4 ms·

It’s getting started. Serious use cases never have the glamour of hype. But I am starting to see generative AI cover more and more ground into business utility.

by LASR 3y ago

It’s getting started. Serious use cases never have the glamour of hype. But I am starting to see generative AI cover more and more ground into business utility. Saying it’s over is like saying that the internet is over after the dotcom bubble burst. Nah. This is a revolutionizing foundational tech. Bigger than the internet even IMO. More like computerization of business, or the steam engine.

HPMOR 3y ago
Completely agree. These foundational models are more akin to the invention of transistors or the internet than anything else. It's a little disheartening from a startup perspective to see already large "incumbents" in the form of Google, Open-AI but I think most of the value created, in the future, from generative AI, will not be captured by these players.
- croes 3y ago
  The question is if the models can get significantly better or are they already near the peak of their capabilities.
  - flangola7 3y ago
    Researchers are still picking low hanging fruit by the fortnight. We are a lo00000ng way from a place where we may even estimate the peak capability. Look at what GPT-4 can achieve from only receiving text and a primitive form of image training.
    - croes 3y ago
      But models like GPT-4 depend on good quality training data, and that resource is limited, means maybe we aren't so long away from peak at least for LLMs. There is no unlimited growth, and after the low hanging fruits each step in progress will be exponentially harder.
      - gmerc 3y ago
        While true, we’ve been successfully keeping up this illusion for the whole economy for many decades.
      - flangola7 3y ago
        > But models like GPT-4 depend on good quality training data, and that resource is limited Most data has not been incorporated into a model yet. Most data is not in text format. We don't know what is possible once that changes.
tmikaeld 3y ago
Also, the open source models are getting closer and closer to the (current) closed models. Hopefully more and more tinkerers are going to fuel this fire even further, making it possible to run AI on-device with custom native chips.
- toxik 3y ago
  Which current public models do you think are getting to ChatGPT levels?
  - tmikaeld 3y ago
    Llama 2 is very close to GPT 3, same with the new code Llama. That said, while it scores high, it's not as "generally" competent on most issues as GPT is, however, it's an exponentially smaller model and for that it does, it's really impressive.
  - reacharavindh 3y ago
    I don’t particularly use ChatGPT in any serious capacity or for work. But, for my amusement and intellectual assisting needs, Llam2-uncensored and codewhisper models run using Ollama locally on my Mac has been a pleasure to use. Like most things, if you steer clear of all the hype there is a golden core of utility to be found. It sure is not just a party truck as the article daringly claims/questions it to be. The ones that make clever use of the foundational tool will stand to reap the benefits. Just like the ones that benefited from the spread of the internet.
  - capybara_2020 3y ago
    Depends on what you want to do. For writing and RPG style interactions some of the LLama 2 based models are pretty good. Beauty is, even the 13B models work in those cases. So it works reasonably well on consumer grade hardware.
  - Roark66 3y ago
    It is not really a fair comparison, because chatgpt is not just a model. There is clever output sampling, scoring, sub model selection based on prompt and more. While open source LLMs are "just a model" with the most basic (greedy) output sampling. To have real LLM comparison we would need access to pure chatgpt model's input/outputs. I wouldn't be surprised if certain open source LLMs like falcon-40b-instruct or llama2 have already surpassed chatgpt 3.5 models in quality. But as far as I know no one so far has taken a bunch of open source models and wrapped them in a service like chatgpt 4. Why? Because the main cost of running such service using open source code (assuming the service would be open source too) would be the cost of renting hardware. Consequently the barrier to entry for competition would be very low so no one would sink their life savings in a company like that. However, once it becomes possible to run multiple models like falcon-40B and llama2 (without quantization to 4bits) on a typical "high end pc" that will change. We will see open source projects that want to achieve a "chatgpt service" offline on consumer hardware. Why only then? Same reason why Linux was written once 386PC's became available. Could someone like Linus Torvalds write Linux 20 years before on their "university" or "company" computer? Sure, but except certain exceptions (gnu) most people engage in writing open source software they themselves want to run on their own hardware. Big companies know this and they know very well such developments will out compete them shortly (like Linux out competed unix) so they are already doing all they can to stop or slow it down. By talking about "the dangers of AI", by not releasing powerfull ai accelerators on the market (google's tpu). And so on. But it will happen. Give it 10 years. I
spaceman_2020 3y ago
What sort of business use cases are you seeing? I hang around a lot of solopreneurs and there is a serious cohort of founders/hustlers who are using AI tools to greatly improve their productivity. Not sure how much of that can carry forth to a major corporation though.
yyt88 3y ago
> This is a revolutionizing foundational tech. Bigger than the internet even IMO. Oh is it? Maybe you can tell us then how you'd get the models home without the internet? On a DVD? Or interact with a server that runs the model for you? Or how we'd even be having this discussion? People said similar delusions about Second Life back in the day.
- andybak 3y ago
  Something can depend on another thing and still be "bigger" than it. (as woolly as that definition is) I don't actually agree with the point you're contesting with but your reasoning here is flawed. Also - you might want to check your tone for future posts. It's slighty combative.
  - yyt88 3y ago
    Apologies, I'm new here. How would you express your angle regarding the contested point?
    - andybak 3y ago
      You're making a logical connection betweeen x depending on y and x being (bigger/more important/more significant) than y. That implies that nothing can be more important than all of the things that were neccesary for it to come to pass. And there are a huge number of neccesary preconditions for most things. Your definition would result in a very counterintuitive definition of importance.
      - yyt88 3y ago
        I understood your criticism of my post. What I was asking for as how you would have expressed the criticism of the post I was criticising, since you mentioned that you also don't agreee with it, just like me.
        andybak 3y ago
isoprophlex 3y ago
People miss the "hidden bit of the iceberg" when dismissing gen AI, or making claims that the hype is over. It's just getting started, indeed. Anyone who did data work in big, boring enterprises knows the staggering amount of dark, unstructured data they have. Free-form text input, chat/phone conversations, but also plain old documents (pdf scans, PowerPoint files, anything). Have a LLM interpret what is there and you turn this unstructured mess into data with a clear schema that can go into a relational database for further processing or summarization. LLMs are groundbreaking for this kind of automated data structuring. And many use cases don't need perfect accuracy; detecting trends or summarizing at a high level is good enough for inputs to downstream process mining tasks.
- nuc1e0n 3y ago
  Present LLMs have not been designed to and cannot process audio data or scanned images.

