GPT-5.2 Breaks Ground | First AI Solves Erdos Problem
Edited By
James O'Connor
In a groundbreaking achievement for artificial intelligence, a team has successfully used GPT-5.2 to resolve an Erdos Problem, marking a notable milestone in advancements of language models in mathematical research. This case highlights both potential and challenges, as previous models struggled significantly with similar tasks.
Understanding the Challenge
Yesterday's resolution of an Erdos Problem—an open mathematical question—by an LLM represents a pivotal moment for AI in research. The endeavor not only illuminates the evolving capabilities of AI but also offers insights on workflows that may assist others in academic and technical environments.
Interestingly, users have encountered several challenges over the years with various AI models, including Gemini 2.5 and Gemini 3, which notably faced barriers like internet dependency and hallucinations in their solutions. As one user put it, "AI acts like a brilliant child, afraid to fail under pressure."
The Breakthrough with GPT-5.2
GPT-5.2, released recently, has transformed the landscape of mathematical proof writing. Users reported that this model demonstrated clarity and honesty in its proofs. Instead of fabricating solutions, it acknowledged when it could not complete a proof, stating something like, "I couldn't prove Lemma X due to complexity." This level of transparency marked a significant shift from earlier experiences.
The Path to Solving Erdos #728
When tackling Erdos Problem #728, the team structured their workflow carefully:
Research Phase: The team prompted GPT-5.2 to understand the problem and brainstorm ideas.
Drafting: After generating initial thoughts, the model created a framework for proof without accessing the internet.
Refinements: A separate instance analyzed and corrected the output, facilitating a round of peer review.
Finalization: The proof was auto-formalized using Lean, targeting clarity and precision.
Through collaboration, including contributions from mathematician Terence Tao, the implementation of feedback allowed advancement toward a comprehensive proof. Tao remarked on the proposal's ambiguity, labeling it as a partial solution while highlighting the team’s efforts to sharpen their argument.
Community Sentiment
The response from the community has been overwhelmingly supportive. Commenters expressed excitement for the potential of future models. As one observer noted, "Assuming everything holds up, congratulations on this truly remarkable milestone!" The community seems eager for the upcoming GPT version—5.5—expected to enhance problem-solving further.
Key Insights
📊 A breakthrough in AI: GPT-5.2 is the first AI to resolve an Erdos Problem not previously solved by humans.
💬 Community engagement: Users highlighted the importance of collaboration in reaching this success.
🚀 Evolving technology: Anticipation builds for future models like GPT-5.5, expected in Q1.
The impact of this achievement emphasizes the growing role of AI in advanced mathematics, potentially reshaping research methodologies in various disciplines. As the technology continues to evolve, the hope remains that innovations will further lower barriers to complex problem-solving.
What Lies Ahead for AI in Mathematics
As researchers continue to explore the boundaries of artificial intelligence in solving complex problems, there’s a strong chance we will see even more breakthroughs in mathematical research. Experts estimate around an 80% probability that following GPT-5.2's success, enhanced models will emerge, capable of tackling more difficult problems previously deemed insurmountable. This could lead to rapid advancements in fields like cryptography and theoretical physics, as AI's role in generating innovative solutions evolves. The collaboration fostered within user boards suggests a paradigm shift in how mathematicians and computer scientists will work together, laying the groundwork for future generations of problem-solving tools.
A Historical Echo: From Calculators to Collaborative Genius
Reflecting on past advancements, the introduction of the first electronic calculators in the 1970s serves as an interesting parallel. Initially, many math professors viewed calculators with skepticism, believing they would diminish students’ abilities to solve problems independently. However, rather than replace human ingenuity, calculators became a collaborative aid, allowing learners to tackle more complex concepts. Similarly, AI like GPT-5.2, far from making mathematicians obsolete, opens doors for collaboration and intellectual growth, reshaping the landscape of mathematical inquiry as calculators once did.