Introduction to Reasoning LLMs

Overview

Explore reasoning LLMs, top models, design patterns, agentic systems, RAG, LLM-as-a-Judge, visual reasoning, and hybrid approaches in this comprehensive talk on reasoning capabilities in large language models.

Syllabus

• Introduction to Reasoning LLMs
Overview of large language models (LLMs) and their reasoning capabilities
Historical context and development of reasoning in LLMs
• Top LLM Models
Overview of leading models in reasoning
Comparison of models based on performance and capabilities
• Design Patterns for Reasoning
Common design patterns for implementing reasoning in LLMs
Analysis of effectiveness and efficiency of different patterns
• Agentic Systems in LLMs
Definition and components of agentic systems
Case studies of agentic systems utilizing LLMs
• Retrieval-Augmented Generation (RAG)
Principles and techniques of RAG
Applications and advantages of RAG in reasoning
• LLM-as-a-Judge
Concept and applications of LLMs in evaluative roles
Ethical considerations and potential biases
• Visual Reasoning Integration
Techniques for integrating visual data into LLM reasoning
Examples of visual reasoning applications
• Hybrid Approaches in Reasoning LLMs
Combining LLMs with other AI systems for enhanced reasoning
Future trends and potential advancements in hybrid systems
• Conclusion
Recap of key points and emerging trends in reasoning LLMs
Opportunities for further exploration and research in the field

Subjects

Computer Science