5 ms·

> Some of those GPT-4 models run on my laptop That's an indication that most business-sized models won't need some giant data center. This is going to be a che

> Some of those GPT-4 models run on my laptop That's an indication that most business-sized models won't need some giant data center. This is going to be a cheap technology most of the time. OpenAI is thus way overvalued.

shihab 2y ago
The last OpenAI valuation I read about was 157 billion. I am struggling to understand what justifies this. To me, it feels like OpenAI is at best few months ahead of competitors in some areas. But even if I am underestimating the advantage, it's few years instead of few months, why does it matter? It's not like AI companies are going to enjoy the first-mover advantage internet giants had over the competition.
- throwpoaster 2y ago
  157 billion implies about a 1% chance at dominating a 1.5 trillion market. Seems reasonable.
  - asqueella 2y ago
    10%, no?
    - throwpoaster 2y ago
      No, there’s a risk term I’m skipping over.
  - airstrike 2y ago
    that's 10% and who's to say that market is worth 1.5 trillion to begin with
    - cloverich 2y ago
      Market cap of apple, google, facebook.
      - tantalor 2y ago
        Market cap and market size are totally different measures
    - throwpoaster 2y ago
      There’s a risk term I’m not including and the comparable is the size of the American economy ($27 trillion). So take the entire economy and ask the question: what does AI not impact? Net that out and assume there’s pricing efficiencies, then build in a risk buffer. 1.5t to 15t seems right.
- benreesman 2y ago
  Us skeptics believe that valuation prices in some form of regulatory capture or other non-market factor. The non-skeptical interpretation is that it's a threshold function, a flat-out race with an unambiguous finish line. If someone actually hit self-improving AGI first there's an argument that no one would ever catch up.
  - com2kid 2y ago
    There are some really good books about wars between cultures that have AGI and it always comes down to math - whoever can get their hands on more compute faster wins.
    - api 2y ago
      This is also a strong argument for immigration, particularly high-skill immigration. In the absence of synthetic AGI whoever imports the most human AGI wins.
      - Jensson 2y ago
        Which suggests that total AGI compute doesn't matter that much, as India isn't the world leader the amount of human compute they posses would suggest then. What matters is how you use the AGI, not how much you have, with wrong or bad or limiting regulations it will not lead anywhere.
- datadrivenangel 2y ago
  It's justified if AGI is possible. If AGI is possible, then the entire human economy stops making sense as far as money goes, and 'owning' part of OpenAI gives you power. That is of course, assuming AGI is possible and exponential, and that marketshare goes to a single entity instead of a set of entities. Lots of big assumptions. Seems like we're heading towards a slow-lackluster singularity though.
  - deleted 2y ago
    [deleted]
  - philipkglass 2y ago
    If AGI is possible, then the entire human economy stops making sense as far as money goes, and 'owning' part of OpenAI gives you power. That's if AGI is possible and not easily replicated. If AGI can be copied and/or re-developed like other software then the value of owning OpenAI stock is more like owning stock in copper producers or other commodity sector companies. (It might even be a poorer investment. Even AGI can't create copper atoms, so owners of real physical resources could be in a better position in a post-human-labor world.)
    - whatshisface 2y ago
      This belief comes from confusing the singularity (every atom on Earth is converted into a giant image of Sam Altman) with AGI (a store employee navigates a confrontation with an unruly customer, then goes home and wins at Super Mario).
      - fullstackchris 2y ago
        Exactly. I continually fail to see how "the entire human economy ends" overnight with another human like agent out there - especially if its confined to a server in the first place - it can't even "go home" :)
      - baobabKoodaa 2y ago
        If I recall correctly, these terms were used more or less interchangeably for a few decades, until 2020 or so, when OpenAI started making actual progress towards AGI, and it was clear that the type of AGI that could be imagined at that point, would not be of the type that would produce singularity.
- criddell 2y ago
  > what justifies this People are buying shares at $x because they believe they will be able to sell them for more later. I don’t think there’s a whole to more to it than that.
- ec109685 2y ago
