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Anthropic's research suggests AI is accelerating AI development, with Claude now writing most of Anthropic's code, and Mythos making better 'next-step' research decisions than human researchers 64% of the time in flawed scenarios.
Chris Summerfield highlights a fundamental difference between AI and human cognition: AI lacks embodiment. Humans learn through interacting with the physical world, while current models are confined to digital environments, limiting their fundamental understanding.
The transformer architecture's self-attention mechanism allows AI to learn relationships between distant pieces of data. Summerfield argues this relational inference - determining what relates to what in context - is a core hallmark of both AI and human intelligence.
The history of AI since 2010 is a search for effective 'inductive biases' - architectural principles like reinforcement learning or the transformer - that enable intelligent behavior when combined with massive data and compute, not just raw scale alone.
Claude Opus 4.6 can now handle tasks taking a skilled human 12 hours, versus four minutes a year ago. Anthropic projects it will manage week-long tasks by the end of 2027.