Rapid Shift to Cloud Computing To Augment Deep Learning Solution Demand

Punit Shah
3 min readJul 4, 2022


Automotive, healthcare, retail, manufacturing, and banking, financial services, and insurance (BFSI) companies around the world are increasingly adopting cloud computing platforms, as they offer hosted data storage solutions, which help organizations in substantial cost savings. Cloud computing serves as an ideal platform for deep learning algorithms, as the architecture provides support for scalability and virtualization and offers storage for a large volume of structured and unstructured data. Deep learning-enabled cloud platforms define the ability of a network, processor, or system to manage a huge volume of data efficiently.

Thus, the increasing adoption of cloud computing platforms in end-use industries will help the deep learning market advance at an exceptional CAGR of 35.2% during 2020–2030. According to P&S Intelligence, the market revenue stood at $3.7 billion in 2019 and it will reach $102.4 billion by 2030. Additionally, the mounting investments being made by public and private organizations in information technology (IT) infrastructure will also result in the widespread adoption of deep learning solutions in the coming years, owing to their ability to analyze a large volume of data.

Deep learning technology is used in signal recognition, data mining, image recognition, natural language processing (NLP), and recommendation engine applications. In the coming years, deep learning solutions will be widely used in NLP applications, due to the surging need to integrate deep learning and NLP in chatbots and voice assistants to increase machine–human interactions, as these technologies help chatbots and voice assistants understand customer queries and respond accordingly, without manual intervention.

Currently, deep learning solution providing companies are focusing on partnerships and acquisitions to cater to the needs of the retail, automotive, manufacturing, healthcare, and BFSI industries. For instance, in July 2017, Alphabet Inc. completed the acquisition of Halli Labs Pvt. Ltd., a provider of machine learning (ML) and deep learning solutions. As per the terms of this agreement, Halli Labs Pvt. Ltd. agreed to join Google’s Next Billion Users team to increase the reach of ML and deep learning technologies among its customers.

Further, in July 2019, Intel Corporation signed a partnership agreement with Baidu Inc. to jointly work on the Nervana Neural Network Processor (NNP) of the former. With this partnership, both the entities agreed to work on the hardware and software of NNP to ensure the optimization of this processor in the PaddlePaddle deep learning framework of Baidu Inc. Other companies opting for such measures include SAS Institute Inc., Qualcomm Incorporated, IBM Corporation, Amazon Web Services Inc., Samsung Electronics Co. Ltd., NVIDIA Corporation, and Microsoft Corporation.

Globally, the North American region dominated the deep learning market in the recent past, owing to the rapid technological advancements and the existence of developed IT infrastructure in the U.S. and Canada. Currently, end-use industries in the region are rapidly adopting deep learning solutions for voice assistance, image recognition, and product recommendation on social networks. Moreover, the mounting investments being made by governments in AI technologies will also result in the widescale adoption of deep learning solutions in North America.

Thus, the surging shift of end-use industries toward cloud computing and the increasing IT expenditure will facilitate the adoption of deep learning solutions, globally.