Introducing LFM2.5: The Next Generation of On-Device AI | Liquid AI https://
buff.ly/6x7JmPE
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MACHINE LEARNING
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LFM2.5: Next Generation On-Device AI from Liquid AI
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Simulation Work Requires Understanding True Performance Gap
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I still think most work should be done in simulation, but it is crucial to calibrate your understanding of the true gap!
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Evaluating RL Performance: Challenges in Benchmarking Improvements
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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.
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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."