OpenAI's new model, O3, has stunned the AI industry with its groundbreaking performance, particularly in solving frontier math problems that even Fields medalists find challenging. It achieved a 25% success rate on a benchmark where the previous state-of-the-art was only 2%. Experts like Ethan Mollick and Francois Chollet acknowledge O3's significant leap in AI capabilities, particularly its ability to adapt to new tasks and solve complex problems when given longer thinking time. However, O3's high computational cost and its failure to solve certain simple logic problems raise questions about its practicality and whether it truly represents AGI. Despite the impressive advancements, there's still debate on whether O3 qualifies as AGI. While it excels in specific domains like math, it struggles with basic reasoning and common sense tasks that even a 5-year-old can solve. The high cost of running O3, estimated at hundreds of thousands of dollars for complex tasks, also raises concerns about its accessibility and sustainability. Nonetheless, O3's development is seen as a significant milestone in AI research, demonstrating the potential of inference time scaling and pushing the boundaries of machine learning capabilities.
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