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You are not missing anything. It's a bubble. This is tech 101 and all over again. You gotta hype some new thing whether it's Web 2.0, Crypto or AI. LLM have pr

by csomar 4y ago

You are not missing anything. It's a bubble. This is tech 101 and all over again. You gotta hype some new thing whether it's Web 2.0, Crypto or AI. LLM have proven to be great as a gimmick or making rather okay localized approximations. You can create a good enough image without any designing skills, or have auto-completion on steroids. However, there is no proof that this same tech can extrapolate to the next level. Most startups are putting their eggs on this single basket. I have the feeling that this will be what triggers another AI winter and some VCs will holding the bags... but why do I care?

zarzavat 4y ago
I believe that you are half right. AI is going to radically change the world, but not now, maybe in 10 years. The pace of research is slower than the expectations of investors. This will lead to the perception of a boom and bust and AI winter, but in reality there will be slow steady improvements. It’s just been commercialized too soon.
- csomar 4y ago
  There is also the other (very high in my opinion) possibility that LLM will hit a wall in regards to performance and a new model is required. It's unfortunate that the current VC landscape encourages this single shot mentality instead of diversification. This will not help in the AI winter since most people will be invested in the same thing.
  - ChatGTP 4y ago
    Wouldn't it stand to reason that LLMs should be obsolete in about a year due to the singularity event and the rapid speed which we're moving towards AGI and then onto exponential technology growth due to ASI? At this point, as an AI researcher, I guess you'd just have to sit back and watch is all unfold, very soon everything you do is obsolete almost immediately.
    - deleted 4y ago
      [deleted]
    - csomar 4y ago
      This suggests that LLM is the path to take us to AGI. There is no proof for that. That seems to be the current bet, but my thinking (and it is strictly mine) that we are still technologically under-powered to achieve such a leap. Maybe in 10 years, or in one year or in a hundred of years. However, for that leap (and strictly my opinion), we need significant infrastructure leaps. Something like processors are x100 faster, or your laptop is powered by a 5Ghz 200 cores CPU... As it stands, we can't even get the Mark Metaverse right. You are trying to convince me that we have the infra. for AGI? Not convinced.
      - nullsense 4y ago
        Three observations here. Firstly it has been a really eye opening experience watching the innovation around Stable Diffusion and locally run LLMs and seeing that the unoptimized research code that needed such beefy hardware could actually be optimized to run on consumer hardware given sufficient motivation. Secondly it wasn't obvious that deep learning was going to work as well as it did if you simply threw enough compute at it. Now that this tech has reached critical mass there is a tonne more money being poured into infra to support it. Lastly, compute power is increasing as always. Nvidia releasing H100 and also their recent work on computational lithography. Also DeepMind finding new state-of-the-art algorithms for doing matrix multiplication with AlphaTensor. You can kinda already see the positive feedback loop in action. I dunno... at this point I just wouldn't bet against the trajectory that we're on.
        ChatGTP 4y ago
        What actually is the trajectory we're on and what will we do once there?
        nullsense 4y ago
        So, it seems the trajectory is one of increasing generality and capability of models and increasing reliance on them. If it's at all possible to improve our technology then we will. If we improve it it increases in utility. If it increases in utility we use it more. What other thesis is there?
spaceman_2020 4y ago
You couldn’t be further from the truth. This is the single greatest leap in productivity we’ve had in the last 100 years. Last week, I used GPT-4 to write my code. Later, I used it to analyze 100+ websites and come up with a personalized pitch for a relevant plugin/product idea - something that would have taken me 100+ hours.
- uxcolumbo 4y ago
  How did you use it to analyse websites? Did it go scrape stuff for you or did already have the data or did you paste in the website data?
  - hallway_monitor 4y ago
    It has plugins now. It can search the web. It's connected to Wolfram. Zapier. It can do things. Even before that you could hack something together. I told it how to request an image be included in responses - it includes [fluffy unicorn], I parse that out, feed it to another GPT to get a better description, then feed that to DALL-E to get the image to include
- mach1ne 4y ago
  Yes, but it hallucinates sometimes. /s
  - Gigablah 4y ago
    I mean, that’s exactly what it’s being used for — hallucination.
    - roer 4y ago
      Can you elaborate on this? Or are you just being cheeky?
      - kolinko 4y ago
        When you use it for brainstorming, hallucination is not that big of a deal - you need to verify ideas anyway. And it's great at "thinking" outside of the box, if you prompt it right.
greeny7373 4y ago
All current indications says otherwise. Web3 or crypto didn't disrupt markets. Chatgpt or let's say ml already did and there is no writing on the wall it will stop. Contrary it shows how much potential there is and how excited a lot of people are. We have already ml now in office, in bing, in Google workspace. There is midjourney, SD etc. You can find ml generated porn pictures. We have constantly news about advantages in multiple ml fields. This is so different to crypto and stuff.

