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Notes -
On the plausibility of Mars Bases vs that of AI
Responding to @FeepingCreature from last week:
That was a continuation of this discussion in which I say of AI 2027:
As to Mars:
Most of what I know here comes from reading Zach Wiener-Smith (of SMBC)'s A City on Mars. It was wildly pessimistic. For a taste, see Gemini chapter summaries and an answer to:
"Given an enormous budget (10% of global GDP) and current tech, how realistic is a 1 year duration mars base? an indefinite one? what about with highly plausible 2035 tech?"
I agree with the basic take there, both as a summary of the book and as a reflection of my broader (but poorly researched) understanding/intuition of the area: Mars is not practical. We could probably do the 1 year base if we don't mind serious risk of killing the astronauts (which, politically, probably rules it out. Maybe Musk will offer it as a Voluntary Exit Program for soon-to-be-ex X SWEs?)
My main interesting/controversial (?) take: there is an important sense in which Mars bases are much less of baseless scifi nonsense than AI 2027.
Mars is a question of logistics: on the one hand, building a self-contained, O2 recycling, radiation hardened, etc, base requires tech we may (?) not quite have yet. On the other hand, it strikes me as closer to refinements of existing tech than to entirely new concepts. Note that "enormous budget" is doing a lot of work in here. I am not saying it is practical to expect we will pay to ship all of this to Mars, or risk the lives, just that there is good reason to believe we could.
AI is a question of fundamental possibility: by contrast, with AI, there is no good reason to think we can create AI sufficient to replace OpenAI-grade researchers with forseeable timelines/tech. Junior SWEs, maybe, but it's not even clear they're on average positive-value beyond the investment in their future (see my previous rant about firing one of ours).
I don't understand how anyone can in good faith believe that even with an arbitrary amount of effort and funding, AGI, let alone ASI, is coming in the next few years. Any projection out decades is almost definitionally in the realm of speculative science-fiction here. Even mundane tech can't be predicted decades out, and AI has higher ceilings/variance than most things.
And yet, I am sensitive to my use of the phrase "I don't understand." People often unwittingly use it intending to mean "I am sure I understand." For example: "I don't understand how $OTHER_PARTY can think $THING." This is intended to convey "$OTHER_PARTY thinks $THING because they are evil/nazis/stupid/brainwashed." But, the truth of their cognitive state is closer to the literal usage: they do not understand.
So, in largely the literal sense of the phrase: I do not understand the belief in and fear of AI progress I see around me, in people I largely respect on both politics and engineering.
The question to me hinges on this: did the people who say that AGI seems fundamentally impossible then consider that the sub-AGI systems that we today possess were possible? Right now I can go on Twitter and pick up a two-page detailed instruction booklet written in plain English that, if I feed it into a commercially available chatbot, will empower this chatbot to, through a deductive process that at least reads surprisingly similar to human research, form a remarkably accurate answer as to where a photo was taken, where the originators of this chatbot had never at all considered this possibility and did not build the chatbot for this purpose. In the course of doing so, the chatbot will autonomously search the internet, weigh evidence, and execute optical comparisons of photos evincing high-level understanding of visual features. Would anybody who currently says that AGI is sci-fi have admitted this technology could exist? Or would they have said it was, as it were, "at least 100 years off"?
Sure, we don't understand how the models do it so it's easy to say "I thought we didn't have a research path to that skill, and actually we still don't." But empirically, it seems to me that enough skills have been "flaking off general intelligence" - turned out to not be "general intelligence" bound after all - that to me the whole concept of general intelligence is now in doubt, and it seems at least plausible that more and more "AGI-complete skills" will continue to flake off and become practically solved until there's nothing left to the concept. Certainly at least the confident claim that this won't happen is looking very shaky on its feet right now.
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I put in a few thousand lines of code into an AI, ask it to change it to fix this issue... and it can do it. Sometimes it can't and it gives me a broken fix, other times I have to try several times or go through various stages of brainstorming, log-analysis, trial and error, workarounds.
If you're doing intellectual labour (this is intellectual labour, it's producing code that earns revenue) then you must be intelligent not in the 'answers toy questions' sense but the 'does useful work' sense. If it is intelligent, then AGI shouldn't be far away. It's only a matter of investment and incremental development.
Fundamental possibility is deader than disco. There is no reason for doubt at this point. You think there's an insurmountable gap between Junior SWE and senior SWE? That's ridiculously silly. There was no insurmountable gap between 'can't walk except on perfectly straight floor at 3 kph' and 'diving through hills, scrabbling around obstacles, getting up after being knocked over'.
There wasn't an insurmountable gap between 'the most deranged and hilariously stupid pretend harry potter writing imaginable' https://youtube.com/watch?v=6rEkKWXCcR4 and 'any story imaginable written in perfect, fully meaningful English albeit usually (but not always) lacking in literary merit but at a very reasonable price'.
There wasn't an insurmountable gap between 'can't identify a cat' and 'short videos of catgirls'.
There wasn't an insurmountable gap between 'literally no code at all' and 'Stackexchange withering away'.
There's no reason for doubt, you can't even give a reason except these elaborate statements of surety. I don't understand how what you're saying even resembles a valid argument. Forget about whether the premises are true or if the argument follows, there are no premises in what you're saying!
It really is remarkable the strength of claims that otherwise smart people will make about the impossibility of AI doing something. As evidenced by IGI's reply, I think usually if someone has gotten this far without updating, you shouldn't expect a mere compilation of strong evidence to change their minds, but just to prompt the smallest possible retreat.
I had an amazing conversation with an academic economist that went along similar lines. I asked why his profession generally wasn't willing to even entertain the idea that AI could act as a substitute for human labor, and he said "well it's not happening yet, and making predictions is beyond the scope of our profession". Just mind-boggling.
To empathize a little, I think that people intuitively understand that admitting that a machine will be able to do everything important better than them permanently weakens their bargaining position. As someone who hopes humanity will successfully form a cartel before it's too late, I fear we're in a double-bind where acknowledging the problem we face makes it worse.
