OpenAI’s o3 model is acing AI reasoning tests–but it’s still not AGI

The race for artificial general intelligence (AGI) continues as OpenAI’s latest o3 model achieves remarkable scores on a key reasoning test, though experts maintain it falls short of true human-level intelligence.

Breaking development: OpenAI’s new o3 model has achieved a breakthrough score of 75.7% on the Abstraction and Reasoning Corpus (ARC) Challenge, a test designed to evaluate AI systems’ pattern recognition and reasoning capabilities.

• The model demonstrated unprecedented task adaptation abilities not previously seen in GPT-family models
• The official score was achieved within the competition’s computing cost limit of $20 per puzzle task
• An unofficial score of 87.5% was reached using significantly more computing power, surpassing the typical human score of 84%

Technical details and constraints: The ARC Challenge tests AI systems’ ability to identify patterns in colored grid puzzles while operating within specific computational limitations.

• The “semi-private” test, used for public rankings, allows computing costs up to $10,000 total
• A more stringent “private” test, used for determining grand prize winners, limits computing costs to 10 cents per task
• O3’s unofficial high score required 172 times more computing power than its official attempt, with costs reaching thousands of dollars per task

Expert perspectives: Leading AI researchers and competition organizers maintain that while impressive, this achievement does not constitute AGI.

• François Chollet, ARC Challenge creator, describes it as an important milestone but not AGI
• Melanie Mitchell of the Santa Fe Institute argues that solving tasks through computational brute force defeats the challenge’s purpose
• Thomas Dietterich from Oregon State University notes that commercial AI systems still lack crucial components of human cognition, including episodic memory and meta-cognition

Industry implications: The achievement comes during a period of perceived slowdown in AI advancement compared to the rapid developments of 2023.

• The results suggest AI models could soon legitimately beat the competition benchmark
• Multiple submissions have already scored above 81% on the private evaluation test set
• Competition organizers are planning a more challenging benchmark test for 2025

Looking ahead: While o3’s performance represents significant progress in AI capabilities, key questions remain about the model’s methodology and true understanding of the tasks it completes.

• Researchers await open-source replication to fully evaluate the achievement’s significance
• The ARC Prize 2025 challenge continues until someone achieves the grand prize with an open-source solution
• The gap between computational problem-solving and true human-like reasoning remains a central challenge in AI development