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Starts 6 June 2025 12:15

Ends 6 June 2025

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Towards Reasoning with a Million Environment Models

Explore advanced techniques for reasoning with large-scale environment models in AI systems, focusing on theoretical aspects of trustworthy artificial intelligence.
Simons Institute via YouTube

Simons Institute

2484 Courses


51 minutes

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Overview

Explore advanced techniques for reasoning with large-scale environment models in AI systems, focusing on theoretical aspects of trustworthy artificial intelligence.

Syllabus

  • Introduction to Large-Scale Environment Models
  • Overview of environment models in AI
    Importance and challenges of large-scale models
  • Theoretical Foundations of Environment Modeling
  • Probabilistic graphical models
    Bayesian networks and reasoning
    Markov decision processes
  • Scalability in Reasoning
  • Parallelization techniques
    Efficient data structures for large environments
    Distributed computing paradigms
  • Trustworthy AI: Ensuring Reliability and Safety
  • Definitions and metrics of trustworthiness
    Formal verification methods
    Robustness to adversarial attacks
  • Advanced Reasoning Techniques
  • Approximate inference methods
    Monte Carlo methods and sampling strategies
    Deep reinforcement learning integration
  • Knowledge Representation and Ontologies
  • Semantic models for environment representation
    Ontology integration for enhanced reasoning
  • Handling Uncertainty in Environment Models
  • Techniques for managing uncertainty
    Risk assessment and mitigation strategies
  • Experimentation and Evaluation of AI Models
  • Evaluation metrics for reasoning systems
    Case studies and real-world applications
  • Emerging Trends and Future Directions
  • Current research and innovation areas
    Future challenges in large-scale reasoning
  • Course Conclusion
  • Recap of key concepts
    Discussion on future ethical considerations in AI reasoning systems

Subjects

Computer Science