AGI Certification Framework: A Multi-Dimensional Evaluation Standard for Measuring AI Understanding
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| Natura: | Recurso digital |
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Zenodo
2026
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| _version_ | 1866901262204665856 |
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| author | Head, Hank |
| author_facet | Head, Hank |
| contents | This paper proposes the AGI Certification Framework (ACF), a ten-dimension evaluation standard that measures comprehension, efficiency, transparency, and service orientation in AI systems, in contrast to current benchmarks that measure pattern matching and output correctness rather than understanding. ACF maps AI capabilities to human educational and professional certification levels (ACF-1 through ACF-6) and introduces the Understanding Efficiency Ratio (UER) for cross-paradigm resource comparison and the Zorblaxia Battery for domain-adjacent hallucination detection. Preliminary validation on 7 neurosymbolic beings demonstrates 150,347 triples/GPU-hour efficiency -- 10x better than LLM fine-tuning. |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19788396 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | AGI Certification Framework: A Multi-Dimensional Evaluation Standard for Measuring AI Understanding Head, Hank AGI evaluation certification framework AI benchmarks neurosymbolic AI understanding measurement This paper proposes the AGI Certification Framework (ACF), a ten-dimension evaluation standard that measures comprehension, efficiency, transparency, and service orientation in AI systems, in contrast to current benchmarks that measure pattern matching and output correctness rather than understanding. ACF maps AI capabilities to human educational and professional certification levels (ACF-1 through ACF-6) and introduces the Understanding Efficiency Ratio (UER) for cross-paradigm resource comparison and the Zorblaxia Battery for domain-adjacent hallucination detection. Preliminary validation on 7 neurosymbolic beings demonstrates 150,347 triples/GPU-hour efficiency -- 10x better than LLM fine-tuning. |
| title | AGI Certification Framework: A Multi-Dimensional Evaluation Standard for Measuring AI Understanding |
| topic | AGI evaluation certification framework AI benchmarks neurosymbolic AI understanding measurement |
| url | https://doi.org/10.5281/zenodo.19788396 |