Introduction
Geoffrey Everest Hinton (born 6 December 1947) is a British-Canadian computer scientist. He is known for his outstanding contributions to machine learning and eventually won the Turing Award in 2018.
Academic Journey
Interestingly, Geoffrey Hinton never found a degree that suited him while attending university, switching degrees between different disciplines such as natural sciences, art history, and philosophy, eventually earning a Bachelor of Arts in experimental psychology. Whilst studying psychology, he developed a great interest in understanding the workings of human consciousness. Then, he went to study at the University of Edinburgh and received his PhD in Artificial Intelligence in 1978.
Major Academic Contributions
Hinton contributed significantly to the development of machine learning during his career in computer science, particularly as a professor at the University of Toronto. He was one of the early proponents of deep learning and proposed the Backpropagation algorithm, which is considered an important tool for training neural networks. In the 1980s, his research laid the groundwork for the renaissance of neural networks and deep learning. However, neural networks were once not considered by the academic community as the right direction for the development of artificial intelligence, limited by the performance of computers and the amount of data at that time, the use of neural networks was not very effective. Marvin Minsky, a famous computer scientist at that time, did not look favorably on the development of neural networks in his publication Perceptrons, and as a result, Hinton has been considered for quite a long time to be out of the mainstream of academia. However, the backpropagation algorithm promoted by Hinton solves the problem of weight updating and error propagation, which enables neural networks to gradually adapt to the input data and improve their accuracy and efficiency in various tasks. This is the basis for the wide range of deep learning and neural network applications.
Hinton has also made important contributions to the field of natural language processing, particularly in Word Embeddings. This approach allows words to be represented as vectors, enabling computers to better understand and process natural language. This is essential for speech recognition, machine translation, and other natural language processing tasks.
Career History
After obtaining his PhD, Hinton worked at the University of Sussex and, after struggling to find funding in the UK, at the University of California, San Diego, and Carnegie Mellon University respectively. Today he is a professor in the Department of Computer Science at the University of Toronto. In addition, he has worked at Google since March 2013 and publicly announced his resignation from Google in May 2023, citing a desire to speak freely about the risks of artificial intelligence.