In the last three years of writing and researching generative AI, I have seen many respected people predict that AGI is close. Most of those predictions come with vague timelines, dramatic warnings, or promises that everything is about to change.
But this one feels different because it comes from Demis Hassabis, someone who has spent most of his life trying to build artificial general intelligence. He co-founded DeepMind, led the development of systems such as AlphaGo and AlphaFold, and now runs one of the few labs with the talent, compute, and resources needed to seriously push the frontier.
So when he says AGI is probably only a few years away, it is difficult to treat it as another prediction on social media.
In a new essay titled A Framework for Frontier AI and the Dawning of a New Age, Hassabis argues that humanity is standing in the “foothills of the singularity.” He believes future generations may look back on this period as the beginning of a completely new age.
He does not compare AGI to the internet, smartphones, or another major software platform. He compares it to electricity and fire.
I know. It sounds poetic, but it is also surprisingly close to what modern AI is. We take silicon, electricity, enormous amounts of data, and carefully designed software, then turn them into systems that can reason, write code, discover patterns, and increasingly act on their own.
Demis is surprisingly optimistic about what comes next
The way Demis describes it, he is very optimistic about the benefits of generative AI. He believes AGI could accelerate drug discovery, help develop new clean-energy systems, create advanced materials, and dramatically speed up scientific research.
He even suggests that its impact could be ten times larger than the Industrial Revolution and happen ten times faster. That is an almost impossible scale to imagine.
Excerpt from Demis Hassabis’s A Framework for Frontier AI and the Dawning of a New Age
The Industrial Revolution changed where people lived, how they worked, how goods were produced, and how wealth was created. If AGI produces a bigger transformation in a fraction of the time, nearly every institution we rely on may have to adapt while the technology is still moving.
Demis also talks about a future where resources may no longer be the main limit on human progress. In the most optimistic version, AI helps us reach a form of abundance where energy, medicine, materials, and knowledge become much cheaper to produce.
This is not a doom-focused essay. He clearly believes AGI could lead to a golden age of scientific progress and human flourishing, but his optimism comes with a warning.
The race to build these systems is moving much faster than our ability to understand or govern them.
The race is becoming the problem
Right now, frontier AI is shaped by two kinds of competition.
- The first is commercial. Google, OpenAI, Anthropic, Meta, xAI, and other labs are trying to release more capable models, win users, attract developers, and secure enterprise customers.
- The second is geopolitical. The United States and China both see advanced AI as a strategic technology that could shape national security, economic power, and military advantage.
Competition has clear benefits. It pushes models forward, lowers prices, improves tools, and forces companies to move quickly.
But it also creates a dangerous incentive. Even if one lab believes it should slow down, it has to assume that its competitors may continue.
We are expecting individual companies to act carefully inside a system that punishes anyone who falls behind.
Commercial and geopolitical AI race
Demis argues that this race is pushing capabilities forward faster than researchers can evaluate them. Cybersecurity risks are already visible, while biological, nuclear, and other dangerous capabilities may become more serious as the models improve.
Agentic systems introduce another layer of risk. Future models may be able to take long sequences of actions, use tools, write and run code, copy themselves across systems, or improve parts of their own workflows.
We are still struggling to evaluate today’s coding agents properly. It is not hard to see why testing a recursively improving system would be much more difficult.
His proposed solution is a Frontier AI Standards Body
Demis does not stop at warning that AGI is close. He proposes a specific institution for testing the most capable models before they are released.
His idea is a U.S.-led Frontier AI Standards Body. It would operate as a public-private organization with federal oversight, independent technical experts, open-source representatives, and funding largely provided by the AI industry.
The closest comparison he gives is FINRA, the organization that oversees parts of the U.S. financial industry.
The body would define what counts as a Frontier Model based on capability thresholds. Any organization building models above those thresholds would be classified as a Frontier Lab.
Those labs would be expected to follow stronger safety and security practices. This would include better cybersecurity, more detailed model cards, internal personnel vetting, and dedicated safety research.
The most consequential part is the proposed review process. Initially, labs would voluntarily provide models for evaluation up to 30 days before release.
Once the process proved reliable, passing the assessment could become a requirement for deploying frontier models in the U.S. market.
Frontier AI Standards body
The tests would focus on areas such as cybersecurity, biological threats, deception, guardrail bypassing, and other dangerous agentic behavior. The benchmarks would be updated regularly as older evaluations become saturated.
Demis also wants the standards body to develop its own private tests over time. This is important because public benchmarks eventually leak into training data, get optimized against, or stop measuring meaningful progress.
In the most serious cases, the organization could coordinate a slowdown between frontier labs. That is a much bigger proposal than asking companies to publish better safety reports. It creates a path toward an institution that could delay or block the release of the most capable AI systems.
This is where the idea becomes controversial
The proposal sounds reasonable when framed as independent testing for dangerous models. The harder questions begin when we ask who controls the process.
A standards body funded by frontier AI companies could easily become shaped by those same companies. Google, OpenAI, Anthropic, Meta, and other large labs already have the money, policy teams, and infrastructure needed to participate in a complex regulatory system, while smaller companies may not.
Demis says startups, academic groups, and non-frontier models would be exempt. That helps, but someone still has to decide where the frontier begins.
A threshold based on model size or compute could miss smaller systems with dangerous capabilities. A threshold based on benchmark scores could be gamed, leaked, or designed in ways that favor certain architectures and labs.
This is why some of the public reaction focused on regulatory capture. A system designed to control frontier labs could also protect them from new competitors.
I share part of that concern. I do not think the answer is to let companies regulate themselves, but I also do not think handing full control to governments automatically makes the system safer.
A credible standards body would need independent leadership, transparent rules, clear appeals, strict conflict-of-interest policies, and enough technical talent to challenge the labs it oversees. Without those protections, it could become either too weak to matter or powerful enough to be abused.
The international problem is even harder
The largest weakness in a U.S.-led framework is that AGI development is not limited to the United States.
American labs could agree to stronger testing while foreign companies, governments, or covert projects continue building systems outside the framework. Advanced models can also be accessed through APIs, copied through leaked weights, or deployed across borders.
This is the concern behind many of the negative reactions to Demis’s proposal. What happens if democratic countries slow down while authoritarian states or hostile groups keep moving?
