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AI Chipsets Market - Growth, Trends, COVID-19 Impact, and Forecast (2022 - 2027)

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  • 120 Pages
  • August 2022
  • Region: Global
  • Mordor Intelligence
  • ID: 4622791
The AI chipsets market is anticipated to register a CAGR of 39% during the forecast period. The acceptance of AI for improving consumer services and reducing operational costs, the expanding number of AI applications, improving processing power, and the growing adoption of deep learning and neural networks are major market drivers. The outbreak of COVID-19 has negatively impacted the AI chipsets market's supply chain and production. The impact on semiconductor producers was severe. Many companies in the semiconductor supply chain worldwide restricted or even stopped operations due to workforce constraints, causing a bottleneck for semiconductor-dependent end-product companies.

Key Highlights

  • Artificial intelligence (AI) is entering nearly every aspect of consumer electronics. Its uses are growing beyond cellphones to include the automotive industry. This growth is bringing a slew of new prospects to the semiconductor industry. The requirement to process a constantly rising volume of data is a major element influencing the AI chipset market's growth.
  • The computational chipsets created exclusively for AI training and inference tasks are cloud-based artificial intelligence. Cloud technology advancements will provide opportunities for key industry players. The expanding use of cloud-based AI chipsets in many industries, such as IT & telecom and automotive, is expected to drive the demand for AI chipsets. Intel Corporation, Alibaba Group Holding Limited, and NVIDIA Corporation also offer cloud-based AI chipsets.
  • Market competitors are concentrating their efforts on providing innovative cloud-based solutions for managing enormous file storage and company data. For instance, in May 2021, Google launched the next generation of its custom Tensor Processing Units (TPU) AI chips. It is the fourth generation of TPU AI chips, which, according to Google, are twice as fast as the last version. As per the company, these chips are combined in pods with 4,096 v4 TPUs. A single pod provides more than one exaflop of computing power. Google uses custom chips to power many machine learning services. The company has also planned to make the latest generation available to developers as part of the Google Cloud Platform.
  • The AI chipset market’s expansion is further aided by growing investments in Industry 4.0 and the use of smart manufacturing technologies by businesses. In 2020, European businesses, such as manufacturing, automotive, and electronics, invested an estimated USD 182.04 billion in Industry 4.0 technologies, according to PricewaterhouseCoopers (PwC).
  • Companies are using new technologies, such as artificial intelligence, to design new AI chips. For instance, as per a paper published in the journal Nature, in June 2021, Google is using AI and machine learning to help design its next generation of AI chips. According to the company, work that takes months for humans can be completed by AI in under six hours.

Key Market Trends

Consumer Electronics Is Expected to Witness Significant Growth

  • Semiconductor chip shortage halted the production of consumer electronics worldwide due to the COVID-19 pandemic. However, the pandemic created a huge demand for consumer electronics, such as laptops, desktops, and gaming consoles, causing chaos for product companies, manufacturers, and end consumers. Equipment manufacturers focused on meeting this demand from the volatile consumer technology market. The chip shortage and high demand scenario are expected to continue until the next 2 to 3 years, driving the demand for AI chips for consumer electronics.
  • The market will benefit from the increased use of quantum computing technologies to tackle complicated issues and perform analytical computations. For example, Google LLC's Sycamore quantum computer is the fastest computer, capable of completing work in roughly 200 seconds. Artificial intelligence, machine learning, computer vision, Big Data, AR/VR, and other technologies enable quantum computers. The expanding understanding of quantum computing will boost the demand for AI chipsets, thus boosting the industry's growth.
  • AI technologies have been deployed in various industries, including automotive and manufacturing, to streamline processes. The industry may benefit from manufacturers' focus on enhanced AI-based solutions during the pandemic. For example, in May 2020, Nvidia Corporation updated its EGX Edge AI platform by launching new devices, namely, the EGX Jetson Xavier NX and EGX A100.
  • The consumer electronics category is likely to occupy a major proportion of the AI chipset market during the forecast period. Various electronic devices, such as tablets and smartphones, are in high demand in the market. The industry's top essential manufacturers, such as Samsung, are using AI technology to enhance and offer highly personalized products.
  • The AI chipsets market is being driven by the increasing need for high-speed computer processors and increasing demand for better customer services and lower operating costs. The industry is being restrained by a shortage of experienced labor and a lack of standards and protocols.

