For the past two decades, the dominant search engines, like Google and Bing, have been our go-to portals for accessing the vast expanse of the internet. However, as time has passed, these search engines have become inundated with ads and algorithm-focused content, making it harder for users to find what they’re looking for among the sea of links. Aravind Srinivas and his team at Perplexity.ai are aiming to change that. Instead of sifting through search results, users can ask questions directly to Perplexity.ai and receive concise, accurate answers from trusted sources. Powered by large language models (LLMs), this “answer engine” puts users first, rather than prioritizing advertisers. This shift has the potential to revolutionize how we discover and consume information online, and may even reshape the internet as we currently know it.
Challenging the search giants is no easy task, but Aravind, armed with a Ph.D. from Berkeley and experience at OpenAI and DeepMind, is the ideal entrepreneur to take on this challenge. In a recent conversation, Aravind and I discussed the origins of Perplexity, his strategy for tackling incumbents and interface design, and his advice for fellow AI founders.
Let’s delve into Aravind’s background and what led him to create Perplexity. Born in Chennai, India, Aravind grew up in a culture that values education and knowledge. This mindset shaped his own pursuit of education, from gaining admission to the prestigious Indian Institutes of Technology (IITs) to pursuing a Ph.D. at U.C. Berkeley in deep learning research. Aravind also found inspiration in movies like “Pirates of Silicon Valley” and “The Social Network,” which sparked his interest in entrepreneurship. While at Berkeley, he delved into books about Google’s early days and became fascinated by Larry Page’s innovations, particularly PageRank and its impact on transforming deep learning models like transformers.
Aravind further honed his skills during an internship at DeepMind, where he had the opportunity to work with Ashish Vaswani, the inventor of transformers. This experience solidified Aravind’s passion for the intersection of academia and entrepreneurship. While deep learning initially seemed too academic for a startup, the success of generative AI startups like Jasper and GitHub Copilot convinced Aravind that the time was right to start his own company. With the support of investors like Elad Gil and Nat Friedman, as well as his three cofounders Denis, Johnny, and Andy, Perplexity was born.
So, why did Aravind choose to tackle the problem of search? As a fan of Google and Larry Page, Aravind admired the scale and ambition of the search giant. He wanted to create something on a similar level, focusing on accuracy, truthfulness, and accessibility to information. Building a product that not only helped users become smarter but also raised the collective knowledge capital of the entire planet held deep personal significance for Aravind. It was about more than just making money.
In the early stages of Perplexity, the team explored other ideas, such as translating natural language to SQL. This concept was inspired by their investor Elad Gil and the desire to make data analysis more accessible. However, they ultimately decided to shift their focus. The technology at the time wasn’t advanced enough, and the fragmented SQL market made it challenging to establish a foothold. Despite this detour, sharing their prototype, BirdSQL, on Twitter brought unexpected success. Jack Dorsey’s endorsement generated significant attention and traffic, overcoming the initial hurdle of being an unknown startup.
Aravind describes Perplexity as an “answer engine.” This term reflects their goal of providing direct, concise answers to users’ questions, rather than simply displaying a list of web pages. While traditional search engines have begun moving in this direction in recent years, Perplexity aims to answer more complex queries that require synthesizing information from multiple sources. Their use of LLMs enables fast and accurate responses. In the past, users were conditioned to use keywords for searches, but LLMs are changing the game by allowing for more dynamic interactions with computers. These language models can not only provide answers but also ask clarifying questions and act as a helpful guide while browsing the web. Perplexity’s vision is to empower users to easily access and utilize information while also assisting with various tasks.
Editor Notes:
The emergence of alternative search engines like Perplexity.ai is an exciting development in the world of information retrieval. While search giants like Google have dominated the landscape for years, the rise of innovative startups like Perplexity.ai challenges the status quo and offers users a new way to access knowledge online. By prioritizing accurate and concise answers, Perplexity.ai is working towards a user-centric approach that values quality information over ad-based revenue models.
As an AI enthusiast, I find the concept of answer engines fascinating. The ability to directly ask questions and receive accurate responses is a game-changer, especially as large language models continue to advance. Aravind’s background and expertise make him well-equipped to take on this challenge, and his entrepreneurial spirit is evident in his journey from academia to building a startup.
It will be interesting to see how Perplexity.ai continues to evolve and how it impacts the search engine landscape. With the power of AI behind it, the potential for a truly transformative search experience is within reach. As users, we can look forward to a more seamless and efficient way of finding the information we need while navigating the vast expanse of the internet.
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