921–930 of 1000 posts
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I'm talking statistically, not what happens for a lucky few. Keynes was hoping that our workweek would be 20h/week by now, through technological advancement. Instead places like the US are thinking about adopting 9/9/6 and some US states are legalizing child labor again.
> what happens for a lucky few. I'm talking about the unlucky.
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It's almost like I disagree with your use of the phrase in this context, rather than that I don't know the meaning of it.
So you defined your own idiosyncratic version of "moving the goalposts" and used it to rebut his argument, with a condescending "you understand that's how science works, right?"--instead of being honest that it is you who are changing the definition, and not his failure to understand anything. I don't see how that's any better.
Actually, I'm really an LLM and this whole thing was a clever bluff.
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Not everyone works for Evil Corp. I work in the public sector and my work supports public health and safety initiatives. AI has allowed my team to get much more done than we would have otherwise which improves the quality of life of the people in my community. So I would like to counter your cynicism with a “YMMV” depending on who you work for.
Examples?
Remember, this is the propaganda arm of a VC. Proof is a hindrance to the hype that drives value.
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In US politics, the right is far, far better at winning elections than the left. This isn’t about personal preference. It’s objective political science. Look at the most contentious issues in the US: abortion, climate change, taxing the wealthy, gun control, Affordable Healthcare Act. The Democratic Party platform is aligned with national polling on every one. Every one of those issues has >60% support with voters an…
Objectively? > Democratic Party platform is aligned with national polling on every one. It depends on the pollster and where you're polling. I guarantee you rural Tennessee will not agree with downtown Washington DC on any of these issues. In contrast, rural California will likely agree with rural Tennessee. It's not as cut and dry as a homogeneous national poll of 2500 people. Every state, city, county are different…
The pretense of Dobbs is that laws against abortion are like laws prohibiting medical marijuana or setting speed limits. This contradicts the purpose of laws against abortion and the actual language of most of them. It was obviously a desperate decision, irrespective of the truth about abortion
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If it seems like I don't understand the meaning of that very well-known phrase, then clearly I have failed to make my point. I'll try again. And please note that I will use some generalizations to make my point more clearly, rather than because I don't understand nuance; kindly grant me a charitable reading. In recent years, I have commonly seen the phrase "you're moving the goalposts" deployed by the "it might be se…
> If we didn't move the goalposts, then by definition we already knew exactly where we were headed at the beginning, and we very clearly did not. To me, the goalposts were already defined by the person you were responding to. "The impact of AI is getting undeniable", so, the goalposts are "the impact of AI". Probably something like "the impact of AI is high, or will be soon". Note that this does not depend on things…
> "The impact of AI is getting undeniable", so, the goalposts are "the impact of AI". Probably something like "the impact of AI is high, or will be soon".
those are not goalposts - that's an incredible vague 'goal'. What are we moving here exactly?
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Five (maybe six?) of the results are improvements on bounds. These kinds of problems tend to have some initial advances, and then stall out as the complexity of the bound skyrockets... until some grad student is bored enough to push the boundary. The big-O complexity of matrix multiplication is a good example of how this works: yeah, it's a useful problem, but the solutions are galactic algorithms, and increasingly c…
Your inverted logic does not hold. The fact that such useless problems for bounds exist does not mean that improving bounds is useless. 9 fields medals in the last twenty years, including the one to Terrence Tao, were for improvements on bounds. 3 of the 4 medals in 2022 were for bounds; 2 of these medals were in combinatorics.
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If it seems like I don't understand the meaning of that very well-known phrase, then clearly I have failed to make my point. I'll try again. And please note that I will use some generalizations to make my point more clearly, rather than because I don't understand nuance; kindly grant me a charitable reading. In recent years, I have commonly seen the phrase "you're moving the goalposts" deployed by the "it might be se…
> When rapid progress is made in a poorly-understood field, then how can our definitions and requirements for success not change? It's in how they change, not the fact that they change. The skeptics seem to have secret definitions for intelligence, sentience, consciousness, creativity, etc. that amounts to "a thing only humans have". Often that thing is equivalent to a soul. When yesterday's challenge (LLMs don't hav…
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Everything has limits, of course. But if you've not yet seen a deceleration, it's reasonable to expect that at the least you're in the middle of the sigmoid, not the top.
> But if you've not yet seen a deceleration We have though. The velocity remains high but the acceleration is decreasing. The improvement between gpt 2-4 where staggering. to 5, 5.6? Much less so. The results improve of course, but the difference is no longer mind blowing. Most of the improvement now has come from agentic harnessing, which is unrelated to the acceleration of the model but the tooling around the use o…
The diminishing returns are colossal. GPT 4 is more than 3 years old now, and while Sol is definitely better, it’s better at a tremendous cost. And 3 years of development. And it still fails in nearly all the same places as 4.0.
I’m not some “zero AI” person, I don’t think this industry will collapse into nothing and we will go back to a no LLM world.
But to look at this industry, which basically began in November 2022, almost 4 years and a trillion+ dollars later and say “oh yeah, definitely riding that exponential growth still” is some of the wildest shit I’ve ever seen, and it’s so common.
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> we’ve seen huge lifts in all of these areas, not just the verifiable ones. most gains are still coming from data. isnt that supposed to 'run out' though?
Labs spend billions hiring experts to generate new data, and better models can better filter existing training data and generate new synthetic data. There’s no reason for that to run out, it’s just expensive. You could view this as just continually patching a leaky ship. But it seems to work.
I thought this is mostly RL data. In my previous comment i was referring to pertaining data.
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Cambridge Analytica gathered data to build targeted profiles and used these profiles for political advertising without informed consent: https://en.wikipedia.org/wiki/Facebook%E2%80%93Cambridge_Ana...
Yes, but there is little evidence this had a meaningful effect on votes.
You're not allowed to bribe public officials. You're not going to escape the law by arguing that the bribe didn't get you the result you wanted.