-risk bursts of extreme speed. The location is a white sand desert. I decided to also test Hailuo AI (MiniMax) start and end frame feature which in my opinion is one of the best since it understands so much about context and camera movement. Start and ends frames let you have much better control over camera movement but where Hailuo truly excels is that it understands speed and camera shake which are essential for any fast paced action sequences. The music was generated with Suno 4.5+ and some additional sound effects like the bike and wind in the desert were sourced from Artlist. Edited with Capcut. There's some more tips and tricks in the thread 👍👍

This is BLITZ 🏍️ starring myself. I've tested a workflow that combines two of the best AI image editing models right now, Nano Banana and Seedream 4. Using these together feels like a superpower. Seedream 4 for instance generates much more dynamic camera angles BUT Nano Banana does a better job with overall consistency, so utilizing both is super beneficial. I wanted to create a sequence where I'm riding a Cyberbike with an electric booster that overclocks the motor to deliver short, high-risk bursts of extreme speed. The location is a white sand desert. I decided to also test Hailuo AI (MiniMax) start and end frame feature which in my opinion is one of the best since it understands so much about context and camera movement. Start and ends frames let you have much better control over camera movement but where Hailuo truly excels is that it understands speed and camera shake which are essential for any fast paced action sequences. The music was generated with Suno 4.5+ and some additional sound effects like the bike and wind in the desert were sourced from Artlist. Edited with Capcut. There's some more tips and tricks in the thread 👍👍

Travis Davids

60,599 views • 10 months ago

🇨🇳 Many people don't know this but Chinese high speed trains are now the fastest in the word and officially faster than even the 🇯🇵 Japanese Shinkansen Chinese trains go 350-400km/h (217-250mph) depending on the model While the Japanese Shinkansen goes 320km/h (200mph) max So I went to try it from Chengdu to Chongqing (just $80 for biz class) This one is the slightly older 350km/h model The business class cabin has 5 big seats that can lay flat with a stewardess dedicated to the cabin who serves you drinks like coffee, water, orange juice etc. I guess if it's a longer trip you probably get food served too The journey was very smooth and very fast, it maintained close to 350km/h at all times and there wasn't many stops or breaks (good) It didn't have WiFi, which is kind of a miss but it seems Chinese just use 5G for everything which worked fine for me without interrruption too I'd say the interior could be a bit more beautiful and modern. I usually say things in Japan look ancient but I think the Shinkansen interior there looks a bit more modern than here The trip took 1 hour and it passed about 300km in that time, roughly equivalent to the width of my country the Netherlands 😂 Anyway solid experience (and cheap!) 👍

🇨🇳 Many people don't know this but Chinese high speed trains are now the fastest in the word and officially faster than even the 🇯🇵 Japanese Shinkansen Chinese trains go 350-400km/h (217-250mph) depending on the model While the Japanese Shinkansen goes 320km/h (200mph) max So I went to try it from Chengdu to Chongqing (just $80 for biz class) This one is the slightly older 350km/h model The business class cabin has 5 big seats that can lay flat with a stewardess dedicated to the cabin who serves you drinks like coffee, water, orange juice etc. I guess if it's a longer trip you probably get food served too The journey was very smooth and very fast, it maintained close to 350km/h at all times and there wasn't many stops or breaks (good) It didn't have WiFi, which is kind of a miss but it seems Chinese just use 5G for everything which worked fine for me without interrruption too I'd say the interior could be a bit more beautiful and modern. I usually say things in Japan look ancient but I think the Shinkansen interior there looks a bit more modern than here The trip took 1 hour and it passed about 300km in that time, roughly equivalent to the width of my country the Netherlands 😂 Anyway solid experience (and cheap!) 👍

@levelsio

2,012,663 views • 7 months ago

🔥HOLY SMOKES! $TAO holders! 🚀 SUBNET 19 (VISION) ON BITTENSOR IS ABSOLUTELY CRUSHING IT! In my 5+ years covering crypto and AI, this is one of the most impressive implementations I've seen. The combination of scale, performance, and decentralization is absolutely next level! 🚀 @namoray_dev @Corcel_X 💨 INSANE Speed Performance: - Llama 3.1 8B: 196.18 tokens/s with +107.23% advantage - Llama 3.1 70B: 124.96 tokens/s with +154.96% advantage - Llama 3.2 3B: 166.69 tokens/s with +21.66% advantage 🔥 Top Tier Model Integration: - Meta-Llama-3-70B & 8B Instruct - FLUX.1-schnell for Text-to-Image - ProteusV0.4-Lightning (Text & Image) - Multiple model variations for redundancy 🔥 What Makes This INSANE: - Complete decentralization - No single point of failure - Multiple model choices for redundancy - Real-time performance tracking - Transparent incentive structure The incentive distribution curve shows a healthy network with: - Strong rewards for top performers - Fair distribution across all participants - Clear path for growth and improvement - Sustainable economic model What's truly MIND-BLOWING is how they've managed to: 1. Scale to millions of operations 2. Maintain high quality across multiple tasks 3. Create a fair, competitive marketplace 4. Build in redundancy and reliability 5. Achieve true decentralization This isn't just another subnet - this is the future of decentralized AI inference happening RIGHT NOW! 🔥 1. MASSIVE Scale & Adoption: - We're seeing 7M+ tokens being processed - 14K+ processing steps being executed - Multiple AI models running simultaneously - Incredible miner participation across the network 2. Revolutionary Task Distribution: - Llama 3.1 70B leading with 20% weighting - Avatar Generation at 15% - Perfectly balanced task distribution for optimal network performance - Multiple specialized tasks including Text-to-Image and Image-to-Image processing 3. Elite Performance Metrics: - Top miners hitting 0.00775 incentive rates - Consistent performance across the network - Impressive scaling from top to bottom performers - Strong incentive curve maintaining network quality 📈 Network Performance: - Consistent upward trend in tokens/s - Quality scores maintaining high levels (>0.9) - Steady improvement in miner performance - Rock-solid network reliability ⚡ Platform Highlights: - Permissionless, serverless architecture - Global network of Always-On GPUs - Instant API access - Full decentralization - Multi-model support with seamless switching What makes this TRULY SPECIAL is the consistent upward trajectory in both speed and quality, while maintaining a decentralized architecture. The performance advantages over industry standards (+154.96% for 70B!) are absolutely mind-blowing! 🚀 This isn't just another AI subnet - it's a glimpse into the future of decentralized AI inference! The combination of speed, reliability, and model variety makes this one of the most impressive implementations in the space! 🔥 📽 Watch Now on YouTube and TikTok: Source 🔗

Andy ττ

11,616 views • 1 year ago

The Agentic Literature Review is Now a Reality. 🚀 I watched a student from King’s College London dismantle a task that used to take weeks. His mission? Deconstruct 47 complex academic papers for his dissertation. The old way: ❌ Endless skimming & highlighting ❌ Messy, unsearchable notes ❌ Citation chaos across 5 different tools The new way? He used a single platform and finished the core analysis in an afternoon. This isn't just another "AI summarizer." ResearchCollab is an AI co-pilot for research. I tested it against the standard "academic grind." The difference was staggering: 🔴 Traditional Workflow: Scattered PDFs, chaotic notes, mental burnout. 🟢 ResearchCollab Workflow: • AI instantly surfaces key insights from 250M+ papers without manual prompting. • Auto-organizes and relates everything personalized to the user. • Generates perfect citations (APA, MLA) in one click. • Brainstorms new research directions you might have missed. 👇 See how it works (No Credit Card Needed): Start your free trial → Why this is a silent revolution for knowledge workers: 1️⃣ Students are cutting literature review time by up to 80%. 2️⃣ Research teams are collaborating in real-time, killing version control nightmares. 3️⃣ The "blank page syndrome" is solved. AI helps you generate outlines and spark unique ideas instantly. The most compelling part? It’s not just about speed. It’s about clarity. ✔️ Finds connections between papers you'd never see. ✔️ Keeps your entire research universe in one searchable place. ✔️ Works 24/7 for less than the cost of your monthly coffee budget. This is the "Copilot" moment for academia and R&D. The barrier to high-quality, organized research has just collapsed. 👉 Support ResearchCollab Product Hunt launch : PS: I've compiled a short guide on "The 5-Day Research Sprint" methodology that this enables. Like 👍 and Comment "Research" and I'll DM you the link.

The Agentic Literature Review is Now a Reality. 🚀 I watched a student from King’s College London dismantle a task that used to take weeks. His mission? Deconstruct 47 complex academic papers for his dissertation. The old way: ❌ Endless skimming & highlighting ❌ Messy, unsearchable notes ❌ Citation chaos across 5 different tools The new way? He used a single platform and finished the core analysis in an afternoon. This isn't just another "AI summarizer." ResearchCollab is an AI co-pilot for research. I tested it against the standard "academic grind." The difference was staggering: 🔴 Traditional Workflow: Scattered PDFs, chaotic notes, mental burnout. 🟢 ResearchCollab Workflow: • AI instantly surfaces key insights from 250M+ papers without manual prompting. • Auto-organizes and relates everything personalized to the user. • Generates perfect citations (APA, MLA) in one click. • Brainstorms new research directions you might have missed. 👇 See how it works (No Credit Card Needed): Start your free trial → Why this is a silent revolution for knowledge workers: 1️⃣ Students are cutting literature review time by up to 80%. 2️⃣ Research teams are collaborating in real-time, killing version control nightmares. 3️⃣ The "blank page syndrome" is solved. AI helps you generate outlines and spark unique ideas instantly. The most compelling part? It’s not just about speed. It’s about clarity. ✔️ Finds connections between papers you'd never see. ✔️ Keeps your entire research universe in one searchable place. ✔️ Works 24/7 for less than the cost of your monthly coffee budget. This is the "Copilot" moment for academia and R&D. The barrier to high-quality, organized research has just collapsed. 👉 Support ResearchCollab Product Hunt launch : PS: I've compiled a short guide on "The 5-Day Research Sprint" methodology that this enables. Like 👍 and Comment "Research" and I'll DM you the link.

Anuj

10,780 views • 8 months ago

🌋🌊 Massive 7.4 Quake Triggers Tsunami Alert | Mindanao, Philippines | Oct 10 2025 (UTC) A magnitude 7.4 earthquake struck off Santiago, Davao Oriental, near Davao City, shaking much of Mindanao and prompting a Pacific Tsunami Warning Center alert for areas within 300 km of the epicenter. ⸻ What’s New • 🕑 18:43 PHT (10:43 UTC) — quake depth ≈ 36 mi (57 km). • 📍 Epicenter: 07°15′N 126°45′E, ~100 km east of Davao City. • 🌊 PTWC: “Hazardous tsunami waves possible for coasts within 300 km.” Why It Matters • 📊 Major quake near the Philippine Trench—a volatile subduction zone. • 🏛️ PHIVOLCS and local LGUs initiating evacuations along the eastern Mindanao coast. • 🌎 Regional tsunami bulletins issued across the Philippine Sea basin. Effects (Developing) • 👥 Strong shaking felt from Davao to Cagayan de Oro; aftershocks reported. • 🏗️ Power outages and structural checks under way in Tagum and Mati. • 💰 Ports and fishers ordered to move vessels to deeper waters immediately. Gunny’s Take This is a serious event along one of Asia’s most dangerous tectonic zones. Shallow, ocean-trench quakes of this size can generate localized tsunami surges within minutes. If you’re on the eastern Mindanao coast — get to high ground now. Aftershocks and secondary tsunami waves remain possible. What to Watch • ⏰ First-wave arrival: 15–45 minutes after main shock. • 🚚 Evac updates from Davao, Mati, and Tagum coastal barangays. • 🛰️ PTWC + PHIVOLCS bulletins for wave height and aftershock tracking. ⸻ BOTTOM LINE: A powerful 7.4 quake has hit Mindanao — move to higher ground and stay off the coast until official all-clear. Lives depend on speed. 🌊 👇 Like • 💬 Comment • 🔁 Share • 👀 Follow Sources: PTWC | PHIVOLCS | USGS | OSINT Defender | Local Gov Feeds — Gunny 🫡 “Fix the facts. Keep the mission.” #Philippines #Mindanao #Earthquake #TsunamiAlert #Davao #Mati #Tagum #PTWC #PHIVOLCS #BreakingNews #GunnyOSINT

🌋🌊 Massive 7.4 Quake Triggers Tsunami Alert | Mindanao, Philippines | Oct 10 2025 (UTC) A magnitude 7.4 earthquake struck off Santiago, Davao Oriental, near Davao City, shaking much of Mindanao and prompting a Pacific Tsunami Warning Center alert for areas within 300 km of the epicenter. ⸻ What’s New • 🕑 18:43 PHT (10:43 UTC) — quake depth ≈ 36 mi (57 km). • 📍 Epicenter: 07°15′N 126°45′E, ~100 km east of Davao City. • 🌊 PTWC: “Hazardous tsunami waves possible for coasts within 300 km.” Why It Matters • 📊 Major quake near the Philippine Trench—a volatile subduction zone. • 🏛️ PHIVOLCS and local LGUs initiating evacuations along the eastern Mindanao coast. • 🌎 Regional tsunami bulletins issued across the Philippine Sea basin. Effects (Developing) • 👥 Strong shaking felt from Davao to Cagayan de Oro; aftershocks reported. • 🏗️ Power outages and structural checks under way in Tagum and Mati. • 💰 Ports and fishers ordered to move vessels to deeper waters immediately. Gunny’s Take This is a serious event along one of Asia’s most dangerous tectonic zones. Shallow, ocean-trench quakes of this size can generate localized tsunami surges within minutes. If you’re on the eastern Mindanao coast — get to high ground now. Aftershocks and secondary tsunami waves remain possible. What to Watch • ⏰ First-wave arrival: 15–45 minutes after main shock. • 🚚 Evac updates from Davao, Mati, and Tagum coastal barangays. • 🛰️ PTWC + PHIVOLCS bulletins for wave height and aftershock tracking. ⸻ BOTTOM LINE: A powerful 7.4 quake has hit Mindanao — move to higher ground and stay off the coast until official all-clear. Lives depend on speed. 🌊 👇 Like • 💬 Comment • 🔁 Share • 👀 Follow Sources: PTWC | PHIVOLCS | USGS | OSINT Defender | Local Gov Feeds — Gunny 🫡 “Fix the facts. Keep the mission.” #Philippines #Mindanao #Earthquake #TsunamiAlert #Davao #Mati #Tagum #PTWC #PHIVOLCS #BreakingNews #GunnyOSINT

Gunnys Adventures

132,725 views • 9 months ago

DeMeco Ryans built an entirely new culture in Houston with one word: SWARM. But it's not just a word - it's an acronym. A simple, memorable, and a powerful way to emphasize what they're looking for. "Swarm mentality is just an acronym for I want to build my team with guys who have a special work ethic and a relentless mindset. And that's where the Swarm mentality came in." S.W.A.R.M. = Special Work Ethic And a Relentless Mindset "That's what the Texan culture will be about - swarming. It's attacking everything." But SWARM isn't just about defense. It's all-encompassing. "It involves teamwork. It involves togetherness. How you attack issues and problems - it's swarming this thing all together. How are you gonna attack a defense or offense? It's those 11 guys out there swarming together on the field." This is what culture looks like when it's built with intention: 1: Get the Right People - Culture starts with who you let in the building. Talent without character is a liability. Ryans' filter is simple: "If it's a guy and I got mixed reports on him...next." 2: Keep It Simple, Play Fast - Complexity doesn't win games. Mastery of the basics does. Your players can't play fast if they're thinking. Simplicity creates speed. 3: Coach The Details, Not The Outcome - Good players can have bad habits. Great coaches see past the result. "In big games...it's not the wow plays. It's who can be consistent, who can not screw it up the most." 4: Be Demanding Without Disrespecting - High standards don't require low respect. You can push hard without tearing down. "You can be demanding without being disrespectful." 5: Let Leaders Be Themselves - Leadership isn't one style. Quiet leaders lead by example. Loud leaders lead by voice. Both work. Ryans tells every player: "I want you to be yourself." Culture isn't a sign on the wall - it's what you emphasize, tolerate, and allow. Special Work Ethic. Relentless Mindset. That's SWARM and the Texans standard. (🎥Pat McAfee)

DeMeco Ryans built an entirely new culture in Houston with one word: SWARM. But it's not just a word - it's an acronym. A simple, memorable, and a powerful way to emphasize what they're looking for. "Swarm mentality is just an acronym for I want to build my team with guys who have a special work ethic and a relentless mindset. And that's where the Swarm mentality came in." S.W.A.R.M. = Special Work Ethic And a Relentless Mindset "That's what the Texan culture will be about - swarming. It's attacking everything." But SWARM isn't just about defense. It's all-encompassing. "It involves teamwork. It involves togetherness. How you attack issues and problems - it's swarming this thing all together. How are you gonna attack a defense or offense? It's those 11 guys out there swarming together on the field." This is what culture looks like when it's built with intention: 1: Get the Right People - Culture starts with who you let in the building. Talent without character is a liability. Ryans' filter is simple: "If it's a guy and I got mixed reports on him...next." 2: Keep It Simple, Play Fast - Complexity doesn't win games. Mastery of the basics does. Your players can't play fast if they're thinking. Simplicity creates speed. 3: Coach The Details, Not The Outcome - Good players can have bad habits. Great coaches see past the result. "In big games...it's not the wow plays. It's who can be consistent, who can not screw it up the most." 4: Be Demanding Without Disrespecting - High standards don't require low respect. You can push hard without tearing down. "You can be demanding without being disrespectful." 5: Let Leaders Be Themselves - Leadership isn't one style. Quiet leaders lead by example. Loud leaders lead by voice. Both work. Ryans tells every player: "I want you to be yourself." Culture isn't a sign on the wall - it's what you emphasize, tolerate, and allow. Special Work Ethic. Relentless Mindset. That's SWARM and the Texans standard. (🎥Pat McAfee)

Coach AJ 🎯 Mental Fitness

69,011 views • 6 months ago

My son and I went to the gym late last night to work out some stuff after 3 HS games worth of not hitting the way that he wanted. The session had both a data component and a feel / cue component. As a 17 year old who now has high 60's / low to mid 70's bat speed he has struggled in the last week - specifically against low velocity pitching - to let the ball travel deep enough to get good flush contact. Point being that we had a specific thing to work on. So on the technology side we're using Blast to bat speed, attack angle and VBA, and we're using HitTrax to monitor contact depth in addition to the outcome stuff - exit velocity, launch angle, distance and direction. We also were using two different pitching machines - one offset to the left side, the other offset to the right side. In terms of cues what we ended up with was: - As deep as possible while still being on time - High pitch posture, flat bat path and adjust off if needed But along the way we tried all sorts of stuff - everything from trying to hit a ball to the hot dog cart in oppo foul territory off the left hand off-set machine to trying to find middle of the field ball flight from the right hand offset machine to just going pure let it eat anywhere ball flight off of either machine to score a runner on 2B. In my mind, the best instruction environment for hitting is just a conversation that revolves around: - What were we trying to do vs what did we actually do - What signal can we get about why we did what we did - What adjustments do we need to make to bring our results closer to the intended outcome on the next swing But if the instructor and the player don't even speak the same language...man that conversation is going to be pretty limited in its effectiveness. Because he's 17 we're now able to have these kinds of conversations - with all of these various layers. But the critically important part of the whole thing is that this is an actual two way conversation. Meaning that he's telling me how he feels, we're looking at the data to correlate the feeling to the outcome, we decide on how or if we need to adjust intention for the next swing and we just wash, rinse and repeat that same cycle over and over and over. I wouldn't - and I didn't - coach him this way when he was 12. We used the same tech stack, but the data we paid attention to was a lot more limited. Because that was the level of depth he was able to have a productive conversation about at that time. I'm also exceptionally fortunate that at 17 years old he's still playing and I still get to have these conversations with him.

My son and I went to the gym late last night to work out some stuff after 3 HS games worth of not hitting the way that he wanted. The session had both a data component and a feel / cue component. As a 17 year old who now has high 60's / low to mid 70's bat speed he has struggled in the last week - specifically against low velocity pitching - to let the ball travel deep enough to get good flush contact. Point being that we had a specific thing to work on. So on the technology side we're using Blast to bat speed, attack angle and VBA, and we're using HitTrax to monitor contact depth in addition to the outcome stuff - exit velocity, launch angle, distance and direction. We also were using two different pitching machines - one offset to the left side, the other offset to the right side. In terms of cues what we ended up with was: - As deep as possible while still being on time - High pitch posture, flat bat path and adjust off if needed But along the way we tried all sorts of stuff - everything from trying to hit a ball to the hot dog cart in oppo foul territory off the left hand off-set machine to trying to find middle of the field ball flight from the right hand offset machine to just going pure let it eat anywhere ball flight off of either machine to score a runner on 2B. In my mind, the best instruction environment for hitting is just a conversation that revolves around: - What were we trying to do vs what did we actually do - What signal can we get about why we did what we did - What adjustments do we need to make to bring our results closer to the intended outcome on the next swing But if the instructor and the player don't even speak the same language...man that conversation is going to be pretty limited in its effectiveness. Because he's 17 we're now able to have these kinds of conversations - with all of these various layers. But the critically important part of the whole thing is that this is an actual two way conversation. Meaning that he's telling me how he feels, we're looking at the data to correlate the feeling to the outcome, we decide on how or if we need to adjust intention for the next swing and we just wash, rinse and repeat that same cycle over and over and over. I wouldn't - and I didn't - coach him this way when he was 12. We used the same tech stack, but the data we paid attention to was a lot more limited. Because that was the level of depth he was able to have a productive conversation about at that time. I'm also exceptionally fortunate that at 17 years old he's still playing and I still get to have these conversations with him.

