Penetration of the Smart Devices to Drive the Deep Learning Market Over the Forecast Period: Ken Research


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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