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> 30 years 45 years: December 1903 to July 1949 https://en.wikipedia.org/wiki/Wright_Flyer https://www.history.com/this-day-in-history/first-jet-makes-...
Oop, sorry I mean 30 years to the first commercial passenger plane (Boeing 247) Yes, 45 years to the first passenger jet plane.
> ‘There will never be enough computing power to create AGI using machine learning that can do the same, because we’d run out of natural resources long before we'd even get close,’ I would say the counter-example that proves this statement false is in the author's skull, but perhaps that's overly presumptuous.
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> We don't have proper language, but certainly we've improved. Even since Peirce. You're right that many people are not well versed in the philosophical and logician discussions as to what reasoning is (and sadly this lack of literature review isn't always common in the ML community), but I'm not convinced Peirce solved it. I do like that there are many different categories of reasoning and subcategories. I'd love to…
I'm no expert, but I've been looking into the prospects and mechanisms of automated reasoning using LLMs recently and there's been a lot of work along those lines in the research literature that is pretty interesting, if not enlightening. It seems clear to me that LLMs are not yet capable of understanding simple implication much less full-blown causality. It's also not clear how limited LLMs' cognitive gains will be…
Surely the referees must have raised this at the review stage?
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How many hours or actually years of evolution have been needed until reaching walking capability? If first life is believed to have happened 4 billion years ago, and first walking animals started 450 million years ago during the siluariab period, that’s around 3,5 billion years.
That's not really a great comparison though because evolution wasn't trying to learn how to walk.
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That is kind of my point. They exist only in a few select locations. If they were truly self driving Google would be rapidly rolling them out around the World, but they are not.
Waymo's first real driverless ride on a public road was less than 10 years ago. Now they are doing 100k rides a week. I think your original post just overestimates the 'normal' pace of change - Taking 10 years to go from the first ride to 100k rides a week is no time at all in the scheme of things. Airplanes are an example of an insanely fast technological adoption, and they still took 30 years to go from the wright…
I suspect this will be the case with any AI workload. Heavy customization to get to a place where it is good enough. So the financial benefit needs to be equally huge and someone needs to feel confident they can extract that value 20 years in the future.
Whatever you think about AGI, this is a dumb paper. So many words and references to say - what. If you can't articulate your point in a few sentences you probably don't have a point. There are all kinds of assumptions being made in the study about how AI systems work, about what people "mean" then they talk about AGI etc. The article starts out talking about white supremacy and replacing women. This isn't a proof. Th…
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I have seen far, far too many people say things along the lines of "Sure, LLMs currently don't seem to be good at [thing LLMs are, at least as of now, fundamentally incapable of ], but hey, some people are pretty bad at that sometimes too!" It demonstrates such a complete misunderstanding of the basic nature of the problem that I am left baffled that some of these people claim to actually be in the machine-learning f…
> How can you not understand the difference between "humans are not absolutely perfect or reliable at this task" and "LLMs by their very nature cannot perform this task"? This is a very good distillation of one side of it. What LLMs have taught us is a superficial grasp of language is good enough to reproduce a shocking proportion of what society has come to view as intelligent behaviors. i.e. it seems quite plausibl…
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> but LLMs do solve problems that people thought were extremely difficult to solve ten years ago Agreed. I would have laughed you out of the room 5 years ago if you told me AI's would be writing code or carrying on coherent discussions on pretty complex topics in 2024. As far as I'm concerned, all bets are off after the collective jaw drop that the entire software engineering industry did when we saw GPT4 released. W…
Are capabilities truly 'emerging'? Or are we just observing new competencies/applications we hadn't previously considered.
I think the best argument I have against AGI's inevitability, is the fact it's not required for ML tools to be useful. Very few things are improved with a generalist behind the wheel. "AGI" has sci-fi vibes around it, which I think where most of the fascination is. "ML getting better" doesn't *have to* mean further anthroaormorphization of computers, especially if say, your AI driven car is not significantly improved…
The core argument has a logical gap; it doesn’t matter if most (present) ML applications need AGI or not. What matters is the value proposition of AGI, independent of how we currently conceive of ML applications. Focus on this question: “Is general intelligence at some level valuable at a particular price point?” General intelligence is generally valuable, so there is a pressure to advance it, whether by improving ca…
But that feels very far off, even in the current exponential curve of efficiency we're on. Can't go on forever.