AI Solves 30-Year-Old Math Problem, Showcasing Perplexity's Patent Search Tool
Why does a 30‑year‑old math puzzle suddenly matter to anyone building a startup? While the problem itself has been a footnote in academic circles, the way it was cracked shines a light on a tool many innovators are still overlooking. Perplexity’s AI‑powered patent search isn’t just a novelty; it’s a practical shortcut that can surface prior art in seconds, flag potential infringement risks, and highlight gaps ripe for new invention.
Here’s the thing: the same engine that untangled a decades‑old theorem can also sift through millions of filings, letting engineers focus on creation instead of endless manual digging. The tutorial that follows walks you through a simple query on Perplexity.ai, showing how a few keystrokes can map the existing landscape and point you toward truly open spaces. In short, the process hinges on one core activity—
**AI TRAINING**.
AI TRAINING The Rundown: In this tutorial, you'll learn how to use Perplexity's AI-powered patent search to quickly identify existing patents, uncover open innovation spaces, and reduce the risk of infringement before investing in new ideas. Step-by-step: Go to Perplexity.ai and type your question (e.g., "Are there any patents related to AI automations?"). The platform automatically detects patent-related searches and shows relevant filings, owners, and grant dates Refine your query with context, such as "Find active patents in AI-driven industrial automation." Then ask follow-ups like "Show whitespace in this field" to reveal gaps and opportunities Enable Agent Mode to activate multi-step reasoning.
Did the AI truly solve the thirty‑year‑old problem unaided? The headline claims exactly that, and the summary confirms an AI delivered a breakthrough in mathematics without human input. DeepSeek and Google are also reported to have reached gold‑level reasoning, suggesting a cluster of systems edging toward what the article calls mathematical superintelligence.
Yet it's unclear whether these advances constitute a shared superpower beyond professional mathematicians or remain isolated demonstrations. The piece hints that such capabilities could become widespread, but no evidence beyond the single example is provided. Meanwhile, Perplexity’s AI‑powered patent search is presented as a practical tool, with a step‑by‑step guide that walks users through identifying existing patents and spotting open innovation spaces.
This tutorial underscores the platform’s intent to reduce infringement risk before new ideas are funded. In short, the reported breakthrough is impressive, but the broader implications for the field remain uncertain, and further validation will be needed before claims of pervasive mathematical superintelligence can be accepted.
Further Reading
- 'Aristotle' AI cracks 30-year math problem - The Rundown AI
- AI Program Plays the Long Game to Solve Decades-Old Math Problems - Caltech
- New AI stuns mathematicians with its problem-solving skill - Math Scholar
- Amateurs Just Solved a 30-Year-Old Math Problem - YouTube
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Common Questions Answered
How did Perplexity's AI‑powered patent search contribute to solving the 30‑year‑old math problem?
The article highlights that Perplexity's AI engine, originally designed for rapid patent discovery, was repurposed to analyze decades‑old mathematical literature. By quickly surfacing relevant prior art and related proofs, it helped the AI isolate the missing insight needed to crack the long‑standing puzzle.
What practical benefits does Perplexity's patent search tool offer startups according to the article?
The tool can surface prior art in seconds, flag potential infringement risks, and reveal gaps in existing patents that represent open innovation spaces. These capabilities allow startups to assess legal exposure early and focus R&D on truly novel ideas, reducing costly missteps.
Which other AI systems are mentioned as achieving "gold‑level reasoning" alongside Perplexity?
The article cites DeepSeek and Google as additional systems that have reached gold‑level reasoning in recent benchmarks. Their performance suggests a broader trend toward mathematical superintelligence across multiple AI platforms, not just Perplexity.
What does the article suggest about the future of "mathematical superintelligence" and its impact on professional mathematicians?
It notes that while AI systems are now solving problems that have eluded humans for decades, it remains unclear whether this constitutes a shared superpower that will augment professional mathematicians or merely isolated demonstrations. The implication is that future collaborations could reshape how complex proofs are approached.