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Weekly AI News January 31 2026: The Pulse & The Pattern Play Introduction If you’ve been wondering when “AI that actually does stuff” would stop being a demo and start being a risk assessment, welcome to AI News January 31 2026. This week’s theme is motion: models moving from chat to action, from single-threaded answers … Read more
Self-Distillation Fine-Tuning (SDFT): The On-Policy Trick That Makes Continual Learning Finally Work Play Introduction Fine-tuning an LLM feels like doing surgery with oven mitts. You make one clean cut, the patient learns a shiny new skill, then you check the vitals and realize it forgot its own name. That is the default behavior of supervised … Read more
DeepSeek OCR 2 Guide: Reads Like A Human, Visual Causal Flow, Copy Paste Local Setup Play Introduction If you have ever tried to pull a table out of a PDF, you know the feeling. The text shows up, sure, but the meaning gets scrambled. Columns swap places. Labels drift away from their values. A neat … Read more
Kimi K2.5 Review: Swarm Mode Reality Check, Benchmarks, and Pricing Play Introduction AI model releases used to be simple: bigger context, higher scores, new logo. Now the real competition is usability. Can the model code without turning your repo into spaghetti. Can it look at a screenshot and stay honest about what it sees. Can … Read more
Qwen3 Max Thinking Review: Heavy Mode, Test-Time Scaling, And Benchmarks Play Introduction Every few months the “reasoning model” race gets a new lap: a flagship shows up, claims it thinks deeper, posts a fresh set of charts, and the internet immediately argues about whether the charts are real. Qwen3 Max Thinking is worth your time … Read more
Clawdbot Install: A Busy Engineer’s Guide To Gateway, Dashboard, And A Local Ollama Model Play Introduction If you’ve ever wanted a “personal assistant” that lives on your machine instead of in a stranger’s cloud, you’re in the right place. The pitch is simple: run a tiny control plane (the Gateway), talk to it through a … Read more
TTT-Discover Explained: Why Test-Time RL Outruns Best-of-N Sampling Play Introduction You have seen this movie. A model tackles a hard problem, fails, tries again, fails differently, then repeats the same mistake with fresh confidence. You can sample more. You can crank temperature. You can run best of n sampling until the GPU fans sound like … Read more