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市場調査レポート
商品コード
1614944
ディープラーニングの市場規模、シェア、成長分析、提供別、用途別、エンドユーザー産業別、地域別- 産業予測、2024~2031年Deep Learning Market Size, Share, Growth Analysis, By Offering (Hardware, Software), By Application, By End-User Industry, By Region - Industry Forecast 2024-2031 |
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ディープラーニングの市場規模、シェア、成長分析、提供別、用途別、エンドユーザー産業別、地域別- 産業予測、2024~2031年 |
出版日: 2024年12月14日
発行: SkyQuest
ページ情報: 英文 193 Pages
納期: 3~5営業日
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ディープラーニングの世界市場規模は、2022年に483億7,000万米ドルと評価され、2023年には641億3,000万米ドル、2031年には6,121億8,000万米ドルに成長し、予測期間(2024年~2031年)のCAGRは32.58%で成長する見通しです。
ディープラーニング市場は、計算能力の向上、ハードウェアコストの低下、クラウドベースの技術の急増によって、力強い成長を遂げています。さまざまな分野でモノのインターネット(IoT)デバイスが普及したことで、1日あたり約2.5兆バイトものデータが流入しており、これを管理するために、企業はより高い処理能力を求めるようになっています。この広大なデータ環境は、ディープラーニングソリューションが適応性と拡張性に優れた洞察を効率的に提供する大きな機会をもたらします。さらに、クラウド分析は、大規模なデータセットからの重要な情報の抽出を効率化し、インフラと運用コストを削減します。AIと機械学習のサブセットであるディープラーニングは、人間の認知機能を模倣し、高度な分類、パターン認識、画像ラベリングや音声転写などのタスクの自動化を可能にします。
Global Deep Learning Market size was valued at USD 48.37 Billion in 2022 and is poised to grow from USD 64.13 Billion in 2023 to USD 612.18 Billion by 2031, growing at a CAGR of 32.58% in the forecast period (2024-2031).
The deep learning market is experiencing robust growth, driven by enhanced computational capabilities, decreasing hardware costs, and a surge in cloud-based technologies. Organizations are increasingly demanding higher processing power to manage the influx of data-approximately 2.5 quintillion bytes daily-fuelled by the proliferation of Internet of Things (IoT) devices across various sectors. This expansive data landscape presents substantial opportunities for deep learning solutions to offer adaptive and scalable insights efficiently. Additionally, cloud analytics streamlines the extraction of critical information from large datasets while reducing infrastructure and operational costs. Deep learning, a subset of AI and machine learning, mimics human cognitive functions, enabling advanced classification, pattern recognition, and automation of tasks such as image labeling and audio transcription.
Top-down and bottom-up approaches were used to estimate and validate the size of the Global Deep Learning market and to estimate the size of various other dependent submarkets. The research methodology used to estimate the market size includes the following details: The key players in the market were identified through secondary research, and their market shares in the respective regions were determined through primary and secondary research. This entire procedure includes the study of the annual and financial reports of the top market players and extensive interviews for key insights from industry leaders such as CEOs, VPs, directors, and marketing executives. All percentage shares split, and breakdowns were determined using secondary sources and verified through Primary sources. All possible parameters that affect the markets covered in this research study have been accounted for, viewed in extensive detail, verified through primary research, and analyzed to get the final quantitative and qualitative data.
Global Deep Learning Market Segmental Analysis
Global Deep Learning Market is segmented by Offering, Application, End-User Industry and region. Based on Offering, the market is segmented into Hardware (Processor, Memory, Network), Software (Solution, Platform/API), Services (Installation, Training, Support & Maintenance). Based on Application, the market is segmented into Image Recognition, Signal Recognition, Data Mining, Others (Recommender System, Drug Discovery). Based on End-User Industry, the market is segmented into Healthcare, Manufacturing, Automotive, Agriculture, Retail, Security, Human Resources, Marketing, Law, and Fintech. Based on region, the market is segmented into North America, Europe, Asia Pacific, Latin America and Middle East & Africa.
Driver of the Global Deep Learning Market
One of the primary drivers of the Global Deep Learning market is its increasing adoption in the healthcare sector. Deep learning technologies are rapidly transforming this industry by enhancing diagnostic precision and enabling personalized treatment strategies. Healthcare providers are increasingly implementing deep learning algorithms to scrutinize medical imaging, such as MRI and CT scans, allowing for the early detection of diseases like cancer. This trend towards utilizing advanced algorithms revolutionizes patient care, making diagnostics more accurate and efficient. As a result, the healthcare industry's focus on integrating deep learning solutions is significantly contributing to the growth of the Global Deep Learning market.
Restraints in the Global Deep Learning Market
One of the significant restraints affecting the Global Deep Learning market is its limited integration with big data. Deep learning relies heavily on extensive and reliable data sets for training, which enhances its performance. However, the scarcity of adequate, trustworthy data can hinder the effectiveness of deep learning systems. For these data models to operate optimally, they require a substantial volume of information. Unfortunately, the difficulty in gathering these vital resources poses a challenge to the entire deep learning ecosystem, impeding advancements and limiting the potential for innovation within the market.
Market Trends of the Global Deep Learning Market
The Global Deep Learning market is witnessing a significant trend as the manufacturing sector increasingly adopts advanced deep learning technologies to enhance operational efficiency and precision. By leveraging sophisticated algorithms for predictive maintenance, manufacturers can proactively identify potential machine failures, thereby minimizing downtime and optimizing production schedules. This shift not only accelerates manufacturing processes but also reduces operational costs, leading to a highly competitive environment. As companies strive for greater automation and innovation, the integration of deep learning in manufacturing is set to reshape industry standards, driving substantial growth in the global deep learning market over the coming years.