Muy de acuerdo con esto. Y uno de los desencantos que me he llevado durante el desarrollo de la IA en la última década es el de ver a científicos reputados y a los que tenía mucho respeto intelectual, más enamorados de sus convicciones que de la evidencia real. O incluso sin evidencias, negándose muy firmemente a dar espacio a hipótesis que luego se ha demostrado verdaderas.
Y esto ha venido pasando incluso de antes de que los modelos empezaran a balbucera. Es desalentador porque cuando esto pasa en un campo del que entiendo, puedo percibirlo, pero imagino que es una dinámica frecuente en el resto de la sociedad.
5 years ago I was working on LLMs because I believed in them. And yet I didn't think we'd get where we are today without a major paradigm shift. I definitely didn't expect things to move so fast.
I was wrong.
It's astonishing to see some of the very vocal people who were far more skeptical than I was insist that they were right all along, because "hey, today's models do a lot more than predict the next token."
Like, sure, coding agents can run commands in a terminal. But they do it by predicting the next token. What in the world did you expect?
No one was claiming that LLMs would solve every problem without any way to interact with their environment. But the layer on top is very thin, and tool use isn't a new paradigm. "Giving BERT a Calculator" came out 7 years ago.
Science is about updating your beliefs based on evidence. Admitting that your view has changed doesn't make you a worse scientist. It makes you a better one.
This obsession with "I've been saying the same thing for X years and I was right all along" is so tiresome, and sets a terrible example for the general public and the new generation of scientists.