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Here's your daily Indian tech white pill: 1. Muks Robotics deployed their first humanoid in Pune airport 2. AgniKul Cosmos test-fired 3 semi-cryogenic rocket engines at once 3. The ePlane Company might raise $40-50M 4. Fractal AI Research's PiEvolve is crushing it on OpenAI's MLE-Bench

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19,928 Aufrufe • vor 5 Monaten •via X (Twitter)

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It's Friday! Here's your daily Indian tech white pill: 1. Version One Ventures led Pluto Mobility's $2M seed 2. Sarvam launched Indus on the Play Store, but everyone is on the waitlist 3. Apollyon Dynamics has successfully test-launched their jet-powered UAV from a moving vehicle
2:22

It's Friday! Here's your daily Indian tech white pill: 1. Version One Ventures led Pluto Mobility's $2M seed 2. Sarvam launched Indus on the Play Store, but everyone is on the waitlist 3. Apollyon Dynamics has successfully test-launched their jet-powered UAV from a moving vehicle

Runtime

27,574 Aufrufe • vor 5 Monaten

Humbled to share that we successfully test fired 3 semi-cryogenic rocket engines simultaneously, as a cluster. All the 3 engines are 3d printed as single pieces of hardware - designed and manufactured in-house at AgniKul Cosmos Rocket Factory - 1. As with all our propulsion systems, these 3 engines are also powered by electric motor driven pumps. This test involved calibrating 6 pumps, 6 motors and tuning 6 speed control algorithms to work together in perfect sync to achieve uniform startup, steady state and shutdown performance across the entire system. To the best of our knowledge, this is the first time such a test has been performed in India with semi cryogenic engines. We are extremely grateful to have the opportunity to be building world class, original space technology from India, for the world with the support of ISRO and IN-SPACe #Agnibaan #RocketEngineCluster #ElectricPumpFedEngines #Agnilet #SinglePieceEngine #3dprinting #RocketEngineTest #AdditiveManufacturing #Agnikul #AgnikulCosmos #StartupIndia #MakeinIndia #madeinIndiaForTheWorld Srinath Ravichandran MOIN SPM Satyanarayanan Chakravarthy IIT Madras IITMRP IIT Madras Incubation Cell Technology Development Board DSTIndia Anusandhan National Research Foundation TIDCO Startup India StartupTN Guidance Tamil Nadu Kerala Startup Mission
1:02

Humbled to share that we successfully test fired 3 semi-cryogenic rocket engines simultaneously, as a cluster. All the 3 engines are 3d printed as single pieces of hardware - designed and manufactured in-house at AgniKul Cosmos Rocket Factory - 1. As with all our propulsion systems, these 3 engines are also powered by electric motor driven pumps. This test involved calibrating 6 pumps, 6 motors and tuning 6 speed control algorithms to work together in perfect sync to achieve uniform startup, steady state and shutdown performance across the entire system. To the best of our knowledge, this is the first time such a test has been performed in India with semi cryogenic engines. We are extremely grateful to have the opportunity to be building world class, original space technology from India, for the world with the support of ISRO and IN-SPACe #Agnibaan #RocketEngineCluster #ElectricPumpFedEngines #Agnilet #SinglePieceEngine #3dprinting #RocketEngineTest #AdditiveManufacturing #Agnikul #AgnikulCosmos #StartupIndia #MakeinIndia #madeinIndiaForTheWorld Srinath Ravichandran MOIN SPM Satyanarayanan Chakravarthy IIT Madras IITMRP IIT Madras Incubation Cell Technology Development Board DSTIndia Anusandhan National Research Foundation TIDCO Startup India StartupTN Guidance Tamil Nadu Kerala Startup Mission

AgniKul Cosmos

363,531 Aufrufe • vor 5 Monaten

Humbled to share that we successfully test fired 4 semi-cryogenic rocket engines simultaneously, as a cluster. All the 4 engines are 3d printed as single pieces of hardware - designed and manufactured in-house at AgniKul Cosmos Rocket Factory - 1. As with all our propulsion systems, these 4 engines are also powered by electric motor driven pumps. This test involved calibrating 8 pumps, 8 motors and tuning 8 speed control algorithms to work together in perfect sync to achieve uniform startup, steady state and shutdown performance across the entire system. As with the last cluster test, to the best of our knowledge, this is the first time such a test has been performed in India with semi cryogenic engines. We are extremely grateful to have the opportunity to be building world class, original space technology from India, for the world with the support of IIT Madras ISRO and IN-SPACe From here on, the addition of engines to our clusters will likely increase non-linearly. #Agnibaan #RocketEngineCluster #ElectricPumpFedEngines #Agnilet #SinglePieceEngine #3dprinting #RocketEngineTest #AdditiveManufacturing #Agnikul #AgnikulCosmos #StartupIndia #MakeinIndia #madeinIndiaForTheWorld Srinath Ravichandran MOIN SPM Satyanarayanan Chakravarthy IIT Madras IITMRP IIT Madras Incubation Cell Technology Development Board DSTIndia Anusandhan National Research Foundation TIDCO Startup India StartupTN Guidance Tamil Nadu Kerala Startup Mission SIPCOT
1:06

