Google DeepMind published a 57-page report titled "From AGI to ASI" on June 10, 2026, outlining the pathways from AGI (Human-level AI) to ASI (Artificial Superintelligence) through 4 main routes:
4 Pathways to Superintelligence
1) Scaling AGI — Expanding AGI models to be larger and more efficient through increased parameters, training data, and computational power 2) AI Paradigm Shifts — New paradigm shifts that could enable AI to leap forward, such as discovering new architectures or fundamentally different learning processes 3) Recursive Improvement — AI improving itself automatically, creating an accelerating feedback loop of development 4) Multi-Agent Collectives — ASI emerging from the collaboration of multiple large AI agents working together, creating more complex and efficient systems than individual agents
Key Facts
This is the first time Google DeepMind has established an official framework for ASI Identifies frictions and bottlenecks that may slow progress, such as hardware limitations, data constraints, and control challenges The transition may be a series of societal changes rather than a single event Impacts AI governance direction and global AI safety policies
Impact and Significance
This report is not just a future prediction but a clear roadmap showing Google DeepMind's long-term AI development vision. The identification of various challenges and obstacles demonstrates the company's serious preparation for the Superintelligence era. Source: https://aitoolsreview.co.uk/insights/google-post-agi-paper