Deven Morgan

72,327 views • 3 months ago

✨New demo: what if vibe coding felt more visual? Brian Lovin Mary Rose Cook and I did a game jam using Notion as our "IDE": launching Cursor agents from a task board, and making a custom image for each task 😎 The demo shows 3 ideas for the future of agents: 1) Agents should collaborate across apps. Each app has its focus--Notion AI is good at drafting specs and organizing tasks; Cursor is good at coding. So let them specialize! Today we're launching a new integration where Notion AI can kick off Cursor Cloud Agents to do coding tasks. The Cursor API accepts natural language prompts, so I think of this as "cross-app sub-agents" -- it's kinda cute how it resembles humans hiring outside contractors 😊 BTW: the parallelism of cloud agents is incredibly freeing for creativity, but it also creates a new problem: sooo much work to keep track of! Which brings us to the next idea... 2) Agent orchestration is a data visualization problem. A powerful frame for designing agent UIs is to think of the chat transcripts as the "raw data" and ask: what visual projections might help people make sense of this data at scale? We need to engage our human GPUs -- our visual processing -- to understand what the computer GPUs are doing for us! One thing we can do is use AI to populate traditional UIs like progress bars and status updates. But there are also new possibilities now... For example: when you have a lot going on, it can be hard to identify tasks just by text titles. So we tried generating an AI image for each task -- turns out this helps a lot by giving it a unique visual identity! And of course, it also just makes it super fun to build with friends 😃 Speaking of friends... 3) The future of coding is collaborative. Sometimes it feels like IC engineers are being reduced to middle managers: shuffling information between the team's context and the coding agents that they individually manage. The solution: bring all the people and agents into one shared space, with shared context and visibility! In the video you can get a glimpse of how this feels. Mary, Brian and I record ourselves chatting about ideas, and then we use AI to turn that conversation into a list of tasks on a shared board. As the ideas get built in parallel, we can all monitor progress and review the work together, nothing is siloed. My main takeaway from this game jam was: damn, creativity with friends, at the speed of conversation, is incredibly fun. --- Our goal here is to let anyone use Notion as a fun and creative "software factory" to build software together with your team. Give the Cursor integration a shot and let us know what you think! (AI Image gen in Notion isn't GA yet, but coming soon and already out to some users) And let me know if you'd want a template or more detailed instructions on the setup we showed in this demo...

✨New demo: what if vibe coding felt more visual? Brian Lovin Mary Rose Cook and I did a game jam using Notion as our "IDE": launching Cursor agents from a task board, and making a custom image for each task 😎 The demo shows 3 ideas for the future of agents: 1) Agents should collaborate across apps. Each app has its focus--Notion AI is good at drafting specs and organizing tasks; Cursor is good at coding. So let them specialize! Today we're launching a new integration where Notion AI can kick off Cursor Cloud Agents to do coding tasks. The Cursor API accepts natural language prompts, so I think of this as "cross-app sub-agents" -- it's kinda cute how it resembles humans hiring outside contractors 😊 BTW: the parallelism of cloud agents is incredibly freeing for creativity, but it also creates a new problem: sooo much work to keep track of! Which brings us to the next idea... 2) Agent orchestration is a data visualization problem. A powerful frame for designing agent UIs is to think of the chat transcripts as the "raw data" and ask: what visual projections might help people make sense of this data at scale? We need to engage our human GPUs -- our visual processing -- to understand what the computer GPUs are doing for us! One thing we can do is use AI to populate traditional UIs like progress bars and status updates. But there are also new possibilities now... For example: when you have a lot going on, it can be hard to identify tasks just by text titles. So we tried generating an AI image for each task -- turns out this helps a lot by giving it a unique visual identity! And of course, it also just makes it super fun to build with friends 😃 Speaking of friends... 3) The future of coding is collaborative. Sometimes it feels like IC engineers are being reduced to middle managers: shuffling information between the team's context and the coding agents that they individually manage. The solution: bring all the people and agents into one shared space, with shared context and visibility! In the video you can get a glimpse of how this feels. Mary, Brian and I record ourselves chatting about ideas, and then we use AI to turn that conversation into a list of tasks on a shared board. As the ideas get built in parallel, we can all monitor progress and review the work together, nothing is siloed. My main takeaway from this game jam was: damn, creativity with friends, at the speed of conversation, is incredibly fun. --- Our goal here is to let anyone use Notion as a fun and creative "software factory" to build software together with your team. Give the Cursor integration a shot and let us know what you think! (AI Image gen in Notion isn't GA yet, but coming soon and already out to some users) And let me know if you'd want a template or more detailed instructions on the setup we showed in this demo...

Geoffrey Litt

88,919 views • 4 months ago

New episode: "The Stubborn Genius of James Dyson" A few notes from the episode: 1. Copying is for losers. 2. They only come to you because you're eccentric. They can get conformity anywhere. 3. Be different and retain total control. 4. Great work is just the vision of a single person, pursued with dogged determination that is nothing less than obsession. 5. The best founders are obsessive, impractical, product-driven enthusiasts. 6. Hire blank slates: Young people who haven’t been ruined by the bad habits of subpar organizations. 7. Be fired by an inner strength and self-belief that is almost impossible to imagine in this feckless age. 8. Vision is just long-term stubbornness. 9. The root principle is to do things your way. It doesn’t matter how other people do it. 10. As long as it works, and it's exciting, people will follow you. 11. Demand difference from what exists. 12. Extreme success comes from doing something no one else is doing. 13. Learning from history is a form of leverage. Have an interest, verging on obsession, with the past. (Dyson literally wrote an encyclopedia on history's greatest inventions) 14. Do not sell a half-finished product. 15. People do not want all-purpose; they want high-tech specificity. 16. Don’t lose the direct connection to your customer. 17. There is no such thing as a quantum leap. There is only dogged persistence — and in the end you make it look like a quantum leap. 18. You simply cannot mix messages when selling something new. Customers can barely handle one great new idea, let alone two, or even several. 19. You want a single message expressed clearly. 20. Appeal to a specific need. Don’t make your product too wide. Narrow it down. 21. You have to think about the incentives of the people you’re selling to. You can’t sell a bagless vacuum cleaner to people that make $500 million selling vacuum bags. 22. No one is ever eager to fix a cash machine that isn’t broken. 23. The more you’re able to control, the better your product— and then your company— will become. 24. Don’t copy the opposition. Don’t worry about market research. Follow your own star. This is what success entrepreneurs do. 25. The opposite of following your own star is following the herd. That is a path to dull conformity. 26. For innovative, intrinsically excellent products, the markets are often larger than you can predict. 27. The entrenched professional is always going to resist far longer than the private consumer. 28. No one ever got an idea starting at a drawing board. 29. Founder led sales is the most powerful tool. 30. The inventive mind knows that there is always further questions to be asked and new discoveries to be made. 31. A clever person doesn’t spend 14 years building 5,127 prototypes of the world’s first cyclonic vacuum cleaner. A determined person does. 32. If you have an idea for a new product, you engineer, prototype, manufacture, market, and sell it yourself. Retain total control. 33. If it’s not beautiful you’re not done. 34. The founder is personally accountable for every product sold. 35. People buy stories. Invest heavily in storytelling. Why your product exists. How it is made. Who made it. 36. Control is more important than money. 37. When you own the whole company all decisions are your own. 38. How bad do you want it? Dyson made a new prototype, every day, for more than 1,000 days. Alone. 39. Perseverance is not cheap. 40. A project will die if the original mule doesn’t stay on it. The self-belief is not there to press through the hard times. 41. Your company should be the most exciting adventure of your life. 42. If you make it, sell it yourself. 43. Only the person with the closest relationship with the product can make a success of it. 44. There's nothing wrong with being persistently dissatisfied or afraid. 45. You need the confidence — and the stupidity — to do things differently. 46. One decent editorial counts for 1,000 advertisements. 47. Difference for the sake of difference and the continuous improvement of products simply for improvement’s sake. 48. Persistent trial and error allows you to wake up one morning, after many, many mornings, with a world-beating product. 49. Seek out originality for its own sake. 50. Companies are built, not made. 51. You are more likely to solve a problem by being unconventional and determined than by being brilliant. 52. Never sacrifice quality for speed. 53. Magic — the unique way a product does what it does — is never to be underestimated. There are 100 more ideas in the episode. I hope you listen to it. 50 years of Dyson's career + 70 hours of reading (and simplifying) and me just ripping through idea after idea at 2x speed for 90 minutes. It will be hard to find a better use of time.

New episode: "The Stubborn Genius of James Dyson" A few notes from the episode: 1. Copying is for losers. 2. They only come to you because you're eccentric. They can get conformity anywhere. 3. Be different and retain total control. 4. Great work is just the vision of a single person, pursued with dogged determination that is nothing less than obsession. 5. The best founders are obsessive, impractical, product-driven enthusiasts. 6. Hire blank slates: Young people who haven’t been ruined by the bad habits of subpar organizations. 7. Be fired by an inner strength and self-belief that is almost impossible to imagine in this feckless age. 8. Vision is just long-term stubbornness. 9. The root principle is to do things your way. It doesn’t matter how other people do it. 10. As long as it works, and it's exciting, people will follow you. 11. Demand difference from what exists. 12. Extreme success comes from doing something no one else is doing. 13. Learning from history is a form of leverage. Have an interest, verging on obsession, with the past. (Dyson literally wrote an encyclopedia on history's greatest inventions) 14. Do not sell a half-finished product. 15. People do not want all-purpose; they want high-tech specificity. 16. Don’t lose the direct connection to your customer. 17. There is no such thing as a quantum leap. There is only dogged persistence — and in the end you make it look like a quantum leap. 18. You simply cannot mix messages when selling something new. Customers can barely handle one great new idea, let alone two, or even several. 19. You want a single message expressed clearly. 20. Appeal to a specific need. Don’t make your product too wide. Narrow it down. 21. You have to think about the incentives of the people you’re selling to. You can’t sell a bagless vacuum cleaner to people that make $500 million selling vacuum bags. 22. No one is ever eager to fix a cash machine that isn’t broken. 23. The more you’re able to control, the better your product— and then your company— will become. 24. Don’t copy the opposition. Don’t worry about market research. Follow your own star. This is what success entrepreneurs do. 25. The opposite of following your own star is following the herd. That is a path to dull conformity. 26. For innovative, intrinsically excellent products, the markets are often larger than you can predict. 27. The entrenched professional is always going to resist far longer than the private consumer. 28. No one ever got an idea starting at a drawing board. 29. Founder led sales is the most powerful tool. 30. The inventive mind knows that there is always further questions to be asked and new discoveries to be made. 31. A clever person doesn’t spend 14 years building 5,127 prototypes of the world’s first cyclonic vacuum cleaner. A determined person does. 32. If you have an idea for a new product, you engineer, prototype, manufacture, market, and sell it yourself. Retain total control. 33. If it’s not beautiful you’re not done. 34. The founder is personally accountable for every product sold. 35. People buy stories. Invest heavily in storytelling. Why your product exists. How it is made. Who made it. 36. Control is more important than money. 37. When you own the whole company all decisions are your own. 38. How bad do you want it? Dyson made a new prototype, every day, for more than 1,000 days. Alone. 39. Perseverance is not cheap. 40. A project will die if the original mule doesn’t stay on it. The self-belief is not there to press through the hard times. 41. Your company should be the most exciting adventure of your life. 42. If you make it, sell it yourself. 43. Only the person with the closest relationship with the product can make a success of it. 44. There's nothing wrong with being persistently dissatisfied or afraid. 45. You need the confidence — and the stupidity — to do things differently. 46. One decent editorial counts for 1,000 advertisements. 47. Difference for the sake of difference and the continuous improvement of products simply for improvement’s sake. 48. Persistent trial and error allows you to wake up one morning, after many, many mornings, with a world-beating product. 49. Seek out originality for its own sake. 50. Companies are built, not made. 51. You are more likely to solve a problem by being unconventional and determined than by being brilliant. 52. Never sacrifice quality for speed. 53. Magic — the unique way a product does what it does — is never to be underestimated. There are 100 more ideas in the episode. I hope you listen to it. 50 years of Dyson's career + 70 hours of reading (and simplifying) and me just ripping through idea after idea at 2x speed for 90 minutes. It will be hard to find a better use of time.

David Senra

177,522 views • 10 months ago

The state of LOW-FI and platform support (Death of PCVR): When the Kickstarter ran back in , the main focus was "Next-Gen VR", meaning at the time PCVR, with high hopes for PSVR2 (which hadn't been officially announced). During the next year or so, we (myself, Noah Rayburn and Mark Schramm #VR #AR #MR) focused purely on supporting PC VR hardware. Rift/S, Vive, Index (including controllers), all WMR devices, etc... Mark even added HOTAS and Leap Motion support. BUT, as I'm sure you know, PCVR has been in decline since around the launch of Half-Life: Alyx, which Anton Hand so eloquently called the punctuation mark on the gravestone of PCVR. The Rift store is a ghost town.. like officially.. even according to Meta, Viveport (lets not even go there), what else we got? WMR Store? Was that even a thing? Anyway... Lucky for us, PSVR2 was just over the horizon and we had the dev kits! How well is PSV2 doing though? Guess is (based on speaking with other top VR devs), not that great... Somewhere in there, the great and powerful Noah Rayburn was able to implement a pretty slick "non-VR mode" upon my request to be able to test the game without having to keep taking the HMD off and on while balancing controllers on my knees and working with janky Quest link stuff. Good news! Non-VR mode is great! No just for testing, but for playing. We decided to go full in on it's development and offer it to the consumers. Bonus, it also runs on Steam Deck! (See video below). Now as we gear up to finish the game and run out of money (hopefully in that order), I'm thinking a lot about the market for the game and our placement in it. We have a decent amount of wishlists (66k on Steam and 24k on PS5) so far. Hope is that launching as a PSVR2 title will capture a good chunk of those users, pushing it up on the general PSN store ranking (notoriously hard for indies to do otherwise), and we'll make some sales to traditional flat PS5 gamers as well. Snowballing a bit if we're lucky. Steam launch could do decently well if timed properly, with hopes of the same "VR first" snowballing effect. Why am I telling you all of this? I just thought it would be good to get it in writing and have a place to point. We are starting to run low on money (PCVR presales have basically dried up), so it's also to let you know that the fire is lit under my ass to ship this thing. That said, it won't ship until its good and done. A delayed game is eventually good, but a rushed game is forever bad. Oh, and before you say "Why not port it to Quest", put down the pipe. I understand that you're not a developer, but take my word for it, that's not happening. Not with this budget(or lack thereof), this sized team , or this generation of devices. Ok. that's it. My longest twitter post. PC/PCVR Preorder and early access: Steam Wishlist PSN Wishlist ❤️🧡💙🖤

The state of LOW-FI and platform support (Death of PCVR): When the Kickstarter ran back in , the main focus was "Next-Gen VR", meaning at the time PCVR, with high hopes for PSVR2 (which hadn't been officially announced). During the next year or so, we (myself, Noah Rayburn and Mark Schramm #VR #AR #MR) focused purely on supporting PC VR hardware. Rift/S, Vive, Index (including controllers), all WMR devices, etc... Mark even added HOTAS and Leap Motion support. BUT, as I'm sure you know, PCVR has been in decline since around the launch of Half-Life: Alyx, which Anton Hand so eloquently called the punctuation mark on the gravestone of PCVR. The Rift store is a ghost town.. like officially.. even according to Meta, Viveport (lets not even go there), what else we got? WMR Store? Was that even a thing? Anyway... Lucky for us, PSVR2 was just over the horizon and we had the dev kits! How well is PSV2 doing though? Guess is (based on speaking with other top VR devs), not that great... Somewhere in there, the great and powerful Noah Rayburn was able to implement a pretty slick "non-VR mode" upon my request to be able to test the game without having to keep taking the HMD off and on while balancing controllers on my knees and working with janky Quest link stuff. Good news! Non-VR mode is great! No just for testing, but for playing. We decided to go full in on it's development and offer it to the consumers. Bonus, it also runs on Steam Deck! (See video below). Now as we gear up to finish the game and run out of money (hopefully in that order), I'm thinking a lot about the market for the game and our placement in it. We have a decent amount of wishlists (66k on Steam and 24k on PS5) so far. Hope is that launching as a PSVR2 title will capture a good chunk of those users, pushing it up on the general PSN store ranking (notoriously hard for indies to do otherwise), and we'll make some sales to traditional flat PS5 gamers as well. Snowballing a bit if we're lucky. Steam launch could do decently well if timed properly, with hopes of the same "VR first" snowballing effect. Why am I telling you all of this? I just thought it would be good to get it in writing and have a place to point. We are starting to run low on money (PCVR presales have basically dried up), so it's also to let you know that the fire is lit under my ass to ship this thing. That said, it won't ship until its good and done. A delayed game is eventually good, but a rushed game is forever bad. Oh, and before you say "Why not port it to Quest", put down the pipe. I understand that you're not a developer, but take my word for it, that's not happening. Not with this budget(or lack thereof), this sized team , or this generation of devices. Ok. that's it. My longest twitter post. PC/PCVR Preorder and early access: Steam Wishlist PSN Wishlist ❤️🧡💙🖤

Blair Renaud // LOW-FI 🟥🟧⬛

69,789 views • 2 years ago

A world first: a demonstration of AI running *on* blockchain as a smart contract 🧠⚡️ The Internet Computer is used – the world's first 3rd gen. blockchain #ICP. AI will become the beating heart of our web3, multi-chain world, and this is only my first demo. Code will follow shortly. This is running on DFINITY's Internet Computer testnet, but you'll be able to take the code and run it on the public network as the NNS is expected to up the per-transaction instruction limit in the coming days. Some important notes. The inference engine used has not been optimized, and we will show vastly greater efficiency in subsequent demos, where the AI runs even faster, and consumes less gas/cycles. We will also propose to the NNS that smart contracts have access to SIMD instructions – which we have determined are deterministic – unlocking vastly more speed and efficiency. Lastly, currently the actor smart contracts ICP hosts run inside a 32 bit environment, which limits their main memory to 4GB. Within the next couple of months, we expect the Internet Computer to move to a 64 bit environment, allowing smart contract memory limits to be raised much higher – allowing for models with far more parameters, and thus power, to be run. Those of you who have followed my posts know that hardware optimization support is planned. Firstly this will involve WASM smart contracts shipping out matrices for processing by the CPUs on existing node machines (another advantage of the Internet Computer running on sovereign node hardware). Secondly, we plan to propose a new public node machine specification, which node providers can build to, for use in subnets specialized for hosting AI smart contracts, in which each machine will incorporate several GPUs. Naturally, this will be packaged with other technological developments that ensure smart contract determinism. This is part of our mission to enable powerful LLMs to run as smart contracts on the Internet Computer – in a forms that are tamperproof, unstoppable, and optionally autonomous (including under the exclusive control of DAOs). Our vision: you will be able to have a chat with a smart contract. A smart contract will be able to coordinate your organization (see my earlier tweet about a "Delphi"). ICP smart contracts will be able to audit Ethereum smart contracts, kitemarking those without backdoors and reentrancy bugs. And smart contracts will be able to do KYC autonmously, matching faces to driving licenses, and more. We will deliver new SDK enhancements, and work with partners, to turbocharge crypto AI developers. Secure and unstoppable AI and third generation blockchain will be two sides of the same coin. Security and AI will be indivisible. AI models will be traded as NFTs. Thanks to Internet Computer's chain key (trustless multi-chain) capabilities, all blockchains will be able to leverage AI smart contracts. The future is beyond exciting. Thanks for watching. Can't wait to give you more demos!