Humbled to share that we successfully test fired 4 semi-cryogenic rocket engines simultaneously, as a cluster. All the 4 engines are 3d printed as single pieces of hardware - designed and manufactured in-house at AgniKul Cosmos Rocket Factory - 1. As with all our propulsion systems, these 4 engines are also powered by electric motor driven pumps. This test involved calibrating 8 pumps, 8 motors and tuning 8 speed control algorithms to work together in perfect sync to achieve uniform startup, steady state and shutdown performance across the entire system. As with the last cluster test, to the best of our knowledge, this is the first time such a test has been performed in India with semi cryogenic engines. We are extremely grateful to have the opportunity to be building world class, original space technology from India, for the world with the support of IIT Madras ISRO and IN-SPACe From here on, the addition of engines to our clusters will likely increase non-linearly. #Agnibaan #RocketEngineCluster #ElectricPumpFedEngines #Agnilet #SinglePieceEngine #3dprinting #RocketEngineTest #AdditiveManufacturing #Agnikul #AgnikulCosmos #StartupIndia #MakeinIndia #madeinIndiaForTheWorld Srinath Ravichandran MOIN SPM Satyanarayanan Chakravarthy IIT Madras IITMRP IIT Madras Incubation Cell Technology Development Board DSTIndia Anusandhan National Research Foundation TIDCO Startup India StartupTN Guidance Tamil Nadu Kerala Startup Mission SIPCOT

AgniKul Cosmos

118,839 Aufrufe • vor 2 Monaten

Here's everything that happened in Indian tech in the last 24 hours: 1. BotLab Dynamics unveiled their new nano drone 2. Xbattery raised $2.3M to build indigenous BMS 3. Apple is doubling down on India manufacturing 4. BharatGen raised ₹988.6 Cr from IndiaAI 🚨 Follow Runtime for daily updates on Indian tech.
2:35

Here's everything that happened in Indian tech in the last 24 hours: 1. BotLab Dynamics unveiled their new nano drone 2. Xbattery raised $2.3M to build indigenous BMS 3. Apple is doubling down on India manufacturing 4. BharatGen raised ₹988.6 Cr from IndiaAI 🚨 Follow Runtime for daily updates on Indian tech.

Runtime

19,838 Aufrufe • vor 10 Monaten

You've probably heard about GPS. But have you heard about VPS? It's the visual positioning tech that gives robots and AR glasses centimeter-level accuracy where GPS fails. Here's how it works: 0:00 - Intro 0:19 - How GPS Actually Works 1:28 - The Problem with GPS for AR & Robotics 2:06 - What is VPS? (Visual Positioning System) 2:38 - Use Cases: Delivery Robots & Drones 3:17 - VPS in Action: Apple Vision Pro & Meta Quest 3:53 - Scanning Your World with an iPhone (Multiset AI) 4:31 - Key Takeaways 4:48 - The Future: Spatial Intelligence
5:21

You've probably heard about GPS. But have you heard about VPS? It's the visual positioning tech that gives robots and AR glasses centimeter-level accuracy where GPS fails. Here's how it works: 0:00 - Intro 0:19 - How GPS Actually Works 1:28 - The Problem with GPS for AR & Robotics 2:06 - What is VPS? (Visual Positioning System) 2:38 - Use Cases: Delivery Robots & Drones 3:17 - VPS in Action: Apple Vision Pro & Meta Quest 3:53 - Scanning Your World with an iPhone (Multiset AI) 4:31 - Key Takeaways 4:48 - The Future: Spatial Intelligence

Bilawal Sidhu

14,757 Aufrufe • vor 7 Monaten

GP at General Catalyst, Zeynep Yavuz on why investing in AI Rollups at General Catalyst is significantly different to traditional PE: "We don't use debt in the beginning because we don't want to put stress in these businesses. We're planning for the long term - we don't have this 3-5 year horizon [like most of traditional PE]" The GC rollup model: 1. Deployed equity capital (cost in) 2. Invest in the tech to automate operations (building for the long term) 3. Invest in rollups using cash and equity 4. Take on leverage at 40% EBITDA margins (not 15%) = better terms to create higher upside using leverage
0:59

GP at General Catalyst, Zeynep Yavuz on why investing in AI Rollups at General Catalyst is significantly different to traditional PE: "We don't use debt in the beginning because we don't want to put stress in these businesses. We're planning for the long term - we don't have this 3-5 year horizon [like most of traditional PE]" The GC rollup model: 1. Deployed equity capital (cost in) 2. Invest in the tech to automate operations (building for the long term) 3. Invest in rollups using cash and equity 4. Take on leverage at 40% EBITDA margins (not 15%) = better terms to create higher upside using leverage

etn.

