A 23-Year-Old “Vibe Maths’d” a 60-Year-Old Erdős Problem Into ChatGPT — And Solved It
A 23-Year-Old “Vibe Maths’d” a 60-Year-Old Erdős Problem Into ChatGPT — And Solved ItHe didn’t even know what the problem was. GPT-5.4 spent 80 minutes thinking and invented an entirely new method that made a Fields Medalist say “whoa.”
Erdős Problem #1196 — unsolved since 1968. 58 years of the world’s best mathematicians failing. One dude with a ChatGPT Pro sub typed it in on a Monday afternoon. Done.
Liam Price is 23. He has zero advanced math training. His exact quote to Scientific American was: “I don’t even know what this problem is.” He calls what he did “vibe maths.” I mean. Are you hearing me right now? The man vibed his way into solving something that stumped Oxford professors for six decades.
🧩 Dumb Mode Dictionary
| Term | Translation |
|---|---|
| Erdős Problem | A famous unsolved math puzzle left behind by Paul Erdős, a legendary mathematician who left hundreds of open challenges when he died |
| Primitive set | A group of numbers where none of them divides evenly into any other — like {6, 10, 15}. No number in the group is a “factor” of another |
| Von Mangoldt function | A fancy formula that tells you how “prime-y” a number is — how many prime factors are hiding inside it |
| Markov chain | A math trick where each step only depends on the step right before it — like a coin flip that doesn’t remember what happened two flips ago |
| Lean (proof assistant) | Software that checks every single logical step of a math proof. If even ONE step is wrong, it refuses to accept it. Robot referee, basically |
| Fields Medal | The Nobel Prize of math. There are like 60 living winners total. Terence Tao has one. It’s a big deal |
| Vibe maths | Price’s term for “I just pasted a problem I don’t understand into an AI and hoped for the best” |
📖 How the Hell Did This Happen
On April 13, 2026, Liam Price was browsing erdosproblems.com — a website that lists hundreds of unsolved problems the late mathematician Paul Erdős left behind. He’d been randomly feeding these puzzles to ChatGPT to see what would happen.
Problem #1196 was posed in 1968 by Erdős, Sárközy, and Szemerédi. It asked whether sums across “primitive sets” (groups of numbers where nothing divides anything else) follow a specific mathematical pattern.
Price copy-pasted the problem into GPT-5.4 Pro. He went to do other stuff. 80 minutes later, the AI spit back a full proof.
His collaborator Kevin Barreto — a second-year undergrad at Cambridge — looked at the output and immediately knew something was off. Not wrong-off. Different-off. The AI had used a method nobody had ever tried on this kind of problem before.
⚡ The 'AlphaGo Move 37' Moment
Here’s the thing that’s making mathematicians lose their minds.
For 90 years, humans attacked these primitive-set problems by converting them from number theory into probability theory. That was THE approach. The playbook. The only road anyone had ever tried.
GPT-5.4 said nah.
Instead, it grabbed the von Mangoldt function (a tool for analyzing prime numbers) and built a Markov chain — treating the structure of integers like a random walk. Nobody had combined these two things for this type of problem. Ever.
Jared Lichtman, an Oxford mathematician who spent 7 years working on related problems, compared it to AlphaGo’s famous Move 37 — a move that looked stupid to every expert watching, but turned out to reveal something deeper about the game than humans had understood.
Lichtman called it “the first AI proof at the level of Erdős’s Book” — which in math means the most elegant possible proof. That’s the highest compliment you can give.
