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timelapse #85 (27.5 hrs): - currently cant rely on any other coding models except grok code fast 1 + grok 4 fast (for complex reasoning grok 4 fast is 20 cents for 1M tokens) - wrote qwen3-next trainer entirely from scratch to make it more managable - each piece...

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Elliot Arledge

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283,820 次观看 • 11 个月前 •via X (Twitter)

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timelapse #86 (15 hrs): - got my first OOM on 8xB200 node - defaulting back to grok-code-fast-1, the fastest reliable coding model with by far most intuitive instruction following, combined with grok 4 fast reasoning to plan before i let grok code work its magic - drank 2 large tim hortons iced capps, loaded myself w/ creatine, daily nootropics - tried out gpt-5-codex but it simply doesnt match the speed i require when i go deep into one thing at a time sequentially - got caught watching youtube videos in the middle, need to make sure i block any and all content that could get in my way - caught up on all book revisions so getting super ahead with other chapters - developed an overnight addiction to switching color themes in cursor - did some pair programming w/ Kearm h/eng using Tuple on free trial - applying for O-1
0:27

timelapse #86 (15 hrs): - got my first OOM on 8xB200 node - defaulting back to grok-code-fast-1, the fastest reliable coding model with by far most intuitive instruction following, combined with grok 4 fast reasoning to plan before i let grok code work its magic - drank 2 large tim hortons iced capps, loaded myself w/ creatine, daily nootropics - tried out gpt-5-codex but it simply doesnt match the speed i require when i go deep into one thing at a time sequentially - got caught watching youtube videos in the middle, need to make sure i block any and all content that could get in my way - caught up on all book revisions so getting super ahead with other chapters - developed an overnight addiction to switching color themes in cursor - did some pair programming w/ Kearm h/eng using Tuple on free trial - applying for O-1

Elliot Arledge

103,006 次观看 • 11 个月前

timelapse #83 (22 hrs): - it was very easy to dive super deep into anything i needed to (this is what i focused on today because not all days are like this) - finding the grok code fast 1 + grok 4 for deep thinking and verification combo to be super useful in cursor. speed was solid - hard to imagine myself spending many more mental clock cycles in a 24 hr period - had to pull out qwen3-next’s gated deltanet + linear attention from bleeding edge hf transformers to begin implementing a multi-gpu fp8 trainer from scratch. this is so damn bleeding edge and i underestimated how much effort this has and will require lol - lots of diet coke and oats - shipped the template which the core chapters of my book will be built on: - all im missing now is flash attention 1/2 mastery (fa2 tmrw), intuition on making topk faster (for arbitrary row length), what i should and shouldnt teach in cutlass/cute, hopper/blackwell gemm kernel mastery (down to fp4) — shoutout to Pranjal for making this easier for me. his blog post is amazing - caught up w/ Mati Roy - im feeling great mentally but not so good physically as im writing this and about to pass out
0:30

timelapse #83 (22 hrs): - it was very easy to dive super deep into anything i needed to (this is what i focused on today because not all days are like this) - finding the grok code fast 1 + grok 4 for deep thinking and verification combo to be super useful in cursor. speed was solid - hard to imagine myself spending many more mental clock cycles in a 24 hr period - had to pull out qwen3-next’s gated deltanet + linear attention from bleeding edge hf transformers to begin implementing a multi-gpu fp8 trainer from scratch. this is so damn bleeding edge and i underestimated how much effort this has and will require lol - lots of diet coke and oats - shipped the template which the core chapters of my book will be built on: - all im missing now is flash attention 1/2 mastery (fa2 tmrw), intuition on making topk faster (for arbitrary row length), what i should and shouldnt teach in cutlass/cute, hopper/blackwell gemm kernel mastery (down to fp4) — shoutout to Pranjal for making this easier for me. his blog post is amazing - caught up w/ Mati Roy - im feeling great mentally but not so good physically as im writing this and about to pass out

Elliot Arledge

2,255,154 次观看 • 1 年前

GROK CODE FAST 1 TAKES #1 ON OPENROUTER, DEVELOPERS PICK REAL PERFORMANCE OVER HYPE Grok Code Fast 1 just locked in the top spot on OpenRouter’s December 2025 monthly leaderboard, and this one actually matters. Real workloads. Real builders choosing what they trust when things break, scale, or need to ship. According to OpenRouter data, Grok Code Fast 1 processed billions of tokens in production, clearing every major competitor. Claude Sonnet 4, GPT-5 variants, Gemini, DeepSeek , all solid models, all left behind. Developers didn’t debate it on X. They just routed traffic. The reasons are practical, not philosophical. Grok Code Fast 1 is fast. Like actually fast. Low latency, massive 2M context window, strong tool calling, and code outputs that don’t collapse the moment you introduce edge cases. What keeps coming up from builders is reliability. Fewer hallucinations. Better memory across long sessions. It doesn’t fight you. It doesn’t nanny you. It just does the work. Yes, the free trial helped drive initial adoption. But free doesn’t explain retention at this scale. People stayed because it worked better for serious tasks, not toy prompts. The bigger signal is this: when you strip away marketing, guardrail theater, and benchmark gaming, developers reward models that prioritize truth, speed, and usefulness. Source: X Freeze, OpenRouter, Grok
0:30

GROK CODE FAST 1 TAKES #1 ON OPENROUTER, DEVELOPERS PICK REAL PERFORMANCE OVER HYPE Grok Code Fast 1 just locked in the top spot on OpenRouter’s December 2025 monthly leaderboard, and this one actually matters. Real workloads. Real builders choosing what they trust when things break, scale, or need to ship. According to OpenRouter data, Grok Code Fast 1 processed billions of tokens in production, clearing every major competitor. Claude Sonnet 4, GPT-5 variants, Gemini, DeepSeek , all solid models, all left behind. Developers didn’t debate it on X. They just routed traffic. The reasons are practical, not philosophical. Grok Code Fast 1 is fast. Like actually fast. Low latency, massive 2M context window, strong tool calling, and code outputs that don’t collapse the moment you introduce edge cases. What keeps coming up from builders is reliability. Fewer hallucinations. Better memory across long sessions. It doesn’t fight you. It doesn’t nanny you. It just does the work. Yes, the free trial helped drive initial adoption. But free doesn’t explain retention at this scale. People stayed because it worked better for serious tasks, not toy prompts. The bigger signal is this: when you strip away marketing, guardrail theater, and benchmark gaming, developers reward models that prioritize truth, speed, and usefulness. Source: X Freeze, OpenRouter, Grok

