What You Need to Know Before
You Start
Starts 6 June 2025 13:19
Ends 6 June 2025
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19 minutes
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Overview
Explore a new neuronal alternative to transformer architecture:
Continuous Thought Machine (CTM) with artificial dimensions for dynamic neuronal synchronization to improve AI reasoning.
Syllabus
- Introduction to AI Architectures
- Fundamentals of Continuous Thought Machine (CTM)
- Artificial Dimensions in CTM
- Dynamic Neuronal Synchronization
- Building a CTM Model
- Training CTM Networks
- Evaluating CTM Performance
- Applications of CTM in AI
- Challenges and Future Directions
- Course Summary and Next Steps
Overview of Traditional AI Architectures
Limitations of Transformer Models
Conceptual Framework of CTM
Differences from Transformers
Defining Artificial Dimensions
Role in Neuronal Synchronization
Mechanisms of Synchronization
Impact on AI Reasoning
Core Components of CTM
Step-by-Step Construction
Data Requirements
Optimization Techniques
Metrics for Comparison
Case Studies
Real-World Use Cases
Future Potential of CTM
Technical and Ethical Considerations
Innovations and Research Opportunities
Key Takeaways
Resources for Further Learning
Subjects
Computer Science
