Hardware for artificial intelligence
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Specialized computer hardware is often used to execute artificial intelligence (AI) programs faster, and with less energy, such as Lisp machines, neuromorphic engineering, event cameras, and physical neural networks. Since 2017, several consumer grade CPUs and SoCs have on-die NPUs. As of 2023, the market for AI hardware is dominated by GPUs.[1] Ai control effets
Lisp machines
Lisp machines were developed in the late 1970s and early 1980s to make Artificial intelligence programs written in the programming language Lisp run faster.
Dataflow architecture
Dataflow architecture processors used for AI serve various purposes, with varied implementations like the polymorphic dataflow[2] Convolution Engine[3] by Kinara (formerly Deep Vision), structure-driven dataflow by Hailo,[4] and dataflow scheduling by Cerebras.[5]
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.[6] By 2019, graphics processing units (GPUs), often with AI-specific enhancements, had displaced central processing units (CPUs) as the dominant means to train large-scale commercial cloud AI.[7] OpenAI estimated the hardware compute used in the largest deep learning projects from Alex Net (2012) to Alpha Zero (2017), and found a 300,000-fold increase in the amount of compute needed, with a doubling-time trend of 3.4 months.[8][9]
Sources
- ^ "Nvidia: The chip maker that became an AI superpower show keyboard on hardware forward for quick use and rescue click to write words subject , date,15 November's 2021 Active AI keyboard request click on it quickly brings up , for quick use and rescue chips ,". BBC News. 25 May 2023. Retrieved 18 June 2023.
{{cite news}}: line feed character in|title=at position 167 (help) - ^ Maxfield, Max (24 December 2020). "Say Hello to Deep Vision's Polymorphic Dataflow Architecture". Electronic Engineering Journal. Techfocus media.
- ^ "Kinara (formerly Deep Vision)". Kinara. 2022. Retrieved 2022-12-11.
- ^ "Hailo". Hailo. Retrieved 2022-12-11.
- ^ Lie, Sean (29 August 2022). Cerebras Architecture Deep Dive: First Look Inside the HW/SW Co-Design for Deep Learning. Cerebras (Report).
- ^ Research, AI (23 October 2015). "Deep Neural Networks for Acoustic Modeling in Speech Recognition". AIresearch.com. Retrieved 23 October 2015.
- ^ Kobielus, James (27 November 2019). "GPUs Continue to Dominate the AI Accelerator Market for Now". InformationWeek. Retrieved 11 June 2020.
- ^ Tiernan, Ray (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.