Page 6: 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.

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.

Consumer & Gadgets

What does it mean to train an AI to speak like you?

Ultra-personalized artificial intelligence for assisted communication risks muting aspects of the user's identity and occasionally breaches privacy, according to a new study from a Cornell Tech doctoral student who trained ...

Computer Sciences

When AI can't count—and what researchers are doing about it

Today, artificial intelligence can describe images, recognize objects, and explain complex relationships. The pace of development is remarkable: So-called vision-language models (VLMs) combine text and image understanding ...

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