A world first: a demonstration of AI running on blockchain as a smart contract 🧠⚡️ The Internet Computer is used – the world's first 3rd gen. blockchain #ICP. AI will become the beating heart of our web3, multi-chain world, and this is only my first demo. Code will follow shortly. This is running on DFINITY's Internet Computer testnet, but you'll be able to take the code and run it on the public network as the NNS is expected to up the per-transaction instruction limit in the coming days. Some important notes. The inference engine used has not been optimized, and we will show vastly greater efficiency in subsequent demos, where the AI runs even faster, and consumes less gas/cycles. We will also propose to the NNS that smart contracts have access to SIMD instructions – which we have determined are deterministic – unlocking vastly more speed and efficiency. Lastly, currently the actor smart contracts ICP hosts run inside a 32 bit environment, which limits their main memory to 4GB. Within the next couple of months, we expect the Internet Computer to move to a 64 bit environment, allowing smart contract memory limits to be raised much higher – allowing for models with far more parameters, and thus power, to be run. Those of you who have followed my posts know that hardware optimization support is planned. Firstly this will involve WASM smart contracts shipping out matrices for processing by the CPUs on existing node machines (another advantage of the Internet Computer running on sovereign node hardware). Secondly, we plan to propose a new public node machine specification, which node providers can build to, for use in subnets specialized for hosting AI smart contracts, in which each machine will incorporate several GPUs. Naturally, this will be packaged with other technological developments that ensure smart contract determinism. This is part of our mission to enable powerful LLMs to run as smart contracts on the Internet Computer – in a forms that are tamperproof, unstoppable, and optionally autonomous (including under the exclusive control of DAOs). Our vision: you will be able to have a chat with a smart contract. A smart contract will be able to coordinate your organization (see my earlier tweet about a "Delphi"). ICP smart contracts will be able to audit Ethereum smart contracts, kitemarking those without backdoors and reentrancy bugs. And smart contracts will be able to do KYC autonmously, matching faces to driving licenses, and more. We will deliver new SDK enhancements, and work with partners, to turbocharge crypto AI developers. Secure and unstoppable AI and third generation blockchain will be two sides of the same coin. Security and AI will be indivisible. AI models will be traded as NFTs. Thanks to Internet Computer's chain key (trustless multi-chain) capabilities, all blockchains will be able to leverage AI smart contracts. The future is beyond exciting. Thanks for watching. Can't wait to give you more demos!

dom | icp

1,362,003 views • 2 years ago

YESTERDAY WAS THAT DAY 😊😊😊 A DAY WITH THE Bolajiogunmolatv 🫶🏽 Have your fav decided to fly all the way just to surprise you? NOOO! So shift back 🤣🤭 I was shocked. It’s very hard to surprise me cos I will always pick up a clue or my instinct will kick in but this time I was legit shocked.. And the fact that she didn’t post in real time for 12 hours so I won’t suspect sealed everything. I was shaking for more than 5 mins. Like how? What! My head wan blow 🤯🤯🤯 When she said “I just came to see you. I came to Abuja for you”… I thought she was whining me but this woman came to my place straight from the airport, spent the day with me and my sisters and left first thing this morning. She didn’t even tell her Abuja friends she was coming just so we can enjoy the day together 🥹🥹. Don’t tell me not to feel special, it’s too late. I AM ALREADY FEELING EXTREMELY SPECIAL 🥰 MY HEAD WAN BURST 🥹🤣 -She came with her brother and was intentional about coming to help me Make content for my brand. His work rate >>>>.. In her words “you gave me your time and that is very important to me”… if you know me, you will know the easiest way to finish me is by supporting my brand 😭🙏🏽🫶🏽 -I have been asking her to send in her measurements for months. Well she came for physical measurements. 💅🏽 -She is such a vibe and holds the best conversation. We were gisting for hours like we knew each other for years.😊 -I got sneak peak of our next YouTube movie and y’all better be ready. Another banger dropping soon 🎉🎉 -Oh! And did I tell you how KIND she is. KIND, GRACEFUL,THOUGHTFUL,HER PRESENCE IS SO SOOTHING AND HER MIND IS BRILLIANT.. She came bearing gifts too. I didn’t even open it cos I was too excited to see her. Will go and open it later today… -SHE IS SOOO PRETTY. OMG! Camera is not doing any justice abeg. Too beautiful and portable. TV definitely makes them look bigger. -Gave her a tour of our 80% done fashion space and she wanted to use hype to finish me. Advised, prayed and encouraged me. -Then we went to watch AJOSEPO the gathering for the 5th time with her. She brought my own personal premiere to me 💅🏽 -Funfact; This was something she didn’t have to do but she did just to show me love. She already messaged me to thank me several times and even chatted on video call and it was very okay. I was always telling her the “Thank you” was enough so you see how this was such a big deal. THANK YOU SO MUCH WIFEY. Yesterday was super special because of you 🫶🏽.. One of the edits her amazing brother did on the spot. 👇🏽👇🏽. He is too good 👍

Ayeesha (Adore By Ayeesha)

82,052 views • 29 days ago

Dwarkesh is WRONG about the "Output Gap" The narrative around Artificial Intelligence has shifted perceptibly in late 2025. After years of exponential hype, a sense of disillusionment has begun to settle over the industry. Commentators and analysts, most notably podcaster and writer Dwarkesh Patel, have recently highlighted what is being called the “Output Gap.” This is the uncomfortable discrepancy between our models’ skyrocketing performance on benchmarks and the relatively stagnant growth in macroeconomic productivity. We have reached “superhuman” capability on tests, yet global GDP hasn’t skyrocketed, and the promised revolution feels curiously delayed. This frustration stems from a fundamental misunderstanding of where we are in the technology cycle. The industry is currently fixated on “Day 0” capabilities—the raw intelligence of the models, the scaling laws, and the saturation of academic benchmarks. However, the bottleneck has shifted. We are no longer limited by the intelligence of the model, but by the inertia of the enterprise. The “Output Gap” is not a failure of technology; it is a lag in organizational digestion. We have invented a powerful jet engine, but we are essentially frustrated that it hasn’t revolutionized travel before we’ve even built the airframe to mount it on. The primary fallacy driving this disappointment is the expectation of the “drop-in remote worker.” Many observers equate Artificial General Intelligence (AGI) with a digital human that can be onboarded, culturally assimilated, and left to run autonomously with minimal supervision. Because current agents cannot seamlessly replace a human employee in this one-to-one fashion, the conclusion is often that the technology has stalled. This view misses the forest for the trees. Disruptive technologies rarely act as direct replacements; instead, they require a complete restructuring of how work is done. In reality, the barrier to adoption is what IT professionals call “Day 2 Operations.” Day 0 is the exciting launch; Day 2 is the boring, messy reality of governance, security, and maintenance. For an enterprise to deploy an autonomous agent, it isn’t enough for the model to be smart. The organization must solve for Role-Based Access Control (RBAC), SOC 2 compliance, liability frameworks, and data sovereignty. Right now, most organizations lack the infrastructure to handle “non-human” identities that have access to sensitive corporate data. Consider the security implications. A human employee has physical limitations and a single identity. An AI agent is an “always-on” entity that, if given improper permissions, could theoretically read every email in a company server to “optimize workflow.” Security teams (CISOs) are rightly terrified of this prospect. Until we develop granular access controls specifically designed for agents—effectively an “RBAC for AI”—the widespread deployment of autonomous agents will remain blocked by the “Departments of No”: Legal, HR, and Security. This operational friction explains why we are seeing a massive divergence between individual and enterprise adoption. Individually, adoption is rampant; we are in the “Shadow IT” era of AI, where employees secretly use tools like ChatGPT to boost their personal productivity. However, at the organizational level, adoption is glacial because the institution’s primary mandate is risk management, not speed. The C-suite is asking questions about ROI, liability, and data leakage that the current software ecosystem cannot yet answer satisfactorily. History offers a comforting precedent for this timeline. We are currently effectively in the “2002 era” of virtualization. In the early 2000s, virtualization technology (like VMware) was technically viable, but it took nearly a decade to become the default enterprise standard. It required years of maturing management software, security protocols, and cultural shifts before “The Cloud” became a reality. AI is undergoing the same digestion period. The technology is ready, but the enterprise “rails” required to run it are still being laid. This leads us to the “Mechanical Horse” fallacy. When the automobile was invented, people didn’t need a mechanical horse that walked on four legs; they needed a car. But the car required asphalt roads, not dirt paths. Similarly, we are currently trying to force AI into human-shaped workflows (”jobs”) rather than rebuilding the workflows to suit the AI. We are waiting for the mechanical horse, failing to realize that the true disruption comes from unbundling the work entirely. A “job” is essentially a bundle of tasks, context, and responsibilities aggregated for a single human. AI does not replace jobs; it unbundles tasks. The transition we are navigating involves breaking down these bundles and determining which specific value streams can be automated by agents. This requires task decomposition and new management frameworks—a “Council of AIs” approach—rather than a single omnipotent bot. This restructuring is an organizational physics problem, not a computer science problem. The disconnect is further exacerbated by the differing timelines of developers versus executives. Developers and researchers live in a world of root access and rapid iteration, often blinded to the molasses-like speed of corporate change management. A CFO, conversely, thinks in fiscal quarters and compliance audits. They require proven ROI and standardized best practices before signing off on widespread automation. Currently, there are no industry standards for deploying autonomous agents, which halts most conversations at the boardroom door. Therefore, the “stalling” progress is an illusion caused by looking at the wrong metrics. If you look at model cards and benchmarks, progress is linear and fast. If you look at widespread economic integration, the curve is flat. This S-curve of adoption is always significantly behind the S-curve of capability. We are in the flat part of the adoption curve, characterized by high hype, high friction, and frantic infrastructure building behind the scenes. The next three to five years will likely be dominated not by flashy new model capabilities, but by the “boring” work of integration. We will see the rise of startups and consultancies dedicated solely to “AI Governance,” “Agent Identity Management,” and “Context Orchestration.” These are the boring rails that will eventually allow the high-speed train of AI to actually run. The output gap is a temporary, necessary phase. It is the silence before the orchestra starts playing. The potential energy is building up in the form of capability, but it cannot convert into kinetic economic energy until the friction is reduced. The “stalled” revolution is simply a revolution that is currently under construction. We are not witnessing the ceiling of AI intelligence; we are witnessing the floor of AI adoption. The technology has done its part; now, the organizations must do theirs. The future isn’t late—it’s just waiting for legal to sign off.

Dwarkesh is WRONG about the "Output Gap" The narrative around Artificial Intelligence has shifted perceptibly in late 2025. After years of exponential hype, a sense of disillusionment has begun to settle over the industry. Commentators and analysts, most notably podcaster and writer Dwarkesh Patel, have recently highlighted what is being called the “Output Gap.” This is the uncomfortable discrepancy between our models’ skyrocketing performance on benchmarks and the relatively stagnant growth in macroeconomic productivity. We have reached “superhuman” capability on tests, yet global GDP hasn’t skyrocketed, and the promised revolution feels curiously delayed. This frustration stems from a fundamental misunderstanding of where we are in the technology cycle. The industry is currently fixated on “Day 0” capabilities—the raw intelligence of the models, the scaling laws, and the saturation of academic benchmarks. However, the bottleneck has shifted. We are no longer limited by the intelligence of the model, but by the inertia of the enterprise. The “Output Gap” is not a failure of technology; it is a lag in organizational digestion. We have invented a powerful jet engine, but we are essentially frustrated that it hasn’t revolutionized travel before we’ve even built the airframe to mount it on. The primary fallacy driving this disappointment is the expectation of the “drop-in remote worker.” Many observers equate Artificial General Intelligence (AGI) with a digital human that can be onboarded, culturally assimilated, and left to run autonomously with minimal supervision. Because current agents cannot seamlessly replace a human employee in this one-to-one fashion, the conclusion is often that the technology has stalled. This view misses the forest for the trees. Disruptive technologies rarely act as direct replacements; instead, they require a complete restructuring of how work is done. In reality, the barrier to adoption is what IT professionals call “Day 2 Operations.” Day 0 is the exciting launch; Day 2 is the boring, messy reality of governance, security, and maintenance. For an enterprise to deploy an autonomous agent, it isn’t enough for the model to be smart. The organization must solve for Role-Based Access Control (RBAC), SOC 2 compliance, liability frameworks, and data sovereignty. Right now, most organizations lack the infrastructure to handle “non-human” identities that have access to sensitive corporate data. Consider the security implications. A human employee has physical limitations and a single identity. An AI agent is an “always-on” entity that, if given improper permissions, could theoretically read every email in a company server to “optimize workflow.” Security teams (CISOs) are rightly terrified of this prospect. Until we develop granular access controls specifically designed for agents—effectively an “RBAC for AI”—the widespread deployment of autonomous agents will remain blocked by the “Departments of No”: Legal, HR, and Security. This operational friction explains why we are seeing a massive divergence between individual and enterprise adoption. Individually, adoption is rampant; we are in the “Shadow IT” era of AI, where employees secretly use tools like ChatGPT to boost their personal productivity. However, at the organizational level, adoption is glacial because the institution’s primary mandate is risk management, not speed. The C-suite is asking questions about ROI, liability, and data leakage that the current software ecosystem cannot yet answer satisfactorily. History offers a comforting precedent for this timeline. We are currently effectively in the “2002 era” of virtualization. In the early 2000s, virtualization technology (like VMware) was technically viable, but it took nearly a decade to become the default enterprise standard. It required years of maturing management software, security protocols, and cultural shifts before “The Cloud” became a reality. AI is undergoing the same digestion period. The technology is ready, but the enterprise “rails” required to run it are still being laid. This leads us to the “Mechanical Horse” fallacy. When the automobile was invented, people didn’t need a mechanical horse that walked on four legs; they needed a car. But the car required asphalt roads, not dirt paths. Similarly, we are currently trying to force AI into human-shaped workflows (”jobs”) rather than rebuilding the workflows to suit the AI. We are waiting for the mechanical horse, failing to realize that the true disruption comes from unbundling the work entirely. A “job” is essentially a bundle of tasks, context, and responsibilities aggregated for a single human. AI does not replace jobs; it unbundles tasks. The transition we are navigating involves breaking down these bundles and determining which specific value streams can be automated by agents. This requires task decomposition and new management frameworks—a “Council of AIs” approach—rather than a single omnipotent bot. This restructuring is an organizational physics problem, not a computer science problem. The disconnect is further exacerbated by the differing timelines of developers versus executives. Developers and researchers live in a world of root access and rapid iteration, often blinded to the molasses-like speed of corporate change management. A CFO, conversely, thinks in fiscal quarters and compliance audits. They require proven ROI and standardized best practices before signing off on widespread automation. Currently, there are no industry standards for deploying autonomous agents, which halts most conversations at the boardroom door. Therefore, the “stalling” progress is an illusion caused by looking at the wrong metrics. If you look at model cards and benchmarks, progress is linear and fast. If you look at widespread economic integration, the curve is flat. This S-curve of adoption is always significantly behind the S-curve of capability. We are in the flat part of the adoption curve, characterized by high hype, high friction, and frantic infrastructure building behind the scenes. The next three to five years will likely be dominated not by flashy new model capabilities, but by the “boring” work of integration. We will see the rise of startups and consultancies dedicated solely to “AI Governance,” “Agent Identity Management,” and “Context Orchestration.” These are the boring rails that will eventually allow the high-speed train of AI to actually run. The output gap is a temporary, necessary phase. It is the silence before the orchestra starts playing. The potential energy is building up in the form of capability, but it cannot convert into kinetic economic energy until the friction is reduced. The “stalled” revolution is simply a revolution that is currently under construction. We are not witnessing the ceiling of AI intelligence; we are witnessing the floor of AI adoption. The technology has done its part; now, the organizations must do theirs. The future isn’t late—it’s just waiting for legal to sign off.

David Shapiro (L/0)

12,656 views • 7 months ago

Here's why $NEAR is a no-brainer in 2025 👇 Everybody loves NEAR Protocol and there is a reason for that (or many). Near is well-positioned to be one of the leading blockchain ecosystems this year. Let’s explore the “whys”. TIMESTAMPS Quick Bio – 00:00:15 Inflation Reduction Proposal – 00:00:43 Technically Speaking – 00:02:40 Near Intents – 00:03:37 Chain Signatures and AI – 00:04:39 Decentralization and DeFi – 00:05:59 I have my Near account since March 2023, but it has been inactive for a while, as I was focused on other stuff. However, the recent inflation halving proposal by HOT DAO (HOT Protocol 🔥) and LiNEAR (LiNEAR Protocol) brought my eyes back to the project and I really like what I’m seeing. So, here’s my first point. If this proposal passes, NEAR could lead the way in what appears to be a market trend of improving the tokenomics, as more and more experts realize holders have been overpaying for these networks' security, with a too high supply inflation. Solana tried something similar, but the proposal was rejected. In my opinion, validators voting favorably to that show a commitment to the chain for the long term. On the other hand, voting against it signals a short-term vision focused on milking the emissions as much as possible, at the ecosystem’s expense. The voting currently goes with 28% “YEA” votes, needing 66.76% to pass. Most of the validators who already cast their votes went with the yes. 2pilot, avb, openshards, qbit, sicmundus, fox, and intear are, so far, the only seven who voted “NAY”. This proposal has the vocal support of most influential figures in the Near ecosystem, including the Near Foundation (NEAR Foundation), led by Illia (root.near) (🇺🇦, ⋈), which makes me believe it will pass and show the power of the halving in getting the market’s attention and presenting a huge investment asymmetry for the native token right now. Is this everything I like about NEAR? Definitely not. This is just what got me looking at it again, just to discover a (very much) thriving ecosystem, full of interesting things happening at the same time. I’ll mention a few, but there is (much) more. Technically speaking, Near is a high-performance blockchain, with really low fees and one of the fastest finalities, with 600ms block time and approximately 1.8s finality. It also has my favorite architecture for internet-scale scalability, using sharding, while keeping a high decentralization standard. As a learning programmer, Near also has one of the best dev experiences (in my limited opinion). The documentation is clear, has a logical journey, presenting from the basic anatomy in details to more complex SDKs and tools. I’m also in love with the near-cli-rs. A command line interface program written in Rust for seamless interaction with the Near blockchain. Allowing wallet creation, chain query, sending transactions, staking, smart contract calls, and more. Near Intents. This was the second thing to get my attention, while studying the project again, and it sets a whole new standard for blockchain interactions, especially cross-chain. Basically, users can declare an intention (for example, swap Ethereum-USDT to Bitcoin) and a network of solvers, running on Near, will find the best path to accomplish this task. We recently saw an impressive 465k-worth swap happening in exactly this example, paying 0.55% of trading fees to thorswap.near and swapkit.near. According to a Dune Dashboard, the protocol accumulates nearly $400 million in volume since its launch not long ago, in November 2024. *obs.: half this volume was achieved in the last month. Massive! Near Intents is possible due to two other very interesting things: (i) Chain abstraction, and (ii) a solid AI infrastructure. Chain abstraction (via Chain Signatures) is a powerful interoperability feature, allowing Near to friendly connect different blockchains as if they were part of a single network. Users and devs benefit from wallet, address, fees, and cross-chain bridges abstractions - not even noticing they are interacting with multiple chains. One wallet that powers everything. Powered by Near. On AI, Near is just built differently. Not for the hype, but for the solution. The team has been looking for AI solutions much before the ChatGPT fever. Actually, they started as an AI company, pivoting to blockchain later. So, being one of the most promising networks for the growing AI economy was just the natural path to follow. There is an extensive and super complete research piece on that topic, recently published by Reflexivity Research (Reflexivity Research) on July 1st. It presents Near as an AI-optimized blockchain, covering AITP, Shade Agents, x402, Near Intents, and more. Definitely worth the reading. Wrapping up this content with one more aspect that really matters to me is how Near remains truthful to decentralization, data ownership, censorship-resistance and open-source primitives that have been increasingly abandoned by other key players. A simple example of that is how the Near Foundation decided to deprecate its public APIs, encouraging the surge of a more decentralized and competitive market of SaaS projects, with a highlight to Lava Network, that recently appeared in my timeline talking about that. DeFi is also huge on Near, leveraging all the previous properties I mentioned, creating a truly decentralized liquidity pool via Rhea Finance, connected with other chains like BTC, Ethereum, ZCash, and more. All that contributes to Near having the second-largest monthly active addresses, with nearly 50 million, only losing to Solana’s nearly 90 million. In the meantime, NEAR, the token, is not even at the 30rd position by market cap. Crazy stuff. To (finally) wrap it up, I also want to mention Near’s consensus decentralization. While having a low node-count, the network has a Nakamoto Coefficient of 11, which is not bad at all. Surely, there is still room for improvement, which is possible as becoming a validator is accessible staking and hardware-wise. If you liked this content, make sure to click the like bottom and share it around. Follow me on X or subscribe to my YouTube channel, both at vinibarbosabr. See ya!

Here's why $NEAR is a no-brainer in 2025 👇 Everybody loves NEAR Protocol and there is a reason for that (or many). Near is well-positioned to be one of the leading blockchain ecosystems this year. Let’s explore the “whys”. TIMESTAMPS Quick Bio – 00:00:15 Inflation Reduction Proposal – 00:00:43 Technically Speaking – 00:02:40 Near Intents – 00:03:37 Chain Signatures and AI – 00:04:39 Decentralization and DeFi – 00:05:59 I have my Near account since March 2023, but it has been inactive for a while, as I was focused on other stuff. However, the recent inflation halving proposal by HOT DAO (HOT Protocol 🔥) and LiNEAR (LiNEAR Protocol) brought my eyes back to the project and I really like what I’m seeing. So, here’s my first point. If this proposal passes, NEAR could lead the way in what appears to be a market trend of improving the tokenomics, as more and more experts realize holders have been overpaying for these networks' security, with a too high supply inflation. Solana tried something similar, but the proposal was rejected. In my opinion, validators voting favorably to that show a commitment to the chain for the long term. On the other hand, voting against it signals a short-term vision focused on milking the emissions as much as possible, at the ecosystem’s expense. The voting currently goes with 28% “YEA” votes, needing 66.76% to pass. Most of the validators who already cast their votes went with the yes. 2pilot, avb, openshards, qbit, sicmundus, fox, and intear are, so far, the only seven who voted “NAY”. This proposal has the vocal support of most influential figures in the Near ecosystem, including the Near Foundation (NEAR Foundation), led by Illia (root.near) (🇺🇦, ⋈), which makes me believe it will pass and show the power of the halving in getting the market’s attention and presenting a huge investment asymmetry for the native token right now. Is this everything I like about NEAR? Definitely not. This is just what got me looking at it again, just to discover a (very much) thriving ecosystem, full of interesting things happening at the same time. I’ll mention a few, but there is (much) more. Technically speaking, Near is a high-performance blockchain, with really low fees and one of the fastest finalities, with 600ms block time and approximately 1.8s finality. It also has my favorite architecture for internet-scale scalability, using sharding, while keeping a high decentralization standard. As a learning programmer, Near also has one of the best dev experiences (in my limited opinion). The documentation is clear, has a logical journey, presenting from the basic anatomy in details to more complex SDKs and tools. I’m also in love with the near-cli-rs. A command line interface program written in Rust for seamless interaction with the Near blockchain. Allowing wallet creation, chain query, sending transactions, staking, smart contract calls, and more. Near Intents. This was the second thing to get my attention, while studying the project again, and it sets a whole new standard for blockchain interactions, especially cross-chain. Basically, users can declare an intention (for example, swap Ethereum-USDT to Bitcoin) and a network of solvers, running on Near, will find the best path to accomplish this task. We recently saw an impressive 465k-worth swap happening in exactly this example, paying 0.55% of trading fees to thorswap.near and swapkit.near. According to a Dune Dashboard, the protocol accumulates nearly $400 million in volume since its launch not long ago, in November 2024. *obs.: half this volume was achieved in the last month. Massive! Near Intents is possible due to two other very interesting things: (i) Chain abstraction, and (ii) a solid AI infrastructure. Chain abstraction (via Chain Signatures) is a powerful interoperability feature, allowing Near to friendly connect different blockchains as if they were part of a single network. Users and devs benefit from wallet, address, fees, and cross-chain bridges abstractions - not even noticing they are interacting with multiple chains. One wallet that powers everything. Powered by Near. On AI, Near is just built differently. Not for the hype, but for the solution. The team has been looking for AI solutions much before the ChatGPT fever. Actually, they started as an AI company, pivoting to blockchain later. So, being one of the most promising networks for the growing AI economy was just the natural path to follow. There is an extensive and super complete research piece on that topic, recently published by Reflexivity Research (Reflexivity Research) on July 1st. It presents Near as an AI-optimized blockchain, covering AITP, Shade Agents, x402, Near Intents, and more. Definitely worth the reading. Wrapping up this content with one more aspect that really matters to me is how Near remains truthful to decentralization, data ownership, censorship-resistance and open-source primitives that have been increasingly abandoned by other key players. A simple example of that is how the Near Foundation decided to deprecate its public APIs, encouraging the surge of a more decentralized and competitive market of SaaS projects, with a highlight to Lava Network, that recently appeared in my timeline talking about that. DeFi is also huge on Near, leveraging all the previous properties I mentioned, creating a truly decentralized liquidity pool via Rhea Finance, connected with other chains like BTC, Ethereum, ZCash, and more. All that contributes to Near having the second-largest monthly active addresses, with nearly 50 million, only losing to Solana’s nearly 90 million. In the meantime, NEAR, the token, is not even at the 30rd position by market cap. Crazy stuff. To (finally) wrap it up, I also want to mention Near’s consensus decentralization. While having a low node-count, the network has a Nakamoto Coefficient of 11, which is not bad at all. Surely, there is still room for improvement, which is possible as becoming a validator is accessible staking and hardware-wise. If you liked this content, make sure to click the like bottom and share it around. Follow me on X or subscribe to my YouTube channel, both at vinibarbosabr. See ya!

