Markt für Deep-Learning-Chips – Erkenntnisse aus globaler und regionaler Analyse – Prognose bis 2031

  • Report Code : TIPRE00003229
  • Category : Electronics and Semiconductor
  • Status : Published
  • No. of Pages : 185
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Der weltweite Markt für Deep-Learning-Chips belief sich im Jahr 2018 auf 2,04 Milliarden US-Dollar und soll im Prognosezeitraum 2019–2027 mit einer durchschnittlichen jährlichen Wachstumsrate von 30,0 % wachsen, sodass er bis 2027 21,31 Milliarden US-Dollar erreichen wird.



Nordamerika ist weltweit führend auf dem Markt für Deep-Learning-Chips und dürfte im gesamten Prognosezeitraum den höchsten Umsatzbeitrag leisten. Die Entwicklung von Deep-Learning-Chips wird durch umfangreiche Investitionen von Technologiegiganten unterstützt, die aus einer riesigen Menge generierter Daten Muster entwickeln. Der Aufstieg des Quantencomputings und die Implementierung von Deep-Learning-Chips in der Robotik treiben das Wachstum des Deep-Learning-Chip-Marktes in den nordamerikanischen Ländern voran.



Lukrativer regionaler Deep-Learning-Chip-Markt



Markteinblicke



Die Bedeutung des Quantencomputings trägt zum Wachstum des Marktes für Deep-Learning-Chips bei



Das Quantencomputing benötigt Sekunden, um eine Berechnung abzuschließen, die sonst mehr Zeit in Anspruch nehmen würde. Quantencomputer sind eine innovative Transformation von künstlicher Intelligenz, maschinellem Lernen und Big Data. Daher wird erwartet, dass die Bedeutung des Quantencomputings das Wachstum des Marktes für Deep-Learning-Chips vorantreiben wird. Darüber hinaus ist Quantencomputing für verschiedene Faktoren von Vorteil, darunter Portfoliooptimierung, Betrugserkennung und Risikomanagement sowie für Bereiche, in denen sofortiges Datenfeedback erforderlich ist. Somit ist es für einen einzelnen Prozessor einfacher, komplexe Berechnungen in Sekundenschnelle durchzuführen. Darüber hinaus hilft Deep Learning angesichts der Größe und Größe des Internets dabei, große Datenmengen zu sehr geringen Kosten zu verwalten. Daher wird erwartet, dass diese Faktoren das Wachstum des globalen Marktes für Deep-Learning-Chips ankurbeln.



Echtzeit-Einblicke in das Verbraucherverhalten und erhöhte betriebliche Effizienz, um das Gesamtwachstum des Marktes für Deep-Learning-Chips voranzutreiben



Die Natur der Wirtschaft wird immer wettbewerbsintensiver und um effizient im Wettbewerb zu bestehen, sind Unternehmen heutzutage auf nützliche Informationen und Geschäftsanalysen angewiesen. Traditionell wurden Geschäftsanalysetools verwendet, um Umsätze anhand der Daten zu Ereignissen zu prognostizieren, die eine Woche oder einen Monat zurückliegen. Mit dem Aufkommen der Technologie der künstlichen Intelligenz, die in Echtzeit lernt und auf Mustern basierende Empfehlungen liefert, haben Unternehmen eine enorme Chance, Deep Learning in verschiedenen Prozessen anzuwenden, um das Geschäftsumfeld und die Kunden besser zu verstehen.



In Anbetracht dessen Faktoren: Künstliche Intelligenz ermöglicht es Unternehmen, die betriebliche Effizienz zu verbessern, die Betriebskosten zu senken, die Servicequalität und das Kundenerlebnis zu verbessern.



Einblicke in Chiptypen



Graphic Processing Units (GPUs) hielten das wichtigste Deep Learning ab Chip-Marktanteil im Jahr 2018, während anwendungsspezifische integrierte Schaltkreise (ASICs) im Prognosezeitraum voraussichtlich das am schnellsten wachsende Segment sein werden. Aufgrund der Tatsache, dass ASICs sehr spezifisch und weniger flexibel sind, stellen sie jedoch eine der leistungsstärksten verfügbaren Hardwareoptionen für Anwendungen der künstlichen Intelligenz dar.



Technologische Einblicke



Die Deep-Learning-Chipsätze umfassen System -on-Chip, System-in-Package, Multi-Chip-Modul und andere sowie andere Chipsätze. Das System-on-Chip-Segment hatte im Jahr 2018 den größten Marktanteil bei Deep-Learning-Chips, da es dazu beiträgt, Energieverschwendung, Platzbedarf großer Systeme und Kosten zu reduzieren.



