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> The usage of LLMs is continuing to increase ~exponentially I would like a source for that statement. Additionally, I want to know by who? Because it certainl

> The usage of LLMs is continuing to increase ~exponentially I would like a source for that statement. Additionally, I want to know by who? Because it certainly isn't end users. Inflating token usage doesn't make it any more economically viable if your user base, b2b or not, hasn't increased with it. On the contrary, that is a worse scenario for providers.

energy123 6mo ago
> I would like a source for that statement The recent enterprise revenue numbers of Anthropic
- dannersy 6mo ago
  So as I said, a self interested metric who also controls how many tokens it takes to get a desirable result from their models.
  - energy123 6mo ago
    Users are willingly paying for larger volumes of tokens. You are layering your own unproven interpretation onto that. I would have arrived at an opposite interpretation given the available facts. Models are becoming more token efficient for the same task, such as ChatGPT 5.3 versus 5.2 which halved the token count, and capabilities show a log relationship with the number of tokens since o1 preview was revealed in September 2024.
    - dannersy 6mo ago
      No, you have gone off in your own tangent. The person you're responding to is talking about money and my point is that you're using a misleading metric. Even if the current user base is paying more for the "exponential token usage", it does not add up to the industry's cost of maintaining and building on this technology, especially since we are not taking into account what that token usage costs the provider. First you said Anthropic as your source, but now you're talking about OpenAI's ChatGPT, who are floundering for a product and user base, which they themselves claim will be profitable through subscriptions at numbers never seen before in a subscription business model.
romanovcode 6mo ago
> Additionally, I want to know by who? 1. As a consultant pretty much every company I have worked with in the last 2 years are doing some kind of in-house "AI Revolution", I'm talking making "AI Taskforce" teams, having weekly internal "AI meetings" and pushing AI everywhere and to everyone. Small companies, SMEs and huge companies. From my observation it is mainly due to C-level being obsessed by the idea that AI will replace/uplift people and revenue will grow by either replacing people or launching features 10x quicker. 2. Did you see software job-boards recently? 9/10 (real) job listings are to do with AI. Either it is fully AI company (99% thin wrapper over Anthropic/OpenAI APIs) or some other SME that needs some AI implementations done. It is truly a breath of fresh air to work for companies that have nothing to do with AI. The biggest laugh/cry for me are those thin wrappers that go down overnight - think all the "create your website" companies that are now completely useless since Ahtropic cut the middleman and created their own version of exactly that.
- dannersy 6mo ago
  Yeah, my only hope is that this is unsustainable, admittedly for selfish reasons. I know plenty of engineers being forced to use these tools whether they want to or not. A lot of which are okay with using AI liberally, but don't particularly like generative AI and see it as pretty irresponsible (which feels more true by the week and it is clear from first hand experience). I don't know, there is a huge gradient of users, but I would argue that in previous revolutionary technologies, we didn't have to force people to use a good tool. I didn't have to be forced to use Google search or Google Maps, tech that is now ubiquitous with western society. It seems really suspect that suits have to enforce the use of something that is supposed to change the way we work and be a force multiplier.
  - romanovcode 6mo ago
    From my limited experience in multiple companies, as stated before I see one very common pattern - The process from feature idea to development is just bad. PMs do not know what exactly they want. C-level interjects in the middle and changes requirements. QAs are unsure what to test because acceptance criteria is vague. C-level strongly believes that AI will fix all these issues. They believe that AI will fix their broken processes. I see strong resemblance with "Agile Development" ~15 years ago. Extremely hyped, noone asked if their org even is a fit for it or need it, and most importantly - the only way to fix agile is to do more agile. Same with AI right now.

energy123 6mo ago

> I would like a source for that statement The recent enterprise revenue numbers of Anthropic

dannersy 6mo ago
So as I said, a self interested metric who also controls how many tokens it takes to get a desirable result from their models.
- energy123 6mo ago
  Users are willingly paying for larger volumes of tokens. You are layering your own unproven interpretation onto that. I would have arrived at an opposite interpretation given the available facts. Models are becoming more token efficient for the same task, such as ChatGPT 5.3 versus 5.2 which halved the token count, and capabilities show a log relationship with the number of tokens since o1 preview was revealed in September 2024.
  - dannersy 6mo ago
    No, you have gone off in your own tangent. The person you're responding to is talking about money and my point is that you're using a misleading metric. Even if the current user base is paying more for the "exponential token usage", it does not add up to the industry's cost of maintaining and building on this technology, especially since we are not taking into account what that token usage costs the provider. First you said Anthropic as your source, but now you're talking about OpenAI's ChatGPT, who are floundering for a product and user base, which they themselves claim will be profitable through subscriptions at numbers never seen before in a subscription business model.

romanovcode 6mo ago

> Additionally, I want to know by who? 1. As a consultant pretty much every company I have worked with in the last 2 years are doing some kind of in-house "AI Revolution", I'm talking making "AI Taskforce" teams, having weekly internal "AI meetings" and pushing AI everywhere and to everyone. Small companies, SMEs and huge companies. From my observation it is mainly due to C-level being obsessed by the idea that AI will replace/uplift people and revenue will grow by either replacing people or launching features 10x quicker. 2. Did you see software job-boards recently? 9/10 (real) job listings are to do with AI. Either it is fully AI company (99% thin wrapper over Anthropic/OpenAI APIs) or some other SME that needs some AI implementations done. It is truly a breath of fresh air to work for companies that have nothing to do with AI. The biggest laugh/cry for me are those thin wrappers that go down overnight - think all the "create your website" companies that are now completely useless since Ahtropic cut the middleman and created their own version of exactly that.

dannersy 6mo ago
Yeah, my only hope is that this is unsustainable, admittedly for selfish reasons. I know plenty of engineers being forced to use these tools whether they want to or not. A lot of which are okay with using AI liberally, but don't particularly like generative AI and see it as pretty irresponsible (which feels more true by the week and it is clear from first hand experience). I don't know, there is a huge gradient of users, but I would argue that in previous revolutionary technologies, we didn't have to force people to use a good tool. I didn't have to be forced to use Google search or Google Maps, tech that is now ubiquitous with western society. It seems really suspect that suits have to enforce the use of something that is supposed to change the way we work and be a force multiplier.
- romanovcode 6mo ago
  From my limited experience in multiple companies, as stated before I see one very common pattern - The process from feature idea to development is just bad. PMs do not know what exactly they want. C-level interjects in the middle and changes requirements. QAs are unsure what to test because acceptance criteria is vague. C-level strongly believes that AI will fix all these issues. They believe that AI will fix their broken processes. I see strong resemblance with "Agile Development" ~15 years ago. Extremely hyped, noone asked if their org even is a fit for it or need it, and most importantly - the only way to fix agile is to do more agile. Same with AI right now.