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In this episode, a fascinating discussion unfolds around the innovative breakthroughs in reinforcement learning, driven by necessity rather than abundance. The guests delve into how a group of thinkers, faced with constraints, crafted a new algorithm that not only conserves computer memory but also enhances performance. They highlight the audacious decision to bypass Nvidia's proprietary language, CUDA, opting instead for PTX, which connects directly to the hardware. This episode challenges the status quo of funding in the tech world, suggesting that perhaps less money could lead to more groundbreaking ideas. It’s a thought-provoking exploration of creativity under pressure and the lessons we can glean from those who innovate outside the box.
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