  OpenAI is becoming synonymous with consumer AI. It has potential of disrupting Google’s cash cow, which explains at least a chunk of the valuation. OpenAI predicts more revenue from ChatGPT than api access through 2029. It’s the old Netflix / HBO trope of which can become the other first: hbo figure out streaming or Netflix figure out original programming. I bet Google will figure this out and thus OpenAI won’t disrupt as much as people think it will.
  - CRConrad 2y ago
    > It’s the old Netflix / HBO trope of which can become the other first: hbo figure out streaming or Netflix figure out original programming. Tangential: So how is that race going, has either taken a commanding lead? (Or, hey, is it over already; has either of them won and the other lost? (Yeah, guess if I'm very well-infomed on that industry or not...))
slimsag 2y ago
Unless the best models themselves are costly/hard to produce, and there is not a company providing them to people free of charge AND for commercial use.
epicureanideal 2y ago
And of course, as processors improve this becomes more and more the case.
refulgentis 2y ago
Been in the Mac ecosystem since 2008, love it, but there is, and always has been, a tendency to talk about inevitabilities from scaling bespoke, extremely expensive configurations, and with LLMs, there's heavy eliding of what the user experience is, beyond noting response generation speed in tokens/s. They run on a laptop, yes - you might squeeze up to 10 token/sec out of a kinda sorta GPT-4 if you paid $5K plus for an Apple laptop in the last 18 months. And that's after you spent 2 minutes watching 1000 token* prompt prefill at 10 tokens/sec. Usually it'd be obvious this'd trickle down, things always do, right? But...Apple infamously has been stuck on 8GB of RAM in even $1500 base models for years. I have 0 idea why, but my intuition is RAM was ~doubling capacity at same cost every 3 years till early 2010s, then it mostly stalled out post 2015. And regardless of any of the above, this absolutely melts your battery. Like, your 16 hr battery life becomes 40 minutes, no exaggeration. I don't know why prefill (loading in your prompt) is so slow for local LLMs, but it is. I assume if you have a bunch of servers there's some caching you can do that works across all prompts. I expect the local LLM community to be roughly the same size it is today 5 years from now. * ~3 pages / ~750 words; what I expect is a conservative average for prompt size when coding
- lowercased 2y ago
  I have a 2023 mbp, and I get about 100-150 tok/sec locally with lmstudio.
  - datadrivenangel 2y ago
    Which models?
    - refulgentis 2y ago
      For context, I got M2 Max MBP, 64 GB shared RAM, bought it March 2023 for $5-6K. Llama 3.2 1.0B - 650 t/s Phi 3.5 3.8B - 60 t/s. Llama 3.1 8.0B - 37 t/s. Mixtral 14.0B - 24 t/s. Full GPU acceleration, using llama.cpp, just like LM Studio.
    - lowercased 2y ago
mjburgess 2y ago
I don't think openai's valuation comes from a data center bet -- rather, I'd suppose, investors think it has a first-mover advantage on model quality that it can (maybe?) attract some buy-out interest or otherwise use in yet-to-be-specified product lines. However, it has been clear for a long time that meta are just demolishing any competitor's moats, driving the whole megacorp AI competition to razor thin margins. It's a very welcome strategy from a consumer pov, but -- it has to be said -- genius from a business pov. By deciding that no one will win, it can prevent anyone leapfrogging them at a relatively cheap price.
hyperpape 2y ago
This seems like a non-sequitur unless you’re assuming something about the amount that people use models. Most web servers can run some number of QPS on a developer laptop, but AWS is a big business, because there are a heck of a lot of QPS across all the servers.
thinkingemote 2y ago
Most of the laptops that the models can run on today are in the high end of dedicated bare metal servers. Most shared VM servers are way below these laptops. Most people buying a new laptop today won't be able to run them, most devs getting a website up with a server won't be able to run them. This means that the definitions of "laptop" and "server" are dependent on use. We should instead talk about RAM, GPU and CPU speed which is more useful and informative but less engaging than "my laptop".
m3kw9 2y ago
The best models are always out of reach on desktops. You can have ok models but AGI will come in a datacenter first

shihab 2y ago

The last OpenAI valuation I read about was 157 billion. I am struggling to understand what justifies this. To me, it feels like OpenAI is at best few months ahead of competitors in some areas. But even if I am underestimating the advantage, it's few years instead of few months, why does it matter? It's not like AI companies are going to enjoy the first-mover advantage internet giants had over the competition.

