Six founding questions.
These are the founding open problems around which MNEOS is organizing its early research and recruiting. Each is deliberately larger than a single project. Each welcomes contributions from multiple disciplines, institutions, and forms of intelligence.
Can engineering intent be translated into governed, testable design workflows?
How does ambiguous human intent become an explicit set of objectives, constraints, permissions, evidence requirements, and executable actions — without losing meaning?
How can humanoid systems safely become useful scientific and manufacturing collaborators?
What forms of authority, accountability, sensing, and human-machine work allocation must exist for embodied AI to belong in laboratories and factories?
How can physical test evidence continuously update simulation and AI models?
What architectures allow experiments, telemetry, and field data to become part of the model rather than a separate artifact that gets stale?
How can engineering failures become reusable institutional knowledge?
What memory, provenance, and access architecture turns a failed attempt into something that saves the next team ten years of rework?
How can biological architectures inspire resilient sensing and autonomous systems?
What is the disciplined form of bio-inspiration — beyond metaphor — that translates evolutionary, developmental, and immune-system architecture into engineered capability?
How can portfolio-level technical learning compound without violating IP boundaries?
What governance and technical architecture allow knowledge to accrue across a portfolio while respecting ownership, permissions, security, and originator rights?
Contribute.
Non-confidential contributions to these open problems are welcome from individual scientists, engineers, students, faculty, laboratories, and organizations.