🔑Building good products on top of AI models is incredibly difficult
💡The focus should be on creating valuable products that solve real-world problems
🔍Retrieval-based models can help improve the quality of AI-generated content
❓AI models need to be trained to express uncertainty and cite sources
💡Dialogue systems provide a unique opportunity for interaction and deeper understanding
Why is building products on top of AI models difficult?
—Building good products requires not only AI expertise but also a deep understanding of user needs, problem-solving, and design principles.
What should the focus be when building products on top of AI models?
—The focus should be on creating valuable products that solve real-world problems and provide meaningful solutions to users.
How can retrieval-based models improve the quality of AI-generated content?
—Retrieval-based models can help provide accurate and relevant information by retrieving data from trusted sources and citing them in AI-generated content.
Why is it important for AI models to express uncertainty and cite sources?
—Expressing uncertainty and citing sources helps build trust in AI-generated content and promotes transparency and accuracy in information dissemination.
What is the advantage of dialogue systems in AI product development?
—Dialogue systems allow for interaction and deeper understanding, enabling users to ask questions, correct the system, and explore topics in a more engaging and informative way.
00:00Building good products on top of AI models is incredibly difficult.
03:28The focus should be on creating valuable products that solve real-world problems.
09:23Retrieval-based models can help improve the quality of AI-generated content.
12:37AI models need to be trained to express uncertainty and cite sources.
13:59Dialogue systems provide a unique opportunity for interaction and deeper understanding.
