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Akin to Artificial Intelligence (AI), the concept and possibilities of deep learning are being contemplated and harnessed for several decades. But, in the recent times, the technology pertaining to algorithmic chips has improved considerably, promising to revolutionize major applications such as data centers to the simplest of microcontrollers. In the near future, as algorithms improve further to become more efficient in inferring and training, the market for deep leaning chipset is primed to flourish. According to this business intelligence publication, the demand in the global deep leaning chipset will multiply at a radically rapid CAGR of 24.7% during the forecast period of 2017 to 2025. The analysts of the report have estimated that the opportunities in the deep leaning chipset market, across the world, will collaborate to a revenue of US$1,264.78 mn by the end of 2025, swelling up substantially from its evaluated valuation of merely US$150.17 mn in 2015.
The deep learning chipset market in current scenario is being led by graphics processing unit and central processing unit, but in the coming years, it is foreseen that there will be an extended role for other chipset types which includes application specific integrated circuit, field programmable gate array, and other emerging chipsets such as the Tensor Processing Unit (TPU). Deep learning models will actually be more of like programs, and will certainly have the capabilities to go far beyond the uninterrupted geometric transformation of the input data, which are currently being worked on. Deep Learning is expected to drive the AI adoption into various enterprises too.
This report segments the deep learning chipset market on the basis of type, compute capacity, and end use industry. By type, the deep learning chipset market is categorized mainly into five categories, namely Graphics Processing Units (GPUs), Central Processing Units (CPUs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) and others. Due to complex algorithms and faster processor, the ASIC and FPGA segments are expected to witness strongest demands over the course of the forecast period. ASIC segment is projected to expand at an above-average CAGR of 25.5% during the aforementioned forecast period. Central processing unit (CPU) is the most known computer component responsible for understanding and executing most of the instructions from the computer devices hardware and software. However by 2025, graphics processing units (GPUs) would be the major chipset among others due its ability to perform together with the CPU for the purpose of deep learning, high end gaming, engineering application, and analytics.
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Based on compute capacity, the deep learning chipset market is bifurcated into Low (<1TFlops) and High (>1 TFlops). Based on end use industry, the market has been classified into consumer electronics, automotive, industrial, healthcare, and aerospace & defense.
Market Segmentation
Global Deep Learning Chipset Market, by Type
- Graphics Processing Units (GPUs)
- Central Processing Units (CPUs)
- Application Specific Integrated Circuits (ASICs)
- Field Programmable Gate Arrays (FPGAs)
- Others
Global Deep Learning Chipset Market, by Compute Capacity
- Low (<1TFlops)
- High (>1 TFlops)
Global Deep Learning Chipset Market, by End-User
- Consumer Electronics,
- Automotive,
- Industrial,
- Healthcare,
- Aerospace & Defense
- Others
Global Deep Learning Chipset Market, by Geography
- North America
- The U.S.
- Canada
- Rest of North America
- Europe
- K.
- Germany
- France
- Rest of Europe
- Asia Pacific (APAC)
- Japan
- China
- India
- South Korea
- Rest of APAC
- Middle East and Africa (MEA)
- GCC
- South Africa
- Rest of MEA
- South America
- Brazil
- Rest of South America
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