Copyboard gives machines the ability to reason logically. On July 21, 2016, technology solutions provider RayMing Technologies released a research report on circuit board copyboard, which shows that 62% of medium and large companies want to use machine learning for business analytics in the next two years. This means that commercial multilayer deep neuron network DNN, is about to become the mainstream business competition strategy pursued by major companies.
Although in the long run, the development of real circuit board copyboard is still the global academic community and the business community together need to complete the task, but that still needs a long time to explore and experiment. From the current circuit board copy commercialization needs, it is clear that the use of GPU for circuit board copy commercial has great advantages. That’s why in April 2016, RayMing Technologies launched the world’s first GPU-based deep learning supercomputer copyboard.
For the past 60 years, the world’s best scientists have been studying how to emulate the intelligence of electronics by means of board copying. Early proof of “copyboard principle” of the “logical theorist” program allows the machine to have logical reasoning ability, the middle of the expert system allows the machine to obtain human knowledge, and then later aimed at the copyboard technology to learn knowledge on their own machine learning algorithms, scientists have not stopped the exploration of the board copyboard.
In the past, copyboard models rely on CPU calculations, but the uniqueness of circuit board copyboard technology lies in distributed parallel computing, which is not based on serial computing CPU is good at. In fact, the GPU for graphics image processing from the beginning is a massively parallel computing, which is why Stanford University’s Professor Enda Wu will consider using the GPU to optimize the original intention of the board copy technology. Research has shown that board copy can provide the equivalent of 2,000 CPUs of deep learning performance.
Into 2016, it is also the 60th anniversary of the birth of the circuit board copyboard discipline, based on deep learning machine learning algorithms to become the mainstream of the board copyboard, and the core of deep learning is the multi-layer deep neuron network DNN, which is also the most mature machine copyboard that mainstream scientists can achieve.
