如果你已经与Claude,ChatGPT,Gemini等类似人互动，你注意到除了他们所做的其他一切之外，这些AI聊天器还可以为您搜索网络。 Google如此热衷于将AI Mode推向自己的搜索引擎。
当被要求搜索网络时，这些bots的最新版本正在结合传统网页搜索(他们基本上只是代表你呻吟)的元素与他们能够从训练数据中抽出的知识。 然后，每件事物都被包装和格式化为现在的熟知，抛光的基因AI风格。
也就是说AI动力搜索可能并不总是最佳选择。
何时使用AI进行网络搜索
如果你在寻找一些简单而广为人知的事物，这种信息不仅容易在线访问，大语言模型所偏爱的“自动校正”概率模式意味着，你看到的结果包括正确信息的可能性几乎可以确定。
如果你需要快速检查，AI是好的。 不过，这个问题越是模糊不清，你就越需要仔细研究答案。 如果你问了一些不太为人所知的问题，比如在一部模糊的电视剧中第五位出票的演员，那么在网络上可能只有一两次提到它，一个AI可能选错了。
最近斯坦福大学研究的外卖之一是，当AI 发现是一个准确的来源时，它非常擅长从中抽出正确的信息。 在它倾向于倒塌的地方，就是没有找到准确的来源(要么是因为没有，要么是因为询问被误解)，反正也提出了自信的答案。
AI搜索也有帮助，当你有一个复杂的查询，一个标准的Google搜索将无法解析："我需要知道旧金山最好的餐厅对于一个五人家庭来说，他们想要花费不超过200美元". AI能够查询和整理多个来源，以响应这样的搜索，然后给出一个精密的解答。 一个传统的网络搜索会给你一个蓝链接列表，这些链接很可能只是按照更基本的标准对旧金山餐馆进行排名。
不过，资料来源也至关重要。 AI bots从来没有去过旧金山或者在那里吃。 他们依靠网络上的公开账户，在没有确切的页面匹配时，他们会寻找相关的单词(如"负担得起的"或"家庭")并生成一个答案。
对于网上有很多信息的查询，比如旧金山餐馆，AI网络搜索可以感到令人难以置信的有用。 对于不太受欢迎的目的地和更具体的要求("像恒星形状的饮食表")，你需要更加小心地处理结果，因为此时点的AI 加入变得不那么可靠。
因此，在提醒你应该总是做某种重复检查的情况下，AI网络搜索最能处理常见的查询，这些查询很可能导致很多准确，最新的在线信息。 无论是处理搜索查询的方式，还是组合和合成答案的方式，AI聊天器都是在浏览器上的重大升级。
不使用AI进行网络搜索时
基因化的AI bots和LLMs的组合方式，意味着它们在拓扑，合成，总结时最有效。 但这些过程也可能引入错误。 如果您的搜索需要精确的细节(如名人引文，报告 stat，或设备规格)，传统的Google搜索可能效果最好。
前往Google并搜索旧方式也可能更好，如果你想完全控制所使用的来源。 向AI卸载网页搜索是方便的，但是你依靠它们来正确解释你的搜索，找到正确的来源，然后从这些来源提取准确的信息。 虽能节省时间，但更为不透明。
如果您知道您最信任的科技新闻网站，例如，您可以在传统的网络搜索中优先排序，以AI可能无法做到的方式。 来自UC圣迭戈的研究人员发现，AI网页搜索有时会选择来源，因为它们与查询更相关，而不是因为它们被排名为更具权威性。
如果AI认为个人博客更接近用户实际搜索内容，这个选择你扫描一个传统的结果列表时不太可能做出，因为你通常会选择你最信任的。
传统搜索仍然获胜的其他领域包括：即时新闻(有时数据AI的及时性可能出现滞后)和高收率搜索，而你绝对不能犯错误——例如，与健康、法律或财务有关的搜索。
如果你真的觉得需要人工智能的方法，请确保双重和三重检查聊天人所使用的源，这些源应该在答案内部链接。 如果你有任何疑问，你可以要求AI澄清什么是来源于什么，以确保它不是LLM发明。
当然，经典的Google搜索仍然可以在网络上发现虚假信息，但是你更有能力辨别哪些是真实和准确的，哪些是中间没有聊天员的。 对于比方便和速度更重要的查询，仍然有旧的搜索网络方式的地方。
本文由 AI图鉴自动抓取并翻译，版权归原作者所有；如需查看原文请点下方链接。
If you've interacted with the likes of Claude, ChatGPT, and Gemini, you've noticed that in addition to everything else they do, these AI chatbots can search the web for you. Depending on what you’re looking for, it can be easier to find more relevant results through a chatbot, which may explain why Google is so keen to push AI Mode for its own search engine.
