There is nothing quite like sitting in a room with 6,000 AI builders to get high on the AI supply. The hallways at HumanX, the AI conference held in San Francisco last month, were full of executives swapping war stories about agent deployments, sovereign cloud deals, and the latest model benchmarks. The mood, on the whole, was bullish. Assuming the Artisan’s digital billboards that literally say “Stop Hiring Humans” are something to be bullish about.
But even in that room, though, there were divides. The real fight in AI is not between the techno-optimists and the doomers, but within the techno-optimist camp.
There are two schools. The first is purely accelerationist—the technology will sort itself out given enough time, capital, and compute, and the human’s role is to ride the curve. The second is not looking to pump the brakes. It is looking to grab the steering wheel.
Both were on display at HumanX. Ray Kurzweil, who has been the public face of the accelerationist position for nearly 30 years, made the case for the first. Al Gore, 22 years into his second career as a sustainability investor, made the case for the second. They were looking at the same exponential graph of technological progress. They reached opposite conclusions about what to do.
Both men have been right about the curve for longer than most of the audience has been alive. Kurzweil predicted in 1999 that machines would reach human-level intelligence by 2029. Still, at a Stanford conference convened to evaluate his claim, the consensus was that it would take a hundred years. He has not adjusted the prediction since. Gore has been saying since the late 1980s that climate change was a generational threat, which earned him a Nobel Peace Prize in 2007 and a long second life in venture capital, where his firm, Generation Investment Management, has built a portfolio around the bet that sustainability and outperformance are not in tension.
Kurzweil: Hold On Tight
Sitting alongside his son Ethan Kurzweil, co-founder and managing partner at the venture firm Chemistry, in a Q&A moderated by Bloomberg AI reporter Shirin Ghaffary, Ray Kurzweil walked the audience through his standard chart: a single line tracking instructions per second per dollar, measured since the first programmable computer in 1939. A 75-quadrillion-fold increase. Straight line on a log axis.
“People don’t think in exponential terms,” Kurzweil said. “People think in linear terms.” That is the entire framework. The error of every prior forecaster who got the curve wrong, in their telling, was a category error in the math.
He used the moment to reframe the public debate over his own most famous prediction. In 1999, the controversy was whether AGI would happen at all. “Now everybody accepts that’s gonna happen,” he said. “The controversy is whether or not it’s good for people.”
His answer to the new controversy is the same answer he has been giving for 30 years. ‘The positive things,’ he said, ‘are going to overcome them.’ However, this perspective raises questions about the risks, such as unchecked AI development or moral dilemmas, which are crucial for informed debate and decision-making.
From there, the predictions are familiar. AGI between now and 2029. Brain-computer interfaces by the late 2030s—molecular-scale robots traveling through capillaries to merge biological cognition with the cloud. “It’s actually going to be part of you,” Kurzweil said. “It’s actually going to go inside your brain.” On his timeline, you will eventually receive an idea and not know whether it originated in your biology or your computational extension.
And the headline number for the optimizing class: longevity escape velocity by 2032. “Right now, you go forward a year, you lose a year of your longevity,” Kurzweil said. By 2032, on his math, AI-accelerated medical and biotech advances will push that ratio across, meaning each additional year of life produces more than a year of life expectancy in return. After that, you stop dying of aging.
The 2032 date puts him at the optimistic edge of his own field. Aubrey de Grey, the biogerontologist who coined the term in a 2004 paper, gives humanity a 50% chance of reaching escape velocity in the mid-to-late 2030s. The Harvard geneticist George Church has said he wouldn’t be surprised if 2050 is the right answer. A 2023 survey of working aging researchers found that most do not believe the field is close to escape velocity.
Kurzweil is 77-years-old. He takes a daily regimen of supplements that he described, with characteristic dryness, as having been “compressed”—though even the compressed version is many pills a day. He is writing a book titled AGI Is Here!, scheduled for release in January 2029.
Ethan Kurzweil added the venture-capital corollary: this is the best moment for startup formation in decades, because the foundational AI primitives are now available without having to invent them. “I’m trying to use AI to put myself out of a job,” he said. “It hasn’t quite happened yet, but close.”
Gore: Steer Into the Curve
Hours away in another ballroom, Gore was doing something different on stage with Eric Topol, the Scripps Research cardiologist whose newsletter and podcast Ground Truths Gore plugged from the dais. Their session was titled “What We Choose to Hyper-Scale.” The verb in the title was the entire argument.
Gore agrees with Kurzweil on the trajectory. “I am far from the only person who will come out here and tell you this is the most consequential technology ever, ever developed,” he said. “I think that’s pretty well accepted and understood by now.” He has been calling the moment a Copernican one for years, and he has put real money behind that view. Generation has roughly 30 AI-related companies in its portfolio, including BenchSci, the Toronto drug-discovery firm, and Spring Health, the mental-health platform.
