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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將人工智慧這一話題推向大衆視線一年半之後，大多數人都會有這樣的疑問：人工智慧何時才能給我的生活帶來巨大改變？
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.
這個問題在大科技公司(Big Tech)的年度開發者大會季節尤爲引人注目，該季節始於5月中旬。這是一年中科技公司展示他們對即將到來的科技未來的願景，試圖用這些願景來吸引顧客的時刻。
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的到來可能引起了大衆的想像力，但對於大多數人來說，透過文字聊天機器人輸入問題的興趣有限。此後，科技圈的關注主要集中在競相構建能夠以大規模交付生成式人工智慧所需能力的競賽上，而不是其應用。頭條新聞主要被越來越強大的大型語言模型、對強大新晶片的大量投資以及處理人工智慧所需的巨大、耗電量大的數據中心的擴散所主導。
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.
現在，這些強大的技術能力正在更接近實際的技術用戶。微軟(Microsoft)本月最大的訊息是推出了一款新一代的AI智慧電腦，將在今年以Copilot+品牌推出，它將具備足夠的能力來處理AI，而無需調用遠距數據中心。
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.
在這個過程中，微軟向蘋果(Apple)發起了挑戰，聲稱新的個人電腦將超越蘋果的MacBook。現在，在個人計算和智慧型手機領域，人工智慧的競賽正如火如荼地進行著。
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，對於大多數消費者來說，這些都沒有回答一個最重要的問題：這些昂貴的新技術將如何在何時讓我的生活變得更好？到目前爲止，生成式人工智慧已經在網路上帶來了大量的文字框，用於回答問題（包括在Meta的WhatsApp和Instagram等服務中）；提供幫助撰寫電子郵件或文檔的服務；以及各種摘要文字的服務，包括谷歌(Google)在其搜索結果頂部開始提供的網頁摘要。目前尚不清楚人們實際上有多少在使用這些功能。
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.
正如本月的事件所強調的那樣，科技公司懷有更大的野心。他們的目標是能夠預測用戶需求並在很大程度上介入其在線活動的個人數字助手，以及能夠進一步代表用戶採取行動的數字代理人。這些想法是谷歌兩週前的活動、微軟上週的活動以及OpenAI的新模型GPT-4o的發佈的核心內容。
Yet if this is AI’s biggest promise, it is just that — a promise.
然而，如果這是人工智慧的最大承諾，那只是一個承諾。
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”.
還有兩個基本問題尚未解決。其中一個問題是讓以歷史數據訓練的人工智慧模型能夠理解並適應任何新的情境，並做出恰當的回應。用谷歌人工智慧研究部門負責人德米斯•哈薩比斯(Demis Hassabis)的話來說，人工智慧需要能夠「像我們一樣理解和應對我們複雜而動態的世界」。
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.
這是一個艱鉅的任務。挑戰不僅在於避免AI系統容易出現的「幻覺」或偶爾的明顯錯誤，還需要對上下文有全面的理解，以便始終提供真正有幫助的結果。谷歌聲稱在這方面取得了重大進展，將擴展的「上下文視窗」引入其最新的雙子座(Gemini)模型，以使系統能夠保持對複雜情況的意識。但是，如果這項技術需要與人類在對世界的理解上相匹敵，仍有很多事情需要證明。
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.
另一個相關問題是如何使與人工智慧的交流像與人交談一樣自然。只有到了那個時候，根據構建這些系統的人們所說，技術才能真正發揮其潛力。
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”.
微軟首席執行長薩蒂亞•納德拉(Satya Nadella)表示，這將涉及學習「如何構建能理解我們的電腦，而不是我們必須理解電腦」。儘管他聲稱這一目標離實現令人心動地近了，但包括哈薩比斯在內的其他人警告稱，試圖實現與電腦的「自然」互動仍然是「一個非常高的門檻」。
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，這是一個設計用於非正式、對話式風格的AI模型，爲未來可能出現的情景提供了一瞥。然而，一個預先排練過的演示和一個有效的現實世界產品之間的差距仍然很大。很難預測AI何時會在消費者世界取得重大突破。