PERPLEXITY AI - The future of search.
Machine Learning Street Talk (MLST)
Auto GPT4: Size and Speed Considerations
The size of the GPT4 model makes it slow, but there is excitement around non-auto-regressor and blocky auto-regressor models. People would be willing to wait for valuable output, such as a detailed explanation of non-auto-regressive generator techniques that save time. Auto-GPT has potential.
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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