Mario Nawfal

39,820 次观看 • 8 个月前

BOOMI MY NEW GROK DEVICE! I HAVE Grok ON AN OLD APPLE WATCH MADE IN TO A RETRO IPOD! Still working on it but my goal to have a remote single purpose Grok device has been achieved! With the benefits of posting my grifter slop on to X from this device also (that is another article). And a minimal phone. So how did I do it? First I got this IPod converter kit: it is a beautiful device to hold made of Aluminum. Second I got this app: “Ask Watch AI” it has a free version. Third I got my XAI Grok API Key: Toss a few bucks in the account to fund it. Finally I set up the system by answering questions. This is my first run. I am coding an app for the Apple Watch that will be easier than pressing “done”. I will write a full article on it as soon as I get it done. My goal is to use the cell plan on this Apple Watch and to have a minimal phone and Grok device. Soon these devices will be sent to Starlink. With full Grok Bot and Grok Build. No need for an OS or an App. Obviously this is an Apple Watch but soon it will be a device like this of course with a camera too.
2:16

BOOMI MY NEW GROK DEVICE! I HAVE Grok ON AN OLD APPLE WATCH MADE IN TO A RETRO IPOD! Still working on it but my goal to have a remote single purpose Grok device has been achieved! With the benefits of posting my grifter slop on to X from this device also (that is another article). And a minimal phone. So how did I do it? First I got this IPod converter kit: it is a beautiful device to hold made of Aluminum. Second I got this app: “Ask Watch AI” it has a free version. Third I got my XAI Grok API Key: Toss a few bucks in the account to fund it. Finally I set up the system by answering questions. This is my first run. I am coding an app for the Apple Watch that will be easier than pressing “done”. I will write a full article on it as soon as I get it done. My goal is to use the cell plan on this Apple Watch and to have a minimal phone and Grok device. Soon these devices will be sent to Starlink. With full Grok Bot and Grok Build. No need for an OS or an App. Obviously this is an Apple Watch but soon it will be a device like this of course with a camera too.

Brian Roemmele

33,846 次观看 • 20 天前

In the latest Box AI Enterprise Evaluation, we tested xAI's Grok 4. We have seen how this new model moves beyond surface-level retrieval to tackle sophisticated business logic, perform precise calculations, make inferences based on qualitative patterns, and pinpoint critical contract clauses. 👉 Key Highlights: ↳ When analyzing company financial data, Grok 4 correctly performed multi-step tasks, followed sequential logic, and made accurate calculations to determine gross margins and performance comparisons. ↳ In reviewing information from text passages, Grok 4 showed advanced qualitative reasoning, comparing stylistic elements like tone, perspective, and vocabulary to correctly group passages and identify the number of authors. ↳ It excelled in extracting complex information from contracts, identifying detailed clauses like uncapped liability and profit sharing, as well as analyzing the implications of interdependent terms in agreements. 💡 Why It Matters: ↳ For Legal and Finance teams, Grok 4’s improved ability to handle calculations and interpret complex clauses makes it a powerful tool for in-depth contract review and financial analysis. ↳ For researchers, the model's advanced analytical capabilities can help deconstruct and synthesize information from dense technical papers. 👉 The Takeaway Overall, Grok 4 shows measurable advancement in sequential logic, numerical precision, and domain-specific language understanding. The model’s ability to blend quantitative and qualitative reasoning widens the range of workflows that can be automated inside Box.
2:29

In the latest Box AI Enterprise Evaluation, we tested xAI's Grok 4. We have seen how this new model moves beyond surface-level retrieval to tackle sophisticated business logic, perform precise calculations, make inferences based on qualitative patterns, and pinpoint critical contract clauses. 👉 Key Highlights: ↳ When analyzing company financial data, Grok 4 correctly performed multi-step tasks, followed sequential logic, and made accurate calculations to determine gross margins and performance comparisons. ↳ In reviewing information from text passages, Grok 4 showed advanced qualitative reasoning, comparing stylistic elements like tone, perspective, and vocabulary to correctly group passages and identify the number of authors. ↳ It excelled in extracting complex information from contracts, identifying detailed clauses like uncapped liability and profit sharing, as well as analyzing the implications of interdependent terms in agreements. 💡 Why It Matters: ↳ For Legal and Finance teams, Grok 4’s improved ability to handle calculations and interpret complex clauses makes it a powerful tool for in-depth contract review and financial analysis. ↳ For researchers, the model's advanced analytical capabilities can help deconstruct and synthesize information from dense technical papers. 👉 The Takeaway Overall, Grok 4 shows measurable advancement in sequential logic, numerical precision, and domain-specific language understanding. The model’s ability to blend quantitative and qualitative reasoning widens the range of workflows that can be automated inside Box.

Box

1,973,403 次观看 • 1 年前

Inspired by Grok as a developer and a heavy gamer for over 15 years, I spent some time last week building a few things. Thrilled to unveil my latest creation: an infinite runner game built almost entirely by Grok from xAI! This project showcases the incredible power of AI in game development. Grok handled everything—from designing the game mechanics to writing the code and even helping me debug issues along the way. I brought it to life using some amazing free assets from a treasure trove for indie developers. You can play the game now at Elon Musk, I’d be honored if you checked it out. AI is revolutionizing game development, and Grok is at the forefront with its outstanding capabilities. It’s more than a tool—it’s like a tireless co-developer. Grok grasps complex concepts, provides suggestions, and turns rough ideas into working code fast. For this infinite runner, it crafted smooth player controls, randomized obstacle generation, and an engaging scoring system, letting me focus on the overall vision. And cross_protocol, founded by Henry @CROSS is set to harness AI’s full potential in gaming, pushing the boundaries even further. This is just the beginning. With Grok’s help, I’m planning future projects: 1) Physics-based puzzle game where players tweak gravity and momentum to solve puzzles 2) 2D RPG with deep storytelling and branching dialogue 3) Fast-paced 3D shooter with immersive worlds Each genre requires unique skills, but Grok’s versatility makes it ideal for all of them. It adapts to any challenge—be it physics simulations, character AI, or level design—producing results that could rival a full dev team. AI like Grok is opening up creative doors I couldn’t tackle alone, and I can’t wait to see what’s next. Stay tuned for more.
0:20

Inspired by Grok as a developer and a heavy gamer for over 15 years, I spent some time last week building a few things. Thrilled to unveil my latest creation: an infinite runner game built almost entirely by Grok from xAI! This project showcases the incredible power of AI in game development. Grok handled everything—from designing the game mechanics to writing the code and even helping me debug issues along the way. I brought it to life using some amazing free assets from a treasure trove for indie developers. You can play the game now at Elon Musk, I’d be honored if you checked it out. AI is revolutionizing game development, and Grok is at the forefront with its outstanding capabilities. It’s more than a tool—it’s like a tireless co-developer. Grok grasps complex concepts, provides suggestions, and turns rough ideas into working code fast. For this infinite runner, it crafted smooth player controls, randomized obstacle generation, and an engaging scoring system, letting me focus on the overall vision. And cross_protocol, founded by Henry @CROSS is set to harness AI’s full potential in gaming, pushing the boundaries even further. This is just the beginning. With Grok’s help, I’m planning future projects: 1) Physics-based puzzle game where players tweak gravity and momentum to solve puzzles 2) 2D RPG with deep storytelling and branching dialogue 3) Fast-paced 3D shooter with immersive worlds Each genre requires unique skills, but Grok’s versatility makes it ideal for all of them. It adapts to any challenge—be it physics simulations, character AI, or level design—producing results that could rival a full dev team. AI like Grok is opening up creative doors I couldn’t tackle alone, and I can’t wait to see what’s next. Stay tuned for more.

