Iman Mirzadeh

Iman Mirzadeh, an AI researcher at Apple, presents fresh insights from his GSM-Symbolic paper. He distinguishes between intelligence and achievement in AI, emphasizing that current methodologies fall short. The conversation explores the limitations of Large Language Models in genuine reasoning and the impact of integrating tools for improved AI performance. Mirzadeh advocates for rethinking benchmarks to capture true intelligence and discusses the importance of active engagement in learning processes, suggesting a paradigm shift is essential for future advancements.