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gpu kernels on on my computer writing other gpu kernels for the same chip to simulate 100ks of particles, each an agent + neural network sensing K bg fields and allocating energy to A actions, at 1000s steps/s, for thermodynamic artificial life i think maybe not a bubble lads

Fraser Price

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32,595 görüntüleme • 15 gün önce •via X (Twitter)

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every other day i yearn for more research fields to adopt the culture from the ML and ML adjacent fields of building a demo website for each paper and put code on github

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NO1ennn

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Hey everyone, today I want to introduce a project that’s aiming to redefine how we access compute for AI — it’s called GPUAI. 🔶 GPUAI: Unlocking Global GPU Power for the AI Era GPUAI isn’t just another GPU marketplace or leasing service. It’s a fully decentralized protocol that connects idle GPU resources around the world — from gaming PCs to data center clusters — and transforms them into a high-performance compute network for AI workloads. 🧠 Why does it matter? Right now, the biggest bottleneck in AI isn’t algorithms — it’s access to compute. Training and running models requires massive GPU power, but it’s locked up in centralized cloud platforms, expensive and hard to access for smaller teams. With GPUAI, anyone can tap into a global GPU pool that’s: ✅ Fully decentralized ✅ Reputation-based and smart contract coordinated ✅ Encrypted and secure ✅ Token-incentivized — meaning contributors get rewarded in $GPUAI 📈 For developers, it’s a flexible way to access GPU compute for training, inference, and more — without cloud lock-in. 💰 For GPU owners, it’s a chance to monetize idle hardware that would otherwise go unused. The protocol is live, the apps are active, and the ecosystem is growing fast. 🌐 Try it yourself at 📖 Learn more on 🎮 Play our community games at This is real infrastructure for the future of AI, not hype. Follow them and explore their mission of decentralized computing at Tell me what you think - if you have a GPU, you can start profiting now. #GPUAI #Web3Infrastructure #AIComputing #DePIN #Decentralization

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The Crypto GEMs

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The Way Forward & A New Chapter For AI powered by GamerHash AI & $GHX. Welcome to the future of bleeding edge connectivity and cloud infrastructure ⚡ GamerHash AI is the answer to the billion dollar question on how to offset the GPU scarcity, enable exponential growth of AI through utilizing consumer-level GPUs and establishing a powerful sharing economy by sourcing a global network of gamers. The synergy of our GPU #DePIN and blockchain for #AI #inference is the technology of the future that already works today. See you in the network!

The Way Forward & A New Chapter For AI powered by GamerHash AI & $GHX. Welcome to the future of bleeding edge connectivity and cloud infrastructure ⚡ GamerHash AI is the answer to the billion dollar question on how to offset the GPU scarcity, enable exponential growth of AI through utilizing consumer-level GPUs and establishing a powerful sharing economy by sourcing a global network of gamers. The synergy of our GPU #DePIN and blockchain for #AI #inference is the technology of the future that already works today. See you in the network!

GamerHash AI

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WATCH: "I am going in with a little chip on my shoulder, but also blessed at the same time for this opportunity to keep on playing football." Over the weekend, Davenport Football player Sy Barnett became the first Panther to EVER sign with an NFL team as an undrafted free agent.

Mark Skol, Jr.

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DeepSeek-v4 now runs at ~23-26 tok/s on MLX! I made some custom kernels for the sinkhorn and it took gen speeds for 17 -> 26 tok/s. The weights are also significantly smaller thanks to Pedro Cuenca tip about keeping the experts in MXFP4! Now you can use it to power your local coding agents (PI, Open code, Hermes agent or even CC) PR:

DeepSeek-v4 now runs at ~23-26 tok/s on MLX! I made some custom kernels for the sinkhorn and it took gen speeds for 17 -> 26 tok/s. The weights are also significantly smaller thanks to Pedro Cuenca tip about keeping the experts in MXFP4! Now you can use it to power your local coding agents (PI, Open code, Hermes agent or even CC) PR:

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“I do not think it is a coincidence that the writing of a woman brought me here. I am so grateful to the women in my life. I cannot overstate the importance of intersectionality to me. We need to look for friends and allies here, and not enemies.”

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Jacob Tierney Updates

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I created a web app for teaching computer vision basics, allowing users to upload an image or video stream and instantly view it as a numerical pixel matrix, with options to display values in RGB, Hex, or Grayscale formats. It features predefined convolution kernels applied in real-time: - Sobel operator for edge detection (computes gradients to highlight boundaries) - Gaussian Blur: averages neighboring pixels with weights to reduce noise - Sharpen: boosts local contrast to enhance details This setup clearly visualizes how images are represented as matrices or tensors, how convolution slides kernels across pixels, and how operations like gradient computation, blurring, or sharpening modify the data step-by-step. I plan to use demos like this in my upcoming computer vision course to build intuition for fundamental image processing concepts, OpenCV filters, and CNN building blocks (e.g., why kernels extract features).

I created a web app for teaching computer vision basics, allowing users to upload an image or video stream and instantly view it as a numerical pixel matrix, with options to display values in RGB, Hex, or Grayscale formats. It features predefined convolution kernels applied in real-time: - Sobel operator for edge detection (computes gradients to highlight boundaries) - Gaussian Blur: averages neighboring pixels with weights to reduce noise - Sharpen: boosts local contrast to enhance details This setup clearly visualizes how images are represented as matrices or tensors, how convolution slides kernels across pixels, and how operations like gradient computation, blurring, or sharpening modify the data step-by-step. I plan to use demos like this in my upcoming computer vision course to build intuition for fundamental image processing concepts, OpenCV filters, and CNN building blocks (e.g., why kernels extract features).

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