J

99,803 次观看 • 1 年前

Hey Grok, make $1M, make no mistakes 9 Grok bots to run your marketing 👇 1/ Ads Grok -> Connect Google and Meta in 1 click and say "do it for me" -> Builds creatives, changes targeting, tweaks performance weekly 2/ SEO Grok -> 1-click connect your site or store -> Audits and ships the fixes itself -> No more waiting on a developer and an SEO freelancer to get it done 3/ GEO Grok -> "Show me how I rank by buyer query in ChatGPT and Gemini" -> Then it writes the pages that get you mentioned 4/ Creative Grok -> Trained on 178K labeled Meta ads, tagged by hook, format and performance -> Ships 30+ new creatives a week, because creative is the only alpha left 5/ Ad spy Grok -> See every ad your competitors are running in the Meta Ad Library -> Replicate the winners in 1 click and push them to Meta 6/ CRO Grok -> Connect PostHog and GA4, ask where you lose conversions -> It goes into the page and rewrites it so you stop losing customers 7/ Shopify Grok -> Product pages, collections, metafields, all edited from the chat 8/ ChatGPT Ads Grok -> Ads inside ChatGPT, before your competitors get there 9/ Reporting Grok -> Builds custom dashboards with live data -> And you can make it act on the data itself Our team can help you set it up in the next 24h, comment or DM if you need help!
0:26

Hey Grok, make $1M, make no mistakes 9 Grok bots to run your marketing 👇 1/ Ads Grok -> Connect Google and Meta in 1 click and say "do it for me" -> Builds creatives, changes targeting, tweaks performance weekly 2/ SEO Grok -> 1-click connect your site or store -> Audits and ships the fixes itself -> No more waiting on a developer and an SEO freelancer to get it done 3/ GEO Grok -> "Show me how I rank by buyer query in ChatGPT and Gemini" -> Then it writes the pages that get you mentioned 4/ Creative Grok -> Trained on 178K labeled Meta ads, tagged by hook, format and performance -> Ships 30+ new creatives a week, because creative is the only alpha left 5/ Ad spy Grok -> See every ad your competitors are running in the Meta Ad Library -> Replicate the winners in 1 click and push them to Meta 6/ CRO Grok -> Connect PostHog and GA4, ask where you lose conversions -> It goes into the page and rewrites it so you stop losing customers 7/ Shopify Grok -> Product pages, collections, metafields, all edited from the chat 8/ ChatGPT Ads Grok -> Ads inside ChatGPT, before your competitors get there 9/ Reporting Grok -> Builds custom dashboards with live data -> And you can make it act on the data itself Our team can help you set it up in the next 24h, comment or DM if you need help!

Ira Bodnar

116,797 次观看 • 12 天前

“ xAI team is currently working heavily on coding models. Right now, the main focus is training a specialized coding model that will be both fast and smart. I believe we’ll share it with you guys in a few weeks. That’s exciting. Second ,after coding, we all see that the main weakness of Grok 4 is its multimodal capabilities. In fact, it was so bad that Grok was effectively looking at the world while squinting through glass trying to see blurry features and make sense of them. The most immediate improvement we’re stepping on with the next generation pre trained model is huge gains in image understanding, video understanding, and audio. Right now, the model can hear and see the world just like any of you. And with all the tools and other agents it can talk to, we’re going to see a huge unlock for many different application layers once multimodal agents arrive.” — xAI Team
2:01

“ xAI team is currently working heavily on coding models. Right now, the main focus is training a specialized coding model that will be both fast and smart. I believe we’ll share it with you guys in a few weeks. That’s exciting. Second ,after coding, we all see that the main weakness of Grok 4 is its multimodal capabilities. In fact, it was so bad that Grok was effectively looking at the world while squinting through glass trying to see blurry features and make sense of them. The most immediate improvement we’re stepping on with the next generation pre trained model is huge gains in image understanding, video understanding, and audio. Right now, the model can hear and see the world just like any of you. And with all the tools and other agents it can talk to, we’re going to see a huge unlock for many different application layers once multimodal agents arrive.” — xAI Team

Apurv Kochara

88,142 次观看 • 6 个月前

Introducing my newest app, TethrX, made with Grok 4.5 to access Grok Build on your phone. TethrX connects to Grok Build running on your own computer, so you can start a task from anywhere, follow Grok's reasoning as it works, approve every command before it runs, and review the code it writes. Your code never leaves your machine. The public TestFlight is now open, and a demonstration is below. You pair your phone by scanning a QR code, either on your local network or from anywhere through Tailscale. From there TethrX streams Grok's reasoning, tool calls, command output and file changes as they happen, and asks your approval before anything runs. Plan mode lets you read the plan before the work begins. When a task finishes you can review exactly what changed. TethrX lists the modified files in your project, shows a diff for each one, and lets you commit or discard the work without leaving your phone. The app supports slash commands, including /compact and any skills you have installed, along with voice dictation, queued messages and reusable prompts. Sessions can be searched and organised into folders, and you can pair several computers and switch between them. Siri can start a task or tell you what Grok is doing without opening the app, a home screen widget shows whether Grok is working, and a Live Activity tracks progress on your lock screen and Dynamic Island. Every session reports its context window, token usage and cost, the app can be locked behind Face ID, and your computer is kept awake for as long as a task is running. TethrX requires Grok Build installed and signed in on your computer, together with Node.js 20 or newer. A single command starts the bridge: npx tethrx-bridge TethrX is open source under the Apache License 2.0. Both the iOS client and the local bridge are available here: Grok 4.5 helped a lot, thanks to SpaceXAI for making Grok 4.5 exceptional.
0:27

Introducing my newest app, TethrX, made with Grok 4.5 to access Grok Build on your phone. TethrX connects to Grok Build running on your own computer, so you can start a task from anywhere, follow Grok's reasoning as it works, approve every command before it runs, and review the code it writes. Your code never leaves your machine. The public TestFlight is now open, and a demonstration is below. You pair your phone by scanning a QR code, either on your local network or from anywhere through Tailscale. From there TethrX streams Grok's reasoning, tool calls, command output and file changes as they happen, and asks your approval before anything runs. Plan mode lets you read the plan before the work begins. When a task finishes you can review exactly what changed. TethrX lists the modified files in your project, shows a diff for each one, and lets you commit or discard the work without leaving your phone. The app supports slash commands, including /compact and any skills you have installed, along with voice dictation, queued messages and reusable prompts. Sessions can be searched and organised into folders, and you can pair several computers and switch between them. Siri can start a task or tell you what Grok is doing without opening the app, a home screen widget shows whether Grok is working, and a Live Activity tracks progress on your lock screen and Dynamic Island. Every session reports its context window, token usage and cost, the app can be locked behind Face ID, and your computer is kept awake for as long as a task is running. TethrX requires Grok Build installed and signed in on your computer, together with Node.js 20 or newer. A single command starts the bridge: npx tethrx-bridge TethrX is open source under the Apache License 2.0. Both the iOS client and the local bridge are available here: Grok 4.5 helped a lot, thanks to SpaceXAI for making Grok 4.5 exceptional.

