AI Model Nearly Aces the Putnam: Why the Real Disruption Is How We Reason
Source: Dev.to
AI Model Nears a Perfect Score on the Putnam
An AI math model recently scored 118/120 on one of the hardest human exams.
Beyond solving problems, it learned to reason, self‑check, and repair its own logic.
Researchers first trained a separate AI verifier to assess whether a proof was sound.
Then they trained the solver AI to write proofs that the verifier would accept.
The resulting system can reread its own arguments, identify gaps, and fix them.
Why This Matters Beyond Mathematics
The approach serves as a blueprint for building teams and systems:
- Human–AI pairs can explore complex ideas.
- They can challenge their own assumptions.
- They can iterate until solutions are rock solid.
How to Apply This Now
- First draft: Use AI for analysis, summaries, and generating options.
- Human verification: Retain humans for judgment, ethics, and contextual understanding.
- Iterative loops: Let AI propose, humans critique, and AI refine.
Companies that treat AI merely as a calculator will see only modest gains.
Those that treat AI as a junior thinker equipped with a built‑in verifier can transform how they solve hard problems.
The Real Competitive Edge
The advantage won’t be simply who has AI, but who learns to reason with it.
What’s your experience so far? Is AI just speeding you up, or actually helping you think better?