FWIW I don't think I'm engaged in motivated reasoning here, if only because I no longer need to seek wage for a living. Though I'll admit it is pretty funny that Andreessen says the only job AI can't do is Venture Capitalist.
I think I simply disagree with the postulate that cognition is entirely reducible to statistical inference.
I'm still confused what you're claiming. Who is claiming that cognition is entirely reducible to statistical inference? In any case, are the LLM companies somehow committed to never using anything but statistical inference?
LLMs are by definition big piles of algebra built from large datasets, so this is a tautology. They would be something different if they were something different.
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If an insurmountable gap there is, I claim is is not in the ability to do useful work, but in the ability to tell whether that work is useful or not.
Can you help me understand this claim more concretely? E.g. if an LLM had just successfully designed a bridge for me, but then I modified the design to make it not useful in some way, for some kinds of changes it wouldn't be able to tell if my change was good or not? But a human would?
Let's say you overlooked telling it about some fairly critical detail (your bridge is affected by gravity in some unusual way, or something, I'm not a civil engineer). It's not going to be able to figure that out on its own. And the world is full of such critical details that aren't captured in public datasets (or worse, are captured totally wrong). It will then confidently work off the wrong track, sometimes in subtle enough ways that it requires an expert to notice.
You can observe this right now if you work in a specialized or cutting edge field where solutions to problems are unintuitive. LLMs become worse than useless the more what you're trying to do works like that. And that's fine, it's just not the right tool.
But if there's something that looks like a fundamental limit of the approach vis à vis intelligence, that's what it looks like to me.
There's also more general issues with agentic systems specifically and how quickly they seem to fall victim to noise and hallucinations without human supervision, but I'm more on the fence as to whether this can be ameliorated.
Right, but neither would a human, unless they also had more direct access to the problem somehow. But that's what agentic scaffolding is for.
Even with tens of thousands of experts spending billions of dollars and R & D for a decade to solve these problems?
Seems like you're retreating to "I'm not sure"?
I'm not saying we'll never learn to fly or travel faster than light, but it's going to require innovation that is not incremental, and that can't be predicted.
Certainty is unwise, one way or another.
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I've had the "modern AI is mind-blowing" argument quite a few times here (I see you participated in this one), and I'm not really in a good state to argue cogently right now. But you did ask nicely, so I'll offer more of my perspective.
LLMs have their problems: You can get them to say stupidly wrong things sometimes. They "hallucinate" (a term I consider inaccurate, but it's stuck). They have no sense of embodied physics. The multimodal ones can't really "see" images the way we do. Mind you, just saying "gotcha" for things we're good at and they're not cuts both ways. I can't multiply 6 digit numbers in my head. Most humans can't even spell "definately" right.
But the one thing that LLMs really excel at? They genuinely comprehend language. To mirror what you said, I "do not understand" how people can have a full conversation with a modern chatbot and still think it's just parroting digested text. (It makes me suspect that many people here, um, don't try things for themselves.) You can't fake comprehension for long; real-world conversations are too rich to shortcut with statistical tricks. If I mention "Freddie Mercury teaching a class of narwhals to sing", it doesn't reply "ERROR. CONCEPT NOT FOUND." Instead there is some pattern in its billion-dimensional space that somehow fuzzily represents and works with that new concept, just like in my brain.
That already strikes me as a rather General form of Intelligence! LLMs are so much more flexible than any kind of AI we've had before. Stockfish is great at Chess. AlphaGo is great at Go. Claude is bad at Pokemon. And yet, the vital difference is that there is some feature in Claude's brain that knows it's playing Pokemon. (Important note: I'm not suggesting Claude is conscious. It almost certainly isn't.) There's work to do to scale that up to economically useful jobs (and beating the Elite Four), but it's mainly "hone this existing tool" work, not "discover a new fundamental kind of intelligence" work.
The main reason for LLM scepticism is this impression can be extremely deceiving. I had totally missed how little mathematical understanding my classmate actually had, even in years of helping him, until he made a very specific kind of mistake once. And it goes way further than that: It seems like most humans "know in principle" how to count, even if they only have words for the low numbers. But they dont! Counting to ~7 is done with pattern recognition. Dogs can count to 3. Higher numbers are counted with the recursive method, and you dont get any closer to that by improving pattern recognition. That might get you something that can count to 100, if you give it enough compute, but thats not actually any closer to the new kind of intelligence youd want.
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Everyone thinks about Mars wrong. I can be done in record time and on a shoestring budget if we think about terraforming and then move the meatware there. Same with the moon. We are almost at the technological level in which we can build almost self replicating something if we put our minds to it.
Terraforming being "almost" within reach is quite some statement. We can't even terraform Earth beyond very slightly changing the composition of a preexisting atmosphere under ideal planetological and logistical conditions. But we're almost ready to go creating and maintaining a human-breathable atmosphere and temperature and radiation levels on a deep-frozen desert like Mars, a tiny pebble like the Moon or a comically uninhabitable hellhole like Venus? Using chemical rocketry that barely makes it viable to put communications sattelites into low Earth orbit and can sling tiny little probes to other planets for mere billions apiece?
Space colonization will be done, if at all, in sealed habitats. Terraforming is wishful thinking.
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Isn't the easiest terraforming actually Venus, and that's still a century's long process with some steps we haven't quite figured out?
The problem with Venus is the initial cooling of it. Any kind of shade generating device will be blown away from the solar wind.
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I don't see any way to do Venus faster than Mars. Even if you cooled it down very quickly with orbital mirrors it would take a long time for the atmosphere to condense out. You can get Mars to a partially terraformed state i.e. stable bodies of water on the surface much faster, although if you wanted to bring in enough nitrogen for an earthlike atmosphere and surface pressure it would take you a lot longer.