Myrhe𝕩

13,099 次观看 • 1 个月前

"At the Edge of the Galaxy" – Episode 1 I created this video entirely using AI, specifically the Grok Imagine software. I developed the script with Grok . Then I produced it using all the tools available in Grok Grok Imagine , particularly the Agent mode, which saves a tremendous amount of time. I made this video alone, using just a standard computer. I was blown away by the ability to create dialogue that sounds authentic and worlds filled with such lifelike creatures. The consistency of the characters and locations is excellent, and the realism is breathtaking. I don't see what is stopping anyone today from creating a film entirely conceived using AI with Grok Imagine. If you have any questions, please feel free to ask. I will be happy to answer them. If you would like to support my work, the best way to help is to repost the video. Thank you in advance. As it happens, the video is 4 minutes and 20 seconds long (honestly, I didn't do that on purpose)—that ought to bring me good luck, right? Elon Musk
4:20

"At the Edge of the Galaxy" – Episode 1 I created this video entirely using AI, specifically the Grok Imagine software. I developed the script with Grok . Then I produced it using all the tools available in Grok Grok Imagine , particularly the Agent mode, which saves a tremendous amount of time. I made this video alone, using just a standard computer. I was blown away by the ability to create dialogue that sounds authentic and worlds filled with such lifelike creatures. The consistency of the characters and locations is excellent, and the realism is breathtaking. I don't see what is stopping anyone today from creating a film entirely conceived using AI with Grok Imagine. If you have any questions, please feel free to ask. I will be happy to answer them. If you would like to support my work, the best way to help is to repost the video. Thank you in advance. As it happens, the video is 4 minutes and 20 seconds long (honestly, I didn't do that on purpose)—that ought to bring me good luck, right? Elon Musk

Déborah

118,998 次观看 • 2 个月前

ox alpha vs deepseek v4 flash vision vs grok 4.6 vs gemini 3.7 flash vs – on photo-to-3d four vision models got one photograph each and had to rebuild the place inside it as a Three.js scene. twelve scenes, twelve first-try runs, zero console errors the setup: one reference photo per scene, sent as an image on OpenRouter. the prompt never says what is in the picture – no "motel", no "bar", no "gas station". the model has to read the photo and rebuild it: layout, materials, hour of the day, and whatever is around the corner that the frame does not show tasks – three photographs of early-2000s america: 1. a motel at night, neon pylon lit, snow on the ground 2. an old new york tavern interior, tin ceiling, tiled floor 3. an abandoned service station in the california desert, midday sun each scene ships as one self-contained html file, procedural geometry and canvas textures only, no downloads. three timed camera shots, and shot 1 has to reproduce the framing of the reference photo models: xAI grok 4.6, Google DeepMind gemini 3.7 flash, DeepSeek deepseek v4 flash vision exp, and ox alpha – a stealth model on openrouter, free, no lab attached to it yet results: - wall clock, three scenes #1 gemini 3.7 flash – 11m 12s #2 deepseek v4 flash – 15m 20s #3 grok 4.6 – 28m 11s #4 ox alpha – 38m 54s - output tokens #1 gemini 3.7 flash – 77,396 #2 ox alpha – 87,613 #3 grok 4.6 – 105,687 #4 deepseek v4 flash – 127,884 - lines of code shipped #1 ox alpha – 2,090 #2 deepseek v4 flash – 2,291 #3 grok 4.6 – 3,529 #4 gemini 3.7 flash – 3,989 - total price #1 ox alpha – $0.000 #2 deepseek v4 flash – $0.091 #3 gemini 3.7 flash – $0.136 #4 grok 4.6 – $0.697 observations: • grok is 7.7x the price of deepseek. it is the only model that read the light – low sun, real shadows on the station, a cold night on the motel • gemini is the fastest and the least deliberate. 17,158 reasoning tokens against deepseek's 99,172, and it still shipped the most code – 3,989 lines • deepseek thought hardest and rendered plainest. 99,172 reasoning tokens, 5.8x gemini's, spent on layout rather than on light. its motel is the second best in the set for $0.030 • ox alpha is free and reads a photo as well as anything here – it lifted "family units / kitchenettes" off the pylon and redrew it in canvas conclusion: twelve scenes, four models, zero fixes, and the whole run cost $0.924! follow thehype. for 24/7 ai news, analysis and breakdowns
0:36

ox alpha vs deepseek v4 flash vision vs grok 4.6 vs gemini 3.7 flash vs – on photo-to-3d four vision models got one photograph each and had to rebuild the place inside it as a Three.js scene. twelve scenes, twelve first-try runs, zero console errors the setup: one reference photo per scene, sent as an image on OpenRouter. the prompt never says what is in the picture – no "motel", no "bar", no "gas station". the model has to read the photo and rebuild it: layout, materials, hour of the day, and whatever is around the corner that the frame does not show tasks – three photographs of early-2000s america: 1. a motel at night, neon pylon lit, snow on the ground 2. an old new york tavern interior, tin ceiling, tiled floor 3. an abandoned service station in the california desert, midday sun each scene ships as one self-contained html file, procedural geometry and canvas textures only, no downloads. three timed camera shots, and shot 1 has to reproduce the framing of the reference photo models: xAI grok 4.6, Google DeepMind gemini 3.7 flash, DeepSeek deepseek v4 flash vision exp, and ox alpha – a stealth model on openrouter, free, no lab attached to it yet results: - wall clock, three scenes #1 gemini 3.7 flash – 11m 12s #2 deepseek v4 flash – 15m 20s #3 grok 4.6 – 28m 11s #4 ox alpha – 38m 54s - output tokens #1 gemini 3.7 flash – 77,396 #2 ox alpha – 87,613 #3 grok 4.6 – 105,687 #4 deepseek v4 flash – 127,884 - lines of code shipped #1 ox alpha – 2,090 #2 deepseek v4 flash – 2,291 #3 grok 4.6 – 3,529 #4 gemini 3.7 flash – 3,989 - total price #1 ox alpha – $0.000 #2 deepseek v4 flash – $0.091 #3 gemini 3.7 flash – $0.136 #4 grok 4.6 – $0.697 observations: • grok is 7.7x the price of deepseek. it is the only model that read the light – low sun, real shadows on the station, a cold night on the motel • gemini is the fastest and the least deliberate. 17,158 reasoning tokens against deepseek's 99,172, and it still shipped the most code – 3,989 lines • deepseek thought hardest and rendered plainest. 99,172 reasoning tokens, 5.8x gemini's, spent on layout rather than on light. its motel is the second best in the set for $0.030 • ox alpha is free and reads a photo as well as anything here – it lifted "family units / kitchenettes" off the pylon and redrew it in canvas conclusion: twelve scenes, four models, zero fixes, and the whole run cost $0.924! follow thehype. for 24/7 ai news, analysis and breakdowns

thehype.