by csomar 4y ago

zarzavat 4y ago

I believe that you are half right. AI is going to radically change the world, but not now, maybe in 10 years. The pace of research is slower than the expectations of investors. This will lead to the perception of a boom and bust and AI winter, but in reality there will be slow steady improvements. It’s just been commercialized too soon.

csomar 4y ago
There is also the other (very high in my opinion) possibility that LLM will hit a wall in regards to performance and a new model is required. It's unfortunate that the current VC landscape encourages this single shot mentality instead of diversification. This will not help in the AI winter since most people will be invested in the same thing.
- ChatGTP 4y ago
  Wouldn't it stand to reason that LLMs should be obsolete in about a year due to the singularity event and the rapid speed which we're moving towards AGI and then onto exponential technology growth due to ASI? At this point, as an AI researcher, I guess you'd just have to sit back and watch is all unfold, very soon everything you do is obsolete almost immediately.
  - deleted 4y ago
    [deleted]
  - csomar 4y ago
    This suggests that LLM is the path to take us to AGI. There is no proof for that. That seems to be the current bet, but my thinking (and it is strictly mine) that we are still technologically under-powered to achieve such a leap. Maybe in 10 years, or in one year or in a hundred of years. However, for that leap (and strictly my opinion), we need significant infrastructure leaps. Something like processors are x100 faster, or your laptop is powered by a 5Ghz 200 cores CPU... As it stands, we can't even get the Mark Metaverse right. You are trying to convince me that we have the infra. for AGI? Not convinced.
    - nullsense 4y ago
      Three observations here. Firstly it has been a really eye opening experience watching the innovation around Stable Diffusion and locally run LLMs and seeing that the unoptimized research code that needed such beefy hardware could actually be optimized to run on consumer hardware given sufficient motivation. Secondly it wasn't obvious that deep learning was going to work as well as it did if you simply threw enough compute at it. Now that this tech has reached critical mass there is a tonne more money being poured into infra to support it. Lastly, compute power is increasing as always. Nvidia releasing H100 and also their recent work on computational lithography. Also DeepMind finding new state-of-the-art algorithms for doing matrix multiplication with AlphaTensor. You can kinda already see the positive feedback loop in action. I dunno... at this point I just wouldn't bet against the trajectory that we're on.
      - ChatGTP 4y ago
        What actually is the trajectory we're on and what will we do once there?
        nullsense 4y ago
        So, it seems the trajectory is one of increasing generality and capability of models and increasing reliance on them. If it's at all possible to improve our technology then we will. If we improve it it increases in utility. If it increases in utility we use it more. What other thesis is there?

spaceman_2020 4y ago

You couldn’t be further from the truth. This is the single greatest leap in productivity we’ve had in the last 100 years. Last week, I used GPT-4 to write my code. Later, I used it to analyze 100+ websites and come up with a personalized pitch for a relevant plugin/product idea - something that would have taken me 100+ hours.

uxcolumbo 4y ago
How did you use it to analyse websites? Did it go scrape stuff for you or did already have the data or did you paste in the website data?
- hallway_monitor 4y ago
  It has plugins now. It can search the web. It's connected to Wolfram. Zapier. It can do things. Even before that you could hack something together. I told it how to request an image be included in responses - it includes [fluffy unicorn], I parse that out, feed it to another GPT to get a better description, then feed that to DALL-E to get the image to include
mach1ne 4y ago
Yes, but it hallucinates sometimes. /s
- Gigablah 4y ago
  I mean, that’s exactly what it’s being used for — hallucination.
  - roer 4y ago
    Can you elaborate on this? Or are you just being cheeky?
    - kolinko 4y ago
      When you use it for brainstorming, hallucination is not that big of a deal - you need to verify ideas anyway. And it's great at "thinking" outside of the box, if you prompt it right.

greeny7373 4y ago

All current indications says otherwise. Web3 or crypto didn't disrupt markets. Chatgpt or let's say ml already did and there is no writing on the wall it will stop. Contrary it shows how much potential there is and how excited a lot of people are. We have already ml now in office, in bing, in Google workspace. There is midjourney, SD etc. You can find ml generated porn pictures. We have constantly news about advantages in multiple ml fields. This is so different to crypto and stuff.