7 ms·

> Someday, such as in 2040, there may be available, for every human being, the performance equivalent of 'a B300 GPU for contemporary LLMs'. What would this wo

> Someday, such as in 2040, there may be available, for every human being, the performance equivalent of 'a B300 GPU for contemporary LLMs'. What would this world be like? If we talk about just LLMs, given how things have been going since ChatGPT, my bet it would not change that much. LLMs are not foundational technology such as Internet or Steam engine or Rail roads were. There are very few products that can build upon them because of reliability issues which are completely unresolvable for LLMs, chatbots is a decent product that came out of it, coding harnesses is another one, this is not even close to the impact Internet or Steam engine had. LLMs gave us nice productivity tools for highly motivated expert knowledge workers, that is all. LLMs are getting better and will get better, but it is impossible to describe the universe and compress it into few terabytes and that is what they are doing atm effectively, so all serious LLMs's issues will still be there in 2040: the lack on continues learning, hallucinations, terrible sample ratio, agent's failures on long horizon tasks, instruction following failures.

jstummbillig 16d ago
The thing that would change it a lot is that people would start trading away their GPUs, because some people would get vastly more economic use out of them.
- RajT88 16d ago
  This. Look at what happened when the government gave out free ATSC tuners for people with old TV's. eBay filled up with ATSC tuners. lol
pazimzadeh 16d ago
that's a lot of opinion without much reasoning/support even if you're right, all fields are progressing at the same time, including biology, and the synergies are going to be significant
dgellow 16d ago
Also, way more centralization, with all that logic pushed to a few AI vendors
setopt 16d ago
I disagree with this take. While LLMs themselves are currently unreliable, the work done in the math community on hooking up creative LLMs to reliable verifiers like Lean show that it’s possible to construct systems where the unreliability is suppressed. For now, that still requires experts to set up and monitor, but I do believe that in a couple of decades we’ll make progress on how to do more mundane tasks in a reliable way without expert supervision, where an LLM still sits as the translation layer between humans and machines. And that universal human-to-machine translator, I would certainly consider a foundational technology. EDIT: If you asked people on the street in 1990, they’d probably not consider the Internet to be in the same category as the Steam engine either. I mean, you already had phone and fax, so it wasn’t that ground breaking. And I’ve even read articles from the mid-90s declaring the Internet a temporary fad.
- alexpotato 15d ago
  > hooking up creative LLMs to reliable verifiers like Lean show that it’s possible to construct systems where the unreliability is suppressed. You can also have LLMs create these things called "programs" that are written in "code" that result in deterministic outputs when given inputs. I say this with a bit of snark to highlight the point that both humans and LLMs can write code that is cheaper to run and easy to verify. I'm not saying Lean being used like this is a bad idea, just that it's just one end of the spectrum.
- wjnc 16d ago
  I share this sentiment, while deploring the current AI board room sentiment. I know some people that design (safe) buildings. They use software all the time for their load-bearing work (lol). Think about the creativity that could be unleashed if that (like LEAN for math) becomes a commodity. The same thing for my job: creating insurance premiums is somewhat hard but not stellar. A combination of skills, data, tools and people. I can imagine a future where you can post a 'have good weather on holiday or money back' bond on a platform. (I can think of more serious applications...) The sheer diversity and amount of liquidity AI's can create is enormous. (Switching to a very general outlook here.) And with liquidity hopefully comes more specificity in the ROI on saving our planet. (Or the disproving of the necessity thereof, if that is your outlook.)
falcor84 16d ago
> it is impossible to describe the universe and compress it into few terabytes Why? I'm not an expert, but from my understanding, there say species that function well in their ecological niches with significantly smaller cognitive capacities. And we already have autonomous cars and drones navigate and function reasonably well. So I don't see any reason to believe it's impossible. And even if terabytes aren't sufficient, there's no real barrier to increasing capacity.
