基于(关键地区、市场参与者、规模和份额)的深度学习芯片市场 - 到 2031 年的预测

  • Report Code : TIPRE00003229
  • Category : Electronics and Semiconductor
  • Status : Published
  • No. of Pages : 185
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2018 年全球深度学习芯片市场规模为 20.4 亿美元,预计 2019 年预测期内复合年增长率为 30.0% –到 2027 年,预计将达到 213.1 亿美元。

北美引领全球深度学习芯片市场,预计将成为全球最大的收入贡献者预测期。深度学习芯片的开发得到了科技巨头大规模投资的支持,从大量生成的数据中开发模式。量子计算的兴起和深度学习芯片在机器人领域的应用正在推动北美国家深度学习芯片市场的增长。

利润丰厚的区域深度学习芯片市场

市场洞察

量子计算的突出地位有助于深度学习芯片市场的增长

量子计算需要秒来完成计算,否则将花费更多时间。量子计算机是人工智能、机器学习和大数据的创新变革。因此,量子计算的突出地位预计将推动深度学习芯片市场的增长。此外,量子计算有利于多种因素,包括投资组合优化、欺诈检测、风险管理以及需要即时数据反馈的领域。因此,单个处理器更容易在几秒钟内执行复杂的计算。此外,随着互联网的规模和规模,深度学习有助于以非常低的成本维护大型数据集。因此,这些因素有望推动全球深度学习芯片市场的增长。

实时消费者行为洞察和运营效率的提高将推动深度学习的整体增长芯片市场

商业的本质正在变得非常竞争,为了有效地竞争,当今的企业依赖于有用的信息和商业分析。传统上,业务分析工具用于根据一周或一个月前的事件数据来预测销售额。随着实时学习并根据模式提供建议的人工智能技术的出现,企业有巨大的机会在各种流程中应用深度学习,以更好地了解业务环境和客户。

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考虑到这些因素,人工智能使企业能够提高运营效率、降低运营成本、提升服务质量和客户体验。

芯片类型洞察< /p>

图形处理单元(GPU)在 2018 年占据了主要的深度学习芯片市场份额,而专用集成电路(ASIC)预计将成为预测期内增长最快的部分。由于 ASIC 非常具体且灵活性较差,但它们是人工智能应用可用的性能最高的硬件选项之一。

技术见解

深度学习芯片组包括片上系统、系统级封装、多芯片模块等以及其他芯片组。片上系统领域在 2018 年占据了深度学习芯片的主要市场份额,因为它有助于减少能源浪费、大型系统占用的空间和成本。

< p>行业垂直洞察

全球深度学习芯片市场分为BFSI、零售、IT&电信、汽车和交通、医疗保健、媒体和娱乐及其他。 BFSI 占据了深度学习芯片市场的主要市场份额,而医疗保健预计将成为该市场中增长最快的领域。降低运营成本、适应不断变化的合规性和法规、专注于核心业务以及在业务流程中集成自动化等因素是推动深度学习芯片市场 BFSI 细分市场增长的其他主要因素


按行业划分的欧盟其他深度学习芯片市场


战略见解

深度学习芯片市场的市场参与者主要关注通过采用先进技术来增强产品。通过在世界各地签署合作伙伴关系、合同、合资企业、融资和开设新办事处,公司可以在全球范围内维持其品牌声誉。下面列出了一些最新进展;

2019 年:NVIDIA 与 Hackster.io 合作推出了 AI at the Edge Challenge,这是一项开发者利用 NVIDIA 的竞赛Jetson Nano 开发者套件,用于构建创意和独特的项目,并有机会赢得 10 万美元的奖金。

2019 年:英特尔宣布计划扩建俄勒冈工厂以生产 7 纳米芯片。英特尔的新工厂将是D1X的第三期,这是英特尔于2010年开始建设的大型工厂。前两期均为1.1。百万平方英尺,创建的综合设施相当于 15 个 Costco 仓库店。第三阶段显然将使 D1X 的制造空间增加约 50%。此外,英特尔表示,工厂扩建将使其应对芯片短缺的速度提高 60%。

2019 年:华为推出业界首款 T 级 AIFW HiSecEngine USG12000。 HiSecEngine USG12000搭载升腾AI芯片,为企业网络提供智能检测能力和智能边防能力。

