#deep learning chipset

According to the latest research report by Transparency Market Research (TMR), the global deep learning chipset market is poised for exponential growth. Driven by the unprecedented surge in data volumes and advanced algorithms, the market is expected to quintuple from approximately USD 6.4 billion in 2019 to nearly USD 35.2 billion by 2027, expanding at a robust compound annual growth rate (CAGR) of around 24%.

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Market Overview

The artificial intelligence (AI) revolution continues to reshape numerous industry verticals—from healthcare and automotive to aerospace & defense and consumer electronics. At the heart of this transformation lies the deep learning chipset market, which has evolved significantly from early neural network models to sophisticated deep learning architectures. High volumes of data required for training and inference, coupled with rapid technological advancements, are catalyzing the widespread adoption of these chipsets across multiple applications.

TMR’s research highlights that while deep learning chipsets have traditionally powered data centers, a notable trend is emerging where a majority of processing is expected to move closer to the sensor arrays—driving innovation in edge computing and next-generation consumer devices.

Top Market Trends

High Demand for Advanced AI Processing: The surge in digitally generated data, propelled by IoT and high-resolution content, has spurred demand for chipsets that can efficiently process complex deep learning and machine learning models.

Shift to Edge Processing: Although data centers have historically been the primary users, companies are increasingly focusing on embedding deep learning capabilities in consumer devices such as security cameras, drones, smartphones, and AR/VR headsets.

Integration of Enhanced Graphical Capabilities: Technological advancements in graphic processing units (GPUs) have ushered in a new era where chipsets now combine high-resolution image processing with state-of-the-art computational capabilities. This is exemplified by recent innovations that have dramatically improved energy efficiency and performance.

Key Players and Latest Developments

Several industry titans and innovative startups are vying for a leading position in this rapidly evolving market. Key players include IBM Corporation, Graphcore Ltd, CEVA, Inc., Advanced Micro Devices, Inc., NVIDIA Corporation, Intel Corporation, Movidius, XILINX INC., TeraDeep Inc., QUALCOMM Incorporated, and Alphabet Inc.

Recent strategic developments have further intensified competition:

Huawei unveiled its Ascend 910 and Ascend 310 AI chips in August 2019, with the former delivering up to 256 TeraFLOPS for advanced processing.

Hailo made headlines in May 2019 by launching the Hailo-8, the first deep learning processor specifically engineered for devices such as drones, smartphones, and smart cameras.

NVIDIA Corporation introduced a breakthrough chip in June 2018, featuring six processing units including a 512-core Volta Tensor Core GPU, an eight-core Carmel Arm64 CPU, and specialized accelerators—all designed to offer unprecedented performance while consuming significantly lower power.

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Deep Learning Chipset Market – Segmentation

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

Consumer Industry Impact

The integration of deep learning chipsets is revolutionizing consumer electronics. Devices ranging from augmented reality/virtual reality (AR/VR) headsets and smart speakers to next-generation smartphones are now equipped with advanced AI processing capabilities. This has not only enhanced user engagement and satisfaction but also driven manufacturers to invest heavily in chipset innovation to meet the evolving demands of the market.

As deep learning facilitates enhanced cognitive functions such as reasoning, learning, and perception, it is expected to further transform industries by enabling smarter, more intuitive devices that better interact with human users.

Future Outlook

Looking ahead, the deep learning chipset market is set to experience remarkable growth, underpinned by:

Continued Technological Advancements: Ongoing innovations in chipset fabrication and design will unlock new applications, particularly in areas requiring real-time data processing at the edge.

Expanding Market Applications: Beyond consumer electronics, sectors such as automotive, industrial, healthcare, and aerospace & defense are anticipated to increasingly leverage deep learning chipsets to improve operational efficiency and safety.

Strategic Industry Collaborations: As companies align their R&D efforts with emerging market trends, strategic partnerships and collaborations are expected to drive further breakthroughs in AI hardware.

