Do you think AGI will be achieved if this trend continues?
A rudimentary intelligence capable of basic object-recognition and permanence* would be an actual step towards AGI over LLMs, in my professional (but still fallible) opinion.
Something as basic as an insect, or hell, even protozoa, is all we would need to say that we're on the way. Once we have that, tying it with an LLM to give it denotative capabilities would be the boom we're all hoping for/terrified of.
[*] this is key, but we don't need to codify this so much as find a way for the object-recognition to build up to it. Even children take a while to develop object permanence (hence peek-a-boo being fun for them - you really are disappearing.)
The generality of the intelligence is unquestionable, at least in a language domain. Discounting it as AGI because a fly is better at being a fly seems besides the point.
1. It has agency. 2. It can move about and manipulate the world in a general as opposed to predefined sense.
Edit: that final point is why I propose an in-to-out approach over an out-to-in approach (which is what LLMs are). Let the intelligence make itself, instead of us trying to make intelligence.
Well, that’s ridiculous out of hand. What makes you say something like that? If they feel intelligent, pass intelligence benchmarks and are designed to be intelligent— why not ascribe to them intelligence? Is it because they aren’t wet?
I don't call any of the ML models that I create "intelligent" - I call them probabilistic. Feigning intelligence with probabilistic methods is nothing new (eg ELIZA). If you can scientifically demonstrate that feigning intelligence is equivocal to de facto intelligence, with something more than "feelings", I'll be happy to read your write-up.
No problem with probabilistic methods. Human intelligence is also probabilistic (ie, predictive coding). Maybe the biggest question: do you think these will be exponentially more powerful in 5 years, learning from failures, self-improving and generally economically “a very big deal” due to human replacement? Because that’s what AGI is supposed to do, rapidly—and that’s why it is worth acknowledging the possibility.
From my perspective, if it barks like a dog, walks like a dog… fulfills all the “dog” benchmarks… even if it came about through unusual means, you’d better consider the possibility.
All these experts Pooh-poohing the possibility of AGI because “I’ve worked with LLMs” is really unconvincing. The debate isn’t balanced because most professionals wouldn’t want to claim AGI for professional reasons.
Most professionals in my field would probably consider this a career-defining moment that would land one in the halls of the greats. I don't really follow this thinking.
And I get the "looks like a duck, quacks like a duck" argument, but as I've repeatedly stated, that's not good enough.
Frankly, I don't buy the "predictive coding" theory - at least, not to the extent that I believe the brain is only probabilistically modeling the phenomena it experiences. This ignores the glaring fact that our senses in-of-themselves exhibit some astounding capabilities right out-of-the-box, and predictive coding has no ground to stand on without the cross-referential analysis of the senses. Human babies are developing their intelligence long before any heavy stimuli. Hearing is the most active before birth, eyesight - our most rich sense - doesn't kick in until after birth. Nonetheless, babies come out of the womb with intelligent reflexes, such as rooting. That bundle of rudimentary intelligence is the basis upon which predictive coding begins - a functional default. An LLM is a set of statically-coded weights, incapable of context switching or object permanence. A child may take a while to understand the difference between "you" and "me", but they still can intuit "thing A" and "thing B". LLMs cannot - at least not without being paired with another model of some sort. And that model will be what tips the scale, not scaling up the features of what's merely a beautiful implementation of the logit function.
You also see that some basic production rules (for basic reflexes) could mean the difference between AGI chatGPT and chatGPT today. Because of how it would help chatGPT orient towards the world, I suppose?
I buy that critique because I do view a cybernetic loop as essential to intelligence — there must be some goalstate (however vague) to be achieved successfully.
But, have you seen many claim that chatGPT is AGI? My issue is not with your argument (it’s good!) but the lack of acknowledgment for the reasonability of the position that chatGPT can be called AGI. Most people DO buy predictive coding. And many would view the missing “reflexes” in chatGPT just a matter of good UI/UX (for instance). Yet, I haven’t seen anyone stand up and systematically argue that chatGPT is AGI. (But I’m not on Twitter, so…)
As for the assertions being made - at first, no, but once the Bing Search fiasco kicked off, I've seen more and more (here on HN) making the claim that ChatGPT and its kin are the beginning. Ultimately, it doesn't irk me - once we hit the same plateau as usual, the hype will boil down - but I do feel a bit concern at what may come of poorly-wielded LLMs before the industry wises up to their risks. A lot of people take ideas they see on HN back to their jobs, so we have a bit of responsibility to manage such hype here.
With hype I think of blockchain (wherein I never understood why removing people from decision-making through automated contracts was worth so much) or the metaverse (where I never understood how they envisioned a world with tech strapped to their face).
The public communication about AGI isn’t exactly a hype cycle. People should, instead, be expecting a fairly dramatic change in many areas of life over the next 3-5 years.