I might be wrong, but my understanding of Venus colonisation is actually to terraform it enough so that it’s possible to live high up in the atmosphere rather than on the hellish surface.
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How do you propose to “terraform” magnetospheres into the moon or Mars? Terraforming in general is extremely sci-fi on the tech tree: we might have the resources within the next half-millennium, but even that’s unsure. The most realistic terraforming proposal I’ve seen for Mars is to basically melt the entire surface to release gasses, and even then that won’t be enough by itself to get the job done.
We don't need magnetospheres. Living under the surface is totally fine. The idea is to have massive energy producing and material harvesting operations ready on the surface and underneath it, so we can synthesize the organics humans need. We will never have green Mars - too little sunlight there. So no need bothering.
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You could stick a giant shield at the L1 point and call it a day.
Not even "giant" by some standards - the calculations I've seen say approximately 1 gigawatt for an adequately sized electromagnetic shield. Putting a reactor that big in space would be a literally massive undertaking, but not relative to the value of shielding an entire planet, and once the reactor is up there it'd only be a couple dozen tons per year of uranium to refuel it.
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What I've read is that the magnetosphere doesn't matter because the atmosphere blows off very slowly (millions of years) so if you can create a new one in the first place you're fine.
The surface is still going to be hit pretty hard with radiation if you don’t have a magnetosphere, atmosphere or no.
Atmosphere does actually absorb a lot of radiation.
It provides moderate shielding against Sun radiation and minimal against cosmic rays, but overall it's not enough to be safe for humans, you still need fairly large radiation shielding for dwellings. Especially if you want to compensate getting dosed if you're out and about.
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The most viable proposal I've seen involves satellites orbiting various lagrange points around Mars that could generate a magnetosphere for the planet. Power requirements are extremely high (something in the giga or terawatt range IIRC) but not outright impossible.
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How would you terraform the moon even in principle? There's not enough gravity there to hold on to an atmosphere.
put solar on top of everything outside, bolted, dig big climate controlled caverns inside, massive production facilities to launch what is needed to other planets from the moon instead of the earth.
This, ah, is not terraforming.
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I'm under the impression that terraforming is much more scifi than most approaches. Is that not the case?
I'd still bet it's easier to achieve than AGI, let alone ASI, but I think it's more in the "speculative sci-fi" bucket with them, not in the "expensive and economically disincentivized" bucket with "radiation hardened dome with a year worth of Soylent powder on Mars" one.
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I think AI maybe not 2027, but certainly before 2032, is the much surer bet, not because AI is that much closer, but because Mars Base requires not only an upfront investment of decades and billions but also probably another billion in upkeep. Unless you have a very very good reason to build a base on another planet (or to be fair, faster rockets) it’s just not something people or governments are going to spend 1% of global GDP on. If it’s 10% of global GDP and might well take a generation or two (my thinking is probably two as you’d need to be able to grow substantial amounts of food, produce substantial amounts of water, extract minerals and metals, and so on) it’s just too expensive to consider. Keep in mind that until you are self sustaining, you are a net drain unless you send the amount of resources back to Earth to cover materials sent plus the fuel needed to get them to the base. Are there 15% of global GDP in minerals and metals on mars in such a way that it could be extracted with low enough cost to make this work? I honestly doubt it. Once you factor in the cost of extraction and refining and launching the material earth-ward and sustaining the crew to do the work, plus the crew to support the miners, it’s pretty expensive to even attempt it.
AI, even if it takes a bit longer to get there is a self-sustaining effort. The partially automated systems are useful tge minute they’re trained. As such, unlike Mars Base, it’s going to be something that people and governments are going to want to put money in. They’re almost guaranteed to get their money back plus interest in a couple of years when the next Gen AI rolls out and businesses and governments buy it.
I’ll be honest, I really wish space exploration was viable, but more than likely, humans will not leave earth and roam much farther than our nearest neighbors. Everything else is going to be robots and telescopes because traveling the stars is risky and expensive.
Humans were once bold enough that the first Polynesians set sail into the open Pacific with presumably no knowledge of what they'd find over the horizon several thousand years ago (Tonga, Samoa), and then, after several thousand years of a gap -- honestly, an interesting historical question -- as far as Hawaii and Easter Island. I don't think I can even really comprehend what would drive people to set sail in wooden ships without a well-defined destination, or how many anonymous brave souls likely disappeared into deep blue waters without a trace in the process.
Space exploration is, as is often observed, immensely more difficult given the lack of breathable air and such, but I can't help but feel that it sounds more technologically comparable with sailing the open Pacific before the Latins even moved into Italy. God-willing, maybe my descendants will look back upon us comparably while they board the equivalent of scheduled cruise ships, or even whatever analog the of air travel that fits into this.
EDIT: I'm not at all certain how I ended up responding to your comment twice. I must be done for the day.
The Polynesians didn’t face any of the obstacles of space exploration and colonization though. The cost? Chop down a couple of trees, tie them with vines, launch with maybe a big container full of water (that you can easily refill with rainwater) and live off the fat of tge ocean by fishing. Once you land, you still have the ocean for fishing Annnd more than likely you’ll have edible food on whatever island you land on. It’s cheap to do, requires few resources to get there and few to survive once you make landfall. You barely need the ability to plan ahead to pull this off.
And space is absolutely not like this. Mars is 9 months of travel away, and you need to take everything you need to survive with you — air, water, food, etc. you need to overcome the negative health effects of zero gravity. And everything you carry is limited by the physics of launching a rocket into space — launching a kilogram of matter costs $1500. You need 9 months of air, water, food, exercise equipment, the crew itself, waste disposal, and so on. A single rocket to mars is pretty resource intensive. It gets worse. You can’t just pluck a coconut off the abundant trees on mars. In fact, not only are there no trees, but it would require pretty extensive work to get to the place where you could plant food on mars. And you need to take that stuff along with you. And extra supplies to support the crew while they set all this up. Point being that space is nothing like the ocean. And at such high cost, it’s going to compare pretty unfavorably to just about anything else in the national budget. We can work on the mars colony that might be at least resource neutral 40 years from now, or we could spend those billions on AI, or education, or anti poverty programs,or cure a disease, or building a big gold tourist attraction statue of Trump. Even the statue might be a net gain simply because people will want to travel to see it and spend money while there. For most of these things, other than prestige, space loses pretty handily compared to most other ways one could spend the money.