- maxnevermind 16d ago
  > there say species that function well in their ecological niches with significantly smaller cognitive capacities Yes, but LLMs are not animals, animals learn from experience and LLMs don't. Btw I meant bigger and bigger amount of data of extracted reasoning chains when you go deeper and generate more and more of them in your attempt to describe the universe, the amount of permutations explodes. And it seems LLMs can't workaround that because they don't build world model inside so they can't deduct it from pre-built world/object model, they must memorize it and look it up later.
  - pixl97 16d ago
    >but LLMs are not animals, animals learn from experience and LLMs don't. I mean they kind of do by distilling said experience and putting it in the next model. Current LLMs can't do it because building said world model is super expensive, anything that lowers that requirement brings us closer to continuous learning. Also the models we train these days are typically generalized human text models. Animal models are a bit different because they won't be "word" models and they aren't going to be generalized text models like us humans use. In fact there is a story just today on HN about a user creating some rather simple transformer models to solve a number of the Arc-AGI problems not using (human) words at all. The reason you don't see more of this is most people aren't dumping compute into these kinds of issues, but instead going for the AGI prize.
embedding-shape 16d ago
> LLMs gave us nice productivity tools for highly motivated expert knowledge workers, that is all. I feel like this is incredibly simplistic, and if you changed "LLM" to "computer" or "internet" and went back decades, it's highly likely you'd read the exact same takes in the newspaper back then about those things. It's also at the same time downplaying just how valuable "nice productivity tools for highly motivated expert knowledge workers" could be, just like computers did for us "highly motivated expert knowledge workers" in the first place. Or computers isn't a "foundational technology" either?
- maxnevermind 16d ago
  > I feel like this is incredibly simplistic, and if you changed "LLM" to "computer" or "internet" and went back decades, it's highly likely you'd read the exact same takes in the newspaper back then about those things. We are not people who write newspapers we are people who are directly involved in application of the technology, we posses a higher level of insight. > I feel like this is incredibly simplistic, and if you changed "LLM" to "computer" or "internet" and went back decades, it's highly likely you'd read the exact same takes in the newspaper back then about those things. Computers, the Internet, Steam engine, Rail roads are much more reliable. If you were a problem solver and entrepreneur you could go and apply those on small scale, get profits, reinvest, set up a flywheel, build a fortune on the top of those, there were a lot of low hanging fruit due to the fact that the foundation was laid out, a break-even period of James Watt steam engine was like 2-3 years I believe until everyone saw it and margins flattened. Can you do that with LLMs? It doesn't look that way.
  - embedding-shape 16d ago
    > We are not people who write newspapers we are people who are directly involved in application of the technology, we posses a higher level of insight. Cool, you're still a person who share their thoughts, just like the people who had similar reactions to when computers and the internet first came around. So many people were railing against the internet with "You'll never make payments over the internet", "it's too slow" and whatever. To the surprise of none of us nerds, the internet eventually ate the whole world and now large swaths of the population can't imagine life without it, for better or worse. > Computers, the Internet, Steam engine, Rail roads are much more reliable. You're comparing the reliability of huge ecosystems after they've gone mainstream, after decades, with something that is a couple of years old, hardly a fair comparison. Instead, compare where LLMs are today with the first years of computers, the internet and all that, and maybe you'll gain a new perspective on where LLMs are? None of those things were reliable initially and in many cases, involved actual human deaths before safety actually caught up. Even when I got started with using the internet, which isn't that long time ago but around the modem-era, things were not so reliable or simple as they are today.
roel_v 16d ago