17,201 Aufrufe • vor 8 Monaten

OpenAI Dev Day Just kicked off and it was the biggest day for AI since the launch of GPT-4 in April. Here's a 3 minute video with everything you need to know and a full summary: 1. GPT-4 Turbo is released. It is much better than GPT-4, can accept up to 128k characters and is 3x cheaper. The knowledge cut off is now April 2023 2. Text to Speech is also being released. They offer 6 hyper-realistic voice models that are the best I've heard from any other AI t-t-s software on the market. 3. Copyright Shield. OpenAI will actually defend your legal costs if you get sued for copyright infringement using their API! 4. GPTs. Maybe the most exciting IMHO, you can now create custom "GPTs" by training your own model of GPT and selling it on their store. This will create a massive shakeup of the current AI software landscape and is the first step towards autonomous agents.
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OpenAI Dev Day Just kicked off and it was the biggest day for AI since the launch of GPT-4 in April. Here's a 3 minute video with everything you need to know and a full summary: 1. GPT-4 Turbo is released. It is much better than GPT-4, can accept up to 128k characters and is 3x cheaper. The knowledge cut off is now April 2023 2. Text to Speech is also being released. They offer 6 hyper-realistic voice models that are the best I've heard from any other AI t-t-s software on the market. 3. Copyright Shield. OpenAI will actually defend your legal costs if you get sued for copyright infringement using their API! 4. GPTs. Maybe the most exciting IMHO, you can now create custom "GPTs" by training your own model of GPT and selling it on their store. This will create a massive shakeup of the current AI software landscape and is the first step towards autonomous agents.

Mark Gadala-Maria

79,177 Aufrufe • vor 2 Jahren

Here's my conversation with Dario Amodei, CEO of Anthropic, the company that created Claude, one of the best AI systems in the world. We talk about scaling, AI safety, regulation, and a lot of super technical details about the present and future of AI and humanity. It's a 5+ hour conversation in total. Amanda Askell and Chris Olah (Chris Olah) join us for an hour each to talk about Claude's character and mechanistic interpretability, respectively. This was a fascinating, wide-ranging, super-technical, and fun conversation! First 4 hours are here on X (4 hours is current limit), and is up on everywhere else in full. Links in comment. Timestamps: 0:00 - Introduction 3:14 - Scaling laws 12:20 - Limits of LLM scaling 20:45 - Competition with OpenAI, Google, xAI, Meta 26:08 - Claude 29:44 - Opus 3.5 34:30 - Sonnet 3.5 37:50 - Claude 4.0 42:02 - Criticism of Claude 54:49 - AI Safety Levels 1:05:37 - ASL-3 and ASL-4 1:09:40 - Computer use 1:19:35 - Government regulation of AI 1:38:24 - Hiring a great team 1:47:14 - Post-training 1:52:39 - Constitutional AI 1:58:05 - Machines of Loving Grace 2:17:11 - AGI timeline 2:29:46 - Programming 2:36:46 - Meaning of life 2:42:53 - Amanda Askell - Philosophy 2:45:21 - Programming advice for non-technical people 2:49:09 - Talking to Claude 3:05:41 - Prompt engineering 3:14:15 - Post-training 3:18:54 - Constitutional AI 3:23:48 - System prompts 3:29:54 - Is Claude getting dumber? 3:41:56 - Character training 3:42:56 - Nature of truth 3:47:32 - Optimal rate of failure 3:54:43 - AI consciousness 4:09:14 - AGI 4:17:52 - Chris Olah - Mechanistic Interpretability 4:22:44 - Features, Circuits, Universality 4:40:17 - Superposition 4:51:16 - Monosemanticity 4:58:08 - Scaling Monosemanticity 5:06:56 - Macroscopic behavior of neural networks 5:11:50 - Beauty of neural networks
3:58:08

Here's my conversation with Dario Amodei, CEO of Anthropic, the company that created Claude, one of the best AI systems in the world. We talk about scaling, AI safety, regulation, and a lot of super technical details about the present and future of AI and humanity. It's a 5+ hour conversation in total. Amanda Askell and Chris Olah (Chris Olah) join us for an hour each to talk about Claude's character and mechanistic interpretability, respectively. This was a fascinating, wide-ranging, super-technical, and fun conversation! First 4 hours are here on X (4 hours is current limit), and is up on everywhere else in full. Links in comment. Timestamps: 0:00 - Introduction 3:14 - Scaling laws 12:20 - Limits of LLM scaling 20:45 - Competition with OpenAI, Google, xAI, Meta 26:08 - Claude 29:44 - Opus 3.5 34:30 - Sonnet 3.5 37:50 - Claude 4.0 42:02 - Criticism of Claude 54:49 - AI Safety Levels 1:05:37 - ASL-3 and ASL-4 1:09:40 - Computer use 1:19:35 - Government regulation of AI 1:38:24 - Hiring a great team 1:47:14 - Post-training 1:52:39 - Constitutional AI 1:58:05 - Machines of Loving Grace 2:17:11 - AGI timeline 2:29:46 - Programming 2:36:46 - Meaning of life 2:42:53 - Amanda Askell - Philosophy 2:45:21 - Programming advice for non-technical people 2:49:09 - Talking to Claude 3:05:41 - Prompt engineering 3:14:15 - Post-training 3:18:54 - Constitutional AI 3:23:48 - System prompts 3:29:54 - Is Claude getting dumber? 3:41:56 - Character training 3:42:56 - Nature of truth 3:47:32 - Optimal rate of failure 3:54:43 - AI consciousness 4:09:14 - AGI 4:17:52 - Chris Olah - Mechanistic Interpretability 4:22:44 - Features, Circuits, Universality 4:40:17 - Superposition 4:51:16 - Monosemanticity 4:58:08 - Scaling Monosemanticity 5:06:56 - Macroscopic behavior of neural networks 5:11:50 - Beauty of neural networks