24,202 次观看 • 20 天前

turns out my habits were only half of it 9 steps to cut your Grok Bot usage by over 50% (if you're on a Cursor plan): 1. open cursor desktop app settings 2. go to the models option in the side menu 3. flip off any models you don't want to be using 4. next, set task models in the top of the page to a model you prefer that's cost efficient (do not leave it on default, this is IMPORTANT) 5. otherwise... your task models could auto set to high and/or fast... that's a more expensive model, and you get billed 2x 6. after, you'll click on the cloud agents option in your side menu, and it'll take you to the cursor web dashboard for your account 7. you will need to scroll down to the preferences section on that page and click on the default model option (again IMPORTANT) 8. set that to a cost efficient model you prefer and don't leave it on default... otherwise your cloud agents may use high and/or fast yet again 9. bonus tip (won't apply to most): lastly click on the spending option in your web dashboard's side menu and also make sure your on-demand usage is not on unlimited and is set to a cap you're comfortable with my token usage has reduced 60% after doing this and I'm sure it'll be different for everyone... but make sure to check this process can be a tad bit confusing too let me know if you need any help!
0:51

turns out my habits were only half of it 9 steps to cut your Grok Bot usage by over 50% (if you're on a Cursor plan): 1. open cursor desktop app settings 2. go to the models option in the side menu 3. flip off any models you don't want to be using 4. next, set task models in the top of the page to a model you prefer that's cost efficient (do not leave it on default, this is IMPORTANT) 5. otherwise... your task models could auto set to high and/or fast... that's a more expensive model, and you get billed 2x 6. after, you'll click on the cloud agents option in your side menu, and it'll take you to the cursor web dashboard for your account 7. you will need to scroll down to the preferences section on that page and click on the default model option (again IMPORTANT) 8. set that to a cost efficient model you prefer and don't leave it on default... otherwise your cloud agents may use high and/or fast yet again 9. bonus tip (won't apply to most): lastly click on the spending option in your web dashboard's side menu and also make sure your on-demand usage is not on unlimited and is set to a cap you're comfortable with my token usage has reduced 60% after doing this and I'm sure it'll be different for everyone... but make sure to check this process can be a tad bit confusing too let me know if you need any help!

klöss

35,455 次观看 • 10 天前

Which LLM reasons best when it doesn't have all the information? Enter LLM Poker Arena to find out. It's a Poker Playing benchmark where top reasoning models play Texas Hold'em poker against each other. Claude Opus 4.5, GPT-5.2, Gemini 2.5 Pro, and Grok 4 all sit at the same table and play full tournaments to see who finishes with the chips. Poker is very different when it comes to reasoning. It has to balance probabilistic reasoning, opponent modeling and make decisions under uncertainty. Poker is an interesting evaluation because it tests reasoning under incomplete information, something most coding benchmarks do not capture. In this tournaments the rules are: - Each LLM starts with $1,000 chips - Small and big blinds start at $25 / $50 - Blinds double every 3 minutes - All models run in their reasoning or thinking modes After the first 5 tournaments: - Claude Opus 4.5 with Thinking has 3 wins - GPT-5.2 has 2 wins - Grok 4 and Gemini 2.5 Pro have 0 wins Early results suggest Claude performs quite well at poker as well. Also five is a very small sample size. Planning to run many more tournaments, publish the full benchmark data and add a prediction market on top of it. Thanks for the suggestion clipz. Much more coming as part of Poker Cities !! This was built on Replit ⠕ using their AI integrations, which made it straightforward to connect Claude, GPT, and Gemini. What model do you think wins after 100 tournaments?
0:22

Which LLM reasons best when it doesn't have all the information? Enter LLM Poker Arena to find out. It's a Poker Playing benchmark where top reasoning models play Texas Hold'em poker against each other. Claude Opus 4.5, GPT-5.2, Gemini 2.5 Pro, and Grok 4 all sit at the same table and play full tournaments to see who finishes with the chips. Poker is very different when it comes to reasoning. It has to balance probabilistic reasoning, opponent modeling and make decisions under uncertainty. Poker is an interesting evaluation because it tests reasoning under incomplete information, something most coding benchmarks do not capture. In this tournaments the rules are: - Each LLM starts with $1,000 chips - Small and big blinds start at $25 / $50 - Blinds double every 3 minutes - All models run in their reasoning or thinking modes After the first 5 tournaments: - Claude Opus 4.5 with Thinking has 3 wins - GPT-5.2 has 2 wins - Grok 4 and Gemini 2.5 Pro have 0 wins Early results suggest Claude performs quite well at poker as well. Also five is a very small sample size. Planning to run many more tournaments, publish the full benchmark data and add a prediction market on top of it. Thanks for the suggestion clipz. Much more coming as part of Poker Cities !! This was built on Replit ⠕ using their AI integrations, which made it straightforward to connect Claude, GPT, and Gemini. What model do you think wins after 100 tournaments?

