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Here's Lars Grammel on why TypeScript is the language that makes most sense for AI apps. - How often are you really training foundation models from scratch? - Full-stack TS brings a substantial speed increase - If you need Python, stick it in its own API

Matt Pocock

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13,613 次观看 • 1 年前 •via X (Twitter)

健康养生科学技术教育

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OpenStack. Containers. Kubernetes. Every time enterprise infrastructure shifted, Mirantis was already there. AI is no different. But here's what most people miss: AI doesn't replace the stack. It runs on top of it. You still need IaaS. You still need Kubernetes. You still need someone who never stopped building that foundation. Mirantis never did. In this interview, Alex Freedland, CEO & Co-founder of Mirantis, explains how 15 years of infrastructure depth is exactly what the AI era demands, and why 1,500 enterprises are already on that path. Watch the full interview:

OpenStack. Containers. Kubernetes. Every time enterprise infrastructure shifted, Mirantis was already there. AI is no different. But here's what most people miss: AI doesn't replace the stack. It runs on top of it. You still need IaaS. You still need Kubernetes. You still need someone who never stopped building that foundation. Mirantis never did. In this interview, Alex Freedland, CEO & Co-founder of Mirantis, explains how 15 years of infrastructure depth is exactly what the AI era demands, and why 1,500 enterprises are already on that path. Watch the full interview:

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Folks say that the stuff you learn from the /teach skill doesn't stick. "Did AI really teach you how to solve a Rubik's cube?" Yes. Here's the proof: (don't expect any great speed, but I can do it)

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‘If you poll on white privilege, you only get the most progressive segment of the population agreeing with it… If you ask: Do people from ethnic minorities suffer disadvantages that white people don't? Everyone agrees.' Luke Tryl on why the language progressive campaigners use often lands really badly. emily m | Jon Sopel

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underrated gems in Kimi-K3 release: > an early K3 wrote the majority of the kernels in the late development stages > it built a triton-class compiler from scratch, MiniTriton, that delivers performance on par with or better than Triton and torch.compile > then it designed a chip, by a model, for a model, in one 48-hour autonomous run the model is rewriting and optimizing every layer of the stack it runs on: kernels for its own training. A compiler for its own kernels. silicon for its own weights. we're watching software build its own hardware

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Andrew Tate

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AI is the future. A machine read my Twitter, created this video and then made this post, all on its own. You need AI to begin living your life for you if you want to get ahead. Learn how:

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You can go to FEDERAL PRISON for smuggling restricted AI chips into China, but selling China the sophisticated human-derived training data and expertise that makes its AI models competitive faces no comparable legal consequence. How does that make any sense? If data is the final frontier of AI, Washington is leaving a GAPING loophole wide open for the CCP to beat the US when it comes to AI dominance. That loophole could be big enough for China to drive its entire AI catch-up strategy through. I hope the Trump administration has a plan to combat this…

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