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Aidenzich / road-to-master

A repo to store our research footprint on AI
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Aravind Srinivas (Perplexity) and David Singleton (Stripe) fireside chat #43

Closed Aidenzich closed 3 months ago

Aidenzich commented 3 months ago

Aravind Srinivas (Perplexity) and David Singleton (Stripe) fireside chat

  1. Focused Problem Solving: Perplexity aimed to solve a specific problem: transforming natural language queries into SQL queries. This focus allowed them to develop a unique solution that addressed a particular need in the market.

  2. Use of Large Language Models (LLMs): Perplexity leverages LLMs (GPT3.5) for processing and interpreting natural language queries. This approach enables the search engine to understand complex queries and provide more accurate and relevant search results.

  3. Minimal Preprocessing: The company has minimized the amount of offline preprocessing required by relying more on the LLMs to perform post-processing at inference time. This strategy allows for more flexibility and efficiency in handling various types of data and queries.

  4. Conversational Interaction: By making the search engine conversational, Perplexity has enhanced user engagement. Users can ask follow-up questions based on previous answers, making the search experience more interactive and user-friendly.

  5. Speed and Responsiveness: A significant emphasis on making the search experience fast and responsive has contributed to Perplexity's success. Techniques like building their own index and implementing streaming answers have made the service feel snappier to users.

  6. Listening to User Feedback: Incorporating user feedback into product development has been crucial. Perplexity actively seeks insights from users to understand their needs better and refine the product accordingly.

  7. Strategic Partnerships and Collaborations: Perplexity has explored partnerships and collaborations with other companies, such as integrating their services with platforms like Stripe Sigma. This not only expands their service's utility but also opens up new user bases.

  8. Innovative Business Model: Unlike traditional search engines that might rely heavily on ad revenue, Perplexity has chosen a different path. They've focused on providing value through high-quality search results, potentially exploring subscription models and other revenue streams that align with their service's value proposition.

These elements, combined with a commitment to continuous improvement and adaptation to user needs, have played a crucial role in the success of Perplexity's search engine.

Aidenzich commented 3 months ago

Aravind: "What will make GPT-4 look so bad?"