Waiter, There's an LLM in My Search - Exploring the Future of Search Engines

Overview

Explore the challenges and potential solutions for modern search engines affected by LLMs, from combating AI-generated content to implementing federated search systems for better information discovery.

Syllabus

• Introduction to Search Engines and LLMs
The evolution of search engines
Overview of Large Language Models (LLMs)
The intersection of search engines and LLMs
• Challenges Posed by AI-Generated Content
Identifying AI-generated content
Impact on search engine accuracy and relevance
Ethical considerations in handling AI-generated content
• Strategies for Combating AI-Generated Content
Content verification and fact-checking methods
Algorithms for detecting AI-generated text
User education and awareness
• Federated Search Systems
Definition and advantages of federated search
Case studies of federated search implementations
Integrating federated search with existing search engines
• Enhancing Information Discovery
Leveraging AI for improved search results
Personalized search experiences
Combining structured and unstructured data for richer results
• Future Directions in Search Engine Development
The role of AI in evolving search algorithms
Privacy and security considerations
Predicting user intent with AI
• Conclusion and Future Outlook
Recap of key challenges and solutions
The ongoing role of LLMs in search
Open questions and areas for further research

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Subjects

Data Science