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I disagree. Crypto people kept suggesting that crypto was a solution to an X problem while ignoring that a database was a better solution the problem. I’ve yet

I disagree. Crypto people kept suggesting that crypto was a solution to an X problem while ignoring that a database was a better solution the problem. I’ve yet to hear any good use cases for crypto, and I’ve been asking for years on here. Meanwhile there are a bunch of AI tools out there that are working and helping.

bayindirh 2y ago
AI is a gigantic landscape with tons of different applications to different problems, and there are many solutions which work for a given problem. However, if we narrow what AI is to LLMs, we have a stochastic parrot which needs to be fed the world literally to enable it to create semi-coherent sentences about something being asked. More importantly, what that parrot says doesn't have to be true, it can't be guaranteed to be true, and can't be verified about its accuracy about its slop. And you spend gigawatts of power just to train this thing which selects and prints words based on probability and some randomness. That doesn't solve any problems.
- maccard 2y ago
  You've moved the goalposts from AI to LLM's. Fair enough, we've been doing AI since the 50's, and this is the second AI boom in a decade. Those "stochastic parrots" have still proven that they are immensely useful. You might not personally find value out of coding assistants, but many many people do (as an example). People are (allegedly) turning to LLM's rather than StackOverflow for help [0]. They work well for boilerplate where you're an SME and able to validate the output - I can review 10x the amount of code I can write for example. They work (remarkably) well for summarising input text. An example - I semi occasionally (3-4x per year) have to deal with a few hundred GB of audio files that need cleanup. The cleanup tasks are "run FFMPEG with parameters", except I can not ever remember the parameters (they're different for different things). I can: read https://ffmpeg.org/ffmpeg.html https://ffmpeg.org/ffmpeg.html or I can ask ChatGPT to write a script to clip the silence and add a 0.5 second intro fade to every file in a specified folder, and the entire task is done before I've even thought about it. I get to focus on what I want to, rather than munging data around. If you expand your definition from LLMs to Transformers, then you get Whisper as a stand out example of something awesome. There's definitely negatives, but things like Diffusion are being used outside of image generation for drug discovery. We're not going to yolo AI generated drugs into human testing, but we can save an awful lot of screwing around to find something viable. > And you spend gigawatts of power just to train this thing which selects and prints words based on probability and some randomness. > That doesn't solve any problems. I disagree, it does solve problems. A very fair question to ask is "is it worth the cost" and I would agree that it's not worth the cost. That doesn't mean it doesn't solve real problems. [0] https://meta.stackexchange.com/questions/387278/has-stack-exchanges-traffic-decreased-since-chatgpt https://meta.stackexchange.com/questions/387278/has-stack-ex...
- lukeschlather 2y ago
  I think it's premature to be integrating LLMs into operating systems. That said I think they're very valuable, and the training is fundamental research. I feel like complaining about the resources used to train new models is a bit like complaining about the resources used to build experimental fusion reactors or particle accelerators. The fact that we're seeing direct applications is a bonus, but it's still more like fundamental research than anything. People are spending all that money training because they are trying to fix the problems you're complaining about, and this includes fixing the power consumption problem. If we can create 3B parameter models that have capabilities on par with today's 405B parameter models, that's worth spending a lot of energy training. But nobody knows what is possible, so they have to try. I feel like you're basically arguing nobody should try because you don't believe they will ever improve, but that seems contradicted by the general trajectory of how things have been working the past decade. More resources spent on training means more efficient and useful models.
dns_snek 2y ago
> Crypto people kept suggesting that crypto was a solution to an X problem while ignoring that a database was a better solution the problem. Only if you ignore the fact that a database (in traditional sense) doesn't solve the problem of decentralized peer to peer payments, which is the key differentiator of cryptocurrencies. > I’ve yet to hear any good use cases for crypto, and I’ve been asking for years on here. If you've been asking for years, I'm sure that someone, at some point, has told you about crypto's censorship resistance and international payments in places that are poorly served by the banking system for a variety of reasons. Would you like to hear more or have you already dismissed these as "not good use cases"? It would be nice to differentiate between use cases that don't apply to you personally, and use cases that don't apply to anyone.
- maccard 2y ago
  > Only if you ignore the fact that a database (in traditional sense) doesn't solve the problem of decentralized peer to peer payments, which is the key differentiator of cryptocurrencies. And the point that the useful cases cede to make a useful product. The thing that is a _feature_ of a cryptocurrency is why people don't use it. I've had this debate dozens of times on here. > If you've been asking for years, I'm sure that someone, at some point, has told you about crypto's censorship resistance and international payments in places that are poorly served by the banking system for a variety of reasons. You know what else solves that? Cash and Western Union. And it has done for a long, long time.
  - dns_snek 2y ago
    > The thing that is a _feature_ of a cryptocurrency is why people don't use it. People do, in fact, use them. Is it a popular payment method in western countries? No, but do some people use it? Yes, they do. For privileged people, decentralization is usually a serious flaw. For others, it's an extremely important characteristic that lets them transact at all. The world isn't black and white, and people have use cases that are different from yours. You're being self-centered, and that's okay, but perhaps you should factor it into your mental model before making sweeping statements in front of a global audience. > You know what else solves that? Cash and Western Union. And it has done for a long, long time. Not nearly as well, or there wouldn't be anyone using cryptocurrencies for that purpose. You could make identical boring, bad-faith arguments about AI products. I think 99.99% of all "AI" products available today are completely useless - to me - but I don't go around proclaiming that all of AI is completely useless, and that all of its problem areas are better solved by statistics and "if" statements. Don't mistake your own privilege, ignorance, and lack of imagination with the lack of real-world applications.

