Configurable Foundational Models: A Modular Approach to Building LLMs
The episode describes a new approach to building large language models (LLMs) based on modularity. This approach, called "configurable foundational models," involves dividing an LLM into distinct functional modules, called "bricks," which can be dynamically combined to tackle complex tasks. The bricks can be pre-trained or customized to meet specific needs, offering unprecedented flexibility and adaptability. This approach promises to improve computational efficiency, reusability, scalability, and personalization of LLMs. The episode also explores the challenges and future directions of this new technology, such as managing interactions between bricks, developing protocols for their construction and updating, and protecting data privacy.