OpenAI Thought GPT-5 Made Big Math News, But… Even Hassabis Felt Awkward

OpenAI Thought GPT-5 Made Big Math News, But… Even Hassabis Felt Awkward

Seasonal Dispatch from AoFeiSi

Quantum Bits | WeChat Official Account QbitAI

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GPT‑5’s “Math Breakthrough” — and the Backfire

Over the weekend, OpenAI promoted what sounded like a mathematics milestone — GPT‑5 had reportedly “solved” several long‑standing Erdős problems.

But within hours, the claim unraveled.

Industry peers called it overhyped marketing, with OpenAI accused of blowing a small achievement out of proportion.

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Public Reactions

  • Demis Hassabis (DeepMind CEO) openly mocked the claim: “This is embarrassing.”
  • Yann LeCun (Meta AI Chief) joined in, quick to highlight the weaknesses.
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How the Claim Started

OpenAI researcher Mark Sellke posted on X:

> After thousands of GPT‑5 queries, we found solutions to 10 Erdős problems marked “unsolved”: 223, 339, 494, 515, 621, 822, 883 (Part II), 903, 1043, 1079.

> Also, 11 other problems saw partial progress. We found an error in Problem 827’s original paper — later confirmed by Martínez and Roldán‑Pensado.

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Other OpenAI leaders amplified the announcement:

  • Kevin Weil: “GPT‑5 found solutions to 10 previously unsolved Erdős problems…”
  • Sebastien Bubeck: “The era of AI‑powered scientific acceleration has officially begun!”

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The Internet Buzz — and Reality Check

The announcement led many to believe GPT‑5 had independently cracked decades‑old math challenges.

Immediate Pushback

  • Demis Hassabis replied under Bubeck’s post:
  • > “This is really embarrassing!”
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Thomas Bloom, maintainer of erdosProblems.com, clarified:

> The “unsolved” label only meant I hadn’t found the published solutions yet — not that mathematicians hadn’t already solved them. GPT‑5 simply located existing papers via search.

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Retraction

Bubeck deleted his post and wrote:

> We simply found solutions already in the literature — nothing novel. Literature search is hard, and AI can help with that.

LeCun summed it up:

> “Their GPT hype backfired badly.”

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Understanding the Misstep

In short:

  • What GPT‑5 did: Retrieve known solutions faster than a human.
  • What it didn’t do: Invent new mathematical proofs.

The incident is a cautionary tale: misleading framing jeopardizes credibility.

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Why Context Matters in AI Achievements

Large language models excel at:

  • Literature searches
  • Synthesizing complex data

They don’t automatically deliver novel discoveries.

Tools like AiToEarn官网 could help:

  • Integrate AI‑driven content generation
  • Streamline multi‑platform publishing (Douyin, Kwai, WeChat, Bilibili, Facebook, Instagram, YouTube, etc.)
  • Track and analyze reach and impact

Such ecosystems ensure clear documentation and communication, avoiding hype‑driven misinterpretations.

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Past GPT‑5 Math Efforts

The latest misstep wasn’t a total anomaly — GPT‑5 has demonstrated value in mathematical research:

  • Terence Tao’s challenge
  • Exploring lcm(1, 2, …, n) in relation to highly abundant numbers.
  • Without AI, coding/debugging would have taken hours.
  • Quantum complexity theory
  • Generated useful proof ideas in under 30 minutes.
  • Fourth Moment Theorem extension
  • Collaborated under expert guidance to produce a quantitative version — a first.
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The Core Problem

  • Ambiguous promotion made audiences think GPT‑5 solved a “hard, unsolved” problem.
  • Internal exaggeration amplified the misunderstanding.
  • Critics noted the desire to prove worth may have fueled the hype.
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The Takeaway

The era of “AI breakthroughs every weekend” is fading — audiences are more skeptical.

Without tangible novelty, hype risks backfiring.

Creators working with AI should:

  • Showcase authentic impact
  • Avoid ambiguous claims
  • Use connected platforms to publish and monetize responsibly

Example: AiToEarn官网 — integrates generation, cross‑platform posting, analytics, and rankings so real achievements can be shared widely without misleading audiences.

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References

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