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dvttoday at 5:26 PM4 repliesview on HN

I think OpenAI and Anthropic will go bust, or at least be scrapped for parts in the next 5 years or so. It's clear that the extreme cost used up for training is impossible to recoup, as inference is already being subsidized.

It's also clear that, as Tan indicates, open-weight models will be (and basically already are) just as good as frontier models. It's all about the harness, baby. We will have two main forks in the road, and two new industries created:

    - AI hardware (NVidia/Cerebras/etc.), the equivalent of Intel/AMD
    - AI software (harnesses, assistants, etc.) the equivalent of Microsoft/Apple
We already saw a glimmer of this with popularity of OpenClaw—the problem is that it's janky, hard to set up, inconsistent, and very hacker-esque. Imo "AI labs" will be a dying breed because there's no real money in the actual models if they get commoditized, which they already kind of are.

Replies

kilroy123today at 9:33 PM

I think this is very possible. Plus, something I don't see talked about enough here. The VERY fragile supply chain that keeps it all going. Look at what is happening in the Middle East.

The US can no longer keep global trade secure on the high seas. What if the supply chains for GPUs get disrupted for months, a year? Then what?

I fear Google will win in the longer run.

Legend2440today at 6:29 PM

>inference is already being subsidized.

Inference is not being subsidized and in fact has pretty high margins.

Similar-sized open weight models on openrouter are 15x cheaper per token than the big labs. This should reflect the isolated cost of inference, since 3rd party hosts have no reason to subsidize and no training costs to amortize.

Only datacenter buildout costs are being subsidized.

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hn993302today at 10:33 PM

If inference needs to be subsidized to be economical (idk if true), open models have the same problem.

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FanaHOVAtoday at 6:03 PM

If harness is all that matters, a co-developed harness + model stack + large compute availability advantage + massive distribution advantage with data for post training will win the market.

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