2025 Queen Elizabeth Prize for Engineering Honors Pioneers of Modern Machine Learning
The 2025 Queen Elizabeth Prize for Engineering has been awarded to seven distinguished engineers for their revolutionary contributions to Modern Machine Learning, a pivotal element propelling artificial intelligence advancements. This recognition underscores their impactful work in enabling systems to autonomously learn from data and make informed decisions or predictions without explicit programming for every situation. Such capabilities are essential in AI development as they allow continuous improvement and adaptation to new information over time. The remarkable progress in machine learning stems from groundbreaking innovations in algorithms, computational power, and crucial benchmark datasets. This confluence of advancements has catalyzed the broad adoption of AI technologies. Among the laureates, Yoshua Bengio, Geoffrey Hinton, John Hopfield, and Yann LeCun have been instrumental in championing artificial neural networks, which have emerged as the predominant model for machine learning. Additionally, Jensen Huang and Bill Dally have spearheaded the evolution of hardware platforms critical for deploying these algorithms efficiently. Their pioneering work with Graphics Processing Units and architectural enhancements has been fundamental in enabling scalable applications. Meanwhile, Fei-Fei Li's creation of ImageNet has set a benchmark in providing high-quality datasets essential for training and assessing computer vision algorithms. Collectively, these engineers have laid the groundwork for machine learning technologies that are at the forefront of today's most exciting and transformative innovations.