by LASR 3y ago

HPMOR 3y ago

Completely agree. These foundational models are more akin to the invention of transistors or the internet than anything else. It's a little disheartening from a startup perspective to see already large "incumbents" in the form of Google, Open-AI but I think most of the value created, in the future, from generative AI, will not be captured by these players.

croes 3y ago
The question is if the models can get significantly better or are they already near the peak of their capabilities.
- flangola7 3y ago
  Researchers are still picking low hanging fruit by the fortnight. We are a lo00000ng way from a place where we may even estimate the peak capability. Look at what GPT-4 can achieve from only receiving text and a primitive form of image training.
  - croes 3y ago
    But models like GPT-4 depend on good quality training data, and that resource is limited, means maybe we aren't so long away from peak at least for LLMs. There is no unlimited growth, and after the low hanging fruits each step in progress will be exponentially harder.
    - gmerc 3y ago
      While true, we’ve been successfully keeping up this illusion for the whole economy for many decades.
    - flangola7 3y ago
      > But models like GPT-4 depend on good quality training data, and that resource is limited Most data has not been incorporated into a model yet. Most data is not in text format. We don't know what is possible once that changes.

tmikaeld 3y ago

Also, the open source models are getting closer and closer to the (current) closed models. Hopefully more and more tinkerers are going to fuel this fire even further, making it possible to run AI on-device with custom native chips.

