Research

Let’s say you’re reading a story, or playing a game of chess. You may not have noticed, but each step of the way, your mind kept track of how the situation (or “state of the world”) was changing. You can imagine this as a sort of sequence of events list, which we use to update our prediction of what will happen next.

Imagine a future where artificial intelligence quietly shoulders the drudgery of software development: refactoring tangled code, migrating legacy systems, and hunting down race conditions, so that human engineers can devote themselves to architecture, design, and the genuinely novel problems still beyond a machine’s reach. Recent advances appear to have nudged that future tantalizingly close, but a new paper by researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and several collaborating institutions argues that this potential future reality demands a hard look at present-day challenges. 

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.