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Perplexity AI is an AI-powered search engine and chatbot that merges traditional search with conversational AI. Using large language models (LLMs), it answers queries in natural language while citing sources from across the web. Think of it as a smarter search engine that not only finds information but explains it clearly.

Founded in 2022 by AI and machine learning experts Aravind Srinivas, Andy Konwinski, Denis Yarats, and Johnny Ho in San Francisco, Perplexity’s mission is to “democratize access to knowledge.” The platform has quickly gained traction, supported by investors including Jeff Bezos, and by mid-2024 had around 15 million users, answering hundreds of millions of queries.


Supported Devices

Perplexity AI works across most platforms, making it easy to access AI-powered answers wherever you are:

  • Web browsers: Accessible on desktops, laptops, tablets, and smartphones via perplexity.ai.
  • Chrome extension: Offers seamless integration directly into your browser.
  • macOS: Native app for macOS 13.0 or later, available on the Mac App Store.
  • iOS & iPadOS: App available for iPhone and iPad running iOS 13.0 or later, supporting multiple languages including English, French, German, Japanese, Korean, and Spanish.
  • Android: App available via Google Play Store.
  • Upcoming devices: Deutsche Telekom plans an “AI Phone” powered by Perplexity Assistant, a voice-controlled device for tasks like flight booking and reservations, expected in late 2025.

Key Features

Perplexity AI stands out for its conversational search and deep research capabilities:

  • Natural language answers: Ask questions in plain English (or supported languages) and receive clear, concise responses instead of just a list of links.
  • Inline citations: Responses include clickable footnotes leading to original sources for verification.
  • Context-aware dialogues: The AI remembers your questions within a session, enabling a true back-and-forth conversation.
  • Focused searches: Prioritize academic sources, news, or community forums like Reddit.
  • Deep research tools: Explore topics in detail with comprehensive data and analysis.
  • Chat history: Free accounts let you revisit past queries and build a personal knowledge base.

Pro version ($20/month) enhances the experience:

  • Access to multiple AI models (OpenAI GPT-4, Anthropic Claude, Meta Llama 2, and Perplexity’s own models)
  • Higher usage limits and faster responses
  • Upload documents (PDFs, Word, images) for AI-assisted analysis
  • Specialized tools for shopping, finance, and research

Beyond Chat and Search

Perplexity isn’t just a question-answering tool. It can:

  • Generate content drafts or compilations (“Pages”) for research or presentations
  • Create images via DALL·E or Stable Diffusion integration
  • Offer domain-specific tools for shopping recommendations or financial lookups

These features demonstrate Perplexity’s versatility, tailoring results to both casual inquiries and in-depth research.


Limitations and Concerns

Despite its strengths, Perplexity AI has challenges:

  • Hallucinations: Occasionally generates incorrect or misleading answers.
  • Bias: Reflects biases present in training data or web sources.
  • Data use: Queries are logged, and privacy audits are limited.
  • Content scraping concerns: Some publishers have sued for reproducing content without permission.
  • Information gaps: Content behind paywalls or blocked sites may limit answers.

Users should treat responses as starting points for research, not infallible facts.


Outlook

Perplexity AI represents a new wave in search technology, blending AI-driven conversation with reliable sources. Its growth pressures major players like Google to innovate, and its modular approach to AI models suggests a future where assistants leverage multiple specialized engines behind the scenes.

While it faces competition, accuracy challenges, and ethical questions, Perplexity is shaping how we explore information online. For curious users, researchers, and students, it’s a compelling tool for conversational, efficient, and citation-backed learning.

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