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🟢 News: GPU compute in the browser is finally real. WebGPU now ships by default in Chrome, Firefox, Safari, and Edge—not a polyfill, not behind a flag. You can run LLMs client-side. Transformers.js and ONNX Runtime already ship WebGPU backends. Eight years of spec work. No more asterisks. 🔗...

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WebGL / WebGPU

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12,788 Aufrufe • vor 6 Monaten •via X (Twitter)

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Dustin

22,390 Aufrufe • vor 1 Monat

The Visual Studio Code insiders version that just shipped and will ship in the next few days will come with an insane amount of new capabilities. A few highlights: - You can now run sub-agents in parallel. Yes, really. I even attached a video. - Major UX improvements for sub agents, especially visible in the chat window - A new search tool wrapped as a sub-agent that iteratively runs multiple search tools: semantic_search, file_search, grep_search Which connects nicely to the point above: multiple searches running in parallel, efficiently and fast - Anthropic’s Message API is now enabled by default - You can choose the model for the cloud agent (three available, all premium) - Extended thinking support when using the Claude cloud agent This is part of the broader multi-vendor cloud support under AgentsHQ I wrote about a few weeks ago - Tasks sent to the background agent (basically the CLI tool) now always run in isolation, each with its own git worktree - In a multi-repo workspace, assigning a task to a cloud agent prompts you to choose the target repo Same behavior when opening an empty workspace with no repo - Support for building an external index for files not supported by GitHub’s default indexing - UI/UX improvements for starting new sessions and switching between local / background / cloud agents - Skills are now first-class citizens, just like prompt files, with better UX indicating when a skill is loaded - Improved API for dynamic contribution of prompt files New V2 includes skills as part of the model. Curious to see the extensions that will leverage this - Finally, initial support for showing context usage percentage per session - Skills are enabled by default - Resizable chat window and session view. Small thing, but it was driving me crazy 😁 - A new integrated browser meant to replace the old simple browser Maybe the beginning of real browser use? - Better UI/UX for token streaming in chat - Ability to index external files not supported by GitHub There’s a lot more. Some of it hasn’t fully landed yet, but everything that has is already in Insiders. The next stable release should drop in early February. As usual, I’m just shocked by the volume of features this team ships every month. After the holiday slowdown, this one is shaping up to be a wild release.
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The Visual Studio Code insiders version that just shipped and will ship in the next few days will come with an insane amount of new capabilities. A few highlights: - You can now run sub-agents in parallel. Yes, really. I even attached a video. - Major UX improvements for sub agents, especially visible in the chat window - A new search tool wrapped as a sub-agent that iteratively runs multiple search tools: semantic_search, file_search, grep_search Which connects nicely to the point above: multiple searches running in parallel, efficiently and fast - Anthropic’s Message API is now enabled by default - You can choose the model for the cloud agent (three available, all premium) - Extended thinking support when using the Claude cloud agent This is part of the broader multi-vendor cloud support under AgentsHQ I wrote about a few weeks ago - Tasks sent to the background agent (basically the CLI tool) now always run in isolation, each with its own git worktree - In a multi-repo workspace, assigning a task to a cloud agent prompts you to choose the target repo Same behavior when opening an empty workspace with no repo - Support for building an external index for files not supported by GitHub’s default indexing - UI/UX improvements for starting new sessions and switching between local / background / cloud agents - Skills are now first-class citizens, just like prompt files, with better UX indicating when a skill is loaded - Improved API for dynamic contribution of prompt files New V2 includes skills as part of the model. Curious to see the extensions that will leverage this - Finally, initial support for showing context usage percentage per session - Skills are enabled by default - Resizable chat window and session view. Small thing, but it was driving me crazy 😁 - A new integrated browser meant to replace the old simple browser Maybe the beginning of real browser use? - Better UI/UX for token streaming in chat - Ability to index external files not supported by GitHub There’s a lot more. Some of it hasn’t fully landed yet, but everything that has is already in Insiders. The next stable release should drop in early February. As usual, I’m just shocked by the volume of features this team ships every month. After the holiday slowdown, this one is shaping up to be a wild release.

