Google이 컴퓨팅 자원과 AI 연구 협력을 통해 DOE Genesis Mission에 4천만 달러의 지원을 약속했다.

July 22, 2026 — Scientists today face challenges of extraordinary scale and complexity, ranging from shaping and simulating the intricate dynamics of fusion plasma, to exploring the vast search space of new materials, to making sense of the exabytes of data pouring out of the world’s most advanced experimental facilities. The demands on modern research are unprecedented. Frontier artificial intelligence can help address these challenges while accelerating groundbreaking scientific discoveries.

In December, Google Cloud shared its commitment to the White House’s Genesis Mission, the national effort to harness AI and double the pace of American scientific discovery within a decade. Since then, Google DeepMind (GDM) announced an early-access program providing AI-for-science tools to all 17 Department of Energy (DOE) National Laboratories, and Google Public Sector outlined how Gemini for Government could serve as an AI backbone for the DOE.

Today, at the DOE Genesis Mission Summit 2026, Google is expanding its support by committing $40 million in AI tokens and cloud credits to researchers advancing the mission.

Frontier AI Tools for Scientific Discovery

Under this expanded commitment, Google will first provide DOE’s Genesis Mission awardees with in-kind access to GDM’s frontier AI-for-science portfolio, including:

AlphaEvolve: A Gemini-powered coding and discovery agent for designing advanced algorithms.

AlphaFold 3: A model for predicting the structure and interactions of proteins and other biomolecules.

AlphaGenome: A tool for understanding how variation in DNA, including the non-coding genome, shapes biology and disease.

WeatherNext: A state-of-the-art family of AI weather forecasting models for mapping weather conditions.

AlphaEarth Foundations: A foundational AI model for mapping and understanding the planet in unprecedented detail.

Second, Google will provide one-year seats and tokens for Gemini for Government to tens of thousands of users across the DOE National Laboratories’ operations, research, and management teams. This secure platform supports the full breadth of work from the research bench to the administration of specialized user facilities serving the entire scientific community, providing a single secure foundation that the DOE mission can depend on.

AI for Science Tools in Action Across the Laboratory Ecosystem

While significant work remains, the practical impact of the Genesis Mission is already taking shape across the laboratory ecosystem. At the Pacific Northwest National Laboratory (PNNL), senior scientist Dr. Henry Kvinge is using AlphaEvolve to map out massive mathematical systems that are far too complex for humans to explore by hand. The AI uncovers hidden connections automatically, fast-tracking discoveries that would normally take researchers years to find.

“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. Kvinge. “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.”

At the National Laboratory of the Rockies (NLR), researchers are utilizing Gemini to fundamentally change how they interact with physical laboratory hardware. Dr. Steven R. Spurgeon, a senior materials data scientist at NLR, leads a pioneering program in autonomous materials discovery.

“Our collaboration has allowed us to build an autonomous experimentation capability,” said Dr. Spurgeon. “By deploying Gemini in our instruments, we cut microscope calibration time from over 90 minutes to about 13 minutes (eight times faster) and reduced the manual steps needed to focus an image from as many as 50 down 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.”

Source: Pushmeet Kohli and Karthik Narain, Google Cloud