Yes, that's going on optimism. It's also possible that we're 80% there and the rest will take forever, while the loans and investments were taken out now.
the decision i have to make dozens if not hundreds times a day: do i actually look at this crap or trust it blindly and let it slide? I'm honestly reading maybe 20% tops of what "I" produce (and what other people post for my review) I think you do lose skills and understanding that way. Sure, you can always ask the robot to do the tldr for you, but.... yeah, something is still lost, not in a good way.
my way of working is make sure I understand every bit of it. Something is still lost but I feel confident my ability to understand systems is not atrophied at all. And its actually improving because I can crunch through new systems rapidly and have a private tutor. Of course its best supplemented by human team members who actually know whats going on. Its not a panacea. But its incredibly useful
but this crap may take forever to play out even if the outcome is well-known. Self-driving is "here", it's obvious that once it's cheap enough having a human behind a car wheel or a freight truck wheel is an absurd waste of human life (kinda like digging canals with bare hands instead of an excavator), yet truckers and uber drivers are still employed. But everyone knows the writing is on the wall for them.
you can't create a new drug by running a model on a laptop. You can't serve a customer support bot running on a laptop. You can't generate video in bulk for many users on a laptop. So there is still a case for paying others for inference.
Does it justify the valuations? No idea, but some major use cases are still there. That's why they are rushing to implement, OpenAI creating a "deployment company", Anthropic having some pharma rumors, etc.
yes, but at that point even open weight models are not free. Can someone set up the best open-weight model for free and charge pretty much just for GPU usage+operations+margin for inference? yes. But they would have to keep up with how good the private models are. The bet is private models would sell in a similar way at a premium and invest in staying ahead. Is this bet going to work? no idea, don't shoot the messenger.
> yes, but at that point even open weight models are not free. Can someone set up the best open-weight model for free and charge pretty much just for GPU usage+operations+margin for inference? yes.
Or, the company itself can rent the GPU and host the model of their choice on it.
> But they would have to keep up with how good the private models are.
Why? The whole point of the thread is that the marginal gains of using private models is a fraction of the additional cost of using those private models.
IOW, if you really need that improvement over the open models, you can go ahead and pay it. What we are seeing though is that the improvement in general is barely noticeable but the cost is 4x as much.
this is really something. They claim (no idea if true) to have patched 4,000+
signals in 550+ C++ files in Chromium. coveryourtracks.eff.org uses like what, 25 signals?
it's a very handwavey way to "explain" anything. Yes, they make money. But they have competition. And if someone runs out of tokens and switches to deepseek or just goes for a friggin hike in the woods, that does not benefit them. If they get a public image of a ripoff that burns all shit on trivial tasks, that does not do them good either. So there is a limit to this "companies make money" thing.
Sure, fair enough. Clearly, if they increase costs by too much, people will go to their competitors, but those competitors also make money selling tokens, so the whole industry is incentivized to inflate token consumption up to the point of driving people to the competition. And nobody is incentivized to reduce token count.
In fact, the one model with great price/performance is Deepseek v4 Flash and I suspect that they are subsidizing it deeply to get access to everyone’s prompts for training. We may find that they raise prices on the next version (v5) after they’ve mined the user data.
Any AI service that people (and to some extent companies) can afford to pay for today is being heavily subsidized. Will that last forever? I really don't know how those economics work, but I know that bubbles do burst having lived through the dot com burst in 2000. And I know this current one is going to hurt if/when it bursts.
On the issue of the bubble, I’m right there with you, 100%. I’m not sure that “subsidized” is the right word for Anthropic’s or OpenAI’s pricing, though. I’d say it’s forward-priced. Supposedly, they have claimed that inference by itself is profitable; it’s the ongoing training that is not. I don’t know what nuances apply to that, however.
You’d be surprised how often this doesn’t end up happening, especially in languages that are supportive of this style:
Kotlin, Python and Typescript, to name a few. A lot of functions you write are helper functions, wrapper functions, system functions, etc and all 3 languages support making things modules of interconnected concepts, extension functions, etc.
You can make code very readable this way - arguably more readable.
Have you ever had so many tests for a single class that you’ve broken the test class into a package and have a whole file / test class for each big method? Same idea! :)