Industry Vertical Insights



Der globale Markt für Deep-Learning-Chips ist in BFSI, Einzelhandel, IT und Telekommunikation, Automobil und Transport, Gesundheitswesen, Medien und Unterhaltung und andere unterteilt. BFSI hatte den größten Marktanteil im Deep-Learning-Chip-Markt, während das Gesundheitswesen voraussichtlich das am schnellsten wachsende Marktsegment sein wird. Faktoren wie die Senkung der Betriebskosten, die Anpassung an sich ändernde Vorschriften und Vorschriften, die Konzentration auf das Kerngeschäft und die Integration der Automatisierung in Geschäftsprozesse sind weitere wichtige Faktoren, die das Wachstum des BFSI-Segments im Markt für Deep-Learning-Chips antreiben



Restlicher EU-Deep-Learning-Chip-Markt nach Branchen



Strategische Einblicke



Die auf dem Deep-Learning-Chip-Markt vorhandenen Marktteilnehmer konzentrieren sich hauptsächlich auf Produktverbesserungen durch Implementierung fortgeschrittene Technologien. Durch die Unterzeichnung von Partnerschaften, Verträgen, Joint Ventures, Finanzierungen und die Eröffnung neuer Büros auf der ganzen Welt kann das Unternehmen seinen Markennamen weltweit aufrechterhalten. Nachfolgend sind einige der jüngsten Entwicklungen aufgeführt.



2019: NVIDIA hat sich mit Hackster.io zusammengetan, um die KI bei der Edge Challenge zu starten, einem Wettbewerb, bei dem Entwickler das NVIDIA Jetson Nano Developer Kit nutzen, um kreative und einzigartige Produkte zu entwickeln Projekte und gewinnen Sie die Chance, Preise im Wert von 100.000 US-Dollar zu gewinnen.



2019: Intel kündigt seine Pläne an, das Werk in Oregon zu erweitern, um einen 7-nm-Chip zu produzieren. Intels neue Fabrik wird die dritte Phase von D1X sein, einer riesigen Fabrik, die Intel 2010 ins Leben gerufen hat. Jede der ersten beiden Phasen war 1.1. Millionen Quadratmeter, wodurch eine Gesamtanlage entsteht, die 15 Costco-Lagerhäusern entspricht. Die dritte Phase wird offenbar die Produktionsfläche des D1X um etwa 50 Prozent vergrößern. Darüber hinaus sagt Intel, dass die Fabrikerweiterung es ihm ermöglichen wird, 60 Prozent schneller auf Chip-Engpässe zu reagieren.



2019: Huawei bringt HiSecEngine USG12000 auf den Markt, das erste T-Level-AIFW der Branche. Die HiSecEngine USG12000 ist mit Ascend AI-Chips ausgestattet, die intelligente Erkennungsfunktionen sowie intelligenten Grenzschutz für Unternehmensnetzwerke bieten.



GLOBALER DEEP-LEARNING-CHIP-MARKTSEGMENTIERUNG



Nach Chiptyp


  • GPU

  • ASIC

  • FPGA

  • CPU

  • Andere


< p>Nach Technologie




  • System-on-Chip

  • System-in-Package

  • Multi-Chip-Modul

  • Andere


Nach Branche




  • Medien und Werbung

  • BFSI, IT und Telekommunikation

  • Einzelhandel
  • Gesundheitswesen

  • Automobil & Transport

  • Andere


Nach Geografie




  • Nordamerika
    • USA

    • Kanada

    • Mexiko



  • Europa

    • Frankreich

    • Deutschland

    • Großbritannien

    • Russland

    • Italien

    • Übriges Europa



  • Asien-Pazifik (APAC)

    • Australien

    • China

    • Indien

    • Japan

    • Südkorea

    • Rest von APAC



  • Naher Osten und Afrika (MEA)

    • Saudi-Arabien

    • Südafrika

    • < li>VAE
    • Rest von MEA



  • Südamerika (SAM)

    • Brasilien

    • Argentinien
    • Rest von SAM




Unternehmensprofile




  • Advanced Micro Devices, Inc.

  • < li>Alphabet Inc. (Google)
  • Amazon.com, Inc.

  • Baidu, Inc.

  • Huawei Technologies Co., Ltd

  • < li>Intel Corporation
  • NVIDIA Corporation

  • Qualcomm Incorporated

  • Samsung Electronics Co., Ltd.

  • 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:

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  • 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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