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Google Research
Google Research covers the core engineering behind modern AI: inference efficiency, memory compression, prompt behavior, and benchmark reliability. Its work often shapes how models are deployed, measured, and optimized in production.
6 articles
Google DeepMind turns science into tools
Google DeepMind’s science tools show how Google is packaging AI for researchers who want precision, not hype.
TurboQuant makes long-context AI much cheaper
4 ways TurboQuant’s 100x KV cache cut could lower long-context AI costs, ease GPU needs, and change model serving.
TurboQuant cuts KV cache memory 6x in Google tests
Google Research says TurboQuant compresses KV caches by over 4x, with up to 6x less memory and no loss on long-context tests.
5 KV cache takeaways for llama.cpp users
5 takeaways from TurboQuant: under-3-bit KV cache compression, memory savings, and the tradeoffs llama.cpp users should watch.
TurboQuant cuts memory use 6x without accuracy loss
Google Research’s TurboQuant claims 6x less memory and 8x faster inference with no accuracy loss, jolting AI inference economics.
Duplicate Prompts Can Lift Accuracy Fast
A Google study found repeating prompts once improved 47 of 70 model-benchmark pairs, with one task jumping from 21% to 97%.