It will likely require research breakthroughs, significant hardware advancement, and anything from a few years to a few decades. But it's coming.
ChatGPT was released 2.5 years ago, and look at all the crazy progress that has been made in that time. That doesn't mean that the progress has to continue, we'll probably see a stall.
But AIs that are on a level with humans for many common tasks is not that far off.
There's a lot of literature on this, and if you've been in the industry for any amount of time since the 1950s, you have seen at least one AI winter.
probably true but this statement would be true if when is 2308 which would defeat the purpose of the statement. when first cars started rolling around some mates around the campfire we saying “not if but when” we’ll have flying cars everywhere and 100 years later (with amazing progress in car manufacturing) we are nowhere near… I think saying “when, not if” is one of those statements that while probably indisputable in theory is easily disputable in practice. give me “when” here and I’ll put up $1,000 to a charity of your choice if you are right and agree to do the same thing if wrong
you can see a pattern of fairly steady progress in different aspects, like they matched humans for image recognition around 2015 but 'complex reasoning' is still much worse than humans but rising.
Looking at the graph, I'd guess maybe five years before it can do all human skills which is roughly AGI?
I've got a personal AGI test of being able to fix my plumbing, given a robot body. Which they are way off just now.
To begin with, systems that don't tell people to use elmer's glue to keep the cheese from sliding off the pizza, displaying a fundamental lack of understanding of.. everything. At minimum it needs to be able to reliably solve hard, unique, but well-defined problems like a group of the most cohesive intelligent people could. It's certainly not AGI until it can do a better job than the most experienced, talented, and intelligent knowledge workers out there.
Every major advancement (which LLMs certainly are) has caused some disruption in the fields it affected, but that isn't useful criteria that can differentiate between "crude but useful tool" from "AGI".
It has taken tens to hundred of billions of dollars without equivalent economic justification(yet) before to reach here. I am not saying economic justification doesn't exist or wont come in the future, just that the upfront investment and risk is already in order of magnitude of what the largest tech companies can expend.
If the the next generation requires hundreds of billions or trillions [2] upfront and a very long time to make returns, no one company (or even country) could allocate that kind of resources.
Many cases of such economically limited innovations[1], nuclear fusion is the classic always 20 years away example. Another close one is anything space related, we cannot replicate in next 5 years what we already achieved from 50 years ago of say landing on the moon and so on.
From a just a economic perspective it is a definitely a "If", without even going into the technology challenges.
[1]Innovations in cost of key components can reshape economics equation, it does happen (as with spaceX) but it also not guaranteed like in fusion.
[2] The next gen may not be close enough to AGI. AGI could require 2-3 more generations ( and equivalent orders of magnitude of resources), which is something the world is unlikely to expend resources on even if it had them.
LLMs destroying any sort of capacity (and incentive) for the population to think pushes this further and further out each day
I don’t agree that this will affect ML progress much, since the general population isn’t contributing to core ML research.
Most HN people are probably too young to remember that the nanotech post-scarcity singularity was right around the corner - just some research and engineering way - which was the widespread opinion in 1986 (yes, 1986). It was _just as dramatic_ as today's AGI.
That took 4-5 years to fall apart, and maybe a bit longer for the broader "nanotech is going to change everything" to fade. Did nanotech disappear? No, but the notion of general purpose universal constructors absolutely is dead. Will we have them someday? Maybe, if humanity survives a hundred more years or more, but it's not happening any time soon.
There are a ton of similarities between nanotech-nanotech singularity and the moderns LLM-AGI situation. People point(ed) to "all the stuff happening" surely the singularity is on the horizon! Similarly, there was the apocalytpic scenario that got a ton of attention and people latching onto "nanotech safety" - instead of runaway AI or paperclip engines, it was Grey Goo (also coined in 1986).
The dynamics of the situation, the prognostications, and aggressive (delusional) timelines, etc. are all almost identical in a 1:1 way with the nanotech era.
I think we will have both AGI and general purpose universal constructors, but they are both no less than 50 years away, and probably more.
So many of the themes are identical that I'm wondering if it's a recurring kind of mass hysteria. Before nanotech, we were on the verge of genetic engineering (not _quite_ the same level of hype, but close, and pretty much the same failure to deliver on the hype as nanotech) and before that the crazy atomic age of nuclear everything.
Yes, yes, I know that this time is different and that AI is different and it won't be another round of "oops, this turned out to be very hard to make progress on and we're going to be in a very slow, multi-decade slow-improvement regime, but that has been the outcome of every example of this that I can think of.
It seems like nanotech is all around us now, but the term "nanotech" has been redefined to mean something different (larger scale, less amazing) from Drexler's molecular assemblers.
I thought this was a "we know we can't" thing rather than a "not with current technology" thing?
The idea of scaling up LLMs and hoping is .. pretty silly.
The problem is that the distance between a nano thin film or an interesting but ultimately rigid nano scale transistor and a programmable nano level sized robot is enormous, despite similar sizes. Same like the distance between an autocomplete heavily relying on the preexisting external validators (compilers, linters, static code analyzers etc.) and a real AI capable of thinking is equally enormous.
We have zero evidence for this. (Folks said the same shit in the 80s.)
I want to believe, man.
