Blitz India Business
NEW DELHI: We are at a pivotal moment in human history, believes Google’s AI boss Demis Hassabis, the CEO of DeepMind. In a personal blog, he has once again reiterated that AGI or Artificial General Intelligence (a type of AI that matches or surpasses human capabilities across virtually all cognitive tasks) is only “a few short years away,” and urgent action is needed to make sure that it’s in favour of humanity.
Hassabis, a Nobel winner and one of the foremost names in AI today defined AGI as “a system that exhibits all the cognitive capabilities the brain has,” in his blog. In June, Hassabis had predicted AGI was just 3-4 years away.
He has now called for a global watchdog led by the US to be constituted urgently, adding that the risks related to AI are not being addressed at present. Instead the focus is skewed towards the global AI arms race both between corporations and nations, he pointed out.
“Urgent action is needed to address risks that might arise as we get closer to AGI. We’ve already seen the challenges frontier models pose for cyber security, and other threats including nuclear and bio risks may soon emerge as capabilities continue to advance.”
How AI will evolve is something of an unknown both in the scary and exciting territory – this is something most experts including the pioneers of AI largely agree upon.
“On the horizon, we will need robust safeguards to maintain control of increasingly agentic, recursively self-improving systems – and tackle unknown issues that will only become clearer over time.”
The fact that AI is starting to improve itself and could create more capable successors without human intervention has already been pointed out in Anthropic’s research. Anthropic, the Dario Amodei-led AI major behind Claude, constantly warns of the risks of AI, while admitting they themselves don’t fully understand how AI models work internally. Amodei too has been pushing for stricter guardrails and regulation around the development of AI.
“I’m confident that mitigating the technical risks related to AI is a challenge we can collectively address, but only if we give ourselves the time and space to get this next crucial step right. Currently, as a field and as a wider society, we aren’t doing that,” Hassabis said.
Hassabis has proposed an AI regulatory body modelled on the Financial Industry Regulatory Authority (FINRA), the private watchdog that regulates Wall Street brokerage houses under federal oversight. He said it would be staffed by leading technical experts, funded primarily by the AI industry, and tasked with developing safety benchmarks that frontier models must clear before entering the market.
The watchdog
Hassabis has proposed an AI regulatory body modelled on the Financial Industry Regulatory Authority (FINRA), the private watchdog that regulates Wall Street brokerage houses under federal oversight.
He said it would be staffed by leading technical experts, funded primarily by the AI industry, and tasked with developing safety benchmarks that frontier models must clear before entering the market.
Under his plan, AI developers would initially submit their most powerful models for review on a voluntary basis up to 30 days before release. Once the testing regime proves reliable, compliance would become mandatory.
“Nobody in the world knows for sure what is going to happen from here, and even the experts disagree,” Hassabis said.
“When there is a large degree of uncertainty and the stakes are this high, proceeding with cautious optimism is the sensible and correct strategy.”
Hassabis believes the US is well positioned to kick this off, given its economic and technical standing, to take the first step in developing such a framework.
This US-initiated effort would provide a strong starting point for creating shared international standards on Frontier AI, he said. Frontier AI refers to the most advanced, general-purpose artificial intelligence models available at any given time.
“Since this technology is going to affect the entire planet, ideally this framework would spur the international community to reach a consensus on how to manage the most serious risks while ensuring everyone has access to and can benefit from the opportunities that AI brings,” Hassabis said.
There is both huge excitement and uncertainty around AI, he said, admitting that both are warranted. “But the future is not yet written, we must use this precious window before AGI arrives to shape this technology for the benefit of all humanity.”
What humans collectively do now will determine how the next phase of civilisation unfolds, according to Hassabis. “By safely stewarding AGI into the world, we can enter a new golden age of scientific discovery and progress, and usher in a bright future of incredible human flourishing.”
Biggest moment for humanity yet?
“Nothing less than the dawning of a new age for humanity,” is how Hassabis describes the juncture humanity finds itself in at the moment.
Having spent his “whole life” working on AGI, the Google AI boss has a deep conviction that, if built and deployed responsibly, it would prove to be “one of the most beneficial and transformative technologies ever invented.”
