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A neural processing unit (NPU), also known as AI accelerator or deep learning processor, is a class of specialized hardware accelerator [1] or computer system [2] [3] designed to accelerate artificial intelligence (AI) and machine learning applications, including artificial neural networks and computer vision.
By 2019, graphics processing units , often with AI-specific enhancements, had displaced CPUs as the dominant method of training large-scale commercial cloud AI. [162] OpenAI estimated the hardware compute used in the largest deep learning projects from AlexNet (2012) to AlphaZero (2017), and found a 300,000-fold increase in the amount of ...
Generative artificial intelligence (generative AI, GenAI, [165] or GAI) is a subset of artificial intelligence that uses generative models to produce text, images, videos, or other forms of data. [ 166 ] [ 167 ] [ 168 ] These models learn the underlying patterns and structures of their training data and use them to produce new data [ 169 ...
Other AI accelerator designs are appearing from other vendors also and are aimed at embedded and robotics markets. Google's TPUs are proprietary. Some models are commercially available, and on February 12, 2018, The New York Times reported that Google "would allow other companies to buy access to those chips through its cloud-computing service."
CI is an alternative to AI; AI includes CI; CI includes AI; The view of the first of the above three points goes back to Zadeh, the founder of the fuzzy set theory, who differentiated machine intelligence into hard and soft computing techniques, which are used in artificial intelligence on the one hand and computational intelligence on the other.
Artificial intelligence arms race – competition between two or more states to have its military forces equipped with the best "artificial intelligence" (AI). Lethal autonomous weapon; Military robot; Unmanned combat aerial vehicle; Mitigating risks: AI safety; AI control problem
Machine learning (ML) is a subfield of artificial intelligence within computer science that evolved from the study of pattern recognition and computational learning theory. [1] In 1959, Arthur Samuel defined machine learning as a "field of study that gives computers the ability to learn without being explicitly programmed". [ 2 ]
In computer science, online machine learning is a method of machine learning in which data becomes available in a sequential order and is used to update the best predictor for future data at each step, as opposed to batch learning techniques which generate the best predictor by learning on the entire training data set at once.