SynthID Bio proof of concept explores watermarking for AI-generated proteins

Google DeepMind’s SynthID watermarking system, originally built to tag AI-generated text, images, audio, and video, has found a surprising new frontier: biology. Researchers at the University of Maryland have adapted the technology to embed invisible watermarks directly into AI-designed protein sequences, creating a potential tracking mechanism for synthetic biology that doesn’t compromise the proteins themselves. How you watermark a protein The technique builds on SynthID-Text, which works by subtly adjusting the probability distribution of tokens (in this case, amino acids rather than words) during the generation process. The researchers used what’s called an unbiased Gumbel sampling approach, embedding a watermark derived from a private key into the amino acid probability distribution of protein design models like ProteinMPNN. ProteinMPNN, which arrived in 2022, is one of the more prominent AI models for designing novel protein sequences. It takes a desired three-dimensional protein structure and works backward to generate amino acid sequences that should fold into that shape. The watermarking layer sits on top of this process, nudging which specific amino acids get selected wit...