全球深度学习芯片市场细分

按芯片类型

  • GPU
  • ASIC
  • FPGA
  • CPU
  • 其他

按技术划分

  • 片上系统
  • < li>系统级封装
  • 多芯片模块
  • 其他

按行业垂直< /p>

  • 媒体与广告
  • BFSI、IT 与广告电信
  • 零售
  • 医疗保健
  • 汽车和医疗保健交通
  • 其他

按地理位置

  • 北美
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 法国
    • 德国
    • 英国
    • 俄罗斯
    • 意大利
    • 欧洲其他地区
  • 亚太地区 (APAC) )
    • 澳大利亚
    • 中国
    • 印度
    • 日本
    • 韩国        
    • 亚太地区其他地区
  • 中东和中东地区非洲 (MEA)
    • 沙特阿拉伯
    • 南非
    • 阿联酋
    • 中东和非洲其他地区
  • 南美洲 (SAM)
    • 巴西
    • 阿根廷
    • SAM 的其他地区

公司简介

  • Advanced Micro Devices, Inc.
  • Alphabet Inc. (Google)
  • 亚马逊公司
  • 百度公司
  • 华为技术有限公司
  • 英特尔公司
  • NVIDIA公司
  • NVIDIA公司
  • 华为技术有限公司
  • 英特尔公司
  • NVIDIA公司
  • 华为技术有限公司li>
  • 高通公司
  • 三星电子有限公司
  • Xilinx, Inc.
Report Coverage
Report Coverage

Revenue forecast, Company Analysis, Industry landscape, Growth factors, and Trends

Segment Covered
Segment Covered

This text is related
to segments covered.

Regional Scope
Regional Scope

North America, Europe, Asia Pacific, Middle East & Africa, South & Central America

Country Scope
Country Scope

This text is related
to country scope.

Frequently Asked Questions


What are reasons behind the North America deep learning chip market growth?

North America is one of the fastest-growing regions in terms of technological development. In the past 3 years, the region witnessed significant adoption of AI solutions across all the sectors. North America contributes the largest market share in terms of revenue, and it is estimated that it will continue its dominance in the market share during the forecast period. Deep learning chip development is backed by large-scale investment from technological giants to develop patterns from huge amount of generated data. The rise of quantum computing and implementation of deep learning chips in robotics drive the growth of the deep learning chip market in the North American countries.

What are market opportunities for deep learning chip?

Presently, the major applications of deep learning chips are in the data center/cloud computing segment, and this trend is expected to continue during the forecast period. Also, majorly due to rising adoption of AI in developing regions, evolving architectures of deep learning chips and increasing applications across various industry verticals. Owing to this growing trend, the companies are anticipated to produce high-quality service by adopting cloud-based artificial intelligence services.

Which industry vertical hold the major share in the deep learning chip market?

The BFSI industry dominated the deep learning chip market in the year 2018. Banking, financial services, and insurance (BFSI) industries have great potential for deep learning chips due to the presence of huge financial and personal data of customers. In this sector, a high amount of sensitive data is generated and exchanged every day. There is growing volume and creation of endpoints and mobile devices in banks, credit card companies, and credit reporting institutions, thus, it becomes important for these industry verticals to harness this data to gain insights about various business aspects.

The List of Companies - Deep Learning Chip Market 

  1. Advanced Micro Devices, Inc.
  2. Alphabet Inc. (Google)
  3. Amazon.com, Inc.
  4. Baidu, Inc.
  5. Huawei Technologies Co., Ltd
  6. Intel Corporation
  7. NVIDIA Corporation
  8. Qualcomm Incorporated
  9. Samsung Electronics Co., Ltd.
  10. Xilinx, Inc.

The Insight Partners performs research in 4 major stages: Data Collection & Secondary Research, Primary Research, Data Analysis and Data Triangulation & Final Review.

  1. Data Collection and Secondary Research:

As a market research and consulting firm operating from a decade, we have published and advised several client across the globe. First step for any study will start with an assessment of currently available data and insights from existing reports. Further, historical and current market information is collected from Investor Presentations, Annual Reports, SEC Filings, etc., and other information related to company’s performance and market positioning are gathered from Paid Databases (Factiva, Hoovers, and Reuters) and various other publications available in public domain.

Several associations trade associates, technical forums, institutes, societies and organization are accessed to gain technical as well as market related insights through their publications such as research papers, blogs and press releases related to the studies are referred to get cues about the market. Further, white papers, journals, magazines, and other news articles published in last 3 years are scrutinized and analyzed to understand the current market trends.

