What You'll Discover
This comprehensive research paper explores contextual AI as the next evolution in artificial intelligence, focusing on systems that understand and respond to human context in real-time across social, economic, and physical spaces.
Learn about groundbreaking applications in smart grids, autonomous navigation, and misinformation detection, backed by real-world case studies from Caltech's research initiatives.
25 pages of cutting-edge research, frameworks, and practical insights into the future of AI systems that truly understand context.
Key Research Areas
š§ In-Context Learning
Discover how AI models perform inference on new tasks without modifying internal parameters, enabling rapid adaptation to novel scenarios.
š Contextual Space Framework
Understand the five dimensions of contextual space: social, spatial, temporal, infrastructural, and task contexts.
š¤ Agentic Systems
Explore the evolution from reactive AI to proactive systems that can independently plan, execute, and manage complex workflows.
š Real-World Applications
Case studies in smart grid management, autonomous ocean vehicles, and AI-powered misinformation detection from Caltech research.
ā” Smart Grid Innovation
Learn how Caltech researchers are transforming energy distribution through AI-powered optimization and predictive maintenance.
š Challenges & Solutions
Address critical issues including data privacy, algorithmic bias, transparency, and regulatory compliance in contextual AI.
The BAI WInter School on Contextual AI
This white paper serves as the foundation for the BAI Winter School at Caltech (February 3-12, 2025), providing essential knowledge on contextual AI concepts, methodologies, and technologies.
Highlights research from Caltech's Center for Autonomous Systems and Technologies (CAST), Resnick Sustainability Institute, and leading industry partners.