AI Drives Global Machine Learning Chip Market

Allied Market Research recently reported that the global machine learnings chip market was valued at $2.4 Billion in 2017 and is expected to reach about $37.8 Billion by 2025 while growing at a compound annual growth rate (CAGR) of 40.8% during the forecast period. The increasing use of artificial intelligence (AI) and machine learning in numerous applications are one of the main factors that drive the market.


Based on chip type, the market is segmented into GPU, ASIC, FPGA, CPU, and others. The ASIC segment is expected to surpass the GPU segment in future, in terms of revenue. Based on industry vertical, the market can be segmented into media & advertising, BFSI, IT & telecom, retail, healthcare, automotive & transportation, and several others. Key players in the market for machine-learning chips include Squire Mining Ltd., Nvidia Corporation, Qualcomm Incorporated, Advanced Micro Devices, Inc., and Micron Technology, Inc.



  • Squire Mining Ltd. has engaged Gaonchips design fabrication firm to perform the back-end design, testing and initial mass production run of its next generation ASIC chip for mining Bitcoin. 
  • Nvidia Corporation recently introduced the NVIDIA DRIVE AGX Xavier Developer Kit, a platform for building autonomous driving systems. This open, scalable software and hardware solution enables companies to seamlessly develop and test customized autonomous driving technology, streamlining production.
  • Qualcomm introduced new roadside units (RSUs) for 3rd Generation Partnership Project (3GPP) Release 14 LTE-V2X direct communication (PC5) based on the Qualcomm® 9150 C-V2X chipset solution.
  • Advanced Micro Devices reimagined its family of AMD Athlon desktop processors with Radeon Vega graphics that have been optimized for everyday PC users: the AMD Athlon 200GE, Athlon 220GE, and Athlon 240GE processor.
  • Micron Technology has ramped up volume production on its 8Gb GDDR6 memory, optimized for a variety of applications including artificial intelligence (AI), networking, automotive and graphics processing units (GPUs).  

For more machine-learning market news, visit