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It's silly to say that the only objective that will vindicate AI investments is AGI. Current batch of deep learning models are fundamentally a technology for l

It's silly to say that the only objective that will vindicate AI investments is AGI. Current batch of deep learning models are fundamentally a technology for labor automation. This is immensely useful in itself, without the need to do AGI. The Sora2 capabilities are absolutely wild (see a great example here of what non-professional users are already able to create with it: https://www.youtube.com/watch?v=HXp8_w3XzgU https://www.youtube.com/watch?v=HXp8_w3XzgU ) So only looking at video capabilities, or at coding capabilities, it's already ready to automate and upend industries worth trillions in the long run. The emerging reasoning capabilities are very promising, able to generate new theories and make scientific experiments in easy to test fields, such as in vitro drug creation. It doesn't matter if the LLM hallucinates 90% of the time, if it correctly reasons a single time and it can create even a single new cancer drug that passes the test. These are all examples of massive, massive economic disruption by automating intellectual labor, that don't require strict AGI capabilities.

asdf1280 1y ago
The problem is that it’s already commodified; there’s no moat. The general tech practice has been capture the market by burning vc money, then jack up prices to profit. All these companies are burning billions to generate a new model and users have already proven there is no brand loyalty. They just hop to the new one when it comes out. So no one can corner the market and when the VC money runs out they’ll have to jack up prices so much that they’ll kill their market
- Wowfunhappy 1y ago
  > The problem is that it’s already commodified; there’s no moat. From an economy-wide perspective, why does that matter? > users have already proven there is no brand loyalty. They just hop to the new one when it comes out. Great, that means there might be real competition! This generally keeps prices down, it doesn't push them up! It's true that VCs may end up unhappy, but will they be able to do anything about it?
- frogperson 1y ago
  The most isnt with the llm crestors, its with nvidia, but even that is under seige by Chinese mskers.
- squidbeak 1y ago
  Compute is the moat.
jennyholzer 1y ago
You seem to be making an implicit claim that LLMs can create an effective cancer drug "10% of the time". Smells like complete and total bullshit to me. Edit: @eucyclos: I don't assume that Chat GPT and LLM tools have saved cancer researchers any time at all. On the contrary, I assume that these tools have only made these critical researchers less productive, and made their internal communications more verbose and less effective.
- eucyclos 1y ago
  How many hours writing emails does it have to save human cancer researchers for it to be effectively true?
- cornholio 1y ago
  No, that's not the claim. The claim is that we will create a hypothetical LLM that, when tasked with a problem at the scientific frontier of molecular biology will, about 10% of the time, correctly reason about existing literature and reach conclusions that are valid or plausible to similar experts in the field. Let's say you run that LLM one million times and get 100.000 valid reasoning chains. Let's say among them are variations on 1000 fundamentally new approaches and ideas, and out of those, you can actually synthesize in the laboratory 200 new candidate compounds, and out of those, 10 substance show strong in-vitro response, and then one of those completely cures some cancerous mice. There you go, you have substantially automated the intellectual work of cancer research and you have one very promising compound you can start phase 1 trials that you didn't have before AI, and all without any AGI.
rafaelmn 1y ago
If you calculate the investment into AI and then divide by say 100k that's how many man-years need to replace with AI to be cost effective as labor automation the numbers aren't that promising given the current level of capability.
- Gerardo1 1y ago
  Don't even need to get too fancy with it. Open AI has publicly committed to ~$500B in spending over the next several years (nevermind even they don't expect to actually bring that much revenue in) $500B/$100,000 is 5 million, or 167k 30-year careers. The math is ludicrous, and the people saying it's fine are incomnprehensible to me. Another comment on a similar post just said, no hyperbole, irony, or joke intended: "Just you switching away from Google is already justifying 1T infrastructure spend."
- cornholio 1y ago
  I don't think I follow. 1 trillion total investment divided by 100k yields 10 million man years, or 300k man-careers. Just the disruption we can already see in the software industry are easily of that magnitude.
  - rafaelmn 1y ago
    >Just the disruption we can already see in the software industry are easily of that magnitude. WTF ? Where are you seeing that ? Also no you can't calculate 100k over 30 years as 3M because you expect investment growth - lets say stock market average of 7 percent per year that investment must return like 24 million in 30 years otherwise its not worth it. That means 8 trillion in next 30 years if you look over that long of an investment period. And who in the hell is going to capture 30 years of profit with model/compute investments made today. The math only maths within short timeframes - hardware will get amortized in 5 years, model obsolete in even less. So best case scenario you have to displace 2 million people and capture their output to repay that. Not with future tech - with tech investments made today.
    - cornholio 1y ago
maeln 1y ago
> Current batch of deep learning models are fundamentally a technology for labor automation. This is immensely useful in itself, without the need to do AGI. The Sora2 capabilities are absolutely wild (see a great example here of what non-professional users are already able to create with it: https://www.youtube.com/watch?v=HXp8_w3XzgU https://www.youtube.com/watch?v=HXp8_w3XzgU ) > So only looking at video capabilities, or at coding capabilities, it's already ready to automate and upend industries worth trillions in the long run. Can Sora2 change the framing of a picture without changing the global scene ? Can it change the temperature of a specific light source ? Can it generate a 8k HDR footage suitable for re-framing and color grading ? Can it generate minute long video without loosing coherence ? Actually, can it generate a few seconds without having to reloop with the last frame and have these obnoxious cuts that the video you pointed has ? Can it reshoot the same exact scene with just one element altered ? All the video models right now are only good at making short, low-res, barely post-processable video. The kind of stuff you see on social media. And considering the metrics on ai-generated video on social media right now, for the most part, nobody want to look at them. They might replace the bottom of the barrel of social media posting (hello cute puppy videos), but there is absolutely nothing indicating that they migth automate or upend any real industry (be used in the pipeline, yeah maybe, why not, automate ? Won't hold my breath). And the argument of their future capabilities, well ... It's been 50+ years that we should have fusion in 20 years. Btw, the same argument can be made for LLM and image-gen tech in any creative purposes. People severly underestimate just how much editing, re-work, purpose and pre-production steps are involved in any major creative endeavor. Most model are just severly ill suited for that work. They can be useful for some stuff (specificaly, for editing images, ai-driven image fill do work decently for exemple), but overall, as of right now, they are mostly good at making low quality content. Which is fine I guess, there is a market for it, but it was already a market that was not keen on spending money.
- ____mr____ 1y ago
  > They might replace the bottom of the barrel of social media posting (hello cute puppy videos) Lay off. Only respite I get from this hell world is cute Rottweiler videos
- data-ottawa 1y ago
hemloc_io 1y ago
Regardless of my opinions on if you're correct about this, I'm not an ML expert so who knows, I'd be very happy if we cured cancer so I hope you're correct and the video is a cool demo. I don't believe the risk vs reward on investing a trillion dollars+ is the same when your thesis changes from "We just need more data/compute and we can automate all white collar work" to "If we can build a bunch of simulations and automate testing of them using ML then maybe we can find new drugs" or "automate personalized entertainment" The move to RL has specifically made me skeptical of the size of the buildout.

