> On the one hand, we’re pretty sure these systems don’t do anything like what humans do to produce or classify language or images. They use massive amounts of

> On the one hand, we’re pretty sure these systems don’t do anything like what humans do to produce or classify language or images. They use massive amounts of data, whereas we seem to use relatively little; This isn't entirely correct; humans work with a roughly 16hr/day audio-visual feed running at very high resolution. That seems to be more data than ChatGPT was trained on. We spend less time looking at character glyphs, but the glyphs are the end of a process for building up language. When we say that cats sit on mats, that is linked to us having seen cats, mats and a lot of physics. Although that strongly supports that humans learn in a way different from an LLM. And humans seem to have a strategy that involves seeking novelty that I don't think the major LLMs have cracked yet. But we use more data than they do.