More Trending Reports: Chiplets Market: It is estimated to advance at a CAGR of 46.47% from 2024 to 2034 and reach US$ 5,55,019.19 Mn by the end of 2034

Magnetoresistive (MR) Sensors Market: It is estimated to advance at a CAGR of 5.57% from 2024 to 2034 and reach US$ 764.39 Mn by the end of 2034

About Us Transparency Market Research Transparency Market Research, a global market research company registered at Wilmington, Delaware, United States, provides custom research and consulting services. The firm scrutinizes factors shaping the dynamics of demand in various markets. The insights and perspectives on the markets evaluate opportunities in various segments. The opportunities in the segments based on source, application, demographics, sales channel, and end-use are analysed, which will determine growth in the markets over the next decade. Our exclusive blend of quantitative forecasting and trends analysis provides forward-looking insights for thousands of decision-makers, made possible by experienced teams of Analysts, Researchers, and Consultants. The proprietary data sources and various tools & techniques we use always reflect the latest trends and information. With a broad research and analysis capability, Transparency Market Research employs rigorous primary and secondary research techniques in all of its business reports.

Deep learning has become a game-changing technique in recent years, finding use in fields including computer vision, autonomous driving, and natural language processing. Deep learning chipsets, specialized hardware made to speed up the intricate calculations needed by deep neural networks, are at the center of this revolution. The market for deep learning chipsets is expanding at a rate never seen before as demand for deep learning keeps rising.

One of the key drivers behind the surge in demand for deep learning chipsets is the exponential increase in data. With the proliferation of connected devices and the advent of big data, organizations across industries are grappling with vast amounts of information. Deep learning chipsets offer a solution by dramatically speeding up the training and inference processes, enabling businesses to extract insights and make decisions in real-time.

Moreover, as deep learning models become increasingly complex, traditional CPUs and GPUs are struggling to keep pace. Deep learning chipsets, on the other hand, are specifically optimized for the matrix multiplications and nonlinear operations that characterize deep neural networks. This optimization results in significant performance gains, allowing for faster and more efficient training of models.

Another factor driving the growth of the deep learning chipset market is the rise of edge computing. With the proliferation of IoT devices, there is a growing need to perform inference tasks directly on the edge, without relying on cloud-based servers. Deep learning chipsets enable this by providing the necessary computational power in a compact and energy-efficient form factor, making them ideal for deployment in edge devices such as smartphones, cameras, and sensors.

Global Deep Learning Chipset Market was valued US$ XX Bn in 2018 and is expected to reach US$ 2.9 Bn by 2026, at CAGR of XX % during the forecast period.

Global Deep Learning Chipset Market was valued US$ XX Bn in 2018 and is expected to reach US$ 2.9 Bn by 2026, at CAGR of XX % during the forecast period.

The report covers all the trends and technologies playing a major role in the growth of the deep learning chipset market over the forecast period. It highlights the drivers, restraints, and opportunities expected to impact market growth during this period.

Deep learning chipset technology has improved drastically in recent times owing to the increasing demand for deep learning in industries to solve problems such as computer vision and pattern recognition. Many semiconductors companies are coming up with new chipset technology to cater to the demand and innovation fueled by heavy investment is underway in the very market.

Increased adoption of cloud-based technology and deep learning usage in big data analytics are the factors driving the growth of the deep learning chipset market. Also, the Invention of a related computer chip, which is known as the GPU. A single-chip processor creates lighting effects and transforms objects every time a 3D scene is redrawn or graphics processing unit is turning out to be very meaningful and effective when it is being applied to types of calculations mandatory for neural nets. This, in turn, is fueling the growth of the deep learning chipset market.

By type, the graphics processing units segment holds the largest XX% market share of and expected to dominate the market during the forecast period. For machine learning tasks, GPUs were found to be between 10 and 100 times as fast as CPU-only machine learning solutions, depending on the exact task.

