Profluent, a biotechnology company that is using AI to design proteins, says it has demonstrated “scaling laws” in the performance of AI models for biology that are similar to those AI researchers have previously claimed for AI models built to handle language. The finding means that building larger AI models for protein design, and feeding them more data, will produce predictably better results—including the ability to accomplish tasks that smaller models cannot. The discovery will give Profluent and its investors further confidence that the company can eventually realize its vision of building AI models that will allow scientists to specify in natural language exactly what properties they wish a protein to have, and then have the model output a DNA recipe for creating exactly that protein. “We are barreling forward toward that future,” Ali Madani, founder and CEO of the Berkeley, Calif.-based Profluent, told Fortune. Profluent has raised $44 million to date in two venture capital funding rounds. Its investors include Spark Capital, Insight Partners, and Air Street Capital. The company’s current valuation has not been disclosed. The news will likely cheer competitors too. Profluent is just one of a clutch of startups applying the same techniques behind large language models to proteins.

Full report : Biotech startup Profluent says it has discovered AI ‘scaling laws’ for AI models used in protein design.