Discover how @ColoradoStateU is revolutionizing severe weather prediction by using NVIDIA Earth-2 and PhysicsNeMo to extend hailstorm lead times from minutes to hours. This collaboration pairs generative AI with high-resolution radar data to deliver real-time, scalable
INNOVATION
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Hugging Face surpasses one million public datasets
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We just crossed 1,000,000 public datasets on Hugging Face! That's petabytes of data available that millions of AI builders download, analyze, and train AI models on every day! What's interesting is that we're seeing a clear acceleration since AI agents started performing well.
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AI context gets fresh with Cocoindex
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The way AI agents access fresh context has just been transformed forever. AI agents constantly face a major hurdle: their context becomes outdated. Every codebase update, new Slack message, or fresh PDF requires rebuilding the entire pipeline from the ground up. Cocoindex is an open-source engine that solves this problem.
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AI Infrastructure and Future Trends Discussed at Web Summit
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AI is hitting a new phase and infrastructure is at the center of it. Don't forget to join @RodrigoLiang at @WebSummit Vancouver as he breaks down what’s changing and what comes next. May 13 | 12:20–12:40 PM https://
vancouver.websummit.com/sessions/van26
/d28d9215-dcdd-4b20-94e3-03d56a46061c/building-ai-s-400b-backbone/
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Multi-Agent Synergy for Scaling Test-Time Compute
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TMAS Scaling Test-Time Compute via Multi-Agent Synergy
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Chip Complexity: The Era of Specialized Processors
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Computational complexity has reached a level where a single general-purpose processor can no longer efficiently handle all AI tasks. To overcome bottlenecks, the industry has turned to specialized chips, each optimized for a specific type of workload. Microblog @antgrasso
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Open-source backend réduit les tokens IA de 3x
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An open-source backend layer just cut AI agent tokens by 3x.
— AlphaSignal AI (@AlphaSignalAI) 12 mai 2026
Claude Code burned through 10.4M tokens with 10 errors on a single project.
One change cut that to 3.7M tokens with zero errors.
The fix was adding InsForge as a backend context layer.
It's an open-source platform… pic.twitter.com/RnoconUkANAn open-source backend layer just cut AI agent tokens by 3x. Claude Code burned through 10.4M tokens with 10 errors on a single project. One change cut that to 3.7M tokens with zero errors. The fix was adding InsForge as a backend context layer. It's an open-source platform
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Sharing Papers and Apps on Hugging Face
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Paper:
https://huggingface.co/papers/2605.10922
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App:
https://huggingface.co/spaces/TencentARC/Pixal3D
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Pixel-Aligned 3D Generation
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Pixal3D
— AK (@_akhaliq) 12 mai 2026
Pixel-Aligned 3D Generation from Images pic.twitter.com/DADl4UQVIGPixal3D Pixel-Aligned 3D Generation from Images
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East Coast consensus contrasts with West Coast rapid automation vision
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I think that is the East Coast consensus, generally: jaggedness + the complexity of actual organizations + social constraints mean that even true ASI is less abruptly transformative than the West Coast vision of massive rapid automation as soon as AI capabilities get good enough