Global Deep Learning Chipset Market was valued US$ XX Bn in 2018 and is expected to reach US$ 2.9 Bn by 2026, at CAGR of XX % during the forecast period.
The report covers all the trends and technologies playing a major role in the growth of the deep learning chipset market over the forecast period. It highlights the drivers, restraints, and opportunities expected to impact market growth during this period.
Deep learning chipset technology has improved drastically in recent times owing to the increasing demand for deep learning in industries to solve problems such as computer vision and pattern recognition. Many semiconductors companies are coming up with new chipset technology to cater to the demand and innovation fueled by heavy investment is underway in the very market.
Increased adoption of cloud-based technology and deep learning usage in big data analytics are the factors driving the growth of the deep learning chipset market. Also, the Invention of a related computer chip, which is known as the GPU. A single-chip processor creates lighting effects and transforms objects every time a 3D scene is redrawn or graphics processing unit is turning out to be very meaningful and effective when it is being applied to types of calculations mandatory for neural nets. This, in turn, is fueling the growth of the deep learning chipset market.
By type, the graphics processing units segment holds the largest XX% market share of and expected to dominate the market during the forecast period. For machine learning tasks, GPUs were found to be between 10 and 100 times as fast as CPU-only machine learning solutions, depending on the exact task.
North America is expected to hold the largest XX% share of the global market for the mass notification system during the forecast period. The high demand for deep learning chipsets in the North American market is attributed to the rising number of startups in the region. The valuation of the APAC is expected to be around worth US$ XX Mn in terms of revenue.