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Cracking the AI Code: ROI, Challenges, and Insights with Luke Arrigoni | Part 2

Making Data Simple

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Challenges of Using Large Language Models and Tailored Solutions

This chapter discusses the challenges of using large language models and the importance of having tailored solutions for specific domains. They emphasize the need to avoid bias and suggest collaboration with IBM for sustainable hardware spending. The chapter also delves into their engagement process with clients, prototype building phases, and the significance of education and knowledge transfer.

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