The AI Chipsets Market is segmented by Component (Central Processing Unit (CPU), Graphics Processing Unit (GPU), and Neural Network Processor (NNP)), by Application (Consumer Electronics, Automotive, Healthcare, Automation & Robotics), and by Geography.

The artificial intelligence (chipset) market is projected to be valued at US$ 27.6 billion in 2024. It is expected to rise to US$ 287.0 billion by 2034. The demand for artificial intelligence chipsets is expected to grow at a CAGR of 26.4% over the forecast period.

Category-wise Insights

Country-wise Insights

The AI chip market size is projected to grow from USD 31.6 billion in the current year to USD 846.85 billion by 2035, representing a CAGR of 34.84%, during the forecast period till 2035

Artificial Intelligence Chipsets Market size was valued at USD 27.36 Billion in 2024 and is projected to reach USD 152.63 Billion by 2031, growing at a CAGR of 26.44% from 2024 to 2031.

Global Artificial Intelligence Chipsets Market Drivers

Fast Growth in AI Applications: The need for AI chipsets is being driven by the widespread use of AI in a number of industries, including healthcare, automotive, finance, retail, and manufacturing. Artificial intelligence (AI) is finding widespread use in fields like robotics, autonomous driving, image identification, natural language processing, and predictive analytics. As a result, AI chip makers are facing enormous market opportunities.

Growing Need for Edge Computing: Real-time processing, lower latency, and bandwidth optimization are driving demand for edge computing, which processes data closer to the source or device than in centralized data centers. AI chipsets designed with edge computing in mind facilitate the effective integration of AI applications into gadgets like drones, IoT devices, autonomous cars, and smartphones.

Developments in AI Hardware Acceleration: The performance, energy efficiency, and scalability of AI are being enhanced by hardware acceleration technologies like neural processing units (NPUs), application-specific integrated circuits (ASICs), graphical processing units (GPUs), and field-programmable gate arrays (FPGAs). When it comes to performance, AI chipsets made especially for AI workloads are superior to standard CPU-based solutions.

Demand for AI in Data Centers and Cloud Computing: To increase the productivity of AI training and inference jobs and to speed up workloads, data centers and cloud computing providers are investing in AI chipsets. AI chipsets with high performance, scalability, and power efficiency that are tailored for data center and cloud environments make large-scale AI deployment possible.

Snapshot img

Artificial Intelligence (AI) Chips Market Size 2025-2029

The artificial intelligence (ai) chips market size is forecast to increase by USD 902.65 billion, at a CAGR of 81.2% between 2024 and 2029.

The market is experiencing significant growth, driven by the increasing focus on developing specialized chips for AI applications in smartphones. The convergence of AI and Internet of Things (IoT) technologies is also fueling market expansion, as more devices require advanced processing capabilities for machine learning and deep learning algorithms. However, the dearth of technically skilled workers for AI chips development poses a substantial challenge to market participants. Companies must invest in training and recruitment efforts to address this talent gap and ensure the timely release of innovative AI chip solutions. Effective navigation of this competitive landscape requires strategic planning and a deep understanding of the evolving market dynamics. Companies that can successfully address the talent challenge and deliver high-performance AI chips will be well-positioned to capitalize on the growing demand for advanced AI technologies.

What will be the Size of the Artificial Intelligence (AI) Chips Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free SampleThe market continues to evolve, driven by advancements in compute units, memory capacity, and processor architecture. The supply chain for AI chips is intricately linked to manufacturing processes, thermal management, and ethical considerations. The applications of AI chips span various sectors, including autonomous vehicles, machine learning, computer vision, natural language processing, and edge computing. Intellectual property and data annotation play crucial roles in the development of AI chips. Industry verticals, such as healthcare, finance, and manufacturing, are adopting AI chips to enhance business models and improve efficiency. Power efficiency remains a significant concern, leading to the exploration of open-source platforms, FPGA acceleration, and ASIC design. AI chips are integral to data centers, powering cloud computing and high-performance computing applications. GPU computing and tensor cores are popular choices for matrix multiplication and deep learning model training. The market is also witnessing the emergence of neural network processors and proprietary technologies. Price-performance ratio, performance benchmarking, and licensing agreements are essential factors influencing investment strategies. Testing methodologies and standards organizations are working to ensure the reliability and interoperability of AI chips. Privacy concerns and data security are also critical considerations in the evolving AI chips market. In the realm of smart devices, AI chips enable advanced capabilities, such as voice recognition and facial recognition. The ongoing development of AI chips is shaping the future of technology, with continuous innovation and advancements on the horizon.

