Transparency Market Research delivers key insights on the global deep learning chipset market. In terms of revenue, the deep learning chipset market is estimated to expand at a CAGR of ~24% during the forecast period, owing to numerous factors, regarding which TMR offers thorough insights and forecasts in its report on the deep learning chipset market.
The deep learning technology is driving advancements in artificial intelligence (AI). In the current scenario, the deep learning chipset technology is being led by graphics processing units and central processing units. However, in the next few years, other chipset types including, application-specific integrated circuits and field programmable gate arrays, are expected to play an extended role.
Deep Learning Chipset Market: Dynamics
While in the current scenario, a large number of developments are being witnessed in the robotics industry, the difference between human skills and robot motor skills still remains large. Machines still need to go a long way to match the human proficiency even at the level of basic sensorimotor skills such as grasping things. However, by linking learning with a continuous feedback, this gap can be bridged. By doing so, it would become easier for robots to understand the complexity of the current world and handle issues intelligently and reliably.
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The neural network technology has made great strides to design computer programs that can process images, text, and speech, and can draw pictures too. However, introducing various actions and control mechanism adds substantial new challenges to the network. Overcoming these challenges would help in understanding the method in which machines would communicate in the current ecosystem. By bringing the power of large-scale deep learning to the robotic control, fundamental issues in robotics and automation can be easily resolved. This, in turn, is expected to augment the deep learning chipset market during the forecast period.
Deep Learning Chipset Market: Prominent Regions
North America is the dominant region in the deep learning chipset market. Growth of the market in the region can be attributed to high investments and a large number of manufacturers in the region. Moreover, the market in Europe is expected to witness significant growth during the forecast period, due to increasing demand for deep learning chipsets for use in prediction of frauds and failures in the region. Asia Pacific, South America, and Middle East & Africa are emerging markets for deep learning chipsets, offering lucrative opportunities to vendors and system integrators in the long term.
With the growing need to streamline large volumes of data (training) and computing answers (interference), demand for highly sophisticated deep learning chipsets witnessed unprecedented growth. A large amount of deep learning chipsets was developed for usage across data centers worldwide. However, the trend is gradually expected to shift as stakeholders in the deep learning chipset market are expecting a majority of processing to be carried out at the edge of and closer to sensor arrays.
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AI companies are investing resources toward the development of deep learning chipset-based technologies. Although the adoption of deep learning chipsets will continue in data centers, AI processing is expected to be employed in next-generation devices, including security cameras, drones, smartphones, etc.
Deep Learning Chipset Market: Key Players
Key players operating in the global deep learning chipset market are IBM Corporation, Graphcore Ltd, CEVA, Inc., Advanced Micro Devices, Inc., NVIDIA Corporation, Intel Corporation, IBM Corporation, Movidius, XILINX INC., TeraDeep Inc., QUALCOMM Incorporated, and Alphabet Inc.
