Liquid AI is a World Models & Specialty company founded in 2023 and based in Cambridge, United States. It is valued at $2.4B.
United States| Date | Stage | Amount | Valuation | Lead investors |
|---|---|---|---|---|
| Dec 13, 2024 | Series A | $250M | $2.4B | AMD Ventures |
Liquid AI carries a real scientific differentiator — liquid neural networks out of MIT CSAIL, positioned as smaller and more compute-efficient than transformers — plus an AMD partnership that gives its edge-and-on-device pitch a hardware ally. The problem is that architecture is not a moat: the open-weight small-model lines from Google, Microsoft, and Alibaba attack the same efficiency niche for free, and nothing about a novel architecture locks a customer in once a transformer model matches the benchmark. With no disclosed revenue or pricing behavior, the investable question — whether anyone pays a premium for liquid networks — remains unanswered.
Ramin Hasani is the co-founder and CEO of Liquid AI and a machine-learning scientist who worked at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL), where the liquid neural network research underpinning the company originated. His work centers on liquid neural networks, an architecture inspired by biological nervous systems such as the C. elegans roundworm, which use dynamically adjustable parameters and far less compute than conventional models.
Mathias Lechner is the co-founder and CTO of Liquid AI. He collaborated with the other founders on liquid neural network research at MIT CSAIL before co-founding the company to commercialize Liquid Foundation Models.
Daniela Rus is a co-founder of Liquid AI and a roboticist who directs MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL). Her lab's research on liquid neural networks formed the scientific foundation of the company.
Alexander Amini is a co-founder and chief scientific officer of Liquid AI. He worked on liquid neural network research at MIT CSAIL alongside the other founders prior to launching the company.
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A family of general-purpose, compute-efficient foundation models built on liquid neural networks, including text and multimodal variants.
A customization and deployment platform for building and shipping applications on top of Liquid Foundation Models.
An on-device private AI application for iOS and Android.