This take is unfathomable to me. How are LLMs not massively revolutionary, despite them not being infallible? This comment reminds me of there being competitions for finding useful purposes for electricity when it was first discovered. Imagine talking about the usefulness of LLMs while thinking that LLMs in 2026 just compress a few TB of data into a set of weights and that's all they work with lol.
- entropy47 16d ago
  Whichever side of the divide you're on, I think it's really weird that on a site like HN (where people have at least a passing familiarity with technology) there are such polarised takes on whether it's the next industrial revolution, or a technological parlour trick. I'm giving away which side I'm on now, but most of the TAM have experienced the product at this point, and trillions of dollars have been invested. I would wager most other revolutionary technologies found their game changing, broad reaching applications by this point.
  - david-gpu 16d ago
    Did you experience the popularization of the WWW? There were massive disagreements even among smart tech-savvy people. We even had a stock market boom and just cycle associated with it. Funnily, none of that mattered. What mattered is that enough ordinary people on the street found it useful, both for personal and business reasons. Ask yourself: are regular people using this tech, either as producers or consumers? And remember that this is the least powerful that it will ever be.
    - maxnevermind 16d ago
      > Funnily, none of that mattered. What mattered is that enough ordinary people on the street found it useful, both for personal and business reasons. Broad economic impact due to Internet boom in the the US came from 2 main categories: 1) New huge internet enabled tech companies appeared(Amazon, Google, Meta etc.), all created their own products, all were build on reliable foundational technology. LLMs is not a reliable foundational technology. 2) Existing legacy companies could utilize internet to connect their teams/departments/offices though a bunch of new software which were build on reliable foundational technology. LLMs is not a reliable foundational technology. > And remember that this is the least powerful that it will ever be. This mantra is being repeated but "serious LLMs's issues" I described are still there and will be there because they are part of how LLMs are built and work. Without addressing those you can't build products but LLMs's capability as a personal productivity tool will keep rising, yes. The "best" possible outcome of LLMs to a broader economy might be that a smaller group of experts will be able to do the job in companies due to boost of their personal productivity and a bunch of people will be freed up(laid off) and they will have to go and work on something else and thus a boost of productivity in the economy. But it seems it won't be any low hanging fruits(problems to solve) this time as it was during the internet era. It is not like we out of problems: new cancer treatments, self driving cars, nuclear fusion, modular nuclear reactors etc. There is a huge value to capture there, here is the thing though, those are hard problems, it is not a new TikTok, gmail, netflix etc. Yes, people will have LLMs now but can we actually start solving hard problems with them? Because it might be the case that a gravy train of the last few decades for Silicon Valley is over, no more useless internet enabled services, no more billion dollar companies built on just applying internet to yet another thing and producing another digital product. People's free time is limited, its redistribution across digital services will not grow the economy, global internet penetration is already pretty high and won't grow that much, so there might not be much value to capture there.
onion2k 16d ago
agent's failures on long horizon tasks We've moved from LLMs being able to work on a task for about 2 minutes to about 2 hours in the last 18 months, and that's mostly limited by the context window size filling up. In 14 years time I don't really see a reason why that wouldn't have extended a time frame that's effectively continuous forever, or at least a ceiling that's indistinguishable from that. The question really becomes "why would we want that?". The main reason you'd want an AI that can focus on a task forever is to completely remove the human from the loop. That's something we should be cautious about.
- bbmatryoshka 16d ago
  2 hours... of agent work, usually for the same output the average worker has to use much more time
  - knollimar 16d ago
    Throw understanding images in there and it becomes less true in my experience. Sure they shit out code and search text well, but one infographic and they circle trying to rasterize it.
