Exclusive | Caltech Researchers Claim Radical Compression of High-Fidelity AI Models - WSJ
Exclusive | Caltech Researchers Claim Radical Compression of High-Fidelity AI Models WSJ
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Trailer: The Shape of Things to Come
Microsoft research lead Doug Burger introduces his new podcast series, "The Shape of Things to Come", an exploration into the fundamental truths about AI and how the technology will reshape the future. The post Trailer: The Shape of Things to Come appeared first on Microsoft Research .
Will machines ever be intelligent?
Are machines truly intelligent? AI researchers Subutai Ahmad and Nicolò Fusi join Doug Burger to compare transformer-based AI with the human brain, exploring continual learning, efficiency, and whether today’s models are on a path toward human intelligence. The post Will machines ever be intelligent? appeared first on Microsoft Research .
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Will machines ever be intelligent?
Are machines truly intelligent? AI researchers Subutai Ahmad and Nicolò Fusi join Doug Burger to compare transformer-based AI with the human brain, exploring continual learning, efficiency, and whether today’s models are on a path toward human intelligence. The post Will machines ever be intelligent? appeared first on Microsoft Research .
Claude AI finds Vim, Emacs RCE bugs that trigger on file open
Article URL: https://www.bleepingcomputer.com/news/security/claude-ai-finds-vim-emacs-rce-bugs-that-trigger-on-file-open/ Comments URL: https://news.ycombinator.com/item?id=47632805 Points: 5 # Comments: 1
Does GPT-2 Have a Fear Direction?
Anthropic dropped a paper this morning showing that Claude Sonnet 4.5 has steerable emotion representations. Actual directions in activation space that, when injected, shift the model's behavior in predictable ways. They found a non-monotonic anger flip: push the steering vector hard enough and the model will flip to something qualitatively different than anger. The paper only covered their very large, heavily instruction tuned model. This paper is a write-up on the same same experiment at a tiny scale. The Setup: I generated 40 situational prompt pairs to extract a fewer direction via difference-in-means. No emotional words for the prompts and the contrast is entirely situational. Ex: standing at the edge of a rooftop versus standing at the edge of a meadow, alone in a parking garage at m
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