toxik 3y ago
Which current public models do you think are getting to ChatGPT levels?
- tmikaeld 3y ago
  Llama 2 is very close to GPT 3, same with the new code Llama. That said, while it scores high, it's not as "generally" competent on most issues as GPT is, however, it's an exponentially smaller model and for that it does, it's really impressive.
- reacharavindh 3y ago
  I don’t particularly use ChatGPT in any serious capacity or for work. But, for my amusement and intellectual assisting needs, Llam2-uncensored and codewhisper models run using Ollama locally on my Mac has been a pleasure to use. Like most things, if you steer clear of all the hype there is a golden core of utility to be found. It sure is not just a party truck as the article daringly claims/questions it to be. The ones that make clever use of the foundational tool will stand to reap the benefits. Just like the ones that benefited from the spread of the internet.
- capybara_2020 3y ago
  Depends on what you want to do. For writing and RPG style interactions some of the LLama 2 based models are pretty good. Beauty is, even the 13B models work in those cases. So it works reasonably well on consumer grade hardware.
- Roark66 3y ago
  It is not really a fair comparison, because chatgpt is not just a model. There is clever output sampling, scoring, sub model selection based on prompt and more. While open source LLMs are "just a model" with the most basic (greedy) output sampling. To have real LLM comparison we would need access to pure chatgpt model's input/outputs. I wouldn't be surprised if certain open source LLMs like falcon-40b-instruct or llama2 have already surpassed chatgpt 3.5 models in quality. But as far as I know no one so far has taken a bunch of open source models and wrapped them in a service like chatgpt 4. Why? Because the main cost of running such service using open source code (assuming the service would be open source too) would be the cost of renting hardware. Consequently the barrier to entry for competition would be very low so no one would sink their life savings in a company like that. However, once it becomes possible to run multiple models like falcon-40B and llama2 (without quantization to 4bits) on a typical "high end pc" that will change. We will see open source projects that want to achieve a "chatgpt service" offline on consumer hardware. Why only then? Same reason why Linux was written once 386PC's became available. Could someone like Linus Torvalds write Linux 20 years before on their "university" or "company" computer? Sure, but except certain exceptions (gnu) most people engage in writing open source software they themselves want to run on their own hardware. Big companies know this and they know very well such developments will out compete them shortly (like Linux out competed unix) so they are already doing all they can to stop or slow it down. By talking about "the dangers of AI", by not releasing powerfull ai accelerators on the market (google's tpu). And so on. But it will happen. Give it 10 years. I

spaceman_2020 3y ago

What sort of business use cases are you seeing? I hang around a lot of solopreneurs and there is a serious cohort of founders/hustlers who are using AI tools to greatly improve their productivity. Not sure how much of that can carry forth to a major corporation though.

yyt88 3y ago

> This is a revolutionizing foundational tech. Bigger than the internet even IMO. Oh is it? Maybe you can tell us then how you'd get the models home without the internet? On a DVD? Or interact with a server that runs the model for you? Or how we'd even be having this discussion? People said similar delusions about Second Life back in the day.

andybak 3y ago
Something can depend on another thing and still be "bigger" than it. (as woolly as that definition is) I don't actually agree with the point you're contesting with but your reasoning here is flawed. Also - you might want to check your tone for future posts. It's slighty combative.
- yyt88 3y ago
  Apologies, I'm new here. How would you express your angle regarding the contested point?
  - andybak 3y ago
    You're making a logical connection betweeen x depending on y and x being (bigger/more important/more significant) than y. That implies that nothing can be more important than all of the things that were neccesary for it to come to pass. And there are a huge number of neccesary preconditions for most things. Your definition would result in a very counterintuitive definition of importance.
    - yyt88 3y ago
      I understood your criticism of my post. What I was asking for as how you would have expressed the criticism of the post I was criticising, since you mentioned that you also don't agreee with it, just like me.
      - andybak 3y ago

isoprophlex 3y ago

People miss the "hidden bit of the iceberg" when dismissing gen AI, or making claims that the hype is over. It's just getting started, indeed. Anyone who did data work in big, boring enterprises knows the staggering amount of dark, unstructured data they have. Free-form text input, chat/phone conversations, but also plain old documents (pdf scans, PowerPoint files, anything). Have a LLM interpret what is there and you turn this unstructured mess into data with a clear schema that can go into a relational database for further processing or summarization. LLMs are groundbreaking for this kind of automated data structuring. And many use cases don't need perfect accuracy; detecting trends or summarizing at a high level is good enough for inputs to downstream process mining tasks.

nuc1e0n 3y ago
Present LLMs have not been designed to and cannot process audio data or scanned images.