O3 is OpenAI's second-generation reasoning model. The company skipped O2 to avoid an intellectual property dispute with a large British telecom company.
O3 outperformed O1 by nearly 23 percentage points on a standard coding benchmark and surpassed OpenAI's chief scientist on Codeforces, ranking among the top 200 in the world.
O3 achieved a near-perfect score on the AIME math exam, missing only one question.
O3 scored 85% on the ARC-AGI test, tripling O1's score. This test measures a model's ability to handle novel problems that are difficult to pre-train, focusing on reasoning capabilities.
Cholet acknowledged O3 as a significant breakthrough in AI's ability to adapt to novel tasks but noted that it is not yet AGI, as there are still easy tasks it cannot solve.
O3's coding abilities suggest it could outperform 99.95% of programmers on competitive coding platforms, raising concerns about job displacement in the coding industry.
While O3 excels in competitive coding challenges, it may not be as effective in real-world programming tasks that require broader problem-solving and collaboration skills.
Didi Das noted that O3 achieved a 25% success rate on a highly challenging math benchmark created by math professors, a feat no other model has come close to.
At $3,000 per task, O3 is already more cost-effective than hiring McKinsey, highlighting its potential as a labor-saving tool despite its high compute costs.
Malik argues that societal and organizational change will be slower than technological advancements due to human inertia, giving society time to adapt to AI's capabilities.
Explore OpenAI's latest achievements with O3, the reasoning model that sparked conversations about its proximity to AGI. This episode unpacks its groundbreaking performance on benchmarks like ARC, Codeforces, and math challenges while addressing the implications for jobs, coding, and society. Hear expert insights on whether O3 signals the dawn of AGI or a significant milestone in AI’s evolution. Brought to you by:
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