How is this Artificial Intelligence (AI) Chips Industry segmented?

The artificial intelligence (ai) chips industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. ProductASICsGPUsCPUsFPGAsEnd-userMedia and advertisingBFSIIT and telecommunicationOthersProcessing TypeEdgeCloudEdgeCloudApplicationNature language processing (NLP)RoboticsComputer visionNetwork securityOthersTechnologySystem on chip (SoC)System in package (SiP)Multi chip module (MCM)OthersFunctionTrainingInferenceGeographyNorth AmericaUSCanadaEuropeFranceGermanyItalyUKMiddle East and AfricaUAEAPACChinaIndiaJapanSouth AmericaBrazilRest of World (ROW)

By Product Insights

The asics segment is estimated to witness significant growth during the forecast period.Application-specific integrated circuits (ASICs) are a type of chip that boasts customized instruction sets and libraries, enabling local data processing and parallel algorithm acceleration. ASICs, resembling GPUs, offer superior performance to GPUs and FPGAs in data center applications. However, their non-reconfigurable nature sets them apart, as once an ASIC's function is established, it cannot be altered. The integration of ASICs in cloud-based data centers is fueling market growth. ASIC-based AI chips have gained traction, surpassing GPUs and FPGAs in popularity for data center applications. These chips deliver enhanced performance and speed compared to GPUs, FPGAs, and CPUs. Manufacturing processes and supply chain management are crucial aspects of ASIC production. Thermal management and power efficiency are significant concerns, as ASICs require substantial power to operate. Ethical

The artificial intelligence (AI) chip market is experiencing rapid growth, with projections indicating it will reach close to ** billion U.S. dollars by 2025. This surge reflects the increasing demand for AI technologies across various industries. The market's expansion is driven by advancements in machine learning, deep learning, and generative AI applications, which are reshaping how businesses operate and interact with customers. Nvidia leads the AI chip race Nvidia has emerged as a dominant player in the AI chip market, with its data center revenue skyrocketing in its 2025 fiscal year. The company's graphics processing units (GPUs) are crucial for training and running large language models, including OpenAI's ChatGPT. Nvidia's success helped propel it into the exclusive tech three trillion club, alongside industry giants like Apple and Microsoft. GPU market growth and AI applications The global GPU market, valued at **** billion U.S. dollars in 2024, has caught much of the world’s attention. This growth is largely fueled by the expanding AI market, particularly in machine learning and deep learning applications. The generative AI market is also contributing significantly, with projections suggesting it will reach surpass *** billion U.S. dollars by 2030. These trends underscore the increasing importance of AI chips in powering next-generation technologies and applications.

Artificial Intelligence Chip Market size was valued at USD 30.96 Billion in 2023 and is projected to reach USD 504.01 Billion by 2031, growing at a CAGR of 46.03% during the forecast period 2024-2031.

Artificial Intelligence Chip Market: Definition/ Overview

An Artificial Intelligence (AI) chip is a specialized hardware component designed to efficiently perform tasks related to artificial intelligence, such as machine learning, natural language processing, and computer vision. These chips are engineered to handle complex computations, enabling faster execution of AI algorithms compared to traditional processors. They include various types, such as Graphics Processing Units (GPUs), Application-Specific Integrated Circuits (ASICs), and Field-Programmable Gate Arrays (FPGAs), each optimized for specific AI workloads. By utilizing parallel processing capabilities, AI chips significantly enhance the performance and efficiency of AI applications.

The Artificial Intelligence (AI) Chip Market was valued at USD 52.92 Bn in 2024, and it is projected to reach USD 295.56 Bn by 2030 with the CAGR of 33.2%.

AI Chipset Market size was USD 14.84 Billion in 2022 and is expected to reach a value of USD 306.61 Billion in 2032 and register a revenue CAGR of 40% during the forecast period.

The entire market will rise very closely there It was predicted to USD 4.2 Billion by 2025 to USD 30.2 Billion by 2035, expanding at a CAGR of 21.6% during the forecast time. Electric vehicle (EV) manufacturers are now integrating AI chipsets into their vehicles to improve their autonomation abilities, committing themselves to utilize AI-based sensor fusion systems for improved navigation, and seeking out more AI-based Automotive Software solutions as they work to deploy AI more broadly. Also, new approaches like AI-on-chip, neuromorphic computing, and energy-efficient AI accelerators will lead to more innovations in automotive AI hardware.

