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'Overhyped' generative AI will get a 'cold shower' in 2024, analysts predict

19 points by kylebenzle 3y ago

kylebenzle 3y ago
CCS Insight predicts a reality check for generative AI in 2024 due to increasing costs and complexity. The hype around this technology is expected to be replaced by a more sober understanding of the challenges it presents, particularly for smaller developers. Additionally, AI regulation in the EU is predicted to stall due to rapid technological advances
- paulddraper 3y ago
  That hasn't been my perception
- DesertVarnish 3y ago
  They really aren't the same. Crypto didn't and still doesn't have the same immediate utility. The value proposition just wasn't there to justify the money and attention it was getting. Bitcoin in particular was a prototype that got mythologized into being "digital gold" despite it's many, many technical limitations. Diffusion models and LLMs work today and make possible things that were science fiction five years ago, and have shown tremendous and exciting progress in the past 18 months.
  - ok_dad 3y ago
    Your last paragraph is the hype. I haven’t seen any effective uses of the current AI tech that couldn’t have been done for the same cost by humans so far. Images, text, code; I haven’t seen anything but toys built yet. The coding tools might work okay for your average HTTP API, but it’s not going to develop novel algorithms to control building HVAC systems to reduce energy or demand, for example. It’s not going to code much more efficient search algorithms, or faster compression. Maybe someday, but so far everything produced by AI seems to have huge problems, whether it be drawing realistic hands, knowing the factual truth of certain questions, or introducing subtle bugs in complex code.
    - Charon77 3y ago
      How about alphafold? Prior usage requires quite literally weeks to months on supercomputers with results often not so comparable with the X ray crystallography. Or the use of AI for real time upscaling that can be done in real time on low to medium GPU. I think you only see chat gpt which don have its own draw back, but AI does not equal gpt, does not even has to be generative.
      - ok_dad 3y ago
        Alphafold: there are lots of caveats, from my limited understanding so far the “thing“ it does isn’t a limiting factor for speeding up drug development. Video cards: I don’t know much about them, it seems impressive but I’m not sold it’s the future of gaming yet; also they’re expensive as Fuck I am not saying this stuff will never be useful, but we’re at the peak of the hype cycle today, and I expect many, many of the supposed breakthroughs turn out to be a dead end or harder to make reliable than expected. Or, way more expensive than financially viable for that problem. I hope I’m wrong, tech wise, because it would be amazing to reduce the needed human work output, but also I’m not sold that our society can survive if AI takes over jobs, so that’s another reason that I’m bullish.
      - AraceliHarker 3y ago
        Although AI has various variations, the recent AI boom is referring to what is called generative AI such as ChatGPT.
    - tomohelix 3y ago
      That is because you are comparing it to the cost of a professional. I personally look at it in a different way. Now, a rando on the street knowing nothing about everything can pop out arts rivaling an experienced illustrator. A completely clueless wet lab scientist can coerce copilot or GPT4 to cobble together an automated data analysis pipeline in a language that they know nothing about. To a professional, those applications are toys, easily made and take little effort. But to someone who does not know anything about the work, it is amazingly useful and open up many possibilities. That is the power and the use cases for AI right now. They are tools to augment productivity, not replacing it. And in that regard, it is very successful imo. Whether it will progress to the point where it can outright handle everything from start to finish or not is another question.
- deleted 3y ago
  [deleted]
deleted 3y ago
[deleted]
futureamish 3y ago
[flagged]
nabla9 3y ago
One of the best uses of generative AI is Gihub Copilot. Microsoft loses $20 per month for each Github Copilot user. Copilot should cost $40 - $50 per month to cover the cost of running it.
- wokwokwok 3y ago
  Yeah, this. The tech is great, but it’s expensive to run, and it’s being given away basically for free at the moment. …and hey, free stuff is great. Enjoy it while you can! At some point, however, companies have to stop giving things away for free (or at a loss); it’s just a matter of what that looks like under sustainable pricing.
  - Closi 3y ago
    Subsidise now, profit later. If you have the cash, it’s probably better to burn some getting early user adoption if you believe the cost base will reduce in the future. Inference costs are dropping fast, so you might as well subsidise now and get market share if you think future costs will drop below future revenue. User aquisition will be much harder later when you lose first mover advantage.
- 5350-uiop-1130 3y ago
  "pay us $40 - $50 a month to train your future replacement"
