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.
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.
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:
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.
The query interface includes:
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.
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.
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.
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.
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.
Perplexity AI's main competitor is ChatGPT. Below is a comparison table of their key features:
Feature |
Perplexity AI |
ChatGPT |
Primary Purpose |
General-purpose tool for various tasks. Suitable for text creation, math problems, academic and educational content. |
Same as Perplexity: versatile use including text generation, coding, etc. |
Built-in Modes |
Search, Research |
Search, Reason, Deep Research |
Free Access |
Yes, but limited: auto model selection only; max 3 file uploads/day |
Yes, with limits: restricted use of GPT-4o, o4-mini, and deep research mode |
Paid Plans |
One plan: Pro at $20/month |
Four plans: Plus ($20/mo), Pro ($200/mo), Team ($25/mo billed annually), Enterprise (custom pricing) |
Mobile App |
Yes (iOS and Android) |
Yes (iOS and Android) |
Desktop App |
Yes (Windows and macOS) |
Yes (Windows and macOS) |
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.
Key strengths of Perplexity AI include:
Like any neural network, Perplexity AI has its drawbacks:
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.