Country-wise Insights

Competitive Outlook

Global Artificial Intelligence Chipset Market has experienced tremendous growth in recent years and is poised to continue its strong expansion.

Discover the latest insights from Market Research Intellect's Artificial Intelligence Chipsets Market Report, valued at USD 45.3 billion in 2024, with significant growth projected to USD 100.8 billion by 2033 at a CAGR of 9.8% (2026-2033).

Artificial Intelligence (AI) Chipset Market Outlook

According to our latest research, the global Artificial Intelligence (AI) Chipset market size reached USD 29.8 billion in 2024, demonstrating robust expansion driven by the rapid proliferation of AI-powered applications across industries. The market is expected to maintain a strong growth trajectory, registering a CAGR of 32.1% from 2025 to 2033. By 2033, the AI Chipset market is forecasted to attain a value of USD 356.7 billion. This impressive growth is primarily fueled by the surging demand for high-performance computing, accelerated adoption of AI in edge devices, and ongoing advancements in deep learning and neural network architectures.

One of the primary growth factors propelling the AI Chipset market is the exponential increase in data generation and the corresponding need for advanced analytics. Enterprises across sectors such as healthcare, automotive, and finance are leveraging AI algorithms to extract actionable insights, automate processes, and enhance decision-making. This surge in AI adoption necessitates powerful and efficient chipsets capable of handling complex computations at scale. Furthermore, the proliferation of IoT devices and the emergence of edge computing have accelerated the demand for AI chipsets that can process data locally, reducing latency and improving real-time responsiveness. As a result, chipset manufacturers are investing heavily in R&D to develop innovative architectures tailored for AI workloads, further fueling market growth.

Another significant factor contributing to the expansion of the Artificial Intelligence Chipset market is the increasing integration of AI functionalities in consumer electronics and smart devices. Smartphones, smart speakers, home automation systems, and wearable devices are now equipped with AI-powered features such as voice recognition, image processing, and predictive analytics. This trend has created a massive demand for AI chipsets optimized for low power consumption and high computational efficiency. Moreover, the automotive industry is rapidly embracing AI for applications like autonomous driving, advanced driver assistance systems (ADAS), and in-vehicle infotainment, further amplifying the need for specialized AI hardware. The convergence of AI with 5G connectivity and cloud computing is expected to unlock new use cases, reinforcing the market's upward trajectory.

The evolving regulatory landscape and government initiatives aimed at promoting AI innovation are also playing a pivotal role in shaping the AI Chipset market. Countries across North America, Europe, and Asia Pacific are implementing policies and funding programs to foster AI research and development, enhance digital infrastructure, and ensure cybersecurity. These efforts are encouraging collaborations between academia, industry, and government agencies, resulting in the creation of cutting-edge AI chipsets that meet stringent performance and security standards. However, the market is not without challenges, as issues related to data privacy, ethical AI deployment, and the high cost of advanced chipsets may pose hurdles to widespread adoption. Nonetheless, the overall outlook remains positive, with significant opportunities for growth and innovation.

Regionally, North America continues to dominate the AI Chipset market, accounting for the largest revenue share in 2024, followed closely by Asia Pacific and Europe. The presence of leading technology companies, robust investment in AI research, and a mature digital ecosystem have positioned North America at the forefront of AI hardware innovation. Meanwhile, Asia Pacific is witnessing the fastest growth, driven by rapid industrialization, government support, and the proliferation of AI startups. Europe is also making significant strides, particularly in sectors such as automotive and healthcare. Latin America and the Middle East & Africa are emerging markets with untapped potential, expected to contribute to the global market's expansion in the coming years.

Edge Artificial Intelligence (AI) Chip Market Outlook

The global market size for Edge Artificial Intelligence (AI) Chips was estimated at USD 3.8 billion in 2023 and is projected to reach USD 18.7 billion by 2032, reflecting a compound annual growth rate (CAGR) of 19.6% during the forecast period. This remarkable growth is driven by the increasing demand for real-time processing capabilities, the proliferation of IoT devices, and the need for efficient and low-latency data processing at the edge.

One of the primary growth factors in the edge AI chip market is the rising need for real-time data processing and analytics. Traditional cloud computing models, while powerful, often introduce latency that is unacceptable for applications requiring immediate decision-making. Edge AI chips bring computational power closer to the data source, enabling faster data processing and reduced latency. This is particularly crucial for applications in healthcare, autonomous driving, and industrial automation where split-second decisions are critical.