North America is expected to hold the largest XX% share of the global market for the mass notification system during the forecast period. The high demand for deep learning chipsets in the North American market is attributed to the rising number of startups in the region. The valuation of the APAC is expected to be around worth US$ XX Mn in terms of revenue.

The report covers a recent development in the market for deep learning chipset like in August 2018, Intel took over Nirvana Systems as well to fortify its deep learning chipset market position in the making of hardware chipsets platform.

The objective of the report is to present a comprehensive assessment of the market and contains thoughtful insights, facts, historical data, industry-validated market data and projections with a suitable set of assumptions and methodology. The report also helps in understanding Global Deep Learning Chipset Market dynamics, structure by identifying and analyzing the market segments and project the global market size. Further, the report also focuses on the competitive analysis of key players by product, price, financial position, product portfolio, growth strategies, and regional presence. The report also provides PEST analysis, PORTER’s analysis, and SWOT analysis to address the question of shareholders to prioritizing the efforts and investment in the near future to the emerging segment in Global Deep Learning Chipset Market. Scope of the Global Deep Learning Chipset Market

Global Deep Learning Chipset Market, By Type

• Central Processing Units (CPUs) • Graphics Processing Units (GPUs) • Field Programmable Gate Arrays (FPGAs) • Application Specific Integrated Circuits (ASICs) • Others (NPU & Hybrid Chip) Global Deep Learning Chipset Market, By Application

• Automotive • Smart Cameras • Robots • Drones • Mobile Phones • Others Global Deep Learning Chipset Market, By Technology

• System-on-chip (SOC) • System-in-package (SIP) • Multi-Chip Module • OTHERS (Package in Package, TSV) Global Deep Learning Chipset Market, By Compute Capacity

• Low (<1TFlops)

• High (>1TFlops) Global Deep Learning Chipset Market, By End-User Industry

• BFSI • IT & Telecom • Retail • Media & Advertising • Healthcare • Automotive • Others Global Deep Learning Chipset Market, By Region

• North America • Europe • Asia Pacific • Middle East and Africa • South America Key players operating in Global Deep Learning Chipset Market

• NVIDIA • Intel • IBM • Qualcomm • CEVA • KnuEdge • AMD • Xilinx • ARM • Google • Graphcore • TeraDeep • Wave Computing • BrainChip

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Deep learning technology is driving the evolution of artificial intelligence (AI) and has become one of the hottest topics of discussion within the technology world and beyond. Given the rate at which deep learning is progressing, some industry observers are predicting it will bring about a doomsday scenario, while others strive for a time when the technology can transform business processes and create new business models through scalable, more efficient automation and predictive capabilities. The current market climate is ripe for innovation in hardware in general, and chipsets more specifically.

Company profile mentioned: Intel, IBM, Qualcomm, CEVA, KnuEdge, AMD, Xilinx, ARM, Google, Graphcore, TeraDeep, Wave Computing, BrainChip

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Market Segment as follows:

By Type - Graphics Processing Units (GPUs), Central Processing Units (CPUs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs), Others

By Application – Consumer, Aerospace, Military & Defense, Automotive, Industrial, Medical, Others

Table of Contents:

1 Market Overview

1.1 Market Segment Overview

1.2 Global and Regional Market Size

2 Global and Regional Market by Company

2.1 Global

2.2 China

3 Global and Regional Market by Type

3.1 Global

3.2 China

4 Global and Regional Market by Application

4.1 Global

4.2 China

5 China Trade

5.1 Export

5.2 Import

6 Key Manufacturers

7 Industry Upstream

7.1 Industry Chain

7.2 Raw Materials

8 Market Environment

8.1 SWOT

8.2 Porter's Five Forces

9 Conclusion

List of Table:

·         Table Global Market Sales Revenue by Company 2013-2017

·         Table Global Market Sales Revenue Share by Company 2013-2017

·         Table Global Market Sales Volume by Company 2013-2017

·         Table Global Market Sales Volume Share by Company 2013-2017

·         Table Global Price by Company 2013-2017

·         Table China Market Sales Revenue by Company 2013-2017

·         Table China Market Sales Revenue Share by Company 2013-2017

·         Table China Market Sales Volume by Company 2013-2017

·         Table China Market Sales Volume Share by Company 2013-2017

·         Table China Price by Company 2013-2017

·         Table Global Market Sales Revenue by Type 2013-2017

·         Table Global Market Sales Revenue Share by Type 2013-2017

·         Table Global Market Sales Volume by Type 2013-2017

·         Table Global Market Sales Volume Share by Type 2013-2017

·         Table Global Price by Type 2013-2017

·         Table China Market Sales Revenue by Type 2013-2017

·         Table China Market Sales Revenue Share by Type 2013-2017

·         Table China Market Sales Volume by Type 2013-2017

·         Table China Market Sales Volume Share by Type 2013-2017

·         Table China Price by Type 2013-2017

·         Table Global Market Sales Revenue by Application 2013-2017

·         Table Global Market Sales Revenue Share by Application 2013-2017

·         Table Global Market Sales Volume by Application 2013-2017

·         Table Global Market Sales Volume Share by Application 2013-2017

·         Table Global Price by Application 2013-2017

·         Table China Market Sales Revenue by Application 2013-2017

·         Table China Market Sales Revenue Share by Application 2013-2017

·         Table China Market Sales Volume by Application 2013-2017

·         Table China Market Sales Volume Share by Application 2013-2017

·         Table China Price by Application 2013-2017

·         Table China Export 2013-2017 (Value)

·         Table China Export 2013-2017 (Volume)

·         Table China Import 2013-2017 (Value)

·         Table China Import 2013-2017 (Volume)

List of Figure:

·         Figure Graphics Processing Units (GPUs) Market Size and CAGR 2013-2017 (Value)

·         Figure Graphics Processing Units (GPUs) Market Size and CAGR 2013-2017 (Volume)

·         Figure Graphics Processing Units (GPUs) Market Forecast and CAGR 2018-2025 (Value)

·         Figure Graphics Processing Units (GPUs) Market Forecast and CAGR 2018-2025 (Volume)

·         Figure Central Processing Units (CPUs) Market Size and CAGR 2013-2017 (Value)

·         Figure Central Processing Units (CPUs) Market Size and CAGR 2013-2017 (Volume)

·         Figure Central Processing Units (CPUs) Market Forecast and CAGR 2018-2025 (Value)

·         Figure Central Processing Units (CPUs) Market Forecast and CAGR 2018-2025 (Volume)

·         Figure Application Specific Integrated Circuits (ASICs) Market Size and CAGR 2013-2017 (Value)

·         Figure Application Specific Integrated Circuits (ASICs) Market Size and CAGR 2013-2017 (Volume)

·         Figure Application Specific Integrated Circuits (ASICs) Market Forecast and CAGR 2018-2025 (Value)

·         Figure Application Specific Integrated Circuits (ASICs) Market Forecast and CAGR 2018-2025 (Volume)

·         Figure Field Programmable Gate Arrays (FPGAs) Market Size and CAGR 2013-2017 (Value)

·         Figure Field Programmable Gate Arrays (FPGAs) Market Size and CAGR 2013-2017 (Volume)

·         Figure Field Programmable Gate Arrays (FPGAs) Market Forecast and CAGR 2018-2025 (Value)

·         Figure Field Programmable Gate Arrays (FPGAs) Market Forecast and CAGR 2018-2025 (Volume)

·         Figure Others Market Size and CAGR 2013-2017 (Value)

·         Figure Others Market Size and CAGR 2013-2017 (Volume)

·         Figure Others Market Forecast and CAGR 2018-2025 (Value)

·         Figure Others Market Forecast and CAGR 2018-2025 (Volume)

