Deep Learning Chipset Market Report 2024

This Deep Learning Chipset industry report covers market characteristics, size and growth, segmentation, regional and country breakdowns, competitive landscape, market shares, trends and strategies for this market. It traces the market’s historic and forecast market growth by geography.

The deep learning chipset market size has grown exponentially in recent years. It will grow from $7.43 billion in 2023 to $9.47 billion in 2024 at a compound annual growth rate (CAGR) of 27.4%. The growth during the historical period can be attributed to several factors such as the increasing need to manage large volumes of data efficiently, the rise of cloud computing, the development of AI-driven applications, government investments, and advancements in AI frameworks and libraries.

The deep learning chipset market size is expected to see exponential growth in the next few years. It will grow to $25.17 billion in 2028 at a compound annual growth rate (CAGR) of 27.7%. The projected growth during the forecast period can be attributed to several factors such as the expansion of autonomous systems, the emergence of 5G technology, a heightened focus on energy efficiency, increasing adoption of IoT, and rising demand for automobiles. Key trends expected to shape this period include advancements in neuromorphic computing, the customization of AI hardware, a focus on energy-efficient AI solutions, progress in AI-powered healthcare devices, and the adoption of cloud-based technologies.

The deep learning chipset market is expected to benefit from the growing adoption of Internet of Things (IoT) devices. IoT devices, which are equipped with sensors, software, and other technologies for internet connectivity and data exchange, are expanding due to declining sensor costs, advancements in AI, increased demand for automation, and the proliferation of smart devices and 5G networks. These devices generate large volumes of data essential for training deep learning models, which are processed efficiently by deep learning chipsets to boost AI capabilities. These chipsets are designed for high-speed processing, enabling real-time analysis and decision-making crucial for various applications. For instance, in September 2022, Ericsson reported that global IoT connections reached 13.2 billion in 2022 and are projected to grow by 18% to 34.7 billion by 2028. This increase in IoT adoption is expected to drive the demand for deep learning chipsets.

Key players in the deep learning chipset market are developing advanced products such as deep-learning processors to improve computational efficiency and processing speeds for complex AI tasks. Deep learning processors are engineered to accelerate tasks related to deep learning and leverage neural networks with multiple layers for data analysis. For example, in May 2022, Habana Labs Ltd., a US-based manufacturer of AI processors, introduced the Habana Gaudi2 Training and Habanab Greco, its second-generation deep learning processors. The Habana Gaudi2 offers up to 2x throughput compared to Nvidia’s A100 GPU and features 24 tensor processor cores, 96 GB of HBM2E memory, and 24 100 Gigabit RDMA connections. Habanab Greco is expected to deliver significant speed improvements over its predecessor, paralleling advancements seen in Gaudi2.

In April 2024, Microchip Technology Inc., a US-based provider of embedded control solutions, acquired Neuronix AI Labs for an undisclosed amount. This acquisition will enable Microchip to develop more cost-effective and scalable edge computing solutions for computer vision, leveraging Neuronix’s expertise. Additionally, it will enhance Microchip’s AI and machine learning processing capabilities on its field programmable gate arrays (FPGAs), facilitating AI deployment on configurable FPGA hardware for non-FPGA professionals. Neuronix AI Labs specializes in deep learning chipsets and optimization technologies.

Major companies operating in the deep learning chipset market are Apple Inc., Microsoft Corporation, Samsung Electronics Co. Ltd., Huawei Technologies Co. Ltd., Amazon Web Services Inc., Intel Corporation, International Business Machines Corporation, Qualcomm Technologies Inc., Micron Technology Inc., NVIDIA Corporation, Advanced Micro Devices Inc., Texas Instruments Incorporated, MediaTek Inc., NXP Semiconductors, INSPUR Co. Ltd., Cambricon Technologies, Rockchip, Cerebras Systems Inc., Mythic, Habana Labs Ltd., BrainChip Inc.

North America was the largest region in the deep learning chipset market in 2023. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the deep learning chipset market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

The countries covered in the deep learning chipset market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

A deep learning chipset is a specialized hardware component engineered to efficiently perform the complex computations required by deep learning algorithms. These chipsets are optimized for large-scale matrix operations and high-volume data processing essential for neural network training and inference.

The primary types of deep learning chipsets include graphics processing units (GPUs), central processing units (CPUs), application-specific integrated circuits (ASICs), and field-programmable gate arrays (FPGAs). GPUs, in particular, are specialized processors designed to accelerate graphics rendering and complex calculations, which is crucial for deep learning tasks that benefit from parallel processing. They come with various technologies such as system-on-chip (SOC), system-in-package (SIP), and multi-chip modules, and are available in different compute capacities, including high and low performance. These chipsets are utilized across a range of industries, including healthcare, automotive, retail, banking, financial services, insurance (BFSI), manufacturing, telecommunications, energy, and others.

The deep learning chipset market research report is one of a series of new reports that provides deep learning chipset market statistics, including the deep learning chipset industry global market size, regional shares, competitors with the deep learning chipset market share, detailed deep learning chipset market segments, market trends, and opportunities, and any further data you may need to thrive in the deep learning chipset industry. These deep-learning chipset market research reports deliver a complete perspective of everything you need, with an in-depth analysis of the current and future scenarios of the industry.

The deep learning chipset market consists of revenues earned by entities by providing services such as model training acceleration, inference processing, support for diverse algorithms, and hardware optimization. The market value includes the value of related goods sold by the service provider or included within the service offering. The deep learning chipset market also includes sales of tensor processing units (TPUs), neural processing units (NPUs), and specialized AI accelerators. Values in this market are ‘factory gate’ values, that is, the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors, and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD, unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.


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