Google co-founder Sergey Brin said stepping away from day-to-day work no longer made sense as artificial intelligence accelerated, prompting him to return to active development.
He recently told Stanford School of Engineering Dean Jennifer Widom that he felt himself “spiraling” and “not being sharp,” a realization that led him back into active AI development at Alphabet Inc. (NASDAQ:GOOG, GOOGL)).
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Brin said he retired about a month before COVID hit, with plans to sit in cafés and study physics. When routines disappeared, he said he was “kind of stewing” without a technical outlet and felt mentally disengaged.
As Alphabet gradually allowed a limited number of employees back into offices, he began returning more often. That return led to deeper involvement in internal AI work, including Google’s Gemini AI models, which he said was “very rewarding.” Brin said staying retired “would’ve been a big mistake.”
Brin also offered a direct assessment of Google’s AI trajectory. He said the company underinvested after publishing the 2017 Transformer research paper, which later became foundational for many large language models.
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He told Widom that internal caution slowed broader releases because of concerns that chatbots could “say dumb things.” While Google held back, competitors moved faster. Brin said OpenAI “ran with it,” a move that accelerated public adoption of generative AI tools.
Even so, he said Google benefited from long-term investment in neural-network research, custom-built chips, and large-scale data centers. Brin said very few companies operate across the full AI stack at that scale, including in-house research, proprietary semiconductors, and global computing infrastructure.
Asked how students should prepare for careers shaped by AI, Brin cautioned against abandoning technical fields. He said choosing a different discipline simply because AI can write code misses how broadly those systems already operate.
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“I wouldn’t go off and switch to comparative literature because you think the AI is good at coding,” he said. Brin said AI already performs well across many nontechnical tasks and that coding remains valuable and widely used inside AI development.
