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In this episode of Data Science Bulletin, hosts Martin and Jakub, delve into the current state of reasoning models in AI, with a focus on a recent research paper from Apple entitled "The Illusion of Thinking." The discussion highlights the paper's critique of current benchmarking methods for AI models, emphasizing issues like data contamination and questioning the true reasoning capabilities of these models. The hosts also explore the broader implications of these findings and how they fit into the ongoing debate about the generalizability and limitations of AI reasoning.
Fo more: https://datasciencebulletin.com/dsb-podcast/dsb-podcast-11-illusion-of-thinking/
In this episode of Data Science Bulletin, hosts Martin and Jakub, delve into the current state of reasoning models in AI, with a focus on a recent research paper from Apple entitled "The Illusion of Thinking." The discussion highlights the paper's critique of current benchmarking methods for AI models, emphasizing issues like data contamination and questioning the true reasoning capabilities of these models. The hosts also explore the broader implications of these findings and how they fit into the ongoing debate about the generalizability and limitations of AI reasoning.
Fo more: https://datasciencebulletin.com/dsb-podcast/dsb-podcast-11-illusion-of-thinking/