faeriechangling 3y ago
Overhyped how? Overhyped like self-driving, in terms of the timelines? Or overhyped in terms of the eventual societal impact? I think people seriously underestimate how much of a struggle driving down the cost of compute/$ is going to be. Every incremental gain in memory and microprocessors is getting exponentially more expensive to develop. This is also a (relatively) high interest rate environment which do not tend to favour long term speculative investments. A lot of people aren't fully aware of how OpenAI and GitHub CoPilot are bleeding red ink from the get-go. I honestly feel like people are really sleeping on the potential still. Most people I know tried it a few times around last Christmas and got bored with it and quit but I never stopped using it.
- brucethemoose2 3y ago
  > struggle driving down the cost of compute/$ Actually I feel that utilization of existing hardware is very poor. For instance, in LLM land, continuous batching is a thing that just starting to proliferate (at least in open source). Many are still doing training/inference in vanilla pipes in PyTorch eager mode, without even a simple `torch.compile` or aggressive quantization, much less a more advanced ML compiler. Architecture optimizations beyond llama's base architecture (like newer attention schemes used during training) are not really picked up yet. I can go on and on, and go on about Stable Diffusion as well, but what I am saying is there is tons of unpicked low hanging fruit, that's unexploited because... everyone is in a rush to just publish or deploy something, I guess? Also, Nvidia's margins are insane. The voltage/clock band they run in is insanely inefficient. I hope that is not sustainable, because sane margins/clocks with no code/hardware advancement would bring costs down a ton.
  - npsomaratna 3y ago
    Can you explain more about the voltage/clock band please? Do you mean that they are very energy inefficient?
    - brucethemoose2 3y ago
      Yes. Basically, power usage increases quadradicaly with clockspeed. Running a little faster takes a lot more power. Nvidia runs GPUs smaller than an Apple M1 Ultra at 250-450W. Thats crazy for a single chip! They could sacrifice a tiny bit of performance and run with much less power... But they don't. The Cerebras CS2, for reference, has a much lower power density and runs more efficiently. Unfortunately most other AI hardware is pretty hotly clocked at the moment.
tomohelix 3y ago
Well, this was already pointed out a long time ago during the peak hype of AI earlier this year. Something about we overhype the effect of the technology in the short term and underestimate the impact long term. One thing that is undeniable is that AIs have actual productive use cases. Some of the previous fads did not actually have any major real applications even years after its introduction. Meanwhile, AI technology, specifically the transformer tech, has already revolutionized biotech, art, and NLP fields. Even if all progress on AI hit a stop today, people will still use alphafold, diffusion, and chatgpt for their intended purposes. So I am sure we can agree that AI isn't going down the road of things like NFT or bitcoins. Next few years would be the optimization and mass adoption steps. Big tech companies are probably plucking all the low hanging fruit already. The hard parts are probably what make it more useful, i.e. cheaper and in a format that can be used easily. Those take time, but 15 years ago, I would be dreaming if I think I can play Crysis on a handheld device. Now I can for a measly $400. So in the next 10 years, it isn't impossible to have something on the level of chatgpt running in real time on something like a phone or smartglass. And that is discounting the possibility of any major breakthrough or genius application like the GUI to computer interface or the iphone to personal computer. Something like that can pop up and change the world as we know it.
- az09mugen 3y ago
  One other thing is worth mentioning, is also the negative impact of AI to take into account. It helps everything to get done easier, but it includes good things and bad things. Did you see AI is also trained to make pentests ? Or create malwares ? Or a model with almost no restrictions is released in the wild (Mistral) ? Or any other bad stuff I can't imagine ? Do people even imagine how it can become easy to do evil things ? No, because they're overhyped by AI. Not everyone, but still.
AraceliHarker 3y ago
In the end, it's the same story as automating warehouse delivery, where it turns out that it's actually cheaper to have humans do it. AI is no different. Moreover, the recent restrictions on AI-generated content have caused inconveniences even in ordinary use that is not socially harmful, and expectations for AI have been greatly damaged.
patrickhogan1 3y ago
Says the analyst who will be replaced by ChatGPT in 2024.
singularity2001 3y ago
Given the results of the latest midjourney version I feel it's even underhyped: https://reddit.com/r/midjourney/s/ODnwsKazlo https://reddit.com/r/midjourney/s/ODnwsKazlo I don't know about the valley but where I am people are unexcited about AI, when they should be

