Liquid AI plans to commercialize this technology and compete with companies building generative AI models. The company also plans to provide on-premises and private AI infrastructure for customers and a platform for building their own models. The company's liquid neural network technology has potential applications in areas such as drone search and rescue, wildlife monitoring, delivery, electric power grids, medical readouts, financial transactions and severe weather patterns.
Key takeaways:
- Liquid AI, an MIT spinoff co-founded by robotics expert Daniela Rus, has raised $37.5 million in a two-stage seed round. The company is valued at $303 million post-money.
- The company aims to build general-purpose AI systems powered by a relatively new type of AI model called a liquid neural network. These networks are smaller than traditional AI models and require less compute power to run.
- Liquid neural networks can adapt their parameters over time, allowing them to deal with shifts in their surroundings and circumstances even if they weren't trained to anticipate these shifts.
- Liquid AI plans to commercialize the liquid neural network architecture and provide on-premises and private AI infrastructure for customers. The company also plans to enable customers to build their own models for various use cases.