bayindirh 2y ago

AI is a gigantic landscape with tons of different applications to different problems, and there are many solutions which work for a given problem. However, if we narrow what AI is to LLMs, we have a stochastic parrot which needs to be fed the world literally to enable it to create semi-coherent sentences about something being asked. More importantly, what that parrot says doesn't have to be true, it can't be guaranteed to be true, and can't be verified about its accuracy about its slop. And you spend gigawatts of power just to train this thing which selects and prints words based on probability and some randomness. That doesn't solve any problems.

maccard 2y ago
You've moved the goalposts from AI to LLM's. Fair enough, we've been doing AI since the 50's, and this is the second AI boom in a decade. Those "stochastic parrots" have still proven that they are immensely useful. You might not personally find value out of coding assistants, but many many people do (as an example). People are (allegedly) turning to LLM's rather than StackOverflow for help [0]. They work well for boilerplate where you're an SME and able to validate the output - I can review 10x the amount of code I can write for example. They work (remarkably) well for summarising input text. An example - I semi occasionally (3-4x per year) have to deal with a few hundred GB of audio files that need cleanup. The cleanup tasks are "run FFMPEG with parameters", except I can not ever remember the parameters (they're different for different things). I can: read https://ffmpeg.org/ffmpeg.html https://ffmpeg.org/ffmpeg.html or I can ask ChatGPT to write a script to clip the silence and add a 0.5 second intro fade to every file in a specified folder, and the entire task is done before I've even thought about it. I get to focus on what I want to, rather than munging data around. If you expand your definition from LLMs to Transformers, then you get Whisper as a stand out example of something awesome. There's definitely negatives, but things like Diffusion are being used outside of image generation for drug discovery. We're not going to yolo AI generated drugs into human testing, but we can save an awful lot of screwing around to find something viable. > And you spend gigawatts of power just to train this thing which selects and prints words based on probability and some randomness. > That doesn't solve any problems. I disagree, it does solve problems. A very fair question to ask is "is it worth the cost" and I would agree that it's not worth the cost. That doesn't mean it doesn't solve real problems. [0] https://meta.stackexchange.com/questions/387278/has-stack-exchanges-traffic-decreased-since-chatgpt https://meta.stackexchange.com/questions/387278/has-stack-ex...
lukeschlather 2y ago
I think it's premature to be integrating LLMs into operating systems. That said I think they're very valuable, and the training is fundamental research. I feel like complaining about the resources used to train new models is a bit like complaining about the resources used to build experimental fusion reactors or particle accelerators. The fact that we're seeing direct applications is a bonus, but it's still more like fundamental research than anything. People are spending all that money training because they are trying to fix the problems you're complaining about, and this includes fixing the power consumption problem. If we can create 3B parameter models that have capabilities on par with today's 405B parameter models, that's worth spending a lot of energy training. But nobody knows what is possible, so they have to try. I feel like you're basically arguing nobody should try because you don't believe they will ever improve, but that seems contradicted by the general trajectory of how things have been working the past decade. More resources spent on training means more efficient and useful models.

dns_snek 2y ago

> Crypto people kept suggesting that crypto was a solution to an X problem while ignoring that a database was a better solution the problem. Only if you ignore the fact that a database (in traditional sense) doesn't solve the problem of decentralized peer to peer payments, which is the key differentiator of cryptocurrencies. > I’ve yet to hear any good use cases for crypto, and I’ve been asking for years on here. If you've been asking for years, I'm sure that someone, at some point, has told you about crypto's censorship resistance and international payments in places that are poorly served by the banking system for a variety of reasons. Would you like to hear more or have you already dismissed these as "not good use cases"? It would be nice to differentiate between use cases that don't apply to you personally, and use cases that don't apply to anyone.

maccard 2y ago
> Only if you ignore the fact that a database (in traditional sense) doesn't solve the problem of decentralized peer to peer payments, which is the key differentiator of cryptocurrencies. And the point that the useful cases cede to make a useful product. The thing that is a _feature_ of a cryptocurrency is why people don't use it. I've had this debate dozens of times on here. > If you've been asking for years, I'm sure that someone, at some point, has told you about crypto's censorship resistance and international payments in places that are poorly served by the banking system for a variety of reasons. You know what else solves that? Cash and Western Union. And it has done for a long, long time.
- dns_snek 2y ago
  > The thing that is a _feature_ of a cryptocurrency is why people don't use it. People do, in fact, use them. Is it a popular payment method in western countries? No, but do some people use it? Yes, they do. For privileged people, decentralization is usually a serious flaw. For others, it's an extremely important characteristic that lets them transact at all. The world isn't black and white, and people have use cases that are different from yours. You're being self-centered, and that's okay, but perhaps you should factor it into your mental model before making sweeping statements in front of a global audience. > You know what else solves that? Cash and Western Union. And it has done for a long, long time. Not nearly as well, or there wouldn't be anyone using cryptocurrencies for that purpose. You could make identical boring, bad-faith arguments about AI products. I think 99.99% of all "AI" products available today are completely useless - to me - but I don't go around proclaiming that all of AI is completely useless, and that all of its problem areas are better solved by statistics and "if" statements. Don't mistake your own privilege, ignorance, and lack of imagination with the lack of real-world applications.