Primary Catalyst Driving Machine Learning Chip Market Evolution in 2025: Surge In Cybersecurity Threats Fuels Demand For Machine Learning Chips Driver

What market dynamics are playing a key role in accelerating the growth of the machine learning chip market?
The escalation in cyberoffenses is projected to fuel the expansion of the machine learning chip market. A cyberoffense encompasses any aggressive act aimed at compromising computer information systems, networks, structures, or individual devices with purposes to gather, interrupt, refuse, degrade, or annihilate information systems resources or data. Machine learning chips play a significant role in cybersecurity by facilitating the application of machine learning algorithms to incessantly evaluate data, recognize patterns, and make precise forecasts to alleviate probable cyber onslaughts. For example, the Australian Cyber Security Centre reported in February 2023 that the cybercrime incidents that occurred in 2022 amounted to 76,000, which is a 13% increase from the previous year. Additionally, the Anti-Phishing Working Group, a US-based institution, reported in June 2022 that APWG recorded a sum of 1,025,968 phishing offenses in the initial 2022 quarter, noting a 15% increment from the last quarter of 2021 when 888,585 offenses were reported. Consequently, the surge in cyberoffenses is spurring the advancement of the machine learning chip market.

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How will the growth rate of the machine learning chip market shape industry trends by 2034?
In recent times, there has been a significant increase in the size of the machine learning chip market. It is projected to expand from $21.12 billion in 2024 to a whopping $28.97 billion in 2025, showcasing a compound annual growth rate (CAGR) of 37.2%. The remarkable growth during the historical period is notably due to the surge in big data analytics, the escalating adoption of cloud services, the appearance of edge computing, the widespread use of AI applications across different sectors, and the expedited growth of IoT devices.

The size of the machine learning chip market is anticipated to witness a significant climb in the near future. It is projected to reach a market size of $103.35 billion by 2029, with a compound annual growth rate (CAGR) of 37.4%. The projected growth in this period can be ascribed to factors such as the integration of AI in edge devices, increased complexity of AI algorithms, a growing emphasis on energy efficiency, widened range of AI applications, and a worldwide surge for autonomous systems. Prominent emerging patterns during this period encompass technological partnerships and collaborations, investment in AI-related research and development, progress in AI technologies, initiatives toward open source hardware, and an emphasis on customization and specialization.

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What trends are poised to drive the future success of the machine learning chip market?
The machine learning chip market is dominated by leading companies that are constantly innovating and creating advanced products like system-on-chips (SoCs) to maintain a competitive advantage. A system-on-chip, commonly known as an SoC, is an integrated circuit containing all elements of a computer or other system on a single chip. Silicon Labs, a semiconductor production company based in the UK, is an example of this. In January 2022, the company released new AI/ML chips and a toolkit specially designed for the edge to facilitate the integration of artificial intelligence (AI) and machine learning (ML) at the IoT edge. Its newly launched wireless SoC incorporates an AI and ML accelerator, a wireless radio, ultra-low-power features, and is also compatible with IP-based connectivity protocols like Matter and Zigbee.

Which primary segments of the machine learning chip market are driving growth and industry transformations?
The machine learning chip market covered in this report is segmented -

1) By Chip Type: Graphics Processing Unit (GPU), Application-Specific Processor (ASIC), Field Programmable Gate Array (FPGA), Central Processing Unit (CPU), Other Chips
2) By Technology: System-On-Chip (SoC), System-In-Package, Multi-Chip Module, Other Technologies
3) By Industry Vertical: Banking, Financial Services, And Insurance (BFSI), IT And Telecom, Media And Advertising, Retail, Healthcare, Automotive, Other Industry Verticals

Subsegments:
1) By Graphics Processing Unit (GPU): Dedicated GPUs, Integrated GPUs
2) By Application-Specific Integrated Circuit (ASIC): Custom ASICs For AI, General-Purpose ASICs
3) By Field Programmable Gate Array (FPGA): Configurable FPGAs, Embedded FPGAs
4) By Central Processing Unit (CPU): Multi-Core CPUs, High-Performance CPUs
5) By Other Chips: Neuromorphic Chips, Digital Signal Processors (DSP), Tensor Processing Units (TPU)

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Which geographical regions are pioneering growth in the machine learning chip market?
North America was the largest region in the machine learning chip market in 2024. The regions covered in the machine learning chip market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

Who are the influential players reshaping the machine learning chip market landscape?
Major companies operating in the machine learning chip market report are Google LLC, Samsung Electronics Co. Ltd., Tencent Holdings Limited, Amazon Web Services Inc., Taiwan Semiconductor Manufacturing Company Limited (TSMC), Intel Corporation, International Business Machines Corporation (IBM), SoftBank Group Corp, Qualcomm Incorporated, Micron Technology, Inc. (US), NVIDIA Corporation, Toshiba Corporation, Advanced Micro Devices Inc., Texas Instruments Incorporated, Baidu Inc., NXP Semiconductors, Synopsys Inc., Lattice Semiconductor Corporation, Horizon Robotics, Hailo, Cerebras Inc., BitMain Technologies Holding Company, Graphcore, Mythic, Gyrfalcon Technology, Flex Logix Technologies, Wave Computing, Inc., Esperanto Technologies, BrainChip Holdings

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What Is Covered In The Machine Learning Chip Global Market Report?

•Market Size Forecast: Examine the machine learning chip market size across key regions, countries, product categories, and applications.
•Segmentation Insights: Identify and classify subsegments within the machine learning chip market for a structured understanding.
•Key Players Overview: Analyze major players in the machine learning chip market, including their market value, share, and competitive positioning.
•Growth Trends Exploration: Assess individual growth patterns and future opportunities in the machine learning chip market.
•Segment Contributions: Evaluate how different segments drive overall growth in the machine learning chip market.
•Growth Factors: Highlight key drivers and opportunities influencing the expansion of the machine learning chip market.
•Industry Challenges: Identify potential risks and obstacles affecting the machine learning chip market.
•Competitive Landscape: Review strategic developments in the machine learning chip market, including expansions, agreements, and new product launches.

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