AI Models' Cognitive Development Uneven: High Verbal, Low Perceptual
A new study analyses the cognitive profiles of generative AI models, revealing uneven development across generations, with high scores in verbal comprehension and working memory but persistent weaknesses in perceptual reasoning.
What happened?
Using a psychometric framework, researchers have evaluated the cognitive abilities of generative AI models. The study employed tasks adapted from the Wechsler Adult Intelligence Scale, alongside a newly developed Artificial Intelligence Quotient (AIQ) Benchmark. Six generations of leading multimodal models from two model families were analysed.
Key facts
| Publikationsdatum | 20 maj 2026 |
|---|---|
| Verbal förståelse/Arbetsminne | >98:e percentilen |
| Perceptuellt resonemang | <1:a percentilen |
| Antal modellgenerationer analyserade | 6 |
| Antal modellfamiljer analyserade | 2 |
”Initial evaluation of leading multimodal models using tasks adapted from the Wechsler Adult Intelligence Scale revealed a profoundly uneven cognitive architecture: near-ceiling performance in verbal comprehension and working memory (>$98^{\text{th}}$ percentile) contrasted with n”
Why it matters
The results indicate that contemporary AI possesses an uneven cognitive architecture. This asymmetry—featuring high performance in verbal comprehension and working memory contrasted with very low scores in perceptual reasoning—is critical for understanding current AI limitations. This further influences development towards artificial general intelligence (AGI).
Who is affected?
The study primarily affects AI researchers and developers working with generative AI and multimodal models. Companies producing or implementing these systems are also concerned, as the results highlight specific areas where current AI has clear deficiencies. Users are indirectly affected by AI service performance in various applications.
What else you should know
The research has been published as a preprint on arXiv and has not yet undergone peer review.
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