Recently, I listened to NVIDIA founder and CEO Jensen Huang’s keynote at the Consumer Electronics Show, where he introduced what he called the Vera Rubin Era. It was not a product announcement; it was a declaration that a civilizational threshold had been crossed.
Huang was not describing faster chips. He was describing the emergence of AI factories — industrial-scale systems that manufacture intelligence the way power plants generate electricity or refineries produce fuel. In that moment, it became clear: higher education is no longer approaching transformation. We are now operating inside an intelligence-infrastructure revolution.
The next 1,000 days will determine whether colleges and universities help shape this new era or are merely shaped by it.
Having led institutions through multiple waves of technological and social change, I have learned that the deepest transformations are never about tools alone. They are about values, governance and the courage to place human judgment above technical convenience.
A new stack: From code to civilization
Huang describes the AI ecosystem as a “five-layer cake.” In the Rubin Era, the order of that cake has changed:
1. Energy and power – Electricity, cooling, thermodynamics, grid capacity
2. Silicon and compute – GPUs, CPUs, accelerators, memory
3. Interconnect – Photonics, NVLink, InfiniBand, Ethernet
4. Systems and software – AI operating systems, orchestration, digital twins
5. Models and applications – Generative, agentic and physical AI
This reordered stack marks the transition from computing as a digital utility to intelligence as physical, energy-bound infrastructure.
For six decades, progress in computing was governed by Moore’s Law. In the Rubin Era, progress is governed by megawatts, heat and the laws of physics. Intelligence is no longer just software; it is infrastructure. The limiting factors are no longer code alone, but energy, materials, governance and human judgment.
Why this time is different: The shift to cognitive systems
Every five to 10 years, computing has undergone a major shift: mainframes, personal computers, the internet, cloud, mobile. Each wave transformed our tools.
This wave transforms civilization’s operating system because for the first time, intelligence itself, not just information processing, has become scalable, programmable and infrastructural.
We are moving:
• From tools to cognitive systems
• From software to manufactured intelligence
• From IT to societal infrastructure
For the first time, we are building machines that can reason, plan, learn and operate autonomously in the physical world. We are moving from a society that uses computers to one that increasingly inhabits an intelligent environment.
This is why the moment is not cyclical; it is foundational.
The central question: Human-guided intelligence
The danger of this era is not that machines will become intelligent. The danger is that institutions may abdicate human guidance.
The central leadership challenge of the Rubin Era is not technical capability. It is:
• Who sets purpose?
• Who defines values?
• Who retains moral agency?
This is why Human-Guided Intelligence (HGI) must be the governing principle, not “human-in-the-loop” as a technical safeguard, but human-in-command as a civilizational doctrine, a doctrine in which accountability, intent and moral responsibility can never be delegated to machines.
AI can optimize. Only humans can judge. AI can scale. Only humans can assign meaning.
The liberal arts: The flight control system of the intelligence age
In the industrial era, higher education’s crown jewel was engineering. In the digital era, it became computer science. In the Rubin Era, the crown jewel is once again the liberal arts.
When intelligence becomes infrastructure, the scarce resource is not computation it is wisdom. And wisdom is cultivated not by scale, but by interpretation, dialogue, history and ethical reasoning.
The liberal arts are not peripheral. They are the governance layer of the intelligence stack.
• Philosophy teaches how to reason about truth.
• History teaches how power evolves.
• Ethics teaches constraint in the face of capability.
• Literature and the social sciences cultivate empathy, judgment and democratic reasoning.
These are not “soft skills.” They are hard constraints on catastrophic misuse. In an era of agentic and physical AI, the liberal arts become the flight-control system of civilization.
The rise of the infrastructure class
Perhaps the most urgent and overlooked workforce shift of the Rubin Era is the emergence of what can be called the Infrastructure Class.
For decades, ed ucation has been organized around a false binary: Career technical education on one side, hands-on, physical, “blue collar.” Academic and STEM education on the other, theoretical, digital, “white collar.” The Rubin Era collapses this wall.
AI factories, smart grids, photonic networks, advanced cooling systems, robotics and autonomous infrastructure demand a new kind of learner, one who understands that a software failure may actually be a thermal failure, and that a policy decision about AI ethics is ultimately constrained by grid capacity.
The Infrastructure Class consists of those who will build, operate, secure and govern the cyber-physical systems that manufacture intelligence itself. They must think across electrons and algorithms, thermodynamics and data, ethics and engineering.
In the community college context, this is the New Blue Collar: a high-skill, high-wage fusion of trades and technology. These learners integrate hands and minds. They will wire the intelligence grid, cool the AI factories, secure cyber-physical systems and translate democratic values into operating constraints.
The 1,000-day mandate for higher education
The next 1,000 days demand that colleges move from being passive consumers of AI to active stewards of intelligence infrastructure. This requires:
- Sovereign governance: Developing institutional AI policies that protect academic freedom, equity and transparency rather than outsourcing ethical judgment to private platforms.
- Cyber-physical literacy: Moving beyond coding to systems thinking — understanding the interplay between energy, compute, networks, automation and human impact.
- Human systems leadership: Developing leaders who understand not only how AI works, but how it reshapes power, labor, trust and institutional legitimacy.
- Educating for agency: Preparing students not merely to use AI, but to govern a world shaped by it. If a student cannot direct an AI agent with purpose and responsibility, they lack the agency required for 21st-century citizenship.
From transformation to stewardship
The Rubin Era marks the moment when intelligence becomes as foundational as electricity. The question before us is not “How do we adopt AI?” but “How do we steward intelligence in an age where our humanity is being challenged?”
The next 1,000 days are not about catching up to technology. They are about ensuring that human values, democratic judgment, and moral responsibility scale faster than machine capability. That is the work of leadership. That is the work of the liberal arts. That is the work of human-guided intelligence.
