131–140 of 557 posts
We've somehow had a calm few months in the industry without the daily hyperbole on AGI, superintelligence and the upcoming singularity. After the string of underwhelming incremental updates from all the top LLM publishers I guess they need to start the hype cycle again.
Underwhelming?! We're probably a year out of AI-led pure math research and full AI SWEs. I think people forget what it was like 1-2 years ago somehow
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Nope. Something can be written by a human being of immense intelligence but not deserve taking seriously, if (for instance) it was written as a deliberate attempt at deception or a joke.
In this instance, you told the AI to argue for a particular conclusion and it did. If the conclusion should happen to be wrong, then no matter how clever the AI might be its arguments can't actually be all that good.
(I don't think GPT-4o is in fact a system of immense intelligence unless you use a really idiosyncratic notion of "intelligence", for what it's worth. That doesn't tell us much about whether its successor's successor's successor might be one.)
What's the goal of posting this right now ? A lot of what's written here seems to be well-trodden ground from the last two years of discussions, is it just to centralize a thesis within one post?
It's damage control because of recent research papers being published saying that AI is not reasoning
> It’s hard to even imagine today what we will have discovered by 2035; maybe we will go from solving high-energy physics one year to beginning space colonization the next year I heard similar things in my college dorm, amid all the hazy smoke. It’s very difficult to take this stuff seriously. It’s like the initial hype around self driving cars wound up by 1000x. Because we got from 1 to 100 of course we’ll get from…
Wait... Self driving cars actually happened. Seems like the hype was true, but 5 years later than expected and now people just think it's normal so they feel the hype was overblown.
Earlier quoted context omitted.
> in areas, AIs are already far better than humans. You could say the same thing about a CPU from 40 years ago - they can do math far better than humans. The problem is that there are some very simple problems that LLMs can’t seem to reliably solve that a child easily could, and this shows that there likely isn’t actual intelligence going on under the hood. I think LLMs are more like human simulators rather than actu…
They could become better at humans bc there's a RL training loop? I don't understand how this isn't directly clear. Even raining purely on human data it's possible to be mildly superhuman (see experiments of chess AI trained on human data only) but once you have verifiable tasks and RL loop the human data is just Kickstarter
We've somehow had a calm few months in the industry without the daily hyperbole on AGI, superintelligence and the upcoming singularity. After the string of underwhelming incremental updates from all the top LLM publishers I guess they need to start the hype cycle again.
Underwhelming?! We're probably a year out of AI-led pure math research and full AI SWEs. I think people forget what it was like 1-2 years ago somehow
> We are past the event horizon; the takeoff has started. Humanity is close to building digital superintelligence, and at least so far it’s much less weird than it seems like it should be. Not sure if wishful thinking trying to LARP-manifest this future into being, or just more unfalsifiable thinking where we can always be said to be past the event horizon and near to the singularity, given sufficiently underwhelming…
Earlier quoted context omitted.
It all sounds probably correct to me. Of course, progress could stall out, but we appear to have sufficient compute to do anything a human brain can do, and in areas, AIs are already far better than humans. With the amount of brain power working in, and capital pouring into, this area, including work on improving algorithms, I think this essay is fundamentally correct that the takeoff has started.
> in areas, AIs are already far better than humans. You could say the same thing about a CPU from 40 years ago - they can do math far better than humans. The problem is that there are some very simple problems that LLMs can’t seem to reliably solve that a child easily could, and this shows that there likely isn’t actual intelligence going on under the hood. I think LLMs are more like human simulators rather than actu…
40 years ago we were clearly compute bound. Today, I think it's fairly clear we are not; if there is anything a human can do that an AI can't, it's because we lack the algorithms, not the compute.
So the question becomes, now that we have sufficient compute capacity, how long do you think it will take the army of intelligent creative humans (comp sci PhDs, and now accelerate by AI assistance) to develop the algorithmic improvements to take AI from LLMs to something human level?
Nobody knows the answer to the above, and I could be very wrong, but my money would bet on it being It seems to me like the building blocks are all here. Computers can now see, process scenes in real time, move through the world as robots, speak and converse with humans in real time, use tools, create images (imagine?), and so forth. Work is continuing to give LLMs memory, expanded context, and other improvements. As those areas all get improved on, tied together, recursively improved, etc., at some point I think it will be hard to argue it is not intelligence.
Where we are with LLMs is Kitty Hawk. The world now knows that flight (true human level intelligence) is possible and within reach, and I strongly believe the progress from here on out will continue to be rapid and extreme.
We've somehow had a calm few months in the industry without the daily hyperbole on AGI, superintelligence and the upcoming singularity. After the string of underwhelming incremental updates from all the top LLM publishers I guess they need to start the hype cycle again.
> A lot more people will be able to create software, and art. But the world wants a lot more of both, and experts will probably still be much better than novices, as long as they embrace the new tools. This isn't correct: people want good software and good art, and the current trajectory of how LLMs are used on average in the real world unfortunately run counter to that. This post doesn't offer any forecasts on the h…
>and the current trajectory of how LLMs are used on average in the real world unfortunately run counter to that. This post doesn't offer any forecasts on the hallucination issues of LLMs. You are getting confused here... LLMs are terrible at doing software engineering jobs. They fall on their face trying to work in sprawling codebases. However, they are excellent at writing small bespoke programs on behalf of regular…
This smells like "Self-checkouts", "perfect bespoke solution so that everyone can check their own groceries out, no need to wait for a slow/expensive _human_ to get the job done, except you end up basically just doing the cashiers job and waiting around inconveniently whenever you want to get some beer