Current LLM scaling hits a wall on fluid intelligence benchmarks (ARC); reasoning models and RL post-training only automate verifiable domains. True AGI needs human-level sample efficiency…

Coding agents succeeded because code provides formal verification (unit tests), enabling massive RL post-training data generation. This paradigm will extend to math and other verifiable dom…

Trillions in compute poured into one architecture (transformers + gradient descent) creates fragility. Chollet argues the same resources applied to alternative paradigms (genetic algorithms…