5 ms·

Pretty easy to hit $100 an hour using Opus on API credits. The model providers are heavily subsidized, the datacenters appear to be too. If you look at the Core

• SV_BubbleTime 1y ago
  > Pretty easy to hit $100 an hour I don’t see how that can be true, but if it is… Either you, or I are definitely use Claude Code incorrectly.
  • shinycode 1y ago
    It’s definitely easy with an API key I hit 200$ in an evening. I didn’t think that could be possible. Horrifying
    • DANmode 1y ago
      To be clear, this is a lot of full-scale reading and (re)writing, without any rules, promots, "agents"/code to limit your resource usage, right? Nobody's asking for $200 in single-line diffs in less than a day - right?
      • shinycode 1y ago
        It’s not about a single line diff but the same prompts with cursor does not end costing that much
        • DANmode 1y ago
          Yes - do you understand why?
          • shinycode 1y ago
            Yes I do, it’s just for new comers who are used to cursor where, without careful prompting you just lock yourself out of premium requests, that’s not immediately a given that CC is more dangerous and does not work the same way at all. Of course it requires careful planning but the trap is easy to fall into.
            • DANmode 1y ago
              In my experience, it's more about the tool's local indexing and aggressive automatic upload and model usage limitations to avoid them (and you) overpaying. People are recreating this with local toolchains now.
      • AJ007 1y ago
        Right, this is having Claude Code just running as an agent doing a lot of stuff. Also tool use is a big context hog here.
  • macrolime 1y ago
    This is around what what Cursor was costing me with Claude 4 Opus before I switched to Claude Code. Sonnet works fine for some things, but for some projects it spews unusable garbage, unless the specification is so detailed that it's almost the implementation already.
    • SV_BubbleTime 1y ago
      > unless the specification is so detailed that it's almost the implementation already. You mean… it’s almost exactly like working with interns and jr developers? ;)
      • macrolime 1y ago
        Yeah, it's like an idiot savant intern who has memorized all the API docs in the world, but still somehow struggles to work independently.
        • calgoo 1y ago
          And never remembers what we talked about 5 minutes ago on a different thread.
          • spopejoy 1y ago
            This is where something like Perplexity's "memory" feature is really great. It treats other threads similarly to web resources. I would love to understand better just how Perplexity is able to integrate up-to-date sources like other theads (and presumably recent web searches, but I haven't verified this, they could be just from the latest model) into it's query responses. It feels seamless.
• manmal 1y ago
  The SOTA models will always run in data centers, because they have 5x or more VRAM and 10-100x the compute allowance. Plus, they can make good use of scaling w/ batch inference which is a huge power savings, and which a single developer machine doesn’t make full use of.
• dostick 1y ago
  Why “no capitalism required”? Competition of this kind is only possible with capitalism.
  • tsimionescu 1y ago
    Not really, it's possible with any market economy, even a hypothetical socialist one (that is, one where all market actors are worker-owned co-ops). And, since there is no global super-state, the world economy is a market economy, so even if every state were a state-owned planned economy, North Korea style, still there would exist this type of competition between states.
    • 0xDEAFBEAD 1y ago
      I mean, if you wanna get technical, many companies in Silicon Valley are worker-owned (equity compensation)
      • tsimionescu 1y ago
        They are not worker owned, they have some small amount of worker ownership. But the majority of stock is never owned by workers, other than the CEO.
        • 0xDEAFBEAD 1y ago
          Consider also that VC funds often have pension funds as their limited partners. Workers have a claim to their pension, and thus a claim to the startup returns that the VC invests in. So yeah it basically comes down to your definition of "worker-owned". What fraction of worker ownership is necessary? Do C-level execs count as workers? Can it be "worker-owned" if the "workers" are people working elsewhere? Beyond the "worker-owned" terminology, why is this distinction supposed to matter exactly? Supposing there was an SV startup that was relatively generous with equity compensation, so over 50% of equity is owned by non-C-level employees. What would you expect to change, if anything, if that threshold was passed?
• mark_l_watson 1y ago
  Your excellent comments make me grateful that I am retired and just work part time on my own research and learning. I believe you when you say professional developers will need large inference compute budgets. Probably because I am an old man, but I don’t personally vibe with full time AI assistant use, rather I will use the best models available for brief periods on specific problems. Ironically, when I do use the best models available to me it is almost always to work on making weaker and smaller models running on Ollama more effective for my interests. BTW, I have used neural network tech in production since 1985, and I am thrilled by the rate of progress, but worry about such externalities as energy use, environmental factors, and hurting the job market for many young people.
  • AJ007 1y ago
    I've been around for a while (not quite retirement age) and this time is the closest to the new feeling I had using the internet and web in the early days. There are simultaneously infinite possibilities but also great uncertainty what pathways will be taken and how things will end up. There are a lot of parts in the near term to dislike here, especially the consequences for privacy, adtech, energy use. I do have concerns that the greatest pitfalls in the short terms are being ignored while other uncertainties are being exaggerated. (I've been warning on deep learning model use for recommendation engines for years, and only a sliver of people seem to have picked up on that one, for example.) On the other hand, if good enough models can run locally, humans can end up with a lot more autonomy and choice with their software and operating systems than they have today. The most powerful models might run on supercomputers and just be solving the really big science problems. There is a lot of fantastic software out there that does not improve by throwing infinite resources at it. Another consideration is while the big tech firms are spending (what will likely approach) hundreds of billions of dollars in a race to "AGI", what matters to those same companies even more than winning is making sure that the winner isn't a winner takes all. In that case, hopefully the outcome looks more like open source.