Technical AI news, automatically curated and generated
CritICL is a new inference-time framework that improves LLM reasoning efficiency by leveraging structured failure patterns observed across model scales within the same family, rather than relying on repeated generation o…
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A common strategy for scaling world models is to train on more crawled video with more compute. We argue that this strategy is inefficient: scaling world models also requires a recursive data engine t
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GLM-5.3 uses the same base model as GLM-5.2 — every gain comes from post-training. Compared with GLM-5.2, it is much better at complex coding and long-horizon tasks: Stronger Codi
→ View original sourceThe release of GLM-5.3, another open-weight model approaching frontier performance, raises questions about Anthropic's $1T valuation. As capable open-source models become increasingly accessible and can be run locally at…
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Anthropic refused to support lethal autonomous warfare and mass surveillance.
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Almost every language model you have used works the same way underneath. It predicts one token, appends it, then predicts the next, one at a time, left to right. That sequential nature is why generati
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A modification to llama.cpp has been developed that enables the KV cache to exceed physical VRAM capacity by adaptively streaming portions between system RAM and GPU memory. This technique allows running Qwen 3.8 27B wit…
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Google AI has released Gemini 3.5 Transcribe, a speech-to-text model achieving 2.6% average Word Error Rate across 85+ languages. The release includes two variants: gemini-3.5-transcribe-live for real-time WebSocket stre…
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In a Stack Overflow blog post, Ryan interviews Leo de Moura about using the Lean theorem prover to formally verify AI agents, ensuring correctness beyond probabilistic reasoning. The discussion highlights how automated r…
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