Transformations in AI: Why Foundation Models are the Future
Smart Talks with IBM
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Rise of Foundation Models in AI
This chapter explores the surge in AI interest attributed to generative AI models like GPT, back propagation, deep learning, and self-supervised learning. It discusses the concept of foundation models in AI, highlighting how they alleviate labor-intensive data labeling by pre-training on vast datasets, enabling efficient automation of tasks. The chapter emphasizes the importance of choosing the right model size for different problems and touches upon bias and hallucination issues in AI models.
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