Vini B |「 thecoding 」

40,183 views • 1 year ago

Greetings, global pioneers! Happy Saturday!🌹🌹🌹 I hope this message finds you well and in high spirits. This Saturday, I encourage you to reflect on all the good things life offers. Spend time with your loved ones, enjoy moments of rest, and cherish the blessings you have. Remember that this is the foundation upon which Pi Network was built a community that values love, support, and hard work. As pioneers, we can significantly impact and achieve financial stability while supporting the Pi community. Finding a job is an excellent way to ensure financial stability and not expect to sell Pi. It is important to understand that solely focusing on completing the KYC process and exchanging Pi to fiat currency, without having a job, can lead to feelings of anxiety and depression. Additionally, selling Pi will not solve any financial difficulties and may cause you to miss out on potential wealth opportunities. As a suggestion, all global pioneers should secure a job before the launch of OM. If you are unable to find a permanent job, consider finding a temporary job, especially in the next 3-6 months. By working during this period and refraining from selling Pi, we can speed up the KYC and migration process, ultimately leading to the launch of OM.✌️✌️✌️✌️ In addition, spending more time with our family can bring harmony to our lives and help us gain their support, which is crucial in achieving our goals. Even small contributions to the Pi community, such as posting "thank you," "I support GCV," "I love Pi Network," or "we are a big family and we support each other," can go a long way in making a difference. If you don't understand why we support GCV, take your time to read and observe instead of posting negative comments. Remember, most pioneers catch up and support each other, so if you missed the class, don't worry, and learn from others who did well. Let's work together and make a difference while achieving our goals. In my previous post, I emphasized the importance of having a strategy and tactics to help you manage your group and community efficiently without wasting too much time. To ensure that your group runs smoothly, it's crucial to establish a sense of unity and ground rules. Remember, the group is not a platform to post anything and everything, especially fake news and misleading information. Mutual respect is non-negotiable, and any attack or smear will not be tolerated. Only share information about GCV education and activities. By following the guidelines provided, you can manage your group efficiently with just half an hour of effort each day. As a group owner or moderator, it is your responsibility to ensure that pioneers study in the correct direction. Please refrain from using fake news to attract and paralyze pioneers, as it will only cause anxiety and hatred towards Pi Network. Education is a top priority. But what exactly is education? In the context of Pi Network, education means helping pioneers understand what Pi Network is and why it has not taken the same steps as Bitcoin or other cryptocurrencies. Pi Network's mission is to resolve technology, financial, and currency problems and apply these benefits in our daily lives. It's important that all pioneers pay attention and not just look at the exchange market. While exchange markets can benefit some investors, they can also lead to significant losses. If you read what Dr. Nicolas has said, you will understand why he has invested so much money, almost a decade, into Pi Network as a real blockchain technology to help our world and society. He cannot achieve this goal without the support of all 50 million pioneers. It's important that we work together to make Pi Network a success. The following is a set of recommendations for pioneers interested in GCV . Our first step should be to understand why we need $314,159 and what measures pioneers should undertake to achieve this goal. To succeed, pioneers should make use of easily accessible resources and avoid unnecessary expenditures and risks. In this context, I recommend that pioneers develop the skills necessary to become self-learners, given the wealth of information available on my Twitter. I have received many questions about GCV from pioneers through Twitter. It can be overwhelming to respond to each one individually, especially when I have my daily work to do. I advised pioneers to become self-learners and cultivate patience and perseverance in studying. It's important to take the time to learn and understand things on your own, and not solely rely on others for answers. I would like to acknowledge the suggestions of Canadian merchant Mengmiao for the creation of the website OrientalPurpleLotus, which serves as a platform to share my articles and videos. This website will enable global pioneers to access my posts with greater ease. I will publish the website when it is ready. I apologize for being unable to respond to all of the private messages I receive from pioneers. While I act as a GCV ambassador focused on education, I do not have the capacity to act as a global community leader. For information on specific regions, I advise pioneers to consult their respective community leaders. It is pivotal to emphasize the importance of mutual trust and support in achieving success, and I urge pioneers to refrain from attacking one another. I am elated to witness the success of the Malaysia Community led by Mr. Patrick and other exceptional community leaders in organizing the Xin Shan Barter support GCV event yesterday. The event drew around 500 pioneers from Singapore, Indonesia, Taiwan, Vietnam, and mainland China, generating thousands of GCV data. I extend my gratitude to the Malaysia community for their dedication to GCV education and barter support. Additionally, I commend the Barter organizers and merchants for their generous support and hard work. Their contributions are an inspiration to all global pioneers to learn from their success.✌️✌️✌️✌️👍👍👍 I look forward to the Philippine community's upcoming barter event on Mar. 10th., which will be led by Ms. Lumari and other outstanding community leaders. I express my gratitude to them and extend my best wishes for a successful event.👏👏👏 I encourage all pioneers to join my GCV group, enabling them to share information with their respective groups. The global GCV group and the Chinese GCV group two such communities. This message is coming to you from my cozy office, where I am surrounded by beautiful music and fragrant candles. I will continue to share Malaysia's fantastic barter videos and photos with you and post speeches from myself and other Chinese community leaders. Stay tuned... Doris Yin 🪷🪷🪷

Greetings, global pioneers! Happy Saturday!🌹🌹🌹 I hope this message finds you well and in high spirits. This Saturday, I encourage you to reflect on all the good things life offers. Spend time with your loved ones, enjoy moments of rest, and cherish the blessings you have. Remember that this is the foundation upon which Pi Network was built a community that values love, support, and hard work. As pioneers, we can significantly impact and achieve financial stability while supporting the Pi community. Finding a job is an excellent way to ensure financial stability and not expect to sell Pi. It is important to understand that solely focusing on completing the KYC process and exchanging Pi to fiat currency, without having a job, can lead to feelings of anxiety and depression. Additionally, selling Pi will not solve any financial difficulties and may cause you to miss out on potential wealth opportunities. As a suggestion, all global pioneers should secure a job before the launch of OM. If you are unable to find a permanent job, consider finding a temporary job, especially in the next 3-6 months. By working during this period and refraining from selling Pi, we can speed up the KYC and migration process, ultimately leading to the launch of OM.✌️✌️✌️✌️ In addition, spending more time with our family can bring harmony to our lives and help us gain their support, which is crucial in achieving our goals. Even small contributions to the Pi community, such as posting "thank you," "I support GCV," "I love Pi Network," or "we are a big family and we support each other," can go a long way in making a difference. If you don't understand why we support GCV, take your time to read and observe instead of posting negative comments. Remember, most pioneers catch up and support each other, so if you missed the class, don't worry, and learn from others who did well. Let's work together and make a difference while achieving our goals. In my previous post, I emphasized the importance of having a strategy and tactics to help you manage your group and community efficiently without wasting too much time. To ensure that your group runs smoothly, it's crucial to establish a sense of unity and ground rules. Remember, the group is not a platform to post anything and everything, especially fake news and misleading information. Mutual respect is non-negotiable, and any attack or smear will not be tolerated. Only share information about GCV education and activities. By following the guidelines provided, you can manage your group efficiently with just half an hour of effort each day. As a group owner or moderator, it is your responsibility to ensure that pioneers study in the correct direction. Please refrain from using fake news to attract and paralyze pioneers, as it will only cause anxiety and hatred towards Pi Network. Education is a top priority. But what exactly is education? In the context of Pi Network, education means helping pioneers understand what Pi Network is and why it has not taken the same steps as Bitcoin or other cryptocurrencies. Pi Network's mission is to resolve technology, financial, and currency problems and apply these benefits in our daily lives. It's important that all pioneers pay attention and not just look at the exchange market. While exchange markets can benefit some investors, they can also lead to significant losses. If you read what Dr. Nicolas has said, you will understand why he has invested so much money, almost a decade, into Pi Network as a real blockchain technology to help our world and society. He cannot achieve this goal without the support of all 50 million pioneers. It's important that we work together to make Pi Network a success. The following is a set of recommendations for pioneers interested in GCV . Our first step should be to understand why we need $314,159 and what measures pioneers should undertake to achieve this goal. To succeed, pioneers should make use of easily accessible resources and avoid unnecessary expenditures and risks. In this context, I recommend that pioneers develop the skills necessary to become self-learners, given the wealth of information available on my Twitter. I have received many questions about GCV from pioneers through Twitter. It can be overwhelming to respond to each one individually, especially when I have my daily work to do. I advised pioneers to become self-learners and cultivate patience and perseverance in studying. It's important to take the time to learn and understand things on your own, and not solely rely on others for answers. I would like to acknowledge the suggestions of Canadian merchant Mengmiao for the creation of the website OrientalPurpleLotus, which serves as a platform to share my articles and videos. This website will enable global pioneers to access my posts with greater ease. I will publish the website when it is ready. I apologize for being unable to respond to all of the private messages I receive from pioneers. While I act as a GCV ambassador focused on education, I do not have the capacity to act as a global community leader. For information on specific regions, I advise pioneers to consult their respective community leaders. It is pivotal to emphasize the importance of mutual trust and support in achieving success, and I urge pioneers to refrain from attacking one another. I am elated to witness the success of the Malaysia Community led by Mr. Patrick and other exceptional community leaders in organizing the Xin Shan Barter support GCV event yesterday. The event drew around 500 pioneers from Singapore, Indonesia, Taiwan, Vietnam, and mainland China, generating thousands of GCV data. I extend my gratitude to the Malaysia community for their dedication to GCV education and barter support. Additionally, I commend the Barter organizers and merchants for their generous support and hard work. Their contributions are an inspiration to all global pioneers to learn from their success.✌️✌️✌️✌️👍👍👍 I look forward to the Philippine community's upcoming barter event on Mar. 10th., which will be led by Ms. Lumari and other outstanding community leaders. I express my gratitude to them and extend my best wishes for a successful event.👏👏👏 I encourage all pioneers to join my GCV group, enabling them to share information with their respective groups. The global GCV group and the Chinese GCV group two such communities. This message is coming to you from my cozy office, where I am surrounded by beautiful music and fragrant candles. I will continue to share Malaysia's fantastic barter videos and photos with you and post speeches from myself and other Chinese community leaders. Stay tuned... Doris Yin 🪷🪷🪷

Doris Yin 东方紫莲🪷

24,667 views • 2 years ago

I paid Alex & Leila Hormozi $5,000 for their 2-day scaling workshop. Why? To grow my business from $6 million to $12 million in 2025. These 12 lessons from the event will help me get there: 1. The fastest-moving entrepreneurs are obsessive resource allocators. Similar to investors, they seek the best risk-adjusted returns with the resources they have. The main resources of the business are: • Time (of the team) • Attention (of the team) • And capital (of the business) So resource allocation is: • Aligning attention on the most important thing • Properly allocating everyone’s time to achieve that thing the fastest • Strategically investing capital to accelerate the outcome or increase its likelihood of achievement 2. $3m to $10m in EBITDA is where the majority of the value in a business is created. $3m in EBITDA likely gets a 1x multiple, so $3m of enterprise value. The process of going to $10m (when done well), not only 3.3x’s the EBITDA, but can take the multiple from 1 to 4 -> which is a 13.2x return. The EV goes from $3m to $40m, and that is the stage we are in right now as a business. 3. LTV:CAC are two metrics you must have staring at you and constantly audited. LTV = lifetime value of the customer CAC = customer acquisition cost The scope of calculating those is beyond this write-up, but basically you want this metric to be ~8:1 or higher when aggressively scaling a service-based business. On top of that, these are the only two metrics that you can “improve” in your business → either making customers worth more or reducing the cost to acquire them. You should be able to tie every project on your list directly to the improvement of one of these metrics. 4. We need a single dashboard with the most important metrics in the business. The quality of the dashboard is: • How many people use it on a daily basis • And how clearly they can connect their performance to the performance of the main numbers on the dashboard. We have data thrown about across Airtable, Google Sheets, and various Slack channels. Now, it’s time to unite them such that we can make even better decisions as a team. 5. Leveling up in business is transitioning from selling to people to selling to employees. In the beginning, you are the one creating all of the value. Over time, you will replace yourself out of certain functions that are customer-facing (if you are approaching business correctly). However, your job then becomes selling to your employees to spark their highest performance and retain them. 6. Brand is the best way to improve LTV and reduce CAC at the same time. It makes it cheaper to acquire customers since you have fixed media expenses (just labor) but unlimited upside in the number of eyeballs you can reach. It increases LTV because the continued content you create makes customers likely to keep purchasing because they associate the good content with the purchase they made, whether it’s free content or not. 7. Every single thing in your business is trainable, you just lack the skill of training. Seeing their presentations, their handshakes, the way they repeat the question back to the audience, it was so clear that Alex & Leila did this first, then obsessively role-played and drilled each person on their performance until it was indistinguishable from theirs. 8. The people doing it at the highest level of an obsessive, intentional standard. It was so evident the way these employees conducted themselves that they: • Loved working there • Loved the culture of high performance • And had been trained with extreme repetition and attention to detail 9. Past $3-5m in revenue, anything “new” starts with “who” not “how.” I made the mistake last year of trying to “bootstrap” our cold ads initiative (while continuing to run the rest of the business & sales team). I spent roughly ~200 hours on this throughout the year, which took time away from both my content and the management of the sales team. But for whatever reason, I thought I “had” to be the one who got it off the ground, then handed it off to a new hire or media buyer. But I had the sequence flipped. I should have spent the first 50 hours finding a world-class director of paid marketing, someone with far more experience than me building out a cold traffic acquisition system. Heck, I could have even spent 200 hours on it and ended up with a far greater return than I ended up with. 10. Excellence is a remarkably high number of extremely small details done well. Throughout the workshop, I paid close attention to the event operations, taking notes on how to run a great in-person event in case we wanted to do so in the future. Several things stood out that were clearly “iterations” from prior events, all based around eliminating the small, annoying parts of attending any kind of seminar. • High-quality food • Greeters at the door • Clear bathroom signs • A barista for fresh coffee • WiFi signs posted everywhere • Constant 15-minute breaks every 90 minutes The list goes on and on. 11. Any change you make in a business you should expect a 20% “decrease” in performance to start. That makes the hurdle rate to doing “new” at least 20% for it to be worth it, and arguably 40%. This happens because the switching cost leads to an immediate drop just from having to retrain the team. Change a meeting cadence, change a sales script, change an onboarding flow, all of these are going to come with a switching cost the team must overcome. Therefore, the highest risk-adjusted return is always to just do more or better or whatever you’re already doing, rather than add something new. 12. The ultimate size of the business is the sum of the intelligence of its people. Alex laid out this golden nugget during one of his talks and I found it interesting for a few reasons. First, because of his definition of intelligence = speed of learning, that means the ultimate size of the company is how quickly everyone can learn things. And so said another way, the ultimate size of the company is correlated to the speed of its iterations. The second reason I found this interesting is because you can create a culture of iteration through constant, rapid feedback on every behavior. And when I say constant, I mean constant. You could tell they’ve built this culture by the way their presenters all presented the exact same way as Alex and Leila. Aaand that’s it! I go deeper into all these lessons in this video, check it out: Timestamps 00:37 The Fastest Moving Entrepreneurs Are Obsessive Resource Allocators 04:09 $3m To $10m EBITDA Is Where The Majority Of The Value In A Business Is Created 07:00 LTV:CAC Are Two Metrics You Must Have Staring At You 10:04 You Need A Single Dashboard With The Most Important Metrics In The Business 12:03 Leveling Up In Business Is Transitioning To Selling To People To Selling To Employees 14:10 Brand Is The Best Way To Improve LTV And Reduce CAC At The Same Time 16:02 Every Single Thing In Your Business Is Trainable, You Just Lack The Skill Of Training 18:54 The People Doing It At The Highest Level Have An Obsessive, Intentional Standard 20:04 Past $3-5m In Revenue, Anything "New" Starts With "Who" Not "How" 23:33 Excellence Is A Remarkably High Number Of Extremely Small Details Done Well 26:23 Any Change You Make In A Business You Should Expect A 20% "Decrease" In Performance To Start 28:07 The Ultimate Size Of The Business Is The Sum Of The Intelligence Of It's People

