QEPrize awarded to AI pioneers

The collective efforts of Yoshua Bengio, Geoffrey Hinton, John Hopfield, Yann LeCun, Jensen Huang, Bill Dally, and Fei-Fei Li have been pivotal in advancing the three core pillars of Modern Machine Learning, namely advanced algorithms, high-performance hardware, and high-quality datasets. The combination of these interrelated breakthroughs has led to the widespread adoption and application of AI systems.

In a statement, Professor Dame Lynn Gladden, Chair of Judging Panel, Queen Elizabeth Prize for Engineering, said: “This year’s Prize celebrates the value of transformative breakthroughs and serves as a reminder of the importance of continuous innovation in engineering.”

Modern Machine Learning enables systems to learn from data, recognise patterns, and make predictions without explicit programming. Consequently, MML has transformed AI by allowing models to self-improve with new data.

"The profound impact of data will continue to fuel AI’s increasing power and technological capabilities, we’ll be able to use it for more scientific discovery, to make education more personalised, improve health and elder care, empower creators and designers, and address the realities of our changing planet and climate, to name just a few,” said Dr Fei-Fei Li, the inaugural Sequoia Professor in the Computer Science Department at Stanford University, and a founding co-director of Stanford’s Human-Centered AI Institute.