Mathematics, Meet Your New Assistant
AI is tackling the legendary Erdős problems, proving that machine intelligence can do more than just summarize text—it can find patterns in deep, unsolvable math.
Paul Erdős was a nomadic genius. He spent his life posing math problems that seemed simple to state but remained locked for decades. He’d offer small cash rewards for solutions. He didn't care about the money. He cared about the beauty of the numbers.
For a long time, these problems were considered the exclusive domain of human insight. You needed a specific kind of intuition, a creative leap, to bridge the gap between knowns and unknowns.
Turns out, AI is starting to make those leaps.
Recent work shows models are solving specific classes of these problems by doing what they do best: finding non-obvious patterns across massive datasets. They aren’t just brute-forcing equations. They’re effectively "thinking" through the combinatorial structure of these puzzles, identifying pathways that human mathematicians hadn't prioritized.
This isn't about AI replacing the mathematician. It's about AI acting as a high-powered, relentless research assistant. When you remove the sheer manual labor of testing thousands of potential edge cases, the human can focus on the core logical structure.
The AI doesn't understand the "why" in the same way a person does. It sees the distribution, the probability, the logical map. It presents a potential solution, and the mathematician checks if it holds water.
It works because it keeps the human in the driver's seat. The model provides the raw material—the patterns and the candidates—and the person provides the proof and the intent.
It’s a partnership of scale and substance. We’re moving past the stage where AI is just a glorified search bar. We’re entering an era where it’s an active participant in the hardest, most abstract work we do.
For founders, there’s a lesson here. We often look for AI to "fix" processes—to automate a workflow or clear an inbox. That's fine. But the real leverage comes when you use these systems to handle the parts of your business that feel like hard, messy math: the strategy, the pattern recognition in your market, the difficult "what if" scenarios.
Don't look for the tool to do the whole job. Look for the part you’re stuck on, and see if the machine can find the pattern you’re missing.
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