View From The Top with Aravind Srinivas, Cofounder and CEO of Perplexity

Introduction and Background

• Aravind Srinivas is welcomed to Stanford, and he mentions he is from Berkeley, representing with blue, and is happy to be at Stanford (15s).
• Many in the audience are active Perplexity users, especially with free Perplexity Pro for all Stanford students, and are excited to have Aravind Srinivas there (27s).
• To craft questions, Perplexity was used, and it suggested discussing Aravind's personal backstory, the early days of Perplexity, the company today, and various leadership lessons (1m12s).
• Perplexity also suggested asking about something the audience may not know about Aravind, the funniest thing about him, and questions to inject humor into the conversation (1m46s).
• Rapid-fire questions were also suggested to be asked at the end of the interview (2m0s).
• Perplexity provided interesting insights, including Aravind's love for cricket, teaching himself to program after missing getting into computer science at IIT Madras by 0.01 points, and his connection to Sundar Pichai, the CEO of Google, who grew up in the same hometown in Chennai, India (2m26s).
• Aravind attributes the success of many tech entrepreneurs from Chennai to the culture of trying to excel and do their best, with a strong emphasis on education and valuing being scholarly and well-read (3m36s).
• He also mentions that people from Chennai are known for being obsessed with cricket statistics (4m23s).
• Growing up in India, cricket was a significant part of life, and knowledge about the game was valued over wealth, with an emphasis on understanding statistics and consistency in performance (4m36s).
• The decision to pursue a PhD in computer science at UC Berkeley was made after not getting accepted into Stanford, and this academic background has shaped the approach to building Perplexity (5m3s).

The Influence of Academia on Perplexity

• The experience at UC Berkeley, where citations were a crucial aspect of academic work, influenced the development of Perplexity, with a focus on providing sources for every answer to establish trust and authority (5m28s).
• The concept of citations and academic currency in the community was learned through working on papers and understanding the importance of simplicity and citability in ideas (6m32s).
• The trade-off between writing complicated, creative ideas and simple, citable ones was a key takeaway from the academic experience, and this has been applied to Perplexity's approach to providing answers (6m54s).
• The inspiration for Google's search engine, which used academic citation graphs and web hyperlinks, also influenced the development of Perplexity's approach to providing trustworthy answers (7m25s).
• Perplexity's unique product experience is built on the idea of providing answers that are backed by sources with domain authority or trust, similar to academic papers, and this is a direct result of the academic roots and experience (8m17s).

Perplexity's Mission and Vision

• Democratizing access to knowledge is crucial as it is a moral duty for individuals to seek wisdom and become perpetual learning machines, and having access to the right tools is essential for making progress in understanding the world better (9m7s).
• The goal of Perplexity is to improve access to information and create the world's first answer engine, making knowledge widely accessible for all, allowing people to ask any question and get an instant answer (8m43s).
• The tagline of Perplexity is "where knowledge begins" because there is no end to knowledge, and the company aims to help people keep getting better by providing them with the tools to do so (9m35s).
• The increasing efficiency and affordability of AI models will make it possible to create a widely accessible version of the answer engine, helping people ask any question and get an instant answer (10m11s).

Building the Perplexity Team

• When building the initial founding team of Perplexity, the qualities looked for were people with complementary skills, who were better in their areas of expertise, and did not overlap with the founder's skills (11m21s).
• The core founding team of Perplexity consisted of Aravind Srinivas, Dennis, and Johnny, who brought together a combination of skills in AI, software engineering, problem-solving, and competitive programming (11m37s).
• Johnny, one of the co-founders, was a world-class competitive programmer who represented the United States at the II and had a strong background in problem-solving and AI (11m47s).
• Dennis, another co-founder, had a strong background in AI and software engineering, which complemented the skills of the other founders (12m20s).
• The academic background of the founders helped them meet like-minded individuals who were motivated and deep thinkers, which was beneficial in building the team (10m49s).
• The founding team's diverse skills allowed them to take bold risks and set up a mission to build a completely new search experience, which would have been impossible to achieve alone (12m24s).
• Over time, the team hired more people with new skills, such as front-end programming and writing Kura kernels, which had an incremental and multiplicative effect on the company's growth (12m39s).
• The team's design was improved by hiring someone specifically for that role, who brought a new perspective and skills, creating a multiplicative effect on the company's product (13m31s).

