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Google hides secret message in name list of 3,295 AI researchers
Gemini 2.5 paper hides Easter egg in massive author list—but why so many contributors?
These large language models, which power Google's chatbot AI assistant, feature simulated reasoning capabilities that produce a string of "thinking out loud" text before generating responses in an attempt to help them solve more difficult problems. It involves not just machine learning researchers but also software engineers building infrastructure, hardware specialists optimizing for specific processors, ethicists evaluating safety implications, product managers coordinating efforts, and domain experts ensuring the models work across different applications and languages. All that being said, we wonder: Does the Gemini 2.5 paper show how modern AI research has become a massive team sport—one where traditional notions of authorship struggle to capture the collaborative reality of pushing the tech frontier, or is Google simply being unusually generous in granting credit?
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