London: Creating computer programs that mimic the human brain wasn’t always accepted, but Geoffrey Hinton’s persistence helped lay the foundation for today’s artificial intelligence.
Early fascination with the human mind
Born in Wimbledon in 1947, Hinton grew up in a family of scientists, inheriting a strong academic lineage. After studying physics, physiology, philosophy and psychology at King’s College, Cambridge, he earned a B.A. in experimental psychology in 1970. By 1978, he had completed a Ph.D. in artificial intelligence at the University of Edinburgh, focusing on artificial neural networks, which were then dismissed by many in the field.
Moving across continents for AI
With funding for AI drying up in the late 1970s, Hinton moved to the University of California, San Diego, before teaching at Carnegie Mellon in 1982 and later joining the University of Toronto in 1987. His belief in neural networks — systems designed to mimic the brain — was initially seen as unconventional, but his work laid the groundwork for “deep learning.”
Breakthrough with deep learning
By the 2000s, advances in computing power allowed Hinton’s theories to flourish. His team’s 2012 breakthrough proved deep learning far superior to traditional computer vision systems. Soon after, Google acquired his start-up, DNNresearch, for USD 44 million, and Hinton split his time between academia and Google Brain.
Collaborations and global recognition
At Toronto, Hinton worked with Yoshua Bengio and Yann LeCun, pioneering deep learning and transforming AI applications in speech, image recognition and more. In 2024, he shared the Nobel Prize for physics with John Hopfield for his contributions to the field.
Raising the alarm on AI risks
Despite his optimism about AI’s potential, Hinton resigned from Google in 2023 to warn about its dangers. He has since cautioned that artificial general intelligence (AGI) could surpass humans within 5 to 20 years, posing existential threats if left unchecked.
Towards safe AI
Hinton now advocates for building safeguards into AI, such as programming systems with “maternal instincts” to prioritise human wellbeing. While acknowledging risks like cyberattacks, unemployment and misuse, he also sees opportunities in healthcare, particularly in medical imaging and drug discovery.
Legacy
Known as the “Godfather of AI,” Hinton’s journey from scepticism to global recognition reflects the transformative impact of persistence and innovation. His lesson is clear: humanity must strike a balance between embracing AI’s benefits and preparing for its unprecedented risks.