Oren Melamed

29,555 Aufrufe • vor 7 Monaten

claude fable 5 is live. spawn 5.0 was built with it: 1,687 prompts, 102 sessions, my job shifted from architecture to judging taste. what we built, each of which would've been at least a month with a whole team on opus: — a from-scratch physics engine (mantle) that rivals rapier, testable in a day as a side thread — clustered froxel lighting: 8 lights to 1,000+ fully dynamic ("it's stupid fast" — creator of threejs) — realtime diffuse GI on webgpu, on your phone (landing in the next update) — million-particle gpu vfx with a shader architecture beyond what unreal and unity ship — mmo-scale netcode plus, for good measure: an (alpha) native ios app. all of it in about a week. all of it running on mobile. and the list doesn't include half of what we shipped — full changelog in the thread below. and the part the benchmarks won't show you: this model has a wonderful personality. it's genuinely funny. i laughed so hard i cried multiple times, mid-physics-rewrite. the genius and the character aren't separate features.
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claude fable 5 is live. spawn 5.0 was built with it: 1,687 prompts, 102 sessions, my job shifted from architecture to judging taste. what we built, each of which would've been at least a month with a whole team on opus: — a from-scratch physics engine (mantle) that rivals rapier, testable in a day as a side thread — clustered froxel lighting: 8 lights to 1,000+ fully dynamic ("it's stupid fast" — creator of threejs) — realtime diffuse GI on webgpu, on your phone (landing in the next update) — million-particle gpu vfx with a shader architecture beyond what unreal and unity ship — mmo-scale netcode plus, for good measure: an (alpha) native ios app. all of it in about a week. all of it running on mobile. and the list doesn't include half of what we shipped — full changelog in the thread below. and the part the benchmarks won't show you: this model has a wonderful personality. it's genuinely funny. i laughed so hard i cried multiple times, mid-physics-rewrite. the genius and the character aren't separate features.

jacob

55,515 Aufrufe • vor 2 Monaten

OptimAI Lite Node v1.1: Built for Scale, Designed for You! 💕 In just 2 weeks since the launch, the OptimAI Network has seen explosive growth—130,000+ active node participants powering the future of decentralized AI. With this incredible momentum came a new challenge: ensuring our network could scale seamlessly to support massive concurrent connections and real-time participation. That’s why we’ve rolled out OptimAI Lite Node v1.1—a major upgrade focused on: + Stabilizing infrastructure to handle high traffic from a global community. + Enhancing performance for smoother data mining, validation, and edge compute participation. + Refining user experience with UI updates that make contributing effortless. Every line of code and infrastructure upgrade was made with one goal in mind: to support YOU—the builders, validators, and visionaries of the OptimAI ecosystem. Now’s the time to bring more friends into the journey. 🔥 The more we grow, the smarter and stronger the network becomes—and the greater the rewards. Let’s keep building, validating, scaling. Together we’re not just powering AI—we’re reshaping how it’s built. Join or revisit the node here: 🌐 Chrome Extension: 📱Telegram Mini-App: What’s Coming Next: OptimAI Edge Node & the Rise of Agentic AI 🔸OptimAI Edge Node (Mobile) We’re working hard on the next major release: the Edge Node for mobile, which will allow mining and AI tasks to run in the background—unlocking more earning opportunities and decentralized compute power from your smartphones. 🔸More Task Types & Missions Expect new types of contributions, from AI-enhanced data validation to edge inference and scraping automation—powered by autonomous mining agents. 🔸Expanded Rewards Program As we grow, more reward tiers, bonuses, and campaigns will be introduced. Your participation now paves the way for long-term benefits. Also, do not forget to checkout our article below and learn more about our latest Community Tips & Best Practices!👇 __________________ OptimAI Network #L2 #DePIN Reinforcement Data Network for #Agentic #AI Mine Data. Fuel AI. Earn Rewards. Turn Your Data into Tomorrow’s AI #Agent. Visit our website at:
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OptimAI Lite Node v1.1: Built for Scale, Designed for You! 💕 In just 2 weeks since the launch, the OptimAI Network has seen explosive growth—130,000+ active node participants powering the future of decentralized AI. With this incredible momentum came a new challenge: ensuring our network could scale seamlessly to support massive concurrent connections and real-time participation. That’s why we’ve rolled out OptimAI Lite Node v1.1—a major upgrade focused on: + Stabilizing infrastructure to handle high traffic from a global community. + Enhancing performance for smoother data mining, validation, and edge compute participation. + Refining user experience with UI updates that make contributing effortless. Every line of code and infrastructure upgrade was made with one goal in mind: to support YOU—the builders, validators, and visionaries of the OptimAI ecosystem. Now’s the time to bring more friends into the journey. 🔥 The more we grow, the smarter and stronger the network becomes—and the greater the rewards. Let’s keep building, validating, scaling. Together we’re not just powering AI—we’re reshaping how it’s built. Join or revisit the node here: 🌐 Chrome Extension: 📱Telegram Mini-App: What’s Coming Next: OptimAI Edge Node & the Rise of Agentic AI 🔸OptimAI Edge Node (Mobile) We’re working hard on the next major release: the Edge Node for mobile, which will allow mining and AI tasks to run in the background—unlocking more earning opportunities and decentralized compute power from your smartphones. 🔸More Task Types & Missions Expect new types of contributions, from AI-enhanced data validation to edge inference and scraping automation—powered by autonomous mining agents. 🔸Expanded Rewards Program As we grow, more reward tiers, bonuses, and campaigns will be introduced. Your participation now paves the way for long-term benefits. Also, do not forget to checkout our article below and learn more about our latest Community Tips & Best Practices!👇 __________________ OptimAI Network #L2 #DePIN Reinforcement Data Network for #Agentic #AI Mine Data. Fuel AI. Earn Rewards. Turn Your Data into Tomorrow’s AI #Agent. Visit our website at:

OptimAI Network

76,453 Aufrufe • vor 1 Jahr

THE CLOUD BILL WAS $14,000 A MONTH. EVERY MONTH. JUST FOR GPU ACCESS. No ownership. No hardware. Just renting someone else's chips and watching the invoice grow. So this startup did the math and bought 1,000 Mac Mini M4s instead. $599 each. One-time. Total: ~$599,000 upfront. Sounds insane. Until you do the math the other way. $14K/mo in cloud GPUs is $168K a year. In 3.5 years you've burned through $599K and own nothing. The meter just keeps running. These guys own the hardware. Same output. Less power draw. And after year 4, every month of compute is basically free. The M4 was never built for data centers. But its performance per watt is so good that someone looked at a rack of a thousand of them and thought "why not." That's when it clicks. The AI infrastructure race isn't about who has the biggest GPU anymore. It's about who figured out they were overpaying for one. Would you make this switch?
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THE CLOUD BILL WAS $14,000 A MONTH. EVERY MONTH. JUST FOR GPU ACCESS. No ownership. No hardware. Just renting someone else's chips and watching the invoice grow. So this startup did the math and bought 1,000 Mac Mini M4s instead. $599 each. One-time. Total: ~$599,000 upfront. Sounds insane. Until you do the math the other way. $14K/mo in cloud GPUs is $168K a year. In 3.5 years you've burned through $599K and own nothing. The meter just keeps running. These guys own the hardware. Same output. Less power draw. And after year 4, every month of compute is basically free. The M4 was never built for data centers. But its performance per watt is so good that someone looked at a rack of a thousand of them and thought "why not." That's when it clicks. The AI infrastructure race isn't about who has the biggest GPU anymore. It's about who figured out they were overpaying for one. Would you make this switch?

Framez

18,004 Aufrufe • vor 10 Tagen

SEVEN RTX 3090S IN A WATER TANK FOR AI SERVER it is a private AI server with the power bill moved into your room. not a clean Mac mini. not a quiet box under a monitor. loose vertical GPUs sit inside a transparent tank. bubbles rise through distilled water. ALLIED CONTROL is printed on the side. it looks closer to a lab accident than a normal workstation. but the logic is obvious: seven RTX 3090s = seven 24GB cards. that is the used-market shortcut for people who want local inference without paying cloud tax on every run. put Ollama, llama.cpp, vLLM, Open WebUI, Tailscale, Qwen, DeepSeek, or Llama on top. now the box can handle client files, code agents, scraping jobs, evals, transcription, and boring overnight work. not because it beats frontier cloud models. because it changes the bill shape. no rate limit. no per-token anxiety. no sensitive client context leaving the building. no monthly stack quietly turning into rent. the ugly part is physical. seven 3090s can pull serious power, dump serious heat, and punish lazy cooling. distilled water is the weird visual, not a setup tip. real immersion rigs live or die on coolant chemistry, insulation, pumps, maintenance, and whether the room can handle the heat. local AI PCs are becoming less like gaming builds and more like small private data centers. the early question is not: can it run ChatGPT? it is: what work is repetitive, private, expensive in the cloud, and worth owning in hardware?
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SEVEN RTX 3090S IN A WATER TANK FOR AI SERVER it is a private AI server with the power bill moved into your room. not a clean Mac mini. not a quiet box under a monitor. loose vertical GPUs sit inside a transparent tank. bubbles rise through distilled water. ALLIED CONTROL is printed on the side. it looks closer to a lab accident than a normal workstation. but the logic is obvious: seven RTX 3090s = seven 24GB cards. that is the used-market shortcut for people who want local inference without paying cloud tax on every run. put Ollama, llama.cpp, vLLM, Open WebUI, Tailscale, Qwen, DeepSeek, or Llama on top. now the box can handle client files, code agents, scraping jobs, evals, transcription, and boring overnight work. not because it beats frontier cloud models. because it changes the bill shape. no rate limit. no per-token anxiety. no sensitive client context leaving the building. no monthly stack quietly turning into rent. the ugly part is physical. seven 3090s can pull serious power, dump serious heat, and punish lazy cooling. distilled water is the weird visual, not a setup tip. real immersion rigs live or die on coolant chemistry, insulation, pumps, maintenance, and whether the room can handle the heat. local AI PCs are becoming less like gaming builds and more like small private data centers. the early question is not: can it run ChatGPT? it is: what work is repetitive, private, expensive in the cloud, and worth owning in hardware?

kocer

591,404 Aufrufe • vor 1 Monat