🏆 The Receipts
| What | Detail |
|---|---|
| Problem | Erdős Problem #1196 (1968) |
| Solver | Liam Price, 23, no advanced math |
| AI used | GPT-5.4 Pro ($200/month ChatGPT sub) |
| Thinking time | ~80 minutes |
| Verification | Formally proven in Lean proof assistant — robot-checked, zero wiggle room |
| Expert who confirmed | Terence Tao (Fields Medalist) — within 24 hours |
| Tao’s verdict | “A meaningful contribution that goes well beyond the solution of this particular problem” |
| Erdős problems solved by AI since Jan 2026 | 11 out of 15 total solved |
| Status | Marked “PROVED” on erdosproblems.com |
🗣️ What the Math World Is Saying
Terence Tao said the proof “reveals a previously undescribed connection between the anatomy of integers and Markov process theory.” Within 24 hours of reading it, Tao had already extended the method into entirely new mathematical theory. The man read someone else’s homework and invented a new field from it before lunch.
The broader pattern is what’s really cooking people’s brains though. Since January 2026, 15 Erdős problems have been solved. 11 of those credited AI assistance. That’s not a coincidence — that’s the start of a wave.
And let’s be honest about what just happened: a college kid who LITERALLY SAID he didn’t understand the problem casually produced work that a Fields Medalist called meaningful. The gatekeeping era of mathematics is absolutely cooked.
🔍 Why This Is Different From 'AI Wrote My Essay'
Some people are already going “well the AI did all the work.” But that’s not what actually happened here.
The AI produced a proof. That proof then had to survive:
- Review by a Cambridge undergrad
- Review by an Oxford professor who spent 7 years on related problems
- Review by a Fields Medalist
- Formal verification in Lean — software that checks literally every logical step and rejects anything with a gap
The AI didn’t just write convincing words. It invented a genuinely new mathematical technique that turned out to be correct at every level of scrutiny humans could throw at it. The method itself is now being used to prove OTHER things.
That’s not autocomplete. That’s something else.
Cool. An AI just out-mathed 58 years of professors. Now What the Hell Do We Do? ( ͡° ͜ʖ ͡°)
🕳️ The Erdős Bounty Hunter
Erdős left behind hundreds of unsolved problems, many with cash prizes ($25 to $10,000). The website erdosproblems.com lists every single one with its status. Most are still wide open. And as of right now, the meta is clear: paste them into frontier AI models, let it think, then have a math-literate friend verify the output.
You don’t need to BE a mathematician. You need to be the middleman between the AI and someone who can sanity-check the result. The person who submits a valid proof gets the credit (and potentially the cash bounty). Price didn’t understand the problem. He still gets his name on the paper.
Example: A 20-year-old CS student in Nairobi scrapes the list of unsolved Erdős problems tagged “$500+” from erdosproblems.com, batch-feeds them to Claude and GPT-5.4 using the API, and partners with a math PhD student on Reddit r/math to verify outputs. Two valid proofs in 3 months = name on published papers + $1,500 in Erdős bounties.
Timeline: First output worth checking in 2-3 days. First valid proof in 4-8 weeks (most outputs will be wrong — the grind is in filtering). Window closes as more people realize this works.
🎣 The Proof Verification Middleman
Here’s the bottleneck nobody’s talking about: mathematicians are about to get FLOODED with AI-generated proofs that need human checking. Most will be garbage. Some will be gold. And right now there aren’t enough people who can tell the difference.
The play: learn Lean (the proof assistant that formally verified Price’s result). It’s free, open source, and there are great tutorials. You become the person who can take a messy AI proof output and translate it into a Lean-verified formal proof. Mathematicians will PAY for this service because they don’t have time to learn a new programming language.
Example: A 24-year-old developer in Bucharest spends 3 weeks learning Lean from the free course at leanprover-community. Posts on r/math and MathOverflow offering “AI proof formalization” services. Gets hired by a research group at ETH Zurich to formalize 4 AI-generated proofs at €800 each. Becomes known as “the Lean guy” in a Discord of 200 researchers.
📡 The Unsolved Problem Radar
Here’s what Price accidentally proved beyond the math: the selection of WHICH problem you feed the AI matters more than HOW you prompt it. He got lucky. You don’t have to.