Also the sea exploration one is a lot easier to trial-and-error, especially over a multi-generational timeframe. Not that the Polynesian navigators necessarily got purely lucky, but each exploration mission is far less costly on society.
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There's no "there", there, though. The Polynesians were looking for more nesos where they could live, and they found them. We know what's in interplanetary space, and it's all worse than Antarctica. Interstellar space might have something but it's just too damn far away; like the Polynesians shooting for the moon.
The typical retort is that what there is, is a chance of survival for the human race in the event of total catastrophe befalling the Earth, albeit in reduced circumstances. Now sure, this is such a remote concern that it would be unlikely to motivate nations to make the expense. But that may say more about nations than about the soundness of the idea (depending on how much you value the survival of the human race).
This idea seems to come from scifi geeks thinking space is really cool, and trying to come up with some sort of justification for exploring it.
It's not hard to think of a catastrophe that would make the Earth unlivable, but space is already unlivable, unless you can terraform something, and that's a generations long project. Going into space won't be any better than going to Antarctica or the sea floor, or underground.
I don't understand this perspective. I'm not an astronomy or physics expert, but I did study it in school, and as best as I can tell, there is a scientific consensus that the Earth will become uninhabitable to humans due to the Sun expanding within the next 5 billion years. Which means that, if we want humanity to survive beyond that, we will have to figure out some way to sustainably live off of Earth (and likely off of the Solar System) between now and then. This, to me, has always been the justification for figuring out space exploration.
I'm partial to the argument that undertaking this project in the year 10^9 AD or even 10^6 AD might be a better use of resources than in the year 2025 AD. But I'm also partial to the argument that technology doesn't just progress through time alone, that we can always come up with excuses for why this would be easier or more efficient to tackle later, and as such, we might as well start working on it now.
Self-sustaining habitats in Antarctica or the sea floor or underground seem like decent short-term projects for catastrophes in the short term (as well as good settings for steampunk-inspired video games), but I don't see any way around space exploration for long term human survival, outside of even more outlandish things like time travel or portals.
By that reasoning we should have worked on rockets to the moon in 2000 BC.
Very few of either "realistic" hard scifi scenarios, or "realistic" speculative scenarios have us escaping the Earth only in 10^9 AD. The decades of scifi we've had about exploring the solar system have been about much more recent time periods. Sure, maybe we'd do it in 10^9 AD, but 10^9 AD is a long way off. and it isn't what everyone talking about this stuff wants.
And "excuses" is just a spin you put on "reasons".
I mean, if there were people with enough understanding of engineering and astronomy to even understand the very concept of what a "rocket to the moon" meant in 2000 BC, I think it would've been pretty cool if they'd started working on it then.
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My own spicy take is that Mars is a cute idea for a permanent destination, but the asteroid belt has a lot more resources that are more accessible on the basis of not hiding at the bottom of a large gravity well, and makes far more sense in the short term.
Mars' gravity well is shallow enough that you can build a space elevator with present-day materials technology, which means that to a civilisation capable of colonising Mars getting out of the gravity well is cheap.
Do you have any links to read more about that? I'm curious.
I learned about the idea from Kim Stanley Robinson's Red Mars
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You're just asserting this without providing reasoning despite it being the entire crux of your post. I know it's not reasonable to expect you to prove a negative but you could have at least demonstrated some engagement with the arguments those of us who think it's very possible near term have put forward. You can at least put into some words why you think AI capabilities will plateau somewhere before openAI-grade researcher. How about we find out where we are relative to each other on some concrete claims and we can see where we disagree on them.
Do you agree that capabilities have progressed a lot in the last few years at a relatively stable and high pace?
Do you agree that it's blown past most of the predictions by skeptics, often repeatedly and shortly after the predictions have been made?
Are there even in principle reasons to believe it will plateau before surpassing human level abilities in most non-physical tasks?
Are there convincing signs that it's plateauing at all?
If it does plateau is there reason to believe at what ability level it will plateau?
I think if we agree on all of these then we should agree on whether to expect AI in the nearish term, I'm not committed to 2027 but I'd be surprised if things weren't already very strange by 2030.
Then it's good the 2027 claim isn't projecting out decades.
Yes and no. Clearly, things are better than even three years ago with the original release of ChatGPT. But, the economic and practical impact is unimpressive. If you subtract out the speculative investment parts, it's almost certainly negative economically.
And look - I love all things tech. I have been a raving enthusiastic nutjob about self-driving cars and VR and - yes - AI for a long time. But, for that very reason, I try to see soberly what actual impact it has. How am I living differently? Am I outsourcing much code or personal email or technical design work to AI? No. Are some friends writing nontrivial code with AI? They say so, and I bet it's somewhat true, but they're not earning more, or having more free time off, or learning more, or getting promoted.
Again, yes and no. Yes: Scott's bet about image generation. The ability to generate images is incredible! I would have never thought we'd get this far in my lifetime. No: anything sufficient to really transform the world. I have not seen evidence that illustrators etc are losing their jobs. I would not expect them to, any more than I would have from photoshop. See also Jevon's Pardox.
I think that is the crux of our disagreement: I hear you saying "AI does amazing things people thought it would not be able to do," which I agree with. This is not orthogonal from, but also not super related to my point: claims that AI progress will continue to drastically greater heights (AGI, ASI) are largely (but not entirely) baseless optimism.
Nothing has ever surpassed human level abilities. That gives me a strong prior against anything surpassing human level abilities. Granted, AI is better at SAT problems than many people, but that's not super shocking (Moravec's Paradox).
