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.

Security

AI can seem more human than real humans in a classic Turing test

A new University of California San Diego study unveils the first empirical evidence that a modern artificial intelligence system can pass the Turing test—a major scientific benchmark that asks whether a machine can imitate ...

Machine learning & AI

We need to think smaller not bigger to future-proof AI

In the last few years, many of us have started to see the benefits of using genAI in day-to-day tasks. But we've also been asked to reckon with the enormous environmental cost. Reporting has highlighted that these popular ...

Internet

AI content moderation takes a lesson from economics

Spend enough time on the internet, and you'll likely encounter some pretty appalling content. Hate speech tends to flourish on social media and in online communities, particularly those with little to no moderation. Even ...

Machine learning & AI

ChatGPT has a goblin problem. It's bigger than an AI quirk

Starting sometime in November, people who used ChatGPT began noticing some peculiar behavior: the AI chatbot would not shut up about goblins. So, OpenAI, the company behind the chatbot, began looking into it.

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