AWS: Powering America’s Genesis Mission from day one

This week, the Department of Energy recognized Amazon Web Services (AWS) as a supporter of the Genesis Mission, highlighting our work with Idaho National Laboratory (INL) on civil nuclear innovation. AWS had the privilege of joining US Secretary of Energy Chris Wright and national laboratory directors at a roundtable discussion at the White House’s Eisenhower Executive Office Building to discuss this transformational initiative. It’s a recognition of a collaboration already underway—and a validation of the infrastructure and approach America needs to win the race for AI-powered scientific leadership.

President Donald Trump launched the Genesis Mission on November 24, 2025, with an audacious goal: harness AI-accelerated innovation to double the productivity and impact of American research within a decade. The Department of Energy will mobilize its 17 National Laboratories (including roughly 40,000 scientists and engineers), and the nation’s most advanced supercomputers to build what aims to become the world’s most powerful scientific platform.

But ambitious visions require infrastructure that exists today, not promises of future capabilities. The race for global AI leadership isn’t about what might be possible tomorrow—it’s about ready-today capabilities that remove the technology barriers limiting innovation. At AWS, we aren’t just preparing to support the Genesis Mission. We’re already powering it.

The infrastructure challenge facing American science

The Genesis Mission represents a fundamental shift in how science is done. The American Science and Security Platform will integrate the nation’s most powerful supercomputers, artificial intelligence (AI) systems, experimental facilities, and unique datasets to accelerate discovery from years to months. It will tackle three critical national challenges: American energy leadership through nuclear and fusion innovation, accelerating scientific discovery through quantum ecosystem development, and ensuring national security through advanced AI for defense and nuclear stockpile readiness and stewardship.

Yet the barriers to achieving this vision are substantial. Scientists spend excessive time managing infrastructure instead of conducting research, compromising critical national priorities. Ramping up new infrastructure at the speed and scale that Genesis demands presents significant timeline challenges that could delay America’s competitive advantage. Limited access to high-performance computing (HPC) resources can hamper progress on breakthrough discoveries that strengthen national security. And accelerating AI adoption across government requires clear governance standards and security frameworks that build organizational trust and enable mission-critical deployments.

These aren’t abstract challenges. They’re the daily reality facing our national laboratories and federal agencies. Over my years working with these organizations, I’ve learned that they don’t need more vendors promising future solutions. They need a complete, scalable, and resilient technical architecture that exists today and lets them focus on breakthrough science rather than managing technology.

Already accelerating discovery

In July 2025, AWS announced a collaboration with Idaho National Laboratory that exemplifies how cloud infrastructure is transforming federal science today. INL leads the nation in adapting AI for the nuclear energy industry, and together we’re developing AI tools to reduce the costs and timeframes of designing, building, and operating nuclear facilities. The collaboration focuses on utilizing agentic AI to accelerate the design, development, and deployment of nuclear energy, enabling what INL calls “nuclear energy AI at scale.”

During the secretary’s recent visit to the lab, he had a chance to see some of these efforts in the initial prototype of an AI-Powered Nuclear Reactor Design & Analysis Platform. This cloud-native tool integrates specialized AI agents to provide engineers and researchers with an intelligent assistant for complex nuclear engineering tasks, generation of digital twins, and advanced simulation capabilities.

Dr. John Wagner, Director of Idaho National Laboratory, shared: “This collaboration with AWS is already changing how we approach nuclear innovation. With cloud-based AI at scale, we’ve already demonstrated capabilities that will lead to compressing design cycles that traditionally took years into months. This isn’t theoretical—we’re using these agentic AI capabilities today to accelerate the design and development process and advance autonomous reactor operations that will define America’s energy future.”

This is exactly what we envisioned 14 years ago when we began our government cloud journey: removing technology barriers so scientists can focus on what they do best.

Building a unified foundation to power breakthroughs

Our government infrastructure foundation spans 14 years of industry firsts. AWS launched the first government-specific cloud in 2011, built the first air-gapped commercial cloud for classified workloads in 2014, and became the first cloud provider accredited across all classifications in 2017. Each milestone represented something many people thought impossible—until it wasn’t.

Last month, we announced our next defining moment: an investment of up to $50 billion in AI and supercomputing infrastructure purpose-built for US government agencies. This represents the largest federal technology investment in Amazon’s history and a fundamental shift from traditional high-performance computing workflows to AI-accelerated discovery and engineering. The investment will add nearly 1.3 gigawatts of capacity across our Top Secret, Secret, and GovCloud Regions. To put that in perspective, that’s enough capacity to run thousands of AI models and simulations simultaneously while processing decades of scientific data in real time. This infrastructure will provide on-demand access to computing power that enables government customers to run sophisticated AI workloads and process massive datasets for critical applications—from autonomous systems development and energy innovation to genomic data processing.