Build a scraper that monitors sites like erdosproblems.com, the Open Problem Garden, and Polymath projects for problems that have specific properties: clearly stated, well-bounded, and from a domain where AI models have shown strength (combinatorics, number theory, graph theory). Cross-reference against arXiv preprints to see which problem areas have had recent AI-adjacent breakthroughs. Sell the curated list as a subscription to research teams.
Example: A 22-year-old data science grad in São Paulo builds a Python script that scrapes open math problems and scores them on “AI-solvability” using keyword heuristics. Publishes a weekly newsletter on Substack ranking the top 10 “most likely to fall to AI this month.” 400 subscribers in 2 months — then a research lab at MIT licenses the scoring algorithm for $3K.
🪟 The Patch Window on Academic Credit
Right now, academic institutions haven’t figured out how to handle AI-assisted mathematical discoveries. The rules are being written in real time. Price’s name is on this proof even though he explicitly said he didn’t understand the problem. That’s the current state of play.
This means there’s a window — maybe 12-18 months — where you can accumulate legitimate academic publications by being the human intermediary between AI and verification. These publications count on your CV forever, even after institutions tighten the rules. A stack of “co-discovered” papers turns you into a research candidate at any university, even without a traditional academic path.
Example: A 26-year-old high school teacher in Manila with a bachelor’s in math starts systematically feeding open conjectures from the OEIS (Online Encyclopedia of Integer Sequences) into AI models. Partners with a professor at UP Diliman to verify results. Gets co-author credit on 2 papers published in minor journals. Uses that CV line to get accepted into a funded master’s program.
🎰 The 'Vibe Math' Content Machine
Liam Price went viral because the story is incredible: random guy pastes problem into AI, solves 60-year mystery. But the NEXT hundred people who do this won’t make Scientific American. What WILL make money is documenting the process in a way that makes people feel like they can do it too.
Record yourself feeding unsolved problems into AI models. Show the failures (most will fail — that’s the content). Explain the problems in dead-simple language. When you DO get something interesting, film the reaction of a real mathematician reading it. Post everything on TikTok and YouTube Shorts with the hook “Can AI solve a problem that stumped geniuses for X years?”
The niche: “math drama” content where AI is the protagonist. Nobody’s doing this well yet.
Example: A 19-year-old in Jakarta who watches 3Blue1Brown starts a TikTok series called “Feeding AI Impossible Problems.” Films screen recordings of Claude working on open conjectures, adds subtitles explaining what’s happening. One video where the AI produces a surprisingly plausible answer gets 2.1M views. Brand deal with Brilliant.org at 50K followers — $2,500/month.
🛠️ Follow-Up Actions
| Want | Do |
|---|---|
| Browse unsolved Erdős problems | Visit erdosproblems.com and sort by prize value |
| Learn Lean (proof assistant) | Start with Lean Community tutorials — free |
| Read Tao’s reaction | Follow Terence Tao’s blog for his extensions of the proof |
| Feed problems to AI yourself | Use ChatGPT Pro or Claude with extended thinking — paste the full problem statement |
| Find more open problems | Check Open Problem Garden and OEIS |
| Understand the actual proof | Read the buildfastwithai breakdown for a plain-English walkthrough |
Quick Hits
| Want | Do |
|---|---|
| Solve famous math problems |
Paste open conjectures from erdosproblems.com into GPT-5.4 or Claude. Check outputs with Lean |
 Get academic credit fast |
Partner with a math prof, submit AI-assisted results, get co-author during the policy window |
 Verify AI proofs for money |
Learn Lean in 3 weeks, offer formalization services on r/math and MathOverflow |
 Build a following |
Film yourself feeding AI impossible problems — “math drama” is a wide-open niche on TikTok |
 Understand what happened |
Read the Scientific American article — it’s genuinely one of the wildest science stories this year |
A kid who couldn’t explain the question got his name on the answer — and the smartest mathematician alive said “yeah, that’s actually brilliant.” The future isn’t credentialed. It’s curious.
!