『Comparing Large Language Models (LLMs), Data Sets, and Potential Breakthroughs』のカバーアート

Comparing Large Language Models (LLMs), Data Sets, and Potential Breakthroughs

Comparing Large Language Models (LLMs), Data Sets, and Potential Breakthroughs

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 In this episode, hosts Erik Brown, EJ, and Ryan Elmore dive into how large language models (LLMs) work and provide a behind-the-scenes look at "Nigel," a generative AI platform developed by West Monroe. The hosts analyze various LLMs, their functionalities, and their real-world implications while offering insights into the balance between technical prowess and practical utility. They also highlight generative AI's current capabilities and debate its future potential across various sectors.

In this episode:
  • Compare Different LLMs: The hosts delve into the functionalities and effectiveness of various large language models, providing insights into their comparative advantages and suitable use cases. This segment helps listeners understand how to choose the right model for specific applications.
  • Understand Current Limitations in AI: The episode covers the current state of generative AI, including its limitations and potential future advancements. This discussion is aimed at providing a comprehensive view of where AI technology stands today and what developments might be on the horizon.
  • Get a Behind-the-Scenes Look: Dive into how generative AI and large language models are applied in real-world scenarios, including a detailed look at the interactive platform "Nigel" by West Monroe–and why West Monroe created it.

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You can watch this series on YouTube
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