High Demand for Deep Learning Chipsets Due to Large Volumes of Data Sets

The artificial intelligence (AI) wave has captivated the attention of stakeholders operating in an array of industry verticals. Evolving from neural networks to present-day deep learning architectures, AI has come a long way. The soaring demand for deep learning across a host of industrial sectors, including healthcare, aerospace & defense, automotive, and consumer electronics has played an imperative role in boosting the demand for deep learning chipsets in recent years – a trend that is likely to play a key role in the expansion of the deep learning chipset market in the coming years. The uptake of deep learning chipsets is primarily driven by high volumes of data required to run deep learning and machine learning models.

In the current scenario, technological advancements are enabling the development of powerful and cutting-edge deep learning chipsets. Deep learning chipsets are increasingly being used in a range of consumer electronic items, including augmented reality/virtual reality (AR/VR) headsets, smart speakers, smartphones, and a host of other devices that require AI processing. Several companies operating in the deep learning chipset market are focusing on introducing innovations in fabrication and deep learning chipset designs to enable the production of state-of-the-art devices.

Moreover, progress in the AI domain is expected to streamline and improve a machine’s capacity to carry out cognitive functions linked with humans, including reasoning, learning, and perceiving. Due to these factors, along with widening applications of AI, the deep learning chipset market is expected to reach a value of ~US$ 35.2 Bn by the end of 2027, a five-fold growth from ~US$ 6.4 Bn in 2019.

deep learning chipset market infographic

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Companies to Employ Deep Learning Chips in Next-generation Consumer Devices

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.

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.

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Advancements in GPUs Mark Beginning of New Era in Global Market

The first-generation of graphic processing units were primarily developed for desktop gaming. However, the trend witnessed a tectonic shift, particularly in the last decade, as new iterations of graphic processing units were more inclined toward high-resolution images and AI. The significant demand for graphic processing units can be largely attributed to significant progress in low-power technology.

For instance, the Google Brain project, which was initiated in 2011, analyzed millions of images from platforms, such as YouTube to recognize cats. Due to significant progress in technology, the generation of graphical processing units could integrate exceptional graphical capabilities with computational processing components. Furthermore, with continual demand for higher graphical requirements, owing to large volumes of high-resolution images, stakeholders in the deep learning chipset market developed deep learning chipsets with improved functions and capabilities. The demand for graphical processing units was largely influenced by the mounting need for advanced graphical processing. Additionally, as deep learning tasks involve highly complex mathematical computations, the demand for graphics processing units grew at an impressive pace. Within the deep learning chipset market, the graphics processing units (GPUs) segment is estimated to reach a value of ~US$ 2.4 Bn and account for a market share of ~31% in 2020.

The deep learning chipset market was largely dominated by NVIDIA for a substantial period. However, in recent times, a large number of companies have turned their attention toward the development of highly advanced deep learning chipsets. For instance, in July 2018, IBM launched a new deep learning chipset, which was predominantly designed to perform high-precision learning as well as low-precision inference.

deep learning chipset market segmentation

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Analysts’ Viewpoint

The deep learning chipset market is expected to grow at an impressive CAGR of ~24% during the forecast period. The growth of the market can be largely attributed to the rising demand for high graphical requirements in a range of consumer electronic goods, including smartphones, AR/VR headsets, etc. The deep learning chipset market was largely dominated by NVIDIA for several years. However, a flurry of startups to prominent brands, including IBM and Intel Corporation are offering cutting-edge deep learning chipsets. Stakeholders should align their operations with evolving industry requirements and leverage advancements in AI to offer next-generation deep learning chipsets.  

Deep Learning Chipset Market: Overview

  • According to Transparency Market Research’s latest research report on the global deep learning chipset market for the historical period of 2017–2018 and the forecast period of 2019–2027, the rising demand for deep learning chipsets for use in various applications is expected to boost the deep learning chipset market during the forecast period
  • In terms of revenue, the deep learning chipset market is estimated to reach a value of ~US$ 35.2 Bn by 2027, expanding at a CAGR of ~24% during the forecast period

High Increase in Data Volume and Significantly Improved Algorithms: A Key Driver

  • Movie DVDs, music CDs, and web pages have been adding to the world’s inventory of digitally encrypted information for more than a decade. Over the past few years, the amount of information generated has increased drastically.
  • A significant percentage of digital data in the current world has been produced over the past two years alone. Moreover, increasing adoption of IoT (Internet of Things) to connect billions of new devices and data streams is expected to present new challenges in terms of security.
  • Furthermore, there is an expected increase in demand for the deep learning for implementation of advanced security measures
  • As high increase in data volumes and significantly improved algorithms of deep learning methods are expected to improve IoT security, they are anticipated to contribute to the growth of the deep learning chipset market

Deep Learning for Consumer Application a Key Trend in Deep Learning Chipset Market

  • The global deep learning chipset market is currently witnessing significant growth, due to the capability of these chipsets to develop deep domain insight and user input for various industries. Deep learning is a kind of machine learning algorithm, which makes deep learning possible via enhanced interaction between systems and humans, improving the organizational capabilities for client engagement and satisfaction.
  • Deep learning is expected to drive the adoption of artificial intelligence (AI) in various enterprises. It is a proven fact that deep learning is the key driver and the most significant approach toward artificial intelligence (AI).
  • Increasingly sophisticating video investigation is revolutionizing the global security sector and thereby, helping fight crime. Development of the artificial intelligence (AI) in general— and toward deep learning, in particular— would have remarkable significance in relation to proactive security systems, at least, in video surveillance systems in the near future.
  • These factors are expected to drive the deep learning chipset market during the forecast period

