If NNs aren't AI, what is?
I don't want to say there is no qualitative difference between what the PDE solvers of 1910 could do and what a GPT can do, but until we don't need scientists running the software at all and it can do decide to do this all on its own and know what to do and how to interpret it, it feels misleading to use terminology like "AI" that in the public consciousness has always meant full autonomy. It's going to make people think someone just told a computer "hey, go do science" and it figured this out.
The rule of thumb is, historically, "something is AI while it doesn't work". Originally, techniques like A* search were regarded as AI; they definitely wouldn't be now. Information retrieval, similarly. "Machine learning", as a brand, was an effort to get statistical techniques (like neural networks, though at the time it was more "linear regression and random forests") out from under the AI stigma; AI was "the thing that doesn't work".
But we're culturally optimistic about AI's prospects again, so all the machine learning work is merrily being rebranded as AI. The wheel will turn again, eventually.
I actually think this is changing given the current rapid ascent of multimodal models.
Neural Networks are not considered AI anymore?
That just reinforces my thesis that "AI" is an ever sliding window that means "something we don't yet have". Voice recognition used to be firmly in the "AI" camp and received grants from even the military. Now we have that on wrist watches (admittedly with some computation offloaded) and nobody cares. Expert systems were once very much "AI".
LLMs will suffer the same treatment pretty soon. Just wait.
Where would you draw the line? Is prediction via linear regression AI?
Also language is fuzzy and fluid, get used to it.
LLMs are not AI.
Neither are neural networks, by that definition. Or 'machine learning' in general. They all have been called "AI" at different points in time. Even expert systems – that are glorified IF statements – they were supposed to replace doctors.
As far as I recall, the turing test was developed long ago to give a practical answer to what was and was not practically artificial intelligence because the debate over the definition is much older than we are
For the sake of my sanity I've just started tuning out what anyone says about AI outside of specialist spaces and forums. I welcome educated disagreement from my positions, but I really can't take the antivaxx equivalent in machine learning anymore.
> we decided it didn't count for some reason
Optimists did move their goals once you realized that solving chess actually didn't lead anywhere, and then they blamed the pessimists for moving even though pessimists mostly stayed still throughout these AI hype waves. It is funny that optimists constantly are wrong and have to move their goal like that, yes, but people tend to point the finger at the wrong people here.
The AI winter came from AI optimists constantly moving the goalposts like that, constantly saying "we are almost there, the goal is just that next thing and we are basically done!". AI pessimists doesn't do that, all that came from the optimists that tried to get more funding.
And we see that exact same thing play out today, a lot of AI optimists clamoring for massive amounts of money because they are close to AGI, just like what we have seen in the past. Maybe they are right this time, but this time just like back then it is those optimists that are setting and moving the goal posts.
I think you'll find that definition "intelligence" is a bit harder than defining "flight", and convincing people that "a machine programmed to mechanically follow the steps in the minimax algorithm as applied to chess, and do nothing else" doesn't fit most people's definition of "intelligence" in the context of the philosophical question of what constitutes intelligence.
> my thesis that "AI" is an ever sliding window that means "something we don't yet have
Or maybe it's the sliding window of "well, turns out this ain't it, there is more to intelligence than we wanted it to be".
If everything is intelligent, nothing is. If you define pattern recognition as intelligence, you'd be challenged to find unintelligent lifeforms, for example. You haven't learned to recognize faces, you are literally born with this ability. And well, life at least has agency. Is evolution itself intelligent? What about water slowly wearing down rock into canyons?
Why do you feel it depressing?
AI
-> machine learning
...-> supervised
........-> neural networks
...-> unsupervised
...-> reinforcement
-> massive if/then statements
-> ...
That is to say NN falls under AI but everything falls into AI.