The real annoying thing about Opus 4.6/Codex 5.3 is that it’s impossible to publicly say “Opus 4.5 (and the models that came after it) are an order of magnitude better than coding LLMs released just months before it” without sounding like an AI hype booster clickbaiting, but it’s the counterintuitive truth to my personal frustration. I have been trying to break this damn model by giving it complex tasks that would take me months to do by myself despite my coding pedigree but Opus and Codex keep doing them correctly. On Hacker News I was accused of said clickbaiting when making a similar statement with accusations of “I haven’t had success with Opus 4.5 so you must be lying.” The remedy to this skepticism is to provide more evidence in addition to greater checks and balances, but what can you do if people refuse to believe your evidence?
Consider the energy crunch: Global data-center power demand will more than double by 2030, per the International Energy Agency, forcing upgrades to grids, water systems, and connectivity. China’s state grids are embarking on a 5 trillion yuan ($722 billion) expansion explicitly for AI and data centers that is equivalent to 4% of GDP, according to Moody’s. The Qatar Investment Authority has announced a project worth $20 billion (9% of the nation’s GDP), to develop AI data centers and computing infrastructure. And in Korea, despite AI-related spending only accounting for 0.4% of GDP, the country’s recently established sovereign wealth fund is almost exclusively targeted at high-tech industries including AI and chips, while planning to deploy a war chest worth 5.7% of GDP over the next five years.，详情可参考同城约会
AI systems, locked in their data-worlds of text or simulated 3D environments, never even come close to this implicit knowledge. Not yet, at least.，详情可参考搜狗输入法2026
分析师观点出现分化。Evercore ISI 认为，IBM 早已向客户提供多种现代化路径，主机客户仍因可靠性、吞吐量、安全性等因素坚持使用该平台，并重申对 IBM 的「跑赢大盘」评级。