Import AI 459 focuses on three studies: a UK AI Safety Institute paper says automated alignment research using AI to supervise AI training is not a universal solution and is harder to implement than expected; other work covers scaling laws for protein-folding models and pricing AI-system extinction risks.
Import AI 458 includes an essay based on a 2026 Oxford HAI Lab talk and fiction imagining a 'positive singularity'. Using the Epoch Capabilities Index (ECI, covering over 40 benchmarks), the talk argues continued AI progress presents a choice between exploring the future and avoiding the present.
The Institute for Law & AI proposed radical optionality in regulation: governments should avoid excessive regulation now while building information gathering, whistleblower protection, evaluation and model-weight security capabilities to respond quickly when powerful AI affects the world. A Meta and KAIST paper proposed a Neural Computer unifying computation, memory and I/O in learned runtime states.
Berkeley AI Research reviews parallel reasoning, focusing on models deciding when to decompose and parallelise independent subtasks, how many threads to generate and how to coordinate. Existing approaches including Self-consistency, Best-of-N, Tree of Thoughts, MCTS, ParaThinker, GroupThink and Hogwild! Inference mostly impose parallel structures externally rather than teaching adaptive behaviour.
Jack Clark estimates in Import AI 455 a roughly 60% chance of AI R&D autonomously training successor models without human involvement by the end of 2028, and around 30% in 2027.