The 2025 Queen Elizabeth Prize for Engineering has been awarded to seven engineers for their groundbreaking contributions to the development of modern machine learning, a fundamental pillar of artificial intelligence (AI).
Machine learning allows systems to learn from data, recognize patterns, and make decisions without explicit programming for each scenario. This ability to self-improve and adapt has been crucial for AI advancements, enabling models to evolve as they process new information.
The success of modern machine learning is built on three key innovations: algorithmic breakthroughs, advancements in computing hardware, and high-quality datasets.
Yoshua Bengio, Geoffrey Hinton, John Hopfield, and Yann LeCun pioneered artificial neural networks, laying the theoretical foundation for deep learning, which has become the dominant machine learning approach.
Jensen Huang and Bill Dally revolutionized hardware platforms, advancing Graphics Processing Units (GPUs) to scale AI model performance and efficiency.
Fei-Fei Li emphasized the importance of large-scale labeled datasets for training AI, leading to the creation of ImageNet, a dataset that transformed computer vision research.
Together, their contributions have laid the groundwork for modern AI, powering innovations in healthcare, robotics, autonomous systems, and many other fields, shaping the technological landscape of today and the future.