PERPLEXITY AI – The future of search.

Interview with Aravind Srinivas, CEO and Co-Founder of Perplexity AI – Revolutionizing Learning with Conversational Search Engines

Dr. Tim Scarfe talks with Dr. Aravind Srinivas, CEO and Co-Founder of Perplexity AI, about his journey from studying AI and reinforcement learning at UC Berkeley to launching Perplexity – a startup that aims to revolutionize learning through the power of conversational search engines. By combining the strengths of large language models like GPT-* with search engines, Perplexity provides users with direct answers to their questions in a decluttered user interface, making the learning process not only more efficient but also enjoyable.

Aravind shares his insights on how advertising can be made more relevant and less intrusive with the help of large language models, emphasizing the importance of transparency in relevance ranking to improve user experience. He also discusses the challenge of balancing the interests of users and advertisers for long-term success.

Exploring the challenges and opportunities with this new search modality, Aravind highlights how blurring the boundaries between a conversational interface and a search user interface can lead to more personalized search experiences. Perplexity’s vision is to create a dynamic, personalized Wikipedia-style experience for users, encouraging them to ask follow-up questions and explore related topics in an engaging loop. As users zoom in on specific details or zoom out to understand broader connections, learning becomes more efficient and tailored to individual needs.

The interview delves into the challenges of maintaining truthfulness and balancing opinions and facts in a world where algorithmic truth is difficult to achieve. Aravind believes that opinionated models can be useful as long as they don’t spread misinformation and are transparent about being opinions. He also emphasizes the importance of allowing users to correct or update information, making the platform more adaptable and dynamic.

Lastly, Aravind shares his thoughts on embracing a digital society with large language models, stressing the need for frequent and iterative deployments of these models to reduce fear of AI and misinformation. He envisions a future where using AI tools effectively requires clear thinking and first-principle reasoning, ultimately benefiting society as a whole. Education and transparency are crucial to counter potential misuse of AI for political or malicious purposes.

Join us in this engaging conversation as we explore the future of AI, language models, and the transformation of learning, research, and personal knowledge management with Aravind Srinivas of Perplexity AI.

Pod version: https://podcasters.spotify.com/pod/show/machinelearningstreettalk/episodes/PERPLEXITY-AI—The-future-of-search-e23i5fq

Aravind Srinivas:
https://www.linkedin.com/in/aravind-srinivas-16051987/
https://scholar.google.com/citations?user=GhrKC1gAAAAJ&hl=en
https://twitter.com/aravsrinivas?lang=en

Interviewer: Dr. Tim Scarfe (CTO XRAI Glass)
Patreon: https://www.patreon.com/mlst
Discord: https://discord.gg/ESrGqhf5CB

TOC:
Introduction and Background of Perplexity AI [00:00:00] The Importance of a Decluttered UI and User Experience [00:04:19] Advertising in Search Engines and Potential Improvements [00:09:02] Challenges and Opportunities in this new Search Modality [00:18:17] Benefits of Perplexity and Personalized Learning [00:21:27] Objective Truth and Personalized Wikipedia [00:26:34] Opinions and Truth in Answer Engines [00:30:53] Embracing the Digital Society with Language Models [00:37:30] Impact on Jobs and Future of Learning [00:40:13] Educating users on when perplexity works and doesn’t work [00:43:13] Improving user experience and the possibilities of voice-to-voice interaction [00:45:04] The future of language models and auto-regressive models [00:49:51] Performance of GPT-4 and potential improvements [00:52:31] Building the ultimate research and knowledge assistant [00:55:33] Revolutionizing note-taking and personal knowledge stores [00:58:16]

References:
Evaluating Verifiability in Generative Search Engines (Nelson F. Liu et al, Stanford University)
https://arxiv.org/pdf/2304.09848.pdf

Note: this was a sponsored interview and filmed on April 19th.