AI in Search in 2023

Overview

Explore AI's impact on search in 2023, covering challenges, models, and future trends in information retrieval and conversational systems.

Syllabus

• Introduction to AI in Search
Overview of AI's role in search engines
Historical context and evolution of search technologies
• Core Challenges in Modern Search
Understanding user intent
Managing scale and efficiency
Handling diverse multimedia content
• Key AI Models in Search
Machine Learning and Deep Learning models for search
Natural Language Processing (NLP) techniques
Transformer-based models (e.g., BERT, GPT)
• Enhancements in Information Retrieval
Semantic search and contextual understanding
Personalization and user-driven search customization
Ranking algorithms and relevance
• AI in Conversational Systems
Chatbots and virtual assistants
Dialogue systems and natural language interaction
Multi-turn conversation dynamics
• Future Trends in AI-Driven Search
Integration of AI with Augmented Reality (AR) and Virtual Reality (VR) in search
Ethical considerations and bias in AI search algorithms
Emerging technologies and hybrid search solutions
• Practical Applications and Case Studies
Industry-specific search applications
Case studies of successful AI implementation in search
• Course Wrap-Up
Review of key concepts
Discussion on the future of search
Final project presentations and feedback

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Subjects

Data Science