COMPUTE
Computing resources for experimentation, development, simulation, AI workloads, and research systems.
Research infrastructure should not have to be rebuilt from zero every time someone wants to experiment.
LAAS explores a reusable infrastructure layer surrounding research: computing, networking, engineering tools, documentation, AI, security, safety, and collaboration.
A functioning laboratory depends on the infrastructure surrounding the research itself.
That includes computing, networks, engineering tools, documentation, security, AI systems, reference architectures, safety practices, technical standards, and the knowledge created through experimentation.
LAAS treats those components as infrastructure that can be designed, maintained, reused, and improved.
LAAS is not one laboratory design. It is an infrastructure model that can be adapted to different laboratories, projects, organizations, and communities.
R&DComputing resources for experimentation, development, simulation, AI workloads, and research systems.
Network infrastructure connecting machines, devices, laboratories, services, and people.
Reusable engineering environments for software, hardware, embedded systems, robotics, and experimentation.
AI infrastructure designed to support people, projects, research, interfaces, and connected systems.
Documentation is part of the infrastructure. Systems should be understandable enough to operate, modify, and improve.
Security, privacy, safety, consent, and human oversight are treated as components of the system itself.
The laboratory becomes a system.
Physical infrastructure, digital infrastructure, intelligent systems, documentation, and people can operate as connected layers rather than isolated components.
The exact implementation can change. The architecture provides the shared foundation.
Identify the research problem, people, requirements, and constraints.
Design the infrastructure, interfaces, architecture, and operating model.
Construct the physical and digital systems required for the work.
Record how the system works so other people can understand it.
Run the infrastructure and learn from real-world use.
Iterate on the infrastructure as new information becomes available.
Make reusable knowledge, tooling, and architecture available to others.
Research infrastructure should not have to be rebuilt from zero for every project.
A system that cannot be understood, operated, or modified by people is incomplete.
Automation and intelligent systems should expand human capability while preserving human oversight.
LAAS should provide building blocks that can be adapted to different laboratories, projects, and communities.
The long-term vision is a network of laboratories and builders contributing improvements back into a shared ecosystem.
LAAS is a long-term vision for reusable research infrastructure that can grow alongside the people building it.