Spot the difference? It gets better because you have to do little more than throw more data at it, the AI figures out the rest. There is no human in loop that has to figure out what makes a picture a picture and teach the AI to draw, the AI learns that simply by example. And it doesn't matter what data you throw at it. You can throw music at it and it'll learn how to do music. You throw speech at it and it learns to talk. And so on. The more data you throw at it, the better it gets and we have only just started.
Everything you see today is little more than a proof of concept that shows that this actually works. Next few years we will be throwing ever more data at it, building multi-modal models that can do text/video/audio together, AI's that can interact with the real world and so no. There is tons of room to improve simply by adding more and different data, without any big chances in the underlying algorithms.
Human takes at least 30min to make a half descent painting. AI takes about a hundreds of a second on consumer hardware. So right now we are already at a point where AI can be 100,000 times faster than a human. AI can basically produce content faster than we can consume it. And we have barely even started optimizing it.
It doesn't really matter if AI will run into a brick wall at some point, since that brick wall will be nowhere near human ability, it will be far past that and better/worse in ways that are quite unnatural to a human and impossible to predict. It's like a self-driving car zipping at 1000km/h through the city, you are not only no longer in control, you couldn't even control it if you tried.
That aside, the scariest part with AI isn't all the ways it can go wrong, but that nobody has figured out a plausible way on how it could go right in the long term. The world in 100 years, how is that going to look like with ubiquitous AI? I have yet to see as much as a single article or scifi story presenting that in a believable manner.
Spot the difference? It gets better because you have to do little more than throw more data at it, the AI figures out the rest. There is no human in loop that has to figure out what makes a picture a picture and teach the AI to draw, the AI learns that simply by example. And it doesn't matter what data you throw at it. You can throw music at it and it'll learn how to do music. You throw speech at it and it learns to talk. And so on. The more data you throw at it, the better it gets and we have only just started.
Everything you see today is little more than a proof of concept that shows that this actually works. Next few years we will be throwing ever more data at it, building multi-modal models that can do text/video/audio together, AI's that can interact with the real world and so no. There is tons of room to improve simply by adding more and different data, without any big chances in the underlying algorithms.