Considering the Relevance of Computational Uncertainty for AI Safety
SMRTR summary
Computational uncertainty problems expected with recursive self-improving AI are less relevant for today's neural networks. Current AI development involves training incomprehensible networks where uncertainty resembles ordinary scientific uncertainty.
SMRTR provides this summary for quick context. The original article belongs to Less Wrong.
Read the original article