Dickie Bush 🚢

62,036 views • 1 year ago

Hezbollah has been boasting how it could destroy the USS Gerald R. Ford (CVN-78) and its escorts. Lets dive into how Hezbollah Terrorists could attack a US Navy Aircraft carrier in the Med, what could happen, and the possible outcomes, assisted with Command Development Team simulation software. To understand the footage shown, let me break down some basic concepts of modern naval combat: Military ships often use a concept called "EMCON", which stands for EMission CONtrol, or "Radio silence" in laymans terms. Consider it like this: if you are with a flashlight in the night, you can spot a person say 500 Meters away by shining at him with the flashlight. You will however, be able to see that flashlight from many kilometers away, without being seen, even if it is directed at you, giving you the location of the person with the flashlight, without disclosing your presence. So ships really avoid "radio emissions", such as radar. Carrier Strike Groups (CSG) like the Ford CSG WANT Radar coverage for their own safety, but not in a way that their location can be known. This is done by Airplanes that fly in the general vicinity of the CSG, providing coverage, without compromising the CSG location. The US Navy uses the E-2 Hawkeye for this in most cases. In this case here, we are not using the E-2 Hawkeye, but the (likely in Theater anyway) E-3 Sentry from NATO. A system that is likely LESS sophisticated than the cutting edge E-2D Advanced Hawkeyes that were visible on the USS Ford pictures that surfaced recently. We do not simulate any carrier based "Combat Air Patrol" either, to test the "ship based" defenses. The composition of the Ford CSG is modeled using the actual ships listed. The CSG is moving on a nothern course at 15 knots, under full EMCON, 115 miles off the coast. The maximum range of the Russian Bastion-P coastal missle complex is about 100 miles, we have to assume that the US Navy will sail their ships outside of (possible) Hezbollah radar range. We also assume, as this is a time of very heightened alert, that the US Navy has Rules of Engagement that would allow it to shoot down any Hezbollah drones or craft coming at it with apparent hostile intention. I have assumed this to be 50 miles away from the CSG in this scenario. Now lets look at the Hezbollah side. We assume to have 6 Bastion-P complexes, with 2 missles per Transport-Erector-Launcher (TEL). So if it can be figured out where the CSG is, 12 P-800 Oniks missle with speeds over Mach 2 would be able to engage the CSG. The problem however is, that you can not "shoot" at a ship without knowing its location. While this may sound very simple indeed, when the ship you are looking for does not disclose its location voluntarily, you can not go to "marinetraffic" and look for the carrier. You can also not use your airforce, if you do not really have one, like Hezbollah. You can not use Sattelites, if you have none. You can try to use drones, if you know the overall direction, or use radar. Land based Radar? Out of Range. Drones? Yes, lets fly drones to the overall direction, hoping to see the carrier. Satellites? Nope. Wait, lets ask Putin. He will probably be nice enough to us, to have a liasion tell us in real time from a russian sattelite where the CSG is. And thats what we are running with here, as drones will not reach the carrier. A russian sattelite could provide rather real time information on the CSG location, allowing manual targeting. The video will provide you with the results. A US CSG with such powerful escorts will not be fundamentally threatened by the assets of Hezbollah. It will have to defend, but will do so rather easily. At the conclusion of the Engagement, the CSG still has literally 100s of SM-2, SM-6 and ESSM Missles. Note: this is done on commercially available software, the software uses NTDS/APP6 icons, white is air radar range, yellow surface, green sonar. The white cones off the missles are their onboard active radar seeker. If you have any questions understanding any of the things displyed, please ask. Note that this is a hobby analysis with publicly available data and tools, and not military research. Thanks for reading! #usnavy #HezbollahTerrorists #hezbullah #hezbollah #israel #IsraelUnderAttack #ukraine #russia #nato Naval News SubBrief Tyler Rogoway Status-6 (War & Military News) TheIntelFrog @CovertShores Raw Combat log output, starting with Hezbollah detecting CSG via RU Proxy: 13/10/2023 12:46:13 - [Hezbollah] New contact! Designated SKUNK #1070 - Detected by Resurs P1 [Sensors: Generic Satellite Visual Camera] at 177deg - 1149.3nm 13/10/2023 12:46:13 - [Hezbollah] New contact! Designated SKUNK #1071 - Detected by Resurs P1 [Sensors: Generic Satellite Visual Camera] at 177deg - 1149.3nm 13/10/2023 12:46:13 - [Hezbollah] New contact! Designated SKUNK #1072 - Detected by Resurs P1 [Sensors: Generic Satellite Visual Camera] at 177deg - 1149.3nm 13/10/2023 12:46:13 - [Hezbollah] New contact! Designated SKUNK #1073 - Detected by Resurs P1 [Sensors: Generic Satellite Visual Camera] at 177deg - 1145.4nm 13/10/2023 12:46:13 - [Hezbollah] New contact! Designated SKUNK #1074 - Detected by Resurs P1 [Sensors: Generic Satellite Visual Camera] at 177deg - 1153.3nm 13/10/2023 12:46:13 - [Hezbollah] New contact! Designated SKUNK #1075 - Detected by Resurs P1 [Sensors: Generic Satellite Visual Camera] at 177deg - 1148nm 13/10/2023 12:46:23 - [Hezbollah] Contact: SKUNK #1073 has been positively identified as: DDG 63 Carney [Arleigh Burke Flight I] - Determined as: Hostile (ID by: Resurs P1 [Sensor: Generic Satellite Visual Camera] at Estimated 1121 nm) 13/10/2023 12:46:23 - [Hezbollah] Contact: SKUNK #1071 has been positively identified as: DDG 116 Thomas Hudner [Arleigh Burke Flight IIA Technology Insertion] - Determined as: Hostile (ID by: Resurs P1 [Sensor: Generic Satellite Visual Camera] at Estimated 1125 nm) 13/10/2023 12:46:23 - [Hezbollah] Contact: SKUNK #1070 has been positively identified as: CVN 78 Gerald R. Ford - Determined as: Hostile (ID by: Resurs P1 [Sensor: Generic Satellite Visual Camera] at Estimated 1125 nm) 13/10/2023 12:46:23 - [Hezbollah] Contact: SKUNK #1072 has been positively identified as: DDG 61 Ramage [Arleigh Burke Flight I] - Determined as: Hostile (ID by: Resurs P1 [Sensor: Generic Satellite Visual Camera] at Estimated 1125 nm) 13/10/2023 12:46:23 - [Hezbollah] Contact: SKUNK #1074 has been positively identified as: DDG 80 Roosevelt [Arleigh Burke Flight IIA] - Determined as: Hostile (ID by: Resurs P1 [Sensor: Generic Satellite Visual Camera] at Estimated 1129 nm) 13/10/2023 12:46:23 - [Hezbollah] Contact: SKUNK #1075 has been positively identified as: CG 60 Normandy [Ticonderoga Baseline 3, VLS] - Determined as: Hostile (ID by: Resurs P1 [Sensor: Generic Satellite Visual Camera] at Estimated 1124 nm) 13/10/2023 12:47:23 - [USA] Contact: BOGEY #24 has been classified as: Ababil-3 UAV [Mod. Seeker 2D Copy] - Determined as: Unfriendly (Classification by: DDG 116 Thomas Hudner [Arleigh Burke Flight IIA Technology Insertion] [Sensor: AN/SPY-1D(V) MFR [ABM Mod]] [NCTR mode] at 56.9 nm) 13/10/2023 12:47:23 - [USA] Contact: BOGEY #26 has been classified as: Shahed-161 UAV - Determined as: Unfriendly (Classification by: DDG 116 Thomas Hudner [Arleigh Burke Flight IIA Technology Insertion] [Sensor: AN/SPY-1D(V) MFR [ABM Mod]] [NCTR mode] at 34.9 nm) 13/10/2023 12:47:52 - [USA] New contact! Designated VAMPIRE #3507 - Detected by E-3A Sentry [Sensors: AN/APY-2 RSIP] at 70deg - 95.2nm 13/10/2023 12:47:52 - [USA] New contact! Designated VAMPIRE #3508 - Detected by E-3A Sentry [Sensors: AN/APY-2 RSIP] at 69deg - 96.4nm 13/10/2023 12:47:52 - [USA] New contact! Designated VAMPIRE #3509 - Detected by E-3A Sentry [Sensors: AN/APY-2 RSIP] at 70deg - 95.6nm 13/10/2023 12:47:52 - [USA] New contact! Designated VAMPIRE #3510 - Detected by E-3A Sentry [Sensors: AN/APY-2 RSIP] at 69deg - 96.8nm 13/10/2023 12:47:52 - [USA] New contact! Designated VAMPIRE #3511 - Detected by E-3A Sentry [Sensors: AN/APY-2 RSIP] at 69deg - 96.1nm 13/10/2023 12:47:52 - [USA] New contact! Designated VAMPIRE #3512 - Detected by E-3A Sentry [Sensors: AN/APY-2 RSIP] at 69deg - 96.4nm 13/10/2023 12:47:52 - [USA] New contact! Designated VAMPIRE #3513 - Detected by E-3A Sentry [Sensors: AN/APY-2 RSIP] at 70deg - 97.1nm 13/10/2023 12:47:52 - [USA] New contact! Designated VAMPIRE #3514 - Detected by E-3A Sentry [Sensors: AN/APY-2 RSIP] at 69deg - 98nm 13/10/2023 12:47:52 - [USA] New contact! Designated VAMPIRE #3515 - Detected by E-3A Sentry [Sensors: AN/APY-2 RSIP] at 70deg - 97.2nm 13/10/2023 12:48:12 - [USA] New contact! Designated VAMPIRE #3576 - Detected by E-3A Sentry [Sensors: AN/APY-2 RSIP] at 68deg - 91nm 13/10/2023 12:48:12 - [USA] New contact! Designated VAMPIRE #3577 - Detected by E-3A Sentry [Sensors: AN/APY-2 RSIP] at 69deg - 89.9nm 13/10/2023 12:48:12 - [USA] New contact! Designated VAMPIRE #3578 - Detected by E-3A Sentry [Sensors: AN/APY-2 RSIP] at 69deg - 90.7nm 13/10/2023 12:48:13 - Side 'Hezbollah' is now considered HOSTILE to USA 13/10/2023 12:48:13 - [USA] Contact: Shahed-161 UAV #26 has been manually marked as hostile! 13/10/2023 12:48:20 - [USA] Contact: BOGEY #22 has been manually marked as hostile! 13/10/2023 12:48:55 - [Hezbollah] New contact! Designated SAM #1238 - Detected by Shahed-161 UAV [Sensors: Generic IRST] at 266deg - 10nm 13/10/2023 12:48:59 - [Hezbollah] New contact! Designated SAM #1243 - Detected by Shahed-161 UAV [Sensors: Generic IRST] at 266deg - 8.6nm 13/10/2023 12:49:00 - [Hezbollah] New contact! Designated SAM #1245 - Detected by Shahed-161 UAV [Sensors: Generic IRST] at 234deg - 13.3nm 13/10/2023 12:49:17 - Weapon: RIM-174A ERAM SM-6 Blk IA #40 is attacking Shahed-161 UAV with a base PH of 90%. PH adjusted for weapon speed: 36% (pure-aerodynamic attitude control). Intercept angle is 304 deg - hit probability adjusted to 25%.Final PH: 25%. Result: 30 - MISS 13/10/2023 12:49:17 - [Hezbollah] Hezbollah :Contact SAM #1238 has been lost. 13/10/2023 12:49:25 - [Hezbollah] New contact! Designated SAM #1271 - Detected by Shahed-161 UAV [Sensors: Generic IRST] at 248deg - 13.1nm 13/10/2023 12:49:34 - Weapon: RIM-174A ERAM SM-6 Blk IB #41 is attacking Ababil-3 UAV [Mod. Seeker 2D Copy] with a base PH of 90%. Intercept angle is 51 deg - hit probability adjusted to 65%.Final PH: 65%. Result: 12 - HIT 13/10/2023 12:49:34 - [Hezbollah] Ababil-3 UAV [Mod. Seeker 2D Copy] has suffered weapon damage: 89.9 DPs 13/10/2023 12:49:34 - [Hezbollah] Hezbollah :Contact SAM #1271 has been lost. 13/10/2023 12:49:34 - [Hezbollah] Ababil-3 UAV [Mod. Seeker 2D Copy] has been destroyed! 13/10/2023 12:49:34 - [USA] Contact Ababil-3 UAV [Mod. Seeker 2D Copy] #23 has been lost. 13/10/2023 12:49:39 - Weapon: RIM-174A ERAM SM-6 Blk IB #42 is attacking Ababil-3 UAV [Mod. Seeker 2D Copy] with a base PH of 90%. Intercept angle is 313 deg - hit probability adjusted to 66%.Final PH: 66%. Result: 11 - HIT 13/10/2023 12:49:39 - [Hezbollah] Ababil-3 UAV [Mod. Seeker 2D Copy] has suffered weapon damage: 89.9 DPs 13/10/2023 12:49:39 - [Hezbollah] Hezbollah :Contact SAM #1243 has been lost. 13/10/2023 12:49:39 - [Hezbollah] Ababil-3 UAV [Mod. Seeker 2D Copy] has been destroyed! 13/10/2023 12:49:39 - [USA] Contact Ababil-3 UAV [Mod. Seeker 2D Copy] #24 has been lost. 13/10/2023 12:49:43 - Weapon: RIM-174A ERAM SM-6 Blk IB #43 is attacking Shahed-161 UAV with a base PH of 90%. Intercept angle is 65 deg - hit probability adjusted to 57%.Final PH: 57%. Result: 11 - HIT 13/10/2023 12:49:43 - [Hezbollah] Shahed-161 UAV has suffered weapon damage: 89.9 DPs 13/10/2023 12:49:43 - [Hezbollah] Hezbollah :Contact SAM #1245 has been lost. 13/10/2023 12:49:43 - [Hezbollah] Shahed-161 UAV has been destroyed! 13/10/2023 12:49:43 - [USA] Contact Shahed-161 UAV #25 has been lost. 13/10/2023 12:49:54 - [Hezbollah] New contact! Designated SAM #1301 - Detected by Shahed-161 UAV [Sensors: Generic IRST] at 258deg - 10.5nm 13/10/2023 12:50:10 - Weapon: RIM-174A ERAM SM-6 Blk IA #44 is attacking Shahed-161 UAV with a base PH of 90%. PH adjusted for weapon speed: 83% (pure-aerodynamic attitude control). Target signature modifier: -5% (Director [Active Radar Seeker] has tech-gen: Late 2010s). Intercept angle is 316 deg - hit probability adjusted to 59%.Final PH: 59%. Result: 42 - HIT 13/10/2023 12:50:10 - [Hezbollah] Shahed-161 UAV has suffered weapon damage: 89 DPs 13/10/2023 12:50:10 - [Hezbollah] Hezbollah :Contact SAM #1301 has been lost. 13/10/2023 12:50:10 - [Hezbollah] Shahed-161 UAV has been destroyed! 13/10/2023 12:50:10 - [USA] Contact Shahed-161 UAV #26 has been lost. 13/10/2023 12:51:58 - [USA] Contact: VAMPIRE #3507 has been type-classified as: GuidedWeapon (Classification by: DDG 116 Thomas Hudner [Arleigh Burke Flight IIA Technology Insertion] [Sensor: Mk46 Mod 1 [CCD]] at 14 nm) 13/10/2023 12:51:59 - [USA] Contact: VAMPIRE #3508 has been type-classified as: GuidedWeapon (Classification by: DDG 116 Thomas Hudner [Arleigh Burke Flight IIA Technology Insertion] [Sensor: Mk46 Mod 1 [CCD]] at 13.9 nm) 13/10/2023 12:51:59 - [USA] Contact: VAMPIRE #3509 has been type-classified as: GuidedWeapon (Classification by: DDG 116 Thomas Hudner [Arleigh Burke Flight IIA Technology Insertion] [Sensor: Mk46 Mod 1 [CCD]] at 14 nm) 13/10/2023 12:51:59 - [USA] Contact: VAMPIRE #3511 has been type-classified as: GuidedWeapon (Classification by: DDG 116 Thomas Hudner [Arleigh Burke Flight IIA Technology Insertion] [Sensor: Mk46 Mod 1 [CCD]] at 14 nm) 13/10/2023 12:52:00 - [USA] Contact: VAMPIRE #3510 has been type-classified as: GuidedWeapon (Classification by: DDG 116 Thomas Hudner [Arleigh Burke Flight IIA Technology Insertion] [Sensor: Mk46 Mod 1 [CCD]] at 13.9 nm) 13/10/2023 12:52:00 - [USA] Contact: VAMPIRE #3512 has been type-classified as: GuidedWeapon (Classification by: DDG 116 Thomas Hudner [Arleigh Burke Flight IIA Technology Insertion] [Sensor: Mk46 Mod 1 [CCD]] at 14 nm) 13/10/2023 12:52:04 - [USA] Contact: VAMPIRE #3513 has been type-classified as: GuidedWeapon (Classification by: DDG 116 Thomas Hudner [Arleigh Burke Flight IIA Technology Insertion] [Sensor: Mk46 Mod 1 [CCD]] at 14 nm) 13/10/2023 12:52:04 - [USA] Contact: VAMPIRE #3577 has been type-classified as: GuidedWeapon (Classification by: DDG 116 Thomas Hudner [Arleigh Burke Flight IIA Technology Insertion] [Sensor: Mk46 Mod 1 [CCD]] at 14 nm) 13/10/2023 12:52:05 - [USA] Contact: VAMPIRE #3514 has been type-classified as: GuidedWeapon (Classification by: DDG 116 Thomas Hudner [Arleigh Burke Flight IIA Technology Insertion] [Sensor: Mk46 Mod 1 [CCD]] at 13.9 nm) 13/10/2023 12:52:05 - [USA] Contact: VAMPIRE #3515 has been type-classified as: GuidedWeapon (Classification by: DDG 116 Thomas Hudner [Arleigh Burke Flight IIA Technology Insertion] [Sensor: Mk46 Mod 1 [CCD]] at 14 nm) 13/10/2023 12:52:06 - [USA] Contact: VAMPIRE #3576 has been type-classified as: GuidedWeapon (Classification by: DDG 116 Thomas Hudner [Arleigh Burke Flight IIA Technology Insertion] [Sensor: Mk46 Mod 1 [CCD]] at 13.9 nm) 13/10/2023 12:52:06 - [USA] Contact: VAMPIRE #3578 has been type-classified as: GuidedWeapon (Classification by: DDG 116 Thomas Hudner [Arleigh Burke Flight IIA Technology Insertion] [Sensor: Mk46 Mod 1 [CCD]] at 14 nm) 13/10/2023 12:52:08 - Weapon: RIM-162D ESSM #45 is attacking SSC-5 Stooge [P-800 Yakhont] #28 with a base PH of 90%. Target speed modifier: -10%. Intercept angle is 357 deg - hit probability adjusted to 79%.Final PH: 79%. Result: 34 - HIT 13/10/2023 12:52:08 - [USA] Contact GuidedWeapon #3507 has been lost. 13/10/2023 12:52:09 - Weapon: RIM-162D ESSM #46 is attacking SSC-5 Stooge [P-800 Yakhont] #29 with a base PH of 90%. Target speed modifier: -10%. Intercept angle is 358 deg - hit probability adjusted to 79%.Final PH: 79%. Result: 31 - HIT 13/10/2023 12:52:09 - [USA] Contact GuidedWeapon #3508 has been lost. 13/10/2023 12:52:11 - Weapon: RIM-162D ESSM #49 is attacking SSC-5 Stooge [P-800 Yakhont] #32 with a base PH of 90%. Target speed modifier: -10%. Intercept angle is 358 deg - hit probability adjusted to 79%.Final PH: 79%. Result: 36 - HIT 13/10/2023 12:52:11 - [USA] Contact GuidedWeapon #3511 has been lost. 13/10/2023 12:52:11 - Weapon: RIM-162A ESSM #52 is attacking SSC-5 Stooge [P-800 Yakhont] #31 with a base PH of 90%. Target speed modifier: -10%. Intercept angle is 355 deg - hit probability adjusted to 78%.Final PH: 78%. Result: 9 - HIT 13/10/2023 12:52:11 - [USA] Weapon: RIM-162A ESSM #57 has been redirected to new target: GuidedWeapon #3515 13/10/2023 12:52:11 - [USA] Contact GuidedWeapon #3510 has been lost. 13/10/2023 12:52:12 - Weapon: RIM-162D ESSM #50 is attacking SSC-5 Stooge [P-800 Yakhont] #30 with a base PH of 90%. Target speed modifier: -10%. Intercept angle is 356 deg - hit probability adjusted to 78%.Final PH: 78%. Result: 25 - HIT 13/10/2023 12:52:12 - [USA] Contact GuidedWeapon #3509 has been lost. 13/10/2023 12:52:12 - Weapon: RIM-162A ESSM #55 is attacking SSC-5 Stooge [P-800 Yakhont] #33 with a base PH of 90%. Target speed modifier: -10%. Intercept angle is 355 deg - hit probability adjusted to 78%.Final PH: 78%. Result: 20 - HIT 13/10/2023 12:52:12 - [USA] Weapon: RIM-162A ESSM #59 has been redirected to new target: GuidedWeapon #3576 13/10/2023 12:52:12 - [USA] Contact GuidedWeapon #3512 has been lost. 13/10/2023 12:52:13 - [USA] Weapon: RIM-162D ESSM #47 is running blind for more than 5 sec... self-destructing. 13/10/2023 12:52:14 - [USA] Weapon: RIM-162D ESSM #48 is running blind for more than 5 sec... self-destructing. 13/10/2023 12:52:15 - Weapon: RIM-162A ESSM #57 is attacking SSC-5 Stooge [P-800 Yakhont] #36 with a base PH of 90%. Target speed modifier: -10%. Intercept angle is 0 deg - hit probability adjusted to 80%.Final PH: 80%. Result: 71 - HIT 13/10/2023 12:52:15 - [USA] Contact GuidedWeapon #3515 has been lost. 13/10/2023 12:52:16 - Weapon: RIM-162A ESSM #60 is attacking SSC-5 Stooge [P-800 Yakhont] #34 with a base PH of 90%. Target speed modifier: -10%. Intercept angle is 360 deg - hit probability adjusted to 80%.Final PH: 80%. Result: 49 - HIT 13/10/2023 12:52:16 - [USA] Weapon: RIM-162A ESSM #65 has no eligible alternative target to be redirected to... 13/10/2023 12:52:16 - [USA] Contact GuidedWeapon #3513 has been lost. 13/10/2023 12:52:16 - [USA] Weapon: RIM-162D ESSM #51 is running blind for more than 5 sec... self-destructing. 13/10/2023 12:52:16 - [USA] Weapon: RIM-162D ESSM #54 is running blind for more than 5 sec... self-destructing. 13/10/2023 12:52:16 - [USA] Weapon: RIM-162D ESSM #58 is running blind for more than 5 sec... self-destructing. 13/10/2023 12:52:16 - Weapon: RIM-162A ESSM #59 is attacking SSC-5 Stooge [P-800 Yakhont] #38 with a base PH of 90%. Target speed modifier: -10%. Intercept angle is 357 deg - hit probability adjusted to 78%.Final PH: 78%. Result: 75 - HIT 13/10/2023 12:52:16 - [USA] Contact GuidedWeapon #3576 has been lost. 13/10/2023 12:52:16 - Weapon: RIM-162A ESSM #63 is attacking SSC-5 Stooge [P-800 Yakhont] #38 with a base PH of 90%. Target speed modifier: -10%. Intercept angle is 359 deg - hit probability adjusted to 79%.Final PH: 79%. Result: 57 - HIT 13/10/2023 12:52:16 - [USA] Weapon: RIM-162A ESSM #70 has been redirected to new target: GuidedWeapon #3514 13/10/2023 12:52:16 - [USA] Contact GuidedWeapon #3577 has been lost. 13/10/2023 12:52:17 - [USA] Weapon: RIM-162D ESSM #53 is running blind for more than 5 sec... self-destructing. 13/10/2023 12:52:17 - [USA] Weapon: RIM-162A ESSM #65 has no eligible alternative target to be redirected to... 13/10/2023 12:52:17 - [USA] Weapon: RIM-162D ESSM #56 is running blind for more than 5 sec... self-destructing. 13/10/2023 12:52:17 - [USA] Weapon: RIM-162D ESSM #61 is running blind for more than 5 sec... self-destructing. 13/10/2023 12:52:18 - Weapon: RIM-162A ESSM #70 is attacking SSC-5 Stooge [P-800 Yakhont] #35 with a base PH of 90%. Target speed modifier: -10%. Intercept angle is 358 deg - hit probability adjusted to 79%.Final PH: 79%. Result: 63 - HIT 13/10/2023 12:52:18 - [USA] Contact GuidedWeapon #3514 has been lost. 13/10/2023 12:52:18 - Weapon: RIM-174A ERAM SM-6 Blk IA #73 is attacking SSC-5 Stooge [P-800 Yakhont] #39 with a base PH of 90%. Intercept angle is 355 deg - hit probability adjusted to 88%.Final PH: 88%. Result: 34 - HIT 13/10/2023 12:52:18 - [USA] Contact GuidedWeapon #3578 has been lost.

