Using power as feedback is neat because it works when you can’t instrument the target but I wonder how they separate new behavior from boring analog noise, e.g. the clocks
You're referring to the Agentic search, but if you look at the Agentic computer use the cost is basically halved.
However, I am also confused about market positioning. Too expensive to perform daily tasks - open souce models are much cheaper - and not frontier model to address complex real world problems.
> In other words, the Trump administration appears to be pressuring OpenAI to do what Anthropic is already voluntarily doing: keeping its most powerful AI models under wraps.
while I generally agree that models with this level of cyber capability should not necessarily be released to everyone on day one, if a company or developer can meet compliance requirements, they should be eligible - and eligibility should not be based on nationality.
Your point is interesting! And with a Mythos-class model already on the market (e.g. DeepSeek or GLM), will OpenAI and Anthropic be forced to apply the same policy?
In many other european countries, the story doesn't change much - with some exceptions. The irony is that the EU is now discussing EU Inc. a law to let startups incorporate online within 48 hours, for at most €100, under a single optional corporate framework across Europe.
That is exactly the right direction. But for now it is just a proposal
Europe will suffocate under the weight of its own bureaucracy. The sad thing is that it is not new to me, I've heard so many stories like this one. This is the kind of friction that makes founders incorporate elsewhere.
Also, a founder spending months coordinating lawyers banks and tax advisors is not talking to customers or building the product. The opportunity cost here is huge.
Anyway, you are pretty close. One more push, don’t give up. :)
I personally found this NVIDIA move very interesting. Automakers generally do not want to become frontier AI infrastructure companies and they love technology standardization.
The real technical challenge is rappresented by edge cases: a software that is excellent 99.9% of the time can still be unacceptable if the remaining 0.1% contains rare but catastrophic scenarios. And that's why we still don't see many self-driving vehicles on the roads today.
However, NVIDIA has a credible shot because it controls much of the loop - hardware, training infrastructure and simulation environment. If it works they will impose a huge vendor lock-in, difficult to replicate for other competitors.