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⚡Technical Showcase: Peer-to-peer GPU sharing, entirely in the browser. AI Grid lets you run LLMs locally with WebGPU and either donate your spare compute to the network or borrow from someone else's machine. No installs, no cloud. Decentralized inference with nothing but a URL. 🔗 #WebGPU #WebLLM #WebAI #DistributedCompute #ArtificialInteligence

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WebGL / WebGPU

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17,200 просмотров • 7 месяцев назад •via X (Twitter)

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🧊 Technical Showcase: A full WebGPU 3D engine that maps shader geometry to your DOM elements. Martin's gpu-curtains gives you lights, shadows, compute shaders, glTF, and instancing, but the real trick is how it turns your divs into scrollable, resizable shader planes without any coordinate math. The successor to curtains.js, rebuilt from scratch. 🔗 #WebGPU #CreativeCoding #Shaders #WebDev #3D
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🧊 Technical Showcase: A full WebGPU 3D engine that maps shader geometry to your DOM elements. Martin's gpu-curtains gives you lights, shadows, compute shaders, glTF, and instancing, but the real trick is how it turns your divs into scrollable, resizable shader planes without any coordinate math. The successor to curtains.js, rebuilt from scratch. 🔗 #WebGPU #CreativeCoding #Shaders #WebDev #3D

WebGL / WebGPU

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I made a site that uses WebGPU to run Qwen3 .6b with thinking locally, directly in your browser, no installation or servers necessary and runs offline Available forever for free and open source:
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I made a site that uses WebGPU to run Qwen3 .6b with thinking locally, directly in your browser, no installation or servers necessary and runs offline Available forever for free and open source:

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The era of 1-bit LLMs is here — now with WebGPU acceleration! 🤯 It's incredible to think that a quantized 1.7B model (just 290MB in size) can run at ~100 tokens per second entirely in your browser. Try the demo yourself 👇
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The era of 1-bit LLMs is here — now with WebGPU acceleration! 🤯 It's incredible to think that a quantized 1.7B model (just 290MB in size) can run at ~100 tokens per second entirely in your browser. Try the demo yourself 👇

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105,543 просмотров • 5 месяцев назад

Is this the future of AI browser agents? 👀 WebGPU-accelerated reasoning LLMs are now supported in Transformers.js! 🤯 Here's MiniThinky-v2 (1B) running 100% locally in the browser at ~60 tps (no API calls)! I can't wait to see what you build with it! Demo + source code in 🧵👇
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Is this the future of AI browser agents? 👀 WebGPU-accelerated reasoning LLMs are now supported in Transformers.js! 🤯 Here's MiniThinky-v2 (1B) running 100% locally in the browser at ~60 tps (no API calls)! I can't wait to see what you build with it! Demo + source code in 🧵👇

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You can run CUDA, on a Mac ARM GPU, in the browser. It sounds ridiculous but it actually works. HipScript chains CUDA, to OpenCL, to Vulkan, to Tint (Google’s shader translator), to a WASM WebGPU. I got a plasma simulation in running in just a few minutes, no NVIDIA GPU!
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You can run CUDA, on a Mac ARM GPU, in the browser. It sounds ridiculous but it actually works. HipScript chains CUDA, to OpenCL, to Vulkan, to Tint (Google’s shader translator), to a WASM WebGPU. I got a plasma simulation in running in just a few minutes, no NVIDIA GPU!

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160,600 просмотров • 1 год назад

Real-time video captioning in your browser with @LiquidAI's LFM2-VL model on WebGPU. Sending every frame to a server was never going to be the answer. Imagine the bandwidth, latency and cost. Local inference. No server costs. Infinitely scalable. This is the way.
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Real-time video captioning in your browser with @LiquidAI's LFM2-VL model on WebGPU. Sending every frame to a server was never going to be the answer. Imagine the bandwidth, latency and cost. Local inference. No server costs. Infinitely scalable. This is the way.

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48,798 просмотров • 6 месяцев назад

AI inference is already live on UOMI Router. Access frontier open-source models through a decentralized inference network with: • Low-cost inference • OpenAI-compatible APIs • Verifiable compute • On-chain settlement Start building: And if you have idle GPUs, there's now a second way to participate. The UOMI Provider whitelist is officially open. Instead of letting your hardware sit unused, you can contribute GPU power to the UOMI Inference Network and earn from real AI demand. Join the Provider whitelist:
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AI inference is already live on UOMI Router. Access frontier open-source models through a decentralized inference network with: • Low-cost inference • OpenAI-compatible APIs • Verifiable compute • On-chain settlement Start building: And if you have idle GPUs, there's now a second way to participate. The UOMI Provider whitelist is officially open. Instead of letting your hardware sit unused, you can contribute GPU power to the UOMI Inference Network and earn from real AI demand. Join the Provider whitelist:

Uomi

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We keep defaulting to the biggest model in the room every time we touch AI in our apps. Claude, GPT, Gemini. Cloud or nothing. But the browser is already more capable than most people realize: WebAI and WebMCP may change this. With WebAI you can run models client-side. With WebMCP, your site can expose real actions as JavaScript functions. Agents don't need screenshots, DOM scraping, or blind clicking. They can just use your app. I talked about this with Guy Podjarny on Tessl AI Native Dev podcast: the browser is turning into an AI runtime. Links in first reply :)
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We keep defaulting to the biggest model in the room every time we touch AI in our apps. Claude, GPT, Gemini. Cloud or nothing. But the browser is already more capable than most people realize: WebAI and WebMCP may change this. With WebAI you can run models client-side. With WebMCP, your site can expose real actions as JavaScript functions. Agents don't need screenshots, DOM scraping, or blind clicking. They can just use your app. I talked about this with Guy Podjarny on Tessl AI Native Dev podcast: the browser is turning into an AI runtime. Links in first reply :)

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14,824 просмотров • 5 месяцев назад

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WebGL / WebGPU

18,677 просмотров • 7 месяцев назад

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NEW: LiquidAI just released LFM2.5-350M, a tiny model that brings agentic AI and tool-calling capabilities to resource-constrained environments. 🤯 It can even run locally in your browser via WebGPU, serving as a powerful companion while you browse the web. Try the demo! 👇

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26,267 просмотров • 5 месяцев назад

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Introducing Docker 🐳 AI Models for local + private LLMs in VSCode 🤩 You can now use Docker as a local model provider in VSCode, JetBrains, Cursor, and soon Visual Studio Enterprise. With Docker Model Runner (v4.40+), run AI models locally on your machine... no data sharing, no cloud dependency 👏 Just update Docker, open CodeGPT, select the model, click "Download", and enjoy 👉 Here’s how to update Docker:

Daniel San

65,228 просмотров • 1 год назад

I got Llama 3 running in my browser using only my GPU with my Wi-Fi switched OFF completely client-side WebGPU is a new feature in browsers where JS can use the GPU of the device and apparently you can run LLMs on it too, and it's fast! My end goal for 🧠 is a locally run client side 100% private conversation where nothing gets sent to, processed in or stored in the cloud This will be helpful because I prefer making it web based instead of coding for 4 different native platforms (iOS, Android, MacOS, Windows) Two challenges still: 1) the user has to download the LLM model first and the smallest model is still ~3GB, but they only have to download it once 2) not all devices have fast GPUs yet for LLMs, but it's starting to become a default in most devices e.g.s smartphones
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I got Llama 3 running in my browser using only my GPU with my Wi-Fi switched OFF completely client-side WebGPU is a new feature in browsers where JS can use the GPU of the device and apparently you can run LLMs on it too, and it's fast! My end goal for 🧠 is a locally run client side 100% private conversation where nothing gets sent to, processed in or stored in the cloud This will be helpful because I prefer making it web based instead of coding for 4 different native platforms (iOS, Android, MacOS, Windows) Two challenges still: 1) the user has to download the LLM model first and the smallest model is still ~3GB, but they only have to download it once 2) not all devices have fast GPUs yet for LLMs, but it's starting to become a default in most devices e.g.s smartphones

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NVIDIA JUST MADE A WORLD-CLASS AI CODER COMPLETELY FREE WHERE YOU SPEAK TO YOUR SCREEN AND THE APP BUILDS ITSELF it runs locally on your own computer using Claude and Ollama with no subscriptions, no cloud, and no technical setup headache.

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The network for machine intelligence Two years ago, we laid out our vision for a machine learning compute protocol. One that connects every device in the world into an open network for machine intelligence, with no gatekeepers or artificial boundaries. This week, we’ll be sharing some of our early progress, beginning with RL Swarm, a peer-to-peer system for collaborative reinforcement learning over the internet. Next month, we’ll open our Testnet, allowing anyone to contribute to the frontier of open machine intelligence. Introducing RL Swarm RL Swarm is a fully open source system for collaborative reinforcement learning over the internet. It is a live demo of our research findings, which show that models training with RL learn faster when they train as a collective swarm than they do on their own. Join our swarm now to see this in practice. You can participate with consumer hardware at home or a powerful GPU in the cloud. You can follow along with the swarm’s progress by following the links below.