·         Figure Consumer Market Size and CAGR 2013-2017 (Value)

·         Figure Consumer Market Size and CAGR 2013-2017 (Volume)

·         Figure Consumer Market Forecast and CAGR 2018-2025 (Value)

·         Figure Consumer Market Forecast and CAGR 2018-2025 (Volume)

·         Figure Aerospace, Military & Defense Market Size and CAGR 2013-2017 (Value)

·         Figure Aerospace, Military & Defense Market Size and CAGR 2013-2017 (Volume)

·         Figure Aerospace, Military & Defense Market Forecast and CAGR 2018-2025 (Value)

·         Figure Aerospace, Military & Defense Market Forecast and CAGR 2018-2025 (Volume)

·         Figure Automotive Market Size and CAGR 2013-2017 (Value)

·         Figure Automotive Market Size and CAGR 2013-2017 (Volume)

·         Figure Automotive Market Forecast and CAGR 2018-2025 (Value)

·         Figure Automotive Market Forecast and CAGR 2018-2025 (Volume)

·         Figure Industrial Market Size and CAGR 2013-2017 (Value)

·         Figure Industrial Market Size and CAGR 2013-2017 (Volume)

·         Figure Industrial Market Forecast and CAGR 2018-2025 (Value)

·         Figure Industrial Market Forecast and CAGR 2018-2025 (Volume)

·         Figure Medical Market Size and CAGR 2013-2017 (Value)

·         Figure Medical Market Size and CAGR 2013-2017 (Volume)

·         Figure Medical Market Forecast and CAGR 2018-2025 (Value)

·         Figure Medical Market Forecast and CAGR 2018-2025 (Volume)

·         Figure Others Market Size and CAGR 2013-2017 (Value)

·         Figure Others Market Size and CAGR 2013-2017 (Volume)

·         Figure Others Market Forecast and CAGR 2018-2025 (Value)

·         Figure Others Market Forecast and CAGR 2018-2025 (Volume)

·         Figure Global Deep Learning Chipset Market Size and CAGR 2013-2017 (Value)

·         Figure Global Deep Learning Chipset Market Size and CAGR 2013-2017 (Volume)

·         Figure Global Deep Learning Chipset Market Forecast and CAGR 2018-2025 (Value)

·         Figure Global Deep Learning Chipset Market Forecast and CAGR 2018-2025 (Volume)

·         Figure China Deep Learning Chipset Market Size and CAGR 2013-2017 (Value)

·         Figure China Deep Learning Chipset Market Size and CAGR 2013-2017 (Volume)

·         Figure China Deep Learning Chipset Market Forecast and CAGR 2018-2025 (Value)

·         Figure China Deep Learning Chipset Market Forecast and CAGR 2018-2025 (Volume)

·         Figure Global Market Sales Revenue Share by Company in 2017

·         Figure Global Market Sales Volume Share by Company in 2017

·         Figure China Market Sales Revenue Share by Company in 2017

·         Figure China Market Sales Volume Share by Company in 2017

·         Figure Global Market Sales Revenue Share by Type in 2017

·         Figure Global Market Sales Volume Share by Type in 2017

·         Figure China Market Sales Revenue Share by Type in 2017

·         Figure China Market Sales Volume Share by Type in 2017

·         Figure Global Market Sales Revenue Share by Application in 2017

·         Figure Global Market Sales Volume Share by Application in 2017

·         Figure China Market Sales Revenue Share by Application in 2017

·         Figure China Market Sales Volume Share by Application in 2017

·         Figure Industry Chain Overview

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The report provides a comprehensive analysis of the Deep Learning Chipset industry market by types, applications, players and regions. This report also displays the production, Consumption, revenue, Gross margin, Cost, Gross, market share, CAGR, and Market influencing factors of the Deep Learning Chipset industry in USA, EU, China,India, Japan and other regions, and forecast to 2022, from 2017.

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