How Perplexity AI Works

In today's article, we will take a detailed look at the Perplexity AI neural network: we'll explore how it works, how to use it, how it differs from its main competitor ChatGPT, and what opportunities it offers for everyday use.

What is Perplexity AI? 

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Perplexity AI is an artificial intelligence-based platform that combines the functionality of a chatbot and a search engine.

The service's architecture is based on the use of large language models (LLMs). When developing Perplexity AI, the creators aimed to provide an alternative to traditional search engines that could help users find accurate and meaningful answers to complex and ambiguous questions.

What Does Perplexity AI Do? 

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As previously mentioned, Perplexity is built on large language models. The supported models include Sonar, Claude 3.5 Sonnet, GPT-4.1, Gemini 1.5 Pro, Grok 3 Beta, and o1-mini. With access to multiple models, the neural network can generate accurate and comprehensive answers to user queries in real time.

A key feature of Perplexity is its ability to analyze user queries while simultaneously gathering information from the internet in real time and generating responses with a list of all sources used. You can view sources not only for the entire generated text but also for individual sentences or even specific words.

The Perplexity workflow includes:

1. Query analysis: once the user submits a prompt (text request), the neural network analyzes its context and content using built-in language models.
2. Data search: information is retrieved from the internet. The search includes not only articles and text-based data but also videos, social media posts, and user comments. Priority is given to authoritative sources.
3. Response generation: the collected and processed information is compiled into a single response with citations and source links. Perplexity uses different data models to ensure the response is as accurate and reliable as possible.
4. Additional functionality (if needed): in Copilot and Deep Research modes, the system refines queries further to deliver more accurate and relevant answers.

Step-by-Step Guide: How to Use Perplexity AI 

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Let's explore how to use the neural network in practice. We'll start with the interface and its basic functions, then move on to using prompts to evaluate the results.

1. Go to the official website of Perplexity AI. You will see the home page.
2. By default, the interface will be in English. To view available interface languages or switch them, click on the language at the bottom of the page.
3. The left-hand panel includes the following elements:

• • New Thread button (plus icon) – allows you to start a new conversation or query. In Perplexity, a Thread is a separate message chain that is not connected to previous queries. Useful for asking about new topics.
  • Home button – takes you back to the home page at any time.
  • Discover – lets you view and customize a news blog with trending topics. Users can choose their interests and get fresh, relevant content.
  • Spaces – used for creating and organizing workspaces to group conversations and uploaded files by topics or projects.

The query interface includes:

• Search mode – the default mode where the AI analyzes the query and generates an answer in real time.
• Research mode – used for deep analysis and information gathering. It offers a more in-depth report with comprehensive source analysis. This mode takes a bit more time.
• Model selection – lets you choose one of eight supported AI models. In the free plan, only Auto mode is available, where Perplexity selects the best model based on the query.
• Source selection – you can choose from Web (all sources), Academic (scientific sources only), or Social (social media and informal sources).
• File attachments – Perplexity supports uploading files with your query. For example, you can upload a file with Python code to find errors. Supported formats include text files, PDFs, and images (JPEG, PNG). You can upload files from local devices, Google Drive, or Dropbox.
• Dictation mode – allows you to create queries via voice input. Submission is still manual.
• Voice mode – enables full voice interaction. You can dictate your query and receive voice responses. Unlike Dictation, Voice mode supports hands-free interaction.

Using Text Prompts 

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Let's test how Perplexity AI handles user prompts. 

We'll start with text-based queries and create several different prompts. The first one will test how the neural network handles a complex scientific topic.

1. First prompt: I'm writing a scientific paper. Write a text on 'Differential Equations.' The text should cover basic first-order differential equations and partial differential equations. The style should be academic.

As shown in the screenshot, the AI began by explaining what differential equations are. Then, following the prompt structure, it provided a breakdown of first-order and partial differential equations, complete with equations.

Perplexity provides a list of sources used, which are shown in the Sources tab. 

If the query includes a practical task (e.g., solving a math problem, writing a program), the AI uses technical sources and lists them in the Tasks section.

The text is accompanied by numbered source links. Clicking a number opens the relevant page. On the right, a context menu appears, breaking down the highlighted text and showing each part's source. 

You can reuse the AI's response to create a new query. Select a paragraph, sentence, or word, and click Add to follow-up. The selected fragment will be added to the new prompt field.

2. Second prompt: What is a passive source? Give real-world examples and advice for beginners.

This prompt tests how the AI provides practical advice. 

As per the prompt, the AI also generated a block of beginner tips. As shown in the screenshots, Perplexity provided detailed examples and actionable advice, completing the task effectively.

Using Files in Queries

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Next, we'll test file handling. We create a text file with Python code containing an intentional error (printed instead of print):

print("\nNumbers from 1 to 5:")
for i in range(1, 6):
  printed(i, end=" ")

We save the file as .txt (other extensions like .py or .js aren't supported due to security policies).

Now we ask the AI to find and fix the error. 

Image Search 

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Perplexity AI can both generate and search for images online using text prompts. Let’s search for an image online. 

Prompt: Find an image of rainy London. There should be a telephone booth in the foreground and Big Ben in the background.

As shown in the screenshot, the AI found a bunch of relevant images. To view more results, go to the Images tab.

Comparing Perplexity AI vs ChatGPT 

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Perplexity AI's main competitor is ChatGPT. Below is a comparison table of their key features:

Hidden Features of Perplexity AI 

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Although it may appear similar to competitors, Perplexity has unique features that enhance the user experience:

• Financial Data Analysis: built-in tools for viewing stock quotes and financial reports, with data from Financial Modeling Prep.

• YouTube Video Summaries: the AI can summarize videos, regardless of language.

• Focus Mode: restricts search to academic papers or specific websites for faster, more targeted results.

Advantages 

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Key strengths of Perplexity AI include:

• Real-time data sourcing for up-to-date answers.
• Convenient source tracking and citation.
• File upload support in queries.
• Built-in financial data analysis tools.
• Two work modes: Search and Research. The Research mode provides deeper, more detailed answers.
• Integrated voice assistant for prompts and conversations.
• Image generation and image search features.
• Built-in YouTube video summarization.

Disadvantages 

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Like any neural network, Perplexity AI has its drawbacks:

• Free plan limitations.
• Prompt-dependent accuracy: for complex scientific/technical topics, even with many sources, it can sometimes give inaccurate responses.

Conclusion 

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In this review, we examined Perplexity AI—a powerful tool built on large language models. It is well-suited for a wide range of tasks and stands out due to its advanced source-handling features and personalized approach.