The ambitious journey of OpenAI towards achieving Artificial General Intelligence (AGI) has taken yet another significant leap forwardJust last Friday, during the culmination of the highly anticipated "OpenAI 12 Days of Innovation" event, CEO Sam Altman shared the unveiling of their latest reasoning models, dubbed o3 and o3-miniThese developments are built upon the previously launched o1 model, showcasing a continued evolution in OpenAI's mission to create advanced artificial intelligence.

The structure of the 12-day event cleverly bookended the presentation of the reasoning models, starting with the reveal of o1—what the team affectionately termed as the "fully charged" versionThe evolving narrative around these models reflect OpenAI's strategic approach, aligning the commencement and conclusion of their campaign around the focal point of advancing reasoning capabilities in AI.

At the heart of these new models lies what OpenAI refers to as a "private thinking chain." This innovation allows the models to pause and internally assess their dialogues before delivering a response

This mechanism, labeled "Simulated Reasoning" (SR), enables an AI capability that transcends that of basic Large Language Models (LLMs), pushing the boundaries of what is possible with current AI technology.

From a branding standpoint, it is noteworthy that the designation of the new reasoning model as "o3" was a strategic decision made to avoid any potential trademark issues with the UK telecommunications company O2, showcasing how companies in the tech industry must navigate intellectual property concerns even as they innovate.

During the livestream announcement, Altman described o3 as "a very, very smart model." The assessments derived from OpenAI's evaluations affirm this claim, demonstrating that o3 excels in software engineering tasks, code writing, mathematical competitions, and even in possessing knowledge at the level of a Ph.Din natural sciencesNotably, results suggest that o3 has achieved breakthroughs in OpenAI's objective of reaching AGI, attaining performance levels akin to human capabilities in various testing environments.

OpenAI's reports indicate that the o3 model has set a record score on the ARC-AGI benchmark—a renowned visual reasoning standard that has remained undefeated since its inception in 2019. In scenarios with lower computational demands, o3 scored an impressive 75.7%, whereas its performance skyrocketed to 87.5% during high-computation tests, closely aligning with human performance at the 85% threshold.

Furthermore, o3 scored an astounding 96.7% in the 2024 U.S

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Math Olympiad, missing just one questionSimilar accolades were noted on the GPQA Diamond benchmark, where o3 attained a score of 87.7% across graduate-level biology, physics, and chemistry questionsIn the cutting-edge EpochAI math benchmark tests, o3 resolved 25.2% of presented problems, whereas competitors' models failed to exceed 2%.

The o3-mini variant incorporates adaptive thinking time functionalities, allowing it to output at low, medium, and high processing speeds—higher computational settings reportedly yield superior resultsIn benchmark tests on Codeforces, o3-mini demonstrated performance improvements over its predecessor, o1.

However, an essential caveat was identified during testing—while the o3 exhibits extraordinary performance, its operational costs are notably highFrancois Chollet, the father of Keras (a high-level neural networks API written in Python), released a report highlighting this aspect after o3’s introduction.

The findings revealed that o3 attained an impressive 87.5% score in high computational mode, yet its performance was threefold better than that of o1 in low computational scenarios

First, the cost implications become evident: operating o3 can be prohibitively expensiveFor each task executed in low computational mode, the price tags amount to around $20, but in high computational modes, costs can escalate to thousands.

Chollet succinctly noted, “It is incredibly expensive, but it is not just brute force—these capabilities delve into entirely new realms that warrant serious attention from the scientific community.” This invokes a broader discussion about the balance between the advancement of AI capabilities and the financial barriers that could impede accessibilityAs the landscape of AI technology evolves, these discussions become critical in shaping future developments.

Reasoning models stand as a cornerstone of artificial intelligence, endowed with robust data processing and analytical capabilities, finding applications in diverse fields spanning virtually all areas tied to intelligent automation

Despite the dazzling results from o3, OpenAI is not poised to launch this advanced reasoning model to the broader public in the immediate future.

At the moment, o3 and o3-mini are not officially released to the marketSecurity researchers have the opportunity to register for a preview of o3-mini, while o3 will be made available for preview at a later date, though no specific timeline has been providedAltman emphasized during the livestream that this announcement was not a product launch but merely the introduction of o3, adding that plans are in place to roll out o3-mini by the end of January, followed by o3 itself.

Moreover, Altman expressed a desire for a federal testing framework to be established prior to the official release of new reasoning modelsThis framework would guide oversight and mitigate risks associated with such powerful AI systemsHe pointed out, "There should be some kind of federal testing framework that indicates we are most concerned about monitoring and mitigating harm, suggesting that there is a set of tests to prove that these models are safe before they can be released." This reflects a growing awareness within the AI community of the ethical implications tied to the rapid development of AI technologies.

Remarkably, OpenAI is not alone in the pursuit of reasoning models

Other AI firms have been actively announcing their developments in this spaceFor instance, on November 16, Moonshot AI introduced their next-generation mathematical reasoning model k0-math, followed by DeepSeek's preview release of its first reasoning model, DeepSeek-R1-Lite, on November 20. Shortly after, on November 28, Alibaba Cloud’s Tongyi team launched the groundbreaking AI reasoning model QwQ-32B-Preview.

In a concurrent revelation on December 19 local time, Google unveiled its first reasoning model, Gemini 2.0 Flash ThinkingThis model shares a conceptual approach with o1—employing a slow-thinking methodology—and brings forth novel visualization capabilities that provide a comprehensive display of thought processes, particularly useful for complex issues such as mathematics and programming.

The most significant distinction in Gemini 2.0 Flash Thinking compared to o1 pertains to user experience; it allows users to observe the step-by-step reasoning process, thereby providing clearer insight into how conclusions are drawn