In March 2016, the world’s attention turned to a hotel ballroom in Seoul where one of the most anticipated contests in the history of artificial intelligence was unfolding. Inside the Four Seasons Hotel, South Korean Go champion Lee Se-dol faced an unconventional opponent: AlphaGo, an AI system created by the London-based research company DeepMind.

The match carried enormous symbolic weight. For centuries, people viewed the ancient strategy game of Go as a uniquely human intellectual challenge. Its complexity far exceeded that of chess, with a nearly unimaginable number of possible board configurations far more, some analysts note, than the number of atoms in the observable universe.


Over five games watched by more than 200 million viewers worldwide, AlphaGo defeated Lee Se-dol four times. After the third loss, Lee addressed the audience with a reflective remark: I, Lee Se-dol, lost, but mankind did not.

The real victor of that historic moment was DeepMind and its co-founder and CEO, Demis Hassabis.


Sebastian Mallaby’s book The Infinity Machine attempts to tell the story of Hassabis and the rise of one of the world’s most influential artificial intelligence laboratories.


From Chess Prodigy to AI Pioneer

Mallaby traces Hassabis’s path from childhood prodigy to one of the leading figures in modern AI research.


His family background alone reads like an unlikely origin story. Hassabis’s mother, originally from Singapore, experienced severe poverty in her early life and spent time as a homeless orphan. His father, a Greek Cypriot immigrant, pursued dreams of becoming a musician while supporting the family by selling toys from a battered red Volkswagen van.


Hassabis displayed extraordinary intellectual ability from a very young age. He began playing chess at four and quickly started defeating adult opponents. By five he was already competing in tournaments, sometimes needing to sit on stacked chairs with a phone book underneath so he could reach the table.


By the age of nine he was captaining England’s under-11 chess team, and at thirteen he had achieved the rank of chess master, placing him among the strongest players in his age group worldwide.


Competitive chess, however, was far from a gentle environment. Tournament organisers reportedly placed wooden boards beneath tables to prevent players from kicking one another during tense matches. The pressure from home could also be intense. According to the book, Hassabis’s father sometimes reacted angrily when his son lost games.


Hassabis himself interpreted the idea of “doing your best” in extreme terms, believing he had only succeeded if he pushed himself to the point of total exhaustion.


Early Career in Video Games and Academia

Before entering the field of artificial intelligence, Hassabis spent time in the video game industry.


He joined the British game developer Bullfrog Productions, working under renowned designer Peter Molyneux on the popular simulation title Theme Park. The experience helped shape his early thinking about how complex systems and simulations could be designed.


Hassabis later studied at the University of Cambridge before launching his own game studio. Eventually, he returned to academic research and completed a PhD in neuroscience, exploring the relationship between memory, learning, and the human brain.


In 2010, Hassabis partnered with Mustafa Suleyman and Shane Legg to establish DeepMind. Their vision was ambitious: to develop artificial intelligence capable of solving complex problems across multiple domains.



Investors, Ambition, and the Promise of Artificial General Intelligence

In its early years, DeepMind sought funding from Silicon Valley investors who were increasingly interested in the future of AI.


One of the company’s earliest supporters was Peter Thiel, co-founder of PayPal and an influential figure in technology and venture capital circles. Thiel helped connect the company to additional funding sources and investors.


At the heart of the company’s pitch was the pursuit of AGI, artificial general intelligence. Unlike narrow AI systems designed for specific tasks, AGI refers to machines capable of performing at or beyond human levels across a wide range of cognitive activities.


For some investors, the concept bordered on philosophical speculation. One supporter described the pursuit of AGI as an attempt to uncover God’s algorithm, suggesting a system capable of understanding the fundamental logic underlying intelligence itself.


Mallaby’s narrative presents this world of venture capital enthusiasm, technological ambition, and speculative thinking in vivid detail, though critics may feel the book occasionally accepts grand claims without sufficient scrutiny.



A Competitive AI Landscape

The rise of DeepMind did not occur in isolation. The global race to develop advanced AI technologies has involved several competing research organisations.

One of the most prominent rivals is OpenAI, led by CEO Sam Altman. In the book, Altman is portrayed as aggressively pushing the boundaries of public AI deployment.


The release of tools such as ChatGPT brought generative AI technologies to a global audience, capturing public attention and intensifying competition between research labs.

For many observers, this competitive dynamic has fuelled both innovation and hype within the AI sector.


Read More: Alphabet Strengthens AI Leadership with Record Q4 2025 Performance


Science Versus Silicon Valley Hype

Despite the venture capital spectacle surrounding artificial intelligence, some of DeepMind’s most meaningful achievements lie in scientific research rather than consumer products.


One notable milestone came when DeepMind researchers developed technology capable of predicting the three-dimensional structures of proteins, a breakthrough that significantly accelerated biological research.


The work earned Hassabis and colleague John Jumper a Nobel Prize in Chemistry, highlighting the potential of AI to transform fields such as medicine and biotechnology.

Such research demonstrates a more practical and socially valuable application of artificial intelligence, one focused less on futuristic speculation and more on solving real scientific problems.


A Complex Portrait of a Tech Visionary

In The Infinity Machine, Mallaby attempts to portray Hassabis not only as a technologist but also as a thinker interested in the deeper philosophical implications of artificial intelligence.


At times, however, the book blurs the line between technical expertise and broader intellectual authority. Hassabis occasionally describes himself as a practical philosopher, suggesting that building AI systems can help unlock deeper insights into the nature of intelligence and reality.


Whether readers find these reflections profound or overly ambitious may depend on their view of the broader AI movement.

What remains clear is that Hassabis has played a central role in shaping the modern AI landscape. From childhood chess champion to the architect of one of the world’s most influential research labs, his journey reflects both the promise and the controversy surrounding artificial intelligence today.


The Infinity Machine ultimately offers a window into the personalities, ambitions, and competing visions that are driving one of the most transformative technological races of the 21st century.