Can you extract entire copyrighted books from top AI models like GPT-4 and Claude? Stanford & Yale researchers developed a two-step attack: first probing, then using iterative prompts to force the model to continue. They successfully extracted large portions of books, with
LLMS
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Context Breakdown: The Hidden Challenge in AI System Reliability
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Most AI systems don’t fail because of bad prompts.
They fail because context breaks at scale. If you’re building AI agents, LLM workflows, copilots, or automation, this is the layer that quietly decides whether your system is reliable or unpredictable. We’re hosting a 5-hour, -
Multimodal Sleep Foundation Model for Disease Prediction
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A multimodal sleep foundation model for disease prediction – Nature Medicine https://
buff.ly/W0r4qKh
#AI #MachineLearning #DeepLearning #LLMs #DataScience -
Why Korean Organizations Should Compete in AI Model Development
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Why not? If deepseek, mistral,… can do it, why not Korean orgs?
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LLM Optimization Through Compute-Controlled Model Family Design
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New post: nanochat miniseries v1 The correct way to think about LLMs is that you are not optimizing for a single specific model but for a family models controlled by a single dial (the compute you wish to spend) to achieve monotonically better results. This allows you to do
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ScaledML Returns After 6 Years with ML Industry Foresight
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ScaledML is back! After a 6 year hiatus. Consistently 2-3 years ahead of where ML will be. Examples of foresight at SML:
– OpenAI in 2016,2017,2019 announced GPT-2 & RL efforts
– Turing award for Deep Learning announced by Turing award winner on morning of award
– Groq chip -
Tailwind Rejects llms.txt PR for Being Too Useful
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How useful is llms.txt? It's so useful that Tailwind rejected a PR to add an llms.txt, on the basis that it would be so useful that people wouldn't need to read their docs any more! https://
github.com/tailwindlabs/t
ailwindcss.com/pull/2388
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Evaluating LLM Legal Reasoning with LEXam Benchmark
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How good are LLMs at legal reasoning? This Friday, join us for our AI for Law session led by @joelniklaus on LEXam — a new benchmark using real law school exams to evaluate long-form, structured legal reasoning. Link to register below
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AMD Evaluates 2.6B Language Model Performance with GAIA Framework
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Nice bit: the 2.6B works well, even with long meetings with 10k tokens It was a pleasure working with the AMD team, who evaluated all the models with their GAIA framework
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LFM2-2.6B: On-Device Meeting Summarization with Cloud Quality
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LFM2-2.6B-Transcript @AMD🤝@liquidai
— Maxime Labonne @ ICLR (@maximelabonne) 7 janvier 2026
> Private, on-device meeting summarization
> Cloud-level quality
> Faster processing, lower memory footprint
> Runs across CPU, GPU, and NPU on AMD Ryzen AI PC
Great showcase of what tiny models can achieve when fine-tuned pic.twitter.com/5kQXfE9j1fLFM2-2.6B-Transcript @AMD
@liquidai > Private, on-device meeting summarization
> Cloud-level quality
> Faster processing, lower memory footprint
> Runs across CPU, GPU, and NPU on AMD Ryzen AI PC Great showcase of what tiny models can achieve when fine-tuned