Introduction of OpenAI o1 and Its Reasoning Capabilities:
- The new model, dubbed OpenAI o1, can solve problems that stump existing AI models, including OpenAI’s most powerful existing model, GPT-4o. Rather than summon up an answer in one step, as a large language model normally does, it reasons through the problem, effectively thinking out loud as a person might, before arriving at the right result (Knight, 2024).
- This is what we consider the new paradigm in these models,” Mira Murati, OpenAI’s chief technology officer, tells WIRED. “It is much better at tackling very complex reasoning tasks (Knight, 2024).
Performance Comparison with GPT-4o and Impact of Reasoning Approach:
- On the American Invitational Mathematics Examination (AIME), a test for math students, GPT-4o solved on average 12 percent of the problems while o1 got 83 percent right, according to the company (Knight, 2024).
- OpenAI’s Chen says that the new reasoning approach developed by the company shows that advancing AI need not cost ungodly amounts of compute power. “One of the exciting things about the paradigm is we believe that it’ll allow us to ship intelligence cheaper,” he says, “and I think that really is the core mission of our company (Knight, 2024).”
Reinforcement Learning and Its Role in Improving Reasoning:
- Murati says OpenAI o1 uses reinforcement learning, which involves giving a model positive feedback when it gets answers right and negative feedback when it does not, in order to improve its reasoning process. ‘The model sharpens its thinking and fine tunes the strategies that it uses to get to the answer,’ she says. Reinforcement learning has enabled computers to play games with superhuman skill and do useful tasks like designing computer chips. The technique is also a key ingredient for turning an LLM into a useful and well-behaved chatbot (Knight, 2024).
Analysis
I’m interested in this article because AI has already played a huge and irreplaceable role in this era, and I believe I could potentially integrate AI systems into my project. OpenAI’s new model, code-named Strawberry and officially called OpenAI o1, represents a shift from merely scaling model sizes, like GPT-4, to focusing on improving reasoning capabilities. The key difference between this new model and traditional large language models (LLMs) is its ability to solve problems step by step, rather than providing one-step solutions. This makes the model much more effective at tackling complex, calculation-based problems.
I found the concept of reinforcement learning particularly interesting. While it’s not entirely new, it still amazed me that the idea of AI improving itself, making adjustments, and sharpening its strategies based on feedback is similar to how humans learn. With reinforcement learning, OpenAI o1 can solve more complex questions, such as advanced math and chemistry problems, which I find inspiring as I explore how to integrate AI into my project.
Reference
Knight, W. (2024, September 12). OpenAI announces a new AI model, code-named Strawberry, that solves difficult problems step by step. Wired. https://www.wired.com/story/openai-o1-strawberry-problem-reasoning/
OpenAI (2024). ChatGPT4o (September 12 Version) [large language model]. https://chatgpt.com/c/66e3504c-ce58-800e-8279-aae14c7e9971
