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Market Leader - Deep Learning Market


Deep learning combines advanced techniques of computing power of processors such as CPUs, GPUs, and neuromorphic chips, along with special types of neural networks, to learn complicated patterns within a large volume of data. Deep learning is a cutting-edge technique for identifying objects in images (e.g., detection of a human face in an image) and signal inputs in the form of sound wave/sound. The deep learning market is expected to grow at a CAGR of 41.7% between 2018 and 2023, from USD 3.18 Billion in 2018 to USD 18.16 Billion by 2023. The increasing usage of cloud-based technology and deep learning usage in big data analytics are supplementing the growth of the deep learning market.

The deep learning market is gaining momentum as a result of organic as well as inorganic growth strategies followed by players operating in this market. Various companies have adopted different strategies to strengthen their position in this market and ensure long-term growth and success. Product launch is the most prominent growth strategy adopted by players in this market. Product developments and launches are mainly focused on improving computing power, memory capacity, and consumer experience. Moreover, companies adopted collaborations and strategic partnerships as key growth strategies in the deep learning market. The key players following these strategies are NVIDIA, Intel, IBM, Microsoft, AWS, Xilinx, Samsung, Qualcomm, and Google, among others.

Intel (US) was an important player in the deep learning market in 2017. Intel enjoys strong market presence and has been effectively defending the same. The company has dominated the market for microprocessors for many years. The company’s dominant market position ensures a large addressable market. Intel’s market position also provides increased scale and related benefits. The established market position provides competitive advantages and allows the company to effectively penetrate the adjacent markets. One of the competitive advantages of Intel is the combination of a network of manufacturing, assembly, and test facilities with the global architecture design teams. This network enables the company to have more direct control over processes, quality control, product cost, production timing, performance, power consumption, and manufacturing yield. Intel Corporation has strengthened its artificial intelligence division by acquiring Mobileye, Saffron Technologies, Altera, and Nervana Systems. Intel aims to make DL technology easily available to all, with open data exchanges and initiatives. To meet this goal, in November 2016, the company launched the Intel Nervana AI Academy program, which has increased the accessibility to data, tools, training, and intelligent machines for developers, academics, and start-ups.

NVIDIA is among the key players involved in the development of deep learning hardware, software, and services. NVIDIA is one of the global leaders in the visual computing business. It has a well-established geographic footprint and mainly deals with major OEMs and ODMs around the globe. NVIDIA has made substantial investments in R&D. This has resulted in its strong organic growth and robust market position in terms of hardware product development in the deep learning market. The company’s GPU segment consists of GeForce, Quadro, GeForce NOW, Quadro, Tesla, and GRID. The company strongly relies on its organic growth capabilities. In December 2017, NVIDIA introduced TITAN V, the world’s most powerful GPU for PC, driven by the world’s most advanced GPU architecture, NVIDIA Volta. TITAN V excels at computational processing for scientific simulation. Its 21.1-billion transistors deliver 110 teraflops of raw horsepower, 9x that of its predecessor, and extreme energy efficiency.

Related Reports:

Deep Learning Market by Offering (Hardware, Software, and Services), Application (Image Recognition, Signal Recognition, Data Mining), End-User Industry (Security, Marketing, Healthcare, Fintech, Automotive, Law), and Geography - Global Forecast to 2023

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