BY KIM BELLARD

Chances are, you’ve read about AI lately.  Maybe you’ve actually even tried DALL-E or ChatGPT, maybe even GPT-4.  Perhaps you can use the term Large Language Model (LLM) with some degree of confidence.  But chances are also good that you haven’t heard of “liquid neural networks,” and don’t get the worm reference above.   

That’s the thing about artificial intelligence: it’s evolving faster than we are. Whatever you think you know is already probably out-of-date.

Liquid neural networks were first introduced in 2020.  The authors wrote: “We introduce a new class of time-continuous recurrent neural network models.” They based the networks on the brain of a tiny roundworm, Caenorhabditis elegans.  The goal was networks that were more adaptable, that could change “on the fly” and would adapt to unfamiliar circumstances. 

Researchers at MIT’s CSAIL have shown some significant progress.  A new paper in Science Robotics discussed how they created “robust flight navigation agents” using liquid neural networks to autonomously pilot drones. They claim that these networks are “causal and adapt to changing conditions,” and that their “experiments showed that this level of robustness in decision-making is exclusive to liquid networks.”