Liquid neural networks can modify the equations that underpin their neurons and change how those neurons interact with each other, making them more adaptable than traditional AI models. They can also be implemented with fewer neurons and require fewer parameters, reducing the infrastructure needed to run them. Liquid AI plans to use the funding to build commercial foundation models and launch a platform that will enable customers to develop their own liquid neural networks. The company also plans to hire eight additional employees in the coming months to support its go-to-market efforts.
Key takeaways:
- Liquid AI Inc., a startup developing AI models based on liquid neural network design, has raised $37.6 million in seed funding.
- The company's liquid neural networks can modify their own architecture, making them more adaptable than traditional AI models and can more easily adapt to new situations, reducing the risk of processing errors.
- Liquid neural networks can be implemented with significantly fewer neurons than traditional AI models and require fewer parameters, reducing the amount of infrastructure necessary to run them.
- Liquid AI plans to use the funding to build commercial foundation models and launch a platform that will enable customers to develop their own liquid neural networks.