- FinnKuhn 16d ago
  I do not think agents need to work continuously. They "just" need to work on a project longer than an employee is able to work on it for them to be commercially useful. Although this does not consider that agents might take a shorter or longer amount of time for the same task. Therefore, we should begin to compare these in tasks completed during that time instead.
  - onion2k 16d ago
    Not sure about that. The nature of work changes if you have some[one|thing] that can work on it continuously forever. The goal of using AI shouldn't be to do the things a person does; it should be to do the things a person would be able to do if they had (practically) unlimited time. This is one of the inflection points around working with AI. When your thinking shifts from "AI does what the person used to do" to "AI does something different that leads to the same outcome as before, but with all that cool stuff I'd love to have the time for", then the equation changes. For example, I will never write another app that doesn't have 100% test coverage again. I stress- and soak-test everything these days. That's changing how I write code - I need to write things in ways that have deterministic harnesses for things mutable state outside of my immediate control (like random numbers or datetimes or state loaded from a save) so that I can task AI with building a fuzzer that does tens of thousands of random tests on every push to see if anything broke. I couldn't do that in the past because it was always effort that a client wouldn't get enough value from to pay me to do it. I can do those things now. It's ace. (Everywhere I put 'I' you can replace with 'AI of the Week')
smusamashah 16d ago
Computers were made and automated lots of work, even though it was still us operating those computers and making and running those automations. But eventually computers took over and running so much of the world. Now LLMs are automating the computers themselves. This is a whole new layer that we never had before, not in this amount or with this much availability. It is not "not foundational".
holoduke 16d ago
Absolutely untrue. LLM will be the automation force of everything. It will connect and orchestrate our entire society. It will be a much bigger impact that any other revolution in the past. Our lives will be unrecognizable in 10 years from now.
- lacedeconstruct 16d ago
  In 10 years from now we will have another AI winter until a new thing arrives that pushes further.
lukan 16d ago
"If we talk about just LLMs" In general we don't, as the "chatbots" already have way more capability than "just" being able to work with text, which "just" means encoding and processing real world information and lot's of it. For example I just fixed the gearing of my bicycle by dropping some pictures into claude and it gave me a step by step guide to fix it. "LLMs gave us nice productivity tools for highly motivated expert knowledge workers, that is all" And I cannot understand how that can be "all" as it means giving this power to every human, not just the few in the position to hire expert knowledge workers. Steam engines gave us the capability to let machines do the hard labour. Now with better engines and tools, AI will give robots the capability to do allmost anything humans can do. If that is not revolutionary then I don't know what is. The main reason we humans got to the top of the food chain was because we are expert knowledge workers, able to transform the world around us to our needs. "but it is impossible to describe the universe and compress it into few terabytes and that is what they are doing atm effectively, so all serious LLMs's issues will still be there in 2040: the lack on continues learning, hallucinations, terrible sample ratio, agent's failures on long horizon tasks, instruction following failures." So again, just limiting this debate to a simple fixed model - then no, not too useful - but a model that can take notes and at some point reliable clear up it's context - that is a whole different story. And it has been repeated often enough, but AI does not need to be perfect - it just has to be as or more reliable than us humans. Because yes - AI does make misstakes - but so do humans.
bsenftner 16d ago
Wow, you really do not understand them. The 'problem' with LLM AI is the weak educations of the people that cannot grasp their subtle multidimensional nature, and how that creates a requirement on the users' behalf to understand the language they use to communicate in a similar manner as numbers are to algebra. LLM AIs are literally literature calculus but that truthful phrase flies right over the majority's heads.
ajjahs 16d ago
[dead]

