Google commits USD $40 million to US Genesis Mission

Google has committed USD $40 million in AI tokens and cloud credits to support researchers working on the US Genesis Mission, expanding its support for a White House-backed effort to accelerate scientific discovery.

The funding will provide in-kind access to AI research tools for awardees under the Department of Energy's Genesis Mission and extend Gemini for Government access across the national laboratory system. The support covers one year of seats and tokens for tens of thousands of users across operations, research, and management teams at the Department of Energy National Labouratories.

The move deepens Google's existing relationship with the Department of Energy system. Google DeepMind had already opened an early access programme for AI-for-science tools to all 17 Department of Energy National Labouratories, and Google Public Sector had outlined a role for Gemini for Government in that work.

Under the latest commitment, researchers will receive access to several Google DeepMind tools, including AlphaEvolve for algorithm design and scientific discovery; AlphaFold 3 for predicting the structure and interactions of proteins and other biomolecules; AlphaGenome for studying how DNA variation affects biology and disease; WeatherNext for weather forecasting; and AlphaEarth Foundations for mapping and analysing the planet.

Gemini for Government will be available not only to researchers but also to administrative and operational staff across the laboratory network. Google described it as a secure platform for work ranging from research tasks to administering specialised user facilities used by the wider scientific community.

Lab use

The announcement also included examples of how the tools are already being used in laboratories.

At Pacific Northwest National Labouratory, Senior Scientist Dr. Henry Kvinge is using AlphaEvolve to study mathematical systems too large and complex to explore manually. The work focuses on combinatorics and related fields, where researchers search for patterns and connections across large structures.

"Modern math relies on abstraction, but combinatorics offers concrete models that make complex geometry and algebra easier to grasp. We've found that systems like AlphaEvolve are perfect for this search," said Dr. Henry Kvinge, Senior Scientist at Pacific Northwest National Labouratory.

"By leveraging the broad mathematical knowledge of LLMs, we can automate the exploration of countless angles. We're still experimenting, but the discoveries are already shaping our future research," Kvinge said.

Another example came from the National Labouratory of the Rockies, where Gemini is being used in autonomous materials discovery.

Dr. Steven R. Spurgeon, Senior Materials Data Scientist at the laboratory, said the project has changed how researchers interact with physical laboratory equipment.

"Our collaboration has allowed us to build an autonomous experimentation capability," said Dr. Steven R. Spurgeon, Senior Materials Data Scientist at the National Labouratory of the Rockies.

"By deploying Gemini in our instruments, we cut microscope calibration time from more than 90 minutes to about 13 minutes and reduced the manual steps needed to focus an image from as many as 50 to two. That's time and attention we've given back to the science itself, enabling genuinely autonomous workflows that observe, reason, and decide in real time. This has helped us explore parts of the material design space we simply could not have reached through manual operation alone," Spurgeon said.

Research pressure

The investment reflects a broader push to apply AI systems to scientific research areas where the scale of data and the complexity of experiments have outgrown conventional workflows. In fields such as fusion, materials science, biology, and climate research, scientists are increasingly dealing with large datasets, long simulation cycles, and laboratory processes that are difficult to optimise by hand.

For the Department of Energy laboratories, which span basic science, energy systems, national security, and large-scale experimental facilities, AI's appeal lies partly in speeding up routine tasks and partly in identifying patterns human researchers might miss. Google's examples highlight both: mathematical exploration at one laboratory and instrument control at another.

The scale of the latest commitment also suggests Google is seeking a larger role in US public-sector research infrastructure. By offering credits, software access, and user seats rather than direct cash grants, it is tying support to the use of its own cloud and AI products across a large federal research ecosystem.

The Genesis Mission is framed as a national effort to use AI to accelerate scientific discovery over the coming decade. Google said its latest contribution is intended to support that work across energy, security, and other scientific challenges.