Deep learning is also called as hierarchical
learning or deep structured learning. It uses different layers of Deep Neutral
Networks (DNNs) to discover the representation & concept that sensesthe
data. Moreover the deep learning activities also include software like Keras or
Lasagne, Tensorflow, Caffe, Theano, Torch and TensorFlow that are used for the
deep learning. The deep learning techniques provides benefits such as
reliability & consistent, easy configuration, simple training interface,
tolerates variations, applications datathat requires less data & computing
power and many others.
According to study, “Global
Deep Learning Market: Drivers, Restraints, Opportunities, Trends, and Forecasts
to 2023” some of the major companies which are currently working in the
global deep learning market areMicrosoft Corporation,Micron Technology, Intel
Corp., Deepmind Technologies Ltd., Baidu Inc., Google Inc., Clairifai Inc., IBM
Corporation, Qualcomm Technologies Inc., Samsung Electronics,Hewlett Packard,
Mellanox Technologies, Nvidia Corporation, Enlitic, ARM Ltd., HyperVerge,
Huawei Technologies, Xilinx Inc., Skymind, Advanced Micro Devices, Inc.,
Sensory Inc.,Fujitsu, General Vision Inc., Amazon Web Services (AWS), Amazon
Web Services. Additionally, some start-ups are Mythic, Koniku, Graphcore and
Adapteva Inc.
Based on offerings or the components, the deep
learning market is segmented into services such as software and hardware. The
components of the services are training, installation and support &
maintenance. Software includes platform or application program interface (API)
and solutions (SDK or software framework). The hardware includes memory,
processor and network on architecture, the SDK market is segmented into
Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Deep
Belief Networks (DBN), Graphical Processing Units (GRU) and Deep Stacking
Networks (DSN).
Based on application market is segmented into
voice or automatic speech recognition, visual art processing, data mining,
image recognition, natural language processing, customer relationship
management, drug discovery & toxicology, recommendation systems, mobile
advertising, financial fraud detection, image restoration, bioinformatics,
artificial intelligence and others. Based on the end-user’s market is segmented
into retail, aerospace & defense, IT & telecommunication, automotive,
finance, medical, oil & gas, energy, industrial and media & advertising
etc.
The deep learning methods are primarily driven
by large training data size, followed by growing artificial intelligence
adoption in customer-centric services, faster processor performance, improving
computing power & declining hardware cost, high economic growth and
sophisticated neural nets etc. Apart from the advantages the major restraints
impacting the market include rigid business models, affordability of
organizations, implementation challenges, dearth of skilled data scientists and
data security concerns & data inaccessibility. Moreover, market is also
driven by new opportunities which include expansion of end-user
base,development in big data technologies, presence of limited structured data
and extensive research & development.
North America holds the largest market share
of deep learning market globally owing to the rising adoption of deep learning
technology in the end-user industries such as marketing, security, healthcare,
agriculture, automotive, fintech, law, retail & manufacturing, and the
strong existence of industry giants & emerging deep learning corporations
or start-ups in the region. It is anticipated that the global deep learning
market to reach at US$28.8 billion, at a CAGR of 48.4 %, by 2023. In the
upcoming years, it is predicted that the market to grow significantly owing to
increasing penetration of smart devices.
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