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A year and a half after ChatGPT brought the subject of artificial intelligence to mass public attention, most people would be forgiven for wondering: when is AI going to make a big difference to my life?
在ChatGPT将人工智能这一话题推向大众视线一年半之后，大多数人都会有这样的疑问：人工智能何时才能给我的生活带来巨大改变？
That question resonates particularly loudly during Big Tech’s annual developer conference season, which began in the middle of May. This is the moment in the year when the tech companies lay out their stalls and try to wow customers with their vision of the immediate tech future.
这个问题在大科技公司(Big Tech)的年度开发者大会季节尤为引人注目，该季节始于5月中旬。这是一年中科技公司展示他们对即将到来的科技未来的愿景，试图用这些愿景来吸引顾客的时刻。
The arrival of ChatGPT may have grabbed the popular imagination, but for most people typing questions into a text-based chatbot is of limited interest. Since then, most of the focus in tech circles has been on the race to build the capabilities needed to deliver generative AI on a mass-market scale, rather than its uses. The headlines have been dominated by news of evermore powerful large language models, the splurge of spending on powerful new chips and the proliferation of huge, power-hungry data centres needed to process AI.
ChatGPT的到来可能引起了大众的想象力，但对于大多数人来说，通过文本聊天机器人输入问题的兴趣有限。此后，科技圈的关注主要集中在竞相构建能够以大规模交付生成式人工智能所需能力的竞赛上，而不是其应用。头条新闻主要被越来越强大的大型语言模型、对强大新芯片的大量投资以及处理人工智能所需的巨大、耗电量大的数据中心的扩散所主导。
Now, these powerful technical capabilities are moving closer to the actual users of technology. The biggest news from Microsoft this month was a new generation of AI-enabled PCs, to be launched this year under the brand Copilot+, which will be powerful enough to handle AI without needing to call on a remote data centre.
现在，这些强大的技术能力正在更接近实际的技术用户。微软(Microsoft)本月最大的消息是推出了一款新一代的AI智能电脑，将在今年以Copilot+品牌推出，它将具备足够的能力来处理AI，而无需调用远程数据中心。
In the process, Microsoft threw down a challenge to Apple with a claim that the new PCs will leapfrog Apple’s MacBooks. An AI arm’s race is now in full swing in the personal computing and smartphone worlds.
在这个过程中，微软向苹果(Apple)发起了挑战，声称新的个人电脑将超越苹果的MacBook。现在，在个人计算和智能手机领域，人工智能的竞赛正如火如荼地进行着。
None of this, though, has done much to answer the overriding questions for most consumers: how — and when — will all this expensive new technology make things better for me? So far, generative AI has brought a proliferation of text boxes online offering to answer questions (including in services such as Meta’s WhatsApp and Instagram); offers to help write emails or documents; and various services that summarise blocks of text, including the web digests that Google has started to provide at the top of its search results. It is unclear yet how much people are actually using these features.
然而，对于大多数消费者来说，这些都没有回答一个最重要的问题：这些昂贵的新技术将如何在何时让我的生活变得更好？到目前为止，生成式人工智能已经在互联网上带来了大量的文本框，用于回答问题（包括在Meta的WhatsApp和Instagram等服务中）；提供帮助撰写电子邮件或文档的服务；以及各种摘要文本的服务，包括谷歌(Google)在其搜索结果顶部开始提供的网页摘要。目前尚不清楚人们实际上有多少在使用这些功能。
As this month’s events have underlined, the tech companies harbour a much bigger ambition than this. Their goal: personal digital assistants capable of anticipating a user’s needs and intermediating much of their online activity, as well as digital agents that can go a step further and take actions on behalf of a user. These ideas were a centrepiece of Google’s event two weeks ago and Microsoft last week, as well as the announcement of a new model from OpenAI, called GPT-4o.
正如本月的事件所强调的那样，科技公司怀有更大的野心。他们的目标是能够预测用户需求并在很大程度上介入其在线活动的个人数字助手，以及能够进一步代表用户采取行动的数字代理人。这些想法是谷歌两周前的活动、微软上周的活动以及OpenAI的新模型GPT-4o的发布的核心内容。
Yet if this is AI’s biggest promise, it is just that — a promise.
然而，如果这是人工智能的最大承诺，那只是一个承诺。
Two fundamental problems remain unsolved. One involves making AI models that are trained on historic data respond understand whatever new situation they are put in and respond appropriately. In the words of Demis Hassabis, head of Google’s AI research division, AI needs to be able to “understand and respond to our complex and dynamic world, just as we do”.
还有两个基本问题尚未解决。其中一个问题是让以历史数据训练的人工智能模型能够理解并适应任何新的情境，并做出恰当的回应。用谷歌人工智能研究部门负责人德米斯•哈萨比斯(Demis Hassabis)的话来说，人工智能需要能够“像我们一样理解和应对我们复杂而动态的世界”。
That is a tall order. The challenge isn’t just to avoid the “hallucinations”, or occasional glaring mistakes, that AI systems are prone to. It also means having a full understanding of context, in order to consistently deliver truly helpful results. Google claims to have made big strides in this department, building an extended “context window” into its latest Gemini models to enable the system to maintain an awareness of complex situations. But if the technology needs to match humans in its understanding of the world, there is a lot still to prove.
这是一个艰巨的任务。挑战不仅在于避免AI系统容易出现的“幻觉”或偶尔的明显错误，还需要对上下文有全面的理解，以便始终提供真正有帮助的结果。谷歌声称在这方面取得了重大进展，将扩展的“上下文窗口”引入其最新的双子座(Gemini)模型，以使系统能够保持对复杂情况的意识。但是，如果这项技术需要与人类在对世界的理解上相匹敌，仍有很多事情需要证明。
Another, related problem is to make communicating with AI as natural as talking to a person. Only at that point, according to the people building the systems, will the technology come into its own.
另一个相关问题是如何使与人工智能的交流像与人交谈一样自然。只有到了那个时候，根据构建这些系统的人们所说，技术才能真正发挥其潜力。
Microsoft chief executive Satya Nadella said this would involve learning “how to build computers that understand us, instead of us having to understand computers”. Despite his claim that this goal is tantalisingly close to being realised, others, including Hassabis, warn that trying to produce “natural” interactions with a computer remains “a very high bar”.
微软首席执行官萨蒂亚•纳德拉(Satya Nadella)表示，这将涉及学习“如何构建能理解我们的计算机，而不是我们必须理解计算机”。尽管他声称这一目标离实现令人心动地近了，但包括哈萨比斯在内的其他人警告称，试图实现与计算机的“自然”互动仍然是“一个非常高的门槛”。
OpenAI gave one glimpse of what might lie ahead with a demonstration of GPT-4o, an AI model designed to work in an informal, conversational style. Yet the gap between a staged demonstration and an effective, real-world product is still large. It remains hard to predict when AI will make its big breakthrough into the consumer world.
OpenAI展示了GPT-4o，这是一个设计用于非正式、对话式风格的AI模型，为未来可能出现的情景提供了一瞥。然而，一个预先排练过的演示和一个有效的现实世界产品之间的差距仍然很大。很难预测AI何时会在消费者世界取得重大突破。
