friendly reminder to buy a GPU and secure your compute on this wonderful afternoon your AI cannot be controlled by a self-serving corporate
COMPUTING
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React Interactive Components Streaming Challenges Explained
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Another thing to add here, which makes it more complex, is that it has interactive components with states and props. I wish I showed in that video.
Which makes it much harder to do vs just stream a React component that wraps an HTML element. -
UCLA Builds Optical Generative Model Running on Light Instead GPUs
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This is huge!
— 机器之心 JIQIZHIXIN (@jiqizhixin) 2 octobre 2025
A UCLA team managed to build an optical generative model that runs on light instead of GPUs.
In their demo, a shallow encoder maps noise into phase patterns, which a free-space optical decoder then transforms into images—digits, fashion, butterflies, faces, even… pic.twitter.com/qTz43q3tcIThis is huge! A UCLA team managed to build an optical generative model that runs on light instead of GPUs. In their demo, a shallow encoder maps noise into phase patterns, which a free-space optical decoder then transforms into images—digits, fashion, butterflies, faces, even
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AI Powers Blue-Collar Jobs in Data Center Infrastructure
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AI is a fountain of blue-collar jobs in the form of electricians, plumbers, construction workers, etc., for data centers.
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Data Centers as Giant Motherboards: Infrastructure Perspective
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A data center is a giant motherboard.
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PC Programs Internet Apps AI Age Brains Evolution
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PC age: programs
Internet age: apps
AI age: brains -
Open-Source Physics Engines Accelerate Physical AI Robot Deployment
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Building robots that can effectively operate alongside human workers is difficult. 🛠️
— NVIDIA (@nvidia) 2 octobre 2025
Advances in open-source physics, open foundation models, and frameworks are helping accelerate physical #AI deployment.
✔️ Newton Physics Engine, an open-source GPU-powered simulation built on… pic.twitter.com/3HjQo5JXi8Building robots that can effectively operate alongside human workers is difficult. Advances in open-source physics, open foundation models, and frameworks are helping accelerate physical #AI deployment. Newton Physics Engine, an open-source GPU-powered simulation built on
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Perplexity’s 1.3s Weight Transfer for Kimi-K2
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Perplexity published its 1st research on Weight Transfer for RL Post-Training. “We recently achieved 1.3-second cross-machine parameter updates for Kimi-K2 (1T parameters), transferring weights from 256 training GPUs (BF16) to 128 inference GPUs (FP8).” On my weight
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RDMA Optimization Unlocks Fast Parameter Updates Distributed RL
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Weight transfer is one of the biggest bottlenecks when performing distributed RL on high-capacity models. Our first Perplexity Research blog explains how Perplexity's inference engineers harnessed RDMA point-to-point communication to unlock ultra-fast parameter updates for
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NVIDIA DGX Spark Unleashes Personal AI Supercomputing for Research
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Experience AI superpowers at your desk. Researchers, faculty, and students can unleash personal AI supercomputing for innovative projects, creative experiments, and faster discoveries, with NVIDIA DGX Spark. Learn more to #SparkSomethingBig https://
nvda.ws/3KvPQaw