Enterprise AI Analysis
General Scales Unlock AI Evaluation
This analysis delves into a novel methodology that transforms AI evaluation by introducing general scales, enabling robust explanations and instance-level predictions for complex AI systems. Learn how this approach addresses the limitations of traditional benchmarking and paves the way for reliable AI deployment.
Executive Impact
Revolutionizing AI Assessment
Our research demonstrates quantifiable advancements in AI evaluation, moving beyond simple performance metrics to provide deep insights into model capabilities and task demands.
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Total Annotations
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General Scales
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Avg. Inter-rater Agreement
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Avg. In-Dist. AUROC
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
Automated AI Evaluation Process
Our two-pronged approach, the System Process and the Task Process, ensures comprehensive and scalable AI evaluation. From model ability profiling to task demand analysis, each step is designed for maximum insight and predictability.
New AI System M (System Process)
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Run on ADeLe Battery
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Plot Characteristic Curves
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Extract Ability Profile
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New Task Instance D (Task Process)
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Apply DeLeAn Rubrics
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Obtain Demand Profile
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Predict Performance
Inter-rater Agreement with GPT-4o
A critical validation of our rubrics shows high agreement between human annotators and GPT-4o, ensuring the reliability and scalability of our demand-level annotations.
0 Average Spearman Correlation (Delphi & GPT-4o)| Assessor Type | In-Distribution (AUROC) | OOD (Task AUROC) | OOD (Benchmark AUROC) |
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| Embeddings (RF) |
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| Finetuned LLaMA |
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Forecasting Novel AI Challenges
Our demand-based assessor enables enterprises to anticipate AI model performance on completely new tasks and benchmarks, mitigating risks and guiding strategic deployment decisions with unprecedented accuracy. This is crucial for navigating rapidly evolving AI landscapes.
LLM Ability Evolution with Scale
Visualizing how LLM abilities in dimensions like 'Knowledge of Formal Sciences' and 'Mind Modelling' scale with model size, revealing insights into the impact of chain-of-thought and distillation.
Small LLM
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Medium LLM (CoT, Distilled)
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Large LLM (CoT, Knowledge)
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SOTA LLM (High Abilities)
LLaMA 3.1 405B-Instruct KNn Ability
The LLaMA 3.1 405B-Instruct model achieves a high ability score in 'Knowledge of Natural Sciences', demonstrating its strong command over domain-specific scientific information.
0 Ability Score (KNn)ROI Calculation
Quantify Your AI Efficiency Gains
Estimate the potential annual cost savings and hours reclaimed by optimizing AI workflows with our methodology.
Estimated Annual Savings
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Hours Reclaimed Annually
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Your Journey
Implementation Roadmap
Our structured approach ensures a seamless integration of general scales into your AI evaluation pipeline, delivering actionable insights at every stage.
Discovery & Customization
Tailor scales and rubrics to your specific enterprise AI use cases and data modalities.
Automated Annotation
Leverage LLMs for efficient, high-quality demand-level annotation across your datasets.
Ability Profiling & Demand Analysis
Generate comprehensive ability profiles for your AI systems and map task demands.
Predictive Assessor Deployment
Integrate robust assessors for instance-level performance prediction and risk mitigation.
Continuous Optimization
Iteratively refine and extend the evaluation framework as your AI capabilities evolve.
Next Steps
Ready to Transform Your AI Evaluation?
Our general scales methodology offers unprecedented clarity and foresight for your enterprise AI initiatives. Let's discuss how to implement a robust, scalable, and explainable AI evaluation framework tailored to your needs.
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