Deep learning is a subset of artificial intelligence and machine learning that uses multi-layered artificial neural networks to deliver state-of-the-art accuracy in tasks such as object detection, speech recognition, language translation and others. Deep learning is responsible for many of the recent breakthroughs in AI such as Google DeepMind’s AlphaGo, self-driving cars, intelligent voice assistants and many more. The accelerated deep learning frameworks/chipsets allow researchers and data scientists can significantly speed up deep learning training, that could otherwise take days and weeks to just hours and days. The chipset’s highly flexible architectures can learn directly from raw data and can increase their predictive accuracy when provided with more data.
The deep learning chipset market, in terms of revenue, which was estimated at US$ 723 million in 2017, is expected to reach US$ 4,170.9 million by 2022.
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Deep Learning Chipset market research is an intelligence report with meticulous efforts undertaken to study the right and valuable information. The data which has been looked upon is done considering both, the existing top players and the upcoming competitors. Business strategies of the key players and the new entering market industries are studied in detail. Well explained SWOT analysis, revenue share and contact information are shared in this report analysis.
The Graphics Processing Units (GPUs) Anticipated to be the Dominant Segment During the Forecast Period 2018 to 2026.
Some of the key participants in global mining renewable energy systems market are Amazon Web Services, Inc., ARM Limited, CEVA Inc., Facebook, Google LLC., Graphcore, IBM Corporation, Intel Corporation, Nvidia Corporation, Qualcomm Technologies, Inc., Teradeep Inc., and Xilinx Inc. amongst others. In 2018, Apple unveiled the A11 Bionic chip, which powers the iPhone 8, 8 Plus and X. The A11 Bionic features a neural engine that is purpose-built for machine-learning among other things. This new architecture enables machine-learning computations, which used to be processed in the cloud, can now be carried out more efficiently on a device.
For the purpose of the study, Global Deep Learning Chipset market is segmented based on various parameters. An in-depth regional classification of the market is also included herein. The factors which are impacting the market’s growth are studied in detail. The report also presents a round-up of vulnerabilities which companies operating in the market must avoid in order to enjoy sustainable growth through the course of the forecast period.
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The report provides insights on the following pointers:
– Market Penetration: Comprehensive information on the product portfolios of the top players in the Deep Learning Chipset market.
– Product Development/Innovation: Detailed insights on the upcoming technologies, R&D activities, and product launches in the market
– Competitive Assessment: In-depth assessment of the market strategies, geographic and business segments of the leading players in the market
– Market Development: Comprehensive information about emerging markets. This report analyzes the market for various products across geographies
– Market Diversification: Exhaustive information about new products, untapped geographies, recent developments, and investments in the Deep Learning Chipset market
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