Another significant growth driver is the exponential increase in connected devices, commonly referred to as the Internet of Things (IoT). As IoT devices continue to proliferate globally, the volume of data generated at the edge of networks is skyrocketing. Edge AI chips are uniquely positioned to handle this influx by enabling localized data processing, reducing the need for bandwidth, and alleviating the load on centralized data centers. This capability not only enhances efficiency but also supports the scalability of IoT ecosystems.

The advancements in AI technologies and algorithms are further propelling the market. Today's edge AI chips are equipped with sophisticated machine learning and deep learning capabilities, enabling them to perform complex tasks such as image and speech recognition, anomaly detection, and predictive maintenance. These advancements are opening up new possibilities across various sectors, from healthcare diagnostics to smart retail solutions, thereby expanding the market's potential.

Regionally, North America is expected to dominate the edge AI chip market, owing to the presence of major technology companies, substantial R&D investments, and early adoption of advanced technologies. Europe and Asia Pacific are also significant markets, with Asia Pacific anticipated to witness the fastest growth. This is driven by rapid industrialization, the growing implementation of smart city projects, and increasing investments in AI and IoT technologies in countries like China, Japan, and South Korea.

Component Analysis

The edge AI chip market is segmented by component into hardware, software, and services. Hardware components, including processors, accelerators, and memory modules, constitute the backbone of edge AI solutions. These hardware components are essential for performing intensive computations directly at the source of data generation. The evolution of specialized AI processors, such as neural processing units (NPUs) and tensor processing units (TPUs), has significantly enhanced the performance and efficiency of edge AI systems.

Software plays a pivotal role in the functionality and versatility of edge AI chips. This segment encompasses AI frameworks, development kits, and runtime environments that enable developers to design, train, and deploy AI models on edge devices. The continual evolution of AI software, with improvements in algorithms and support for a wide range of hardware platforms, is critical for unlocking the full potential of edge AI technology. Additionally, software solutions often incorporate features for model optimization, energy efficiency, and security, which are paramount for edge deployments.

The services component includes consulting, integration, and maintenance services that facilitate the deployment and operation of edge AI solutions. As organizations adopt edge AI technologies, the need for expert guidance and support becomes essential. Service providers offer bespoke solutions tailored to the specific needs of different industries, ensuring seamless integration with existing systems and workflows. Moreover, ongoing maintenance services are vital for optimizing performance, ensuring reliability, and addressing any technical issues that may arise.

The synergy between hardware, software, and services is crucial for the successful deployment of edge AI solutions. Hardware advancements provide the necessary computational power, software optimizes performance and functionality, and services en

Artificial Intelligence (AI) Chipset Market Outlook

The AI chipset market size is projected to grow from USD 10.5 billion in 2023 to an impressive USD 102.3 billion by 2032, at a compound annual growth rate (CAGR) of 29.4%. This market growth can be attributed to the increasing integration of AI across various sectors including healthcare, automotive, and consumer electronics, driven by the rising demand for high-speed data processing and efficient computing capabilities.

The first major growth factor driving the AI chipset market is the rapid advancements in AI technologies such as machine learning, natural language processing, and computer vision. These advancements are facilitating more sophisticated and efficient AI applications, necessitating the development of highly specialized AI chipsets to handle the complex computations involved. For instance, the growing adoption of AI in healthcare for predictive diagnostics and personalized medicine is creating a significant demand for AI chipsets capable of processing large volumes of data at high speeds.

Another critical factor contributing to the expansion of the AI chipset market is the proliferation of smart devices and the Internet of Things (IoT). The integration of AI with IoT devices has led to the creation of smarter and more autonomous systems, requiring advanced chipsets to manage these functionalities. Smart home devices, wearable tech, and autonomous vehicles all rely on AI chipsets for efficient operation, driving the market forward. The increasing investment in AI and IoT by tech giants and startups alike further accelerates this trend, fostering innovation and expanding the market landscape.

Additionally, the rising demand for AI-driven customer experiences in various sectors such as retail and finance is significantly boosting the AI chipset market. Retailers are increasingly leveraging AI for personalized shopping experiences, demand forecasting, and inventory management, while financial institutions utilize AI for fraud detection, credit scoring, and customer service automation. This surge in AI applications requires robust and efficient AI chipsets, spurring market growth. Moreover, the continuous development and deployment of AI technologies by leading global corporations are setting new benchmarks for performance, driving further advancements in AI chipsets.

