What I suspect isn't that AI goes somewhere, but I do think that the cutting edge companies like Anthropic and OpenAI are in a very precarious position. They don't have very much of a moat and the competition has been catching up quick while spending a lot less doing so. IMO, the main thing keeping them alive right now is name recognition.

If I were to make a prediction, it's that ultimately these cheaper models are going end up eating their lunch. I don't think they'll make back the money they've invested and once that reality hits investors, those two companies are sunk.

That, however, is not the end of AI. Nor will it be the end of Nvidia/micron/etc. It will more just be a localized bubble pop that doesn't eliminate the product from the market.

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aogaili 6 hours ago | parent | next [-]

It is not just about cheaper models; it is about integration with the economy.

These models are building deep integrations into companies and the entire economy. Once that stabilizes, it will be like the electricity grid—pumping tokens to fuel decision-making across the entire global society. Good luck unplugging from that.

Furthermore, there is a massive geopolitical aspect to it: those who are already on the Western financial and technical stack will get integrated even deeper now.

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cogman10 6 hours ago | parent [-]

> These models are building deep integrations into companies and the entire economy. Once that stabilizes, it will be like the electricity grid—pumping tokens to fuel decision-making across the entire global society. Good luck unplugging from that.

Much like the electric grid, what we are seeing is a convergence on standard APIs. For example, most of these cheaper models are hosted using APIs compatible with OpenAI. It's not a matter of rewiring your electric plug to work with a different socket standard, instead it's just the process of plugging it into a new socket.

> Furthermore, there is a massive geopolitical aspect to it: those who are already on the Western financial and technical stack will get integrated even deeper now.

Certainly the Chinese models appear to be some of the best when it comes to competition, but they aren't the only ones. There are European models and other US based models which all run for cheaper.

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aogaili 6 hours ago | parent [-]

I see your point, but having worked as a consultant for a few years, I think most companies will opt to stay once things are stable. Once these systems are functional, nobody wants to touch them.

I remember one government project where we wanted to migrate a system from COBOL to a modern stack. The requirement was for the UI to stay exactly the same as the old green terminal; the evaluation criterion was pixel-perfect proximity to the original. We literally had to build terminals using web tech.

These models are not the same as each other. Once they are integrated and working, the incentive to change them is incredibly low. So really, the race is about who can integrate deeper, wider, and faster over the next couple of years—that is what will determine the long-term winners.

This is the exact same playbook we saw with social networks. There is a reason why we have only a handful of them dominating globally, and guess what? It's not because of the tech.

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cogman10 6 hours ago | parent [-]

> the incentive to change them is incredibly low

There is no incentive to rewrite working software in COBOL to something else. You don't really change the people cost of maintaining that code all that much and you incur a huge rewrite cost.

AI is different, it's an ongoing cost to the company. If that cost raises aggressively, you can bet companies will race to eliminate it, no matter how integrated it is. Companies can and do do this all the time.

And the models are close, not the same, but close. That's what matters in LLM stuff in general. If a model is capable of doing the same work for less, it will be chosen. Especially since the switch over cost is often on the level of "point the tool at this URL instead of that URL".

I get what you are saying if this were a more sticky concrete tech that is harder to move away from. But that's simply not the case for these LLMs. A big selling point they have is that they are super flexible.

	▲	aogaili 5 hours ago \| parent [-]
		We might need to agree to disagree on this one. I don't think the transition will be as simple as just flipping a URL. There is an entire legal and technical infrastructure being built around these models and their integration. I think you underestimate an organization's resistance to change once things actually work, as well as the sheer complexity of making that shift. I also expect pressure will eventually drive the cost of running these models down. Power plants are being built, more capable chips are being produced, and a big chunk of the capital right now is being used to scale the physical infrastructure—the data centers and energy grid. Once that stabilizes, these companies will have positive cash flows. Again, it's highly similar to what we saw with the expansion of social networks, just with more aggressive and widespread adoption. Ultimately, a handful of companies are going to provide these core capabilities, just like we have a handful of major cloud providers right now. Why do you think this would change? If anything, the trend toward deep vendor lock-in is even stronger now.

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partiallypro 6 hours ago | parent | prev [-]

The moat is the infrastructure and lock-in. Similar to AWS or anything else. Small data centers can't compete, and similarly people without massive compute won't be able to either (at least not on the enterprise level.) You might get a few edge models, but for huge businesses they will be using OpenAI and Anthropic (and Google/Microsoft/Amazon, etc).

The biggest competitors aren't small models, they are just the traditional players that already have an "in" with enterprises. That I think will start to show its face once this initial round of buildout is complete, which may not be for another 5+ years.

	▲	cogman10 6 hours ago \| parent [-]
		> The biggest competitors aren't small models I disagree. Mainly because those small models are exactly what erode away the moat of needing a giant data center. Those smaller models have been proving themselves to not be far of from the SOTA models. As OpenAI and Anthropic look to raise their prices, businesses will be much more compelled to looking at cheaper models. And if the narrative is "do the same as you did with OpenAI at 1/20th the cost" that's going to sell to a lot of businesses. It certainly cuts into what exactly these companies can sell in general. For example, if I wanted to integrate AI into a product I'd almost certainly not chose OpenAI or Anthropic. That's because they are simply way too expensive and what they'd give me is a lot less. We've actually ran into just this. We needed a classifier for a lot of records, we picked a free model because, as you can imagine, we didn't need something as good as what OpenAI and Anthopic offered and free works.