Remember the early days of Uber and Lyft, when rides were dirt cheap because the companies were operating at a loss in order to capture the minds/wallets of the masses?
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Remember the early days of Uber and Lyft, when rides were dirt cheap because the companies were operating at a loss in order to capture the minds/wallets of the masses?
The rug pull in the AI/LLM world when the companies adjust pricing to actually make a profit is going to be spectacular. Especially when you consider the numbers of people / orgs that are addicted to or dependent on such technology.
@wdormann what if it took 5 or 10 years maybe until there were cost-reflective pricing for llms?
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Companies and people don't care. They're looking at replacing people, especially at the junior level, but the junior simpler jobs are how people train up to be architects or experts. We're no longer giving them that chance.
The cost doesn't matter, as long as it's cheaper than a full time junior person being replaced.
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Remember the early days of Uber and Lyft, when rides were dirt cheap because the companies were operating at a loss in order to capture the minds/wallets of the masses?
The rug pull in the AI/LLM world when the companies adjust pricing to actually make a profit is going to be spectacular. Especially when you consider the numbers of people / orgs that are addicted to or dependent on such technology.
Is uber still operating at a loss?
Last I heard they have yet to turn a profit because they're trying to undercut all the competition
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Remember the early days of Uber and Lyft, when rides were dirt cheap because the companies were operating at a loss in order to capture the minds/wallets of the masses?
The rug pull in the AI/LLM world when the companies adjust pricing to actually make a profit is going to be spectacular. Especially when you consider the numbers of people / orgs that are addicted to or dependent on such technology.
@wdormann already starting to happen. See the recent GitHub copilot price increases.
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Remember the early days of Uber and Lyft, when rides were dirt cheap because the companies were operating at a loss in order to capture the minds/wallets of the masses?
The rug pull in the AI/LLM world when the companies adjust pricing to actually make a profit is going to be spectacular. Especially when you consider the numbers of people / orgs that are addicted to or dependent on such technology.
@wdormann except we’re not dependent on llm
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Remember the early days of Uber and Lyft, when rides were dirt cheap because the companies were operating at a loss in order to capture the minds/wallets of the masses?
The rug pull in the AI/LLM world when the companies adjust pricing to actually make a profit is going to be spectacular. Especially when you consider the numbers of people / orgs that are addicted to or dependent on such technology.
@wdormann@infosec.exchange next upgrade cycle everybody is going to want a laptop that can run local LLMs
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Remember the early days of Uber and Lyft, when rides were dirt cheap because the companies were operating at a loss in order to capture the minds/wallets of the masses?
The rug pull in the AI/LLM world when the companies adjust pricing to actually make a profit is going to be spectacular. Especially when you consider the numbers of people / orgs that are addicted to or dependent on such technology.
@wdormann while I am critical about LLMs (but also use them) and it is clear that companies are currently trying to capture/create the market through losses, there is another scenario where LLM training/inference gets much cheaper through technological advances. But I am not sure of how probable this is.
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Companies and people don't care. They're looking at replacing people, especially at the junior level, but the junior simpler jobs are how people train up to be architects or experts. We're no longer giving them that chance.
The cost doesn't matter, as long as it's cheaper than a full time junior person being replaced.
@hittitezombie @crispius @wdormann @witchescauldron when I first started in this industry, decades ago now, I apologized for taking up so much of a senior engineer's time helping me solve a problem. His response has stuck with me ever since: "my most important deliverable to the company is more senior engineers".
The short sighted murdering of that pipeline in many modern orgs is *shocking* to me
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Remember the early days of Uber and Lyft, when rides were dirt cheap because the companies were operating at a loss in order to capture the minds/wallets of the masses?
The rug pull in the AI/LLM world when the companies adjust pricing to actually make a profit is going to be spectacular. Especially when you consider the numbers of people / orgs that are addicted to or dependent on such technology.
@wdormann the plan is: try to keep your job until that moment. Then find another position at a company that fired all devs and got the rug pulled from under it. Demand the appropriate salary. It will be absolutely glorious!!
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Remember the early days of Uber and Lyft, when rides were dirt cheap because the companies were operating at a loss in order to capture the minds/wallets of the masses?
The rug pull in the AI/LLM world when the companies adjust pricing to actually make a profit is going to be spectacular. Especially when you consider the numbers of people / orgs that are addicted to or dependent on such technology.
@wdormann they wait until all true developers have been eliminated, and then rise prices. Companies won't be able to hire back. Profit!
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@wdormann while I am critical about LLMs (but also use them) and it is clear that companies are currently trying to capture/create the market through losses, there is another scenario where LLM training/inference gets much cheaper through technological advances. But I am not sure of how probable this is.
