Page 8: Research news on Large language models

Large language models are high-capacity neural sequence models trained on massive text and multimodal corpora to perform language understanding, generation, and reasoning. Current work examines their internal representations, cognitive and social behavior analogies to humans, and limitations in mathematical, causal, and strategic reasoning. Research also addresses alignment with human values and brain activity, safety and security vulnerabilities, privacy and de-anonymization risks, cross-lingual and sociocultural biases, scaling and efficiency laws, and frameworks for tool use, multi-agent interaction, and domain-specific deployment.

Computer Sciences

What flocking birds can teach AI about reducing noise

Among the primary concerns surrounding artificial intelligence is its tendency to yield erroneous information when summarizing long documents. These "hallucinations" are problematic not only because they convey falsehoods, ...

Consumer & Gadgets

New deep learning framework solves the cold-start problem

Recommender systems suggest potentially relevant content by evaluating user preferences and are essential in reducing information overload. However, when users join a new online platform, recommendation systems often struggle ...

Computer Sciences

The AI that taught itself: How AI can learn what it never knew

For years, the guiding assumption of artificial intelligence has been simple: an AI is only as good as the data it has seen. Feed it more, train it longer, and it performs better. Feed it less, and it stumbles. A new study ...

Computer Sciences

Improving AI models' ability to explain their predictions

In high-stakes settings like medical diagnostics, users often want to know what led a computer vision model to make a certain prediction, so they can determine whether to trust its output. Concept bottleneck modeling is one ...

Security

How AI could end online anonymity

The internet is rife with anonymous accounts as users adopt pseudonyms, sometimes for genuine reasons like speaking freely, and other times for nefarious ones. But this era of online privacy could be coming to a close. In ...

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