Exploring Fine-Tuning and Grounding Features in AI Models

This chapter discusses the recent advancements in fine-tuning language models through API keys, moving beyond OAuth methods. It also highlights the new grounding feature utilizing Google search results to improve response quality and examines how different providers are evolving in model capabilities.

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Nathan interviews Google product managers Shrestha Basu Mallick and Logan Kilpatrick about the Gemini API and AI Studio. They discuss Google's new grounding feature, allowing Gemini models to access real-time web information via Google search. The conversation explores Gemini's rapid growth, its position in the AI landscape, and Google's competitive strategy. Nathan shares insights from integrating Gemini into his own application and ponders the future of large language model capabilities across providers. Tune in for an in-depth look at Google's AI API product strategy and the latest Gemini features.

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CHAPTERS:

(00:00:00) About the Show

(00:00:53) Sponsors: Weights & Biases RAG++

(00:01:28) About the Episode

(00:04:15) Gemini API Growth

(00:05:26) Intro to AI Studio

(00:07:35) Vertex vs. AI Studio

(00:09:33) Developer Adoption

(00:14:23) Gemini Use Cases (Part 1)

(00:17:41) Sponsors: Shopify | Notion

(00:20:01) Gemini Use Cases (Part 2)

(00:23:08) Multimodality & Flash