Deep Learning Market Growth & Trends
The global deep learning market size is expected to reach USD 526.7 billion by 2030, registering a CAGR of 34.3% over the forecast period, according to a new report by Grand View Research, Inc. Deep learning is expected to gain sustainable momentum in the coming years owing to its high computational ability and improved complex data-driven applications. The growing emphasis on big data analytics and Artificial Intelligence (AI) adoption in customer-centric services is expected to propel the growth of the market over the forecast period.
AI has evolved rapidly over the period, enabling the machine to perform cognitive tasks effectively. The adoption of AI across various sectors has unlocked the potential opportunities for machine learning and deep learning applications. AI-as-a-service has allowed smaller organizations to implement the AI algorithms required for deep learning applications without a large capital investment. Moreover, the availability of a large amount of data and the need for high computing power encourage Small & Medium Enterprises (SMEs) and large enterprises to invest significantly in deep learning technology.
Deep learning allows the machine to solve complex problems even if the data is not well organized. A deep learning algorithm performs a task repeatedly, every time tweaking it to improve the outcomes. Thus, the more the task performed by the machines, the better will be the outcome. As a result, large amounts of unstructured data can be analyzed using deep learning algorithms and obtain relevant insights for the decision-making process. For instance, the organizations may use deep learning technology to unveil any data pointers between industry insights, social media conversation, and a stock price of a given organization.
Image and voice recognition are some of the leading applications in the deep learning market. Several online and offline services such as Alexa virtual assistant by Amazon, Microsoft Cortana, and Siri use deep learning to understand humans’ language while interacting with them. Facebook and Google have implemented deep learning technology for cognitive image analysis in their image classification application. It helps the companies to provide relevant results and automatic descriptions related to the image. Besides, deep learning algorithms can recreate a black-and-white image in color, offering impressive and accurate results in image colorization applications. For instance, In June 2019, Amazon introduced a new deep learning model called Alexa Conversations to create natural voice experiences on Alexa.
Deep learning offers lucrative investment opportunities for vendors due to the technology’s high adoption rate. As a result, the companies consider product development as one of the strategic initiatives to capture the deep learning market share. Recently, in February 2020, Google Inc. announced the launch of Reformer, an updated version of the transformer deep-learning model. In February 2020, Concentrix Corporation launched the deep learning algorithm tool for cybersecurity applications.
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Deep Learning Market Report
Deep Learning Market Report Highlights
- The hardware segment is expected to witness the fastest growth over the forecast period owing to the growing demand for deep learning chipsets and reduced hardware costs
- The Field Programmable Gate Array (FPGA) possesses a high computational capability and has better power efficiency. As a result, the FPGA segment is expected to grow at the highest CAGR during the forecast period
- Deep learning algorithms exhibit great potential in the automated extraction of complex data, thereby excelling in the big data analytics application
- Deep learning is expected to revolutionize the healthcare industry in the coming years by applying neural networks to patients’ data to provide better outcomes
- Several government initiatives related to digitalization and the growing adoption of next-generation technologies such as AI and machine learning in the APAC region exhibited the strong growth of deep learning technology