AI-enabled Cybersecurity Chipsets are becoming increasingly vital in securing digital infrastructures as the integration of AI technologies expands across various sectors. These chipsets are designed to enhance security measures by providing real-time threat detection and response capabilities. With the rise of sophisticated cyber threats, AI-enabled cybersecurity chipsets offer a robust solution by leveraging machine learning algorithms to identify and mitigate potential vulnerabilities. As organizations continue to adopt AI-driven systems, the demand for these specialized chipsets is expected to grow, ensuring the protection of sensitive data and maintaining the integrity of critical operations.

The AI chipset market also exhibits strong regional growth trends. North America, with its technological prowess, leads the market, followed by Asia Pacific, which is witnessing rapid adoption of AI technologies across various industries. Europe is also showing significant growth, driven by advancements in AI research and development. The Middle East and Africa, along with Latin America, are gradually catching up, leveraging AI to boost their respective economic sectors. This regional diversification not only expands the market reach but also enriches the global AI ecosystem, fostering innovation and competition.

Component Analysis

The AI chipset market is segmented by component into hardware, software, and services. The hardware segment, which includes processors, memory, and network devices, holds a significant market share. The growing demand for high-performance processors like GPUs, TPUs, and FPGAs is driving this segment. These processors are essential for handling the intensive computational tasks associated with AI applications. For instance, GPUs are widely used in training deep learning models, while TPUs are optimized for inference tasks in AI applications. The continuous advancements in semiconductor technologies further enhance the performance capabilities of these processors, contributing to the growth of the hardware segment.

The software segment encompa

The size of the Artificial Intelligence (AI) Chipsets Market market was valued at USD 8.14 USD billion in 2023 and is projected to reach USD 21.00 USD billion by 2032, with an expected CAGR of 14.5% during the forecast period. Artificial Intelligence (AI) chipsets are specialized processors designed to handle complex AI tasks more efficiently than traditional processors. These chipsets accelerate machine learning, deep learning, and neural network computations, enabling faster data processing and decision-making. There are several types, including Graphics Processing Units (GPUs), Tensor Processing Units (TPUs), Field Programmable Gate Arrays (FPGAs), and Application-Specific Integrated Circuits (ASICs). Key features include high parallel processing capability, low power consumption, and the ability to handle large datasets in real time. AI chipsets are used in applications like autonomous vehicles, robotics, healthcare diagnostics, natural language processing, and smart devices, enhancing the performance and efficiency of AI-driven solutions across various industries. Key drivers for this market are: Surging Demand for Electric Vehicles is Driving the Market Growth. Potential restraints include: Lack of Skilled AI Workforce to Inhibiting the Market . Notable trends are: Growing Demand for Energy Efficient Simulating Lighting Solutions to Emerge as Leading Market Trend.

Artificial Intelligence Chipsets Market Outlook

The global Artificial Intelligence Chipsets market size was valued at approximately USD 15.5 billion in 2023 and is projected to reach an impressive USD 127.2 billion by 2032, exhibiting a robust compound annual growth rate (CAGR) of 26.5% during the forecast period. This significant growth is largely driven by the increasing demand for AI-driven technologies across various sectors such as healthcare, automotive, and consumer electronics, as well as the continual advancements in AI research and applications. The market is poised to expand rapidly as industries increasingly integrate AI solutions to enhance efficiencies, reduce costs, and deliver innovative products and services.

A key growth factor for the AI chipsets market is the escalating demand for intelligent devices and applications that require high computational power and efficiency. Industries such as consumer electronics are increasingly adopting AI chipsets to enable smarter, more interactive devices, resulting in enhanced user experiences. For instance, smartphones, smart speakers, and various wearable devices are now equipped with AI capabilities that rely heavily on these advanced chipsets. Additionally, the rise of smart homes and IoT devices further contributes to the demand for AI chipsets, as these technologies require seamless connectivity and processing capabilities provided by AI-optimized hardware.

Another significant driver of market growth is the ongoing advancements in machine learning and deep learning algorithms, which necessitate the deployment of AI chipsets capable of handling complex computations. These technologies are being rapidly adopted across industries, including automotive, where AI chipsets are crucial for the development of autonomous vehicles and advanced driver-assistance systems (ADAS). The healthcare sector is also leveraging AI chipsets to enhance diagnostics, personalized medicine, and patient care. The ability of AI chipsets to process vast amounts of data swiftly and accurately is a critical component in the successful implementation of AI technologies across these diverse fields.