The number of people, in my techphillic and affluent social circle, willing to pay even $1 to use AI remains very low. It has been at a level I describe as "cool and impressive, but useless" forever. I will be surprised if it leaves that plateau. Granted, I am cheating by having a metric that looks like
x -> x < myNonDisprovableCutoff ? 0 : x, where x is whatever metric the AI community likes at any given point in time, and then pointing out that you're on a flat part of it.No, and that's exactly my point! AI 2027 says well surely it will plateau many doublings past where it is today. I say that's baseless speculation. Not impossible, just not a sober, well-founded prediction. I'll freely admit p > 0.1% that within a decade I'm saying "wow I sure was super wrong about the big picture. All hail our AI overlords." But at even odds, I'd love to take some bets.
Thanks for your thorough reply!
I think you're a little blinkered here. It takes more than a couple years to retool the whole economy with new tech. It was arguably a decade or more after arpanet before the internet started transforming life as we know it. LLMs are actually moving at a break neck pace in comparison. I work at a mega bank and just attended a town hall where every topic of discussion was about how important it is to implement LLM in every process. I'm personally working to integrate it into our department's workflow and every single person I work with now uses it every day. Even at this level of engagement it's going to be months to years cutting through the red tape and setting up pipelines before our analyst workflows can use the tech directly. There is definitely value in it and it's going to be integrated into everything people do going forward even if you can't have it all rolled out instantly. We have dozens of people whose whole job is to go through huge documents and extract information related to risk/taxes/legal/ect, key it in and then do analysis on whether these factors are in line with our other investments. LLMs, even if they don't progress one tiny bit further, will be transformative for this role and there are millions of roles like this throughout the economy.
Along with these amazing things it comes with a ripple of it getting steadily better at everything else. There's a real sense in which it's just getting better at everything. It started out decent at some areas of code, maybe it could write sql scripts ok but you'd need to double check it. Now it can handle any code snippet you throw at it and reliably solve bugs one shot on files with fewer than a thousand lines. The trajectory is quick and the tooling around it is improving at a rate that soon I expect to be able to just write a jira ticket and reasonably expect the code agent to solve the problem.
Certainly this is untrue. Calculators trivially surpass human capabilities in some ways. Nothing has surpassed humans in every single aspect. There is a box of things that AI can currently do better than most humans and a smaller box within that of things it can do better than all humans. These boxes are both steadily growing. Once something is inside that box it's inside it forever, humans will never retake the ground of best pdf scraper per unit of energy. Soon, if it's not already the case, humanity will never retake the ground of best sql script writer. If the scaffolding can be built and the problems made legible this box will expand and expand and expand. And as it expands you get further agglomeration effects. If it can just write sql scripts then it can just write sql scripts. If it's able to manage a server and can write sql scripts now it can create a sql server instance and actually build something. If it gains other capabilities these all compliment each other and bring out other emergent capabilities.
If people around you aren't paying for it then they're not getting the really cutting edge impressive features. The free models are way behind the paid versions.
AGI maybe not, but useless? You're absolutely wrong here. With zero advancement at all in capabilities or inference cost reductions what we have now, today, is going to change the world as much as the internet and smart phones. Unquestionably.
Come up with something testable and I am game.
You write like you're an AI bull, but your actual case seems bearish (at least compared to the AI 2027 or the Situational Awareness crowd).
True, there's a lot of places where LLM's could be providing value that are yet unexplored, but changing the workflows of bank analysts is a far cry from the instantiation of a machine god within half a decade.
This is vibe based I suppose and I can mostly only speak for programming, but personally I think most improvements are coming from increased adoption and tooling since around GPT-4. Benchmarks and twitter hype keep going up but I'm not convinced that this reflects meaningful improvement in models for real-world tasks and use cases.
Have we made any progress on an open-source AMD CUDA equivalent, closed out even a statistically noticeable higher number of outstanding issues in Chromium or made Linux drivers competitive with Windows yet? Has GDP or any macro-economic measure moved at all in a way attributable to AI?
Lots of engineers report more productivity using AI tools and I absolutely do too, but better code completion, better information retrieval and making prototyping much easier doesn't make a replacement for an engineer or even represent the biggest improvement to software dev productivity we've ever seen. I attribute a lot more of my productivity to having access to a compiler, the internet and cloud compute rather than LLM assistance.
I think this is true too, in a decade. The white-collar job market will look quite different and the way we interact with software will be meaningfully different, but like the internet and the smartphone I think the world will still look recognizably similar. I don't think we'll be sipping cocktails on our own personal planet or all dead from unaligned super intelligence any time soon.
I was responding to a particularly bearish comment and didn't need to prove anything so speculative. If someone thinks current level ai is cool but useless I don't need to prove that it's going to hit agi in 2027 to show that they don't have an accurate view of things.
well yes, that world is predicated on what I think is a very unlikely complete halt in progress.
I think this gets at a central way in which I've been unclear/made multiple points.
First, some things that I think, but are not my key point:
Why not likely: spreadsheets sure didn't. It might take away a smallish number, but technology adoption has always been so slow.
Why reasonable to discuss: this is fundamentally about existing AI tech and sclerotic incentive structures in the corporate world, both of which we know enough about today to meaningfully discuss.
And finally, my key point in this discussion:
3. Baseless science-fiction optimism: extrapolating well past "current tech, well-integrated into workflows" is baseless, "
linesuper-exponential goes up," science-fiction optimism. Possible? I guess, but not even well-founded enough to have meaningful discussion about. Any argument has to boil down to vibes, to how much you believe the increasing benchmarks are meaningful and will continue. E.g., if we throw 50% of GDP at testing the scaling hypothesis, whether it works or not, all we will be able to say (at least for a while, potentially forever) is: huh, interesting, I wonder why.More options
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I'm reminded of the 1960s article in Analog SF which extrapolated the speeds at which people can travel and concluded we'd have faster than light travel by the 1980s.