Hezbollah has been boasting how it could destroy the USS Gerald R. Ford (CVN-78) and its escorts. Lets dive into how Hezbollah Terrorists could attack a US Navy Aircraft carrier in the Med, what could happen, and the possible outcomes, assisted with Command Development Team simulation software. To understand the footage shown, let me break down some basic concepts of modern naval combat: Military ships often use a concept called "EMCON", which stands for EMission CONtrol, or "Radio silence" in laymans terms. Consider it like this: if you are with a flashlight in the night, you can spot a person say 500 Meters away by shining at him with the flashlight. You will however, be able to see that flashlight from many kilometers away, without being seen, even if it is directed at you, giving you the location of the person with the flashlight, without disclosing your presence. So ships really avoid "radio emissions", such as radar. Carrier Strike Groups (CSG) like the Ford CSG WANT Radar coverage for their own safety, but not in a way that their location can be known. This is done by Airplanes that fly in the general vicinity of the CSG, providing coverage, without compromising the CSG location. The US Navy uses the E-2 Hawkeye for this in most cases. In this case here, we are not using the E-2 Hawkeye, but the (likely in Theater anyway) E-3 Sentry from NATO. A system that is likely LESS sophisticated than the cutting edge E-2D Advanced Hawkeyes that were visible on the USS Ford pictures that surfaced recently. We do not simulate any carrier based "Combat Air Patrol" either, to test the "ship based" defenses. The composition of the Ford CSG is modeled using the actual ships listed. The CSG is moving on a nothern course at 15 knots, under full EMCON, 115 miles off the coast. The maximum range of the Russian Bastion-P coastal missle complex is about 100 miles, we have to assume that the US Navy will sail their ships outside of (possible) Hezbollah radar range. We also assume, as this is a time of very heightened alert, that the US Navy has Rules of Engagement that would allow it to shoot down any Hezbollah drones or craft coming at it with apparent hostile intention. I have assumed this to be 50 miles away from the CSG in this scenario. Now lets look at the Hezbollah side. We assume to have 6 Bastion-P complexes, with 2 missles per Transport-Erector-Launcher (TEL). So if it can be figured out where the CSG is, 12 P-800 Oniks missle with speeds over Mach 2 would be able to engage the CSG. The problem however is, that you can not "shoot" at a ship without knowing its location. While this may sound very simple indeed, when the ship you are looking for does not disclose its location voluntarily, you can not go to "marinetraffic" and look for the carrier. You can also not use your airforce, if you do not really have one, like Hezbollah. You can not use Sattelites, if you have none. You can try to use drones, if you know the overall direction, or use radar. Land based Radar? Out of Range. Drones? Yes, lets fly drones to the overall direction, hoping to see the carrier. Satellites? Nope. Wait, lets ask Putin. He will probably be nice enough to us, to have a liasion tell us in real time from a russian sattelite where the CSG is. And thats what we are running with here, as drones will not reach the carrier. A russian sattelite could provide rather real time information on the CSG location, allowing manual targeting. The video will provide you with the results. A US CSG with such powerful escorts will not be fundamentally threatened by the assets of Hezbollah. It will have to defend, but will do so rather easily. At the conclusion of the Engagement, the CSG still has literally 100s of SM-2, SM-6 and ESSM Missles. Note: this is done on commercially available software, the software uses NTDS/APP6 icons, white is air radar range, yellow surface, green sonar. The white cones off the missles are their onboard active radar seeker. If you have any questions understanding any of the things displyed, please ask. Note that this is a hobby analysis with publicly available data and tools, and not military research. Thanks for reading! #usnavy #HezbollahTerrorists #hezbullah #hezbollah #israel #IsraelUnderAttack #ukraine #russia #nato Naval News SubBrief Tyler Rogoway Status-6 (War & Military News) TheIntelFrog @CovertShores Raw Combat log output, starting with Hezbollah detecting CSG via RU Proxy: 13/10/2023 12:46:13 - [Hezbollah] New contact! Designated SKUNK #1070 - Detected by Resurs P1 [Sensors: Generic Satellite Visual Camera] at 177deg - 1149.3nm 13/10/2023 12:46:13 - [Hezbollah] New contact! Designated SKUNK #1071 - Detected by Resurs P1 [Sensors: Generic Satellite Visual Camera] at 177deg - 1149.3nm 13/10/2023 12:46:13 - [Hezbollah] New contact! Designated SKUNK #1072 - Detected by Resurs P1 [Sensors: Generic Satellite Visual Camera] at 177deg - 1149.3nm 13/10/2023 12:46:13 - [Hezbollah] New contact! Designated SKUNK #1073 - Detected by Resurs P1 [Sensors: Generic Satellite Visual Camera] at 177deg - 1145.4nm 13/10/2023 12:46:13 - [Hezbollah] New contact! Designated SKUNK #1074 - Detected by Resurs P1 [Sensors: Generic Satellite Visual Camera] at 177deg - 1153.3nm 13/10/2023 12:46:13 - [Hezbollah] New contact! Designated SKUNK #1075 - Detected by Resurs P1 [Sensors: Generic Satellite Visual Camera] at 177deg - 1148nm 13/10/2023 12:46:23 - [Hezbollah] Contact: SKUNK #1073 has been positively identified as: DDG 63 Carney [Arleigh Burke Flight I] - Determined as: Hostile (ID by: Resurs P1 [Sensor: Generic Satellite Visual Camera] at Estimated 1121 nm) 13/10/2023 12:46:23 - [Hezbollah] Contact: SKUNK #1071 has been positively identified as: DDG 116 Thomas Hudner [Arleigh Burke Flight IIA Technology Insertion] - Determined as: Hostile (ID by: Resurs P1 [Sensor: Generic Satellite Visual Camera] at Estimated 1125 nm) 13/10/2023 12:46:23 - [Hezbollah] Contact: SKUNK #1070 has been positively identified as: CVN 78 Gerald R. Ford - Determined as: Hostile (ID by: Resurs P1 [Sensor: Generic Satellite Visual Camera] at Estimated 1125 nm) 13/10/2023 12:46:23 - [Hezbollah] Contact: SKUNK #1072 has been positively identified as: DDG 61 Ramage [Arleigh Burke Flight I] - Determined as: Hostile (ID by: Resurs P1 [Sensor: Generic Satellite Visual Camera] at Estimated 1125 nm) 13/10/2023 12:46:23 - [Hezbollah] Contact: SKUNK #1074 has been positively identified as: DDG 80 Roosevelt [Arleigh Burke Flight IIA] - Determined as: Hostile (ID by: Resurs P1 [Sensor: Generic Satellite Visual Camera] at Estimated 1129 nm) 13/10/2023 12:46:23 - [Hezbollah] Contact: SKUNK #1075 has been positively identified as: CG 60 Normandy [Ticonderoga Baseline 3, VLS] - Determined as: Hostile (ID by: Resurs P1 [Sensor: Generic Satellite Visual Camera] at Estimated 1124 nm) 13/10/2023 12:47:23 - [USA] Contact: BOGEY #24 has been classified as: Ababil-3 UAV [Mod. Seeker 2D Copy] - Determined as: Unfriendly (Classification by: DDG 116 Thomas Hudner [Arleigh Burke Flight IIA Technology Insertion] [Sensor: AN/SPY-1D(V) MFR [ABM Mod]] [NCTR mode] at 56.9 nm) 13/10/2023 12:47:23 - [USA] Contact: BOGEY #26 has been classified as: Shahed-161 UAV - Determined as: Unfriendly (Classification by: DDG 116 Thomas Hudner [Arleigh Burke Flight IIA Technology Insertion] [Sensor: AN/SPY-1D(V) MFR [ABM Mod]] [NCTR mode] at 34.9 nm) 13/10/2023 12:47:52 - [USA] New contact! Designated VAMPIRE #3507 - Detected by E-3A Sentry [Sensors: AN/APY-2 RSIP] at 70deg - 95.2nm 13/10/2023 12:47:52 - [USA] New contact! Designated VAMPIRE #3508 - Detected by E-3A Sentry [Sensors: AN/APY-2 RSIP] at 69deg - 96.4nm 13/10/2023 12:47:52 - [USA] New contact! Designated VAMPIRE #3509 - Detected by E-3A Sentry [Sensors: AN/APY-2 RSIP] at 70deg - 95.6nm 13/10/2023 12:47:52 - [USA] New contact! Designated VAMPIRE #3510 - Detected by E-3A Sentry [Sensors: AN/APY-2 RSIP] at 69deg - 96.8nm 13/10/2023 12:47:52 - [USA] New contact! Designated VAMPIRE #3511 - Detected by E-3A Sentry [Sensors: AN/APY-2 RSIP] at 69deg - 96.1nm 13/10/2023 12:47:52 - [USA] New contact! Designated VAMPIRE #3512 - Detected by E-3A Sentry [Sensors: AN/APY-2 RSIP] at 69deg - 96.4nm 13/10/2023 12:47:52 - [USA] New contact! Designated VAMPIRE #3513 - Detected by E-3A Sentry [Sensors: AN/APY-2 RSIP] at 70deg - 97.1nm 13/10/2023 12:47:52 - [USA] New contact! Designated VAMPIRE #3514 - Detected by E-3A Sentry [Sensors: AN/APY-2 RSIP] at 69deg - 98nm 13/10/2023 12:47:52 - [USA] New contact! Designated VAMPIRE #3515 - Detected by E-3A Sentry [Sensors: AN/APY-2 RSIP] at 70deg - 97.2nm 13/10/2023 12:48:12 - [USA] New contact! Designated VAMPIRE #3576 - Detected by E-3A Sentry [Sensors: AN/APY-2 RSIP] at 68deg - 91nm 13/10/2023 12:48:12 - [USA] New contact! Designated VAMPIRE #3577 - Detected by E-3A Sentry [Sensors: AN/APY-2 RSIP] at 69deg - 89.9nm 13/10/2023 12:48:12 - [USA] New contact! Designated VAMPIRE #3578 - Detected by E-3A Sentry [Sensors: AN/APY-2 RSIP] at 69deg - 90.7nm 13/10/2023 12:48:13 - Side 'Hezbollah' is now considered HOSTILE to USA 13/10/2023 12:48:13 - [USA] Contact: Shahed-161 UAV #26 has been manually marked as hostile! 13/10/2023 12:48:20 - [USA] Contact: BOGEY #22 has been manually marked as hostile! 13/10/2023 12:48:55 - [Hezbollah] New contact! Designated SAM #1238 - Detected by Shahed-161 UAV [Sensors: Generic IRST] at 266deg - 10nm 13/10/2023 12:48:59 - [Hezbollah] New contact! Designated SAM #1243 - Detected by Shahed-161 UAV [Sensors: Generic IRST] at 266deg - 8.6nm 13/10/2023 12:49:00 - [Hezbollah] New contact! Designated SAM #1245 - Detected by Shahed-161 UAV [Sensors: Generic IRST] at 234deg - 13.3nm 13/10/2023 12:49:17 - Weapon: RIM-174A ERAM SM-6 Blk IA #40 is attacking Shahed-161 UAV with a base PH of 90%. PH adjusted for weapon speed: 36% (pure-aerodynamic attitude control). Intercept angle is 304 deg - hit probability adjusted to 25%.Final PH: 25%. Result: 30 - MISS 13/10/2023 12:49:17 - [Hezbollah] Hezbollah :Contact SAM #1238 has been lost. 13/10/2023 12:49:25 - [Hezbollah] New contact! Designated SAM #1271 - Detected by Shahed-161 UAV [Sensors: Generic IRST] at 248deg - 13.1nm 13/10/2023 12:49:34 - Weapon: RIM-174A ERAM SM-6 Blk IB #41 is attacking Ababil-3 UAV [Mod. Seeker 2D Copy] with a base PH of 90%. Intercept angle is 51 deg - hit probability adjusted to 65%.Final PH: 65%. Result: 12 - HIT 13/10/2023 12:49:34 - [Hezbollah] Ababil-3 UAV [Mod. Seeker 2D Copy] has suffered weapon damage: 89.9 DPs 13/10/2023 12:49:34 - [Hezbollah] Hezbollah :Contact SAM #1271 has been lost. 13/10/2023 12:49:34 - [Hezbollah] Ababil-3 UAV [Mod. Seeker 2D Copy] has been destroyed! 13/10/2023 12:49:34 - [USA] Contact Ababil-3 UAV [Mod. Seeker 2D Copy] #23 has been lost. 13/10/2023 12:49:39 - Weapon: RIM-174A ERAM SM-6 Blk IB #42 is attacking Ababil-3 UAV [Mod. Seeker 2D Copy] with a base PH of 90%. Intercept angle is 313 deg - hit probability adjusted to 66%.Final PH: 66%. Result: 11 - HIT 13/10/2023 12:49:39 - [Hezbollah] Ababil-3 UAV [Mod. Seeker 2D Copy] has suffered weapon damage: 89.9 DPs 13/10/2023 12:49:39 - [Hezbollah] Hezbollah :Contact SAM #1243 has been lost. 13/10/2023 12:49:39 - [Hezbollah] Ababil-3 UAV [Mod. Seeker 2D Copy] has been destroyed! 13/10/2023 12:49:39 - [USA] Contact Ababil-3 UAV [Mod. Seeker 2D Copy] #24 has been lost. 13/10/2023 12:49:43 - Weapon: RIM-174A ERAM SM-6 Blk IB #43 is attacking Shahed-161 UAV with a base PH of 90%. Intercept angle is 65 deg - hit probability adjusted to 57%.Final PH: 57%. Result: 11 - HIT 13/10/2023 12:49:43 - [Hezbollah] Shahed-161 UAV has suffered weapon damage: 89.9 DPs 13/10/2023 12:49:43 - [Hezbollah] Hezbollah :Contact SAM #1245 has been lost. 13/10/2023 12:49:43 - [Hezbollah] Shahed-161 UAV has been destroyed! 13/10/2023 12:49:43 - [USA] Contact Shahed-161 UAV #25 has been lost. 13/10/2023 12:49:54 - [Hezbollah] New contact! Designated SAM #1301 - Detected by Shahed-161 UAV [Sensors: Generic IRST] at 258deg - 10.5nm 13/10/2023 12:50:10 - Weapon: RIM-174A ERAM SM-6 Blk IA #44 is attacking Shahed-161 UAV with a base PH of 90%. PH adjusted for weapon speed: 83% (pure-aerodynamic attitude control). Target signature modifier: -5% (Director [Active Radar Seeker] has tech-gen: Late 2010s). Intercept angle is 316 deg - hit probability adjusted to 59%.Final PH: 59%. Result: 42 - HIT 13/10/2023 12:50:10 - [Hezbollah] Shahed-161 UAV has suffered weapon damage: 89 DPs 13/10/2023 12:50:10 - [Hezbollah] Hezbollah :Contact SAM #1301 has been lost. 13/10/2023 12:50:10 - [Hezbollah] Shahed-161 UAV has been destroyed! 13/10/2023 12:50:10 - [USA] Contact Shahed-161 UAV #26 has been lost. 13/10/2023 12:51:58 - [USA] Contact: VAMPIRE #3507 has been type-classified as: GuidedWeapon (Classification by: DDG 116 Thomas Hudner [Arleigh Burke Flight IIA Technology Insertion] [Sensor: Mk46 Mod 1 [CCD]] at 14 nm) 13/10/2023 12:51:59 - [USA] Contact: VAMPIRE #3508 has been type-classified as: GuidedWeapon (Classification by: DDG 116 Thomas Hudner [Arleigh Burke Flight IIA Technology Insertion] [Sensor: Mk46 Mod 1 [CCD]] at 13.9 nm) 13/10/2023 12:51:59 - [USA] Contact: VAMPIRE #3509 has been type-classified as: GuidedWeapon (Classification by: DDG 116 Thomas Hudner [Arleigh Burke Flight IIA Technology Insertion] [Sensor: Mk46 Mod 1 [CCD]] at 14 nm) 13/10/2023 12:51:59 - [USA] Contact: VAMPIRE #3511 has been type-classified as: GuidedWeapon (Classification by: DDG 116 Thomas Hudner [Arleigh Burke Flight IIA Technology Insertion] [Sensor: Mk46 Mod 1 [CCD]] at 14 nm) 13/10/2023 12:52:00 - [USA] Contact: VAMPIRE #3510 has been type-classified as: GuidedWeapon (Classification by: DDG 116 Thomas Hudner [Arleigh Burke Flight IIA Technology Insertion] [Sensor: Mk46 Mod 1 [CCD]] at 13.9 nm) 13/10/2023 12:52:00 - [USA] Contact: VAMPIRE #3512 has been type-classified as: GuidedWeapon (Classification by: DDG 116 Thomas Hudner [Arleigh Burke Flight IIA Technology Insertion] [Sensor: Mk46 Mod 1 [CCD]] at 14 nm) 13/10/2023 12:52:04 - [USA] Contact: VAMPIRE #3513 has been type-classified as: GuidedWeapon (Classification by: DDG 116 Thomas Hudner [Arleigh Burke Flight IIA Technology Insertion] [Sensor: Mk46 Mod 1 [CCD]] at 14 nm) 13/10/2023 12:52:04 - [USA] Contact: VAMPIRE #3577 has been type-classified as: GuidedWeapon (Classification by: DDG 116 Thomas Hudner [Arleigh Burke Flight IIA Technology Insertion] [Sensor: Mk46 Mod 1 [CCD]] at 14 nm) 13/10/2023 12:52:05 - [USA] Contact: VAMPIRE #3514 has been type-classified as: GuidedWeapon (Classification by: DDG 116 Thomas Hudner [Arleigh Burke Flight IIA Technology Insertion] [Sensor: Mk46 Mod 1 [CCD]] at 13.9 nm) 13/10/2023 12:52:05 - [USA] Contact: VAMPIRE #3515 has been type-classified as: GuidedWeapon (Classification by: DDG 116 Thomas Hudner [Arleigh Burke Flight IIA Technology Insertion] [Sensor: Mk46 Mod 1 [CCD]] at 14 nm) 13/10/2023 12:52:06 - [USA] Contact: VAMPIRE #3576 has been type-classified as: GuidedWeapon (Classification by: DDG 116 Thomas Hudner [Arleigh Burke Flight IIA Technology Insertion] [Sensor: Mk46 Mod 1 [CCD]] at 13.9 nm) 13/10/2023 12:52:06 - [USA] Contact: VAMPIRE #3578 has been type-classified as: GuidedWeapon (Classification by: DDG 116 Thomas Hudner [Arleigh Burke Flight IIA Technology Insertion] [Sensor: Mk46 Mod 1 [CCD]] at 14 nm) 13/10/2023 12:52:08 - Weapon: RIM-162D ESSM #45 is attacking SSC-5 Stooge [P-800 Yakhont] #28 with a base PH of 90%. Target speed modifier: -10%. Intercept angle is 357 deg - hit probability adjusted to 79%.Final PH: 79%. Result: 34 - HIT 13/10/2023 12:52:08 - [USA] Contact GuidedWeapon #3507 has been lost. 13/10/2023 12:52:09 - Weapon: RIM-162D ESSM #46 is attacking SSC-5 Stooge [P-800 Yakhont] #29 with a base PH of 90%. Target speed modifier: -10%. Intercept angle is 358 deg - hit probability adjusted to 79%.Final PH: 79%. Result: 31 - HIT 13/10/2023 12:52:09 - [USA] Contact GuidedWeapon #3508 has been lost. 13/10/2023 12:52:11 - Weapon: RIM-162D ESSM #49 is attacking SSC-5 Stooge [P-800 Yakhont] #32 with a base PH of 90%. Target speed modifier: -10%. Intercept angle is 358 deg - hit probability adjusted to 79%.Final PH: 79%. Result: 36 - HIT 13/10/2023 12:52:11 - [USA] Contact GuidedWeapon #3511 has been lost. 13/10/2023 12:52:11 - Weapon: RIM-162A ESSM #52 is attacking SSC-5 Stooge [P-800 Yakhont] #31 with a base PH of 90%. Target speed modifier: -10%. Intercept angle is 355 deg - hit probability adjusted to 78%.Final PH: 78%. Result: 9 - HIT 13/10/2023 12:52:11 - [USA] Weapon: RIM-162A ESSM #57 has been redirected to new target: GuidedWeapon #3515 13/10/2023 12:52:11 - [USA] Contact GuidedWeapon #3510 has been lost. 13/10/2023 12:52:12 - Weapon: RIM-162D ESSM #50 is attacking SSC-5 Stooge [P-800 Yakhont] #30 with a base PH of 90%. Target speed modifier: -10%. Intercept angle is 356 deg - hit probability adjusted to 78%.Final PH: 78%. Result: 25 - HIT 13/10/2023 12:52:12 - [USA] Contact GuidedWeapon #3509 has been lost. 13/10/2023 12:52:12 - Weapon: RIM-162A ESSM #55 is attacking SSC-5 Stooge [P-800 Yakhont] #33 with a base PH of 90%. Target speed modifier: -10%. Intercept angle is 355 deg - hit probability adjusted to 78%.Final PH: 78%. Result: 20 - HIT 13/10/2023 12:52:12 - [USA] Weapon: RIM-162A ESSM #59 has been redirected to new target: GuidedWeapon #3576 13/10/2023 12:52:12 - [USA] Contact GuidedWeapon #3512 has been lost. 13/10/2023 12:52:13 - [USA] Weapon: RIM-162D ESSM #47 is running blind for more than 5 sec... self-destructing. 13/10/2023 12:52:14 - [USA] Weapon: RIM-162D ESSM #48 is running blind for more than 5 sec... self-destructing. 13/10/2023 12:52:15 - Weapon: RIM-162A ESSM #57 is attacking SSC-5 Stooge [P-800 Yakhont] #36 with a base PH of 90%. Target speed modifier: -10%. Intercept angle is 0 deg - hit probability adjusted to 80%.Final PH: 80%. Result: 71 - HIT 13/10/2023 12:52:15 - [USA] Contact GuidedWeapon #3515 has been lost. 13/10/2023 12:52:16 - Weapon: RIM-162A ESSM #60 is attacking SSC-5 Stooge [P-800 Yakhont] #34 with a base PH of 90%. Target speed modifier: -10%. Intercept angle is 360 deg - hit probability adjusted to 80%.Final PH: 80%. Result: 49 - HIT 13/10/2023 12:52:16 - [USA] Weapon: RIM-162A ESSM #65 has no eligible alternative target to be redirected to... 13/10/2023 12:52:16 - [USA] Contact GuidedWeapon #3513 has been lost. 13/10/2023 12:52:16 - [USA] Weapon: RIM-162D ESSM #51 is running blind for more than 5 sec... self-destructing. 13/10/2023 12:52:16 - [USA] Weapon: RIM-162D ESSM #54 is running blind for more than 5 sec... self-destructing. 13/10/2023 12:52:16 - [USA] Weapon: RIM-162D ESSM #58 is running blind for more than 5 sec... self-destructing. 13/10/2023 12:52:16 - Weapon: RIM-162A ESSM #59 is attacking SSC-5 Stooge [P-800 Yakhont] #38 with a base PH of 90%. Target speed modifier: -10%. Intercept angle is 357 deg - hit probability adjusted to 78%.Final PH: 78%. Result: 75 - HIT 13/10/2023 12:52:16 - [USA] Contact GuidedWeapon #3576 has been lost. 13/10/2023 12:52:16 - Weapon: RIM-162A ESSM #63 is attacking SSC-5 Stooge [P-800 Yakhont] #38 with a base PH of 90%. Target speed modifier: -10%. Intercept angle is 359 deg - hit probability adjusted to 79%.Final PH: 79%. Result: 57 - HIT 13/10/2023 12:52:16 - [USA] Weapon: RIM-162A ESSM #70 has been redirected to new target: GuidedWeapon #3514 13/10/2023 12:52:16 - [USA] Contact GuidedWeapon #3577 has been lost. 13/10/2023 12:52:17 - [USA] Weapon: RIM-162D ESSM #53 is running blind for more than 5 sec... self-destructing. 13/10/2023 12:52:17 - [USA] Weapon: RIM-162A ESSM #65 has no eligible alternative target to be redirected to... 13/10/2023 12:52:17 - [USA] Weapon: RIM-162D ESSM #56 is running blind for more than 5 sec... self-destructing. 13/10/2023 12:52:17 - [USA] Weapon: RIM-162D ESSM #61 is running blind for more than 5 sec... self-destructing. 13/10/2023 12:52:18 - Weapon: RIM-162A ESSM #70 is attacking SSC-5 Stooge [P-800 Yakhont] #35 with a base PH of 90%. Target speed modifier: -10%. Intercept angle is 358 deg - hit probability adjusted to 79%.Final PH: 79%. Result: 63 - HIT 13/10/2023 12:52:18 - [USA] Contact GuidedWeapon #3514 has been lost. 13/10/2023 12:52:18 - Weapon: RIM-174A ERAM SM-6 Blk IA #73 is attacking SSC-5 Stooge [P-800 Yakhont] #39 with a base PH of 90%. Intercept angle is 355 deg - hit probability adjusted to 88%.Final PH: 88%. Result: 34 - HIT 13/10/2023 12:52:18 - [USA] Contact GuidedWeapon #3578 has been lost.