Funding and Investment

• When raising their series A financing round, the team found out that Microsoft was launching a search competitor, Bing, but their investors, Nea, expressed confidence in the team and the company, which gave them the confidence to continue (14m11s).
• The investors, Nea, called to reassure the team that they believed in them and would not back out of the deal, despite the news of Microsoft's launch, which was a crucial moment for the company (15m37s).
• The team's response to the news was not to worry, but to focus on finding a way to move forward and continue growing, thanks to the confidence boost from their investors (15m52s).
• Perplexity's investors include Jeff Bezos, Yan Lecun, and Nvidia, and the company's success in attracting these investors can be attributed to creative fundraising strategies (16m11s).
• Yan Lecun, also known as the "Godfather of AI," was initially difficult to reach, but the founders managed to meet with him by camping out in front of his office at NYU, and they impressed him with a Twitter demo that allowed him to search his own tweets and see who was replying to him (16m36s).
• The founders also impressed other investors, such as Karpathy, by sending them a link to try the product directly, rather than sending a deck, which was a strategy that worked well for them (17m41s).
• The key takeaway from these experiences is that it's essential to play to your strengths and not try to do something you're not good at, such as making decks, and instead focus on creating a working product that can be tried instantly (17m58s).
• Having a working product that can be tried instantly is more effective than having a deck, as it communicates more and shows that the product works, which is essential for investors (18m28s).
• The founders have not used decks much, even for their series A and B funding rounds, and instead prefer to write memos or Notion documents, which is a strategy that has worked well for them (18m52s).
• Successful decks from the past, such as those from Airbnb, LinkedIn, and Facebook, can be confusing and make it difficult to know how to create an original deck, which is why the founders have avoided trying to make decks (19m11s).

Perplexity's Approach to AI Models

• Perplexity is building an answer engine without owning the content or models, instead relying on using APIs and post-training them for specific tasks like summarization and referencing. (20m8s)
• The decision to use other people's models was made due to the conviction that models would become increasingly commoditized, requiring an enormous amount of funding to develop and maintain. (20m51s)
• The company chose not to compete in building their own models, as it would require losing billions of dollars per year, and instead focused on shaping existing models for a better end-consumer experience. (21m6s)
• This approach has proven to be correct, as many companies that attempted to build their own models are no longer in existence, highlighting the need for significant funding or a different approach. (21m33s)
• The cost of using APIs for models is decreasing rapidly, with a 2x reduction every four months, making it a good time to be an application layer company using these models. (22m14s)
• Open-source models are keeping a check on closed-source models, bringing the price down and increasing the level of intelligence and reasoning, making it a perfect time to build on top of these models. (22m30s)
• Perplexity aims to create a successful business by building on top of existing models and technologies, similar to how other successful companies have done in the past, such as Coca-Cola leveraging refrigeration technology. (23m2s)
• The company's goal is to create something that provides immense value to consumers by using the right packaging and foundational technology, making it worth building and leveraging existing technologies. (23m31s)

Advertising and Monetization

• Perplexity has introduced advertising for the first time, with a strategy that differs from Google's overreliance on advertising, aiming to avoid influencing the accuracy and truthfulness of answers (23m50s).
• Perplexity's ad unit is designed to suggest follow-up questions after providing unbiased and truthful answers, allowing brands to get users' attention without manipulating the original answer (24m56s).
• The ad unit is still in its early days, with a few brands experimenting with it, and the major concern is the lack of control over the answer, which requires courage for brands to try out this new style (26m2s).
• Perplexity is clear on not trying to influence the accuracy and truthfulness of answers, to avoid ending up like Google, where people are frustrated with the answers (26m31s).