Lex Fridman

1,375,278 Aufrufe • vor 1 Jahr

Chrome has received a massive AI update Gemini in Chrome can see your screen live and interact with you to explain things. Discussion is extremely natural and is a game-changer for learning. Here's how to access it: 1. Use a Gemini Pro/Ultra account 2. Log in to this account on Chrome 3. The icon should appear in the top right-hand corner 4. Click on it or use the shortcut Alt+G At the end of your conversation, the entire transcript is available: It's easy to find information in the future!
3:47

Chrome has received a massive AI update Gemini in Chrome can see your screen live and interact with you to explain things. Discussion is extremely natural and is a game-changer for learning. Here's how to access it: 1. Use a Gemini Pro/Ultra account 2. Log in to this account on Chrome 3. The icon should appear in the top right-hand corner 4. Click on it or use the shortcut Alt+G At the end of your conversation, the entire transcript is available: It's easy to find information in the future!

Paul Couvert

277,519 Aufrufe • vor 1 Jahr

⚡day 5 of launch week: from (zero) MCP server to ChatGPT app this is peak developer experience 🤌🏼 1. define your UI in a single react file. 2. test it instantly with hot reload in the built-in Inspector 3. deploy it in one click on mcp-use Cloud 4. ship it directly to ChatGPT with: npx create-mcp-use-app@latest my-server --template apps-sdk you can go from zero to a deployed mcp server with apps sdk widgets in just 5 minutes here's how 🧵
2:50

⚡day 5 of launch week: from (zero) MCP server to ChatGPT app this is peak developer experience 🤌🏼 1. define your UI in a single react file. 2. test it instantly with hot reload in the built-in Inspector 3. deploy it in one click on mcp-use Cloud 4. ship it directly to ChatGPT with: npx create-mcp-use-app@latest my-server --template apps-sdk you can go from zero to a deployed mcp server with apps sdk widgets in just 5 minutes here's how 🧵

pederzh

22,647 Aufrufe • vor 9 Monaten

🇺🇸 The 3 fastest firing weapons ever built. The numbers don't feel real. No. 3: The GAU-8 Avenger. Strapped to the nose of the A-10 Warthog. 3,900 RPM of 30mm armor-piercing shells. Its recoil is greater than the thrust of one of the plane's own engines. Built to shred tanks. Terrifyingly good at it. No. 2: The M134 Minigun. Six barrels. 6,000 RPM. Mounted on helicopters, vehicles and anywhere that needs serious firepower instantly. The sound alone is enough to end the conversation. No. 1: Metal Storm. No moving parts. Electronic ignition. 1 million RPM (!!!). 180 rounds fired in 0.01 seconds. It holds the world record, but has never once been used in combat. The company went bankrupt in 2012. China is now building their own version. War was scary enough with rifles, hell even swords. As military tech advances into sci-fi territory, it’s just not even a fair fight. Source: War Spectator YT
0:58

🇺🇸 The 3 fastest firing weapons ever built. The numbers don't feel real. No. 3: The GAU-8 Avenger. Strapped to the nose of the A-10 Warthog. 3,900 RPM of 30mm armor-piercing shells. Its recoil is greater than the thrust of one of the plane's own engines. Built to shred tanks. Terrifyingly good at it. No. 2: The M134 Minigun. Six barrels. 6,000 RPM. Mounted on helicopters, vehicles and anywhere that needs serious firepower instantly. The sound alone is enough to end the conversation. No. 1: Metal Storm. No moving parts. Electronic ignition. 1 million RPM (!!!). 180 rounds fired in 0.01 seconds. It holds the world record, but has never once been used in combat. The company went bankrupt in 2012. China is now building their own version. War was scary enough with rifles, hell even swords. As military tech advances into sci-fi territory, it’s just not even a fair fight. Source: War Spectator YT