C Schmitz

47,464 views • 2 years ago

Just in $AMD Anush "Speed is the moat"|ROCm🎙️ In the race to define the future of AI, what's the one advantage that truly lasts? It's not proprietary tech, argues Anush Elangovan Elangovan, VP of AI Software at AMD , but the sustainable speed of innovation. He explains why AMD is rejecting the "walled garden" model for its open source ROCm stack, betting that an open community flywheel is the key to victory. Listen to understand how this open strategy is designed to out-innovate closed systems by empowering developers to solve everything from frontier-model challenges to the mundane, everyday problems that define the "last mile" of AI. AMD ROCm Software: Part 1 Transcript [00:00:00] Andrew Zigler: Joining me is Anush Elangovan, VP of AI software at AMD. And when people talk about AI compute, the conversation often stops at hardware specs, but it's more than just physical chips that win the game. It's also the software ecosystems supporting them. [00:00:18] Andrew Zigler: The prevailing strategy in the industry has been to build something like a walled garden. You know, something closed, proprietary locks, developers in. But AMD is betting on an entirely different play, open source acceleration, and with rock, their open source AI software stack. AMD is building not just hardware parity, but an innovation flywheel that's powered by the community with interoperability and the freedom to scale without all of that pesky lockin. [00:00:48] Andrew Zigler: And in this world, speed is your moat and how fast you can innovate while your platform remains open, flexible, and standardize across all of its applications. That's what we're gonna explore [00:01:00] today. So Anush, I'm really excited to have you here. Welcome to Dev Interrupted. [00:01:04] Anush Elangovan: Thanks for having me. Uh, super excited to chat about it. [00:01:07] Andrew Zigler: Amazing. Well, let's go ahead and dive right in with kind of what I laid it out with in the beginning, the idea of the moat and it being about speed. I wanna unpack that a bit because that came from you when you and I first spoke. And I, and I want to know, you know, how do you define speed inside of AMD beyond just things like hardware, benchmarks. [00:01:27] Anush Elangovan: Yeah, that's a very good question. So when we typically talk about speed, everyone's like, Hey, hardware benchmark specs, right? Like, uh, memory bandwidth or, or flops. And that is one important part of it, uh, AMD does very well. With that, we do have, a, a very good history of executing on that axis. [00:01:47] Anush Elangovan: But when I say speed is the moat, it is about, uh, how we prepare, how we build the muscle to run the race for a long time and run it fast. And it is [00:02:00] not about a single point in time that you've, you've beat some you know, benchmark and, and you declare victory. It's about building the ability to consistently develop and deliver. [00:02:13] Anush Elangovan: Both hardware and software innovation at scale and do it fast, right? Like, you know, we we're increasingly getting to a point where models come out and they're, uh, you know, a year or two ago it was like, Hey, they work on AMD on day zero, which is great, but now they are performing on AMD the day it releases, right? [00:02:32] Anush Elangovan: So, what does it take to Prefetch where the industry is going? Be prepared to intercept. At that point is what you know, I, I refer to as you know, the, the speed factor in, in creating this mode, right? And the mode is just shed all things that hold you back and run as fast as you can. [00:02:53] Anush Elangovan: Uh, because the pace of innovation that is, uh, being seen in, in AI [00:03:00] industries is just. Amazing. Right? And it's like, it's transformational at at how you generate electricity. It's transformational as at how you build data centers. It's transformational at how you deploy compute, networking. It's transformational at what kind of use cases you, you know, uh, use AI for. [00:03:17] Anush Elangovan: Uh, and for that, you need to be prepared to, see what comes tomorrow and be prepared to run the race tomorrow. [00:03:23] Andrew Zigler: Yeah, it's a really great perspective because it highlights that it's not just like a checkpoint that you run through. I like how you called out, like it's not just hitting that benchmark or being the best in class at that moment, in that snapshot, it's about having a. The throughput and about having that dedication to the idea and continuing to deliver on it. [00:03:43] Andrew Zigler: It's not just crossing the threshold, but it's also being the engine. And that's what, that's what protects a business. That is the moat, because the moat is that innovation layer, the faster and more, uh, future forward. That you can work and think, [00:04:00] you know, the better. Uh, we, we talk a lot about like future forward work styles. [00:04:04] Andrew Zigler: Like what are the things I could be doing right now today that are gonna be like, way more useful tomorrow? Let, let's abandon those, workflows that are older and that kind of like, that translates into. An advantage when you work that way. You know, what kind of things have you learned working with, uh, like across all spectrums of people who would use ROCm, right? [00:04:23] Andrew Zigler: You have like the developers, but then you also have the enterprises and you have this large span of adoptees, right? So what is the, what does that look like that you learn? [00:04:32] Anush Elangovan: Yeah, so, so the way I look at it is there are gonna be pockets of different, uh, you know, cadences, right? Like, so people who are deploying in enterprises, for example, right? The validation and how long it takes for them to deploy an LLM that's secure. It's, with guardrails, et cetera, maybe longer. [00:04:52] Anush Elangovan: but you still have to go through the process and you have to be prepared to like, walk that walk to deploy an enterprises. That doesn't mean it's [00:05:00] not fast, that's as fast as you can do for that industry, right? And if you are deploying AI in healthcare, right, it's, it's got its own, uh, cycle. [00:05:07] Anush Elangovan: but in each one of these, you want to see how, like, go down to the essence of what is it that you actually have to do. And, you know, I, I, I like how you framed it. It's like it's, you shed your prior assumptions of how things are done, right. And, and you kind of build up from a, uh, first principles, uh, approach to say, this is how I could use AI to unlock, whatever I'm doing. [00:05:33] Anush Elangovan: And, and, some of it, you know, it's good to really step back and look at. Just question every part of it, right? Like right now you're getting chat GPT and, Gemini competing for like, math, olympiads and, and, uh, college, uh, reasoning, uh, tests. Right? And, and those are like that, that is amazing and increasingly like complex tasks that they're trying to do. [00:05:58] Anush Elangovan: But there may also be like. [00:06:00] More mundane things that AI could, could get applied to. Right? And, and so when we think about shedding old ways, you wanna shed it not just in like the tip of the spear. It's like, you know, I'm gonna see what's the frontier model. It's also, it could be something as simple as. [00:06:18] Anush Elangovan: How do you choose a, a movie, uh, you know, like a recommendation system, right? Or, or, uh, an automated, uh, flight, uh, rebooking system. So the moment, you know, your flight is late, uh, right now it's a notification, right? It's like, oh, you got a text message saying your flight's late. And I got that like three times this week. [00:06:38] Anush Elangovan: But anyway, uh, and, and, and, and, I was just like, okay, so if I were to rethink this. All this MCPs that we have that should be hooked up into an MCP that says, your flight's delayed. Here are your options. If you want, you know, these are the paid options. Yeah. Here are the free options. This will get you back into your you know, Toronto airport [00:07:00] tonight. [00:07:00] Anush Elangovan: Or if you stay, here's a hotel plus this, plus this, plus. It's just like, go ahead is all I should say. Versus now I'm like, okay, can someone, you know, can I call a travel agent? Can I do this? Can I go online and log into And you know, so we gotta fundamentally rethink even those like small, nuances of, things that we do that can be automated out and AI is really, really good at doing something like this, right? Maybe I just explained an AI startup idea right now. Somebody should just start that. [00:07:29] Andrew Zigler: I think you did. Yeah, you definitely did. Someone, one of our listeners is definitely going to lift that off of you. I, I, I, you know, I hate being on the receiving end of those. You feel a little helpless and then you have to like, follow the whole flow. So I know what you mean. Like I, I like how you called out that the build and this like. [00:07:45] Andrew Zigler: Where speed is your moat and the innovation layer is protecting you, is what makes you better than your competitors. How you scale that and you bring that to market. So by understanding the problems that you're solving, uh, throwing away those older assumptions, but also [00:08:00] recognizing that like. We're building every single day, new things and new ways of using stuff that we're still figuring out the implications of. [00:08:08] Andrew Zigler: And so when you have a lot of velocity and you're introducing a lot of new ideas, and maybe you have that workflow now that automatically rebook your flight off of your late flight text message, and uh, I know I would certainly use it, but you know, what kind of philosophies guide the way that y'all think about building this ecosystem to manage that stability while letting folks. [00:08:29] Andrew Zigler: Play with the speed and the assumptions and the airplane re bookings. [00:08:34] Anush Elangovan: so, so I think, you know, we need to peel one layer down, right? and the philosophy is, Hey, we, we just discovered electricity, right? And you know what we're gonna do? We are gonna make motors, uh, or dynamos, right? Like engines. Uh, sure. We don't know if it's gonna be a Ferrari that you're gonna make, or it's a a a a dump truck. [00:08:57] Anush Elangovan: That's good for doing this. But let's [00:09:00] let, which is also required, right? You need a dump truck. You need a garbage truck. And, [00:09:04] Andrew Zigler: Yeah. You need the [00:09:04] Anush Elangovan: course you need, uh, a Ferrari for a midlife crisis, right? So, [00:09:09] Andrew Zigler: precisely. [00:09:10] Anush Elangovan: But, but my, uh, point is what do we build next? And, uh, and this is what I meant by like, okay, let's, let's take those baby steps to build the. [00:09:20] Anush Elangovan: Infrastructure that's required that we know we'll have to use, right? So, so if I just discovered electricity, okay, great. Now one, how do I save this electricity and how do I use it? So there's battery technology, so you need to do something like that, right? Like so. But then you also want to make it into an actionable thing. [00:09:37] Anush Elangovan: You want to make it for like automobiles, or you wanna use it for, you know, powering, uh, entire cities. So it is that transformational. So, uh, AI is that transformational. So, if you distill down, it'll, it'll come down to how do we think about, what we can do with this this fundamental technology that, We may not be aware of what it [00:10:00] is gonna unlock next, but at least you know the next step is clear, right? It's like a dense fog, you know, it's gonna be like, it, it's the right path. You see the light, but it's kind of like out there and, and the steps you're taking are concrete and you're like, okay, this is good. [00:10:16] Anush Elangovan: I, this is better than where I was or where we were. So we are moving forward. So you can build with the. Intuition from what you see in the short term and a tactical view, but towards what you think the future is gonna be. [00:10:28] Andrew Zigler: Right. You almost like we're all in this like fog of war, right? And like you said, you're reaching out and you're trying to step through it. You could think of it too, as like you're in the dark and your hands are up in front of you and you know that. You're, you're not gonna run your face into a wall because your hands are out in front of you, but you're not gonna maybe do much better than that. [00:10:45] Andrew Zigler: So that's kind of like, I think the eco, the, the industry, the world that we find ourselves in, uh, and we all have to, then this becomes the power of an ecosystem, of a group of people working together to create that layer of, [00:11:00] uh, of establishing the [00:11:01] Anush Elangovan: exactly. And I, I, I just, instead of, you know, saying fog of war I describe it as like, you're in this. Beautiful valley with like a morning, uh, fog that's in. You can smell the flowers. You, you hear the birds. You are like, okay, it's, we are in like, uh, utopian paradise and yes, I just need to like, continue the walk, right? [00:11:24] Anush Elangovan: and then move forward with that, conviction that you're in the right spot. [00:11:27] Andrew Zigler: Yeah. So let's talk about that ecosystem world. This nice, I love how you describe it, this grassy side of a hill in the morning that's covered in some mist and maybe we can't see 30 feet in one direction, but it sure is a beautiful hill and it smells nice. And so we're all here. And why is, in that world, why is. [00:11:44] Andrew Zigler: You know, open source, their strategic advantage that y'all are going for in the AI hardware market. And, and then how does like ROCm turn that into wins for people within that ecosystem? [00:11:56] Anush Elangovan: you know, the, the way we look at it is this, is kind of like how I view [00:12:00] AI and the ecosystem, right? But, but it is for everyone to enjoy. Uh, and so we do want to make sure that. You know, it is, uh, beneficial for everyone. [00:12:09] Anush Elangovan: The ecosystem can come in and, and innovate. It's an open innovation engine. and uh, it is very different from, you know, having a walled garden with, Hey, only I know how to do this and I'm gonna do it and throw it over the fence and you can use it or keep walking, right? So we'd like to be good citizens that way, but also. [00:12:30] Anush Elangovan: Uh, it is self-fulfilling in a way, right? Like it, the, the pace at which we innovate with open source is unmatched. Like, you know, our serving engines are like VLLM and, and sg l. Those things, uh, those frameworks are like super, super aggressive in terms of how fast they come out with features and how fast they can you know, get performant models out. [00:12:52] Anush Elangovan: And that compared with what, uh, you'd get from, you know, the likes of like T-R-T-L-L-M or something is always lagging, right? Because you [00:13:00] just can't keep up with you know, 200 commits a week just on one particular model to get that model really performant [00:13:06] Andrew Zigler: And, and, and in that world where, you know, everyone can enjoy the winds of this, what kind of customer stories or innovation stories have really stood out to you and excite you about building and creating this place for developers? [00:13:19] Anush Elangovan: Yeah. So I think the parts that are super exciting for me are when when we get to see a customer that is first skeptical. Then they start a little like, okay, fine, we'll give you a chance. Uh, we do a simple, uh, POC and then they're like, huh, this seems to work. Yeah, we told you it works. [00:13:42] Anush Elangovan: You don't have to change one line of code. Really? Yes, no need to change one line of code. Okay, let's try a production workload. So then they try it. Oh, you're more performant than the competition. Yes. We're more performant than, than the competition. So how much does it cost? And we're like, oh, it's your TCO is better with, uh, [00:14:00] AMD. [00:14:00] Anush Elangovan: So again, they're like, wow, okay, good. So now how do we deploy at scale? And then we go deploy it at scale. And when they give a thumbs up on that and they say, this is good, right? That's when you know, you, you see it go full circle from like, oh, we, we've never heard about AMD to like actually deploy to tens of thousands of GPUs In the order of a few months, right? It, it, it really is fascinating to see and very exciting and invigorating to [00:14:28] Andrew Zigler: Yeah. At like a great exposure to a lot of interesting problems. And, and then people using the infrastructure, the, the technology available to solve those problems. Really specific problems by the way, that's often why they're bringing their data and AI to it, uh, is because it is really specific and important for them. [00:14:45] Andrew Zigler: And there's a, a lot I think that other engineering orgs can learn and even emulate from AMD's success and, and having this open source ecosystem and it causing this acceleration within. You [00:15:00] know, uh, customers and enterprises that use and adopt the tools and, and, and that creates an advantage. And that goes back to why we're talking and like the real thesis of our conversation today. [00:15:10] Andrew Zigler: So how do you think engineering leaders that are listening to this and obviously tapping into this great success AMD has from an open source flywheel, how do you think other, other folks building in the same space can foster that open, first, that open source oriented culture in order to, you know, accelerate their innovation goals? [00:15:29] Anush Elangovan: Yeah, that's a very good question. So the startup that um, was acquired by AMD we, we built, I mean, we started off doing iot stuff and you know, smart ring and all that, right? But in the, the end of like, uh, and not the end, the last six years of the company was building ML compilers. [00:15:47] Anush Elangovan: And ml, ML compilers are like super, uh, complicated, sophisticated, advanced algorithms, dah, dah, dah. but it was all open source, right? So our VCs were like, wait, what do you mean your core [00:16:00] IP is open source? And um, the speed is the moat applied even then, right? It was just like, yes, if you have an idea that. [00:16:08] Anush Elangovan: Because someone saw this idea that you are, they're gonna be able to catch up, then you probably have the wrong idea anyway. But if they are, you know, you execute and they're gonna catch up, that you should assume they're gonna catch up. Right? So you gotta move forward. So keeping it open source is super important. [00:16:25] Anush Elangovan: But also to your question on like, you know, the learnings from an AMD standpoint, right? If there are, hard problems, I'd say dig in and work through it, right? Like there's no way but through it, right? That should be the simple mentality. And more, uh, frequently than not. you'll see that you'll just make it through in a, in, in good form. [00:16:52] Anush Elangovan: But if you doubt it and you're like, oh, I don't know if I should commit, if I'm, I, you know, what should just commit to do the right thing [00:17:00] every step, right? Every step, and just keep taking one step in front of the other. And in no time you'll see that you'll be running. Right. And, and yes, the first few steps will be like, yeah, everyone's complaining about your software quality. [00:17:15] Anush Elangovan: Everyone's complaining about this and that, and it doesn't work. And, and a few steps in, you know, you get, you get the hang of all the complaints that are coming in. You get the feedback loop. You're like, okay, what, what are you prioritizing again? One step in front of the other, right? You just keep knocking that out and then you get to a point where you're, it just becomes second nature, right? To do the, to do the right thing. And, and then yes, if someone gives you two options, you'll be like, fine. This is, uh, you know, there's always the resource trade off. There's always a human capital trade off, but what's the right thing to do? of course, I, I'm pragmatic about what we choose, but, but if the right thing for your long-term success is dig in, go first, principles, make it [00:18:00] happen. [00:18:00] Anush Elangovan: Well. Then just go for that. There's, there is no shortcut to [00:18:04] Andrew Zigler: acknowledging, you know, how it aligns with your mission, your core company goals, and what you're looking to achieve. And, and I, I love how you rightfully called out that in the open source world and you know, you have your technology that you've built, what you think is your moat upon, right? [00:18:22] Andrew Zigler: It's your code and, and to open source that, or to just make it where anyone could peer in is, you know. Scary in one regard, but two, it just kind of feels like you're handing away your throne room in some kind of sense, a very direct feeling sense. But the ultimately, you were really right to call out, and this is something I think about all the time, that the real power there is still the speed This the speed. [00:18:42] Andrew Zigler: That was the moat at the beginning of our conversation. It's the speed in combination with your. Very specific domain understanding of what you're building and what you're creating, and your new role as the steward of that world and how people plug into it, which [00:19:00] has frankly, a lot more influence and power than lording over a closed. [00:19:04] Andrew Zigler: You know, repository or an ecosystem, and like you said, like throwing things over the wall. Sure. There, there might be people always on the other side of that wall, but you're not gonna have a great connection with them. You're not gonna be able to really clearly understand them. I, I like your metaphor of the side of the field of the mountain a lot more. [00:19:23] Andrew Zigler: But, but in the, in this world, you know, where. That speed is, is the power and, and open source is just one way that you can harness that speed to get really far ahead and to innovate. , There's other parts of this equation that you can be experimenting with too, and I'd love to pick your brain about them as a software leader and, and, and one of them is about looking forward and kind of understanding that future that we're all building towards and beyond today's models and hardware. [00:19:48] Andrew Zigler: You know, what do you see as the next major bottleneck or opportunity in the AI compute space? As, as you know, enterprises and folks start to get a little more mature about what's available to [00:20:00] them. [00:20:00] Anush Elangovan: Yeah, I think, the bottleneck and opportunity is, uh, what I'd call, call walking the last mile of ai. Right. Uh, and like I I, I gave you an example, uh, previously, but, but it's similar to that. It's like there are cases where Humans have so many, uh, things to do in your day. You know, like the, if we sit down and actually had a customer focus like, okay, these customers lives, I'm gonna save four hours of this customer's life. And if you actually sit down and look at all of that, it'll be. Easily automatable, easily you know, uh, applicable, uh, for ai, right? [00:20:39] Anush Elangovan: Like, but then making it happen is gonna take a little bit, right? It's like maybe it's, uh, paying your utility bill, right? Or something like that, right? Or, or, your healthcare explanation of benefits. Uh, like, I'm sure you get an explanation of benefits, and I'm like, I, I don't even know what that thing is. [00:20:55] Anush Elangovan: It's just like EOB and like. [00:20:57] Andrew Zigler: it's a big, a big old PDF. Yeah, [00:21:00] exactly. [00:21:01] Anush Elangovan: Like, like, I'm like great straight to the, uh, shredder, right? And but that could be, you know, automated with the ai, right? It, it, it'd be like, Hey, the summary of this thing is you went and visited this day. Everything is okay. Everything is paid for, so don't worry, it's not a bill. [00:21:17] Anush Elangovan: That again, the same, uh, thing, but the sense of what that information overload is could be. Digested by ai, uh, accumulated over time and retrieved when you need it. Like, I don't, I actually don't even need to know this EOB right now, unless of course, whenever I need to know it, that maybe, you know, like for some benefits I need to figure out what do, what did I do over the past year and how do I apply it? Source:

