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6min chapter
Transformations in AI: Why Foundation Models Are the Future
Smart Talks with IBM
The Efficiency and Limitations of Giant Models
This chapter explores the inefficiency of using one giant model for every problem and highlights the benefits of specialized smaller models. It also delves into the issues of bias and hallucination in AI models and the importance of addressing these problems.
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Discover
highlights
Listen to the best highlights from the podcasts you love and dive into the full episode