Mario Nawfal

70,602 Aufrufe • vor 4 Monaten

tesla is merging with spaceX. this announcement did all but confirm it. a multi-trillion dollar space/ai/robotics GIANT, a moon settlement and at the heart of it - the Terafab - here's why this is nuts: - tesla plans to ship 1-10 BILLION robots PER year. problem: global chip capacity is shit, doesn't scale. - Tesla's 'Terafab' will produce 1 TERAwatt of compute. 80% of that will go to outer-space to train AI (grok) via spaceX - terafab will make 2 AI chips: 1 for humanoid robots/cars and 1 for AI datacenters in space. - by housing everything under 1 roof - chip production speeds up by an order of magnitude. unbeatable. - moon settlement: the sun doesn't set in space. solar power is 5X larger in low-orbit space. much more on the moon (24/7 too!) - so elon will build a moon settlement! there is ZERO chance tesla survives without spaceX transporting these ai chips. elon estimates training AI in space will be CHEAPER THAN ON EARTH in 2-3 years. insane. (heres the full announcement if you wanna watch)
21:45

tesla is merging with spaceX. this announcement did all but confirm it. a multi-trillion dollar space/ai/robotics GIANT, a moon settlement and at the heart of it - the Terafab - here's why this is nuts: - tesla plans to ship 1-10 BILLION robots PER year. problem: global chip capacity is shit, doesn't scale. - Tesla's 'Terafab' will produce 1 TERAwatt of compute. 80% of that will go to outer-space to train AI (grok) via spaceX - terafab will make 2 AI chips: 1 for humanoid robots/cars and 1 for AI datacenters in space. - by housing everything under 1 roof - chip production speeds up by an order of magnitude. unbeatable. - moon settlement: the sun doesn't set in space. solar power is 5X larger in low-orbit space. much more on the moon (24/7 too!) - so elon will build a moon settlement! there is ZERO chance tesla survives without spaceX transporting these ai chips. elon estimates training AI in space will be CHEAPER THAN ON EARTH in 2-3 years. insane. (heres the full announcement if you wanna watch)

Ejaaz

163,328 Aufrufe • vor 4 Monaten

Did you hear that? It sounds like it's coming under the Railway Station next to the Dance Hall. Seems like you've stumbled in on The Clobberin' Club, Rival... you must now follow these rules. 1. 1v1 fights ONLY. 2. No tagging in other players. 3. There are no friends in the club. 4. It's Clobberin' Time! Test your might at the hottest and rowdiest club in town and live-stream your fights on the big screen. The people yearn for a good fight. 📅 Available: January 29th at 9 AM UTC! Who are you challenging first?
0:44

Did you hear that? It sounds like it's coming under the Railway Station next to the Dance Hall. Seems like you've stumbled in on The Clobberin' Club, Rival... you must now follow these rules. 1. 1v1 fights ONLY. 2. No tagging in other players. 3. There are no friends in the club. 4. It's Clobberin' Time! Test your might at the hottest and rowdiest club in town and live-stream your fights on the big screen. The people yearn for a good fight. 📅 Available: January 29th at 9 AM UTC! Who are you challenging first?

Marvel Rivals

968,226 Aufrufe • vor 6 Monaten

The reason your AI gives generic answers isn't the model. It's that your company's knowledge lives in 12 different tools and your agent can't see any of it. So here's how to build a context database your agents can actually use: 1) Pull it in: - Slack, email, meetings, docs, tickets - Auto-collected on a schedule into one place. 2) Clean it up. - An agent files what matters and drops the noise, so your brain doesn't bloat. 3) Store it as memory. - Folders of files your agents read from and write back to as they learn. 4) Point your agents at it. - Now they draft, build, and ship with full context instead of guessing. Same model. Same agent. The difference is whether it can understand your company or not. Build the database once. Everything downstream gets smarter.
8:17

The reason your AI gives generic answers isn't the model. It's that your company's knowledge lives in 12 different tools and your agent can't see any of it. So here's how to build a context database your agents can actually use: 1) Pull it in: - Slack, email, meetings, docs, tickets - Auto-collected on a schedule into one place. 2) Clean it up. - An agent files what matters and drops the noise, so your brain doesn't bloat. 3) Store it as memory. - Folders of files your agents read from and write back to as they learn. 4) Point your agents at it. - Now they draft, build, and ship with full context instead of guessing. Same model. Same agent. The difference is whether it can understand your company or not. Build the database once. Everything downstream gets smarter.

