It’s All Fun & Games For AI at MIT: Improving Language Generations

Trying to make the normal and often boring world of AI sound exciting can be a task harder than trying to explain quantum physics to a three-year-old. But the folks from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have just made it a tad bit easier. By playing games or, to be more precise, by taking ideas from game theory, they are working towards improving the reliability of language generation in language models. So gamers and AI enthusiasts, rejoice!

Key points: Roll the Dice and Speak Nice?

• The MIT CSAIL team is turning to game theory, usually associated with economics and not language teaching, in order to help AI learn to generate more reliable and accurate language. Bet you never thought a strategy for winning Monopoly could help you understand Shakespeare better, huh?
• This particular approach trains AI models to think of language generation as a game, where each player’s goal is to accurately predict the other’s actions. You could almost call this “Jeopardy! – AI Version.”
• Earlier methods struggled with the issue of AI generating incorrect or nonsensical responses, kind of like using predictive text on your phone and ending up inviting your boss for a date. Using game theory, MIT’s team has been able to make some groundbreaking advancements in this area.

Final Thoughts

In the grand, fascinating arcade game of life, the arcade wizards at MIT may just have discovered the bonus level. By transplanting game theory into language models, they’ve shown that sometimes the road to success is paved with fun and games. Or, in other words, AI may play games better than your average teenage gamer soon – and they can do it while enlightening us on the subtleties of Shakespearean prose. Such fancy! Looks like the world of AI just got its joystick, and there’s a high score waiting to be beaten in the language model leaderboard. Game on, folks!