A Stanford PhD and AI researcher discusses his career path through quantitative finance at Citadel and back to AI research at Cartesia. He covers whether a PhD is necessary for AI research and quant roles, the differences in work culture and compensation between finance and tech, how to develop research taste and find meaningful problems, and technical details about state space models versus transformers. He also explains Cartesia's work in voice AI, competing with 11 Labs, and the advantages of AI startups over big labs in exploring unconventional research directions.
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