  1. Primary Research:

The primarily interview analysis comprise of data obtained from industry participants interview and answers to survey questions gathered by in-house primary team.

For primary research, interviews are conducted with industry experts/CEOs/Marketing Managers/VPs/Subject Matter Experts from both demand and supply side to get a 360-degree view of the market. The primary team conducts several interviews based on the complexity of the markets to understand the various market trends and dynamics which makes research more credible and precise.

A typical research interview fulfils the following functions:

  • Provides first-hand information on the market size, market trends, growth trends, competitive landscape, and outlook
  • Validates and strengthens in-house secondary research findings
  • Develops the analysis team’s expertise and market understanding

Primary research involves email interactions and telephone interviews for each market, category, segment, and sub-segment across geographies. The participants who typically take part in such a process include, but are not limited to:

  • Industry participants: VPs, business development managers, market intelligence managers and national sales managers
  • Outside experts: Valuation experts, research analysts and key opinion leaders specializing in the electronics and semiconductor industry.

Below is the breakup of our primary respondents by company, designation, and region:

Research Methodology

Once we receive the confirmation from primary research sources or primary respondents, we finalize the base year market estimation and forecast the data as per the macroeconomic and microeconomic factors assessed during data collection.

  1. Data Analysis:

Once data is validated through both secondary as well as primary respondents, we finalize the market estimations by hypothesis formulation and factor analysis at regional and country level.

  • Macro-Economic Factor Analysis:

We analyse macroeconomic indicators such the gross domestic product (GDP), increase in the demand for goods and services across industries, technological advancement, regional economic growth, governmental policies, the influence of COVID-19, PEST analysis, and other aspects. This analysis aids in setting benchmarks for various nations/regions and approximating market splits. Additionally, the general trend of the aforementioned components aid in determining the market's development possibilities.

  • Country Level Data:

Various factors that are especially aligned to the country are taken into account to determine the market size for a certain area and country, including the presence of vendors, such as headquarters and offices, the country's GDP, demand patterns, and industry growth. To comprehend the market dynamics for the nation, a number of growth variables, inhibitors, application areas, and current market trends are researched. The aforementioned elements aid in determining the country's overall market's growth potential.

  • Company Profile:

The “Table of Contents” is formulated by listing and analyzing more than 25 - 30 companies operating in the market ecosystem across geographies. However, we profile only 10 companies as a standard practice in our syndicate reports. These 10 companies comprise leading, emerging, and regional players. Nonetheless, our analysis is not restricted to the 10 listed companies, we also analyze other companies present in the market to develop a holistic view and understand the prevailing trends. The “Company Profiles” section in the report covers key facts, business description, products & services, financial information, SWOT analysis, and key developments. The financial information presented is extracted from the annual reports and official documents of the publicly listed companies. Upon collecting the information for the sections of respective companies, we verify them via various primary sources and then compile the data in respective company profiles. The company level information helps us in deriving the base number as well as in forecasting the market size.

  • Developing Base Number:

Aggregation of sales statistics (2020-2022) and macro-economic factor, and other secondary and primary research insights are utilized to arrive at base number and related market shares for 2022. The data gaps are identified in this step and relevant market data is analyzed, collected from paid primary interviews or databases. On finalizing the base year market size, forecasts are developed on the basis of macro-economic, industry and market growth factors and company level analysis.

  1. Data Triangulation and Final Review:

The market findings and base year market size calculations are validated from supply as well as demand side. Demand side validations are based on macro-economic factor analysis and benchmarks for respective regions and countries. In case of supply side validations, revenues of major companies are estimated (in case not available) based on industry benchmark, approximate number of employees, product portfolio, and primary interviews revenues are gathered. Further revenue from target product/service segment is assessed to avoid overshooting of market statistics. In case of heavy deviations between supply and demand side values, all thes steps are repeated to achieve synchronization.

We follow an iterative model, wherein we share our research findings with Subject Matter Experts (SME’s) and Key Opinion Leaders (KOLs) until consensus view of the market is not formulated – this model negates any drastic deviation in the opinions of experts. Only validated and universally acceptable research findings are quoted in our reports.

We have important check points that we use to validate our research findings – which we call – data triangulation, where we validate the information, we generate from secondary sources with primary interviews and then we re-validate with our internal data bases and Subject matter experts. This comprehensive model enables us to deliver high quality, reliable data in shortest possible time.

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