jstummbillig 16d ago

The thing that would change it a lot is that people would start trading away their GPUs, because some people would get vastly more economic use out of them.

RajT88 16d ago
This. Look at what happened when the government gave out free ATSC tuners for people with old TV's. eBay filled up with ATSC tuners. lol

pazimzadeh 16d ago

that's a lot of opinion without much reasoning/support even if you're right, all fields are progressing at the same time, including biology, and the synergies are going to be significant

dgellow 16d ago

Also, way more centralization, with all that logic pushed to a few AI vendors

setopt 16d ago

I disagree with this take. While LLMs themselves are currently unreliable, the work done in the math community on hooking up creative LLMs to reliable verifiers like Lean show that it’s possible to construct systems where the unreliability is suppressed. For now, that still requires experts to set up and monitor, but I do believe that in a couple of decades we’ll make progress on how to do more mundane tasks in a reliable way without expert supervision, where an LLM still sits as the translation layer between humans and machines. And that universal human-to-machine translator, I would certainly consider a foundational technology. EDIT: If you asked people on the street in 1990, they’d probably not consider the Internet to be in the same category as the Steam engine either. I mean, you already had phone and fax, so it wasn’t that ground breaking. And I’ve even read articles from the mid-90s declaring the Internet a temporary fad.

alexpotato 15d ago
> hooking up creative LLMs to reliable verifiers like Lean show that it’s possible to construct systems where the unreliability is suppressed. You can also have LLMs create these things called "programs" that are written in "code" that result in deterministic outputs when given inputs. I say this with a bit of snark to highlight the point that both humans and LLMs can write code that is cheaper to run and easy to verify. I'm not saying Lean being used like this is a bad idea, just that it's just one end of the spectrum.
wjnc 16d ago
I share this sentiment, while deploring the current AI board room sentiment. I know some people that design (safe) buildings. They use software all the time for their load-bearing work (lol). Think about the creativity that could be unleashed if that (like LEAN for math) becomes a commodity. The same thing for my job: creating insurance premiums is somewhat hard but not stellar. A combination of skills, data, tools and people. I can imagine a future where you can post a 'have good weather on holiday or money back' bond on a platform. (I can think of more serious applications...) The sheer diversity and amount of liquidity AI's can create is enormous. (Switching to a very general outlook here.) And with liquidity hopefully comes more specificity in the ROI on saving our planet. (Or the disproving of the necessity thereof, if that is your outlook.)

falcor84 16d ago

> it is impossible to describe the universe and compress it into few terabytes Why? I'm not an expert, but from my understanding, there say species that function well in their ecological niches with significantly smaller cognitive capacities. And we already have autonomous cars and drones navigate and function reasonably well. So I don't see any reason to believe it's impossible. And even if terabytes aren't sufficient, there's no real barrier to increasing capacity.

maxnevermind 16d ago
> there say species that function well in their ecological niches with significantly smaller cognitive capacities Yes, but LLMs are not animals, animals learn from experience and LLMs don't. Btw I meant bigger and bigger amount of data of extracted reasoning chains when you go deeper and generate more and more of them in your attempt to describe the universe, the amount of permutations explodes. And it seems LLMs can't workaround that because they don't build world model inside so they can't deduct it from pre-built world/object model, they must memorize it and look it up later.
- pixl97 16d ago
  >but LLMs are not animals, animals learn from experience and LLMs don't. I mean they kind of do by distilling said experience and putting it in the next model. Current LLMs can't do it because building said world model is super expensive, anything that lowers that requirement brings us closer to continuous learning. Also the models we train these days are typically generalized human text models. Animal models are a bit different because they won't be "word" models and they aren't going to be generalized text models like us humans use. In fact there is a story just today on HN about a user creating some rather simple transformer models to solve a number of the Arc-AGI problems not using (human) words at all. The reason you don't see more of this is most people aren't dumping compute into these kinds of issues, but instead going for the AGI prize.

embedding-shape 16d ago

> LLMs gave us nice productivity tools for highly motivated expert knowledge workers, that is all. I feel like this is incredibly simplistic, and if you changed "LLM" to "computer" or "internet" and went back decades, it's highly likely you'd read the exact same takes in the newspaper back then about those things. It's also at the same time downplaying just how valuable "nice productivity tools for highly motivated expert knowledge workers" could be, just like computers did for us "highly motivated expert knowledge workers" in the first place. Or computers isn't a "foundational technology" either?

maxnevermind 16d ago
> I feel like this is incredibly simplistic, and if you changed "LLM" to "computer" or "internet" and went back decades, it's highly likely you'd read the exact same takes in the newspaper back then about those things. We are not people who write newspapers we are people who are directly involved in application of the technology, we posses a higher level of insight. > I feel like this is incredibly simplistic, and if you changed "LLM" to "computer" or "internet" and went back decades, it's highly likely you'd read the exact same takes in the newspaper back then about those things. Computers, the Internet, Steam engine, Rail roads are much more reliable. If you were a problem solver and entrepreneur you could go and apply those on small scale, get profits, reinvest, set up a flywheel, build a fortune on the top of those, there were a lot of low hanging fruit due to the fact that the foundation was laid out, a break-even period of James Watt steam engine was like 2-3 years I believe until everyone saw it and margins flattened. Can you do that with LLMs? It doesn't look that way.
- embedding-shape 16d ago
  > We are not people who write newspapers we are people who are directly involved in application of the technology, we posses a higher level of insight. Cool, you're still a person who share their thoughts, just like the people who had similar reactions to when computers and the internet first came around. So many people were railing against the internet with "You'll never make payments over the internet", "it's too slow" and whatever. To the surprise of none of us nerds, the internet eventually ate the whole world and now large swaths of the population can't imagine life without it, for better or worse. > Computers, the Internet, Steam engine, Rail roads are much more reliable. You're comparing the reliability of huge ecosystems after they've gone mainstream, after decades, with something that is a couple of years old, hardly a fair comparison. Instead, compare where LLMs are today with the first years of computers, the internet and all that, and maybe you'll gain a new perspective on where LLMs are? None of those things were reliable initially and in many cases, involved actual human deaths before safety actually caught up. Even when I got started with using the internet, which isn't that long time ago but around the modem-era, things were not so reliable or simple as they are today.

