Google DeepMind CEO Demis Hassabis says current AGI falls short of human intelligence in continuous learning, long-term planning, and performance consistency. Systems excel in niches like IMO math but falter on basics. True AGI expected in 5-10 years.
Key Points
- 1.Lacks continuous learning: post-training systems remain static
- 2.No long-term planning: limited to short-term tasks unlike humans
- 3.Inconsistent performance: IMO gold medals but basic math errors
- 4.True AGI arrival predicted in 5-10 years by Hassabis
Impact Analysis
Highlights critical gaps for AGI development, guiding research priorities. Resets hype around near-term human-level AI. Reinforces need for robust, adaptable systems.
Technical Details
Ideal AGI should learn from runtime experience and adapt contextually. Humans plan over years; current systems cannot. No ability cliffs: experts don't fail basics.