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Google's MKA benchmark tests AI agents on 200 private professional tasks; a separate set of 10 public tasks is available for inspection
Google DeepMind's new Multimodal Knowledge Agent benchmark evaluates AI agents on 200 private tasks requiring visual analysis of complex professional files like architectural blueprints and engineering schematics. While the benchmark's headline scores are based on these private evaluations, only 10 sample tasks are publicly available for inspection. The benchmark uses weighted criteria where harder 'Climb' criteria measure advanced performance, and costs reported by Artificial Analysis exclude judge calls, limiting direct workplace cost comparisons.
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Nexus Mods: disclose AI at upload
Existing mods get a narrow transition.
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ASAPP’s chat sample
Selected brands limit generalization.