ChatGPT vs Google Search

ChatGPT一出现,大家普遍觉得将会对Google搜索产生冲击,甚至有人放言“Google搜索完了”。而Google管理团队也在老神在在地评估了一周以后,开始紧急召集团队商讨应对策略和行动计划。Google团队应该发现ChatGPT的许多功能超出他们的预期,Google搜索引擎优势地位可能也不如他们想象得那么牢不可破。这两个工具到底那个更优,我们也来作几个小实验,探究一番。

我们首先把把这个问题抛给它们,让它们自己说说。

Ask Can you analyze the relative strength and weakness of ChatGPT and Google search engine?

ChatGPTAs a language model, ChatGPT is designed to generate text that resembles human conversation. It has been trained on a large dataset of chat logs and is able to generate coherent and contextually appropriate responses to text prompts, often with a conversational or chatty tone.

One of the strengths of ChatGPT is its ability to generate text that is coherent and flows naturally, making it well-suited for tasks such as chatbot development or language translation. Additionally, ChatGPT can be fine-tuned for specific tasks or domains, allowing it to generate text that is more relevant and accurate for a particular use case.

One potential weakness of ChatGPT is that, like all language models, it is limited by the data it has been trained on. This means that it may not always be able to generate text that is completely accurate or relevant, especially for tasks or topics that are outside of its training data.

Google’s search engine is a powerful tool for finding information on the internet. It is able to search billions of web pages and return relevant results in a matter of seconds. One of the strengths of Google’s search engine is its vast index of web pages and the ability to return results that are highly relevant to the user’s query.

One potential weakness of Google’s search engine is that it is dependent on the quality and relevance of the content on the web. If the content on the web is not accurate or up-to-date, the search results returned by Google may not be as useful or reliable. Additionally, the search results returned by Google may be biased or influenced by the ranking algorithms used by the search engine, which can impact the relevance and objectivity of the results.

把这个问题输入Google搜索框,给了一些相关文章的列表,正如预期。我们先抛开输出内容的质量,就输出形式来说,ChatGPT给了问题相对完整的回答,也正如你所期望的一个有相关知识的人的回答。而Google搜索给出的是一堆它认为的相关内容的列表,你还需要再进一步阅读和整理来形成自己的答案,并不是一个完整的解决方案。就输出形式来说,ChatGPT胜出,而且这个优势越到后来会越明显。就输出内容来说,ChatGPT的回答中规中矩,虽然没有谈深,但是主要点也都涵盖了。我也通读了Google搜索给出列表上的前面三篇文章,都是从一些技术指标去谈两者的优劣和差异,所以Google搜索给了更多的信息源和可能性,深度和广度上占优。这一题我会判ChatGPT以小优势胜出。

第二题接着问了几个相关的同类问题:

Ask When is the earliest year Union Pacific started to pay dividend?

Ask When is the earliest year York Water Company started to pay dividend?

Ask When is the earliest year Bank of Nova Scotia started to pay dividend?

这些问题ChatGPT都给出了准确无误的答案:Union Pacific: 1890年; York Water Company: 1816年; Bank of Nova Scotia: 1832年.而且还告诉说这些公司自那以后,一直连续不断,每年都给股东发股息。

把同样的问题输入Google搜索框,给了许多链接列表,我逐条点击二三十条,全都是这些公司近期的股息信息,如股息日期,公告日期,股息率等等,就是找不到这几家公司最早哪一年发股息的信息。这些早期股息信息都是公开信息,一定在Google扒来的数据库里,但就是浮不上来,这肯定是和Google的搜索算法有关了。我的猜测是Google搜索主要靠关键词搜索,对自然语言处理能力还是整合得不够。现在微软的Bing搜索已经明确要开始整合ChatGPT的功能了,Google如果不及时应对,还真有可能让Bing这个千年老二打个翻身仗。这一题,ChatGPT完胜,Google搜索彻底翻车。

接着再问第三题:

Ask Can you explain the ‘thousand brains’ theory work developed by Jeff Hawkins?

ChatGPT:The “thousand brains” theory, developed by neuroscientist Jeff Hawkins, is a theory of how the brain processes and stores information. It suggests that the brain is made up of many small, specialized regions, or “columns,” that work together to process different types of information. Each of these columns is thought to have its own specific function, such as recognizing patterns, identifying objects, or processing language.

According to the theory, the brain’s processing power comes from the interaction and coordination of these columns, rather than from any single region or area. This approach suggests that the brain is more like a network of interconnected systems, rather than a single, unified entity.

The “thousand brains” theory has been influential in the field of neuroscience and has helped to shape our understanding of how the brain works. It has also been used to inform the development of artificial intelligence systems, which aim to replicate some of the functions of the human brain.

把问题输入Google搜索框,首先第一条是Amazon上卖‘A Thousand Brains’这本书的链接,然后是一些包括盖茨在内的书评链接,还有Jeff Hawkins自己在YouTube上介绍这个理论的视频链接。这样的两种形式可以说是各有优劣。如果搜索着对这个话题就是想简单了解一下,ChatGPT这样一个的简洁单一、明确响应的体验更可取。而如果搜索者想对这个话题进行深入探究,那Google搜索所提供的的众多信息会更有价值。这题我本来想判Google搜索小胜,但是考虑到它首先就想到推销卖书,让我略有不爽,就判平局。

从以上三个例子其实已经可以看出两者之间优劣的一些端倪。对大多数搜索者和搜索场景来说,ChatGPT所给的单一明确形式的用户体验更佳。从信息搜索工具的演进路径来说,Google搜索曾经毫不费力地打败了提供明确形式答案的搜索工具,如ask.com, about.com, 而占据了绝大部分的搜索市场份额。Google搜索靠的是其背后巨大的实时全网信息库以及强大的算力支撑,而这两点对于ChatGPT来说已经不见得是绝对优势了。Google搜索的优化算法依然将权重放在关键词上,会让搜索引擎对有些问题的理解完全偏失;而对广告收入的考量,也多多少少会让用户体验打折扣。对于ChatGPT来说,虽然搜索问题答案只是其功能的一部分,但是它目前的局限性也很明显,就是没有能够做到全网信息的实时更新,对于一些时效性强的问题就根本没有办法和Google搜索抗衡。要做到全网信息的实时更新虽然在技术和资金上对于OpenAI和其投资者们来说并不是更具一个巨大的挑战,但是Google控制的互联网的底层基础设施将会给Google很大的优势,所以Google有相当的窗口期来改弦更张,继续优化自己的搜索引擎。所以从企业战略的角度来说,我们猜测OpenAI很可能不会让 ChatGPT 在搜索这一块来和Google搜索抢占地盘,而会强化其他功能来进行商业化。

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