QA harness built for Claude Code | E2E testing with screen recordings, console logs, network HARs, and Playwright traces - wizenheimer/canary

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As more and more of us use Large Language Models (LLMs) for daily tasks, their potential biases become increasingly important. We investigated whether today’s leading models, such as those from OpenAI, Google, and others, exhibit ideological leanings. Our results reveal that LLMs are not ideologically uniform. Different models displayed distinct “personalities”, with some favouring progressive, libertarian, or regulatory stances, for example, while others frequently refused to answer.

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When SoTA LLMs are tasked to keep books tidy for a long period of time, they drift and the balance accuracy falls over time. This is a good example that we still need humans in the loop