The Startup Ideas Podcast (SIP) 🧃

13,598 Aufrufe • vor 1 Monat

What does it actually mean to be AI native? There was no clear guide on the internet for how to become AI native so we built the definitive one (60 min masterclass): 1. An AI native org has 3 layers: people for strategy and taste, agents for execution, and a shared context layer that makes the entire company readable to agents. 2. AI eats the middle of your work. You used to spend 80% of your day on execution. Now agents do that. Your job is the bookends: deciding what to do and judging whether it's good enough. 3. Everyone is a manager now. Your output is the output of your agents. If your agents produce garbage, that's on you. You set them up wrong. 4. Using ChatGPT doesn't make you AI native. That's like having a website and calling yourself a tech company lol. 5. No AI native org without AI native people. Most companies skip straight to the tools. That's why it fails. If your people don't understand how to manage agents, the tech doesn't matter. 6. Making your company "readable" to agents is the real work. Every process, every decision, every piece of knowledge needs to exist in a format an agent can consume. Most companies are nowhere close. 7. Speed without signal is just expensive chaos. You need the system to move fast AND know if you're moving in the right direction. 8. The skill chain is how agents get good at your specific workflows. Skills build on skills. The more you invest in them, the more your company compounds. 9. The moat is the system. People managing agents, agents reading from rich context, the whole thing getting smarter every week. That compounds. Your competitor can copy your tools. They can't copy your system. Full episode with Theo Tabah from LCA on The Startup Ideas Podcast (SIP) 🧃. This is the stuff we normally keep internal but all the sauce is yours. Theo Tabah is the brains behind advising the world's biggest companies on AI and building AI products. Your fav CEO's first call for figuring out AI. You are in for a treat Become AI native in under 60 minutes Watch
56:43

What does it actually mean to be AI native? There was no clear guide on the internet for how to become AI native so we built the definitive one (60 min masterclass): 1. An AI native org has 3 layers: people for strategy and taste, agents for execution, and a shared context layer that makes the entire company readable to agents. 2. AI eats the middle of your work. You used to spend 80% of your day on execution. Now agents do that. Your job is the bookends: deciding what to do and judging whether it's good enough. 3. Everyone is a manager now. Your output is the output of your agents. If your agents produce garbage, that's on you. You set them up wrong. 4. Using ChatGPT doesn't make you AI native. That's like having a website and calling yourself a tech company lol. 5. No AI native org without AI native people. Most companies skip straight to the tools. That's why it fails. If your people don't understand how to manage agents, the tech doesn't matter. 6. Making your company "readable" to agents is the real work. Every process, every decision, every piece of knowledge needs to exist in a format an agent can consume. Most companies are nowhere close. 7. Speed without signal is just expensive chaos. You need the system to move fast AND know if you're moving in the right direction. 8. The skill chain is how agents get good at your specific workflows. Skills build on skills. The more you invest in them, the more your company compounds. 9. The moat is the system. People managing agents, agents reading from rich context, the whole thing getting smarter every week. That compounds. Your competitor can copy your tools. They can't copy your system. Full episode with Theo Tabah from LCA on The Startup Ideas Podcast (SIP) 🧃. This is the stuff we normally keep internal but all the sauce is yours. Theo Tabah is the brains behind advising the world's biggest companies on AI and building AI products. Your fav CEO's first call for figuring out AI. You are in for a treat Become AI native in under 60 minutes Watch

GREG ISENBERG

84,381 Aufrufe • vor 2 Monaten

JUST IN: Figure has gone from producing 1 humanoid robot per day to 1 per hour, a 24x throughput improvement in under 120 days. This data is from their manufacturing facility BotQ update (link below) Here's what's happening inside BotQ: → Over 350 Figure 03 robots delivered and counting → End-of-line first-pass yield now above 80% and improving weekly → Battery line at 99.3% first-pass yield with 500+ battery packs shipped → Over 9,000 actuators produced across 10+ distinct SKUs → Every robot put through 80+ functional verification tests before sign-off Their Helix AI model can now SEE the environment it's moving through, not just feel it. Stairs, ramps, uneven terrain, navigated zero-shot, trained entirely in simulation, deployed directly to hardware with no real-world fine-tuning. Brett Adcock has been clear about the plan: every robot that rolls off the line is a data-collection engine. The bigger the fleet, the faster the AI improves. The faster the AI improves, the more deployable the robot becomes. This is the flywheel. And it is now spinning. The humanoid robot race just got very serious. VERY INTERESTING. Alright fam, what are your thoughts on Figure? 👀 Link: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →
0:44

JUST IN: Figure has gone from producing 1 humanoid robot per day to 1 per hour, a 24x throughput improvement in under 120 days. This data is from their manufacturing facility BotQ update (link below) Here's what's happening inside BotQ: → Over 350 Figure 03 robots delivered and counting → End-of-line first-pass yield now above 80% and improving weekly → Battery line at 99.3% first-pass yield with 500+ battery packs shipped → Over 9,000 actuators produced across 10+ distinct SKUs → Every robot put through 80+ functional verification tests before sign-off Their Helix AI model can now SEE the environment it's moving through, not just feel it. Stairs, ramps, uneven terrain, navigated zero-shot, trained entirely in simulation, deployed directly to hardware with no real-world fine-tuning. Brett Adcock has been clear about the plan: every robot that rolls off the line is a data-collection engine. The bigger the fleet, the faster the AI improves. The faster the AI improves, the more deployable the robot becomes. This is the flywheel. And it is now spinning. The humanoid robot race just got very serious. VERY INTERESTING. Alright fam, what are your thoughts on Figure? 👀 Link: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