roel_v 16d ago

This take is unfathomable to me. How are LLMs not massively revolutionary, despite them not being infallible? This comment reminds me of there being competitions for finding useful purposes for electricity when it was first discovered. Imagine talking about the usefulness of LLMs while thinking that LLMs in 2026 just compress a few TB of data into a set of weights and that's all they work with lol.

entropy47 16d ago
Whichever side of the divide you're on, I think it's really weird that on a site like HN (where people have at least a passing familiarity with technology) there are such polarised takes on whether it's the next industrial revolution, or a technological parlour trick. I'm giving away which side I'm on now, but most of the TAM have experienced the product at this point, and trillions of dollars have been invested. I would wager most other revolutionary technologies found their game changing, broad reaching applications by this point.
- david-gpu 16d ago
  Did you experience the popularization of the WWW? There were massive disagreements even among smart tech-savvy people. We even had a stock market boom and just cycle associated with it. Funnily, none of that mattered. What mattered is that enough ordinary people on the street found it useful, both for personal and business reasons. Ask yourself: are regular people using this tech, either as producers or consumers? And remember that this is the least powerful that it will ever be.
  - maxnevermind 16d ago
    > Funnily, none of that mattered. What mattered is that enough ordinary people on the street found it useful, both for personal and business reasons. Broad economic impact due to Internet boom in the the US came from 2 main categories: 1) New huge internet enabled tech companies appeared(Amazon, Google, Meta etc.), all created their own products, all were build on reliable foundational technology. LLMs is not a reliable foundational technology. 2) Existing legacy companies could utilize internet to connect their teams/departments/offices though a bunch of new software which were build on reliable foundational technology. LLMs is not a reliable foundational technology. > And remember that this is the least powerful that it will ever be. This mantra is being repeated but "serious LLMs's issues" I described are still there and will be there because they are part of how LLMs are built and work. Without addressing those you can't build products but LLMs's capability as a personal productivity tool will keep rising, yes. The "best" possible outcome of LLMs to a broader economy might be that a smaller group of experts will be able to do the job in companies due to boost of their personal productivity and a bunch of people will be freed up(laid off) and they will have to go and work on something else and thus a boost of productivity in the economy. But it seems it won't be any low hanging fruits(problems to solve) this time as it was during the internet era. It is not like we out of problems: new cancer treatments, self driving cars, nuclear fusion, modular nuclear reactors etc. There is a huge value to capture there, here is the thing though, those are hard problems, it is not a new TikTok, gmail, netflix etc. Yes, people will have LLMs now but can we actually start solving hard problems with them? Because it might be the case that a gravy train of the last few decades for Silicon Valley is over, no more useless internet enabled services, no more billion dollar companies built on just applying internet to yet another thing and producing another digital product. People's free time is limited, its redistribution across digital services will not grow the economy, global internet penetration is already pretty high and won't grow that much, so there might not be much value to capture there.

onion2k 16d ago

agent's failures on long horizon tasks We've moved from LLMs being able to work on a task for about 2 minutes to about 2 hours in the last 18 months, and that's mostly limited by the context window size filling up. In 14 years time I don't really see a reason why that wouldn't have extended a time frame that's effectively continuous forever, or at least a ceiling that's indistinguishable from that. The question really becomes "why would we want that?". The main reason you'd want an AI that can focus on a task forever is to completely remove the human from the loop. That's something we should be cautious about.

