Evolving Tool Use
The conversation delves into the exciting evolution of tool use in language models, highlighting retrieval augmented generation as a key example. By integrating tools like calculators and Python, models can perform complex tasks such as generating graphs from data. This progression hints at a future where language serves as the primary interface between users and computers, enabling seamless interaction and problem-solving.In this clip
From this podcast
Machine Learning Street Talk (MLST)
Cohere co-founder Nick Frosst on building LLM apps for business
Related Questions
Do I get it right that a Retrieval Augmented Generation (RAG) system can retrieve data in addition to its training data as discussed in the episode with Cohere co-founder Nick Frosst on building LLM apps for business?
Do I get it right that a Retrieval Augmented Generation (RAG) system can retrieve data in addition to its training data, as discussed in the episode with Cohere co-founder Nick Frosst on building LLM apps for business?
Do I get it right that a Retrieval Augmented Generation (RAG) system can retrieve data in addition to its training data, as discussed in the episode with Cohere co-founder Nick Frosst on building LLM apps for business and the clip Model Evaluation Insights?