Addressing Legal and Ethical Challenges

• The company is handling recent challenges, including a lawsuit from News Corp for copyright infringement and a cease and assist order from The New York Times for inappropriate content use, with a vision for ethical AI development (26m57s).
• Perplexity believes in its approach to AI development, as stated on its blog post, and is committed to handling these challenges while continuing to innovate (27m18s).
• No one has copyright or ownership over truth or facts, and this applies to journalism as well, where referencing existing information from other sources is allowed, as long as the specific expression of truth is not copied verbatim (27m24s).
• The specific way something is written can have a copyright angle, which is relevant to the Open AI and New York Times scenario, but Perplexity is referencing truth that already exists in outlets and summarizing and synthesizing it for the user in a search experience (28m4s).
• There is a difference between AI that trains on proprietary content and AI that uses sources to give answers without training, and Perplexity falls into the latter category (28m23s).
• Perplexity relies on an open and thriving ecosystem of journalism to survive and improve, and the company needs real-time information created every day, which is why it wants to support publishers financially (28m44s).
• To address this, Perplexity will share ad revenue with publishers through a program that is not a short-term licensing model, but rather a long-term model where revenue is shared on a query level basis as the company scales (29m2s).
• The program is inspired by how Spotify shares revenue, and several publishers, including Fortune, Time, and WordPress, have signed up to be part of it, with more partners to be announced in the coming weeks (29m31s).
• Perplexity has also made grants to Northwestern University to research how tools like theirs can help journalists write better and do fact checks more efficiently (29m50s).
• The company is confident that its program will resonate with the journalism community and help both parties flourish together in the future (29m45s).
• Perplexity handles allegations of plagiarism by always attributing sources, which makes it hard to claim plagiarism, and the company is trying its best to synthesize information rather than reproduce it verbatim (30m39s).
• The goal is to summarize and synthesize information from a diverse set of sources, giving credit to the original sources, and controlling AI systems to the best possible extent (31m8s).
• A revenue-sharing model is being implemented, where ad revenue is shared with the original source, unlike Google, which only provides traffic but keeps the ad revenue (31m31s).
• This approach aims to create a sustainable system where users can access information without being bombarded with ads, and content creators can monetize their work more effectively (32m7s).
• APIs are being offered for free to journalists and websites, allowing them to build AI-native products and chatbots, and to create a system that is economically lucrative for them (32m18s).

Perplexity's Long-Term Goals and Vision

• The company's vision is to become a reliable answer machine, helping people get answers to their questions and accomplish tasks, and making transactions more efficient (33m24s).
• The goal is to become a category-creating company, like Uber, Facebook, and Airbnb, and to be a history-defining company in the future (32m52s).
• The company's leadership journey has involved rapid growth, from a scrappy founder to a CEO of a $9 billion AI company, and the leader is still learning and upgrading their skills (34m27s).
• A bias for action is encouraged in the company to maintain speed, even with a growing team of around 100 people, with the goal of solving the problem of scaling while staying fast (34m53s).
• The company avoids hiring experts who have already had major successes, instead opting for talented individuals who have not yet had their first major hit, as they tend to be more motivated and driven (35m42s).
• This approach is based on the idea that people who have already achieved success may struggle to push themselves for further success, and may not be as motivated to put in the effort required for a new challenge (36m47s).
• The company's approach to hiring and talent development is focused on giving people opportunities to try new things and take on new challenges, rather than relying on established experts (35m33s).
• The CEO uses the product extensively, averaging at least 10 queries a day, to stay close to the source of truth and make informed decisions (37m17s).
• This approach helps to identify customer frustrations and user pain points, and allows the CEO to provide feedback to engineers and product managers to drive improvements (38m8s).
• The company's focus on staying scrappy and agile at scale is driven by a desire to maintain a fast and innovative culture, even as the team grows (38m33s).
• The goal is for Perplexity to be known for helping the world become smarter, with users feeling they have learned something new after using the platform, making them wiser and more knowledgeable (38m52s).
• Most consumer products tend to waste people's time, but Perplexity aims to be different, with features like the Discover feed allowing users to learn something new while scrolling through it (39m43s).
• The ultimate goal is to make assistance and personal help accessible to everyone, similar to how billionaires have access to executive assistance, by leveraging AI to help people with mundane tasks and planning (39m52s).
• This vision is inspired by a fireside chat between Sam Altman and Bill Gates, where Gates described a future with AGI as being able to live a life similar to his, with access to information and assistance at all times (40m6s).
• The idea is to make life easier for people by providing them with tools that can truly understand and help them, making their lives more manageable and freeing up time for more important things (41m10s).
• The founder's goal is to leave a mark in the world by creating a tool that helps people live a better life, and if Perplexity can provide a life similar to Bill Gates', he would be very happy (41m37s).

