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Anthropic and other models are roughly par with OpenAI. I would value each of those companies' practical revenue potential as equal for now. The operating cos

Anthropic and other models are roughly par with OpenAI. I would value each of those companies' practical revenue potential as equal for now. The operating costs themselves are eye watering, and the hardware is deprecating. So that has to be subtracted from revenue projections to get something like a real valuation. I would invest in anthropic today, they seem to understand use cases better at the moment. I also think LLMs are wildly over hyped, and they will be shunted to a niche in the next few years, essentially providing autocomplete or search for business tasks for the most part, with strong inroads on video analysis, automated translation, and other classic machine learning & neural net tasks.

fragmede 2y ago
Why would they go backwards in capabilities and get shunted to a niche instead of growing?
- junipertea 2y ago
  Probably as copyright lawsuits settle and they will have to pay for their training data
  - fragmede 2y ago
    that would increase costs, not downgrade capabilities though
    - Jensson 2y ago
      Data holders often ban others from using their data and then create a competitor using it. See Netflix etc. So it is possible that capabilities go down instead of costs going up, simple because data holders would rather create their own service than sell their data.
      - malfist 2y ago
        What's more likely is both. Capabilities go down because companies see their data as their moat, and costs go up as people price their data closer to the real value. See reddit
matusp 2y ago
> I also think LLMs are wildly over hyped, and they will be shunted to a niche in the next few years, essentially providing autocomplete or search for business tasks for the most part, with strong inroads on video analysis, automated translation, and other classic machine learning & neural net tasks. There are many useful tasks that LLMs can automate and they will provide great value for humanity. The problem (for investors) is that it's hard to make people pay for it or make money out of it. This is the same problem Google Search had, and ads seem to be the only way forward here as well.
- throwup238 2y ago
  It's hard to get people to pay for just AI in a way I think is similar to the dotcom companies like WebVan and Pets.com. They couldn't just spin up some software and a website and hope that was enough to create a sustainable business, they still needed to be good at their core competency. I think AI will be just like the web and software: there are a thousand little niches it could be applied to at any business but at the end of the day, it's just an enabling tool. The current hype around LLMs hasn't reached that point yet. Everyone is still selling AI for the sake of AI, which will inevitably fail because they're not good at their core business.
- aswegs8 2y ago
  Why is that? There are many thinkable use cases for the API. Their revenue isnt limited to consumers.

fragmede 2y ago

Why would they go backwards in capabilities and get shunted to a niche instead of growing?

junipertea 2y ago
Probably as copyright lawsuits settle and they will have to pay for their training data
- fragmede 2y ago
  that would increase costs, not downgrade capabilities though
  - Jensson 2y ago
    Data holders often ban others from using their data and then create a competitor using it. See Netflix etc. So it is possible that capabilities go down instead of costs going up, simple because data holders would rather create their own service than sell their data.
    - malfist 2y ago
      What's more likely is both. Capabilities go down because companies see their data as their moat, and costs go up as people price their data closer to the real value. See reddit

matusp 2y ago

> I also think LLMs are wildly over hyped, and they will be shunted to a niche in the next few years, essentially providing autocomplete or search for business tasks for the most part, with strong inroads on video analysis, automated translation, and other classic machine learning & neural net tasks. There are many useful tasks that LLMs can automate and they will provide great value for humanity. The problem (for investors) is that it's hard to make people pay for it or make money out of it. This is the same problem Google Search had, and ads seem to be the only way forward here as well.

throwup238 2y ago
It's hard to get people to pay for just AI in a way I think is similar to the dotcom companies like WebVan and Pets.com. They couldn't just spin up some software and a website and hope that was enough to create a sustainable business, they still needed to be good at their core competency. I think AI will be just like the web and software: there are a thousand little niches it could be applied to at any business but at the end of the day, it's just an enabling tool. The current hype around LLMs hasn't reached that point yet. Everyone is still selling AI for the sake of AI, which will inevitably fail because they're not good at their core business.
aswegs8 2y ago
Why is that? There are many thinkable use cases for the API. Their revenue isnt limited to consumers.