But scale alone won’t solve the Genesis Mission’s challenges. Federal agencies need comprehensive capabilities across computing, AI, data, security, and integration. They need managed services that eliminate infrastructure overhead. They need purpose-built secure environments already approved and compliant across all classification levels. They need the flexibility to run AI systems in their own data centers while maintaining cloud connectivity through hybrid deployment. AWS AI Factories deliver exactly this—bringing two decades of AWS cloud expertise directly into government facilities, enabling agencies to run AWS AI systems on-premises while maintaining seamless cloud integration.

And they need model diversity. At AWS, we’ve never believed there would be one model to rule them all. The Genesis Mission spans six priority domains—advanced manufacturing, biotechnology, critical materials, nuclear fission and fusion energy, quantum information science, and semiconductors. Each requires different AI capabilities, different approaches to processing proprietary scientific data, different ways of integrating simulation with real-time decision-making. AWS provides this breadth: foundation models with multimodal capabilities, tools for building custom domain-specific models that deeply understand proprietary scientific data, autonomous capabilities for continuous security reviews and infrastructure monitoring, and the ability to pivot missions between AI and high-performance computing—using HPC to build models, then applying AI inference for real-time decision-making.

Through Amazon Bedrock, agencies can access foundation models like Amazon Nova—our latest family of state-of-the-art, cost-effective models offering multimodal understanding, custom model development, and agentic capabilities—alongside models from leading AI companies like Anthropic. This gives researchers the flexibility to choose the right model for each scientific challenge, from analyzing complex genomic data to generating synthetic training datasets for autonomous systems.

Just as critical is compute diversity. Different scientific challenges demand different infrastructure—from specialized AI chips like AWS Trainium that are optimized for training and inference as well as NVIDIA AI infrastructure, to quantum computing capabilities through services like Amazon Braket that enable agencies to explore multiple quantum hardware approaches. This flexibility ensures researchers can match their compute infrastructure to their specific mission needs, whether they’re running genomic simulations, materials science modeling, or quantum algorithm development.

We believe these capabilities will ensure American researchers always have access to the world’s most advanced capabilities as mission needs evolve.

The convergence that makes Genesis possible

The Genesis Mission embodies something profound: the convergence of AI and high-performance computing into a fundamentally new model for scientific discovery. Traditional HPC and modern AI have evolved separately. Genesis requires their integration—AI agents testing hypotheses and automating experiments, processing decades of data in real time, simulation and modeling integrated with AI to deliver results in hours instead of weeks or months.

And the transformation goes far beyond speed. AI-accelerated discovery has the potential to unlock breakthroughs that would be impossible through traditional methods alone—identifying patterns in genomic data that lead to cures for debilitating diseases, designing autonomous systems that enhance national security, generating predictive intelligence that anticipates threats before they materialize. This is about discovering what we don’t yet know to ask.

Amazon’s recent $50 billion investment announcement is designed to deliver this AI-HPC convergence at scale. It enables orchestrating expert AI models, agents, and natural language interfaces so scientists can specify challenges and receive AI-driven recommendations backed by high-fidelity simulations. This represents a seismic shift in scientific research.

I envision a future where scientists work alongside autonomous AI agents that explore design spaces, evaluate outcomes, and accelerate discovery loops—not just compressing months into minutes, but uncovering insights that would remain hidden in traditional workflows. Where researchers can test hypotheses at scales previously impossible, revealing patterns and solutions that human intuition alone might never identify. This creates a sustainable competitive advantage that compounds over decades. The Genesis Mission Executive Order envisions a future where AI agents can explore design spaces, evaluate experimental outcomes, and automate workflows. It calls for autonomous and AI-augmented experimentation across the Department of Energy’s national laboratories. What we’re building provides exactly these capabilities to meet the mission’s aggressive 270-day timeline and demonstrates current operating capability.

Accelerating American scientific leadership for decades to come

When I think about the Genesis Mission, I don’t just see the next decade. I see the foundation we’ve built for generations of American scientific leadership. The mission will tackle more than 20 science and technology challenges spanning advanced manufacturing, biotechnology, critical materials, nuclear energy, quantum information science, and semiconductors. AWS provides not just infrastructure, but integrated capabilities across computing, AI, data, and security. And our approach doesn’t lock agencies into today’s architectures—it evolves with mission needs, ensuring America can continuously innovate across domains we haven’t yet imagined.

Our 14-year track record removes security and compliance barriers, allowing agencies to focus on breakthrough science. Our investment in purpose-built government cloud and AI infrastructure removes the technology barriers that have delayed innovation. And our commitment to model diversity and customization ensures that as new scientific frontiers emerge, American researchers will have the tools to lead.

We’re building the foundation for multi-generational scientific leadership—where today’s AI-HPC convergence evolves into tomorrow’s quantum-integrated discovery platforms. Where the infrastructure we’re deploying today enables breakthrough discoveries now while supporting scientific challenges we haven’t yet conceived.

The Genesis Mission represents America’s commitment to scientific excellence and technological leadership. At AWS, we’re proud to power this transformation from day one—not with promises of what might be possible, but with infrastructure that turns ambitious vision into operational reality today. The future of American science isn’t just bright. It’s already here, and we’re honored to help build it.