About Liquid AI
Liquid AI builds general-purpose AI models that depart from the transformer design used by most large language models. Its Liquid Foundation Models are based on dynamical systems theory, which describes how a system's state changes over time, and grew out of earlier work on liquid neural networks. The company says the models are aimed at private, on-device and on-premise use. Liquid AI is a spinout from MIT, founded by researchers including Ramin Hasani, Mathias Lechner, Alexander Amini and Daniela Rus, and is headquartered in Boston, Massachusetts.
Liquid AI was founded in 2023 and is based in Boston, MA, United States. It is listed under Neuromorphic Computing, AI Accelerators. Reported funding is $250M Series A (Dec 2024, AMD Ventures-led, $2.35B valuation).
Compute Technologies
- Neuromorphic
- AI Accelerators
What Liquid AI works on
Neuromorphic Computing
Neuromorphic computing builds chips that copy some features of the brain. Instead of a central processor and separate memory, a neuromorphic chip has many small units that act like neurons, each with its own local memory, joined by connections that act like synapses.
AI Accelerators
An AI accelerator is a chip, or a part of a chip, designed to run machine learning faster or with less energy than a general-purpose processor. The category includes GPUs, TPUs, neural processing units (NPUs) and chips from many startups.
Also in United States
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