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
Large Language Models (LLMs) have rapidly become an integral part of our digital landscape, powering everything from chatbots to code generators. However, as these AI systems increasingly rely on proprietary, cloud-hosted ...
Mar 26, 2025
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Machine learning & AI
Artificial intelligence (AI) plays a role in virtually every aspect of our lives, from self-driving cars to smart vacuum cleaners, to computer models that can predict the course of an epidemic. No matter how advanced these ...
Mar 20, 2025
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Security
Security was top of mind when Dr. Marcus Botacin, assistant professor in the Department of Computer Science and Engineering, heard about large language models (LLMs) like ChatGPT. LLMs are a type of AI that can quickly craft ...
Mar 20, 2025
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Machine learning & AI
Since ChatGPT burst onto the scene in late 2022, generative artificial intelligence (GenAI) models have been vying for the lead—with the US and China hotbeds for the technology.
Mar 13, 2025
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Machine learning & AI
The computer scientists Rich Sutton and Andrew Barto have been recognized for a long track record of influential ideas with this year's Turing Award, the most prestigious in the field. Sutton's 2019 essay The Bitter Lesson, ...
Mar 10, 2025
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