Making AI show its work might be a mistake
Sometimes, progress means letting go of our need to understand every step of the process.
When neuroscientists study how our brains solve complex problems, they notice something fascinating - our language centers often stay surprisingly quiet. Think about it: when you're deep in problem-solving mode, are you really narrating every step in your head? Probably not.
Yet that's exactly what we've been making AI do.
Some new research out of Meta is making some rethink AI reasoning.
Meta's researchers noticed three big problems with making AI explain everything:
Most of what the AI writes is just filler - all those "therefore" and "next" transitions that don't add any real value
The AI gets stuck at critical moments because it has to commit to specific words instead of exploring multiple paths
It wastes enormous effort making sure its explanations sound grammatically correct instead of actually solving the problem