Asia-Pacific Is Anticipated to Witness Significant Growth

  • The Asia-Pacific market is projected to grow significantly due to emerging economies like South Korea, India, and China. The increased acceptance of AI-based solutions will support the market’s healthy expansion in the region. As part of its AI strategy to deploy AI applications across many industries in 2018, Singapore's government established an AI Ethics Advisory Council. The Asia-Pacific market is projected to be driven by the robust startup ecosystem.
  • Several government efforts in China will also help boost the country's market growth. For example, in July 2017, China's State Council announced the "New Generation Artificial Intelligence Development Plan" to expand the domestic AI industry to USD 150 billion by 2030.
  • The integration of voice commands, enhancement of photography experience, gathering and sorting relevant data based on previous searches, and other applications of AI chipsets in consumer electronics, such as smartphones, tablets, and laptops, resulted in the high adoption of AI chipsets.
  • The region is home to the world's largest smartphone manufacturers and semiconductor companies. China, Japan, Taiwan, and South Korea account for roughly 80% of smartphone manufacturers worldwide. The greatest population has led to increased smartphone usage, which is likely to drive market growth.
  • Several market players in the region are at the forefront of developing and producing AI chips. For instance, in August 2021, Baidu, a Chinese tech giant, started mass-producing second-generation Kunlun AI chips to become a major player in the chip industry. According to Baidu, the new generation of Kunlun AI chips are produced using 7 nm process technology, with computational capability 2-3 times better than the previous generation.

Competitive Landscape

Though some small and large global companies have influenced the market, the AI chipsets market is expected to be consolidated. The market is still in its early stages of development. Some of the prominent participants in the current industry include Advanced Micro Devices Inc. (AMD), Amazon Web Services Inc., Graphcore Ltd, and Huawei Technologies Co. Ltd. To obtain leading positions in the AI chipsets market, these players are engaged in competitive strategic advancements, such as collaborations, new product innovations, and market expansions.
  • September 2021 - Chipset vendors are actively forging partnerships to increase their capabilities, recognizing the relevance of edge-based NLP and ambient sound processing. Qualcomm, for example, partnered with notable NLP businesses, such as Audio Analytics and Hugging Face. CEVA, a chipset IP company, partnered with Fluent.ai to bring multilingual voice recognition to low-power audio devices. Syntiant and Renesas teamed up to create a multimodal AI platform that blends deep learning-based visual and audio processing.
  • August 2020 - An Edge AI company, Kneron, announced the debut of its newest bespoke chip, the Kneron KL 720 SoC, following a USD 40 million Series A financing. The company claims that its KL 720 is four times more energy-efficient than Google's Coral Edge TPU at executing the MobileNetV2 image recognition benchmark than Intel's latest Movidius CPUs. It also includes several new audio recognition advancements for Kneron, which will allow devices that utilize its chips to bypass the conventional wake words on other chips and have immediate interactions with the device.

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Table of Contents

1.1 Study Assumptions and Market Definition
1.2 Scope of the Study
4.1 Market Overview
4.2 Industry Attractiveness - Porter's Five Forces Analysis
4.2.1 Threat of New Entrants
4.2.2 Bargaining Power of Buyers
4.2.3 Bargaining Power of Suppliers
4.2.4 Threat of Substitute Products
4.2.5 Intensity of Competitive Rivalry
4.3 Industry Value Chain Analysis
4.4 Assessment of the Impact of COVID-19 on the Industry
5.1 Market Drivers
5.1.1 Increase in Demand for Autonomous Driving Technology
5.1.2 Growth in Edge Analytics for IoT Application
5.2 Market Restraints
5.2.1 Complexity in Design and AI Interface
6.1 Component
6.1.1 Central Processing Unit (CPU)
6.1.2 Graphics Processing Unit (GPU)
6.1.3 Neural Network Processor (NNP)
6.1.4 Other Components
6.2 Application
6.2.1 Consumer Electronics
6.2.2 Autmotive
6.2.3 Healthcare
6.2.4 Automation and Robotics
6.2.5 Other Applications
6.3 Geography
6.3.1 North America
6.3.2 Europe
6.3.3 Asia-Pacific
6.3.4 Latin America
6.3.5 Middle-East
7.1 Company Profiles
7.1.1 Advanced Micro Devices Inc. (AMD)
7.1.2 Amazon Web Services Inc.
7.1.3 Xilinx Inc.
7.1.4 Graphcore Ltd
7.1.5 Huawei Technologies Co. Ltd
7.1.6 IBM Corporation
7.1.7 Intel Corporation
7.1.8 NVIDIA Corporation
7.1.9 Micron Technology Inc.
7.1.10 Samsung Semiconductor (Samsung Electronics Co. Ltd)

Companies Mentioned

A selection of companies mentioned in this report includes:

  • Advanced Micro Devices Inc. (AMD)
  • Amazon Web Services Inc.
  • Xilinx Inc.
  • Graphcore Ltd
  • Huawei Technologies Co. Ltd
  • IBM Corporation
  • Intel Corporation
  • NVIDIA Corporation
  • Micron Technology Inc.
  • Samsung Semiconductor (Samsung Electronics Co. Ltd)