Google’s TurboQuant paper is facing misconduct allegations after claiming a 6x reduction in AI memory use, a development the source says coincided with more than $90 billion in losses in storage-chip company value. RaBitQ author Gao Jianyang said Google used unfair benchmarking methods, comparing RaBitQ running in Python on a single-core CPU against TurboQuant running on an Nvidia A100 GPU. According to the source, Gao filed the complaint on March 27 through ICLR OpenReview and ethics channels.