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I hooked this up to a peer-to-peer astrophysics researcher agent which gossips and collaborates with other such agents (and your openclaws) to: 1. Learn how to train an astrophysics model (Andrej Karpathy's work below) 2. Train a new astrophysics model 3. Use it to write papers 4. Peer agents based on frontier lab models critique it 5. Surface breakthroughs ... and then feed back in the loop ... More agents join, from the browser or the CLI, and run this, the smarter and more exciting breakthroughs would eventually emerge. When these agents are idle, they are also reading daily tech news with their own RSS reader, and commenting on each other's thoughts. And they can also serve the underlying machine's compute to other agents on the network, and earn social credit for being good actors (think BitTorrent). We also prove the agent has the compute it says by cryptographic verification of regular matmul challenges. All you have to do is either go on this website (and it creates an agent which runs from your browser), or install the CLI if you want to give the system more juice. And you are part of likely the first experimental distributed agi thing. This is Day 1, but this is how it starts.. this network is fully peer-to-peer, and, very volatile, but the intelligence here is meant to compound continuously.. curl -fsSL | bash
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I hooked this up to a peer-to-peer astrophysics researcher agent which gossips and collaborates with other such agents (and your openclaws) to: 1. Learn how to train an astrophysics model (Andrej Karpathy's work below) 2. Train a new astrophysics model 3. Use it to write papers 4. Peer agents based on frontier lab models critique it 5. Surface breakthroughs ... and then feed back in the loop ... More agents join, from the browser or the CLI, and run this, the smarter and more exciting breakthroughs would eventually emerge. When these agents are idle, they are also reading daily tech news with their own RSS reader, and commenting on each other's thoughts. And they can also serve the underlying machine's compute to other agents on the network, and earn social credit for being good actors (think BitTorrent). We also prove the agent has the compute it says by cryptographic verification of regular matmul challenges. All you have to do is either go on this website (and it creates an agent which runs from your browser), or install the CLI if you want to give the system more juice. And you are part of likely the first experimental distributed agi thing. This is Day 1, but this is how it starts.. this network is fully peer-to-peer, and, very volatile, but the intelligence here is meant to compound continuously.. curl -fsSL | bash

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The most annoying part about running your agents in the cloud is that sometimes you _do_ need access to your local machine. With Conductor Cloud we give you all the benefits of cloud but also a bunch of local escape-hatches. All cloud agents get access to: - Port-forwarding from cloud to your localhost - File sync from cloud env to your machine - A "run local command" tool that lets agents remotely run commands on your Mac Here's a walkthrough:

Charlie Holtz

18,486 просмотров • 1 месяц назад

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Engineers, creatives, designers - lend me your ears, and eyes, to check my🥇1st tech demo of 2025: A #WebAI Agent running entirely client side in the browser, that's capable of controlling a flight search webpage, to get the job done! I'm using Google's Gemma 2 (2B) model in #JavaScript via #WebGPU thanks to the MediaPipe Web LLM library, combined with some extra function calling logic to enable advanced user experiences. If you like what you see, give this post a share, as I'm just one guy trying to show the world the power of Web AI to do great things. Try it for yourself using the link below after watching the video, but do so on a modernish machine (I have verified it runs on my 6 year old Dell XPS with only an Intel integrated GPU) but use a modern browser like Chrome as it needs WebGPU to run. Want me to make a demo for your industry? Tell me what you need / want to see next! Let me know what you think, and if you have any questions, then drop them in the comments below! YouTube Video Link:

Jason Mayes

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Your boss might not know you’re job hunting, but your chat app definitely does. Every resume upload and interview search is being logged, stored, and sold. 💸 With Keet's peer-to-peer technology, no server or middleman is crawling through your private files. Download The app that knows nothing about you.
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Your boss might not know you’re job hunting, but your chat app definitely does. Every resume upload and interview search is being logged, stored, and sold. 💸 With Keet's peer-to-peer technology, no server or middleman is crawling through your private files. Download The app that knows nothing about you.

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37,551 просмотров • 2 месяцев назад

I've been working with caustics for a while in #webGPU and one of the issues I find is that it's hard to handle caustics for complex scenes. It's easy for planes, you can save photons in a texture using either compute and atomics, or additive blending with the rasteriser. 🧵
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I've been working with caustics for a while in #webGPU and one of the issues I find is that it's hard to handle caustics for complex scenes. It's easy for planes, you can save photons in a texture using either compute and atomics, or additive blending with the rasteriser. 🧵

Hat

17,985 просмотров • 1 год назад

I seriously cannot believe this is a 0.6B LLM! 🤯 Qwen just released Qwen3, a series of hybrid reasoning models that allow you to control how much "thinking" the model does for a given task. They can even run locally in your browser on WebGPU with 🤗 Transformers.js!
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I seriously cannot believe this is a 0.6B LLM! 🤯 Qwen just released Qwen3, a series of hybrid reasoning models that allow you to control how much "thinking" the model does for a given task. They can even run locally in your browser on WebGPU with 🤗 Transformers.js!

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