OpenAI has introduced a new model series, GPT-o1, which demonstrates superior reasoning capabilities compared to previous models, offering promising performance.
GPT-o1: Enhanced Reasoning Abilities
This series of new reasoning models is designed to help solve complex problems. These models are specially trained to think longer before responding, capable of tackling more challenging problems in fields like science, coding, and mathematics. GPT-o1 will initially be available on ChatGPT and the API.
How do the new models operate? According to official introductions, they are trained to think like humans, trying different strategies to solve problems and promptly identify errors.
Tests have shown that the performance of the next-generation models is comparable to that of doctoral students in high-difficulty tasks such as physics, chemistry, and biology, especially excelling in mathematics and coding. For instance, in the qualifying exam for the International Mathematical Olympiad, the traditional model GPT-4o only solved 13% of the problems correctly, while the new reasoning model achieved 83%. In coding competitions on Codeforces, they scored 89%.
However, it's important to note that as an early model, o1-preview lacks some practical features for ChatGPT, such as web browsing and file uploading. Yet, it represents a significant advancement in handling complex reasoning tasks. To align with the capabilities of the new model, researchers have also enhanced security measures to ensure compliance with safety and alignment guidelines.
These enhanced reasoning abilities are particularly suitable for users who solve complex problems in science, coding, mathematics, and other fields, such as medical researchers, physicists, and developers.
OpenAI o1-mini
OpenAI has also released a smaller model, OpenAI o1-mini, which excels in code generation and debugging with lower costs, suitable for applications requiring reasoning but not extensive knowledge.
As a smaller model, o1-mini is 80% cheaper than o1-preview, making it a powerful and cost-effective option for applications requiring reasoning without the need for extensive world knowledge.
How to Use GPT-o1
Starting today, ChatGPT Plus and Team users can find the o1-preview and o1-mini options in the model selection. Subsequently, ChatGPT Enterprise and Edu users will also gain access to these models. For developers, users meeting the API usage criteria can already start prototyping with these models.
In the future, the official will continuously update these reasoning models, adding more practical features, including browsing and file uploading, to ensure a better user experience.
However, to fully utilize this new model, users need to adjust their prompting methods, as the working mechanism of GPT-o1 differs significantly from GPT-4 and even GPT-4o.
According to OpenAI's API documentation, the GPT-o1 model prefers simple and direct prompts.
Prompt Engineering Design, Simplifying Model Guidance
This means users do not need to provide complex guidance or extensive context as before. Previous models required more guidance, often utilizing longer context windows to help the model understand tasks, but GPT-o1 has stronger internal reasoning capabilities and thus no longer needs these lengthy explanations.
OpenAI also reminds users to pay attention to the following when using the o1 model:
- Keep prompts simple and direct, avoiding excessive guidance as the model can understand instructions well.
- Avoid using "chain of thought" prompts, as the o1 model can perform internal reasoning.
- Use delimiters such as triple quotes, XML tags, and section titles to clarify which part the model is parsing.
- Limit additional contextual information, especially when performing enhanced retrieval generation (RAG) tasks, as adding too much background information can complicate the model's responses.
This is a departure from OpenAI's previous advice to users. Previously, OpenAI recommended being very specific, including detailed information and guiding the model step-by-step, but now GPT-o1 can think independently and find solutions to problems.
In a blog by Ethan Mollick, a professor at the Wharton School of the University of Pennsylvania, he mentioned that as an early user, he found GPT-o1 to perform better in tasks requiring planning, able to come up with solutions on its own.
Prompt engineering is becoming increasingly important, not only as a crucial skill but also as a new career category. To this end, other AI developers have also introduced tools to facilitate user-designed prompts, such as Google's Prompt Poet, which integrates external data sources to make responses more relevant.
Due to the differences in GPT-o1, users are still figuring out how to use it. However, some social media users predict that people will have to change the way they prompt ChatGPT.
Although GPT-o1 is still new, and users are exploring how to use it, some social media users have already predicted that people will need to rethink their interactions with ChatGPT.
Official Blog: https://openai.com/index/introducing-openai-o1-preview/
Key Points:
- 🤖 The GPT-o1 model requires simple, direct prompts rather than complex guidance.
- 🧠 Avoid using chain of thought prompts, as the o1 model already possesses internal reasoning capabilities.
- 📑 Use delimiters to clearly identify the parts the model is parsing and limit additional context to avoid complex responses.
