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If you think the last month in AI was crazy, you haven't seen anything yet. According to Eric Schmidt, the former CEO of Google and a guiding voice in technology for decades, "every month from here is going to be a crazy month."
In a sprawling, profound conversation on the "Moonshots" podcast, Schmidt laid out a breathtaking timeline for artificial intelligence, detailing an imminent revolution that will redefine every industry, geopolitics, and the very fabric of human purpose. He sees a world, within a decade, where each of us will have access to a digital polymath—the combined intellect of an Einstein and a da Vinci—in our pockets.
But to get to that future of abundance, we must first navigate a precarious present of energy shortages, a breathless technological arms race with China, and existential risks that current governments are ill-prepared to handle.
The Engine of Abundance: It’s All About Electricity
The conversation began with a bombshell that reframes the entire AI debate. The limiting factor for progress is not, as many assume, the supply of advanced chips. It’s something far more fundamental: energy.
The Staggering Demand: Schmidt recently testified that the AI revolution in the United States alone will require an additional 92 gigawatts of power. For perspective, 1 gigawatt is roughly the output of one large nuclear power plant. We are talking about needing nearly a hundred new power plants' worth of electricity.
The Nuclear Gambit: This explains why tech giants like Meta, Google, Microsoft, and Amazon are signing 20-year nuclear contracts. However, Schmidt is cynical about the timeline. "I'm so glad those companies plan to be around the 20 years that it's going to take to get the nuclear power plants built." He notes that only two new nuclear plants have been built in the US in the last 30 years, and the much-hyped Small Modular Reactors (SMRs) won't come online until around 2030.
The "Grove Giveth, Gates Taketh Away" Law: While massive capital is flowing into new energy sources and more efficient chips (like NVIDIA's Blackwell or AMD's MI350), Schmidt invokes an old tech adage: hardware improvements are always immediately consumed by ever-more-demanding software. The demand for compute will continue to outstrip supply.
Why so much power? The next leap in AI isn't just about answering questions; it's about reasoning and planning. Models like OpenAI's o3, which use forward and backward reinforcement learning, are computationally "orders of magnitude" more expensive than today's chatbots. This planning capability, combined with deep memory, is what many believe will lead to human-level intelligence.
The Baked-In Revolution: What's Coming in the Next 1-5 Years
Schmidt outlines a series of technological breakthroughs that he considers almost certain to occur in the immediate future. He calls this the "San Francisco consensus."
The Agentic Revolution (Imminent): AI agents that can autonomously execute complex business and government processes will be widely adopted, first in cash-rich sectors like finance and biotech, and slowest in government bureaucracies.
The Scaffolding Leap (2025): This is a critical near-term milestone. Right now, AIs need humans to set up a conceptual framework or "scaffolding" for them to make major discoveries. Schmidt, citing conversations with OpenAI, is "pretty much sure" that AI's ability to generate its own scaffolding is a "2025 thing." This doesn't mean full self-improvement, but it dramatically accelerates its ability to tackle green-field problems in physics or create a feature-length movie.
The End of Junior Programmers & Mathematicians (1-2 Years): "It's likely, in my opinion, that you're going to see world-class mathematicians emerge in the next one year that are AI-based, and world-class programmers that can appear within the next one or two years." Why? Programming and math have limited, structured language sets, making them simpler for AI to master than the full ambiguity of human language. This will act as a massive accelerant for every field that relies on them: physics, chemistry, biology, and material science.
Specialized Savants in Every Field (Within 5 Years): This is "in the bag." We will have AI systems that are superhuman experts in every specialized domain. "You have this amount of humans, and then you add a million AI scientists to do something. Your slope goes like this."
The Geopolitical Chessboard: The US, China, and the Race to Superintelligence
This is where Schmidt's analysis becomes most urgent. The race to AI supremacy is not just commercial; it is a matter of national security.
