Scaling LLMs and Accelerating Adoption with Aidan Gomez at Cohere
Show notes
On this episode, we’re joined by Aidan Gomez, Co-Founder and CEO at Cohere. Cohere develops and releases a range of innovative AI-powered tools and solutions for a variety of NLP use cases. We discuss: - What “attention” means in the context of ML. - Aidan’s role in the “Attention Is All You Need” paper. - What state-space models (SSMs) are, and how they could be an alternative to transformers. - What it means for an ML architecture to saturate compute. - Details around data constraints for when LLMs scale. - Challenges of measuring LLM performance. - How Cohere is positioned within the LLM development space. - Insights around scaling down an LLM into a more domain-specific one. - Concerns around synthetic content and AI changing public discourse. - The importance of raising money at healthy milestones for AI development. Aidan Gomez - https://www.linkedin.com/in/aidangomez/ Cohere - https://www.linkedin.com/company/cohere-ai/ Thanks for listening to the Gradient Dissent podcast, brought to you by Weights & Biases. If you enjoyed this episode, please leave a review to help get the word out about the show. And be sure to subscribe so you never miss another insightful conversation. Resources: - https://cohere.ai/ - “Attention Is All You Need” #OCR #DeepLearning #AI #Modeling #ML
Guests
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