In a recent development, OpenAI unveiled their latest creation, the o1 model, which has been anticipated by many as a potential leap forward in AI technology. However, initial impressions suggest that the model might be more of an incremental update rather than a revolutionary breakthrough. The o1 model, while showcasing advancements in complex reasoning and enhanced security features through reinforcement learning, remains tethered to the foundational constraints of the GPT architecture and the Transformer-based framework. Notably, the model includes a novel feature that tracks its reasoning process and estimated thinking time, indicating a step towards more transparent AI operations. Yet, the o1's knowledge base appears to be capped at an October 2023 update, possibly due to its beta status. This release aligns with previous predictions regarding functional enhancements, yet falls short of expectations for a transformative shift in AI capabilities.
(276 characters)
For a stricter 300-word limit, the summary could be further condensed:
OpenAI's newest model, o1, introduces improvements in complex reasoning and security via reinforcement learning, yet retains the limitations of the GPT and Transformer frameworks. Its tracking of reasoning processes and thinking time adds transparency, though the knowledge base's October 2023 cutoff hints at a beta phase. Despite functional advances, o1 represents an evolutionary step rather than a revolutionary leap in AI.
(194 characters)
Asianfin -- I saw the news that OpenAI has released the long-awaited new model Orion o1 today, but I was a little disappointed. I said in my last video that the iteration of the GPT large model has entered a bottleneck period. And o1 seems to be just a transitional product, not a breakthrough.
Essentially, o1 is trained through reinforcement learning in complex reasoning capabilities and security mechanisms. Indeed, significant progress has been made in these two aspects. However, the existing fundamental limitations of GPT and the underlying architecture based on Transformer have not changed.
The new model is not named Orion exactly, nor the project code Strawberry, but o1. Unlike GPT, the o1 model marks its own reasoning process and thinking time, but it seems that its knowledge base was only updated as of October 2023. The reason may be that it is still in the beta stage. From a functional point of view, it is similar to what I predicted in the last video.
First, it has more enhanced complex reasoning capabilities and is specially designed to deal with complex reasoning tasks, such as solving mathematical problems and generating complex code. In International Mathematical Olympiad, GPT 4o can only answer 13% of the problems correctly, while the correct rate of o1 model reaches 83%.
Second, its reinforcement learning is closer to the way human thinking and reasoning, and it introduces new security protocols in the security mechanism, becoming more compliant with the rules. For example, in one of the hardest jailbreaking test of OpenAI, the o1 Preview model scored 84, while the GPT 4o scored 22. These improvements all indicate that the o1 model will provide more possibilities for ToB scenario applications, rather than for ToC.
It is foreseeable that OpenAI will earn more from ToB business. The o1 model series focuses more on specialized complex tasks than general-purpose AI, making it an important tool for coding mathematics and scientific research experts, especially in scientific research, engineering calculation, medical treatment, data analysis and other scenarios. The advanced reasoning capabilities of the o1 model make it particularly suitable for enterprise users.
In addition, OPAI also released the o1 mini version, and the cost of o1 Mini is roughly 80% lower than that of o1 Preview. Designed to provide more cost-effective options for developers and professional teams, enterprises can also use these models to develop and deploy complex workflows and solutions, and these requirements are usually the mainstream requirements in the B2B market.
It should be noted that ToB has never been the main area for China’s application innovation. When we say that China leads in application innovation, we are talking about the ToC application market and individual user applications, not ToB. The U.S. ToB market is way more mature than the Chinese ToB market, so for a long time to come, we may no longer be able to claim that we lead in the AI applications, and it will become more difficult to catch up.
