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Summary
Further key aspects of the report indicate that:
Chapter 1: Research Scope: Product Definition, Type, End-Use & Methodology
Chapter 2: Global Industry Summary
Chapter 3: Market Dynamics
Chapter 4: Global Market Segmentation by region, type and End-Use
Chapter 5: North America Market Segmentation by region, type and End-Use
Chapter 6: Europe Market Segmentation by region, type and End-Use
Chapter 7: Asia-Pacific Market Segmentation by region, type and End-Use
Chapter 8: South America Market Segmentation by region, type and End-Use
Chapter 9: Middle East and Africa Market Segmentation by region, type and End-Use.
Chapter 10: Market Competition by Companies
Chapter 11: Market forecast and environment forecast.
Chapter 12: Industry Summary.
The global Deep Learning Chipset market has the potential to grow with xx million USD with growing CAGR in the forecast period from 2021f to 2026f. Factors driving the market for @@@@@ are the significant development of demand and improvement of COVID-19 and geo-economics.
Based on the type of product, the global Deep Learning Chipset market segmented into
- Consumer
- Central Processing Units (CPUs)
- Application Specific Integrated Circuits (ASICs)
- Field Programmable Gate Arrays (FPGAs)
- Others
Based on the end-use, the global Deep Learning Chipset market classified into
- Consumer
- Aerospace, Military & Defense
- Automotive
- Industrial
- Medical
- Others
Based on geography, the global Deep Learning Chipset market segmented into
- North America [U.S., Canada, Mexico]
- Europe [Germany, UK, France, Italy, Rest of Europe]
- Asia-Pacific [China, India, Japan, South Korea, Southeast Asia, Australia, Rest of Asia Pacific]
- South America [Brazil, Argentina, Rest of Latin America]
- Middle East & Africa [GCC, North Africa, South Africa, Rest of Middle East and Africa]
And the major players included in the report are
- NVIDIA
- Intel
- IBM
- Qualcomm
- CEVA
- KnuEdge
- AMD
- Xilinx
- ARM
- Graphcore
- TeraDeep
- Wave Computing
- BrainChip