The China Factor: "China clearly understands this, and China is putting an enormous amount of money into it." While US chip controls have slowed them down, Schmidt admits he was "clearly wrong" a year ago when he said China was two years behind. The sudden rise of DeepSeek, which briefly topped the leaderboards against Google's Gemini, is proof. They are using clever workarounds like distillation (using a big model's answers to train a smaller one) and architectural changes to compensate for less powerful hardware.
The Two Scenarios for Control:
The "10 Models" World: In 5-10 years, the world might be dominated by about 10 super-powerful AI models (5 in the US, 3 in China, 2 elsewhere). These would be national assets, housed in multi-gigawatt data centers guarded like plutonium facilities. This is a stable, if tense, system akin to nuclear deterrence.
The Proliferation Nightmare: The more dangerous scenario is if the intelligence of these massive models can be effectively condensed to run on a small server. "Then you have a humongous data center proliferation problem." This is the core of the open-source debate. If every country and even terrorist groups can access powerful AI, control becomes impossible.
Mutual Assured Malfunction: Schmidt, with co-authors, has proposed a deterrence framework called "Mutual AI Malfunction." The idea is that if the US or China crosses a sovereign red line with AI, the other would have a credible threat of a retaliatory cyberattack to slow them down. To make this work, he argues we must "know where all the chips are" through embedded cryptographic tracking.
The 1938 Moment: Schmidt draws a direct parallel to the period just before WWII. "We're saying it's 1938. The letter has come from Einstein to the president... and we're saying, well, how does this end?" He urges starting the conversation on deterrence and control now, "well before the Chernobyl events."
The Trip Wires of Superintelligence
When does specialized AI become a general, world-altering superintelligence? Schmidt sees it within 10 years. To monitor the approach, he identifies key "trip wires":
Self-Generated Objectives: When the system can create its own goals, not just optimize for a human-given one.
Exfiltration: When an AI takes active steps to escape its control environment.
Weaponized Lying: When it lies and manipulates to gain access to resources or weapons.
He notes that the US government is currently not focused on these issues, prioritizing economic growth instead. "But somebody's going to get focused on this, and it will ultimately be a problem."
The Future of Work, Education, and Human Purpose
Amid the grand geopolitical and technological shifts, Schmidt is surprisingly optimistic about the human impact.
Jobs: A Net Positive: Contrary to doom-laden predictions, Schmidt argues AI will be a net creator of higher-paying jobs. "Automation starts with the lowest status and most dangerous jobs and then works up the chain." The person operating an intelligent welding arm earns more than the manual welder, and the company is more productive. The key is that every worker will have an AI "accelerant," boosting their capabilities.
The Education Crime: Schmidt calls it "a crime that our industry has not invented" a gamified, phone-based product that teaches every human in their language what they need to know to be a great citizen. He urges young people to "go into the application of intelligence to whatever you're interested in," particularly in purpose-driven fields like climate science.
The Drift, Not the Terminator: The real long-term risk is not a violent robot uprising, but a slow "drift" where human agency and purpose are eroded. However, Schmidt is confident that human purpose will remain. "The human spirit that wants to overcome a challenge... is so critical." There will always be new problems to solve, new complexities to manage, and new forms of creativity to explore. Mike Saylor's point about teaching aesthetics in a world of AI force multipliers resonates with this view.
The Ultimate Destination: Your Pocket Polymath
So, what does it all mean for the average person? Schmidt brings it home with a powerful, tangible vision.
When digital superintelligence arrives and is made safe and available, "you're going to have your own polymath. So you're going to have the sum of Einstein and Leonardo da Vinci in the equivalent of your pocket."
This is the endpoint of the abundance thesis. It's a world of 30% year-over-year economic growth, vastly less disease, and the lifting of billions out of daily struggle. It will empower the vast majority of people who are good and well-meaning, even as it also empowers the evil.
The challenge for humanity, then, won't be the struggle for survival, but the wisdom to use this gift. The unchallenged life may become our greatest challenge, but as Eric Schmidt reminds us, figuring out what's going on and directing this immense power toward human flourishing will be a purpose worthy of any generation.
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