AI Benchmarks Are Fake

AI benchmarks are how every major lab — OpenAI, Google, Anthropic, Meta — proves their model is "the best." The problem? The system is rigged by design. Labs can inflate their scores without technically breaking any rules — and some of them do. In this video I break down exactly how benchmark gaming works, why it's nearly impossible to detect, and why you can't trust a single leaderboard number in 2026. If you've ever wondered why the "#1 AI model" changes every week, or why benchmark scores don't match how the model actually performs when you use it — this is why. What you'll learn: → How benchmarks can be gamed without "cheating" → Why training data contamination is the industry's open secret → The 3 benchmarks most vulnerable to manipulation (including SWE-Bench) → Why "vibe evals" are replacing traditional benchmarks → How to actually test which AI model works best for your workflow