asdf1280 1y ago

The problem is that it’s already commodified; there’s no moat. The general tech practice has been capture the market by burning vc money, then jack up prices to profit. All these companies are burning billions to generate a new model and users have already proven there is no brand loyalty. They just hop to the new one when it comes out. So no one can corner the market and when the VC money runs out they’ll have to jack up prices so much that they’ll kill their market

Wowfunhappy 1y ago
> The problem is that it’s already commodified; there’s no moat. From an economy-wide perspective, why does that matter? > users have already proven there is no brand loyalty. They just hop to the new one when it comes out. Great, that means there might be real competition! This generally keeps prices down, it doesn't push them up! It's true that VCs may end up unhappy, but will they be able to do anything about it?
frogperson 1y ago
The most isnt with the llm crestors, its with nvidia, but even that is under seige by Chinese mskers.
squidbeak 1y ago
Compute is the moat.

jennyholzer 1y ago

You seem to be making an implicit claim that LLMs can create an effective cancer drug "10% of the time". Smells like complete and total bullshit to me. Edit: @eucyclos: I don't assume that Chat GPT and LLM tools have saved cancer researchers any time at all. On the contrary, I assume that these tools have only made these critical researchers less productive, and made their internal communications more verbose and less effective.

eucyclos 1y ago
How many hours writing emails does it have to save human cancer researchers for it to be effectively true?
cornholio 1y ago
No, that's not the claim. The claim is that we will create a hypothetical LLM that, when tasked with a problem at the scientific frontier of molecular biology will, about 10% of the time, correctly reason about existing literature and reach conclusions that are valid or plausible to similar experts in the field. Let's say you run that LLM one million times and get 100.000 valid reasoning chains. Let's say among them are variations on 1000 fundamentally new approaches and ideas, and out of those, you can actually synthesize in the laboratory 200 new candidate compounds, and out of those, 10 substance show strong in-vitro response, and then one of those completely cures some cancerous mice. There you go, you have substantially automated the intellectual work of cancer research and you have one very promising compound you can start phase 1 trials that you didn't have before AI, and all without any AGI.

rafaelmn 1y ago

If you calculate the investment into AI and then divide by say 100k that's how many man-years need to replace with AI to be cost effective as labor automation the numbers aren't that promising given the current level of capability.

