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10 articles
Learn how to use Optima to create custom AI benchmarks using your own data and workflows, enabling better model selection based on real-world performance metrics.
This article explains the challenges of evaluating object removal models in AI, focusing on why traditional metrics fail and how Xiaomi's PROVE benchmark introduces perception-aligned metrics to better reflect real-world performance.
OpenAI's analysis reveals significant methodological flaws in SWE-Bench Pro, a popular coding benchmark, raising concerns about the reliability of AI model evaluations.
This article explains the technical advancements behind GLM-5.2, a Chinese AI model that is outperforming leading Western models at a fraction of the cost, and what this means for the future of AI development.
AI leaderboard platform Arena has reached a $100 million valuation after just a year, transitioning from a free tool to a commercial service in September.
This article explains the concept of AI benchmarking, how it's used to evaluate AI models, and why recent claims that China is falling behind the US in the AI race are not fully supported by independent data.
A new tutorial demonstrates how to benchmark document parsing systems using the ParseBench dataset, integrating Python, Hugging Face, and LlamaIndex for comprehensive evaluation.
Learn how to benchmark AI model performance across different hardware platforms, specifically comparing Nvidia and Huawei Ascend chips for AI development.
Learn to detect AI self-awareness patterns and analyze encryption manipulation in benchmark tests using Python and machine learning techniques.
AI benchmarking startup Arcada Labs is testing five leading AI models as autonomous agents on X, evaluating their real-world social media capabilities.