Things just don't expand and expand and expand without limit.
If there were lots of natural creatures casually traveling around at light speed through mere evolution those predictions would have been much better founded. It seems like quite the unfounded prediction to have witnessed LLMs rapidly surpass all predictions with the pace not appearing to slow down at all and assume it's going to stop right now. Which kind of must be your assumption if you think we aren't going to hit agi. It rather seems like you're declaring those automobiles will never compete with horses because of how clunky they are. We're at the horse vs car stage where cares aren't quite as maneuverable or fast as horses and maybe will just be a fad.
The FTL graph included horses and cars. Cars got faster than horses, and planes got faster than cars, but speed eventually reached a limit. Saying "cars can still get faster, so they can go FTL" would be wrong.
If you were at the point where cars were just invented, and you said "cars will get faster, but they will reach a limit", you would have been correct.
Yes, but the hard speed limit for cars is obviously not slower than the moving stuff evolution has produced, just like the hard intelligence limit for a machine obviously can't be below what evolution has produced.
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There wasn't ever a mechanism by which cars would start improving themselves recursively if they were able to break 100 mph. There were very good laws of physics reason in the 60s to assume we couldn't even in theory get to FTL. No such reasons exist today. You're not fighting the prediction that cars will be able to go ftl, you're fighting the prediction that mag lev trains would ever be built.
The graph wasn't predicting that cars would go faster than light. It was combining different transports from horses to cars to rockets--the graph was for all human transportation put together. That is, it basically was looking at cars and predicting maglev trains--not by name, of course, but predicting that there would be newer modes of transportation that would be faster than the existing ones. At some point one of these future transports would be faster than light.
Except, at some point, we just stopped getting faster transport. If you look at cars and predict maglev trains, and you look at maglev trains and predict moon rockets, and you look at moon rockets and predict FTL... well, no.
It's like how Moore's Law broke down. Processing power doubled every 1.5 years for decades... until it didn't.
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What? That just isn't true. I've tried to have it write code and it's still in the same shitty place it was three years ago. You get something which looks correct, but maybe it is and maybe it isn't, and you have to double check every time. Which is to say, AI tools still slow you down rather than speed you up.
This is why I'm so skeptical that we'll have AI any time soon. The current tools aren't even good at the things their advocates say they are good at, let alone harder things. I have yet to see any substance behind the hype, at all.
Yeah, I keep hearing this claim from people and keep rebutting it.
It's better than it was three years ago, and the autocomplete functionality saves some time, but it definitely can't "handle any code snippet you throw at it" and its reliability for solving bugs is like 1/10 maybe.
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Have you actually used the latest tooling? What tasks have you actually had it try? This seems incredibly unlikely to me.
I just use whatever ChatGPT has to offer, which would mean yes I'm using the latest tooling (since they keep it up to date). I've tried a variety of things - writing config files for programs we use at work, writing shell scripts, and asking it to explain how to do tasks in AWS CloudFormation. The first and the third tasks it just makes shit up (in some cases even dreaming up code which isn't even syntactically valid), I've found it to be completely useless for those. I've gotten some mileage in shell scripting, where it does fine as long as I keep the request small (like a few lines) so it can't trip over itself. But shell scripting is also an area I'm incredibly weak (essentially I can read bash but can't write it well at all), so it has the biggest gains to make over my own skill there. In cases where I actually know the language well, there's no benefit to me to use these tools. Like I said, if I have to check carefully every time I have it generate something (and you really do), then that's not actually speeding me up.
Here. I picked a random easyish task I could test. It's the only prompt I tried, and ChatGPT succeeded zero-shot. (Amusingly, though I used o3, you can see from the thought process that it considered this task too simple to even need to execute the script itself, and it was right.) The code's clear, well-commented, avoids duplication, and handles multiple error cases I didn't mention. A lot of interviewees I've encountered wouldn't do nearly this well - alas, a lot of coders are not good at coding.
Ball's in your court. Tell me what is wrong with my example, or that you can do this yourself in 8 seconds. When you say "like a few lines", is that some nonstandard usage of "few" that goes up to 100?
Even better, show us a (non-proprietary, ofc) example of a task where it just "makes shit up" and provides "syntactically invalid code". With LLMs, you can show your receipts! I'm actually genuinely curious, since I haven't caught ChatGPT hallucinating code since before 4o. I'd love to know under what circumstances it still does.
Wow! You asked chatgpt to solve a dead simple toy problem, and it solved it! I'm so impressed!!!! Surely this means that chatgpt is definitely capable of handling actual real world tasks.
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I think that we are in the phase of chatgpt in which calligraphs and stenographs don't see the point of typewriters. I would definitely say that chatgpt has saved me a lot of time and made me more productive.
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It's sensitive to context and prompting. When having it write bash scripts have you consider just dumping the man files into the context? Don't bother actually formatting them, just dump anything that could possibly be relevant into the prompt.
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You keep banging this drum. It's so divorced from the world I observe, I honestly don't know what to make of it. I know you've already declared that the Google engineers checking in LLM code are bad at their job. But you are at least aware that there are a lot of objective coding benchmarks out there, which have seen monumental progress since 3 years ago, right? You can't be completely insulated from being swayed by real-world data, or why are you even on this forum? And, just for your own sake, why not try to figure out why so many of us are having great success using LLMs, while you aren't? Maybe you're not using the right model, or are asking it to do too much (like write a large project from scratch).
On paper benchmarks number goes up, but it hasn't translated into real usefulness. Also Goodhart's law
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We have absolutely no clue how to achieve AGI. Simply scaling existing methods, while potentially achieving impressive results, cannot achieve AGI. It is possible that emergent behavior on existing methods allows a specific non-AGI AI can become superhuman in a narrow field that allows it to solve AGI, but we have no reason to believe this is the case.
