Nvidia and Eli Lilly have agreed to invest up to $1 billion over five years in a joint lab in Silicon Valley. The project aims to translate AI-generated ideas into lab-tested results more quickly.
Nvidia and Eli Lilly have agreed to invest up to $1 billion over five years in a joint lab in Silicon Valley. The project aims to translate AI-generated ideas into lab-tested results more quickly.
According to Bloomberg, at the new center, Nvidia engineers and Lilly scientists will work together to automate some of the routine research operations. The company emphasizes that the main bottleneck in modern laboratories is human time: even if algorithms suggest promising molecules or compounds, they need to be confirmed with a series of physical tests and equipment adjustments.
The initiative will train AI engineers to work with lab processes, and Lilly’s team will work with Nvidia to tailor computing systems and software to specific tasks. Nvidia also plans to expand its set of models and agents, or autonomous software assistants, for the healthcare sector and make them open so that third-party developers can adapt the tools to their needs. Separately, the company is working with Thermo Fisher to connect lab equipment to the DGX Spark computer and automate some of the operations.
The project builds on the companies' previous collaboration: in October, they announced a supercomputer for Lilly in Indianapolis, which is expected to be fully operational in the first quarter.
For Nvidia, medicine and pharma are emerging as a major new market for AI computing, as the pharmaceutical industry looks to shorten long research cycles. Despite aggressive investment, AI-powered drug discovery has yet to yield big breakthroughs, so companies are relying on combining models with real-world experiments and automation.
Previously, dev.ua wrote about how Universal Music Group (UMG) has reached an agreement with NVIDIA to use the Music Flamingo model in its ecosystem. The companies say that AI will simplify the search for music in one of the world’s largest catalogs not only by genres and playlists, but also by mood, compositional drama, and other musical characteristics.
