Summary
In the podcast episode S3 E4 of Dr. Pawd, host Pieter Abbeel interviews Aiden Gomez, an AI researcher and entrepreneur known for his contribution to the original Transformer neural network paper. The podcast focuses on large language models (LLMs), particularly Transformers, and their applications in natural language processing, computer vision, speech recognition, and protein folding. Gomez, who is the founder of Cohere, a company building tools and APIs that incorporate natural language processing into every developer's toolkit, explains the challenges involved in training LLMs, especially in filtering out noise from the diverse data in the internet.
The discussion also delves into fine-tuning, a necessary phase to steer LLMs toward specific behaviors and tasks, and Cohere's command models that provide an intuitive way to talk to models to get the desired results. The topic of prompt engineering, used to guide the model's state of mind and steer it in the right direction to generate appropriate responses, is also tackled. Moreover, the podcast explores the high cost of computing, talent, and knowledge that has been a barrier for many people to access LLMs. However, Gomez notes that Cohere aims to lower that barrier, making the technology more accessible to everyone.
Furthermore, the podcast goes on to highlight that large language models offer endless possibilities for products and offerings. Cohere provides a platform for everyone to build off of these large language models without needing to raise huge amounts of funding. The podcast concludes by discussing the emerging ecosystem of large language models that are multiplying their utility through repeated action with them. Cohere recently launched a multilingual text understanding model that incorporates 109 languages in a really robust way.
Throughout the podcast episode, Gomez shares his insight into the background and future of LLMs. He discusses entrepreneurship, especially in Europe, and how he became involved in AI research and development. The podcast is described as inspiring, and the listeners are left with a deep understanding of the potential of LLMs. The podcast is recommended for anyone interested in AI, its applications, and its future direction.
