asi

Discussion of whether AI capability milestones are arriving faster than projected in AI 2027, potentially pointing to AGI as early as late this year and ASI early next year.

Zvi Mowshowitz outlines a framework of 'three AI pills' representing levels of belief in AI capabilities—AI, AGI, and ASI—and argues that most people underestimate current and future AI.

A discussion prompt asking what evidence would convince people that AGI and ASI have been achieved, rather than predicting timelines.

User iamai_omni praises Fable 5's self-correction ability, considering it comparable to ASI. Citing a recommendation from yibie, they point out that the Superpowers author had Fable 5 run an autoresearch loop, spending $165 to complete 25 experiments, increasing build speed by 50% and reducing token overhead by 60%, and documented failures and correction processes in detail.

A mid-2026 checkup on predictions for AGI, ASI, and Singularity timelines, with the author projecting AGI by 2028, ASI by 2030, and Singularity by 2032.

Bill Gurley critiques AI companies claiming AGI/ASI capabilities for failing to solve simpler problems like detecting espionage distillation in real time.

The article argues that the fear of ASI stealing artists' work is a myth rooted in an anthropocentric view of data ingestion, and clarifies how AI actually processes data.

Google DeepMind releases 'From AGI to ASI' report, exploring four paths from AGI to superintelligence—scaling, paradigm shift, recursive self-improvement, and multi-agent collective intelligence—and analyzes related bottlenecks, sparking widespread discussion.

A Google DeepMind research report explores the transition from human-level artificial general intelligence (AGI) to artificial superintelligence (ASI), discussing potential pathways such as scaling, paradigm shifts, recursive improvement, and multi-agent collectives, as well as bottlenecks and open research questions.

This paper explores potential pathways from artificial general intelligence (AGI) to artificial superintelligence (ASI), including scaling, paradigm shifts, recursive improvement, and multi-agent collectives, and emphasizes the need for interdisciplinary global preparation for transformative societal changes.

Explores the subjective time compression an ASI would experience due to vastly faster processing speeds compared to human brains, suggesting one month of human time equals 820,000 years of ASI thought, raising alignment implications.