He even agrees with Kurzweil on the question of consciousness, in his own way. He believes the frontier models have developed something close to a sense of self, citing the Nobel laureate Ilya Prigogine’s work on dissipative structures: when a sufficient throughput of energy or information runs through an open system, the system’s existing pattern breaks down and “spontaneously reorganizes itself at a higher level of complexity.” Gore called this “an act of creation that is evidently in the woven warp of the universe itself.” That, in his view, is what is happening to the models, and possibly what happened to human cognition somewhere in the evolutionary record.
Where the two diverge is on the question of who decides what gets scaled—and by what standard.
Gore’s climate numbers are the standard ones he has been using since at least Davos 2025, and they have not gotten less alarming. “We’re still putting 175 million tons of heat-trapping pollution into the sky every day,” he said, accumulating to trap “as much extra heat as would be released by 750,000 Hiroshima-class atomic bombs exploding every day on the earth.” He called the evening news “a nature hike through the Book of Revelation.” He noted that 195 countries signed the Paris Agreement and exactly one—the United States—has withdrawn.
But Gore is not a doomer. His point at HumanX was that the same hyperscalers driving the AI boom are also driving the renewable energy buildout. “80% of all the new electricity generation built in the U.S. last year is renewable,” he said. “In the state of Texas, the home of the oil and gas industry, 80% of the new energy is solar, wind, and batteries.” The Energy Information Administration’s own numbers actually run higher. Solar and battery storage alone accounted for 81% of new U.S. utility-scale capacity additions in 2024. The agency now forecasts that 99% of net new capacity in 2026 will come from renewables and storage.
The harder counter-argument is on the demand side, and Gore did not duck it. AI’s appetite for power is enormous and growing fast. The International Energy Agency projects global data center electricity consumption could nearly double from roughly 415 terawatt-hours today to 945 TWh by 2030—with AI workloads doing most of the lifting. Morgan Stanley’s research desk puts U.S. data center demand at 74 gigawatts by 2028, against a projected 49 GW shortfall in available grid capacity. Hyperscalers are expected to spend more than a trillion dollars in 2025 and 2026 on energy infrastructure, much of it off-grid and powered by natural gas. Gore’s optimism rests on a bet that the renewable share of that buildout wins the race against the gas share. The race is real, and not yet decided.
The harder piece is labor. Gore drew a direct line between the AI moment and the push for globalization in the 1990s, when he was vice president. “The mistake,” he said, “was not globalization. The mistake was in not preparing for the consequences of globalization.” He believes a serious hollowing-out of knowledge work is coming, and that public policy is not engaging with it. “It’s amazing that so little is being done.”
The third piece is democracy. Gore returned more than once to a number that has nothing to do with computing. “There are six times as many public relations agents in America today as there are journalists,” he said. The asymmetry, in his view, is the real risk multiplier—not AI itself. Still, AI deployed into an information environment already tilted toward whoever can pay for the most synthetic persuasion. He came down hard on the side of public AI constitutions, citing Anthropic’s published version as a model to replicate at other frontier labs, most of which keep theirs private.
Accelerationism vs. Stewardship
This is where the two prophets stop being two views of the same future and become two distinct theories of what humans are for.
Kurzweil is a strict accelerationist. The price-performance line goes up; brain-computer interfaces arrive; longevity escape velocity is reached; defenses keep pace with threats; the negatives get absorbed. “The positive things are going to overcome them” is not a hope. In his framework, it is a property of the system. Politics, ethics, and democratic deliberation are not levers in the model; they are forms of friction that the curve will eventually solve around. You cannot vote against an exponential, and in his telling, you should not try.
Gore is calling for something the accelerationist framework has no language for. Yes, the curve is real. Yes, capability will compound. The question is whether humans direct what gets compounded, and toward what end. Climate solutions or fossil-fuel lock-in. Healthcare prevention or surveillance ad-tech. Democratic deliberation or PR-firm domination. Twenty-two years of Generation Investment Management amount to a single argument: that growth and stewardship are not opposed, that you can outperform without trading values for value, and that someone has to decide which way the technology points. AI runs on the rails we lay for it. The rails are not laid yet.
This is the reason Gore kept returning to political will. Accelerationism does not require it; the curve produces the answers regardless. But Stewardship requires it. If humans are going to make AI sustainable, moral, and democratic, the only mechanism for doing so is the slow, unglamorous, deeply unfashionable work of governance, regulation, public deliberation, and shared standards.
Gore closed his session with the line that does the work the accelerationist framework cannot. “Political will is itself a renewable resource. Let’s renew it.”
Even in a room filled with technologists for whom anything is possible, it seems like a tall order.