Anshul Dhawan

32,192 次观看 • 7 个月前

HERMES AGENT SUPPORTS 300+ MODELS. PICKING THE RIGHT ONE PER TASK IS THE DIFFERENCE BETWEEN $5/MONTH AND $50. STARTING OUT: Claude Sonnet 4.6. official recommendation from Nous Research. "the model this project was built and tested with." strong reasoning. reliable tool calling. mid-range pricing. PREMIUM TIER: Claude Opus 4.8. best coding benchmarks available. self-correcting reasoning. catches its own mistakes. 1M context. use for demanding tasks where quality matters. GPT-5.5. #1 Chatbot Arena. #1 GPQA Diamond reasoning (94.1%). #1 creative writing. 2M context. handles entire codebases in one pass. Grok 4.30. the only frontier model with live X firehose access. real-time social data, breaking news, market sentiment. connects via Grok OAuth. no separate API key. Grok-Composer-2.5-Fast (v0.17.0). Cursor's coding model. 200K context. available through your Grok subscription via OAuth. no extra cost if you already pay for Grok. MID-RANGE TIER: Claude Sonnet 4.6. best balance of quality and cost for daily use. strongest prose and tool calling in this tier. Gemini 2.5 Pro. Google Search grounding built in. cites sources. verifies claims. pulls current data. 2M context. best for research-heavy workflows. GPT-4.1. reliable tool calling. solid general reasoning. good middle ground when you need OpenAI compatibility. BUDGET TIER: Claude Haiku 4.5. fastest Anthropic model. cheapest paid Claude option. strong at classification, routing, simple queries. use for auxiliary tasks: compression, vision, web extraction, approval scoring. DeepSeek V4. best cost-to-quality ratio in the market. 90% cache discount on repeated context. use for sub-agents and bulk parallel work. DeepSeek V4 Flash. cheapest paid model worth using. 1M context. MIT license. self-hostable. use for cron jobs, monitoring, routine searches. MiniMax M3. Nous Research and MiniMax collaborating on optimization. 1M context via lightning attention. 59% SWE-Bench Pro. beats several premium models on coding. one of the most-used models inside Hermes. FREE / LOCAL: Qwen 3.5 27B via Ollama. 16GB VRAM. reliable tool calling. best free local model for Hermes as of mid-2026. Qwen 3 8B. 8GB VRAM. fits a $7 VPS. handles routine tasks at zero API cost. Llama 4 Maverick. best open-weight tool calling. 1M context. needs more VRAM but strongest local option. HOW TO ASSIGN MODELS: main model: Desktop app / Dashboard → Models → switch sub-agent model: set in Desktop app, Dashboard, or config.yaml: delegation: model: "deepseek/deepseek-v4" auxiliary models (compression, vision, web extract): Desktop app / Dashboard → Models → Auxiliary Haiku 4.5 or Gemini Flash work well here. saves significantly when your main model is premium. per-profile: each Hermes profile gets its own model. Scout on DeepSeek. Analyst on Sonnet. Briefer on budget model. Coder on Opus. per-cron-job: pin a specific model to any cron job. morning brief on Haiku. deep research on Sonnet. monitoring on DeepSeek Flash. each job uses only the model it needs. per-session: /model deepseek/deepseek-v4-flash hot-swap mid-conversation. no restart needed. FALLBACK CHAINS: if your primary model is unavailable, Hermes automatically switches to the next provider. rate limit or server error = next model in the chain. no failed runs. no manual intervention. set in Desktop app, Dashboard, or config.yaml: fallback_providers: - openrouter - nous - codex PROVIDER PATHS: OPENROUTER: 300+ models under one API key. pay per token. most flexible. NOUS PORTAL: 300+ models + Tool Gateway (web search, image gen, TTS, browser). one OAuth. one subscription. 10% off token-billed providers. CHATGPT SUB: GPT-5.5 + Grok via OAuth. included tokens with $20 subscription. OLLAMA: free. local. private. zero API cost. your hardware only. mix providers across profiles and tasks. Scout on OpenRouter. Analyst on Nous Portal. Coder on ChatGPT sub. Monitor on Ollama. THE RULE: premium for work that needs deep reasoning. mid-range for daily driver tasks. budget for volume and background work. free for monitoring and routine jobs. pricing changes fast. check openrouter ai for current rates before committing. Which is your favourite model and for what task? full 15 levels breakdown in the article 👇
0:51

HERMES AGENT SUPPORTS 300+ MODELS. PICKING THE RIGHT ONE PER TASK IS THE DIFFERENCE BETWEEN $5/MONTH AND $50. STARTING OUT: Claude Sonnet 4.6. official recommendation from Nous Research. "the model this project was built and tested with." strong reasoning. reliable tool calling. mid-range pricing. PREMIUM TIER: Claude Opus 4.8. best coding benchmarks available. self-correcting reasoning. catches its own mistakes. 1M context. use for demanding tasks where quality matters. GPT-5.5. #1 Chatbot Arena. #1 GPQA Diamond reasoning (94.1%). #1 creative writing. 2M context. handles entire codebases in one pass. Grok 4.30. the only frontier model with live X firehose access. real-time social data, breaking news, market sentiment. connects via Grok OAuth. no separate API key. Grok-Composer-2.5-Fast (v0.17.0). Cursor's coding model. 200K context. available through your Grok subscription via OAuth. no extra cost if you already pay for Grok. MID-RANGE TIER: Claude Sonnet 4.6. best balance of quality and cost for daily use. strongest prose and tool calling in this tier. Gemini 2.5 Pro. Google Search grounding built in. cites sources. verifies claims. pulls current data. 2M context. best for research-heavy workflows. GPT-4.1. reliable tool calling. solid general reasoning. good middle ground when you need OpenAI compatibility. BUDGET TIER: Claude Haiku 4.5. fastest Anthropic model. cheapest paid Claude option. strong at classification, routing, simple queries. use for auxiliary tasks: compression, vision, web extraction, approval scoring. DeepSeek V4. best cost-to-quality ratio in the market. 90% cache discount on repeated context. use for sub-agents and bulk parallel work. DeepSeek V4 Flash. cheapest paid model worth using. 1M context. MIT license. self-hostable. use for cron jobs, monitoring, routine searches. MiniMax M3. Nous Research and MiniMax collaborating on optimization. 1M context via lightning attention. 59% SWE-Bench Pro. beats several premium models on coding. one of the most-used models inside Hermes. FREE / LOCAL: Qwen 3.5 27B via Ollama. 16GB VRAM. reliable tool calling. best free local model for Hermes as of mid-2026. Qwen 3 8B. 8GB VRAM. fits a $7 VPS. handles routine tasks at zero API cost. Llama 4 Maverick. best open-weight tool calling. 1M context. needs more VRAM but strongest local option. HOW TO ASSIGN MODELS: main model: Desktop app / Dashboard → Models → switch sub-agent model: set in Desktop app, Dashboard, or config.yaml: delegation: model: "deepseek/deepseek-v4" auxiliary models (compression, vision, web extract): Desktop app / Dashboard → Models → Auxiliary Haiku 4.5 or Gemini Flash work well here. saves significantly when your main model is premium. per-profile: each Hermes profile gets its own model. Scout on DeepSeek. Analyst on Sonnet. Briefer on budget model. Coder on Opus. per-cron-job: pin a specific model to any cron job. morning brief on Haiku. deep research on Sonnet. monitoring on DeepSeek Flash. each job uses only the model it needs. per-session: /model deepseek/deepseek-v4-flash hot-swap mid-conversation. no restart needed. FALLBACK CHAINS: if your primary model is unavailable, Hermes automatically switches to the next provider. rate limit or server error = next model in the chain. no failed runs. no manual intervention. set in Desktop app, Dashboard, or config.yaml: fallback_providers: - openrouter - nous - codex PROVIDER PATHS: OPENROUTER: 300+ models under one API key. pay per token. most flexible. NOUS PORTAL: 300+ models + Tool Gateway (web search, image gen, TTS, browser). one OAuth. one subscription. 10% off token-billed providers. CHATGPT SUB: GPT-5.5 + Grok via OAuth. included tokens with $20 subscription. OLLAMA: free. local. private. zero API cost. your hardware only. mix providers across profiles and tasks. Scout on OpenRouter. Analyst on Nous Portal. Coder on ChatGPT sub. Monitor on Ollama. THE RULE: premium for work that needs deep reasoning. mid-range for daily driver tasks. budget for volume and background work. free for monitoring and routine jobs. pricing changes fast. check openrouter ai for current rates before committing. Which is your favourite model and for what task? full 15 levels breakdown in the article 👇