throwpoaster 2y ago
157 billion implies about a 1% chance at dominating a 1.5 trillion market. Seems reasonable.
- asqueella 2y ago
  10%, no?
  - throwpoaster 2y ago
    No, there’s a risk term I’m skipping over.
- airstrike 2y ago
  that's 10% and who's to say that market is worth 1.5 trillion to begin with
  - cloverich 2y ago
    Market cap of apple, google, facebook.
    - tantalor 2y ago
      Market cap and market size are totally different measures
  - throwpoaster 2y ago
    There’s a risk term I’m not including and the comparable is the size of the American economy ($27 trillion). So take the entire economy and ask the question: what does AI not impact? Net that out and assume there’s pricing efficiencies, then build in a risk buffer. 1.5t to 15t seems right.
benreesman 2y ago
Us skeptics believe that valuation prices in some form of regulatory capture or other non-market factor. The non-skeptical interpretation is that it's a threshold function, a flat-out race with an unambiguous finish line. If someone actually hit self-improving AGI first there's an argument that no one would ever catch up.
- com2kid 2y ago
  There are some really good books about wars between cultures that have AGI and it always comes down to math - whoever can get their hands on more compute faster wins.
  - api 2y ago
    This is also a strong argument for immigration, particularly high-skill immigration. In the absence of synthetic AGI whoever imports the most human AGI wins.
    - Jensson 2y ago
      Which suggests that total AGI compute doesn't matter that much, as India isn't the world leader the amount of human compute they posses would suggest then. What matters is how you use the AGI, not how much you have, with wrong or bad or limiting regulations it will not lead anywhere.
datadrivenangel 2y ago
It's justified if AGI is possible. If AGI is possible, then the entire human economy stops making sense as far as money goes, and 'owning' part of OpenAI gives you power. That is of course, assuming AGI is possible and exponential, and that marketshare goes to a single entity instead of a set of entities. Lots of big assumptions. Seems like we're heading towards a slow-lackluster singularity though.
- deleted 2y ago
  [deleted]
- philipkglass 2y ago
  If AGI is possible, then the entire human economy stops making sense as far as money goes, and 'owning' part of OpenAI gives you power. That's if AGI is possible and not easily replicated. If AGI can be copied and/or re-developed like other software then the value of owning OpenAI stock is more like owning stock in copper producers or other commodity sector companies. (It might even be a poorer investment. Even AGI can't create copper atoms, so owners of real physical resources could be in a better position in a post-human-labor world.)
  - whatshisface 2y ago
    This belief comes from confusing the singularity (every atom on Earth is converted into a giant image of Sam Altman) with AGI (a store employee navigates a confrontation with an unruly customer, then goes home and wins at Super Mario).
    - fullstackchris 2y ago
      Exactly. I continually fail to see how "the entire human economy ends" overnight with another human like agent out there - especially if its confined to a server in the first place - it can't even "go home" :)
    - baobabKoodaa 2y ago
      If I recall correctly, these terms were used more or less interchangeably for a few decades, until 2020 or so, when OpenAI started making actual progress towards AGI, and it was clear that the type of AGI that could be imagined at that point, would not be of the type that would produce singularity.
criddell 2y ago
> what justifies this People are buying shares at $x because they believe they will be able to sell them for more later. I don’t think there’s a whole to more to it than that.
ec109685 2y ago
OpenAI is becoming synonymous with consumer AI. It has potential of disrupting Google’s cash cow, which explains at least a chunk of the valuation. OpenAI predicts more revenue from ChatGPT than api access through 2029. It’s the old Netflix / HBO trope of which can become the other first: hbo figure out streaming or Netflix figure out original programming. I bet Google will figure this out and thus OpenAI won’t disrupt as much as people think it will.
- CRConrad 2y ago
  > It’s the old Netflix / HBO trope of which can become the other first: hbo figure out streaming or Netflix figure out original programming. Tangential: So how is that race going, has either taken a commanding lead? (Or, hey, is it over already; has either of them won and the other lost? (Yeah, guess if I'm very well-infomed on that industry or not...))