19 points by kylebenzle 3y ago

CCS Insight predicts a reality check for generative AI in 2024 due to increasing costs and complexity. The hype around this technology is expected to be replaced by a more sober understanding of the challenges it presents, particularly for smaller developers. Additionally, AI regulation in the EU is predicted to stall due to rapid technological advances

paulddraper 3y ago
That hasn't been my perception
DesertVarnish 3y ago
They really aren't the same. Crypto didn't and still doesn't have the same immediate utility. The value proposition just wasn't there to justify the money and attention it was getting. Bitcoin in particular was a prototype that got mythologized into being "digital gold" despite it's many, many technical limitations. Diffusion models and LLMs work today and make possible things that were science fiction five years ago, and have shown tremendous and exciting progress in the past 18 months.
- ok_dad 3y ago
  Your last paragraph is the hype. I haven’t seen any effective uses of the current AI tech that couldn’t have been done for the same cost by humans so far. Images, text, code; I haven’t seen anything but toys built yet. The coding tools might work okay for your average HTTP API, but it’s not going to develop novel algorithms to control building HVAC systems to reduce energy or demand, for example. It’s not going to code much more efficient search algorithms, or faster compression. Maybe someday, but so far everything produced by AI seems to have huge problems, whether it be drawing realistic hands, knowing the factual truth of certain questions, or introducing subtle bugs in complex code.
  - Charon77 3y ago
    How about alphafold? Prior usage requires quite literally weeks to months on supercomputers with results often not so comparable with the X ray crystallography. Or the use of AI for real time upscaling that can be done in real time on low to medium GPU. I think you only see chat gpt which don have its own draw back, but AI does not equal gpt, does not even has to be generative.
    - ok_dad 3y ago
      Alphafold: there are lots of caveats, from my limited understanding so far the “thing“ it does isn’t a limiting factor for speeding up drug development. Video cards: I don’t know much about them, it seems impressive but I’m not sold it’s the future of gaming yet; also they’re expensive as Fuck I am not saying this stuff will never be useful, but we’re at the peak of the hype cycle today, and I expect many, many of the supposed breakthroughs turn out to be a dead end or harder to make reliable than expected. Or, way more expensive than financially viable for that problem. I hope I’m wrong, tech wise, because it would be amazing to reduce the needed human work output, but also I’m not sold that our society can survive if AI takes over jobs, so that’s another reason that I’m bullish.
    - AraceliHarker 3y ago
      Although AI has various variations, the recent AI boom is referring to what is called generative AI such as ChatGPT.
  - tomohelix 3y ago
    That is because you are comparing it to the cost of a professional. I personally look at it in a different way. Now, a rando on the street knowing nothing about everything can pop out arts rivaling an experienced illustrator. A completely clueless wet lab scientist can coerce copilot or GPT4 to cobble together an automated data analysis pipeline in a language that they know nothing about. To a professional, those applications are toys, easily made and take little effort. But to someone who does not know anything about the work, it is amazingly useful and open up many possibilities. That is the power and the use cases for AI right now. They are tools to augment productivity, not replacing it. And in that regard, it is very successful imo. Whether it will progress to the point where it can outright handle everything from start to finish or not is another question.
deleted 3y ago
[deleted]

deleted 3y ago

[deleted]

futureamish 3y ago

[flagged]

nabla9 3y ago

One of the best uses of generative AI is Gihub Copilot. Microsoft loses $20 per month for each Github Copilot user. Copilot should cost $40 - $50 per month to cover the cost of running it.

wokwokwok 3y ago
Yeah, this. The tech is great, but it’s expensive to run, and it’s being given away basically for free at the moment. …and hey, free stuff is great. Enjoy it while you can! At some point, however, companies have to stop giving things away for free (or at a loss); it’s just a matter of what that looks like under sustainable pricing.
- Closi 3y ago
  Subsidise now, profit later. If you have the cash, it’s probably better to burn some getting early user adoption if you believe the cost base will reduce in the future. Inference costs are dropping fast, so you might as well subsidise now and get market share if you think future costs will drop below future revenue. User aquisition will be much harder later when you lose first mover advantage.
5350-uiop-1130 3y ago
"pay us $40 - $50 a month to train your future replacement"

faeriechangling 3y ago

Overhyped how? Overhyped like self-driving, in terms of the timelines? Or overhyped in terms of the eventual societal impact? I think people seriously underestimate how much of a struggle driving down the cost of compute/$ is going to be. Every incremental gain in memory and microprocessors is getting exponentially more expensive to develop. This is also a (relatively) high interest rate environment which do not tend to favour long term speculative investments. A lot of people aren't fully aware of how OpenAI and GitHub CoPilot are bleeding red ink from the get-go. I honestly feel like people are really sleeping on the potential still. Most people I know tried it a few times around last Christmas and got bored with it and quit but I never stopped using it.