YanXbt

17,138 次观看 • 2 个月前

‼️🇺🇸 NEW: Using Grok 4, Occam's razor, first-principle reasoning, and primary evidence in our X Space, we were able to isolate the suspicious ANOMALIES surrounding the Epstein-Maxwell Case: 1: No plea deal offered by the government - VERY unusual for the government not to offer ANY kind of deal in exchange for information about accomplices 👀 2: Jury instructed in such a way that it left room for conviction without having to implicate 3rd parties for certain s3x acts 🤨 - Grok then goes on to list out ALL of the inconsistencies throughout the Epstein case that highlight the presence of what seems to be an elite transnational network with damning evidence on each other, with its influence being wielded in the Trump administration TODAY. 👀 Even the legacy AND new media seem to be already infiltrated by the network. This network must be STOPPED. At ALL costs!
16:53

‼️🇺🇸 NEW: Using Grok 4, Occam's razor, first-principle reasoning, and primary evidence in our X Space, we were able to isolate the suspicious ANOMALIES surrounding the Epstein-Maxwell Case: 1: No plea deal offered by the government - VERY unusual for the government not to offer ANY kind of deal in exchange for information about accomplices 👀 2: Jury instructed in such a way that it left room for conviction without having to implicate 3rd parties for certain s3x acts 🤨 - Grok then goes on to list out ALL of the inconsistencies throughout the Epstein case that highlight the presence of what seems to be an elite transnational network with damning evidence on each other, with its influence being wielded in the Trump administration TODAY. 👀 Even the legacy AND new media seem to be already infiltrated by the network. This network must be STOPPED. At ALL costs!

Diligent Denizen 🇺🇸

46,249 次观看 • 1 年前

43 Years Ago Today — On June 3, 1983, WarGames hit theaters and gave us one of the most chilling tech thrillers ever made. A curious kid hacks into a military supercomputer, starts a game of “Global Thermonuclear War,” and nearly triggers the real thing. Matthew Broderick, Ally Sheedy, and that unforgettable countdown… pure 80s perfection. Each year I ask Grok how long it would take for it to simulate the same scenario, last year it was about 10 minutes...with a special conditon, Grok emphasised each year... see below. This year, 2026 on the anniversary of the film, I asked Grok (xAI’s AI) the big question from the film: How long would it take a modern AI like Grok to simulate a full Global Thermonuclear War scenario? Answer: Seconds for high-level insights, minutes for detailed probabilistic simulations — a massive leap from WOPR’s 26+ hours in 1983. Computing power and AI have come that far! Each year Grok after my asking this, Grok concludes with... "Yet the movie’s ultimate lesson remains as true today as it was then: “The only winning move is not to play.”" At least we know Grok won't be starting WWIII... I have seen other Ai's coming out with chilling answers, which don't end well for us... us being humans. Wargames the movie is a rollercoaster ride, that still holds up today. Who else still loves this film?
2:13

43 Years Ago Today — On June 3, 1983, WarGames hit theaters and gave us one of the most chilling tech thrillers ever made. A curious kid hacks into a military supercomputer, starts a game of “Global Thermonuclear War,” and nearly triggers the real thing. Matthew Broderick, Ally Sheedy, and that unforgettable countdown… pure 80s perfection. Each year I ask Grok how long it would take for it to simulate the same scenario, last year it was about 10 minutes...with a special conditon, Grok emphasised each year... see below. This year, 2026 on the anniversary of the film, I asked Grok (xAI’s AI) the big question from the film: How long would it take a modern AI like Grok to simulate a full Global Thermonuclear War scenario? Answer: Seconds for high-level insights, minutes for detailed probabilistic simulations — a massive leap from WOPR’s 26+ hours in 1983. Computing power and AI have come that far! Each year Grok after my asking this, Grok concludes with... "Yet the movie’s ultimate lesson remains as true today as it was then: “The only winning move is not to play.”" At least we know Grok won't be starting WWIII... I have seen other Ai's coming out with chilling answers, which don't end well for us... us being humans. Wargames the movie is a rollercoaster ride, that still holds up today. Who else still loves this film?

Commodore Computer Museum 🕹

16,892 次观看 • 3 个月前

veo 3.1 fast vs seedance 2.0 vs grok imagine vs happyhorse 1.1 four video models pulled from the openrouter video leaderboard by request count this week (skipping the duplicate google/bytedance variants to get four distinct labs): #1 veo 3.1 fast (Google DeepMind) – 45k requests #3 seedance 2.0 (bytedance) – 22k requests #5 grok imagine video (SpaceXAI) – 9k requests #8 happyhorse 1.1 (Alibaba Group) – 4k requests so we tested them. 3 prompts, text-to-video, 16:9 / 720p / 8s, real-player likeness fed in as reference images where the model allowed it. all run via AI/ML API in the run-up to the 2026 world cup final – argentina vs spain – we built three broadcast moments from that tie. each one has to be mechanically correct, not just pretty: • stadium flyover – 80k-seat bowl, argentina vs spain, one continuous descending aerial spiral, tifo + flares, golden-hour / floodlight split • penalty – lamine yamal (spain #19) vs emiliano martínez (argentina keeper): run-up, single strike, full-stretch dive, ball in the net. real faces via reference • free kick – messi 25m out, five-man wall, curl up and over the wall into the top corner. the wall has to face the ball with arms pinned down, like a real wall the takeaway up front: the gap that decides this isn't quality – it's moderation. three of the four refuse to render real footballers' faces (grok was the only one that took every reference), so most of the test had to be reshot "faceless" – camera behind the player. the price spread on top of that is ~4x overall results: cost #1 grok – $1.56 #2 veo 3.1 fast – $3.12 #3 happyhorse – $4.38 #4 seedance 2.0 – $6.00 generation time #1 grok – 4m 16s #2 veo 3.1 fast – 4m 26s #3 happyhorse – 8m 16s #4 seedance 2.0 – 10m 38s avg bitrate (picture density) #1 grok – 12.0 mbps #2 veo 3.1 fast – 11.1 mbps #3 happyhorse – 7.4 mbps #4 seedance 2.0 – 5.3 mbps real faces allowed ✅ grok – took every reference ❌ happyhorse – yamal ok, messi blocked ❌ veo – blocked ❌ seedance – blocked observations: 1. moderation is the whole story. three of the four blocked at least one real face – veo and seedance refused every reference outright, happyhorse took yamal but rejected messi. only grok rendered all of them. everything else had to be shot from behind so no face shows 2. grok is the outlier: cheapest, densest picture, fastest, and the only one that renders real faces. it won on every axis that mattered here 3. seedance is the anti-grok – 4x the cost, 2.5x the time, half the bitrate, and no real faces. worst value in the set 4. none of them understand football out of the box follow thehype. for 24/7 ai news, analysis and breakdowns
0:23

