Why better sampling ā not smarter training ā might be the real AI revolution
šŖ The Twist We Didnāt Expect
What if ChatGPT isnāt dumb ā we just keep interrupting it?
For years, the default assumption has been that smarter AI requires more: more data, more reinforcement learning, more GPUs that hum like jet engines. But new research out of Harvard quietly rewrites the script.
It turns out, large language models (LLMs) might already be capable of deep reasoning. We just havenāt been letting them show it ā because weāve been sampling their thoughts the wrong way.
Thatās right: the next big AI breakthrough might not be about training models better⦠but about listening better.
š² Stop Blaming the Model. Start Blaming the Dice.
When you talk to ChatGPT, it doesnāt āthink.ā It predicts.
It looks at every possible next word, assigns each a probability, and picks one. Usually, the most likely.
And thatās exactly the problem.
The āmost likelyā next word is what youād get from a thousand bloggers writing the same thought. Predictable. Polished. Occasionally useful ā but rarely insightful.
Harvardās team found that by adjusting the sampling ā choosing not just the most probableā¦
