People forget that the Web was built on one.
COMPUTING
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SpaceX Future: Space Datacenters and Distributed Robot Control Systems
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The new SpaceX to me will be: 1. Way to get datacenters and robots to space.
2. Datacenters in space.
3. Distribution from datacenters to planets they serve. 4. Control systems for the robots and humans they are distributing to. These four things alone are worth many -
Technology Adoption Across Generations: Learning from Computing History
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Yeah, it was similar. Most "old people" would have their kids help them with their computer because they didn't understand how to use early Macintosh, Apple II, or something like that. It is the same thing. Everybody will get on board eventually, but it'll take a while.
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Chiplet Architectures: Real Solution to Chip Miniaturization Limits?
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Are Chiplet Architectures a Real Answer to Chip Miniaturization Limits? by @antgrasso #EmergingTech #Innovation #Tech #Technology
→ View original post on X — @ronald_vanloon, 2026-04-10 05:50 UTC
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Cognitive Enhancement Devices: Glasses and Neural Computing Hardware
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Yes, there will be a series of steps involving various devices that provide cognitive enhancements. The glasses that are about to come out are a big step toward that, but there are also hats being developed and other devices that will let you think and compute. The "Full Monty"
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JAX Solver for Gyrokinetics Achieves 10x Speedup with CUDA
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The power of JAX https://t.co/qtC3JcVik9
— François Chollet (@fchollet) 10 avril 2026The power of JAX Eric Volkmann (@e_volkmann) Introducing gyaradax 🐉: A JAX solver for local flux-tube gyrokinetics with custom CUDA kernels for acceleration. This entire code was vibecoded by @ggalletti_ and me in a month. Validated against GKW (CPU-only Fortran code) with 10x speedups. Details and code in the replies. — https://nitter.net/e_volkmann/status/2041853935430881771#m
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Bfloat16 Precision Gaps in Large Scatter Plots Beyond Origin
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Making a scatter plot of 400_000 data points, some of the plots had odd gaps in coverage. It took me a little while to realize that it was only when the data was farther from the origin — it was the raw bfloat16 precision. Everything looks great from -1 to 1, but as you go past 2 and 4, the coverage gaps get larger. My intuition didn't have it being quite so "discretely countable" at those modest numeric values. Float32 for comparison.
→ View original post on X — @id_aa_carmack, 2026-04-09 23:01 UTC
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Agentic AI Inference Optimization Across Specialized Hardware
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Big moment for agentic AI Inference isn’t one-size-fits-all—and this blueprint proves it. By matching each phase to the right compute (GPUs for prefill, SambaNova RDUs for high-throughput decode, and Intel Xeon 6 for orchestration + tools), we unlock a new level of
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AI Inference: Enterprise-Grade Model Optimization Explained
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What exactly is AI inference? It’s where trained AI models generate real-world predictions. For enterprises, optimized inference = reliable, scalable AI. Read why it matters & how it works in our latest blog: https://
sambanova.ai/blog/what-is-a
i-inference?utm_source=x&utm_medium=organic&utm_content=blog-announcement
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AI Homes: Optical Networks Enable Intelligent Connected Experiences
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AI is moving into our homes — and networks must evolve with it. At #MWC2026, Huawei highlighted how optical networks are enabling AI-driven services, from smart homes to distributed computing. It’s no longer just about connectivity. It’s about intelligent experiences. Read more 👉 go.kenovy.com/sRN7 #AI #Telecom #OpticalNetworks #Innovation
→ View original post on X — @ingliguori, 2026-04-09 21:22 UTC