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Stanford's AI Index Report 2024
Practical AI: Machine Learning, Data Science, LLM
Relevance of Benchmarks in AI Development
Current benchmarks in AI, rooted in academic tests like grade eight math problems, may not adequately address real-world industrial needs. While these benchmarks were vital in understanding AI capabilities initially, they may not reflect the diverse and context-dependent requirements of businesses utilizing AI solutions. Real-world applications vary significantly from academic benchmarks, requiring a shift towards more practical and industry-specific evaluation metrics to assess AI capabilities effectively.
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