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ML promises to be profoundly weird

aphyr.com

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Re: ML promises to be profoundly weird

#491
post #476

Earlier quoted context omitted.

It's sort of the exception that proves the rule. This is where STEM people are weak- a lack of knowledge on history. In another forum, someone would have chipped in that England's virgin forests were fully deforested by 1150. And someone else would have pointed out that this deforestation produced the economic demand for coal that drove the Industrial Revolution in the first place. Still, that kind of underscores OP'…

> powered solely by human muscle Both animals and water power go way back. The early steam engine was measured in horsepower because that’s what it was replacing in mines. It couldn’t compete with nearby water power which was already being moved relatively long distances through mechanical means at the time. Hand waving this as unimportant really misunderstands just how limited the Industrial Revolution was.

Irrelevant. Here's Bret Devereaux (an actual historian) explaining this distinction and precisely why those are irrelevant in the context of the Industrial Revolution:

https://acoup.blog/2022/08/26/collections-why-no-roman-indus...

> Diet indicators and midden remains indicate that there’s more meat being eaten, indicates a greater availability of animals which may include draft animals (for pulling plows) and must necessarily include manure, both products of animal ‘capital’ which can improve farming outputs. Of course many of the innovations above feed into this: stability makes it more sensible to invest in things like new mills or presses which need to be used for a while for the small efficiency gains to outweigh the cost of putting them up, but once up the labor savings result in more overall production.

> But the key here is that none of these processes inches this system closer to the key sets of conditions that formed the foundation of the industrial revolution. Instead, they are all about wringing efficiencies out the same set of organic energy sources with small admixtures of hydro- (watermills) or wind-power (sailing ships); mostly wringing more production out of the same set of energy inputs rather than adding new energy inputs. It is a more efficient organic economy, but still an organic economy, no closer to being an industrial economy for its efficiency, much like how realizing design efficiencies in an (unmotorized) bicycle does not bring it any closer to being a motorcycle; you are still stuck with the limits of the energy that can be applied by two legs.

So yeah, actual historians would be dismissive at your exact response, basically saying "I know, I know, but I don't care". You're still just talking about a society mostly 'wringing efficiencies out the same set of organic energy sources'. It IS unimportant, and you completely misunderstand how the Industrial Revolution reshaped production if you think it is important.

Re: ML promises to be profoundly weird

#492

Earlier quoted context omitted.

> They do not reason How do you disprove it?

We know that they do not reason because we know the algorithm behind the curtain. The model is generating the next token via model weights and some randomness. That’s all. It not reasoning. Sometimes it has an appearance of reasoning, but not if you know how it works. It doesn’t matter that the model manufacturer marketing department slaps a “Reasoning!” sticker on the side of the model. It’s not actually doing that.…

And the brain is just a complicated chemical reaction.

Re: ML promises to be profoundly weird

#493

There is a whole giant essay I probably need to write at some point, but I can't help but see parallels between today and the Industrial Revolution. Prior to the industrial revolution, the natural world was nearly infinitely abundant. We simply weren't efficient enough to fully exploit it. That meant that it was fine for things like property and the commons to be poorly defined. If all of us can go hunting in the woo…

>This completely unpends the tenuous balance between creators and consumers. Why would a writer put an article online if ChatGPT will slurp it up and regurgitate it back to users without anyone ever even finding the original article? Who will contribute to the digital common when rapacious AI companies are constantly harvesting it? Why would anyone plant seeds on someone else's farm?

This is completely reversed. Why should anyone honour the right of some creator who was merely the first to plant their flag on a creative task that is now absolutely trivial to perform by AI? Who needs a digital commons when creation itself is now the commons and freely accessible for pennies? The seeds plant and grow by themselves now. The only question is who should be allowed to claim the farms?

Answer: No one. AI companies will have their lunch eaten by open source. And if they don't - they should be nationalized and protocolized into free utilities. The entire idea of digital ownership should (and will) be abolished by the very nature of this technology.

The digital world is the new infinitely-abundant nature. We're just returning it to where it should have been, before corporations clawed it into fenced off empires.

