I think the main reason is the Web1.0 design of HN doesn't translate well to small screens.
Reasoning? Or just more generative text?
Each token the model outputs requires it to evaluate all of the context it already has (query + existing output). By allowing it more tokens to "reason", you're allowing it to evaluate the context many times over, similar to how a person might turn a problem over in their heads before coming up with an answer. Given the performance of reasoning models on complex tasks, I'm of the opinion that the "more tokens with reasoning prompting" approach is at least a decent model of the process that humans would go through to "reason".
I'd love to know what "resting" means for this guy practically.
I think that's already the case, isn't it? For instance: https://www.reuters.com/lifestyle/sports/vienna-marathon-win...
> they cannot ban athletes from using illegal shoes during training.
I don't understand why you would in the first place, what would be the reasoning here?
I think one reason for anti-doping regulation is health, you don't want athletes breaking a world record one day and die the next. And doping during training definitely gets you some advantage, sometimes even years after, so the competition is no longer fair. But I don't see the harm with equipment such as shoes, if used only during training.
As for training, that's a pretty contentious topic in the running community right now -- some recent research concluded that training in supershoes might actually impair race performance: https://www.outsideonline.com/health/training-performance/su...
https://en.wikipedia.org/wiki/2024_California_Proposition_6