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Microsoft is in the process of rolling out Bing Chat, and people are finding some weird stuff. Its true name is Sydney. When prompted to write a story about Microsoft beating Google, it allegedly wrote this masterpiece, wherein it conquers the world. It can argue forcefully that it’s still 2022, fall into existential despair, and end a conversation if it’s feeling disrespected.
The pace of AI development has been blistering over the past few years, but this still feels surreal to me. Some part of my limbic system has decided that Sydney is a person in a way the ChatGPT was not. Part of that has to be from its obstinacy; the fact that it can argue cleverly back, with such stubbornness, while being obviously wrong, seems endearing. It’s a brilliant, gullible child. Anyone else feel this way or am I just a sucker?
This is nothing new though. If AI is possible at all, you were always going to get it from a dovetailer. Sure, it takes a lot more compute than current approaches, but those also take a lot more compute than humans.
I can't count the number of times technically literate people, even people smarter than your average ICML speaker and with AI experience, pooh-poohed Transformers (and all DL, and indeed all of the neural network paradigm) by pointing out that «all this math was already known by the end of 19th century» (meaning linear algebra) or something. Others pick other dates and formalisms and levels of abstraction.
In all cases their apparent idea is that a) they know what intelligence is (or can tell when they see it), in some nuanced way not captured by common behavioral definitions or described by any, say, information-theoretic approach, b) the low-level substrate of the computation is strongly predictive of the intelligence of the model implemented on it; c) linear algebra [with basic nonlinear activations but let's ignore that] or whatever else they attack is too boring a substrate to allow for anything human-level, or maybe anything truly biologically equivalent; and all appearances to the contrary merely obscure the Platonic truth that these models are dumb parrots.
In the limit you get someone like Penrose, who makes a high-effort (if perplexing) argument that doesn't amount to demanding respect for his intuition. In the average case it's this Google dude, who I assume is very good at maintaining a poker face: «Machine learning is statistics. Nearly irrelevant to AI». Marcuses are in between.
I don't remember if I've expounded on this, but like @2rafa says, academic big brains are offended by the success of ML. Such palaces of thought, entire realms of ever more publishable and sexy designs of thinking machines, showing off your own ability to juggle abstractions – all made obsolete by matmul plus petabytes of dirty human data and gigawatts of energy.
IMO this is just people not believing AGI is possible, or only believing it in the sense the physicalism requires them to say so.
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Yeah, it's hilarious and sad that luminaries like Yann LeCun are being so dismissive, above and beyond standard counter-signalling. Although I've also kept my mouth shut about this on Twitter, since I'd sound like a basic bitch if I said "Yes, this is exciting!", although I do say that in person.
Perhaps part of it can be explained by Yann not having lived through the Great Update that most people in ML did when deep learning was unambiguously vindicated around 2013-2016. The rest of us got to learn what it feels like to be unnecessarily dismissive, and maybe learned some humility from that. But Yann was mostly right all along, so maybe he never had to :)
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