bbmatryoshka 16d ago
2 hours... of agent work, usually for the same output the average worker has to use much more time
- knollimar 16d ago
  Throw understanding images in there and it becomes less true in my experience. Sure they shit out code and search text well, but one infographic and they circle trying to rasterize it.
FinnKuhn 16d ago
I do not think agents need to work continuously. They "just" need to work on a project longer than an employee is able to work on it for them to be commercially useful. Although this does not consider that agents might take a shorter or longer amount of time for the same task. Therefore, we should begin to compare these in tasks completed during that time instead.
- onion2k 16d ago
  Not sure about that. The nature of work changes if you have some[one|thing] that can work on it continuously forever. The goal of using AI shouldn't be to do the things a person does; it should be to do the things a person would be able to do if they had (practically) unlimited time. This is one of the inflection points around working with AI. When your thinking shifts from "AI does what the person used to do" to "AI does something different that leads to the same outcome as before, but with all that cool stuff I'd love to have the time for", then the equation changes. For example, I will never write another app that doesn't have 100% test coverage again. I stress- and soak-test everything these days. That's changing how I write code - I need to write things in ways that have deterministic harnesses for things mutable state outside of my immediate control (like random numbers or datetimes or state loaded from a save) so that I can task AI with building a fuzzer that does tens of thousands of random tests on every push to see if anything broke. I couldn't do that in the past because it was always effort that a client wouldn't get enough value from to pay me to do it. I can do those things now. It's ace. (Everywhere I put 'I' you can replace with 'AI of the Week')

smusamashah 16d ago

Computers were made and automated lots of work, even though it was still us operating those computers and making and running those automations. But eventually computers took over and running so much of the world. Now LLMs are automating the computers themselves. This is a whole new layer that we never had before, not in this amount or with this much availability. It is not "not foundational".

holoduke 16d ago

Absolutely untrue. LLM will be the automation force of everything. It will connect and orchestrate our entire society. It will be a much bigger impact that any other revolution in the past. Our lives will be unrecognizable in 10 years from now.

lacedeconstruct 16d ago
In 10 years from now we will have another AI winter until a new thing arrives that pushes further.

lukan 16d ago

"If we talk about just LLMs" In general we don't, as the "chatbots" already have way more capability than "just" being able to work with text, which "just" means encoding and processing real world information and lot's of it. For example I just fixed the gearing of my bicycle by dropping some pictures into claude and it gave me a step by step guide to fix it. "LLMs gave us nice productivity tools for highly motivated expert knowledge workers, that is all" And I cannot understand how that can be "all" as it means giving this power to every human, not just the few in the position to hire expert knowledge workers. Steam engines gave us the capability to let machines do the hard labour. Now with better engines and tools, AI will give robots the capability to do allmost anything humans can do. If that is not revolutionary then I don't know what is. The main reason we humans got to the top of the food chain was because we are expert knowledge workers, able to transform the world around us to our needs. "but it is impossible to describe the universe and compress it into few terabytes and that is what they are doing atm effectively, so all serious LLMs's issues will still be there in 2040: the lack on continues learning, hallucinations, terrible sample ratio, agent's failures on long horizon tasks, instruction following failures." So again, just limiting this debate to a simple fixed model - then no, not too useful - but a model that can take notes and at some point reliable clear up it's context - that is a whole different story. And it has been repeated often enough, but AI does not need to be perfect - it just has to be as or more reliable than us humans. Because yes - AI does make misstakes - but so do humans.

bsenftner 16d ago

Wow, you really do not understand them. The 'problem' with LLM AI is the weak educations of the people that cannot grasp their subtle multidimensional nature, and how that creates a requirement on the users' behalf to understand the language they use to communicate in a similar manner as numbers are to algebra. LLM AIs are literally literature calculus but that truthful phrase flies right over the majority's heads.

ajjahs 16d ago

[dead]