An interactive learning resource for understanding Tensor Logic: The Language of AI by Pedro Domingos (2025).
This is a comprehensive, interactive guide designed for entry-level RL engineers who want to understand the groundbreaking Tensor Logic paper. It unifies neural networks and symbolic AI into a single programming language.
- 🎨 Beautiful, interactive web interface
- 📊 Live demos and visualizations
- 📈 Progress tracking
- 🧪 Interactive exercises
- 📝 Knowledge check quiz
- 🗺️ 12-week learning roadmap
- 🎮 RL application examples
- Einstein Summation: The foundation of tensor operations
- Logic Programming: Datalog and symbolic reasoning
- The Unification: How logic rules = tensor operations
- Embedding Space Reasoning: Temperature-controlled inference
- RL Applications: Safe RL, explainable policies, sample-efficient learning
This guide is specifically designed for:
- RL engineers (entry level)
- Deep learning practitioners curious about symbolic AI
- Researchers interested in neurosymbolic AI
- Anyone who knows PyTorch and wants to learn tensor logic
Must Have:
- Basic Python and PyTorch
- Understanding of tensors and matrix operations
- Neural network basics (MLPs, backprop)
Nice to Have:
- Familiarity with
torch.einsum() - Graph neural networks
- Basic logic/reasoning concepts
This repository also includes:
- Comprehensive Markdown guide (60+ pages)
- Quick reference cheat sheet
- Python starter code with 5 demos
"Tensor Logic: The Language of AI" by Pedro Domingos (2025)
Found a typo? Have suggestions? Want to add more examples?
- Open an issue
- Submit a pull request
- Share your feedback!
This educational resource is provided for learning purposes. The original paper belongs to its author.
Based on the excellent work by Pedro Domingos at the University of Washington.
Created for the AI/RL community
Start learning now: Open the Interactive Guide →