What's really happening inside AI memory, and why it's the bottleneck threatening every LLM deployment at scale?
The common story is that we just need more chips, but the reality is more interesting: a new Google paper may have just changed the math without touching the hardware.
In this video, I share the inside scoop on TurboQuant, Google's lossless KV cache compression breakthrough:
• Why the AI memory crisis is structural, not temporary
• How TurboQuant achieves 6x compression with zero data loss
• What lossless KV cache optimization means for LLM architecture
• Where Google, NVIDIA, and enterprises each stand to win or lose
The operators and builders who start treating memory as a years-long constraint, and take control of their own context layers now, will hold a real structural advantage as this rolls toward production.
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