Liquid AI, a startup designing artificial intelligence systems inspired by the structure of the tiny brain of a worm, is set to raise $250 million in funding at a $2.3 billion valuation.

The Series A round is being led by Advanced Micro Devices Inc., with participation from OSS Capital, Duke Capital Partners and PagsGroup, among other investors. The startup previously raised $46.6 million in seed funding, according to the company.

Traditionally, developers have relied on neural networks loosely modeled off of the human brain to help AI systems learn through trial and error. Liquid AI is taking a different approach. Founded in 2023 by a group of AI researchers at the Massachusetts Institute of Technology, the startup is building a novel technology called liquid foundation models that instead uses mathematical techniques discovered by studying the architecture of a worm's brain.

By focusing on an organism -- specifically, a small nematode worm called Caenorhabditis elegans that's just 1 millimeter long -- with far fewer neurons than the human brain, Liquid AI said it's able to build an AI system that is more flexible. Its systems also require less data and computing power than the conventional transformer-based models that underpin chatbots and other popular AI tools, the company said.

"We have been proving the technology in the last year, making sure that an alternative structure to transformers can be scaled," said Ramin Hasani, co-founder and chief executive officer. "This funding will help get us to the next level."

Two years after ChatGPT's release kicked off a frenzy around generative AI, there is a growing debate about whether top developers are hitting a wall in building more advanced artificial intelligence systems that justify the tremendous cost. A key part of Liquid AI's pitch is effectively that its technology can do more with less. The startup said its models are better suited to run on devices, reducing the need for costly data centers. Liquid also claims a text-based version of its AI system outperformed some leading alternatives of similar size on various benchmarks.