“Perplexity AI Raises $70M in Funding, Valuation Skyrockets to $520M Thanks to Cutting-Edge AI Search Engine”

As search engine incumbents — namely Google — amp up their platforms with gen AI tech, startups are looking to reinvent AI-powered search from the ground up. Srinivas, Perplexity’s CEO, previously worked at OpenAI, where he researched language and gen AI models along the lines of Stable Diffusion and DALL-E 3. This reporter is skeptical about the longevity of gen AI search tools for a number of reasons, not least of which AI models are costly to run. Concerns around misuse and misinformation inevitably crop up around gen AI search tools like Perplexity, as well — as they well should. Some plaintiffs, like The New York Times, have argued gen AI search experiences siphon off publishers’ content, readers and ad revenue through anticompetitive means.

The Rise of Next-Generation AI-Powered Search

Search engines have come a long way since their inception, with Google leading the pack in terms of technology. But as gen AI continues to revolutionize the field of search, new startups are emerging to challenge the incumbents. Despite facing competitors with billions of users, these innovative search upstarts believe they can deliver a superior experience and carve out a niche in the market

One such standout among the cohort is Perplexity AI, which announced this morning that it has raised $70 million in funding. The round was led by IVP, with additional investments from NEA, Databricks Ventures, former Twitter VP Elad Gil, Shopify CEO Tobi Lutke, ex-GitHub CEO Nat Friedman, and Vercel founder Guillermo Rauch. Notably, the round also included participation from Nvidia and Jeff Bezos.

Sources familiar with the matter tell TechCrunch that the round has valued Perplexity at $520 million post-money – a significant feat for a startup that has only been around since August 2022.

From Engineers to Entrepreneurs

Perplexity was founded by a team of experienced engineers with backgrounds in AI, distributed systems, search engines, and databases. Led by CEO Aravind Srinivas, the team also includes Denis Yarats, Johnny Ho, and Andy Konwinski. Srinivas previously worked at OpenAI, where he researched language and gen AI models, such as Stable Diffusion and DALL-E 3.

Unlike traditional search engines, Perplexity offers a chatbot-like interface that allows users to ask questions in natural language. For example, users can ask questions like “Do we burn calories while sleeping?” or “What’s the least visited country?” The platform’s AI responds with a summary containing source citations, usually from websites and articles. Users can then ask follow-up questions to delve deeper into a particular subject.

“With Perplexity, users can get instant … answers to any question with full sources and citations included,” Srinivas explains. “Perplexity is for anyone and everyone who uses technology to search for information.”

Harnessing the Power of Gen AI

At the core of Perplexity’s platform are a variety of gen AI models developed both in-house and by third parties. Subscribers to Perplexity’s Pro plan ($20 per month) have access to a variety of models, including Google’s Gemini, Mistra 7Bl, Anthropic’s Claude 2.1, and OpenAI’s GPT-4. These models allow for features such as image generation, unlimited use of the platform’s Copilot, and file uploads, which can be analyzed by the models to provide answers.

While comparable to other popular gen AI tools such as Google’s Bard, Microsoft’s Copilot, and ChatGPT, Perplexity stands out with its chat-forward user interface. Additionally, the search engine startup You.com offers similar AI-powered summarizing and source-citing tools, powered optionally by GPT-4.

Expanding the Search Experience

Srinivas argues that Perplexity offers more robust search filtering and discovery options compared to its competitors. For example, users can limit their searches to academic papers or browse trending search topics submitted by other users on the platform. However, some question whether these features are enough to differentiate Perplexity, as they can easily be replicated or have already been replicated by others.

But Perplexity’s ambitions extend beyond just search. The company is now starting to serve its own gen AI models, which leverage Perplexity’s search index and the public web for improved performance. This is available through an API for Pro customers.

Innovative, but at a Cost

Despite the potential of gen AI search tools, there are still many uncertainties surrounding their longevity and business model. OpenAI, for example, was spending approximately $700,000 per day to keep up with demand for ChatGPT. Similarly, Microsoft is reportedly losing an average of $20 per user per month on its AI code generator.

There are also concerns about the misuse and misinformation that can arise from gen AI search tools like Perplexity. Despite its ability to provide quick answers and source citations, AI is not always the best at summarizing information accurately. Additionally, it is prone to bias and toxicity, as Perplexity’s own models have demonstrated.

Another potential challenge is copyright issues stemming from the use of gen AI models, which often scrape millions to billions of web examples to train their models. While vendors argue that this falls under fair use doctrine, copyright holders are starting to file lawsuits seeking compensation. Interestingly, Perplexity does not currently offer any protection for customers from IP claims.

Yet Another Roadblock

One of the main criticisms against gen AI search experiences is their impact on website traffic. A model by The Atlantic found that if a search engine like Google were to integrate AI into their search results, it would provide a relevant answer 75% of the time without requiring a click-through to the website. This means that gen AI tools could potentially reduce traffic for publishers. While some vendors, including OpenAI, have made deals with certain news publishers, most have not – including Perplexity.

However, Srinivas sees this as a positive feature of Perplexity. The platform eliminates the need to click on different links or sift through sponsored content to find information. Instead, users can get all the necessary information from one source.

Investing in the Future

Despite these challenges, Perplexity’s investors are confident in the company’s potential. With a reported 10 million active monthly users, the startup has already raised over $100 million to expand its 39-person team and develop new product features. “Perplexity is intensely building a product capable of bringing the power of AI to billions,” says Cack Wilhelm, a general partner at IVP. “Aravind possesses the unique ability to uphold a grand, long-term vision while shipping product relentlessly, requirements to tackle a problem as important and fundamental as search.”

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Max Chen

Max Chen is an AI expert and journalist with a focus on the ethical and societal implications of emerging technologies. He has a background in computer science and is known for his clear and concise writing on complex technical topics. He has also written extensively on the potential risks and benefits of AI, and is a frequent speaker on the subject at industry conferences and events.

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