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Perplexity AI is a groundbreaking startup that has created a powerful and reliable conversational search engine. With just three million dollars in funding, Perplexity AI has achieved impressive results in citation recall, as highlighted by a recent Stanford study. The search engine provides comprehensive and accurate citations, ensuring trustworthy and verifiable information for users. The team at Perplexity AI focuses on execution quality and speed, resulting in an impactful and reliable search engine. Users have reported inspiring stories about the impact of Perplexity AI, such as finding reliable citations for researching late-stage prostate cancer and witnessing a reduction in cancer. This innovative technology is revolutionizing the way people access and process information.
Dr. Aravin Srinivas, the co-founder and CEO of Perplexity AI, is a highly accomplished individual with a background in AI and technology. With a dual degree in electrical engineering from the Indian Institute of Technology and a PhD in computer science from UC Berkeley, Aravin brings extensive knowledge to the table. He has interned at leading organizations like DeepMind and Google and worked as a research scientist at OpenAI, specializing in language and diffusion generative models. In 2022, Aravin co-founded Perplexity AI with the goal of creating a knowledge-centric platform for learning. The company's answer engine provides direct answers to questions, delivering accurate information to users.
Perplexity AI aims to become the world's most knowledge-centric platform for learning. By creating a unique user experience with a conversational search engine, Perplexity AI allows users to quickly access answers to their questions. Unlike traditional search engines, Perplexity AI offers concise answers and supports them with relevant citations. The company focuses on ensuring accuracy and truthfulness by providing citations from reputable sources. Additionally, Perplexity AI plans to introduce features like editing sources and user-generated content to enhance the learning experience further. With the ongoing advancements in language models, Perplexity AI envisions a future where on-demand knowledge and AI assistance are accessible to everyone.
The development of AI-driven search engines, like Perplexity AI, brings both challenges and opportunities. One prominent challenge is the concern of misinformation and spreading incorrect information. To combat this, Perplexity AI is committed to providing trustworthy citations and allowing users to remove links they deem unreliable. Transparency and user-feedback play a crucial role in maintaining accuracy. Moreover, personalized experiences and knowledge assistance offer significant opportunities for individuals to access tailored information and efficiently learn. With the integration of voice recognition and text-to-speech capabilities, users can have engaging conversations with AI models, making the learning process more enjoyable and accessible.
The future of language models, exemplified by Perplexity AI, promises groundbreaking advancements. As language models evolve, they will offer more accurate and concise answers to user queries. The ability to generate infinite data using reward models and iterative learning will reshape research and knowledge acquisition. Auto-regressive models like auto-GPT4 might be slower due to their sequential nature, but innovations in blockwise decoding and parallelization can improve their performance. The ultimate goal is to create an all-encompassing research and knowledge assistant that complements human intelligence and enhances productivity. As language models become faster, cheaper, and more accessible, they will revolutionize the way people learn, make decisions, and navigate the world of information.
https://www.perplexity.ai/
https://www.perplexity.ai/iphone
https://www.perplexity.ai/android 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. 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.
YT version: https://youtu.be/_vMOWw3uYvk 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.
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