#ai-evaluation

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The Morning After: Google accused of using novices to fact-check Gemini's AI answers

Google instructed contract workers to evaluate all prompts regardless of expertise, only skipping if content is missing or harmful.

Google accused of using novices to fact-check Gemini's AI answers

Google's new guidelines may compromise the accuracy of AI evaluations by requiring workers to rate prompts outside their area of expertise.

GPT is far likelier than other AI models to fabricate quotes by public figures, our analysis shows

Large language models exhibit significant differences in generating responses to prompts, particularly when asked for quotes from public figures.

Gentrace makes it easier for businesses to test AI-powered software

Gentrace offers a platform that simplifies testing for generative AI, fostering collaboration across teams and improving evaluation methods.
#machine-learning

Epoch AI Unveils FrontierMath: A New Frontier in Testing AI's Mathematical Reasoning Capabilities

Epoch AI's FrontierMath addresses the inadequacies of existing AI benchmarks by evaluating advanced mathematical reasoning with rigorous, novel problems.

Podcast: Best Practices for Generative AI Production Deployment with Lukas Biewald

Best practices for integrating generative AI into production focus on robust evaluation and performance metrics.

The Role of the Confusion Matrix in Addressing Imbalanced Datasets

Confusion matrices are essential tools for evaluating classification algorithms, especially when dealing with imbalanced datasets.

Human Evaluation of Large Audio-Language Models | HackerNoon

GPT-4 exhibits high consistency in evaluations compared to human judgments, outperforming GPT-3.5 Turbo.

Holistic Evaluation of Text-to-Image Models: Author contributions, Acknowledgments and References | HackerNoon

The collaboration resulted in a framework to improve the evaluation of AI metrics and scenarios.
The project emphasizes the importance of structured AI research approaches.

Epoch AI Unveils FrontierMath: A New Frontier in Testing AI's Mathematical Reasoning Capabilities

Epoch AI's FrontierMath addresses the inadequacies of existing AI benchmarks by evaluating advanced mathematical reasoning with rigorous, novel problems.

Podcast: Best Practices for Generative AI Production Deployment with Lukas Biewald

Best practices for integrating generative AI into production focus on robust evaluation and performance metrics.

The Role of the Confusion Matrix in Addressing Imbalanced Datasets

Confusion matrices are essential tools for evaluating classification algorithms, especially when dealing with imbalanced datasets.

Human Evaluation of Large Audio-Language Models | HackerNoon

GPT-4 exhibits high consistency in evaluations compared to human judgments, outperforming GPT-3.5 Turbo.

Holistic Evaluation of Text-to-Image Models: Author contributions, Acknowledgments and References | HackerNoon

The collaboration resulted in a framework to improve the evaluation of AI metrics and scenarios.
The project emphasizes the importance of structured AI research approaches.
moremachine-learning

New Dimensions in Text-to-Image Model Evaluation | HackerNoon

A comprehensive evaluation framework for image generation models is essential to address biases and societal impacts, highlighting the need for holistic assessment beyond traditional benchmarks.

The AI industry is obsessed with Chatbot Arena, but it might not be the best benchmark | TechCrunch

Chatbot Arena has emerged as a crucial platform for evaluating AI models, emphasizing real-world user preferences over traditional benchmarks.

Deriving the DPO Objective Under the Plackett-Luce Model | HackerNoon

The Plackett-Luce model provides a foundation for understanding user preferences in ranking systems.

AI now beats humans at basic tasks - new benchmarks are needed, says major report

AI systems are rapidly advancing and often outperforming humans, rendering many benchmarks obsolete.

Lawmaker set to introduce bill to standardize AI system testing

Sen. John Hickenlooper is sponsoring the "Validation and Evaluation for Trustworthy Artificial Intelligence Act" to ensure accurate testing and safe deployment of AI systems.
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