The increasing investments in AI research and development by governments and private organizations are further bolstering the AI chipsets market. These investments are aimed at fostering innovation and creating a robust AI ecosystem that supports the development and deployment of AI technologies. In particular, tech giants and startups alike are focusing on developing AI chipsets that cater to specific industry needs, driving customization and innovation in this space. The competition to create more efficient, powerful, and versatile AI chipsets is resulting in rapid technological advancements, contributing significantly to market growth.

From a regional perspective, North America currently holds the largest share of the AI chipsets market, thanks to the presence of major technology companies and a strong focus on research and development activities. However, the Asia Pacific region is expected to witness the quickest growth during the forecast period, fueled by the rapid adoption of AI technologies in emerging economies such as China and India, as well as substantial investments in AI development by regional governments. These dynamics highlight the global nature of the AI chipsets market and the diverse factors contributing to its growth.

Chip Type Analysis

The AI chipsets market is segmented by chip types, including Graphics Processing Units (GPUs), Application-Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), Central Processing Units (CPUs), and others. GPUs are leading this segment due to their high parallel processing capabilities, which make them ideal for handling the large volumes of data required in AI applications. The demand for GPUs is notably high in sectors such as gaming, automotive, and data centers where complex simulations and high-performance computations are crucial. This demand is further amplified by AI frameworks that rely on GPU acceleration to process deep learning algorithms efficiently.

ASICs are gaining traction in the AI chipsets market, especially for applications that require high performance and low power consumption. These chips are custom-built for specific AI tasks, allowing them to deliver unparalleled efficiency and speed. ASICs are particularly prevalent in data centers and cloud computing environments where energy efficiency and processing speed are paramount. As AI applications continue to scale, the need for ASICs is expected to grow, driven by the demand for cost-effectiv

Discover the latest insights from Market Research Intellect's Cloud AI Chipsets Market Report, valued at USD 12.5 billion in 2024, with significant growth projected to USD 35 billion by 2033 at a CAGR of 15.7% (2026-2033).

The size of the AI Chipsets market was valued at USD XX Million in 2023 and is projected to reach USD XXX Million by 2032, with an expected CAGR of 39.00% during the forecast period.The term AI accelerators or AI processors for AI chipsets may be used to describe specialized hardware parts specifically made for the acceleration of AI workloads. Generally, those traditional CPUs and GPUs cannot cope well with the demanding computational needs for AI tasks. Being dedicatedly designed for optimizing AI algorithm processing, AI chipsets can allow faster, much more efficient computations related to artificial intelligence. They rely on parallel processing and dedicated architectures to work with the highly mathematical computations. These are required to implement deep learning, computer vision, and natural language processing applications. They generally lead to a significant improvement in the performance of AI applications, which support fast real-time inferences as well as training on large datasets. Besides such applications as autonomous vehicles, smart cities, healthcare, and financial services, AI chipsets are the motive forces of the development of intelligent systems-analysing large volumes of data as they settle to make informed decisions and drive innovation. Recent developments include: May 2022 - Intel introduced two new deep-learning processors for instruction and inference: Habana Gaudi2 and Habana GrecoTM. These innovative processors fill a market void by offering clients high-efficiency, high-performance, deep learning computing options for simultaneous training applications and inference installations in the data center and also reducing the AI obstacle to the entrance to businesses of all sizes., February 2022 - Celestial AI, an AI accelerator company with a proprietary hardware and software platform for machine learning chipsets, announced a USD 56 million Series A investment. The new capital will be used for product development and strategic supplier engagements, including Broadcom., January 2022 - Nvidia and AMD announced that the U.S. government has put in place new restrictions to cut China and Russia off from high-end AI chips., March 2021 - Intel collaborated with the Central Board of Secondary Education (CBSE), aiming to introduce the 'AI For All' initiative to create a basic understanding of artificial intelligence across various industry verticals in India.. Key drivers for this market are: Increase in Demand for Autonomous Driving Technology, Growth in Edge Analytics for IoT Application. Potential restraints include: Complexity in Design and AI Interface. Notable trends are: Consumer Electronics Is Expected to Witness Significant Growth.

Global artificial intelligence chip market to reach $164.07 billion by 2029 at 41.6% CAGR, driven by growing demand for smart homes, cities, and intelligent devices.