veo 3.1 fast vs seedance 2.0 vs grok imagine vs happyhorse 1.1 four video models pulled from the openrouter video leaderboard by request count this week (skipping the duplicate google/bytedance variants to get four distinct labs): #1 veo 3.1 fast (Google DeepMind) – 45k requests #3 seedance 2.0 (bytedance) – 22k requests #5 grok imagine video (SpaceXAI) – 9k requests #8 happyhorse 1.1 (Alibaba Group) – 4k requests so we tested them. 3 prompts, text-to-video, 16:9 / 720p / 8s, real-player likeness fed in as reference images where the model allowed it. all run via AI/ML API in the run-up to the 2026 world cup final – argentina vs spain – we built three broadcast moments from that tie. each one has to be mechanically correct, not just pretty: • stadium flyover – 80k-seat bowl, argentina vs spain, one continuous descending aerial spiral, tifo + flares, golden-hour / floodlight split • penalty – lamine yamal (spain #19) vs emiliano martínez (argentina keeper): run-up, single strike, full-stretch dive, ball in the net. real faces via reference • free kick – messi 25m out, five-man wall, curl up and over the wall into the top corner. the wall has to face the ball with arms pinned down, like a real wall the takeaway up front: the gap that decides this isn't quality – it's moderation. three of the four refuse to render real footballers' faces (grok was the only one that took every reference), so most of the test had to be reshot "faceless" – camera behind the player. the price spread on top of that is ~4x overall results: cost #1 grok – $1.56 #2 veo 3.1 fast – $3.12 #3 happyhorse – $4.38 #4 seedance 2.0 – $6.00 generation time #1 grok – 4m 16s #2 veo 3.1 fast – 4m 26s #3 happyhorse – 8m 16s #4 seedance 2.0 – 10m 38s avg bitrate (picture density) #1 grok – 12.0 mbps #2 veo 3.1 fast – 11.1 mbps #3 happyhorse – 7.4 mbps #4 seedance 2.0 – 5.3 mbps real faces allowed ✅ grok – took every reference ❌ happyhorse – yamal ok, messi blocked ❌ veo – blocked ❌ seedance – blocked observations: 1. moderation is the whole story. three of the four blocked at least one real face – veo and seedance refused every reference outright, happyhorse took yamal but rejected messi. only grok rendered all of them. everything else had to be shot from behind so no face shows 2. grok is the outlier: cheapest, densest picture, fastest, and the only one that renders real faces. it won on every axis that mattered here 3. seedance is the anti-grok – 4x the cost, 2.5x the time, half the bitrate, and no real faces. worst value in the set 4. none of them understand football out of the box follow thehype. for 24/7 ai news, analysis and breakdowns

thehype.

15,453 次观看 • 1 个月前

This is something no other AI and no other car company can do right now, except Grok, fully integrated with FSD (Supervised) v14.2.25. Today, I gave it a wild, real-world task: • Drive to Apple HQ • Then Tesla Engineering HQ • Then a Warriors game at Chase Center SF • Then the beach • Then Asian dinner It got it all ready from the beginning. Mid-route I said I really needed to use the bathroom! It added it as the first stop. Then I added a Tesla Supercharger on the fly for after the Warriors game. It added it. AND stopped for grandparents and baby crossing the street. Then I asked for the weather and exactly how much I should $ budget for the entire day. No friction. No talking back. Just getting it done insanely fast. It just handled it all naturally, intelligently, all in real time. Better than any driver, for sure… This is reasoning + autonomy + AI + real life, all working beautifully in synch. No other car, AI, is close to this capability imo. This is a MAJOR update. I honestly feel if this was any other company, they would’ve had a whole event just to showcase this feature.
2:54

This is something no other AI and no other car company can do right now, except Grok, fully integrated with FSD (Supervised) v14.2.25. Today, I gave it a wild, real-world task: • Drive to Apple HQ • Then Tesla Engineering HQ • Then a Warriors game at Chase Center SF • Then the beach • Then Asian dinner It got it all ready from the beginning. Mid-route I said I really needed to use the bathroom! It added it as the first stop. Then I added a Tesla Supercharger on the fly for after the Warriors game. It added it. AND stopped for grandparents and baby crossing the street. Then I asked for the weather and exactly how much I should $ budget for the entire day. No friction. No talking back. Just getting it done insanely fast. It just handled it all naturally, intelligently, all in real time. Better than any driver, for sure… This is reasoning + autonomy + AI + real life, all working beautifully in synch. No other car, AI, is close to this capability imo. This is a MAJOR update. I honestly feel if this was any other company, they would’ve had a whole event just to showcase this feature.

Teslaconomics

258,326 次观看 • 9 个月前

I cant believe this guy just made a permanent solution to context bloat and open sourced it all! when we tested this tool (Context+) for solving an issue on the OpenCode repository, the agent using this tool used ~6.5k fewer tokens, found the code and fixed it in half the time! the results were surprising: 6 to 10k tokens saved per prompt, completed task in ~2 minutes while the agent running without the tool took ~4 mins for the same and got stuck in loops bro built an entire beast by using all the modern tools that we could think of: undo trees, semantic search by meaning (by haskellforall), advanced refactoring, blast radius, advanced file context trees, restore points... i can keep going on semantic code search and context trees are the future of agentic coding and this tool proves it the feature i loved the most is semantic search and how it gets things done 2x faster with least possible tokens it makes an agent that actually knows what it’s doing and not just guessing, it makes meaning from your code similar to RAG. if you aren't optimizing your context, you are just burning money the developer says this tool is still under development, it can have unexpected behavior and the docs need updates but the video shows the reality of how fast it can be github: get here:
0:46

I cant believe this guy just made a permanent solution to context bloat and open sourced it all! when we tested this tool (Context+) for solving an issue on the OpenCode repository, the agent using this tool used ~6.5k fewer tokens, found the code and fixed it in half the time! the results were surprising: 6 to 10k tokens saved per prompt, completed task in ~2 minutes while the agent running without the tool took ~4 mins for the same and got stuck in loops bro built an entire beast by using all the modern tools that we could think of: undo trees, semantic search by meaning (by haskellforall), advanced refactoring, blast radius, advanced file context trees, restore points... i can keep going on semantic code search and context trees are the future of agentic coding and this tool proves it the feature i loved the most is semantic search and how it gets things done 2x faster with least possible tokens it makes an agent that actually knows what it’s doing and not just guessing, it makes meaning from your code similar to RAG. if you aren't optimizing your context, you are just burning money the developer says this tool is still under development, it can have unexpected behavior and the docs need updates but the video shows the reality of how fast it can be github: get here:

forloop

226,271 次观看 • 6 个月前