@aaronkurz @wdormann Already happening. That's why Apple is suddenly out of Mac Minis and Mac Studios. Forward-thinking PC developers will be ready to pivot to that market when the current server boom busts. (You can be sure Apple is ramping up supply chains for relevant hardware in a massive way right now.)
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Remember the early days of Uber and Lyft, when rides were dirt cheap because the companies were operating at a loss in order to capture the minds/wallets of the masses?
The rug pull in the AI/LLM world when the companies adjust pricing to actually make a profit is going to be spectacular. Especially when you consider the numbers of people / orgs that are addicted to or dependent on such technology.
@wdormann Do you think companies that start installing LLMs directly on users' machines may have an edge in this war? Considering they're offloading the price of energy onto the end user?
https://www.thatprivacyguy.com/blog/chrome-silent-nano-install/
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Remember the early days of Uber and Lyft, when rides were dirt cheap because the companies were operating at a loss in order to capture the minds/wallets of the masses?
The rug pull in the AI/LLM world when the companies adjust pricing to actually make a profit is going to be spectacular. Especially when you consider the numbers of people / orgs that are addicted to or dependent on such technology.
@wdormann Yeah; I've been sandbagging on AI even though my org is all-in, partly because I really don't see the benefit, but _mostly_ because it was obvious what would happen as soon as AI was fully integrated into the workflow because _the exact same_ thing has happened with:
- Ride share services
- Streaming services
- Cloud servicesWhen the heroin dealer comes around with "free samples", you don't proffer your veins, you stay away!
This is exactly the same business model. -
Remember the early days of Uber and Lyft, when rides were dirt cheap because the companies were operating at a loss in order to capture the minds/wallets of the masses?
The rug pull in the AI/LLM world when the companies adjust pricing to actually make a profit is going to be spectacular. Especially when you consider the numbers of people / orgs that are addicted to or dependent on such technology.
@wdormann That's why I won't pay.
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Remember the early days of Uber and Lyft, when rides were dirt cheap because the companies were operating at a loss in order to capture the minds/wallets of the masses?
The rug pull in the AI/LLM world when the companies adjust pricing to actually make a profit is going to be spectacular. Especially when you consider the numbers of people / orgs that are addicted to or dependent on such technology.
-
Remember the early days of Uber and Lyft, when rides were dirt cheap because the companies were operating at a loss in order to capture the minds/wallets of the masses?
The rug pull in the AI/LLM world when the companies adjust pricing to actually make a profit is going to be spectacular. Especially when you consider the numbers of people / orgs that are addicted to or dependent on such technology.
@wdormann haha, the same for the crack heroin that is called “AWS” ¯\_(ツ)_/¯
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Remember the early days of Uber and Lyft, when rides were dirt cheap because the companies were operating at a loss in order to capture the minds/wallets of the masses?
The rug pull in the AI/LLM world when the companies adjust pricing to actually make a profit is going to be spectacular. Especially when you consider the numbers of people / orgs that are addicted to or dependent on such technology.
@wdormann Perhaps of interest https://www.wheresyoured.at/ais-economics-dont-make-sense/
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Remember the early days of Uber and Lyft, when rides were dirt cheap because the companies were operating at a loss in order to capture the minds/wallets of the masses?
The rug pull in the AI/LLM world when the companies adjust pricing to actually make a profit is going to be spectacular. Especially when you consider the numbers of people / orgs that are addicted to or dependent on such technology.
@wdormann
I think the difference might be that Uber and Lyft provide actual services, even if they are leeches and screw their employees to death. Whereas AI doesn't provide anything of any real value anyway. -
Remember the early days of Uber and Lyft, when rides were dirt cheap because the companies were operating at a loss in order to capture the minds/wallets of the masses?
The rug pull in the AI/LLM world when the companies adjust pricing to actually make a profit is going to be spectacular. Especially when you consider the numbers of people / orgs that are addicted to or dependent on such technology.
@wdormann
I'm just using API pricing up front to make sure the economics still work out.
The $20/month plans will go away and the $200/month plans will be scaled back, probably. -
@wdormann Do you think companies that start installing LLMs directly on users' machines may have an edge in this war? Considering they're offloading the price of energy onto the end user?
https://www.thatprivacyguy.com/blog/chrome-silent-nano-install/
@mdm @wdormann Yes. That will reduce the blood loss. You still have to train it, but you can train it once for all users, you can even distribute the training for the next model among your users too. The problem is efficiency, cloud providers *could* get efficiency through scale, use renewable energy, reuse cooling water. They typically dont, they do whatever is cheapest which is usually to freeload on the local town's resources.
