Deep Learning Market in the US 2017-2021
About Deep Learning
Deep learning is an advanced algorithm that possesses the ability to study large chunks of relevant data to derive meaningful patterns that assist cognitive decision- making. This technology is preferred over machine learning as it enables the user to analyze large data sets. Deep learning algorithms can assess complicated data sets using matrix multiplication. Although machine learning and deep learning algorithms are overlapping subsets of artificial intelligence (AI), the difference lies in the size of input data.
Technavio’s analysts forecast the deep learning market in the US to grow at a CAGR of 57.29% during the period 2017-2021.
Covered in this report
The report covers the present scenario and the growth prospects of the deep learning market in the US for 2017-2021. To calculate the market size, the report considers technology/software installations and related services carried out for deep learning algorithms in process and discrete industries.Technavio's report, Deep Learning Market in the US 2017-2021, has been prepared based on an in-depth market analysis with inputs from industry experts. The report covers the market landscape and its growth prospects over the coming years. The report also includes a discussion of the key vendors operating in this market.
Technavio Announces the Publication of its Research Report – Deep Learning Market in the US 2017-2021
Technavio recognizes the following companies as the key players in the deep learning market in the US: Amazon Web Services, Google, IBM, and Intel.
Other Prominent Vendors in the market are: Microsoft, NVIDIA, OMRON, and Qualcomm Technologies.
Commenting on the report, an analyst from Technavio’s team said: “One trend in the market is advances in deep learning. With industries harnessing deep learning technology to optimize operations and make real-time decisions, modular capabilities in deep learning will aid visual design, configuration, and training new models obtained from pre-existent building blocks. A major structural change will emerge as a result, known as transfer learning, which will enable experiential solving of similar cases.”
According to the report, one driver in the market is enabling condition monitoring in industries. Deep learning facilitates condition monitoring to map the overall equipment effectiveness (OEE) across plant level to generate real-time data regarding assets deployed on the shop floor. Post implementation of deep learning in industries, end-users can leverage technology as a medium to gain knowledge regarding the productivity and machine condition. It has been observed that the overall equipment effectiveness across industries with deep learning technology increased from 65% to 85% with an average improvement of 17-20% across all industries.
Further, the report states that one challenge in the market is technical difficulties encountered. Deep learning technology, which deploys artificial neural networks to make real-time decisions, requires voluminous data to form a knowledge base in order to interpret the behavior of data set. However, carrying out the data acquisition is an arduous task and is also considered unethical. In addition, most of the companies specializing in deep learning technology and AI are small- to mid-sized start-ups. These companies are rated high on their technical capability but lack sufficient funds to gather massive chunk of data.
Amazon Web Services, Google, IBM, Intel, Microsoft, NVIDIA, OMRON, and Qualcomm Technologies.
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