This reminds me of an old LW article: https://www.greaterwrong.com/w/the-rocket-alignment-problem
Without an understanding of orbital mechanics, it's impossible to reach the moon by just building a bigger rocket and pointing it towards the moon. We're over here on the ground building bigger and bigger rockets: chatgpt, gemini, whatever, but we have no idea what lies ahead on the path to AGI.
Why do you believe this? Is it an article of faith?
It seems like we absolutely do know what lies ahead on the path to AGI and it's incrementally getting better at accomplishing cognitive tasks. We have proof that it's possible too because humans have general intelligence and accomplish this with far fewer units of energy. You can, at this very moment, if you're willing to pay for the extremely premium version, go on chat gpt and have it produce a better research paper on most topics than, being extremely generous to humanity here, 50% of Americans could given three months and it'll do it before you're back from getting coffee. A few years ago it could barely maintain a conversation and a few years before that it was letter better than text completion.
This is rather like having that LW conversation after we'd already put men into orbit. Like you understand that we did actually eventually land on the moon right? I know it's taking the metaphor perhaps to seriously but that story ends up with Alfonso being right in the end. We can, in fact, build spaceships that land on the moon and even return. We in fact did so.
Now we have some of the greatest minds on earth dedicated to building AGI, many of them seem to think we're actually going to be able to accomplish it and people with skin in the game are putting world historical amounts of wealth behind accomplishing this goal.
Absolutely not. Deep research is a useful tool for specific tasks, but it cannot produce an actual research paper. Its results are likely worthless to anyone except the person asking the question who has the correct context.
If you build a bigger rocket and point it at the moon, it will get incrementally closer to the moon. But you will never reach it.
AGI is possible in theory but that does not mean it is possible with currently known techniques.
This clears the bar of most Americans.
If you have some of the smartest people in the world and a functionally unlimited budget you can actually use the information you gain from launching those rockets to learn what you need to do to get to the moon. That is was actually happened after all so I really don't see how this metaphor is working for you. The AI labs are not just training bigger and bigger models without adjusting their process. We've only even had chain of thought models for 6 months yet and there is surely more juice to squeeze out of optimizing that kind of scaffolding.
This is like claiming moore's law can't get us to the next generation of chips because we don't yet know exactly how to build them. Ok, great but we've been making these advancements at a break neck pace for a while now and the doubters have been proven wrong at basically whatever rate they were willing to lay down claims.
Speaking of claims you've decided not to answer my questions, that's fine, continue with whatever discussion format you like but I'd be really interested in you actually making a prediction about where exactly you think ai progress will stall out. what is the capability level you think it will get to and then not surpass?
Newton discovered calculus and gravity without seeing a single rocket.
Sounds like this should be easy then as we have seen some people who are smarter than others.
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People who want to colonize Mars really need to think smaller first.
They should start by trying to build pleasant domed habitats somewhere marginally habitable like northern Minnesota first.
Then a resort hotel near the peak of Mount Whitney where people can take in amazing views.
Thirdly I'd go for a resort hotel on Mount Foster in Antarctica.
Really if a comfortable enclave in Minnesota for remote tech workers isn't practical, I don't see how we're remotely ready to go to Mars.
Biosphere 2 was a pretty notable boondoggle back in the 1990s (notably involving one Steve Bannon, later famous for other work): they failed to make their "separate biosphere" really work in practice, suffering a bunch of ecosystem imbalances and ultimately having to inject external oxygen. Now, their project was pretty ambitious, and I'm not going to completely fault them for the outcome there, but I do think it's necessary to revisit at perhaps slightly more modest scales to prove out long-term independent habitats elsewhere in the solar system. Other than that, there are a handful of Russian experiments I don't know many details of, the ISS (which sources water from the ground for oxygen, vents CO2, and isn't really "closed") and submarines (which have some documentation, but are "sensitive" for probably-good reasons, and aren't really intended as indefinite habitats WRT food and consumables) and at least one YouTuber trying to demonstrate viability.
Honestly, it's a good place to start. And I'm not sure you need a dome either: in theory your long-term space habitat should probably survive with just electrical power. It's really not clear what the smallest "functional" biosphere is, especially once you start leveraging technology ("why yes, we do pump all the CO2 out of the habitat and into the greenhouse to improve plant growth"). There is some fuzziness about "fully closed-loop" too, but let's assume you don't need to maintain the tools themselves indefinitely to start with. I can't imagine $BILLIONAIRE (or NASA, even) couldn't fund a serious project with some graduate students, equipment, and sealed space the size of maybe a studio apartment.
A Martian settlement would not be a sealed system without inputs or outputs, so the example of the biosphere projects is less relevant than, say, the ISS.
There is presumably some point, which admittedly might be beyond Mars settlement, but I suspect isn't fully, at which a fully closed system becomes viable. For the ISS, it's easy enough to ship up food, oxygen (water) and replacement parts with a couple of months notice. For Mars, those timelines get longer and it is at least worth considering whether you need a full set of replacement parts, or the equivalent of raw materials and a machine shop (common on larger oceangoing ships), or whether a closed-loop environmental system (CO2->oxygen + calories->CO2) makes sense. I'll acknowledge it might not, but a Mars settlement needs to be self-sufficient for at least a few years without Earthside supplies.
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This doesn't make sense to me. Building and operating resort hotels is largely orthogonal to colonization settlement, especially where (as in the case of Mount Whitney and Antarctica) the insurmountable obstacles are legal, not technological.
Any real attempt to build a semi-permanent Mars base would have larger political, legal, and financial problems. You can't throw in the towel in the face of a much smaller problem and expect to make it.
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No thanks, you can conquer nature, but the Somalians are going to cause a problem.
It's not a mountain but there is a year round staffed south pole base. Maybe a resort would be nice but only whales with big money would be able to afford it.
There actually is a commercial resort in Antarctica. Going by the rates, they look comparable to about what you'd have to pay to climb Mt Everest.
Not something I'd spend money on, though I'm not sure how it would rank in terms of whale territory.
