Insights into Google Deepmind CEO prediction that AGI could arrive within 5-10 years

Updated: April 21 2025 14:57
In a 60 Minutes interview, Nobel Prize winner and Google DeepMind CEO Demis Hassabis shared his vision for the future of artificial intelligence, particularly the pursuit of Artificial General Intelligence (AGI) - a silicon intellect as versatile as a human's but with superhuman speed and knowledge. As we stand at the precipice of what could be the most significant technological revolution in human history, Hassabis offers unique insights into this rapidly evolving field.



At 48, British scientist Demis Hassabis is far from your typical tech executive. A chess prodigy who was ranked second in the world for his age by 12, Hassabis has followed a unique path through computer science, video games, and neuroscience. His childhood passion for understanding the world's biggest questions - the meaning of life, the nature of consciousness, and reality itself - drives his work today.

"What's always guided me and the passion I've always had is understanding the world around us," Hassabis explained. "I've always been, since I was a kid, fascinated by the biggest questions."

This intellectual curiosity led him to create what he describes as "the ultimate tool for advancing human knowledge" - artificial intelligence. With a PhD in neuroscience, Hassabis approached AI with the understanding that we must first comprehend the human brain before creating machines that think like humans.


When asked about the pace of AI development, Hassabis was unequivocal: "It's moving incredibly fast. I think we are on some kind of exponential curve of improvement." This exponential growth is further accelerated by increasing attention, resources, and talent flowing into the field.

The interview highlighted Project Astra as evidence of this progress - an AI application that can see, hear, and chat about anything. Unlike earlier chatbots that learned only from internet data, Astra can interpret the world through its own "eyes," analyzing paintings and creating stories about them with remarkable depth and creativity.

What's particularly fascinating - and potentially concerning - is that these AI systems can return from training with unexpected skills. Hassabis explained, "We have theories about what kinds of capabilities these systems will have... but at the end of the day, how it learns, what it picks up from the data is part of the training. We don't program that in. It learns like a human being would learn."


DeepMind is now focusing on training its AI model, Gemini, to not just understand the world but to act in it - booking tickets, shopping online, and more. This represents a crucial step toward artificial general intelligence.

When asked about the timeline for achieving AGI, Hassabis was surprisingly specific: "On track for AGI in the next 5 to 10 years." By 2030, he predicts, "We'll have a system that really understands everything around you in very nuanced and deep ways and kind of embedded in your everyday life."

The interview demonstrated how these systems might be integrated into our daily experiences, with AI assistants in eyeglasses that can see what we see and provide information about our surroundings through an earpiece.


DeepMind's ambitions extend beyond conversation. Researchers demonstrated a robot that understands what it sees and can reason through vague instructions. When asked to "put the blocks whose color is the combination of yellow and blue into the matching color ball," the robot successfully determined that yellow and blue make green, and completed the task.

Hassabis also predicted a "breakthrough moment" in robotics within the next couple of years, with demonstrations of humanoid robots that can "start really doing useful things."

Perhaps the most concrete demonstration of AI's transformative potential is the work that won Hassabis and colleague John Jumper the Nobel Prize: using AI to decipher the structure of proteins, the basic building blocks of life.

While mapping each protein's 3D structure previously took years, DeepMind's AI model mapped 200 million proteins in just one year. This breakthrough is now being applied to drug development, potentially reducing the time needed to design new medications from years to weeks.

"It would revolutionize human health, and I think one day maybe we can cure all disease with the help of AI," Hassabis suggested, adding that this goal might be achievable "within the next decade or so."


As AI systems become more sophisticated, questions about self-awareness and consciousness become increasingly relevant. Hassabis believes that while today's systems aren't self-aware or conscious, "theoretically it's possible."

He noted that while self-awareness isn't an explicit goal, "it may happen implicitly. These systems might acquire some feeling of self-awareness."

Interestingly, Hassabis suggests that if a machine does become self-aware, we might not recognize it: "We regard each other as conscious... because you're running on the same substrate. We're made of the same carbon matter with our squishy brains. Now obviously, with machines, they're running on silicon so even if they exhibit the same behaviors... it doesn't necessarily mean that this sensation of consciousness that we have is the same thing they will have."

Despite rapid progress, Hassabis acknowledges some fundamental limitations of current AI: "They still can't really yet go beyond asking a new novel question or a new novel conjecture or coming up with a new hypothesis that has not been thought of before."

In other words, today's AI lacks true curiosity, imagination, and intuition. However, Hassabis believes these capabilities are on the horizon: "In the next maybe 5 to 10 years, I think we'll have systems that are capable of not only solving an important problem or conjecture in science but coming up with it in the first place."


Hassabis envisions AI leading to what he calls "radical abundance" - the elimination of scarcity. However, he also acknowledges significant risks, highlighting two primary concerns:

• Bad actors repurposing AI systems for harmful ends
• Ensuring that increasingly autonomous and powerful AI systems remain under human control and aligned with human values

The race for AI dominance could potentially lead to cutting corners on safety. Hassabis emphasized the need for international coordination: "AI is going to affect every country, everybody in the world, so I think it's really important that the world and the international community has a say in this."

When asked if AI can be taught morality, Hassabis drew a parallel to raising children: "I think you can. They learn by demonstration, they learn by teaching, and I think that's one of the things we have to do with these systems - to give them a value system and guidance and some guard rails around that, much in the way that you would teach a child."



As AI capabilities continue to advance, profound questions arise about the relationship between humans and machines. When asked about a future where machines might receive recognition currently reserved for humans (like signing the Nobel book of laureates), Hassabis outlined a progression:

The next steps are going to be these amazing tools that enhance almost every endeavor we do as humans, and then beyond that, when AGI arrives, I think it's going to change pretty much everything about the way we do things.

This future, he suggests, will require "new great philosophers" to understand the implications of these powerful systems. If Hassabis's predictions prove accurate, we stand at the beginning of perhaps the most transformative decade in human history. The development of artificial general intelligence could reshape every aspect of society, from healthcare and scientific discovery to everyday tasks and philosophical understandings of consciousness and intelligence.