The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) The Enterprise LLM Landscape with Atul Deo - #640
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Jul 31, 2023 Atul Deo, General Manager of Amazon Bedrock, brings a wealth of experience in software development and product engineering. He dives into the intricacies of training large language models in enterprises, discussing the challenges and advantages of pre-trained models. The conversation highlights retrieval augmented generation (RAG) for improved query responses, as well as the complexities of implementing LLMs at scale. Atul also unveils insights into Bedrock, a managed service designed to streamline generative AI app development for businesses.
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Foundation Models vs. Task-Specific Models
- Companies previously built task-specific models, leading to scaling challenges and expert dependency.
- Foundation models leverage unlabeled data and centralized training, enabling broader applications.
The LLM Analogy
- Atul Deo analogizes a pre-trained LLM to a smart employee stuck in a conference room without resources.
- LLMs need access to tools and data sources to be truly productive, like an employee needing access to company systems.
Retrieval Augmented Generation (RAG)
- Retrieval Augmented Generation (RAG) enhances LLMs by providing relevant context from documents within prompts.
- This allows LLMs to answer questions accurately by grounding responses in provided information, like giving an employee access to files.