I'll admit I'm experiencing a degree of pleasure in thinking about how nervous Anthropic and OpenAI must be with their IPOs supposedly coming up.
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Their IPOs are how they cash out and walk away. It's just a matter of "does it crash before or after?". Yes they'll be anxious about getting there, but the fact the market is still behind them and they're this close is very bad for the rest of us.
OpenAI already explicitly postponed their IPO somehow hoping for a better climate to IPO in...
A certainly... optimistic expectation.
What's stopping people from using open sourced trained models? Like, why are tokens going to be needed in the future? Isn't this their whole business model?
The hardware requirements are substantial. If companies or individuals want to run models locally, especially at the speed you'd expect from the big name models, then everyone needs a pretty serious GPU on their work station. That or the company needs to build and maintain a server capable of running whatever loads they expect to see.
None of this is impossible of course. But you pay for the tokens one way or another. Either you pay the upfront cost of the hardware and continuing cost of the electricity to run it, or you pay with the inconvenience of running a model very slowly on lower end hardware, or you pay a subscription for someone else to worry about all that.
This is why local models are still niche. Only hobbyists nerds are willing to go through the trouble of setting up and running a local model. Most companies still are not sure if AI is actually worth it for them. So it's much easier to pay for tokens than the giant upfront cost required to build you own infrastructure.
If the numbers the AI companies are putting up as far as infrastructure cost vs revenue are anything to go by, it probably isn't worth it to most companies.
They don't need to, OpenAI and Anthropic are running at a huge loss to keep it cheaper to use them than to buy the comparable hardware required to replace them. The only way running open source models is cheaper is if you ignore hardware costs, or if you have a very specific and unusual usage pattern (i.e. constant 100% capacity, and not a clock cycle more or less), or if you go with another cloud provider who are also running at a loss.
For enterprise, I think same reasons why companies using paid software instead of open software. Someone else to maintain and blamed if something doesn't work.
They thought they sold tokens, they actually sell marginally (6 months lead) improved models.
If you want it well rounded I can see the argument for enterprise but for me personally I programmed one on my workstation and it’s trained on very specific things I think it barely uses up all 24gb vram I have available.
I'd love more of the msm to pick up these articles.
I need to convince my family this current state of AI is just smoke, mirrors and debt, but i need a normie-credible source to anchor it.
Does anyone know of one? Guardian would do.
Why do you need to convince them?
MSM is too scared to talk about these topics. If the AI companies fall, the global markets will crash. Banks lend out too much money to those companies, same for retirement funds and the owners of those media.
This might be a case of too big to fail and "look out China will use it to destroy us". That's what those AI companies are betting on at this point. Their last hope, apart from continuing the deception for as long as possible.
China is already eating our lunch in everything else. At this point, I'm just gonna learn some mandarin and wear a jade necklace.