The article explores the concept of alignment in artificial intelligence through the lens of language equivariance. It discusses how leveraging language structures can lead to more robust alignment mechanisms in AI systems, addressing challenges in ensuring that AI goals are in line with human intentions. Furthermore, it emphasizes the importance of understanding equivariance to improve AI safety and functionality.

The article explores the implications of having larger brains, both in humans and artificial intelligence, particularly focusing on how increased neural capacity could enhance cognitive abilities and the potential for new concepts and language. It discusses the relationship between brain size, computation, and the abstraction of concepts, emphasizing the significance of "pockets of computational reducibility" in understanding complex systems. The author speculates on how larger brains might lead to richer forms of communication and a more nuanced model of the world.