Q&A with Aravind Srinivas

• The founder is open to audience questions and is willing to share his experiences and insights with the audience (41m46s).
• When asked about his journey from PhD student to CEO, the founder is asked to share a habit he had to let go of and a new one he learned that helped him become a leader (42m2s).
• Waking up early has been a helpful habit, with the goal of getting more hours in the day, and going to bed early to achieve this, with the last time waking up later than 8:00 a.m. being at least two to four years ago (42m32s).
• Regular workouts have become a priority, aiming for at least three days a week, which is a change from not working out much before (43m8s).
• The biggest risk or challenge facing the company is the difficulty in scaling while maintaining quality, as it gets harder to execute well without a drop in quality when the number of people increases (43m48s).
• This challenge is referred to as "edification," where the product gets worse in quality for initial loyalists as the business scales (44m32s).
• As a leader, seeking opinions from others, such as the chief business officer Dimitri, is crucial in addressing ethical issues, and trusting others' instincts when they are better suited to solve a problem (45m23s).
• Engaging with people on the other side of an issue and educating them on the company's goals can be an effective approach, as seen in the instance with Forbes, where a critic changed their stance after being explained the company's intentions (46m9s).
• The goal is to help people find the answers they're looking for, and introducing ads in suggestions doesn't affect the unbiased nature of the information presented to users, as the answers to those suggested questions are still unbiased and uninfluenced by ads (47m15s).
• The key to making ads work without interfering with the core value of the product is relevance, and evidence shows that people find relevant ads, such as those on Instagram, useful and often make purchases as a result (48m16s).
• To bring a high-quality product to scale, the company needs to figure out intelligent sweet spots of monetization, but the core value of the product remains that any question asked will have an answer that is uninfluenced by ads and always truthful (48m40s).
• As the co-founder of Perplexity, the question that is most perplexing is not explicitly stated, but rather leads to a round of Rapid Fire questions (49m11s).
• If not the CEO of Perplexity, the alternative career path would likely be AI research, which was the previous field of work (49m54s).
• The all-time favorite Cricket moment is when India won the World Cup in 2011 (50m6s).
• The preferred Tech Visionary to have dinner with, dead or alive, is Larry Page (50m18s).
• The strangest search query seen on Perplexity is someone buying a face mask with an opening only for the eyes, possibly for skiing or another specific context (50m36s).
• A user's search query was analyzed, which involved biking in cold weather, and the intent behind the query was to find a product that could cover the face, keep the user warm, and allow them to breathe while only having an opening for the eyes (51m7s).
• The user's search query was ambiguous, as it could also be interpreted as planning a heist, but the actual intent was related to biking in cold weather (51m1s).
• The search results provided to the user were effective, as they ended up buying a product directly from the search results (51m25s).
• The conversation with Aravind Srinivas, Cofounder and CEO of Perplexity, came to a close, with appreciation expressed for his participation (51m34s).