The Cognitive Revolution · Saturday, July 4, 2026
Liquid AI is developing alternative machine learning algorithms inspired by brain dynamics to achieve better out-of-distribution generalization, a key challenge in real-world applications like robotics. Ramin Hassani explained their research into "Liquid neural networks" aims to mimic how neurons exchange information, potentially unlocking greater capabilities than traditional artificial neural networks.
“Essentially what we what we try to do, we try to, you know, like build alternative algorithms. To in order to get creative in the algorithmic space, to see how can we build machine learning systems that can generalize beyond the data that they have seen.”
“Because when you go in the real world, the distribution shifts becomes like a real thing, you know, like you you imagine you deploy a robot in an open world kind of like like let's say autonomous car, a flying drone, a fixed wing vehicle, you know?”
“So naturally the place that we started looking into was brains, you know, we started looking into animal brains, you know, and and we started looking into how neurons exchange information with each other, you know?”