Code Over Silicon: How Google's 'TurboQuant' Crashed the AI Hardware Party

This episode explores how the immense memory demands of AI models created a global shortage, negatively impacting consumer devices like smartphones with downgraded specifications. It details Google's "mathematical breakthrough" that significantly reduces memory needed for AI's KV cache, a development initially misinterpreted by Wall Street as solving the problem. Listeners will learn how this innovation, paradoxically, is expected to intensify the demand for memory, revealing a counter-intuitive tech curveball.