brucethemoose2 3y ago
> struggle driving down the cost of compute/$ Actually I feel that utilization of existing hardware is very poor. For instance, in LLM land, continuous batching is a thing that just starting to proliferate (at least in open source). Many are still doing training/inference in vanilla pipes in PyTorch eager mode, without even a simple `torch.compile` or aggressive quantization, much less a more advanced ML compiler. Architecture optimizations beyond llama's base architecture (like newer attention schemes used during training) are not really picked up yet. I can go on and on, and go on about Stable Diffusion as well, but what I am saying is there is tons of unpicked low hanging fruit, that's unexploited because... everyone is in a rush to just publish or deploy something, I guess? Also, Nvidia's margins are insane. The voltage/clock band they run in is insanely inefficient. I hope that is not sustainable, because sane margins/clocks with no code/hardware advancement would bring costs down a ton.
- npsomaratna 3y ago
  Can you explain more about the voltage/clock band please? Do you mean that they are very energy inefficient?
  - brucethemoose2 3y ago
    Yes. Basically, power usage increases quadradicaly with clockspeed. Running a little faster takes a lot more power. Nvidia runs GPUs smaller than an Apple M1 Ultra at 250-450W. Thats crazy for a single chip! They could sacrifice a tiny bit of performance and run with much less power... But they don't. The Cerebras CS2, for reference, has a much lower power density and runs more efficiently. Unfortunately most other AI hardware is pretty hotly clocked at the moment.

tomohelix 3y ago

Well, this was already pointed out a long time ago during the peak hype of AI earlier this year. Something about we overhype the effect of the technology in the short term and underestimate the impact long term. One thing that is undeniable is that AIs have actual productive use cases. Some of the previous fads did not actually have any major real applications even years after its introduction. Meanwhile, AI technology, specifically the transformer tech, has already revolutionized biotech, art, and NLP fields. Even if all progress on AI hit a stop today, people will still use alphafold, diffusion, and chatgpt for their intended purposes. So I am sure we can agree that AI isn't going down the road of things like NFT or bitcoins. Next few years would be the optimization and mass adoption steps. Big tech companies are probably plucking all the low hanging fruit already. The hard parts are probably what make it more useful, i.e. cheaper and in a format that can be used easily. Those take time, but 15 years ago, I would be dreaming if I think I can play Crysis on a handheld device. Now I can for a measly $400. So in the next 10 years, it isn't impossible to have something on the level of chatgpt running in real time on something like a phone or smartglass. And that is discounting the possibility of any major breakthrough or genius application like the GUI to computer interface or the iphone to personal computer. Something like that can pop up and change the world as we know it.

az09mugen 3y ago
One other thing is worth mentioning, is also the negative impact of AI to take into account. It helps everything to get done easier, but it includes good things and bad things. Did you see AI is also trained to make pentests ? Or create malwares ? Or a model with almost no restrictions is released in the wild (Mistral) ? Or any other bad stuff I can't imagine ? Do people even imagine how it can become easy to do evil things ? No, because they're overhyped by AI. Not everyone, but still.

AraceliHarker 3y ago

In the end, it's the same story as automating warehouse delivery, where it turns out that it's actually cheaper to have humans do it. AI is no different. Moreover, the recent restrictions on AI-generated content have caused inconveniences even in ordinary use that is not socially harmful, and expectations for AI have been greatly damaged.

patrickhogan1 3y ago

Says the analyst who will be replaced by ChatGPT in 2024.

singularity2001 3y ago

Given the results of the latest midjourney version I feel it's even underhyped: https://reddit.com/r/midjourney/s/ODnwsKazlo https://reddit.com/r/midjourney/s/ODnwsKazlo I don't know about the valley but where I am people are unexcited about AI, when they should be