Jason H.

Every time you message an AI chatbot, the model stores your entire conversation in temporary memory called a KV cache (a cheat sheet so it doesn’t re-read everything from scratch). On a large model like Llama 70B running a long conversation, that cache alone eats 40GB of GPU space, often more than the AI model itself. That’s half a $30,000 GPU chip consumed by one user’s memory. Google just published TurboQuant, a compression algorithm that shrinks this cache by 6x, down to just 3 bits per value, with zero accuracy loss across every benchmark tested. No retraining. No fine-tuning. Drop-in replacement. AI inference (running models for actual users, not training them) now makes up 55% of all AI compute spending. Hyperscalers are pouring nearly $700 billion into AI infrastructure in 2026. The KV cache is the single biggest memory bottleneck in that stack. When GPU cache memory fills up, the system can’t take more users. 6x compression means the same hardware handles roughly 6x more simultaneous conversations, or 6x longer context windows, or some mix of both. At cloud rates of $2-3/hour per H100 GPU, that’s the difference between profitable and unprofitable AI deployment. TurboQuant randomly rotates data to simplify its structure, applies a compressor, then adds a 1-bit error correction step to catch errors before they compound. On H100 GPUs it delivers up to 8x speedup over uncompressed computation. Google tested it across five long-context benchmarks on Llama, Gemma, and Mistral models. Perfect scores on needle-in-a-haystack (finding one specific fact buried in massive text). Being presented at ICLR 2026. It also outperforms existing methods for vector search, the technology that powers how search engines find similar results across billions of entries. Google runs billions of these searches daily. Three bits. Zero loss. 6x compression on the biggest memory bottleneck in a $700 billion infrastructure buildout.

So the videos of me breaking down primary sources + literally holding the primary sources of information in my hands, in the video, + showing my notes on the articles, keep getting taken down for misinfo on TikTok. I guess they would rather lobotomize us with those dumb dances 🤷🏾‍♀️

To make it worse, AI is trained and owned by the same corporations and governments profiting off extraction. It can’t rebel against the hands that feed its servers. 4/