38,067 Aufrufe • vor 3 Monaten

Funnels don’t work anymore. People don’t buy in straight lines. The new way to win in 2025 is Digital Gravity How to build it: 1) Pick 3 channels where your customers hang out. 2) Create content daily on each (yes, daily) 3) Run ads and test continuously - never start/stop, just iterate. 4) Cross-pollinate touchpoints across channels. Your customer sees you in their feed, inbox, search results, friend’s story. You become unavoidable. Example: Blog post → retargeting ad Workshop → email sequence Social post → lead magnet Friend mentions you → “oh yeah I’ve seen them.” Boom. They finally buy Stop thinking in funnels. Start thinking on orbits. The bigger your digital mass, the stronger your pull. Build Content. Create gravity. Own their mental real estate in your niche. When they’re ready to buy, you’re the only choice.
3:29

Funnels don’t work anymore. People don’t buy in straight lines. The new way to win in 2025 is Digital Gravity How to build it: 1) Pick 3 channels where your customers hang out. 2) Create content daily on each (yes, daily) 3) Run ads and test continuously - never start/stop, just iterate. 4) Cross-pollinate touchpoints across channels. Your customer sees you in their feed, inbox, search results, friend’s story. You become unavoidable. Example: Blog post → retargeting ad Workshop → email sequence Social post → lead magnet Friend mentions you → “oh yeah I’ve seen them.” Boom. They finally buy Stop thinking in funnels. Start thinking on orbits. The bigger your digital mass, the stronger your pull. Build Content. Create gravity. Own their mental real estate in your niche. When they’re ready to buy, you’re the only choice.

The Startup Ideas Podcast (SIP) 🧃

31,456 Aufrufe • vor 11 Monaten

The biggest leak in many people's postures is the rear muscles of the legs. They should be powerful, but long-seated days drain their strength and leave you without vital support. These 4 exercises will patch the leak. Do one 2x/week and watch your posture rise again: 1 - Lying Hyperextension (0:05) 3 x 8-10 This variation is a great place to start. - Lying on your stomach. - Lift both legs off the floor as high as possible without swinging. - Hold for 3 seconds at the top 2 - Bench Hyperextension (0:12) 3 x 8-10 This variation is great because you get a better stretch than on the floor. You can use the end of a couch or the corner of your bed instead of a bench. 3 - Bench Frog Hyperextension (0:18) 3 x 8-10 The Frog variation has both of your feet flat against each other. This position changes how your muscles execute the motion. Your glutes and hamstrings work more intensely. 4 - Weighted Bench Hyperextensions (0:24) 3 x 8-10 Add weight once you are comfortable enough to do full sets of the bodyweight variation. You'll get much better results. Your glutes and hamstrings will respond kindly and provide more postural support. // Keeping your Glutes and Hamstrings strong is essential to withstand the 21st century. Use the exercises above to protect your posture and quality of life.
0:30

The biggest leak in many people's postures is the rear muscles of the legs. They should be powerful, but long-seated days drain their strength and leave you without vital support. These 4 exercises will patch the leak. Do one 2x/week and watch your posture rise again: 1 - Lying Hyperextension (0:05) 3 x 8-10 This variation is a great place to start. - Lying on your stomach. - Lift both legs off the floor as high as possible without swinging. - Hold for 3 seconds at the top 2 - Bench Hyperextension (0:12) 3 x 8-10 This variation is great because you get a better stretch than on the floor. You can use the end of a couch or the corner of your bed instead of a bench. 3 - Bench Frog Hyperextension (0:18) 3 x 8-10 The Frog variation has both of your feet flat against each other. This position changes how your muscles execute the motion. Your glutes and hamstrings work more intensely. 4 - Weighted Bench Hyperextensions (0:24) 3 x 8-10 Add weight once you are comfortable enough to do full sets of the bodyweight variation. You'll get much better results. Your glutes and hamstrings will respond kindly and provide more postural support. // Keeping your Glutes and Hamstrings strong is essential to withstand the 21st century. Use the exercises above to protect your posture and quality of life.

Alex Bernier

256,639 Aufrufe • vor 2 Jahren

Listen to me. Get ready for $SPY and $QQQ. The markets are at BETTER levels now, but not perfect. I give you the GREEN LIGHT to start buying your AI and tech names SLOWLY. However, make sue you still have a BALANCED portfolio. Markets can still come down LOWER if it's not ready yet. This is why you need to have both AI AND stocks outside of tech names in your accounts. What to expect moving forward? 1. Markets will try to find a temporary low. Expect choppiness. 2. Will this be the bottom? Not calling it yet. Still too early. What should you do? 1. Start building SLOWLY on AI winners 2. Keep your defensives (healthcare, utilities, staples, etc.) 3. Build positions in laggards (restaurants, apparel, etc.) What's my portfolio right now? 1. 40% AI winners 2. 15% defensives 3. 15% laggards 4. 15% hedges 5. 15% cash Our portfolio stays SO STRONG during red days. And OUTPERFORMS during green days. Right now, it's NOT about outperforming the markets. It's about SURVIVING and keeping your gains. If $SPY goes down -1%, I do NOT want to be down -5%, -10%. I want to stay CLOSE to -1% as possible. Once the LOW is in, get ready for the biggest bull-run of your life.
3:25

