AI Today Podcast: Generative AI Series: Foundation Models, Fine-Tuning, and Domain-Specific LLMs
Sep 27, 2023
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The podcast explores the concept of generative AI and its impact on organizations. They discuss the use of foundation models and the benefits of fine-tuning these models for specific applications. They also showcase Langchain, a system for building NLP applications on top of language models. Additionally, they touch on the CPM AI training and certification program and its topics.
Foundation models are large pre-trained models that can be adapted for specific applications, reducing the need to train new models from scratch.
Fine-tuning large language models allows for more specific responses tailored to domain-specific or proprietary information and enhances accuracy.
Deep dives
Overview of AI Today podcast and its history
The AI Today podcast, hosted by Kathleen Mulch and Ron Schmelzer, has been running for seven seasons and has witnessed the evolution of AI over the years. The podcast covers emerging AI trends, technologies, and use cases, with interviews and series dedicated to various topics. It explores both the advancements and the challenges in the AI field, providing practical insights for listeners.
Introduction to Generative AI series
The podcast episode features an excerpt from the CPMAI training on generative AI. The focus of this episode is on foundation models and their application in AI projects. Foundation models, which are large pre-trained models for language or computer vision, can be adapted or fine-tuned for specific applications. They handle a broad range of tasks and reduce the need to train new models from scratch. The episode discusses the advantages of foundation models and how they are revolutionizing AI model development.
Fine-tuning Large Language Models
The episode delves into the importance of fine-tuning large language models. While general purpose language models are good for various tasks, fine-tuning allows them to provide more specific responses tailored to domain-specific or proprietary information. Fine-tuning can enhance accuracy, address specific use cases, and ensure up-to-date information. The episode highlights different approaches to fine-tuning, including feature-based fine-tuning and parameter-efficient fine-tuning.
Exploring Langchain and its Applications
The episode introduces Langchain, an open-source framework and toolkit for building applications based on large language models. Langchain facilitates data-aware and agent-based interactions with the models, enabling tasks such as question answering, summarization, code analysis, and more. It offers flexibility in connecting with various data sources, APIs, databases, and web scraping, accelerating AI projects and reducing the need for data collection and labeling.
It’s hard to have a conversation about AI these days without the topic of Generative AI coming up. People are using generative AI and LLMs to help with many things. But what do these technologies mean at an organizational level? And how do you apply this technology for your organization?
In this podcast episode hosts Kathleen Walch and Ron Schmelzer take a deeper look at generative AI.