> learning new things

I wonder lately, doesn't that all new knowledge push out the old knowledge? As in new things replace old things we know. I don't know any studies on this but do we have infinite capacity for knowledge?

What about retaining it? I catch myself asking AI wondering about random things that pop into my head, reading it, maybe using that knowledge once and later no longer remembering what it was. Maybe if you use that knowledge in practice from the get go but projects get so complicated sometimes it seems like there is not enough space in my brain for things AI is learning me.

Knowledge memory doesn't really work that way, it is more like that it is constantly fading unless re-imprinted by use and learning new things is just imprinting new knowledge on top. The new knowledge will form connections with the old knowledge which will help keep some of it from fading, but not all.

Another way of looking at what you said is that the practicing the new knowledge takes the place of practicing the old knowledge. So it isn't the knowledge that is replaced, but the learning (imprinting).

New knowledge doesn't necessarily push out old knowledge, and we probably don't have infinite capacity for knowledge. That being said, at least in my experience, the time when new pushes out old is when old is less useful than new.

Retaining (again just speaking for myself) requires actually using / applying the knowledge at some point within some timeframe of learning it. Otherwise yeah it fades to the point of disappearing over time.