How Perplexity aims to reinvent web search

The way we search the web—picking through a list of links, some of them paid for, some gamed to show up high on the page—has remained virtually unchanged for more than two decades. Then came AI chatbots, which can understand plain-language questions and return direct answers, potentially reshuffling the $110 billion search ad business now dominated by Google.  One-year-old Perplexity’s “answer engine” is at the forefront of this new world of chatbot-assisted search.

Perplexity uses a combination of homegrown large language models (LLMs), third-party models (OpenAI’s GPT-4 and Anthropic’s Claude 2, among others), and web crawlers to return results that are highly relevant and fastidiously cited. Perplexity’s secret sauce is its embrace of retrieval-augmented generation (RAG), AI that finds the right documents on the web to help the LLM create more contextualized and accurate answers. This works especially well for open-ended questions such as “How should I prepare for my vacation in Rome?” and less well in searches for specific things like local business hours and live sports scores.

Users can type queries at Perplexity’s website or speak them into Perplexity’s mobile apps (its iOS app arrived in March 2023; its Android one in May), which have been downloaded more than 2 million times, the company says, and are now responding to more than 1 million queries per day. Perplexity recently announced it will be the search mechanism in the buzzy new R1 AI device, from Rabbit, which is expected to ship this spring.

“We do not have to challenge Google’s search market share in order to succeed,” says Perplexity cofounder and CEO Aravind Srinivas. “In fact, that’s precisely why I think we have a winning shot: We are operating in a new segment of AI assistants, chatbots, and answer bots where new businesses and products will continue to be created.”

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