Research

As large language models (LLMs) like ChatGPT continue to advance, user expectations of them keep growing, including with respect to how quickly they can respond to our increasingly intricate prompts requesting answers to ever-challenging problems and tasks.

MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) has announced a new direction for its long-standing FinTech research initiative, now FinTechAI@CSAIL, to highlight the central role artificial intelligence is playing in shaping the future of finance.

When ChatGPT or Gemini gives what seems to be an expert response to your burning questions, you may not realize how much information it relies on to give that reply. Like other popular artificial intelligence (AI) models, these chatbots rely on backbone systems called foundation models that train on billions or even trillions of data points.

For all their impressive capabilities, large language models (LLMs) often fall short when given challenging new tasks that require complex reasoning skills.