Tensor Processing Unit Market Segment Analysis By Type
Based on type segmentation, Type v4 is analyzed to grow with the highest CAGR of 8.2% in the global tensor processing unit market during the forecast period 2022-2027. With growing demand towards machine learning (ML) training or AI based workloads across enterprises, the need for processors or hardware capable of providing high level computing power have become essential. Adoption of TPU type v4 chipsets can help in delivering faster speed data computing efficiency, causing reduction in power consumption, while making it a cost efficient alternative. Factors including rising investments on establishment or expansion of cloud data center facilities, shift towards infrastructures with higher user handling capacity, as well as need for improving processing requirements during cloud computing applications across large enterprises overtime can also positively impact the market growth of tensor processing units. In May 2021, Google announced the launch of its next-generation AI processing chip, named TPU v4, as a part of boosting TPU hardware performance by more than two times compared to earlier TPU v3 chips. This development was done to bring critical new power as well as promise towards machine learning training speeds on the Google Cloud platform, while sustaining the rapid advances of artificial intelligence and machine learning technologies. Such developments are meant to boost the market growth forward in the long run.
Tensor Processing Unit Market Segment Analysis By Application
Smartphone segment is analyzed to account for the highest CAGR of around 7.5% in the global Tensor Processing Unit market during 2022-2027. Growing demand for high-end smartphones, increasing shift towards optimum battery backup smartphone models, and so on can be considered as some major factors driving the market growth of tensor processing units (TPU). In comparison to graphical processing units (GPU), these application-specific integrated circuits or TPUs are capable of accelerating artificial intelligence (AI) calculations or algorithms with higher flexibility, latency as well as faster speeds. This in turn, has been gaining wide popularity to be utilized for enhancing smartphone hardware processing capabilities. In August 2021, Google had revealed its plans of utilizing the in-house processor, Tensor in order to power the upcoming product line of Pixel smartphones, expected to be shipped in late 2021. This integration of TPU chipsets will help in assisting artificial intelligence based workloads with the roll out of more advanced features including image processing, speech recognition and many others for the Pixel 6 and Pixel 6 pro smartphones. Such factors are further set to drive the market demand for smartphone integrated with tensor processing units in the long run.
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Tensor Processing Unit Market Segment Analysis By Geography
APAC region had accounted with the largest share of around 35% in the global Tensor Processing Unit market in 2021, attributing to factors like growing shift of IT firms towards optimizing enterprise workflows along with rising investments or initiatives to support the development of autonomous driving or connected vehicles. Adoption of advanced technologies like AI, machine learning and others within enterprises as well as the growing requirement of high end processors or hardware interfaces to improve smartphone and gaming applications can also fuel the demand for tensor processing units within the region. In addition, shift towards modernizing healthcare facilities through adoption of real-time predictive analytics and monitoring, increasing demand for smart watches, fitness trackers, virtual reality or augmented reality devices and so on will further drive the need for hardware processors enabling accurate and high-speed data collection capabilities as of tensor processing units in the long run. In September 2020, an Indian Tech startup, named Muse Wearables announced the launch of an AI powered personal wellness smart band, Muse Cue. Equipped with a skin temperature sensor, this band is capable to offer context-aware activity tracking through detecting silent hypoxia at an early stage as well as with the intelligent cough analysis tool, can also predict and alert users in advance regarding onset of COVID-19 symptoms. Such innovations are further set to drive the market growth for AI based chipsets in the long run.
Tensor Processing Unit Market Drivers
Growing shift towards predictive analytics and monitoring to boost healthcare or clinical operations drive the market forward:
A growing shift towards predictive analytics and monitoring to boost healthcare or clinical operations can be considered as a major factor driving the growth of tensor processing unit market. Growing demand for real-time predictive analysis across healthcare industry, shift towards improving standard of care through optimizing clinical and related medical operational procedures, as well as rising adoption of health monitoring platforms have been attributed towards the market growth. Utilizing AI based TPU chipsets for health monitoring, regulating or gaining early insights regarding patient care along with reducing preventative medical errors can also drive the demand forward. In December 2019, a provider of AI-powered autonomous monitoring platform for the healthcare industry, named care.ai had revealed about its partnership with Google in order to leverage the Coral Edge TPU for powering its autonomous monitoring platform. This partnership was meant to make the care.ais platform capable of utilizing speedy neural networks for converting an ordinary room into a self-aware room at an enterprise scale. Under this, an AI sensor was built for monitoring, predicting as well as inferring behaviours from billions of data points within real-time, and is set to drive such innovations for the healthcare industry in the long run.
Increasing demand for connected vehicles and autonomous cars will positively impact the market growth for AI chipsets:
Increasing demand for connected vehicles and autonomous cars can also be considered one of the prime factors driving the market growth of tensor processing unit. With growing advancement towards mobility, demand for connected vehicles and autonomous cars is getting impacted significantly, which serves as one of the key application areas of artificial intelligence (AI). Since these vehicles rely on AI, either in the form of machine learning or deep learning algorithms, the need for instant processing capabilities for massive amounts of data becomes highly essential. Integration of various hardware components including cameras, safety systems and so on, eventually impacts the market growth of high-end chipsets or processors like TPU, capable of accelerating AI based workflows more efficiently. In January 2019, Robert Bosch had revealed about its plans on research alliance expansion regarding autonomous vehicles along with the 4 billion euros investment ($4.6 billion) towards development of self-driving cars by 2022. In April 2021, researchers at the Technical University of Munich in collaboration with BMW Group announced about conducting a study related to development of an early warning system, designed for autonomous vehicles. This system leverages AI technology for learning related to thousands of real traffic situations, offering seven seconds advanced warning against potentially critical situations with over 85% accuracy, thereby set to drive the market growth for TPU in the coming time.
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Tensor Processing Unit Market Challenges
Limited support for small sized workload models hampers its market growth:
Limited support for small-sized workload models act as one of the major factors restraining the market growth of tensor processing unit. Since these processing units utilizes topology different from hardware platforms available in the market, there are complexities regarding its integration and framework distribution. In addition, its capability of supporting certain workload models or operations with limited scope hampers its adoption across varied end use sectors. Moreover, tensor processing units or TPU serve its optimal capacity particularly for large models having very large batch sizes or workloads which are dominated by matrix-multiplication, which slows down its adoptability for serving small scale application areas.
Tensor Processing Unit Market Landscape
Product launches, acquisitions, and R&D activities are key strategies adopted by players in the Tensor Processing Unit market. Tensor Processing Unit top 10 companies include:
In July 2020, Graphcore announced the launch of its first-generation Intelligence Processing Unit, named IPU-Machine M2000. This development was meant to offer greater processing power, high memory as well as built-in scalability for handling extremely large machine intelligence workloads.
In May 2020, Xilinx Inc. announced the launch of 20 nm space grade FPGA, named Kintex UltraScale XQRKU060, capable of providing ultra-high throughput as well as bandwidth performance, particularly for satellite and space applications.
Type v4 based tensor processing unit market is anticipated to grow with the highest CAGR during the forecast period 2022-2027, attributing to growing demand towards high level computing power chipsets.
APAC Tensor Processing Unit market held the largest share in 2021, due to shift of IT firms towards optimizing enterprise workflows, adoption of advanced technologies like AI and machine learning within organisations, and others.
Increasing demand for autonomous cars or connected vehicles along with growing shift towards predictive analytics and monitoring to boost healthcare or clinical operations is analyzed to significantly drive the Tensor Processing Unit market during the forecast period 2022-2027.
Relevant Report Title:
Graphic Processing Unit (GPU) Market
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