agi

A model went from 27 percent to around 57 percent, so it is more than halfway to AGI and the rest arrives shortly. That inference is wrong in at least four ways, and working through why is more useful than the score itself. This lesson covers the linearity assumption, construct validity, contamination, and what the framework is good for once you stop reading it as a progress bar.

The framework scores ten cognitive domains at ten percent each. Running it produces something more useful than the headline totals of 27 percent for GPT-4 and around 57 for GPT-5: a jagged profile, where a model is at or near full marks on some domains and at zero on others. This lesson walks the domains, reads both profiles column by column, and shows what the jaggedness explains.

For a term that anchors company charters, safety policy and hundreds of billions in investment, AGI has been remarkably undefined. A 2025 paper with over thirty authors proposes fixing that by borrowing psychology's most validated framework for human intelligence. This lesson covers why the definition was missing, what the paper anchors to, and what the borrowing assumes.