Can GPT-5 Really Solve Research-Level Maths Problems?

Summary

In this video, a PhD math researcher expresses both excitement and skepticism over the launch of GPT-5. Despite concerns about a misleading graph presented by OpenAI, the researcher finds GPT-5 to be highly effective in addressing complex mathematical problems. The model's improved ability to solve research problems, offer creative insights, and deliver faster, more accurate results is highlighted. Although there are doubts surrounding OpenAI’s business model, the researcher is impressed by GPT-5’s performance compared to its predecessors and competitors like Gemini, especially in math-related tasks, making it a valuable tool for research.

Takeaways

• 😀 The speaker expresses skepticism about OpenAI's GPT-5 launch, particularly around a confusing bar chart presented in the release.
• 😀 The speaker highlights concerns about OpenAI's valuation and unprofitability despite its large valuation.
• 😀 The speaker is a PhD math researcher, and they were excited about the potential of GPT-5 to solve complex research problems.
• 😀 The speaker tested GPT-5 by asking it to simulate the Riemann Zeta function, a well-known mathematical function related to the Riemann Hypothesis.
• 😀 GPT-5's ability to generate a 500-line code to simulate the Riemann Zeta function impressed the speaker, saving significant time and effort.
• 😀 The speaker compares GPT-5's simulation quality with previous models and finds it significantly improved, especially for outreach talks.
• 😀 GPT-5 provided insightful and creative answers to the speaker's math research questions, exceeding expectations compared to GPT-3.
• 😀 Despite initial concerns, GPT-5 delivered faster and more detailed responses than previous versions, showing better reasoning ability.
• 😀 The speaker emphasizes the value of GPT-5 in assisting with research, allowing them to work more efficiently and focus on other activities.
• 😀 The speaker compares GPT-5 to Google's Gemini, noting that GPT-5 consistently provides more creative and effective solutions to math problems.
• 😀 The speaker is cautiously optimistic about GPT-5's potential and acknowledges its performance improvements while recognizing the flawed presentation of graphs in OpenAI's release.

Q & A

What concerns does the speaker have regarding the GPT-5 launch?

The speaker is concerned about the confusing bar chart presentation in the launch, where it seems illogical that 52.8 is considered bigger than 69.1, which is then the same size as 30.8. This raises doubts about the accuracy of the visuals and whether the product can live up to its promises.

Why is the speaker particularly interested in GPT-5?

The speaker, a PhD mathematics researcher, is excited about the potential capabilities of GPT-5 in tackling complex research problems in mathematics, particularly ones that previous models could not address.

How does the speaker feel about the quality of GPT-5's simulation capabilities?

The speaker is impressed by GPT-5’s ability to create high-quality simulations. It has created simulations such as the Riemann Zeta function and the Koch curve in a way that is both visually appealing and functional, saving the speaker considerable time.

What is the significance of the Riemann Zeta function mentioned in the transcript?

The Riemann Zeta function is a complex mathematical function, notably associated with the unsolved Riemann Hypothesis. The speaker is interested in how GPT-5 might be able to simulate or provide insight into such functions, which are crucial in mathematical research.

How does the speaker compare GPT-5 to previous models, like GPT-3?

The speaker compares GPT-5 favorably to GPT-3, noting that GPT-5’s performance in handling complex problems and offering detailed, creative solutions was significantly better than GPT-3's. It was able to produce answers with more depth and insight, which the speaker found impressive.

What role does the speaker see GPT-5 playing in their daily work as a researcher?

GPT-5 helps the speaker accelerate their research by quickly processing large amounts of information and generating reasonable, logical answers. This allows the speaker to focus on other areas of their work, such as learning the piano.

What concern did the speaker express regarding the thinking time of the models?

The speaker was concerned that with GPT-5, the granularity of selecting models had decreased, which might affect the time spent reasoning through problems. However, the speaker notes that GPT-5 still provides valuable answers within a reasonable time frame (3-6 minutes).

Why does the speaker believe that GPT-5 could be more sustainable for OpenAI?

The speaker hopes that GPT-5’s improved efficiency will help OpenAI reduce operational costs, making the service more sustainable. The speaker emphasizes that sustainability is important, as the company currently operates at a loss despite its high valuation.

How does the speaker describe their experience with Google's Gemini model in comparison to GPT-5?

The speaker had a negative experience with Google’s Gemini model, stating that its responses to mathematical queries were inadequate. In contrast, GPT-5 consistently provided creative and useful answers, making it the preferred tool for the speaker.

What other industries or sectors does the speaker mention where GPT-5 has had a positive impact?

The speaker mentions friends in the semiconductor industry who were impressed by GPT-5’s ability to help identify bugs. One example involved GPT-5 spotting additional bugs that GPT-3 had missed, which demonstrates its usefulness across different fields.