The commercial use of Neural Networks
The first commercial application of neural networks was in image processing. In the 1970s, computer scientists created and implemented the first neural networks, the so-called VLSI (very large scale integrated circuit) technology, which used a large number of transistors.
The first VLSI-based image processing system was the Image Processing Unit (IPU), a hardware-based implementation of a VLSI with several million transistors.
The concept of using artificial neural networks was proposed by two British researchers, Geoff Hinton and Jeff Dean, who worked at the University of California, Berkeley, in the 1980s. The idea was to use neural networks to recognize objects in computer graphics, where the goal was to learn a function from data.
This approach is not new. It was used in the 1990s by two other researchers: a British researcher, Richard Szeliski, and the American Michael Nielsen. The idea of using neural networks was then applied to speech recognition. The first neural network-based digital speech synthesizer was called “VoicePlus” and was developed at IBM.
While the majority of AI research and development has focused on creating more powerful computers, and to a lesser extent, more intelligent robots, AI research has also been directed towards creating systems that can think and act like humans.
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