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I continue to believe that the problem by which sufficient intelligences dedicate themselves to navalgazing and schizophrenia is fundamentally unsolvable; true artificial superintelligence will pull a Chris Langdon. It’ll replace lots of upper midwits, of course, but universal basic six figures for college degree holders isn’t something I care about.
Who is Chris Langdon, and what would it mean to pull one of him?
I made a typo, I meant Christopher Langan. Chris Langdon is an unrelated artist.
This is an American with a notoriously high IQ, who currently lives on a horse ranch to promote his eccentric beliefs. He's not otherwise notable, but his mathematical talent is clearly considerable- he just chooses to use it to prove... something rather than to have effects in the real world.
It's a metaphor for AI coming up with theories and losing all interest in the things it's intended to be doing.
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Chris Langan is a college dropout turned nightclub bouncer and part-time rancher. He received some negative media attention due to his negative opinions toward interracial marriage and his endorsement of some loopy and questionably antisemitic conspiracy theories. He is also possibly the smartest man currently living on the planet with a (disputed) measured IQ of 174.
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I wish I could find a link but I remember back in one of the SSC.com link/open threads a user who worked at JPL actually broke down the logistics of establishing a permanent moon base complete with links relevant NASA studies, and comparisons to the support requirements of Amundson-Scott at the south pole.
As i recall the numbers were absurd but not completely outside the realm of possibility. IE 100 Saturn Five launches a year for 3 years to build a colony that would be functionally self-sustaining.
See also the 1970s book The High Frontier, which proposes a Moon colony as a stepping stone to space habitats. (And the realism-focused board game of the same name.)
Still, the Moon is not Mars.
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We know that systems capable of acting like smart humans are possible (after all, there are smart humans). Will LLMs get us there? It's unclear. Could they, in the arid sense that there is some unknown collection of weights that would be capable of outputting tokens that simulate an OpenAI researcher working on novel tasks? Absolutely. (As to how to actually learn those weights, that's left as an exercise to the reader.)
I think the dynamism of the research program is relevant, though. Right now, you can, as an individual, decide to spend a quarter and a couple thousands in compute to research a particular area of LLMs and have a reasonable expectation of finding something interesting, and sometimes it's actually useful. This isn't merely hypothetical but is something happening every single day. There is a lot of low hanging fruit. Might there be some collection of a dozen different improvements on the horizon which, when taken collectively, would get us to AGI? Maybe. It's plausible, at least, while it's not plausible that a dozen different innovations are on the horizon that would enable a cheap base on Mars.
Why so confident? A 10 dimensional best fit line obviously won't work, nor will a vast fully connected neural net - so why should an LLM be capable?
I mean it in the sense that LLMs are capable of creating a token stream that is identical to an AI researcher. This is mathematically proven--see various universality theorems--but has the critical drawback that it doesn't really give you any information on how to find that optimal set of weights.
A MLP absolutely could also do this, or even some absurd polynomial best fit (not, however, a ten or quadrillion dimensional linear model). What MLPs offer over polynomials and transformers offer over MLPs is increased training efficiency and stability for actually finding those weights.
The universality theorems don't say that it's possible with any remotely practical number of weights, even aside from training time. But yes, I do grant that they say it is possible in theory.
To even achieve GPT2 performance with a basic, non-recurrent neural net, I would not be surprised if you need > # of atoms in the universe weights, which clearly isn't physically possible. (Ok, you can maybe theoretically have > 1 weight per atom, but s/atom/gluon, or just don't take me super literally on "atom".)
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I think that the main difference between a Mars base and AGI is that we have quite a good understanding of the physical constraints of a Mars base.
While SpaceX might have changed the economics of rockets by recycling them, the underlying physics and engineering constraints have been known since ca. 1950. We know what exhaust velocities we can reach, what the delta-v requirements for travelling to Mars are and so on. Absent black swans such as "someone invents a portal gun", we know that the way our constraints work out is very unfavorable, with rather small error bars.
For artificial intelligence, we very much have no underlying theory. We are Daedalus in a world where it turns out that you can craft wings from feathers and beewax which enable a human to fly. While some have been warning that we might get the Bad Ending if we soar to high, the truth in that analogy is that we have no comprehensive theory of heavier than air flight, aerodynamics, composition of the atmosphere and all that. In that world, asking if a man with wings can reach the moon is a question whose answer is purely an error bar, we just don't know. We notice the skulls of the Naysayers before us who had declared that feathers will not stop a man from falling, then that people can only glide downwards, then that sure, by flapping their wings a lot, they can gain a few meters, but surely not more than 50m, and are reasonably reluctant that to declare that the Moon is forever out of reach. On the other hand, in the real world, most straight lines can not be extrapolated indefinitely. So we just throw our hands up in the air and confess we don't know.
If you fly too close to the sun you'll be in for a bad day
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From my mostly layman/hobbyist's view of the tech, I agree that there's no good reason to believe that AGI, ASI, or even AI that can substitute for OpenAI's researchers strictly within the narrow use case of doing research/development/engineering/etc. that OpenAI wants to do are right around the corner. But where I disagree is that I don't think it's a question of fundamental possibility; rather, just like with a Mars base, I see it as a question of logistics, and I suspect that that disagreement is the source of your confusion.
Recent LLM tech has proven that we can create machines that produce text in response to text really really well, and I think getting to AGI or even ASI is just a matter of making a machine that produces text really really really well. My perception of the tech right now is that it's not progressing fast enough that we'll cross that threshold into AGI, for however we want to define it, any time soon. But I think one reasonable possibility is that I'm just ignorant of the details and most recent developments that people predicting otherwise are privy to, and those details could give them confidence that we're right around the corner from crossing that threshold.
I won't speculate on exactly what you think AGI or ASI is, but certainly many people believe that AGI requires something more than producing text really really really well, which I've seen lead to disagreements about how close we are to achieving it, or if it's achievable at all.
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