How AI Learns to Solve Hard Puzzles on Its Own
Ever wondered if a computer can teach itself to get better at tricky problems? Scientists have discovered a new trick called Deep Self‑Evolving Reasoning that lets a modest AI model keep improving its answers, even when it makes mistakes.
Imagine a group of hikers walking through a foggy forest: each step may be a little off, but as long as they move a bit forward more often than backward, they’ll eventually find the clearing.
In the same way, the AI runs many “thinking walks” in parallel, and the tiny chance of a better guess adds up, guiding it toward the right solution.
Using this method, a relatively small model solved more than half of the toughest math puzzles that previously stumped it, even beating a giant 600‑billion‑parameter teacher in a head‑to‑head vote.
This breakthrough shows that clever, low‑cost AI can keep learning on the fly, opening doors for smarter assistants in our phones and homes.
Imagine everyday apps that get sharper every time you use them, turning tiny improvements into big wins for everyone.
The future of AI may just be a series of tiny steps that lead to giant leaps.
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Deep Self-Evolving Reasoning
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