alt Hacker NewsIf what you're saying is true and accurate, then US-based AI labs are in big trouble. The only saving grace might be some sort of a 'national security' proclamation banning the use of state-of-the-art Chinese (and non-US) models across US federal and state governments and large enterprises (especially ones with federal government contracts), but even still, US AI labs will probably lose out massively on international market if a smaller model can match SOTA of just a few months ago.
There's no way large companies outside the US will pay the "US AI lab" premium if they can get the same workloads done at a fraction of the cost using open-weight models that they can self-host and optimize/fine-tune on.
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It is true. I don't care about having infinite frontier-level intelligence, and I don't care if Fable can one-shot frobnicate a klaxelzorp with a benchmark performance of 97%. I doubt most people do, in fact. I just want something that meets the baseline level of intelligence needed to be a really, really good pair programming agent. It shouldn't have any silly dealbreaker issues involving laziness or hallucinations, it should be smart enough to bounce ideas off of, and it should automate doing tedious boilerplate. And - most of all - I want to be able to afford using it as much as I want. That's what has happened here.
It is amazing how fast it happened. Right now one of my main projects is fully running on DeepSeek flash. My reason was that I was blocked by both of the main US AI labs from working on it because it involves viruses. DeepSeek flash has been killing it since I switched it on, completing the first phase of the project and setting up an iteration in another application space. It isn't the most brilliant model, but it is reliable and I don't have to manage my weekly token allowance. I just spend freely and end up spending only a few dollars a day. Intelligence is going to become a basic commodity. Only special stuff is going to drive us to use special models. And maybe not even that.
If programming in the US to become unconditionally 10x more expensive, then the exodus from the US is about to begin.
It's been true for almost every business. "Cheap and good enough" usually trumps "excellent but expensive". Ikea, McDonald's, Ryanair, AliExpress, Aldi - these brands prove that catering to poor people is more profitable than catering to rich people simply because there are so many poor people that their collective spending power outweights the one of rich people.
I think you're overlooking the fact that for long-horizon tasks, even small errors compound over time and can lead to catastrophic outcomes.
For simple queries, we have reached the threshold since the beginning of the year, and models are good enough from every provider to make a meaningful difference between one another. (ChatGPT, Claude, Gemini, Grok, MuseSpark, Kimi, DeepSeek, GLM...)
The real unlock will be, and you can already see it with GPT-5.6 and Fable-5, to delegate complex enough tasks that will take more than 24 hours to get done and they will not lose track. I'm not talking about a loop, but the actual intelligence to recover from these compounding errors that accumulate in dumber models.
We're still a long way from the intelligence needed to let one of these agents go ahead and supervise multiple layers of sub-agents underneath to do complex orchestration. The future looks very promising and exciting. Imagine having the possibility of a Frontier model orchestrating as many sub-agents as needed that are running on cheaper models like DeepSeek.