From @chris_noring and @PacktDataML … "Learn Model Context Protocol [MCP] with TypeScript: Build Agentic Systems in TypeScript with the new standard for AI capabilities" at http://
amzn.to/48W6Izu TypeScript explained and why & when to use it: https://
contentful.com/blog/what-is-t
ypescript-and-why-should-you-use-it/
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Learn Model Context Protocol (MCP) to Build Agentic Systems in TypeScript
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Naive Bayes classification tutorial with Python code
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Naive Bayes Classification, explained with Python code: https://
github.com/taspinar/siml/
blob/master/notebooks/Naive_Bayes.ipynb
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Learn more in this book: http://
amzn.to/312hAHF
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#DataScience #MachineLearning #AI #ML #Algorithms #Statistics #DataScientist #Mathematics -
Grok API Credits Reward Program for X Developers
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Supercharge your X apps with Grok by unlocking free xAI API credits! For every dollar spent on X API credits, earn up to 20% back in xAI credits based on your cumulative spend. Details: docs.x.com/overview#pricing Developers (@XDevelopers) Officially launching X API Pay-Per-Use The core of X developers are indie builders, early stage products, startups, and hobbyists It’s time to open up our X API ecosystem and instill a new wave of next generation X apps We’re so back. developer.x.com — https://nitter.net/XDevelopers/status/2019881223666233717#m
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Securing fast-paced development with AI-generated code
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Securing fast-paced development in a world of AI-generated code
#AI #AIio #AIInnovation #ML #DataScience #Futureofwork @lexfridman @sama @kaifulee @ID_AA_Carmack @karpathy @2morrowknight @ylecun -
Codex not recognizing CUDA on user’s machines
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I still can’t get codex to recognize that CUDA exists on my machines.
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Why AI Products Fail: Serving Phase Challenges and LLM Inference
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Why Most AI Products Fail (It’s Not Training) ❌
— Satya Mallick (@LearnOpenCV) 6 février 2026
Everyone focuses on training, but "serving" is where the real collapse happens. Learn the two phases of LLM inference: Prefill and Decode.#AI #MachineLearning #LLM #SoftwareEngineering pic.twitter.com/XKg886p9QdWhy Most AI Products Fail (It’s Not Training) Everyone focuses on training, but "serving" is where the real collapse happens. Learn the two phases of LLM inference: Prefill and Decode. #AI #MachineLearning #LLM #SoftwareEngineering
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Agents and LLMs documentation references discussion
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llms.txt is something else i think agents.txt do you have a ref?
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EdgeFlowNet Optical Flow Deployment on OrangePix Plus Hardware
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EdgeFlowNet optical flow running on @orangepixunlong 5 Plus + Metis M.2 Community member Enmin solved some gnarly deployment challenges:
→ Custom 6-channel DataAdapter for frame-pair calibration
→ Debug flags to hunt down shape mismatches
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Developer’s Mind Voice: The Best Coding Tool Humor
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On a lighter note 😀 Every developer’s mind voice Sridhar Vembu (@svembu) We better pay attention to him because he has the best coding tool in the world. — https://nitter.net/svembu/status/2019737601423597685#m
→ View original post on X — @skathirmani, 2026-02-06 11:57 UTC
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Voxtral Transcription Quality Improvements and FFT Fixes
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Voxtral (from @MistralAI) transcription quality is quite incredible, the way it handles the punctation and all the rest, makes transcribed audio messages so much more understandable. I implemented a few fixes in the FFT and now there is no longer a skipped tokens issue in voxtral.c
→ View original post on X — @guillaumelample, 2026-02-06 10:11 UTC