Relevance in the Age of Generative Search - Haystack US 2023 Keynote

Overview

Explore strategies for integrating generative AI and language models into search applications, balancing accuracy and relevance while leveraging new capabilities in the evolving search landscape.

Syllabus

• Introduction to Generative AI in Search
Overview of Generative AI and Language Models
Evolution of Search Technology and Generative Capabilities
• Understanding Relevance and Accuracy in Search Applications
Defining Relevance in the Context of Generative Search
Challenges in Balancing Accuracy with Relevance
• Integrating Generative AI into Search Systems
Strategies for Implementing Generative AI in Existing Search Applications
Tools and Platforms for Building Generative Search Solutions
• Leveraging New Capabilities in Generative Search
Advanced Features Enabled by Language Models
Case Studies: Successful Integration of Generative AI in Search
• Evaluating and Measuring Search Effectiveness
Metrics for Assessing Relevance and Accuracy
Continuous Improvement through Feedback Loops and Model Tuning
• Ethical Considerations and Bias in Generative Search
Identifying and Mitigating Bias in AI-Driven Search Applications
Ensuring Responsible and Ethical Use of Generative Models
• Future Trends in Generative Search Technology
Emerging Technologies and Innovations
Predictions for the Evolution of Search Applications
• Conclusion and Key Takeaways
Summary of Strategies and Best Practices
Open Discussion on Future Opportunities and Challenges in Generative Search

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Subjects

Data Science