DataFramed
#226 Creating Custom LLMs with Vincent Granville, Founder, CEO & Chief Al Scientist at GenAltechLab.com
Jul 15, 2024
Vincent Granville, Founder and CEO of GenAI Tech Lab and a prominent figure in the AI field, discusses the intriguing world of custom large language models (LLMs). He highlights the limitations of standard LLMs and the unique advantages of developing custom solutions tailored to specific corporate needs. The conversation dives into the importance of knowledge graphs, ethical considerations, and the evolving dynamics of AI in information retrieval. Vincent also shares his insights on navigating the complexities of LLM development, including legal and technical challenges.
52:48
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Quick takeaways
- Creating custom LLMs caters to specialized knowledge requirements that existing models struggle to address.
- Custom LLMs enhance efficiency by focusing on specialized topics like statistics and probability, outperforming standard tools.
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Reasons for Developing Custom LLMs
The decision to create custom LLMs arises from the need to cater to specialized knowledge requirements that existing models struggle to address. Traditional language models like Google Search or GPT may not offer the depth or technical focus required, prompting the development of tailored solutions. By creating a bespoke LLM, based on a simple yet specialized architecture, users can access precise and advanced information, especially beneficial for professional users seeking specific insights.
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