Re: ML promises to be profoundly weird

#494

There is a whole giant essay I probably need to write at some point, but I can't help but see parallels between today and the Industrial Revolution. Prior to the industrial revolution, the natural world was nearly infinitely abundant. We simply weren't efficient enough to fully exploit it. That meant that it was fine for things like property and the commons to be poorly defined. If all of us can go hunting in the woo…

The silver lining in that scenario is that consumers can "choose" to just go back offline. I put choose in quotes because with so many things in life requiring online accounts nowadays, that choice is tenuous.

Re: ML promises to be profoundly weird

#495

Earlier quoted context omitted.

> To some extent. It's not clear where specifically the boundaries are, but it seems to fail to approach problems in ways that aren't embedded in the training set. I certainly would not put money on it solving an arbitrary logical problem. In what way can you falsify this without having the LLM be omniscient? We have examples of it solving things that are not in the training set - it found vulnerabilities in 25 year…

Here's an odd example of testing, but I design very complex board and card games, and LLMs are terrible at figuring out whether they make sense or really even restating the rules in a different wording. I thought they would be ideal for the job, until I realized that it would just pretend that the rules worked because they looked like board game rules. The more you ask it to restate, manipulate or simulate the rules,…

Re: cheap - Anthropic’s write-up said it cost $20,000 of runs to find that bug (and a few others). So not that cheap compared to other tools - more similar in cost to human review/pentest, but probably more exhaustive.

> This was the most critical vulnerability we discovered in OpenBSD with Mythos Preview after a thousand runs through our scaffold. Across a thousand runs through our scaffold, the total cost was under $20,000 and found several dozen more findings.

They don’t talk about the other findings, so I’m guessing they are minor.

Re: ML promises to be profoundly weird

#496
post #478

Earlier quoted context omitted.

I believe running out of trees was always a local issue - there weren't enough trees where you were at because getting trees had to be gotten locally, you didn't go get trees from far away. So yes that was in constant tension, the thing is that the problem of having enough trees turned from a local problem to a global problem, with the side effects of not having enough trees globally that the world needed to maintain…

By local you mean over 5 thousand of miles? Because yes moving wood was always in competition with growing it locally. But pine forests in the far north were untouched because of the low quality of the lumber they produce not the distances involved. All of Africa Europe and Asia ran out of the most valuable natural lumber a fucking long time ago. > I think the natural world was nearly infinitely abundant is a reasona…

>By local you mean over 5 thousand of miles?

maybe, "local" is a function of a lot of things, it is only fairly recently in human history that the "global" functions the way that "local" did centuries ago, meaning that it is cheap enough to source things from across the world that it does not need to be made in the next village.

>> I think the natural world was nearly infinitely abundant is a reasonable description

>Very little of the world’s woodland was untouched at the time of the Industrial Revolution and forests in the Americas survived as long as they did largely due to disease drastically reducing native populations.

things seemed appeared abundant prior to one event, soon after that event the thing no longer appears abundant, there's a correlation is the point, not a causation, but

>American forests were on the clock independent from industrial development.

sure, the Native Americans would have used up their forests if they had kept growing and not been killed off by disease brought by Europeans. Nonetheless they had been killed off, the world appeared infinite, because all you needed to do when you ran out of wood in one place is go to another place to source it, hurray, but now that is no longer the case. We have ran out of places to go get more wood.

As noted I said I felt the phrase "the natural world was nearly infinitely abundant" uttered by the original poster in this subthread is a reasonable description, and I mean obviously that is dependent on the impressions of the people of the time, and from my readings it seems like this was more the feeling than oh noes, we are running out of wood.

Although we got into a side track on wood, because that is what the first response to the OP was, that wood was always a problem, which that some natural resources were constrained still does not really disprove the phrase "the natural world was nearly infinitely abundant" since the word nearly can be seen as a cheat, and really what it means is that the world felt infinitely abundant at one time now it does not.

>We still can’t reasonably extract most resources from the ocean bottom. That’s ~70% of the world’s mineral wealth just off the table.

see, it sounds like you still feel like it is closer to infinitely abundant than dangerously used up. All we need to do is up our extraction game, at least were minerals are concerned.

