Cohere co-founder Nick Frosst on building LLM apps for business
Jun 16, 2024
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Nick Frosst, Co-founder of Cohere, discusses the future of LLMs and AGI, solving real business problems with AI models. He talks about Cohere's Command R* models, challenges with large language models, specialized vs. general-purpose models, retrieval augmented generation, and the evolving benchmarks in language model development.
Cohere prioritizes practical business solutions over AGI ambitions.
Cohere's Command R models enhance language models with retrieved external knowledge for improved performance.
Deep dives
Cohere's Focus on Real-World Solutions
Cohere distances itself from AGI ambitions, prioritizing practical technology applications to solve real-world problems. The release of Command R models by Cohere, particularly beneficial for retrieval augmented generation, aims to enhance language models with external knowledge retrieved from databases. This approach helps in knowledge-intensive tasks where external information augments the model's performance.
Nick Frost's Background and Cohere's Focus on Business Solutions
Nick Frost, a co-founder of Cohere, shares his journey from meeting Aiden at Google Brain to co-founding Cohere. The company's differentiation lies in its focus on developing specialized technology for real-world enterprise solutions, rather than pursuing AGI aspirations. Cohere's objective is to leverage language models for businesses' practical needs, aiming to serve specific business purposes using retrieved external knowledge.
The Evolution and Significance of Command -R Models
Cohere introduces the Command -R and Command -R Plus models, known for multilingual retrieval augmented generation and tool use capabilities. By open-sourcing these models, Cohere encourages builders and enterprises to explore and utilize them for real-world problem-solving applications. The standout feature, retrieval augmented generation, enhances language models by ensuring extracted information is relevant, accurate, and traceable back to its source.
Future Prospects of Multi-Step Tool Use in Language Models
Cohere's exploration of tool use within language models, like search queries, calculators, and Python interpreters, hints at potential advancements in multitasking capabilities. The integration of various tools in a multi-step process could revolutionize how language models interact with external systems and automate complex tasks, enhancing their utility in diverse business scenarios. By combining and chaining these tools effectively, language models could become efficient interfaces for a wide range of applications, bridging human-computer interactions seamlessly.
Nick Frosst, co-founder of Cohere, on the future of LLMs, and AGI. Learn how Cohere is solving real problems for business with their new AI models.
This is the first podcast from our new Cohere partnership!
Nick talks about his journey at Google Brain, working with AI legends like Geoff Hinton, and the amazing things his company, Cohere, is doing. From creating the must useful language models for businesses to making tools for developers, Nick shares a lot of interesting insights. He even talks about his band, Good Kid! Nick said that RAG is one of the best features of Cohere's new Command R* models. We are about to release a deep-dive on RAG with Patrick Lewis from Cohere, keep an eye out for that - he explains why their models are specifically optimised for RAG use cases.
Disclaimer: We are in a partnership with Cohere to release content for them. We were not told what to say in the interview, and didn't edit anything out from the interview. We are currently planning to release 2 shows per month under the partnership about their AI platform, research and strategy.
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