Having AIs learn human language at all is a transient hack priority. Like humans learning whale squeak language.
And trying to come up with cartoon squeaks whales would find funny.
Humans use text representation schemes because we have specific limits/constraints
Conversation
If you have an AI a rich enough embodiment with raw sensor info and showed it birds and airplanes, it might figure out flight but bypass all human representation schemes we think must be encountered along the way — symbolic language and math, physics theories etc
1
1
9
We can no more teach AIs to fly than we can teach birds to fly. Birds sort of taught us how to fly but by simply existing as a demonstration, not by conveying their evolutionary learning history.
1
6
This makes me think language models are a giant yak shave that are valuable right now but in the long term irrelevant. If AIs need language they’ll invent their own. If they need math they’ll discover their own.
1
2
11
Learning the human versions of important signification maps will be a temporary crutch but not speed up their own actual evolution of comparable native structural phenomena.
It’s not clear to me they ever will though. Faking shallow versions of the human thing might be it.
1
6
They have a lot of useful power but it may not be relevant to the capabilities we are considering here. Horses are much more powerful than humans in muscle terms but Clever Hans learning to fake counting didn’t lead to a species of genius horses
1
3
We are simultaneously overestimating and underestimating what AIs can do by projecting the arbitrary biases of our own embodiments onto a radically different substrate.
What humans have learned over 1 million years of evolution with a 2lb brain is simply not that relevant here
2
1
13
AIs are not “faster humans” anymore than cats are “faster horses”
Data from the evolutionary history of horses is not relevant to cars. The only overlap is in the term “horsepower” and roughly similar sizes of cars and carts due to early substitution effects.
3
9
This week’s developments lead me to strongly conclude robotics models (SayCan) >> image models >> text+image models > text models
Dall-e2 etc are text++ models that use a subset of image model power to do a sort of interesting parlor trick.
2
1
9
Replying to
Don’t most breakthroughs begin with an interesting parlour trick? Cc
1
But most interesting parlor tricks don’t lead to breakthroughs

