Simulating the future is a key missing skill of LLMs

Tags: #ai

In order for AI to really be more like a human mind, it must be able to plan, and currently it can’t simulate the future.

“When holding a serious conversation, we simulate how different replies might shift the mood—just as, when navigating a supermarket checkout, we predict how slowly the various lines will likely progress. Goal-directed behavior more generally almost always requires us to look into the future to test how much various actions might move us closer to our objectives. This holds true whether we’re pondering life’s big decisions, such as whether to move or have kids, or answering the small but insistent queries that propel our workdays forward, such as which to-do-list item to tackle next.”

If we want to build more recognizably human artificial intelligences, they will have to include this ability to prognosticate. (How did Hal 9000 from the movie 2001 know not to open the pod bay doors for Dave? It must have simulated the consequences of the action.)

But as I elaborate in the article, this is not something large language models like GPT-4 will ever be able to do. Their architectures are static and feedforward, incapable of recurrence or iteration or on-demand exploration of novel possibilities. No matter how big we push these systems, or how intensely we train them, they can’t perform true planning.

Does this mean we’re safe for now from creating a real life Hal 9000? Not necessarily. As I go on to explain, there do exist AI systems, that operate quite differently then language models, that can simulate the future. In recent years, an increasing effort has been to combine these planning programs with the linguistic brilliance of language models.

written on 2024-03-21 9