Fine Tuning LLMs and Optimizing Generative AI Architectures

[@GoCloudArchitects]

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[@ParvizEshonov]

Thank you, David and Mike, for this great high-level overview of how AI systems are developed and fine-tuned. It makes a lot of sense to ensure that the proper dataset is used to build a good AI model, and that the AI model is also maintained and improved to minimize bias and to maintain the relevancy of the information it outputs. This video definitely provided very valuable information.

[@GoCloudArchitects]

Ensuring the right dataset and ongoing maintenance to minimize bias and keep information relevant are crucial steps in building effective AI models. It is great to hear that the video provided the insights you were looking for. We appreciate your feedback!

[@chautmpham1269]

Just watched the video, what an incredible deep dive into fine-tuning LLMs and optimizing generative AI architectures! Mike Gibbs and David Linthicum broke down complex concepts in a way that is easy to understand, making it a must watch for anyone serious about AI architecture. The practical tips on avoiding common pitfalls and ensuring ethical AI are especially valuable.

[@GoCloudArchitects]

David Linthicum and I aimed to make complex topics accessible. It is great to know that the insights on avoiding pitfalls and ethical considerations were especially helpful. Thanks for watching and sharing your thoughts!

[@gcc-markmilo]

Fantastic insights on fine-tuning LLMs in a digestible format! Definitely worth the time watching and understanding the viewpoint of an Architect that is looking to optimize systems such as GenAI.

[@GoCloudArchitects]

Thank you! I'm glad you found the insights on fine-tuning LLMs valuable and easy to understand. It is great to know that the content resonated with you, especially from an architectural perspective. Appreciate you taking the time to watch and share your thoughts!

[@GoCloudArchitects]

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[@GoCloudArchitects]

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