How to Read an AI Safety Benchmark Before You Buy
A buyer’s guide to benchmark scope, hazard taxonomies, prompts, graders, attacks and deployment gaps in AI safety testing.
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Meydo Journal
Ideas, product stories, and a closer look at how personal AI is moving into everyday life.
Synthetic Data Is Not a Privacy Shortcut
How to evaluate synthetic data for leakage, utility, coverage and governance—and when differential privacy changes the claim.
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Model Cards and Data Cards: Documentation Buyers Can Use
What useful AI model and dataset documentation should reveal about intended use, evaluation, provenance, limitations and change history.
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Do AI Coding Assistants Speed Up a Team? Measure the Whole Change
A practical pilot for AI coding assistants: compare all assigned work, author and reviewer effort, acceptance, rework and safety—then apply explicit st...
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A NIST AI RMF Release Gate for a Document-Answering Assistant
A bounded document-answering assistant becomes an auditable release decision: map four risks, freeze a 100-case test set, set illustrative go/no-go thr...
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Content Credentials Explained: What C2PA Proves—and What It Doesn’t
How to check a C2PA Content Credential after export and distribution: validate the delivered file, inspect signer and ingredient claims, and distinguis...
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AI Energy Claims: A Worksheet for Comparing Real Tasks
Test an AI energy-per-query claim with matched IT and facility meters, successful tasks, grid factors and explicit training allocation. Includes a clea...
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Prompt Caching for LLM Apps: Cut Repeated Work, Not Corners
A concrete support-assistant prefix layout and two-request cost and latency exercise show when prompt caching helps—and when misses, output quality or ...
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Small Language Models on the Edge: When Local AI Wins
A worked decision for on-device, server or hybrid language processing: a repeatable test protocol, synthetic Python gate, and the privacy, latency, ene...
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