Cohere's SVP Technology - Saurabh Baji

Saurabh Baji discusses Cohere's approach to developing and deploying large language models (LLMs) for enterprise use. * Cohere focuses on pragmatic, efficient models tailored for business applications rather than pursuing the largest possible models. * They offer flexible deployment options, from cloud services to on-premises installations, to meet diverse enterprise needs. * Retrieval-augmented generation (RAG) is highlighted as a critical capability, allowing models to leverage enterprise data securely. * Cohere emphasizes model customization, fine-tuning, and tools like reranking to optimize performance for specific use cases. * The company has seen significant growth, transitioning from developer-focused to enterprise-oriented services. * Major customers like Oracle, Fujitsu, and TD Bank are using Cohere's models across various applications, from HR to finance. * Baji predicts a surge in enterprise AI adoption over the next 12-18 months as more companies move from experimentation to production. * He emphasizes the importance of trust, security, and verifiability in enterprise AI applications. The interview provides insights into Cohere's strategy, technology, and vision for the future of enterprise AI adoption. https://www.linkedin.com/in/saurabhbaji/ https://x.com/sbaji https://cohere.com/ https://cohere.com/business MLST is sponsored by Brave: The Brave Search API covers over 20 billion webpages, built from scratch without Big Tech biases or the recent extortionate price hikes on search API access. Perfect for AI model training and retrieval augmentated generation. Try it now - get 2,000 free queries monthly at http://brave.com/api. TOC (*) are best bits 00:00:00 1. Introduction and Background 00:04:24 2. Cloud Infrastructure and LLM Optimization 00:06:43 2.1 Model deployment and fine-tuning strategies * 00:09:37 3. Enterprise AI Deployment Strategies 00:11:10 3.1 Retrieval-augmented generation in enterprise environments * 00:13:40 3.2 Stand