NOTE: I think maybe the world feeling infinitely abundant thing is actually an American thing, this has been remarked by others in the past, that the first European settlers felt this was a world that had not been touched because in comparison to Europe it was under-exploited in many areas, it was big and had everything, and there is a whole part of American frontier myth that as soon as one area got settled and used up all you had to do was to pack up your stuff and move west and get a bunch of resources to use up, like locusts, or maybe just colonizers.

In this case the OP's idea of writing this up is that really what they are dealing with is not how the world was - infinitely abundant - but how it felt to people coming from one overly exploited area to an under-exploited one. They believe there is a narrative of economic constraints and results playing out, and that the two situations were analogous, but the source of the analogy - the world before the industrial revolution - was perhaps not as the analogy would have it but really how a memetic framework of exploration and conquest had interpreted the world.

Sorry my note went overly long, but that sometimes happens when I write what I think just as I'm thinking it.

Re: ML promises to be profoundly weird

#497

I think the discussion has to be more nuanced than this. "LLMs still can't do X so it's an idiot" is a bad line of thought. LLMs with harnesses are clearly capable of engaging with logical problems that only need text. LLMs are not there yet with images, but we are improving with UI and access to tools like figma. LLMs are clearly unable to propose new, creative solutions for problems it has never seen before.

Harnesses could have solved things like the bathroom remodel, maybe, but the main point about how LLMs don't understand is the key here. You can make chatgpt better at rendering 3d scenes but you can't make it think, not really. Reasoning was only ever a feedback loop.

Anyone who has worked with LLMs has experienced all the issues he talks about here, we're either optimistic and imagine they'll be fixed, or we're pessimistic and we say they are inherent to the nature of the technology and will never be fixed

Re: ML promises to be profoundly weird

#498
post #370

Earlier quoted context omitted.

> Prior to the industrial revolution, the natural world was nearly infinitely abundant. We simply weren't efficient enough to fully exploit it. This is just wildly incorrect. People started running out of trees during the early Iron Age. Woodlands have been a managed and often over exploited resource for a long time. Active agriculture vs passive woodlands vs animal grazing has been in constant tension for thousands…

The general point is accurate, don’t take it so literally. There were more than enough trees until we developed the technology to clear cut in expeditious manner. There were more than enough fish until we developed the technology to pull massive indiscriminate amounts out of the ocean (and/or started polluting our rivers with industry). There was more than enough topsoil until we developed mechanized plows and artifi…

The general point is not. Iceland and Easter Island were fully deforested way before the industrial age. Countless species went extinct in Britain and more examples abound.

Re: ML promises to be profoundly weird

#499

Earlier quoted context omitted.

I've got about 20 minutes in this; mostly I've been reading wallstreetbets at the Shake Shack bar in the Boston airport. I'm happy to post this over and over again until you engage w/ it: > I found over 500 examples that fit your criteria.

They don't use tools. Like the 4th time you ignored this on purpose. That was not part of the challenge.

GPT-5.4 gets 82.7% on Browsecomp (a benchmark specifically testing tool use), which is a hallucination rate of 17.3%, on questions like "Give me the title of the scientific paper published in the EMNLP conference between 2018-2023 where the first author did their undergrad at Dartmouth College and the fourth author did their undergrad at University of Pennsylvania."

Since the goalposts have been moved to include effort, I'm compelled to say I found this while waiting in line at Starbucks, 5 mins tops. Probably GPT-5.4 could have found this too, though it lies > 1/6 the time, so one could be forgiven for not wanting to risk it.

https://llm-stats.com/benchmarks/browsecomp

https://openai.com/index/browsecomp/

Re: ML promises to be profoundly weird

#500

There is a whole giant essay I probably need to write at some point, but I can't help but see parallels between today and the Industrial Revolution. Prior to the industrial revolution, the natural world was nearly infinitely abundant. We simply weren't efficient enough to fully exploit it. That meant that it was fine for things like property and the commons to be poorly defined. If all of us can go hunting in the woo…

> Prior to the industrial revolution, the natural world was nearly infinitely abundant.

Prior to the industrial revolution, people fight to death for who can use the rivers. Pre-industrial societies are societies of scarcity.

[0]: People have been fighting for water for more than 4000 years: https://en.wikipedia.org/wiki/Umma%E2%80%93Lagash_war

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