• Perplexity CEO Aravind Srinivas spoke about the lawsuits the company is facing from news publishers.
• Speaking at WSJ, Srinivas said Perplexity has already had conversations with Dow Jones.

Latent tensions between press publishers and search engines built with artificial intelligence were revealed to the public on Wednesday during a seaside conference.

“Let’s talk about the elephant in the room,” Aravind Srinivas, co-founder and CEO of Perplexity, opened his interview at the Wall Street Journal’s Tech Live conference.

Dow Jones by Rupert Murdoch, publisher of the Journal and the New York Post filed a complaint in New York on Monday, accusing Perplexity of “freeriding” on the journalism they produce. The perplexity the app allows users to get instant answers to questions with sources and citations from trusted blogs, media outlets, and academic articles.

The two-year-old startup takes money like oxygen, having raised consecutive funding cycles a few months apart, and it’s he is said to be in talks to raise a fourth round of funding which would value the startup at $8 billion.

The lawsuit alleges that Perplexity removes copyrighted works to power its search engine and, in doing so, drives potential readers and customers away from their websites.

“Nobody comes to Perplexity to ingest its information. People go straight to the New York Times, to the Wall Street Journal,” Srinivas said. He explained the goal of Perplexity: to help users digest the news. “People come to Perplexity to understand current news in the context of what they already know. ‘How does this news affect me?'”

“We’re not interested in taking the exact content and resurfacing it. We’re not trying to be an alternative in information,” he later added. “So we’re going to do our best to engage and communicate what the goals of our product are and how they can mesh with existing media.”

The company has said it does not retrieve data to train large language models; rather, it crawls the Internet, creating an index of web pages to which its models can refer.

The entrepreneur remained calm while WSJ reporter Deepa Seetharaman asked about Perplexity’s cash flow and claimed through media reports that the quotes are unclear. Srinivas acknowledged that the technology is “not perfect.”

“We always work with technology that is constantly improving,” he responded to a question about plagiarism. “Even yesterday Anthropic released another version of their models, Claudius 3.5. It gets better and better every few months. So whatever problems exist today, they are a new set of problems that did not exist a year or two ago. »

In her interview, Srinivas defended the company’s modus operandi, saying she had a conversation with the Journal’s publisher in June about potentially entering into a contract that would allow Perplexity to share future advertising revenue with the publisher. He did not elaborate on the contents of the contract but said the conversation had turned dark.

“We were definitely very surprised by the trial because we actually wanted a conversation,” Srinivas said.

This month, the company will start selling ads for popular searches, Srinivas said. So, for example, a user might ask Perplexity about a shoe company that just went public on Wall Street. The search engine will return a summary of the shoemaker’s stock market debut with sources and citations. If a shoe brand pays to advertise in the results, Perplexity will share some of the money it makes with the publishers whose content it used to answer the query.

“We can only exist if we make our own money, not just by continuing to raise funds,” Srinivas said. “Then when we start making our own money, that will definitely benefit all publishers and ensure that they continue to thrive as well.”

Just last week, the New York Times sent Perplexity a cease and desist letter seeking to end the practice of using its stories to train chatbots. The media outlet is also suing OpenAI and Microsoft for copyright infringement.

Perplexity hopes to become profitable within three to five years through the sale of subscriptions and advertisements, according to Srinivas. He acknowledged that while Perplexity doesn’t train large language models and doesn’t need to raise as much capital as OpenAI or Anthropic, the influx of cash from investors allows it to move faster.

“Raising money obviously helps us stay focused on the product and continue to improve it, but not worry too much about finances,” Srinivas said.