Last week, I reflected that I’d underestimated the potential of large language models by basing my opinion on the early versions of ChatGPT. Interestingly, Casey Newton has talked in the latest edition of Platformer about making the same mistake.

I had recently subscribed to ChatGPT Plus at the encouragement of a friend who had found it to be an excellent tutor in biology. A few days later, I found myself embarrassed: what I thought I knew about the state of the art had essentially been frozen a year ago when ChatGPT was first released. Only by using the updated model did I see how much better it performed at tasks involving reasoning and explanation.

I told the researcher I was surprised by how quickly my knowledge had gone out of date. Now that I had the more powerful model, the disruptive potential of large language models seemed much more tangible to me. 

The researcher nodded. “You can fast forward through time by spending money,” she said.

Naturally, Casey’s thoughts are more extensive and more fully formed than my own, and the whole piece is well worth reading.