Chapter 3: The Road to AGI
Current Capabilities vs AGI
| Capability | Current LLMs | AGI Requirement |
|---|---|---|
| Language | Excellent | ✓ |
| Reasoning | Improving | Robust |
| Learning | In-context | Online, continuous |
| Planning | Basic | Complex, long-term |
| World model | Limited | Deep understanding |
What LLMs Can Do
- Generate coherent text
- Follow instructions
- Basic reasoning
- Code generation
- Knowledge synthesis
What LLMs Struggle With
- Reliable factual accuracy
- Complex multi-step reasoning
- Novel problem solving
- Consistent world modeling
- True understanding vs pattern matching
Timeline Perspectives
Optimistic (5-10 years):
- Rapid capability gains
- Emergence of general abilities
- Breakthroughs in reasoning
Moderate (15-30 years):
- Steady progress
- Hybrid approaches needed
- Safety solutions developed
Skeptical (50+ years or never):
- Fundamental limits
- Wrong paradigm
- Need new approaches
Key Research Directions
- Reasoning: Chain-of-thought, verification
- World models: Grounded understanding
- Continual learning: Updating without forgetting
- Safety: Alignment that scales
Implications
Regardless of timeline:
- Massive economic impact
- Need for AI governance
- Education transformation
- Ethical considerations