Long-term Planning and Algorithmic Data Manipulation Unattainable for Deep Learning Models

  • Several applications in the current scenario are out of reach for the deep learning technique, even after providing a large volume of human-annotated data
  • In general, anything that requires rational-like algorithmic data manipulation, long-term planning, and programming is currently unobtainable for deep learning models
  • Above factors are anticipated to hinder the deep learning chipset market during the forecast period

Deep Learning Chipset Market: Competition Landscape

  • Detailed profiles of providers of deep learning chipsets have been provided in the report to evaluate their financials, key product offerings, recent developments, and strategies
  • Key players operating in the 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
    • Alphabet Inc.

Deep Learning Chipset Market: Key Developments

  • Key providers of deep learning chipsets are focusing on new product development and technological advancements. Some of the key developments in the deep learning chipset market are as follows:
    • In August 2019, Huawei announced the launch of two new AI chips i.e. Ascend 910 and Ascend 310. Ascend 910 delivers 256 TeraFLOPS. For integer precision calculations (INT8), it delivers 512 TeraOPS, which consumes much lower power.
    • In May 2019, Hailo introduced Hailo-8 chips, the first of its deep learning processors for deep learning applications in devices such as drones, smartphones, smart cameras, autonomous cars, and augmented reality platforms
    • In June 2018, NVidia Corporation announced release of a new chip, which consists of six processing units, including a 512-core NVidia Volta Tensor Core GPU, an eight-core Carmel Arm64 CPU, a dual NVidia deep learning accelerator, and image, vision, and video processors. The new chip is 10 times more energy efficient and 20 times more powerful than its predecessor.
  • In the report on the deep learning chipset market, we have discussed individual strategies, followed by company profiles of providers of deep learning chipsets. The ‘Competition Landscape’ section has been included in the report to provide readers with a dashboard view and company market share analysis of key players operating in the deep learning chipset market.

Deep Learning Chipset Market – Scope of the Report

A new study on the global deep learning chipset market was published by Transparency Market Research (TMR). It presents a wealth of information on key market dynamics, including drivers, market trends, and challenges as well as structure of the deep learning chipset market. TMR’s study offers valuable information about the global market, to illustrate how market growth would discern during the forecast period i.e. 2019–2027.

Key indicators of market growth, which include value chain analysis as well as supply chain analysis, and compounded annual growth rate (CAGR), are elucidated in TMR’s study in a comprehensive manner. This data can help readers interpret the quantitative growth aspects of the deep learning chipset market during the forecast period.

An extensive analysis of leading market players’ business strategies has also been featured in TMR’s study on the deep learning chipset market. This can help readers understand key factors driving the deep learning chipset market. In this study, readers can also find specific data on qualitative and quantitative growth avenues for the deep learning chipset market, which would guide market players in making apt decisions in the near future.

Key Questions Answered in TMR’s Study of Deep Learning Chipset Market

  • What would be the Y-o-Y growth trend of the deep learning chipset market between 2019 and 2027?
  • What is the influence of the changing trend in technologies on the deep learning chipset market?
  • Would North America continue to remain the most profitable regional market for providers of deep learning chipsets in the near future?
  • Which factors would hinder the deep learning chipset market during the forecast period?
  • Which are the leading companies operating in the deep learning chipset market?

Research Methodology

A unique research methodology has been utilized by TMR to conduct comprehensive research on the deep learning chipset market and arrive at conclusions on future growth prospects for the market. This research methodology is a combination of primary and secondary research, which helps analysts warrant the accuracy and reliability of the conclusions drawn.

Secondary research sources referred to by analysts during production of the report on the deep learning chipset market include statistics from company annual reports, SEC filings, company websites, World Bank database, investor presentations, regulatory databases, government publications, and market white papers. Analysts have also interviewed senior managers, product portfolio managers, CEOs, VPs, and market intelligence managers, who have contributed to the production of TMR’s study on the deep learning chipset market, as a primary research source.

These primary and secondary sources provided exclusive information during interviews, which served as a validation from leading players operating in the deep learning chipset market. Access to an extensive internal repository as well as external proprietary databases allowed this report to address specific details and questions about the deep learning chipset market with accuracy. The study also uses a top-down approach to assess the numbers for each segment and a bottom-up approach to counter-validate them. This has helped in making TMR’s estimates on future prospects for the deep learning chipset market more reliable and accurate.

Deep Learning Chipset Market – Segmentation

TMR’s study on the deep learning chipset market includes segmentation based on type, compute capacity, end user, and region. Changing market trends and other crucial market dynamics associated with segments of the deep learning chipset market are discussed in detail.

Type

  • Graphics Processing Units (GPUs)
  • Central Processing Units (CPUs)
  • Application Specific
  • Integrated Circuits (ASICs)
  • Field Programmable Gate Arrays (FPGAs)
  • Others

Compute Capacity

  • Low
  • High

End User

  • Consumer Electronics
  • Automotive
  • Industrial
  • Healthcare
  • Aerospace & Defense
  • Others

Region

  • North America
  • Europe
  • Asia Pacific
  • Middle East & Africa
  • South America

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Deep Learning Chipset Market

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