slimsag 2y ago

Unless the best models themselves are costly/hard to produce, and there is not a company providing them to people free of charge AND for commercial use.

epicureanideal 2y ago

And of course, as processors improve this becomes more and more the case.

refulgentis 2y ago

Been in the Mac ecosystem since 2008, love it, but there is, and always has been, a tendency to talk about inevitabilities from scaling bespoke, extremely expensive configurations, and with LLMs, there's heavy eliding of what the user experience is, beyond noting response generation speed in tokens/s. They run on a laptop, yes - you might squeeze up to 10 token/sec out of a kinda sorta GPT-4 if you paid $5K plus for an Apple laptop in the last 18 months. And that's after you spent 2 minutes watching 1000 token* prompt prefill at 10 tokens/sec. Usually it'd be obvious this'd trickle down, things always do, right? But...Apple infamously has been stuck on 8GB of RAM in even $1500 base models for years. I have 0 idea why, but my intuition is RAM was ~doubling capacity at same cost every 3 years till early 2010s, then it mostly stalled out post 2015. And regardless of any of the above, this absolutely melts your battery. Like, your 16 hr battery life becomes 40 minutes, no exaggeration. I don't know why prefill (loading in your prompt) is so slow for local LLMs, but it is. I assume if you have a bunch of servers there's some caching you can do that works across all prompts. I expect the local LLM community to be roughly the same size it is today 5 years from now. * ~3 pages / ~750 words; what I expect is a conservative average for prompt size when coding

lowercased 2y ago
I have a 2023 mbp, and I get about 100-150 tok/sec locally with lmstudio.
- datadrivenangel 2y ago
  Which models?
  - refulgentis 2y ago
    For context, I got M2 Max MBP, 64 GB shared RAM, bought it March 2023 for $5-6K. Llama 3.2 1.0B - 650 t/s Phi 3.5 3.8B - 60 t/s. Llama 3.1 8.0B - 37 t/s. Mixtral 14.0B - 24 t/s. Full GPU acceleration, using llama.cpp, just like LM Studio.
  - lowercased 2y ago

mjburgess 2y ago

I don't think openai's valuation comes from a data center bet -- rather, I'd suppose, investors think it has a first-mover advantage on model quality that it can (maybe?) attract some buy-out interest or otherwise use in yet-to-be-specified product lines. However, it has been clear for a long time that meta are just demolishing any competitor's moats, driving the whole megacorp AI competition to razor thin margins. It's a very welcome strategy from a consumer pov, but -- it has to be said -- genius from a business pov. By deciding that no one will win, it can prevent anyone leapfrogging them at a relatively cheap price.

hyperpape 2y ago

This seems like a non-sequitur unless you’re assuming something about the amount that people use models. Most web servers can run some number of QPS on a developer laptop, but AWS is a big business, because there are a heck of a lot of QPS across all the servers.

thinkingemote 2y ago

Most of the laptops that the models can run on today are in the high end of dedicated bare metal servers. Most shared VM servers are way below these laptops. Most people buying a new laptop today won't be able to run them, most devs getting a website up with a server won't be able to run them. This means that the definitions of "laptop" and "server" are dependent on use. We should instead talk about RAM, GPU and CPU speed which is more useful and informative but less engaging than "my laptop".

m3kw9 2y ago

The best models are always out of reach on desktops. You can have ok models but AGI will come in a datacenter first