Hardware for artificial intelligence
 | This article needs attention from an expert on the subject. The specific problem is: Needs attention from a current expert to incorporate modern developments in this area from the last few decades, including TPUs and GPUs, and to clean up the existing material and clarify how it relates to the subject. (November 2021) |
 | This article is missing information about its scope: What is AI hardware for the purposes of this article? "Memristors" are not even specialized hardware for AI, it's a basic electronic component, like resister, capacitor, inductor. Event cameras are an application of neuromorphic design, but LISP machines are not an end use application.. (November 2021) |
Specialized hardware for artificial intelligence is used to execute artificial intelligence programs faster, such as Lisp machines, neuromorphic engineering, event cameras, JAIC, physical neural networks, or the memristor.
Lisp machines
 | This section should include only a brief summary of another article. (October 2021) |
Lisp machines were developed in the late 70s and early 80s to make AI programs written in the language Lisp to run faster.
Neural network hardware
Physical neural networks
Component hardware
AI accelerators
Since the 2010s, advances in computer hardware have led to more efficient methods for training deep neural networks that contain many layers of non-linear hidden units and a very large output layer.[1] By 2019, graphic processing units (GPUs), often with AI-specific enhancements, had displaced CPUs as the dominant method of training large-scale commercial cloud AI.[2] 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 compute required, with a doubling-time trendline of 3.4 months.[3][4]
Sources
- ^ Research, AI (23 October 2015). "Deep Neural Networks for Acoustic Modeling in Speech Recognition". airesearch.com. Retrieved 23 October 2015.
- ^ "GPUs Continue to Dominate the AI Accelerator Market for Now". InformationWeek. December 2019. Retrieved 11 June 2020.
- ^ Ray, Tiernan (2019). "AI is changing the entire nature of compute". ZDNet. Retrieved 11 June 2020.
- ^ "AI and Compute". OpenAI. 16 May 2018. Retrieved 11 June 2020.
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