From prophet to product: How AI came back down to earth in 2025
摘要
经过2023和2024年的巨大炒作，2025年成为基于大语言模型的AI产业回归务实的一年。公众讨论逐渐从将AI视为文明威胁或未来神祇的宏大叙事，转向承认其虽不完美但极具实用价值的工具属性。尽管关于人工通用智能（AGI）的远景宣称依然存在，业界日益认识到其背后的商业营销色彩。当前，商业模型构建者面临的核心挑战是如何开发可靠、实用的AI解决方案以实现盈利。这种务
Following two years of immense hype in 2023 and 2024, this year felt more like a settling-in period for the LLM-based token prediction industry. After more than two years of public fretting over AI models as future threats to human civilization or the seedlings of future gods, it's starting to look like hype is giving way to pragmatism: Today's AI can be very useful, but it's also clearly imperfect and prone to mistakes.
That view isn't universal, of course. There's a lot of money (and rhetoric) betting on a stratospheric, world-rocking trajectory for AI. But the "when" keeps getting pushed back, and that's because nearly everyone agrees that more significant technical breakthroughs are required. The original, lofty claims that we're on the verge of artificial general intelligence (AGI) or superintelligence (ASI) have not disappeared. Still, there's a growing awareness that such proclaimations are perhaps best viewed as venture capital marketing. And every commercial foundational model builder out there has to grapple with the reality that, if they're going to make money now, they have to sell practical AI-powered solutions that perform as reliable tools.
This has made 2025 a year of wild juxtapositions. For example, in January, OpenAI's CEO, Sam Altman, claimed that the company knew how to build AGI, but by November, he was publicly celebrating that GPT-5.1 finally learned to use em dashes correctly when instructed (but not always). Nvidia soared past a $5 trillion valuation, with Wall Street still projecting high price targets for that company's stock while some banks warned of the potential for an AI bubble that might rival the 2000s dotcom crash.
转载信息
评论 (1)