Gerardo1 1y ago
Don't even need to get too fancy with it. Open AI has publicly committed to ~$500B in spending over the next several years (nevermind even they don't expect to actually bring that much revenue in) $500B/$100,000 is 5 million, or 167k 30-year careers. The math is ludicrous, and the people saying it's fine are incomnprehensible to me. Another comment on a similar post just said, no hyperbole, irony, or joke intended: "Just you switching away from Google is already justifying 1T infrastructure spend."
cornholio 1y ago
I don't think I follow. 1 trillion total investment divided by 100k yields 10 million man years, or 300k man-careers. Just the disruption we can already see in the software industry are easily of that magnitude.
- rafaelmn 1y ago
  >Just the disruption we can already see in the software industry are easily of that magnitude. WTF ? Where are you seeing that ? Also no you can't calculate 100k over 30 years as 3M because you expect investment growth - lets say stock market average of 7 percent per year that investment must return like 24 million in 30 years otherwise its not worth it. That means 8 trillion in next 30 years if you look over that long of an investment period. And who in the hell is going to capture 30 years of profit with model/compute investments made today. The math only maths within short timeframes - hardware will get amortized in 5 years, model obsolete in even less. So best case scenario you have to displace 2 million people and capture their output to repay that. Not with future tech - with tech investments made today.
  - cornholio 1y ago

maeln 1y ago

> Current batch of deep learning models are fundamentally a technology for labor automation. This is immensely useful in itself, without the need to do AGI. The Sora2 capabilities are absolutely wild (see a great example here of what non-professional users are already able to create with it: https://www.youtube.com/watch?v=HXp8_w3XzgU https://www.youtube.com/watch?v=HXp8_w3XzgU ) > So only looking at video capabilities, or at coding capabilities, it's already ready to automate and upend industries worth trillions in the long run. Can Sora2 change the framing of a picture without changing the global scene ? Can it change the temperature of a specific light source ? Can it generate a 8k HDR footage suitable for re-framing and color grading ? Can it generate minute long video without loosing coherence ? Actually, can it generate a few seconds without having to reloop with the last frame and have these obnoxious cuts that the video you pointed has ? Can it reshoot the same exact scene with just one element altered ? All the video models right now are only good at making short, low-res, barely post-processable video. The kind of stuff you see on social media. And considering the metrics on ai-generated video on social media right now, for the most part, nobody want to look at them. They might replace the bottom of the barrel of social media posting (hello cute puppy videos), but there is absolutely nothing indicating that they migth automate or upend any real industry (be used in the pipeline, yeah maybe, why not, automate ? Won't hold my breath). And the argument of their future capabilities, well ... It's been 50+ years that we should have fusion in 20 years. Btw, the same argument can be made for LLM and image-gen tech in any creative purposes. People severly underestimate just how much editing, re-work, purpose and pre-production steps are involved in any major creative endeavor. Most model are just severly ill suited for that work. They can be useful for some stuff (specificaly, for editing images, ai-driven image fill do work decently for exemple), but overall, as of right now, they are mostly good at making low quality content. Which is fine I guess, there is a market for it, but it was already a market that was not keen on spending money.

____mr____ 1y ago
> They might replace the bottom of the barrel of social media posting (hello cute puppy videos) Lay off. Only respite I get from this hell world is cute Rottweiler videos
data-ottawa 1y ago

hemloc_io 1y ago

Regardless of my opinions on if you're correct about this, I'm not an ML expert so who knows, I'd be very happy if we cured cancer so I hope you're correct and the video is a cool demo. I don't believe the risk vs reward on investing a trillion dollars+ is the same when your thesis changes from "We just need more data/compute and we can automate all white collar work" to "If we can build a bunch of simulations and automate testing of them using ML then maybe we can find new drugs" or "automate personalized entertainment" The move to RL has specifically made me skeptical of the size of the buildout.