High altitude planes going to the moon is a beautiful analogy. I think this is what I’ll use to explain to less technical friends why I think we’re still many years from self driving cars.
I've never seen a language model that could create language models. (Never mind the hardware that runs them.)
You're using a very loaded and narrow sense of 'human' here.
It isn't conclusive evidence however, and larger models may produce significantly more human like results. But from what we know about how gpt-3 works, all the evidence is on the side of it not resembling human intelligence.
Perhaps now, but if history is any indication, when we (as humans) think we have a good grip on how something really works (like human intellect in this example), we've been wrong.
We model the world around us from observation and testing, find our errors, remodel, and improve over time.
Then at some point we find some piece of information that shows us our model was a decent approximation, but fundamentally wrong, and that we need to start from scratch.
If we find that we want to go beyond the moon (and we eventually will), or that the moon is further than we think, we'll again need a different approach.
I always feel like there's a certain beauty and cosmic humor to it.
GPT3 doesn't know the difference between a given set of characters and the idea/object the characters represent. It can associate "river" and "stream" and "water" but has no understanding beyond that they appear in patterns together. It couldn't possibly make the connection that river and streams are bodies of water, because there is no association with reality.
GPT3 wouldn't even know the difference between human language and characters derived from some random data source.
The only thing it does is identify deeply complex patterns, as long as there are humans around to notify it when it's doing a good job. It's going to be very useful for auto-complete, and jumping in to help users finish repetitive tasks, along with the other stuff ML is good at, but it's simply a GIGO pattern recognition system.
So I think you have it exactly backwards -- there is a dearth of evidence that AGI is even remotely possible. We have known the full anatomy of the C. Elegans ringworm since 1984 -- it's 1mm long and has 300 neurons. There is a foundation dedicated to replicating it's behavior[1], and all they have achieved is complex animation.
Yet if you asked it if rivers and streams are bodies of water it would probably say that they are.
Likewise if I asked you if black holes and neutron stars are both celestial bodies you would say yes... but you've presumably never seen them, only read about them.
Now I think you could argue that you could ultimately tie your knowledge back to some reality, like star ties to the sun and how you've seen the sun, but I haven't been so convinced that we know enough about how the mind works to be sure that the distinction between form and meaning is real.
Assuming there is no "soul" which makes meat life special, I don't see any fundamental problems with building simulated intelligence.
It makes people think "driverless", which "full self-driving" is not.
What term would you prefer to describe a car that can get you from A to B without your input?
Explain to them also that you think one highly specialized skill (driving) is the same as the sum of all human knowledge.