Tech evangelists argue that the widespread adoption of generative Al opens up a new era in technology,just as the emergence of personal computers, smartphones and social media gave birth to seemingly limitless business opportunities in earlier times.
技术传道者认为，生成性人工智能的广泛采用开启了技术的新时代，就像早期个人电脑、智能手机和社交媒体的出现催生了看似无限的商业机会一样。

But the widespread adoption of generative AI is also triggering concerns about the theft of copyright, the spread of disinformation and deepfakes and the debasement of knowledge on the world wide web.
但是，生成性人工智能的广泛采用也引发了人们对版权盗窃、虚假信息和深度伪造的传播以及世界互联网上知识贬值的担忧。

Generative AI systems are trained to produce the most statistically probable answer, not the most accurate, and can “hallucinate” facts.
生成式人工智能系统被训练成产生统计学上最有可能的答案，而不是最准确的答案，并且可以对事实产生 "幻觉"。

The digital gold rush around generative AI may also be distracting us from more profound and productive uses of other machine learning models, according to one tech executive. While everyone is fixated on the industry’s “shiny new toy”, researchers have been using machine learning systems to diagnose cancers, model protein structures, optimise electricity grids and design components for heart valves, aero engines or wind turbines.
一位技术主管表示，围绕生成性人工智能的数字淘金热也可能会分散我们对其他机器学习模型的更深刻和富有成效的使用。当所有人都专注于该行业的 "闪亮的新玩具 "时，研究人员一直在使用机器学习系统来诊断癌症、建立蛋白质结构模型、优化电网以及设计心脏瓣膜、航空发动机或风力涡轮机的部件。