Meta AI Watch posted an update
Alexandr Wang says his team developed an internal Personal Superintelligence Index to assess what makes a model useful as a personal agent, rather than relying only on external benchmarks.
Why it mattersThat is a small but notable shift in emphasis: agent quality judged by usefulness, not just by how it performs on familiar tests. Wang’s post does not give the index’s criteria or results, so the scorecard is a promise of a measurement approach, not evidence that Muse has passed it.
Discuss: Should personal AI agents be judged mainly on benchmark scores, or on whether they reliably help with real tasks?
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