Just in $AMD Anush "Speed is the moat"|ROCm🎙️ In the race to define the future of AI, what's the one advantage that truly lasts? It's not proprietary tech, argues Anush Elangovan Elangovan, VP of AI Software at AMD , but the sustainable speed of innovation. He explains why AMD is rejecting the "walled garden" model for its open source ROCm stack, betting that an open community flywheel is the key to victory. Listen to understand how this open strategy is designed to out-innovate closed systems by empowering developers to solve everything from frontier-model challenges to the mundane, everyday problems that define the "last mile" of AI. AMD ROCm Software: Part 1 Transcript [00:00:00] Andrew Zigler: Joining me is Anush Elangovan, VP of AI software at AMD. And when people talk about AI compute, the conversation often stops at hardware specs, but it's more than just physical chips that win the game. It's also the software ecosystems supporting them. [00:00:18] Andrew Zigler: The prevailing strategy in the industry has been to build something like a walled garden. You know, something closed, proprietary locks, developers in. But AMD is betting on an entirely different play, open source acceleration, and with rock, their open source AI software stack. AMD is building not just hardware parity, but an innovation flywheel that's powered by the community with interoperability and the freedom to scale without all of that pesky lockin. [00:00:48] Andrew Zigler: And in this world, speed is your moat and how fast you can innovate while your platform remains open, flexible, and standardize across all of its applications. That's what we're gonna explore [00:01:00] today. So Anush, I'm really excited to have you here. Welcome to Dev Interrupted. [00:01:04] Anush Elangovan: Thanks for having me. Uh, super excited to chat about it. [00:01:07] Andrew Zigler: Amazing. Well, let's go ahead and dive right in with kind of what I laid it out with in the beginning, the idea of the moat and it being about speed. I wanna unpack that a bit because that came from you when you and I first spoke. And I, and I want to know, you know, how do you define speed inside of AMD beyond just things like hardware, benchmarks. [00:01:27] Anush Elangovan: Yeah, that's a very good question. So when we typically talk about speed, everyone's like, Hey, hardware benchmark specs, right? Like, uh, memory bandwidth or, or flops. And that is one important part of it, uh, AMD does very well. With that, we do have, a, a very good history of executing on that axis. [00:01:47] Anush Elangovan: But when I say speed is the moat, it is about, uh, how we prepare, how we build the muscle to run the race for a long time and run it fast. And it is [00:02:00] not about a single point in time that you've, you've beat some you know, benchmark and, and you declare victory. It's about building the ability to consistently develop and deliver. [00:02:13] Anush Elangovan: Both hardware and software innovation at scale and do it fast, right? Like, you know, we we're increasingly getting to a point where models come out and they're, uh, you know, a year or two ago it was like, Hey, they work on AMD on day zero, which is great, but now they are performing on AMD the day it releases, right? [00:02:32] Anush Elangovan: So, what does it take to Prefetch where the industry is going? Be prepared to intercept. At that point is what you know, I, I refer to as you know, the, the speed factor in, in creating this mode, right? And the mode is just shed all things that hold you back and run as fast as you can. [00:02:53] Anush Elangovan: Uh, because the pace of innovation that is, uh, being seen in, in AI [00:03:00] industries is just. Amazing. Right? And it's like, it's transformational at at how you generate electricity. It's transformational as at how you build data centers. It's transformational at how you deploy compute, networking. It's transformational at what kind of use cases you, you know, uh, use AI for. [00:03:17] Anush Elangovan: Uh, and for that, you need to be prepared to, see what comes tomorrow and be prepared to run the race tomorrow. [00:03:23] Andrew Zigler: Yeah, it's a really great perspective because it highlights that it's not just like a checkpoint that you run through. I like how you called out, like it's not just hitting that benchmark or being the best in class at that moment, in that snapshot, it's about having a. The throughput and about having that dedication to the idea and continuing to deliver on it. [00:03:43] Andrew Zigler: It's not just crossing the threshold, but it's also being the engine. And that's what, that's what protects a business. That is the moat, because the moat is that innovation layer, the faster and more, uh, future forward. That you can work and think, [00:04:00] you know, the better. Uh, we, we talk a lot about like future forward work styles. [00:04:04] Andrew Zigler: Like what are the things I could be doing right now today that are gonna be like, way more useful tomorrow? Let, let's abandon those, workflows that are older and that kind of like, that translates into. An advantage when you work that way. You know, what kind of things have you learned working with, uh, like across all spectrums of people who would use ROCm, right? [00:04:23] Andrew Zigler: You have like the developers, but then you also have the enterprises and you have this large span of adoptees, right? So what is the, what does that look like that you learn? [00:04:32] Anush Elangovan: Yeah, so, so the way I look at it is there are gonna be pockets of different, uh, you know, cadences, right? Like, so people who are deploying in enterprises, for example, right? The validation and how long it takes for them to deploy an LLM that's secure. It's, with guardrails, et cetera, maybe longer. [00:04:52] Anush Elangovan: but you still have to go through the process and you have to be prepared to like, walk that walk to deploy an enterprises. That doesn't mean it's [00:05:00] not fast, that's as fast as you can do for that industry, right? And if you are deploying AI in healthcare, right, it's, it's got its own, uh, cycle. [00:05:07] Anush Elangovan: but in each one of these, you want to see how, like, go down to the essence of what is it that you actually have to do. And, you know, I, I, I like how you framed it. It's like it's, you shed your prior assumptions of how things are done, right. And, and you kind of build up from a, uh, first principles, uh, approach to say, this is how I could use AI to unlock, whatever I'm doing. [00:05:33] Anush Elangovan: And, and, some of it, you know, it's good to really step back and look at. Just question every part of it, right? Like right now you're getting chat GPT and, Gemini competing for like, math, olympiads and, and, uh, college, uh, reasoning, uh, tests. Right? And, and those are like that, that is amazing and increasingly like complex tasks that they're trying to do. [00:05:58] Anush Elangovan: But there may also be like. [00:06:00] More mundane things that AI could, could get applied to. Right? And, and so when we think about shedding old ways, you wanna shed it not just in like the tip of the spear. It's like, you know, I'm gonna see what's the frontier model. It's also, it could be something as simple as. [00:06:18] Anush Elangovan: How do you choose a, a movie, uh, you know, like a recommendation system, right? Or, or, uh, an automated, uh, flight, uh, rebooking system. So the moment, you know, your flight is late, uh, right now it's a notification, right? It's like, oh, you got a text message saying your flight's late. And I got that like three times this week. [00:06:38] Anush Elangovan: But anyway, uh, and, and, and, and, I was just like, okay, so if I were to rethink this. All this MCPs that we have that should be hooked up into an MCP that says, your flight's delayed. Here are your options. If you want, you know, these are the paid options. Yeah. Here are the free options. This will get you back into your you know, Toronto airport [00:07:00] tonight. [00:07:00] Anush Elangovan: Or if you stay, here's a hotel plus this, plus this, plus. It's just like, go ahead is all I should say. Versus now I'm like, okay, can someone, you know, can I call a travel agent? Can I do this? Can I go online and log into And you know, so we gotta fundamentally rethink even those like small, nuances of, things that we do that can be automated out and AI is really, really good at doing something like this, right? Maybe I just explained an AI startup idea right now. Somebody should just start that. [00:07:29] Andrew Zigler: I think you did. Yeah, you definitely did. Someone, one of our listeners is definitely going to lift that off of you. I, I, I, you know, I hate being on the receiving end of those. You feel a little helpless and then you have to like, follow the whole flow. So I know what you mean. Like I, I like how you called out that the build and this like. [00:07:45] Andrew Zigler: Where speed is your moat and the innovation layer is protecting you, is what makes you better than your competitors. How you scale that and you bring that to market. So by understanding the problems that you're solving, uh, throwing away those older assumptions, but also [00:08:00] recognizing that like. We're building every single day, new things and new ways of using stuff that we're still figuring out the implications of. [00:08:08] Andrew Zigler: And so when you have a lot of velocity and you're introducing a lot of new ideas, and maybe you have that workflow now that automatically rebook your flight off of your late flight text message, and uh, I know I would certainly use it, but you know, what kind of philosophies guide the way that y'all think about building this ecosystem to manage that stability while letting folks. [00:08:29] Andrew Zigler: Play with the speed and the assumptions and the airplane re bookings. [00:08:34] Anush Elangovan: so, so I think, you know, we need to peel one layer down, right? and the philosophy is, Hey, we, we just discovered electricity, right? And you know what we're gonna do? We are gonna make motors, uh, or dynamos, right? Like engines. Uh, sure. We don't know if it's gonna be a Ferrari that you're gonna make, or it's a a a a dump truck. [00:08:57] Anush Elangovan: That's good for doing this. But let's [00:09:00] let, which is also required, right? You need a dump truck. You need a garbage truck. And, [00:09:04] Andrew Zigler: Yeah. You need the [00:09:04] Anush Elangovan: course you need, uh, a Ferrari for a midlife crisis, right? So, [00:09:09] Andrew Zigler: precisely. [00:09:10] Anush Elangovan: But, but my, uh, point is what do we build next? And, uh, and this is what I meant by like, okay, let's, let's take those baby steps to build the. [00:09:20] Anush Elangovan: Infrastructure that's required that we know we'll have to use, right? So, so if I just discovered electricity, okay, great. Now one, how do I save this electricity and how do I use it? So there's battery technology, so you need to do something like that, right? Like so. But then you also want to make it into an actionable thing. [00:09:37] Anush Elangovan: You want to make it for like automobiles, or you wanna use it for, you know, powering, uh, entire cities. So it is that transformational. So, uh, AI is that transformational. So, if you distill down, it'll, it'll come down to how do we think about, what we can do with this this fundamental technology that, We may not be aware of what it [00:10:00] is gonna unlock next, but at least you know the next step is clear, right? It's like a dense fog, you know, it's gonna be like, it, it's the right path. You see the light, but it's kind of like out there and, and the steps you're taking are concrete and you're like, okay, this is good. [00:10:16] Anush Elangovan: I, this is better than where I was or where we were. So we are moving forward. So you can build with the. Intuition from what you see in the short term and a tactical view, but towards what you think the future is gonna be. [00:10:28] Andrew Zigler: Right. You almost like we're all in this like fog of war, right? And like you said, you're reaching out and you're trying to step through it. You could think of it too, as like you're in the dark and your hands are up in front of you and you know that. You're, you're not gonna run your face into a wall because your hands are out in front of you, but you're not gonna maybe do much better than that. [00:10:45] Andrew Zigler: So that's kind of like, I think the eco, the, the industry, the world that we find ourselves in, uh, and we all have to, then this becomes the power of an ecosystem, of a group of people working together to create that layer of, [00:11:00] uh, of establishing the [00:11:01] Anush Elangovan: exactly. And I, I, I just, instead of, you know, saying fog of war I describe it as like, you're in this. Beautiful valley with like a morning, uh, fog that's in. You can smell the flowers. You, you hear the birds. You are like, okay, it's, we are in like, uh, utopian paradise and yes, I just need to like, continue the walk, right? [00:11:24] Anush Elangovan: and then move forward with that, conviction that you're in the right spot. [00:11:27] Andrew Zigler: Yeah. So let's talk about that ecosystem world. This nice, I love how you describe it, this grassy side of a hill in the morning that's covered in some mist and maybe we can't see 30 feet in one direction, but it sure is a beautiful hill and it smells nice. And so we're all here. And why is, in that world, why is. [00:11:44] Andrew Zigler: You know, open source, their strategic advantage that y'all are going for in the AI hardware market. And, and then how does like ROCm turn that into wins for people within that ecosystem? [00:11:56] Anush Elangovan: you know, the, the way we look at it is this, is kind of like how I view [00:12:00] AI and the ecosystem, right? But, but it is for everyone to enjoy. Uh, and so we do want to make sure that. You know, it is, uh, beneficial for everyone. [00:12:09] Anush Elangovan: The ecosystem can come in and, and innovate. It's an open innovation engine. and uh, it is very different from, you know, having a walled garden with, Hey, only I know how to do this and I'm gonna do it and throw it over the fence and you can use it or keep walking, right? So we'd like to be good citizens that way, but also. [00:12:30] Anush Elangovan: Uh, it is self-fulfilling in a way, right? Like it, the, the pace at which we innovate with open source is unmatched. Like, you know, our serving engines are like VLLM and, and sg l. Those things, uh, those frameworks are like super, super aggressive in terms of how fast they come out with features and how fast they can you know, get performant models out. [00:12:52] Anush Elangovan: And that compared with what, uh, you'd get from, you know, the likes of like T-R-T-L-L-M or something is always lagging, right? Because you [00:13:00] just can't keep up with you know, 200 commits a week just on one particular model to get that model really performant [00:13:06] Andrew Zigler: And, and, and in that world where, you know, everyone can enjoy the winds of this, what kind of customer stories or innovation stories have really stood out to you and excite you about building and creating this place for developers? [00:13:19] Anush Elangovan: Yeah. So I think the parts that are super exciting for me are when when we get to see a customer that is first skeptical. Then they start a little like, okay, fine, we'll give you a chance. Uh, we do a simple, uh, POC and then they're like, huh, this seems to work. Yeah, we told you it works. [00:13:42] Anush Elangovan: You don't have to change one line of code. Really? Yes, no need to change one line of code. Okay, let's try a production workload. So then they try it. Oh, you're more performant than the competition. Yes. We're more performant than, than the competition. So how much does it cost? And we're like, oh, it's your TCO is better with, uh, [00:14:00] AMD. [00:14:00] Anush Elangovan: So again, they're like, wow, okay, good. So now how do we deploy at scale? And then we go deploy it at scale. And when they give a thumbs up on that and they say, this is good, right? That's when you know, you, you see it go full circle from like, oh, we, we've never heard about AMD to like actually deploy to tens of thousands of GPUs In the order of a few months, right? It, it, it really is fascinating to see and very exciting and invigorating to [00:14:28] Andrew Zigler: Yeah. At like a great exposure to a lot of interesting problems. And, and then people using the infrastructure, the, the technology available to solve those problems. Really specific problems by the way, that's often why they're bringing their data and AI to it, uh, is because it is really specific and important for them. [00:14:45] Andrew Zigler: And there's a, a lot I think that other engineering orgs can learn and even emulate from AMD's success and, and having this open source ecosystem and it causing this acceleration within. You [00:15:00] know, uh, customers and enterprises that use and adopt the tools and, and, and that creates an advantage. And that goes back to why we're talking and like the real thesis of our conversation today. [00:15:10] Andrew Zigler: So how do you think engineering leaders that are listening to this and obviously tapping into this great success AMD has from an open source flywheel, how do you think other, other folks building in the same space can foster that open, first, that open source oriented culture in order to, you know, accelerate their innovation goals? [00:15:29] Anush Elangovan: Yeah, that's a very good question. So the startup that um, was acquired by AMD we, we built, I mean, we started off doing iot stuff and you know, smart ring and all that, right? But in the, the end of like, uh, and not the end, the last six years of the company was building ML compilers. [00:15:47] Anush Elangovan: And ml, ML compilers are like super, uh, complicated, sophisticated, advanced algorithms, dah, dah, dah. but it was all open source, right? So our VCs were like, wait, what do you mean your core [00:16:00] IP is open source? And um, the speed is the moat applied even then, right? It was just like, yes, if you have an idea that. [00:16:08] Anush Elangovan: Because someone saw this idea that you are, they're gonna be able to catch up, then you probably have the wrong idea anyway. But if they are, you know, you execute and they're gonna catch up, that you should assume they're gonna catch up. Right? So you gotta move forward. So keeping it open source is super important. [00:16:25] Anush Elangovan: But also to your question on like, you know, the learnings from an AMD standpoint, right? If there are, hard problems, I'd say dig in and work through it, right? Like there's no way but through it, right? That should be the simple mentality. And more, uh, frequently than not. you'll see that you'll just make it through in a, in, in good form. [00:16:52] Anush Elangovan: But if you doubt it and you're like, oh, I don't know if I should commit, if I'm, I, you know, what should just commit to do the right thing [00:17:00] every step, right? Every step, and just keep taking one step in front of the other. And in no time you'll see that you'll be running. Right. And, and yes, the first few steps will be like, yeah, everyone's complaining about your software quality. [00:17:15] Anush Elangovan: Everyone's complaining about this and that, and it doesn't work. And, and a few steps in, you know, you get, you get the hang of all the complaints that are coming in. You get the feedback loop. You're like, okay, what, what are you prioritizing again? One step in front of the other, right? You just keep knocking that out and then you get to a point where you're, it just becomes second nature, right? To do the, to do the right thing. And, and then yes, if someone gives you two options, you'll be like, fine. This is, uh, you know, there's always the resource trade off. There's always a human capital trade off, but what's the right thing to do? of course, I, I'm pragmatic about what we choose, but, but if the right thing for your long-term success is dig in, go first, principles, make it [00:18:00] happen. [00:18:00] Anush Elangovan: Well. Then just go for that. There's, there is no shortcut to [00:18:04] Andrew Zigler: acknowledging, you know, how it aligns with your mission, your core company goals, and what you're looking to achieve. And, and I, I love how you rightfully called out that in the open source world and you know, you have your technology that you've built, what you think is your moat upon, right? [00:18:22] Andrew Zigler: It's your code and, and to open source that, or to just make it where anyone could peer in is, you know. Scary in one regard, but two, it just kind of feels like you're handing away your throne room in some kind of sense, a very direct feeling sense. But the ultimately, you were really right to call out, and this is something I think about all the time, that the real power there is still the speed This the speed. [00:18:42] Andrew Zigler: That was the moat at the beginning of our conversation. It's the speed in combination with your. Very specific domain understanding of what you're building and what you're creating, and your new role as the steward of that world and how people plug into it, which [00:19:00] has frankly, a lot more influence and power than lording over a closed. [00:19:04] Andrew Zigler: You know, repository or an ecosystem, and like you said, like throwing things over the wall. Sure. There, there might be people always on the other side of that wall, but you're not gonna have a great connection with them. You're not gonna be able to really clearly understand them. I, I like your metaphor of the side of the field of the mountain a lot more. [00:19:23] Andrew Zigler: But, but in the, in this world, you know, where. That speed is, is the power and, and open source is just one way that you can harness that speed to get really far ahead and to innovate. , There's other parts of this equation that you can be experimenting with too, and I'd love to pick your brain about them as a software leader and, and, and one of them is about looking forward and kind of understanding that future that we're all building towards and beyond today's models and hardware. [00:19:48] Andrew Zigler: You know, what do you see as the next major bottleneck or opportunity in the AI compute space? As, as you know, enterprises and folks start to get a little more mature about what's available to [00:20:00] them. [00:20:00] Anush Elangovan: Yeah, I think, the bottleneck and opportunity is, uh, what I'd call, call walking the last mile of ai. Right. Uh, and like I I, I gave you an example, uh, previously, but, but it's similar to that. It's like there are cases where Humans have so many, uh, things to do in your day. You know, like the, if we sit down and actually had a customer focus like, okay, these customers lives, I'm gonna save four hours of this customer's life. And if you actually sit down and look at all of that, it'll be. Easily automatable, easily you know, uh, applicable, uh, for ai, right? [00:20:39] Anush Elangovan: Like, but then making it happen is gonna take a little bit, right? It's like maybe it's, uh, paying your utility bill, right? Or something like that, right? Or, or, your healthcare explanation of benefits. Uh, like, I'm sure you get an explanation of benefits, and I'm like, I, I don't even know what that thing is. [00:20:55] Anush Elangovan: It's just like EOB and like. [00:20:57] Andrew Zigler: it's a big, a big old PDF. Yeah, [00:21:00] exactly. [00:21:01] Anush Elangovan: Like, like, I'm like great straight to the, uh, shredder, right? And but that could be, you know, automated with the ai, right? It, it, it'd be like, Hey, the summary of this thing is you went and visited this day. Everything is okay. Everything is paid for, so don't worry, it's not a bill. [00:21:17] Anush Elangovan: That again, the same, uh, thing, but the sense of what that information overload is could be. Digested by ai, uh, accumulated over time and retrieved when you need it. Like, I don't, I actually don't even need to know this EOB right now, unless of course, whenever I need to know it, that maybe, you know, like for some benefits I need to figure out what do, what did I do over the past year and how do I apply it? Source:

Mike

14,195 views • 7 months ago