In particular, we propose an adaptive evaluation method that statistically early terminates a costly hardware measurement without losing much accuracy. We further devise a surrogate model with uncertainty quantification that allows the optimization to adapt to hardware and model heterogeneity better.

This implies that adversarial training can serve as a principled defense against delusive attacks. Thus, the test accuracy decreased by delusive attacks can be largely recovered by adversarial training.

In other words, is deep learning a universal learning paradigm?

In other words, is deep learning a universal learning paradigm?

Never mind the GPT-5 complaints; Sam Altman says he believes ChatGPT is on track to have more conversations per day than all human beings combined. "If you project our growth forward, pretty soon billions of people a day will be talking to ChatGPT," said the CEO of OpenAI during a dinner with journalists in San Francisco. "ChatGPT will be having more conversations, maybe, than all human words put together, at some point. I think it's unreasonable to expect a single model personality or style to work for all of that." The remarks followed the chaotic launch of a long-awaited new flagship model, GPT-5, which some users felt had a less friendly and supportive personality. As part of the launch, OpenAI stopped offering users access to the prior model, GPT-4o.