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Ep22: Demystifying AI and separating hype from genuine progress

Ep22: Demystifying AI and separating hype from genuine progress

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 In this episode, we look into the inflated claims about artificial intelligence, how to distinguish between predictive AI, which often fails to accurately predict individual behavior due to inherent limitations in forecasting and data quality, and generative AI, which is seen more favorably as it creates useful output rather than attempting future predictions. The conversation also touches upon the rapid advancements and decreasing costs of AI development, particularly highlighting the competitiveness of Chinese AI models despite sanctions, and explores the potential societal impacts of AI, including job displacement and the proposal of a "partial lottery system" to mitigate inequalities in merit-based systems. Technological acceleration is increasing exponentially. Innovations that once took decades are now happening in a matter of years, or even months. AI, automation, and robotics are making jobs and industries obsolete while creating new roles and economic opportunities. To make sense of this acceleration our host John Xavier speaks to scientists, business leaders and policymakers on The Interface. Guest: Sayash Kapoor, co-author of AI Snake Oil and computer science Ph.D. candidate at Princeton University. Host: John Xavier, Technology Editor, The Hindu. Edited by Jude Francis Weston

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