«От глав миссий ожидается, что они будут избегать любых комментариев по вопросам, которые могут усилить напряженность или вызвать путаницу в политике США. Дисциплина в публичных заявлениях крайне важна, особенно в этот период», — говорится в меморандуме.
中国有互联网/AI 巨头，海外何尝不是如此？像 Meta、Amazon 这样的老对手，本身还拥有强势的平台与生态，它们未必心甘情愿对 Google 开放，让 Gemini 来自动化一切。无论是以隐私、安全，还是平台规则为由，设置限制、提高接入门槛，博弈必然发生，争斗将进一步白热化。
，更多细节参见旺商聊官方下载
On X, Kurt Caz dismissed criticism of the thumbnail as "clickbait" and said "if you're going to do a hit piece on me do it properly".
“把推进乡村全面振兴作为新时代新征程‘三农’工作的总抓手”“一步一个脚印，把乡村全面振兴的美好蓝图变为现实，为实现农业农村现代化、建设农业强国奠定基础”……
It’s Not AI Psychosis If It Works#Before I wrote my blog post about how I use LLMs, I wrote a tongue-in-cheek blog post titled Can LLMs write better code if you keep asking them to “write better code”? which is exactly as the name suggests. It was an experiment to determine how LLMs interpret the ambiguous command “write better code”: in this case, it was to prioritize making the code more convoluted with more helpful features, but if instead given commands to optimize the code, it did make the code faster successfully albeit at the cost of significant readability. In software engineering, one of the greatest sins is premature optimization, where you sacrifice code readability and thus maintainability to chase performance gains that slow down development time and may not be worth it. Buuuuuuut with agentic coding, we implicitly accept that our interpretation of the code is fuzzy: could agents iteratively applying optimizations for the sole purpose of minimizing benchmark runtime — and therefore faster code in typical use cases if said benchmarks are representative — now actually be a good idea? People complain about how AI-generated code is slow, but if AI can now reliably generate fast code, that changes the debate.