Week 13: Business Models & Economics of AI
How AI companies make money and the investment landscape
Time Estimate: 3-4 hours
Topics Covered
- API-based business models vs open source
- AI infrastructure costs and unit economics
- Venture capital perspectives on AI investing
- The generative AI market map
- Future of AI business models
Featured Speaker
BH
Ben Horowitz
Co-founder, Andreessen Horowitz
Learn from industry leaders who are building the future of AI infrastructure and applications.
Video Resources
📹 Video content will be added here by Agent 2
Videos include keynotes, technical talks, and tutorials from industry leaders.
Reading Materials
📚 Reading list will be added here by Agent 3
Research papers, blog posts, and technical documentation.
🛠️ Hands-On Lab
Train an Autonomous Driving Agent
Advanced 4 hoursObjective
Implement imitation learning for autonomous driving in CARLA simulator.
Prerequisites
- PyTorch proficiency
- Reinforcement learning basics
- Python 3.8+
- Linux recommended for CARLA
Setup Instructions
- Install CARLA simulator:
https://github.com/carla-simulator/carla - Install Gymnasium:
pip install gymnasium - Clone starter:
git clone https://github.com/stanford-cs153/carla-lab - Download expert driving demonstrations
Tasks
- Set up CARLA environment and collect driving data
- Implement behavioral cloning (supervised learning)
- Train end-to-end driving model (image → steering/throttle)
- Implement DAgger (dataset aggregation)
- Compare behavioral cloning vs DAgger performance
- Visualize learned policy in CARLA