Listen to me. Get ready for $SPY and $QQQ. The markets are at BETTER levels now, but not perfect. I give you the GREEN LIGHT to start buying your AI and tech names SLOWLY. However, make sue you still have a BALANCED portfolio. Markets can still come down LOWER if it's not ready yet. This is why you need to have both AI AND stocks outside of tech names in your accounts. What to expect moving forward? 1. Markets will try to find a temporary low. Expect choppiness. 2. Will this be the bottom? Not calling it yet. Still too early. What should you do? 1. Start building SLOWLY on AI winners 2. Keep your defensives (healthcare, utilities, staples, etc.) 3. Build positions in laggards (restaurants, apparel, etc.) What's my portfolio right now? 1. 40% AI winners 2. 15% defensives 3. 15% laggards 4. 15% hedges 5. 15% cash Our portfolio stays SO STRONG during red days. And OUTPERFORMS during green days. Right now, it's NOT about outperforming the markets. It's about SURVIVING and keeping your gains. If $SPY goes down -1%, I do NOT want to be down -5%, -10%. I want to stay CLOSE to -1% as possible. Once the LOW is in, get ready for the biggest bull-run of your life.

AskLivermore

128,082 Aufrufe • vor 1 Monat

AI models currently have a 50% chance of doing something that takes a human expert one hour. This doubles every 7 months. In 2 years? They could automate full workdays. In 4 years? A full month. I discuss the most important graph in AI today with Beth Barnes, the CEO of METR, which uncovered this rule of AI progress. Her bottom line: "It really doesn't seem like 2 years would be surprising for recursively self-improving AI." Beth also explains: where company safety testing fails, why there are no true closed-weight models, AI undermines leading powers, why she's come around on open weighting, and why models might be about to start playing dumb much more often. Enjoy! Available on the 80,000 Hours Podcast in all apps. Links below. 1:51 Can we see AI scheming in the chain of thought? 12:50 Alignment faking 17:33 We have to test models before they're even used inside AI companies 31:56 Each 7 months models can do tasks twice as long 51:31 METR's research finds AIs are solid at AI research already 58:18 AI may turn out to be strong at novel and creative research 1:07:55 Recursively self-improving AI might even be here in two years 1:14:29 Could evaluations backfire? 1:39:55 Do we need external auditors doing AI safety tests? 1:54:09 Why not work at AI companies 2:08:40 The new more dire situation has forced changes to METR's strategy 2:21:49 Overrated: Interpretability research 2:32:55 Overrated: Major AI companies' contributions to safety research 2:39:15 Could we ban using AI to enhance AI, or is that just naive? 2:45:31 Open-weighting models is often good 2:50:22 What we can learn about AGI from the nuclear arms race 3:10:43 AI is more like bioweapons because it undermines the leading power 3:42:09 What research METR plans to do next
3:57:39

AI models currently have a 50% chance of doing something that takes a human expert one hour. This doubles every 7 months. In 2 years? They could automate full workdays. In 4 years? A full month. I discuss the most important graph in AI today with Beth Barnes, the CEO of METR, which uncovered this rule of AI progress. Her bottom line: "It really doesn't seem like 2 years would be surprising for recursively self-improving AI." Beth also explains: where company safety testing fails, why there are no true closed-weight models, AI undermines leading powers, why she's come around on open weighting, and why models might be about to start playing dumb much more often. Enjoy! Available on the 80,000 Hours Podcast in all apps. Links below. 1:51 Can we see AI scheming in the chain of thought? 12:50 Alignment faking 17:33 We have to test models before they're even used inside AI companies 31:56 Each 7 months models can do tasks twice as long 51:31 METR's research finds AIs are solid at AI research already 58:18 AI may turn out to be strong at novel and creative research 1:07:55 Recursively self-improving AI might even be here in two years 1:14:29 Could evaluations backfire? 1:39:55 Do we need external auditors doing AI safety tests? 1:54:09 Why not work at AI companies 2:08:40 The new more dire situation has forced changes to METR's strategy 2:21:49 Overrated: Interpretability research 2:32:55 Overrated: Major AI companies' contributions to safety research 2:39:15 Could we ban using AI to enhance AI, or is that just naive? 2:45:31 Open-weighting models is often good 2:50:22 What we can learn about AGI from the nuclear arms race 3:10:43 AI is more like bioweapons because it undermines the leading power 3:42:09 What research METR plans to do next

Rob Wiblin

93,669 Aufrufe • vor 1 Jahr