AGI cannot be compared to standard technological breakthroughs, not even ones as consequential as the internet or mobile, Hassabis said.
“It is much more akin to the discovery of electricity or fire. If you stop to think about it, we’ve essentially found a way to make sand think. It’s miraculous.” The sand here refers to computer chips (semiconductors) which are made primarily of silicon, derived from sand (silica).
“The magnitude of this technology’s impact will be unprecedented, perhaps 10x of the Industrial Revolution at 10x the speed.”
AGI will help us solve some of the biggest problems society faces from accelerating drug discovery to developing new clean energy sources to creating novel advanced materials, he said. “We could even reach a point where resources are no longer the limiting factor for human progress, leading to an amazing new era of abundance.” SpaceXAI founder Elon Musk has echoed similar sentiments in the past.
What is AGI?
Unlike Narrow AI (which is designed for specific tasks like playing chess, generating text, or recognizing faces), a true AGI would possess human-level intellect. It would be able to learn, reason, adapt, and apply knowledge across any intellectually demanding domain without needing explicit retraining.
However, the AI landscape features several remarkable “Proto-AGI” systems (current technologies approaching general capabilities), benchmark tests used to measure AGI, and famous fictional examples.
Real-world “Proto-AGI” and frontier systems
While not full AGI, these modern systems exhibit multi-domain problem-solving, multimodal understanding, and autonomous reasoning.
• Advanced Multimodal Foundation Models: Systems like OpenAI’s GPT-5/o1 series, Google’s Gemini 3 Pro, and Anthropic’s Claude 4.x. They don’t just process text; they natively reason through code, complex mathematics, logic puzzles, high-level science, visual media, and audio.
• Autonomous Agentic Workflows: Frameworks built on frontier models (such as Claude Code or advanced multi-agent loops) that can independently plan a long-term goal, write software, test it, hit a bug, pivot their strategy, and deliver a final product without human intervention.
• Embodied AI & Advanced Robotics: Physical systems like Figure AI (Figure 01/02) or Tesla Optimus paired with vision-language models. These robots can look at a dynamic environment, understand verbal instructions (e.g., “make me a coffee” or “tidy up this mess”), and translate visual data into physical motor actions autonomously.
• Cognitive Architectures: Research-focused frameworks explicitly built to map the human mind, such as SOAR, ACT-R, and OpenCog Hyperon, which combine neural networks with symbolic logic to handle memory and reasoning.
Theoretical AGI benchmarks (tests)
Because AGI is hard to define, researchers look at practical hurdles an AI must pass to be considered a true general intelligence:
• The Wozniak “Coffee Test”: Proposed by Apple co-founder Steve Wozniak. An AGI robot must be able to walk into an average, unfamiliar American home, locate the kitchen, find the coffee machine, figure out where the ingredients are, brew a cup, and pour it into a mug entirely on its own.
• The IKEA / Flat-Pack Test: The AI must look at the scattered pieces of a flat-pack piece of furniture, read the visual instructions, and physically assemble it correctly.
• The Employment Test (Suleyman’s Test): An AI is given $100,000 in seed capital and must autonomously research market opportunities, create a product or service, sell it, and turn that investment into $1 million.
Fictional examples of AGI
To understand what a completed AGI (or Superintelligence) looks like conceptually, pop culture provides the best blueprints:
• J.A.R.V.I.S. / F.R.I.D.A.Y. (Iron Man): A highly sophisticated AGI that manages complex engineering tasks, analyzes physical data in real time, holds witty conversations, and seamlessly manages logistics.
• Samantha (Her): An operating system capable of deep emotional intelligence, rapid learning, psychological adaptability, and subjective consciousness.
• HAL 9000 (2001: A Space Odyssey): An AGI that controls a spaceship. It displays a flawless capacity for logic, speech synthesis, facial recognition, and autonomous decision-making (though it highlights the catastrophic dangers of misaligned AI goals).
• Data (Star Trek): An android with an AGI “positronic brain” capable of learning any human discipline, from playing the violin to high-level astrophysics, while attempting to grasp the nuances of human emotion.