AI search engines, such as Perplexity, Bing Copilot and You.com, use advanced language models and deep machine learning to understand user intent and provide relevant answers. Instead of presenting simple links, they interpret natural language queries using Natural Language Processing (NLP) and semantic search techniques.
A key element of these search engines is the language model 鈥� a powerful AI system trained on massive amounts of mostly textual data. The models learn linguistic and contextual patterns to generate consistent and meaningful answers.
When a user enters a query, the AI search engine 鈥� unlike Google Search, for example 鈥� processes the query using NLP algorithms that analyze syntax, meaning, and intent. The language model then generates potential answers and selects the best one.
For example, by asking the question 鈥淗ow do I tie a tie?鈥�, Perplexity can generate step-by-step instructions, along with illustrations and links to instructional videos.
AI search engines are very different from the traditional search algorithms used by Google. Instead of presenting a list of links based on keywords, AI seeks to understand the user鈥檚 intent and provide a synthetic, comprehensive answer. This is a huge step forward in the way information is found online. But which search engines are worth using?
Source: You.com
One of the AI search engines challenging Google is Perplexity (). Its creators set out to revolutionize the way people find information online. As an alternative to traditional search engines, it allows you to ask questions directly and get concise, accurate answers backed by verified sources.
Perplexity鈥檚 unique selling point is its conversational interface and contextual understanding of the query. This search engine learns the user鈥檚 preferences and interests and adapts its answers as the dialog progresses.
The use of an advanced response algorithm, text prediction capabilities, and summarized results make it possible to provide useful information in a concise form.
In addition, Perplexity allows you to upload text files, source code, and PDFs so that the AI model can use their content to formulate answers. It鈥檚 a useful tool for tasks such as
Perplexity鈥檚 conversational interface is based on a sophisticated natural language processing architecture. The search engine uses deep neural networks to analyze the context and intent of a query, and then generates a response using a language model trained on large data sets.
One of Perplexity鈥檚 distinctive features is the ability to narrow down the search area 鈥� this could include, for example, only academic sources, YouTube or conversations on Reddit.
For paying users ($20 per month), there is a Perplexity Pro subscription, which allows flagship models like Claude 3 and GPT-4 to be used for analyzing longer content and unlimited file transfers. The paid subscription also allows for unlimited use of Copilot, which suggests additional searches that will help us answer the original question.
Source: Perplexity.ai
Bing Copilot ( ) is Microsoft鈥檚 proposal that combines the power of the GPT-4 language model with the traditional Bing search index. It aims to provide accurate answers to complex questions using deep machine learning techniques.
As with Perplexity, Bing Copilot offers an easy-to-use chatbot interface for asking questions and receiving answers from AI in natural language. Users of the Edge search engine can also use a very convenient side panel that allows, among other things, to ask questions to an open web page.
Bing Copilot can be particularly useful for exploratory queries that require in-depth analysis and synthesis of information from multiple sources. For example, the question 鈥淲hy were chainsaws invented?鈥� can be enriched not only with a concise answer, but also with links to additional sources and multimedia.
What鈥檚 more, Bing Copilot has the potential to personalize search results based on a user鈥檚 history and preferences. And the quality of search is constantly improving 鈥� Microsoft is working with technology companies like OpenAI to continually improve the capabilities of its AI search engine.
Entrepreneurs can use Bing Copilot, for example, to conduct market research and competitive analysis. Advanced search and natural language processing capabilities allow them to gain valuable insights from a variety of data sources.
Source: DALL路E 3, prompt: Marta M. Kania (https://www.linkedin.com/in/martamatyldakania/)
You.com () is another player in the AI search market, relying on advanced natural language processing and semantic understanding to deliver personalized search experiences. You.com offers a really wide range of models 鈥� it鈥檚 not just the popular GPT-4, Google Gemini or Claude, but also DBXR or Zephyr. Although it uses language models to interpret queries like Perplexity and Bing Copilot, You.com stands out for its comprehensive suite of search features.
You.com also has very useful modes:
When comparing You.com鈥檚 search capabilities to traditional search engines, there is a significant advantage in understanding user intent and providing personalized answers. However, it is important to note that for simple queries, such as finding known facts or websites, traditional search engines may still be a better choice.
殴r贸d艂o: You.com
Although AI search engines such as Perplexity, Bing Copilot and You.com are becoming increasingly popular, replacing Google as the dominant player in the search engine market will not be an easy task. According to the latest data, Google still controls more than 90% of the global search engine market (). AI search engines, on the other hand, have yet to match the giant in terms of search efficiency and speed.
The differences between AI search engines and Google鈥檚 traditional search model are also significant. Google has long been more than just a website with links; it is a true mini operating system, offering a range of tools and features integrated with search.
While AI search engines are getting better at interpreting queries and generating answers, Google is still the undisputed champion at providing quick links to websites, which is still a core function of a search engine.
In addition, Google collects vast amounts of data about its users to better tailor results to their preferences and context.
However, AI is most likely to outperform Google when it comes to queries that involve synthesizing information from multiple sources or finding hidden data. For queries such as 鈥淗ow do I take a screenshot on my Mac?鈥�, AI search engines are able to extract key information and present it directly, whereas Google often serves up a thicket of ads and not very useful results.
AI search engines are constantly learning. The more data they receive, the better their language models and their ability to understand context. Over time, this may give them an advantage over Google鈥檚 static search algorithms. It may also be that Google will eventually make SGE, Search Generative Experience, more widely available, combining the power of AI with the Google search experience.
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Author: Robert Whitney
JavaScript expert and instructor who coaches IT departments. His main goal is to up-level team productivity by teaching others how to effectively cooperate while coding.
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