Thanks — I always half expect someone to pop up say “we just cloned this other repo and ran it for a 50% performance improvement”. With RL it is very hard to know what “good performance” is.
MACHINE LEARNING
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Tesla FSD significantly outperforms human drivers
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Tesla FSD is way better at driving than you are.
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Why Chasing New Models and More Data Often Fails
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Why chasing new models and more data often fails in AI training. pic.twitter.com/5hqmEYXSWi
— Satya Mallick (@LearnOpenCV) 7 janvier 2026Why chasing new models and more data often fails in AI training.
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Company behind low power AI chips in coolest CES products
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Great #ces2026 Report #7: The company inside the coolest AI products at CES.
— Robert Scoble (@Scobleizer) 6 janvier 2026
Makes low power AI chips inside a wide range of consumer products. Watches, rings, AI glasses, medical devices, all use their chips because they are best at running neural networks at very low power.… pic.twitter.com/BhaqWesHB6Great #ces2026 Report #7: The company inside the coolest AI products at CES. Makes low power AI chips inside a wide range of consumer products. Watches, rings, AI glasses, medical devices, all use their chips because they are best at running neural networks at very low power.
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Add Datasets to Hugging Face for AI Builders
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you should add the datasets to http://
hf.co/datasets for AI builders to use! -
Using Claude Code with Opus 4.5 to refactor Ubuntu in React Native
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brb i’m gonna use claude code with opus 4.5 to refactor ubuntu in react native
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Semantic vs Instance vs Panoptic Segmentation Explained
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Semantic vs Instance vs Panoptic Segmentation — explained
— Satya Mallick (@LearnOpenCV) 6 janvier 2026
🟦 Semantic Segmentation: assigns a class label (person, road, tree, sky, etc.) to every pixel.
✅ You know what the pixel is — ❌ not which exact object (person 1 vs person 2).
🧍♂️ Instance Segmentation: separates… pic.twitter.com/GKPORRq2PYSemantic vs Instance vs Panoptic Segmentation — explained Semantic Segmentation: assigns a class label (person, road, tree, sky, etc.) to every pixel. You know what the pixel is — not which exact object (person 1 vs person 2). Instance Segmentation: separates
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Mercedes Combines Model-Free and Model-Based Approaches
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Model-free + Model-based ! : “…alongside the end-to-end model, the Mercedes cars will also run more traditional software [GOFE]…, and a ‘safety policy evaluator’ will decide which of the two gets to take the wheel at any given moment, Huang said.” https://t.co/OQzIOQnWCT
— Ken Goldberg (@Ken_Goldberg) 6 janvier 2026Model-free + Model-based!: "…alongside the end-to-end model, the Mercedes cars will also run more traditional software [GOFE]…, and a 'safety policy evaluator' will decide which of the two gets to take the wheel at any given moment, Huang said."
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2026 AI Predictions from Industry Expert
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I started in AI almost 20 years ago, worked at both IBM and Amazon in AI, have been posting about AI for a decade, and have been sharing my AI and tech predictions for 8 years. Read my 2026 AI predictions here:
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Christian Jacobi on PyTorch Community and AI Deployment
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IBM’s Christian Jacobi (@IBM Fellow and CTO, IBM Systems Development) on why the PyTorch community matters for AI today, the role of open source, and what he’s hearing from clients deploying AI in core IT and business processes. 🎥 https://t.co/ZTwg7fz7xi pic.twitter.com/TdHLMNkbiT
— PyTorch (@PyTorch) 6 janvier 2026IBM’s Christian Jacobi (@IBM Fellow and CTO, IBM Systems Development) on why the PyTorch community matters for AI today, the role of open source, and what he’s hearing from clients deploying AI in core IT and business processes. 🎥 piped.video/Y_R4JMg2Vwo