When asked to search the web, the latest versions of these bots are combining elements of traditional web search (they're essentially just googling on your behalf) with knowledge they are able to pull out of their training data. Everything is then packaged and formatted in the now-familiar, polished generative AI style.
It's the added AI elements on top of the traditional googling where the differences come in, and that means AI-powered search may not always be the best option.
When to Use AI for Web Search
If you're looking up something simple and widely known—like the height of the Empire State Building—then AI search is a pretty safe bet. Not only is information like this easy to access online, the “autocorrect” probability patterns favored by large language models mean there's a near-certain chance that the results you see will include the right information.
If you just need a quick look-up, AI is OK. The more obscure the question, though, the closer you need to look at the answer. If you've asked something less well known, like the fifth-billed actor in an obscure television show, there might only be one or two references to it on the web, and an AI might choose the wrong one.
One of the takeaways from recent Stanford University research is that when AI finds an accurate source, it's very good at pulling the right information out of it. Where it tends to fall down is in not finding accurate sources (either because there aren't any or because the query has been misinterpreted) and presenting a confident answer anyway.
AI search is also helpful when you have a complex query that a standard Google search wouldn't be able to parse: "I need to know the best restaurants in San Francisco for a family of five who want to spend no more than $200." AI is able to query and collate multiple sources in response to a search like this, and then present a well-synthesized answer. A traditional web search would give you a list of blue links that most probably just rank San Francisco restaurants by more basic criteria.
Again though, sources are crucial. AI bots have never been to San Francisco or eaten there. They are relying on public accounts on the web, written by people who have. Where there are no exact page matches, they'll look for related words (like "affordable" or "family") and generate an answer.
For queries where there's lots of information online, like San Francisco restaurants, AI web search can feel incredibly useful. For less popular destinations and more specific requests ("dining tables shaped like stars"), you need to be more careful with the results, as the way that AI joins the dots then becomes less reliable.
So, with the caveat that you should always do some kind of double-check, AI web search works best for common queries that are likely to lead to a lot of accurate, up-to-date information online. In both the way they process search queries, and package together and synthesize answers, AI chatbots are a significant upgrade on googling.
When Not to Use AI for Web Search
The way generative AI bots and LLMs are put together means they work best when paraphrasing, synthesizing, and summarizing. But these processes can also introduce mistakes. If your search needs precise details (like a celebrity quotation, a report stat, or a device specification), a traditional Google search may work best.
Heading to Google and searching the old way is also likely to be better if you want full control over the sources used. Offloading web searches to AI is convenient, but you're relying on them to interpret your search correctly, find the right sources, and then extract accurate information from those sources. It saves time, but it's more opaque.
If you know the websites you trust most for technology news, for example, you can prioritize them in a traditional web search in a way that AI might not be able to. Researchers from UC San Diego have found that AI web searches will sometimes pick sources because they're more relevant to the query, rather than because they're ranked as more authoritative.
That means a personal blog might get chosen above a professional health care site if the AI deems it to be a closer match to what the user is actually searching for. This is a choice that you would be much less likely to make when scanning a traditional list of results, as you'd typically pick the one you trusted the most.
Other areas where traditional searching still wins out are for breaking news (there can sometimes be a lag in the timeliness of the data AI pulls up) and for high-stakes searches where you absolutely cannot make a mistake—searches related to health, the law, or your finances, for instance.
If you do feel like an AI approach is needed, be sure to double- and triple-check the sources the chatbot has used, which should be linked inside the answer. If you're in any doubt, you can ask the AI for clarification on where something was sourced from, to make sure it isn't an LLM invention.
Classic Google searches can still turn up false information on the web, of course, but you're in a much better position to discern what's true and accurate and what isn't without a chatbot in the middle. For queries where that's more important than convenience and speed, there's still a place for the old way of searching the web.
Auto-fetched and translated by AI Atlas. All rights belong to the original author.