Yes, and I think this reflects an interesting "environmental" difference experienced by humans and AIs.

Complex living creatures (like humans) exist for a long time in a changing world, and so they need to continuously learn and adapt to change. Now, to some extent, we do follow the model of, "Spend N years getting trained and then M years reaping the benefit", but that's only a subtle shift in emphasis, not a black-and-white thing as for ML training vs. inference.

In contrast, AI developed largely for short-term, high-volume applications. In that setting, it makes sense to spend spend a lot of upfront time on training, because you're going to effectively clone the thing and run it a billion times, amortizing the training cost. And giving it continuous learning ability isn't that useful, because each application lasts only minutes, seconds, or even milliseconds.

Making persistent AI that continuously learns and remembers seems like a cool problem! I'm sure this will require some new ideas, but with the number of smart people now engaged in the area, I bet those will come quickly-- if there's sufficient market demand. An I can believe that there might be...