Geoffrey Hinton
AI researcher · shared the 2018 Turing Award and 2024 Physics Nobel
Records 12
Newest first. Open one to see it with its source.
A move from 2023's risk warnings to a 2025 alignment prescription. Head-on skepticism toward alignment strategies built on control and obedience
Turned a qualitative warning into a number. Since then, the most widely cited reference value in the p(doom) debate
A public change of position by one of the founders of deep learning. The turning point at which discussion of AI existential risk moved from the fringe into the mainstream press
Normalization that does not depend on the batch. Once the Transformer adopted it, it became a de facto basic component
Formalized distillation, which transfers a large model's knowledge to a small model. The root of today's small-model lineage
Established in a paper the combination of GPUs, large-scale data and deep CNNs. The conventional starting point of the current deep learning era
The turning point at which, with a wide margin over second place, deep CNNs became the mainstream methodology of computer vision
Curbed overfitting with simple regularization and later became a standard technique
Separate industry groups confirmed the same shift (HMM→DNN), and deep learning became the industry standard for speech recognition
An early paper demonstrating the advantages of ReLU, which later became the standard activation function
Showed once again that deep networks can be trained, sparking the revival of deep learning in the 2000s
Showed that hidden layers learn useful internal representations for a task on their own, making the training of multilayer neural networks practical