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| 🔗 Stories, Tutorials & Articles |
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| Building a Healthcare Robot from Simulation to Deployment with NVIDIA Isaac ✅ |
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NVIDIA just dropped Isaac for Healthcare v0.4, and it’s a big one. Headliner: the new SO-ARM starter workflow - a full-stack sim2real pipeline built for surgical robotics.
It covers the whole loop: spin up synthetic and real-world data capture, train with GR00t N1.5, and deploy straight to 6-DOF hardware. All wired into IsaacLab and LeRobot 0.4.0 out of the box. |
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| The Fatal Math Error Killing Every AI Architecture - Including The New Ones |
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| LLMs are fading as JEPA (Joint Embedding Predictive Architecture) emerges with joint, embedding, predictive architecture. JEPA is a step towards true intelligence by avoiding the flat, finite spreadsheet trap of Euclidean space and opting for a toroidal model. |
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| LaTeX, LLMs and Boring Technology |
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LLMs are tearing down LaTeX's old walls. Syntax hell, cryptic errors, clunky formatting - easier now. Whether baked into editors or running solo, these models smooth the pain.
Why does it work so well? LaTeX has history. Mountains of examples. It's the perfect training set. That puts newer contenders like Typst in a tough spot - less data, less help.
The twist: LLMs are quietly reviving legacy tools. When AI makes "boring tech" fast and useful, the shiny new stuff has to work a lot harder to matter. |
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| Context Management in Amp |
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Amp stretches the context window into something more useful. It pulls in system prompts, tool info, runtime metadata, even AGENTS.md files - fuel for agentic behavior.
It gives devs serious control: edit messages, fork threads, drop in files with @mentions, hand off conversations, or link threads together. Context becomes a flexible workspace. |
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| Inside Cursor - Sixty days with the AI coding decacorn |
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| Cursor is shaking up recruiting by treating the hiring process as more about the person than the job, resulting in a fast-growing team of exceptional individuals drawn in by the company's compelling mission and focus on challenging technical problems. Women in product and engineering roles are a known gap that Cursor is actively working to address. |
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| Jensen Huang's Stark Warning: China's 1 Million AI Workers vs America's 20,000 ✅ |
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Nvidia CEO Jensen Huang, in some leaked comments, didn’t mince words: U.S. export bans aren’t hobbling China’s AI game - they’re fueling it.
He pointed to Huawei’s 910C chip edging close to H100 territory, a forecast putting China ahead in AI compute by 2027, and a fast-growing local chip industry now covering 65% of its own AI needs.
System shift: The export crackdown spawned a whole new ecosystem in China - custom chips, homegrown frameworks, and a swelling pool of domestic talent. A second AI stack is coming online, and it doesn't need the West. |
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| The 1 Billion Token Challenge: Finding the Perfect Pre-training Mix ✅ |
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Researchers squeezed GPT-2-class performance out of a model trained on just 1 billion tokens - 10× less data - by dialing in a sharp dataset mix: 50% finePDFs, 30% DCLM-baseline, 20% FineWeb-Edu.
Static mixing beat curriculum strategies. No catastrophic forgetting. No overfitting. And it hit 90%+ of GPT-2’s benchmark scores at 50× lower training cost. |
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