When people say the AI bubble is about to bust, I don't think anybody means that "the use of AI is going to go away." AI is absurdly useful. I think what people mean is "the valuations of these companies will have to snap to a reality that is actually attached to their market value."
Exactly, small edge models is the future, highly personal experiences, and not these massive models that the cloud providers currently shove down our throats. While massive models are useful, these massive platforms are about to burst out of their promises. All while we’re supper happy with tiny 4b up to 12b models working amazing for all these “omg ai thinks” daily tasks.
We used to not know, but now because open source models are being hosted and served by people whose only incentive is making profit on directly running inference, we have a ballpark idea.
There's no reason to think that the latest frontier models have similar inference costs to open source models.
It would be more surprising if the surrounding architecture hasn't significantly diverged. If it _hasn't_ significantly diverged, then given the performance difference it would imply that the frontier models have significantly greater param counts, which would result in a higher cost.
No we have no idea that the open source inference market isn’t being kept artificially low because some of the operators are operating a loss hoping to gain market share. All it takes is a few and everyone else has to lower prices to compete while they hope for lower costs and subsidies to dry up.
We also have to assume that these operators are correctly pricing GPU depreciation, and the market is so new there is no reason to believe they are.
My Catherine thanks you for the golden ring, whom I have hardly ever seen more indignant than when she realized that it had been stolen or lost through her own negligence (which is not likely for me, although I still insist on it), which I had persuaded her that this gift was a happy omen and augury sent to her, as if it were now certain that your Church would agree pleasantly with ours; this grieves the woman wonderfully.
The human mind is capable of the same thing, you know? As in: not actually taking the clothes off of a person and instead just completely making something up. I hereby give permission to all AI, and human minds, to completely make up what I look like naked.
What's puzzling or schizophrenic about that? Those seem like two very natural factors that would be in tension with one another and have to be balanced.
PaymentMethods = a specific credit card, debit card, etc. Payment Method is basically a term of art so ubiquitous that it's user-facing in UIs and has nothing to do with Stripe.
PaymentIntents is definitely a Stripe abstraction, however, but that's one that I like. It's been a while since I used it, but I remember liking that it allowed me to bundle up everything related to the payment, i.e. the amount, the payment method, etc, and pass it around between server, client, and different views in the client, such that you could really build the exact payment flow you want without touching PCI data.
The Stripe abstractions I have always felt are much clunkier are the distinctions between Products/Prices/Subscriptions/SubscriptionSchedules, etc. A lot of "what lives where?" with those; very clunky to work with.
I'm pretty sure that all Stripe abstractions and layers they do have a merit. No doubt and I'm being serious here.
However:
PaymentIntent, InvoiceCreationIntent, InvoiceCreationSession, InvoiceCharge. InvoiceChargeIntent, InvoiceChargeSession, InvoiceChargeSessionIntent, InvoiceChargeSessionIntentSession, InvoiceChargeSucceed, InvoicePaid, InvoiceFinalized, and so on.
All of those can absolutely be explained in a way that justifies their existence.
But in the end systems end up incurring so much mental tax that no one wants to really have to do anything with it.
Stripe began as a company to outsource complexity to and then grew to become a source of complexity itself.
That feels like it wouldn't provide a useful comparison, because the people who were going to bet on sports when LV was the legal place to do it, would go to LV to do it. Their delinquency rates wouldn't necessarily be reflected in LV, though, since they've come from elsewhere to do it.
I'm a software engineer that, like the vast majority of you, uses AI/agents in my workflow every day. That being said, I have to admit that it feels a little weird to hear someone who does not write code say that they built something, without even mentioning that they had an agent build it (unless I missed that).
> Be Proactive: The user is highly technical (a VFX professional/coder). Skip basic tutorials and dive straight into advanced implementation, but be sure to document math thoroughly.
Back when I played with animation and post pipelines, I was writing a decent amount of python. It's part of how I got into programming. At the time I would have said I can't program, and I suspect this guy is similar.
It's actually a bit refreshing that they didn't brand this with the usual "LLM hype". And it's actually a good example of someone using LLMs to solve a problem by bringing in their domain knowledge. (The solution is surprisingly simple though, I wonder if other people have done this before but kept it proprietary/in-house).
This is interesting. I had the exact opposite reaction.
You don't hear architects get hounded because they say they "built" some building even though it was definitely the guys swinging hammers that built it. But yet, somehow because he didn't artisanally hand-craft the code, he needs to caveat that he didn't actually build it?
Maybe it's a language thing. Architects saying they built something sounds a bit off to me. In my native language, and in everyday language, I don't think people would use "built" like that. I don't know how architects talk with each other, though.
There were definitely many keygens I would open just to have on in the background.
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