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市場調査レポート
商品コード
1364001
生成AIの世界市場:2023-2030年Global Generative AI Market 2023-2030 |
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カスタマイズ可能
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生成AIの世界市場:2023-2030年 |
出版日: 2023年09月24日
発行: Orion Market Research
ページ情報: 英文 180 Pages
納期: 2~3営業日
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世界の生成AI市場は、予測期間中に48.5%というかなりのCAGRで成長すると予測されています。生成AI(人工知能)は、プロンプトに応じてテキスト、画像、動画などの新しいコンテンツを生成できるAIの一種です。生成AIモデルは、入力訓練データのパターンと構造を学習し、類似した特性を持つ新しいデータを生成します。生成AIモデルは、テキスト、コード、画像などの大規模なデータセットで学習されます。より多くのデータが利用可能になるにつれて、生成AIモデルはよりリアルでクリエイティブなコンテンツを生成できるようになります。生成AIモデルは、テキスト、コード、または画像の大規模なデータセットで学習されます。これは、モデルが生成するはずのコンテンツの種類の多種多様な例にさらされることを意味します。
コードのデータセットで訓練された生成AIモデルは、ソフトウェア・アプリケーションやWebサイトなどの新しいコードを生成するために使用できます。このモデルは、データセットのコードに似たコードを生成することができますが、新しいオリジナルのコードを生成することもできます。DALL-E 2は、テキストと画像のデータセットで学習される生成AIモデルです。DALL-E 2は、テキスト記述から画像を生成するために使用することができます。
医療、金融、製造業など、生成AIソフトウェアの幅広い用途で高い需要があることから、2022年の生成AI市場ではソフトウェア分野が大きなシェアを占めました。クラウドベースの生成AIソフトウェアソリューションの採用が増加しているため、企業は生成AIの導入と利用が容易になっています。オープンソースの生成AIソフトウェア・ライブラリの利用可能性が高まっているため、開発者は生成AIアプリケーションを容易に構築できます。
アジア太平洋地域には、アリババ、バイドゥ、テンセントなどの大手テクノロジー企業があります。これらの企業は生成AIの研究開発に多額の投資を行っており、ビジネス向けの生成AIアプリケーションも開発しています。例えば、バイドゥの共同創業者でCEOのロビン・リーは2023年6月、生成AI企業を支援する10億元(1億4,500万米ドル)ファンドの立ち上げを発表しました。この投資は、この地域における生成AI市場の成長を後押ししています。
Title: Global Generative AI Market Size, Share & Trends Analysis Report Market by Offering (Software and Services), by Application (Text, Image, Video, and Others (Audio)), Business Function (Marketing and Sales, Finance, Human Resource, Research and Development, and Others (Customer service and Education)), Vertical (BFSI, IT and Telecommunication, Healthcare, Media and Entertainment, Retail and E-Commerce, Manufacturing, Construction and Real Estate, and Others)) Forecast Period (2022-2030).
Global generative AI market is anticipated to grow at a considerable CAGR of 48.5% during the forecast period. Generative artificial intelligence (AI) is a type of AI that can generate new content, such as text, images, or videos, in response to prompts. Generative AI models learn the patterns and structure of their input training data and then generate new data that has similar characteristics. Generative AI models are trained on large datasets of text, code, or images. As more and more data becomes available, generative AI models can produce more realistic and creative content. Generative AI models are trained on large datasets of text, code, or images. This means that the models are exposed to a wide variety of examples of the type of content that they are supposed to generate.
A generative AI model that is trained on a dataset of code can be used to generate new code, such as software applications and websites. The model will be able to generate code that is similar to the code in the dataset, but it will also be able to generate new and original code. DALL-E 2 is a generative AI model that is trained on a dataset of text and images. DALL-E 2 can be used to generate images from text descriptions.
The global generative AI market is segmented based on offering, application, business function, and vertical. Based on the offering, the market is segmented into software and services. Based on application, the market is sub-segmented into text, image, video, and others. Based on business function, the market is segmented into marketing and sales, human resources, research and development, finance, and others (customer service and education). Based on vertical, the market is sub-segmented into BFSI, IT and telecommunication, healthcare, media and entertainment, retail and e-commerce, manufacturing, construction and real estate, and others.
The software segment held the major market share of the generative AI market in 2022 due to the high demand in a wide range of applications for generative AI software including healthcare, finance, and manufacturing. The increasing adoption of cloud-based generative AI software solutions makes it easier for businesses to deploy and use generative AI. The growing availability of open-source generative AI software libraries makes it easier for developers to build generative AI applications.
The global generative AI market is further segmented based on geography, including North America (the US and Canada), Europe (Italy, Spain, Germany, France, and others), Asia-Pacific (India, China, Japan, South Korea, and others), and the Rest of the World (the Middle East & Africa and Latin America). Among these North America holds the major market share of the market owing to high adoption of generative AI technologies in the region, particularly in the US. The well-developed technology infrastructure in the region supports the development and deployment of generative AI applications.
The Asia Pacific region is home to several large technology companies such as Alibaba, Baidu, and Tencent. These companies are investing heavily in generative AI research and development, and they are also developing generative AI applications for their businesses. For instance, in June 2023, Baidu's co-founder and CEO Robin Li announced the launch of a billion yuan ($145 million) fund to back generative AI companies. This investment is helping to drive the growth of the generative AI market in the region.
The major companies serving the global generative AI market include Amazon Web Services, Inc., Microsoft, Corp., Google LLC., and IBM Corp., among others. The market players are considerably contributing to the market growth by the adoption of various strategies, including mergers and acquisitions, partnerships, collaborations, and new product launches, to stay competitive in the market. For instance, In 2023, Google AI and OpenAI announced a partnership to develop and deploy generative AI technologies. This partnership brings together two of the leading companies in generative AI research and development. The partnership between Google AI and OpenAI to develop and deploy generative AI technologies is significant because it brings together two of the leading companies in generative AI research and development. This partnership has the potential to accelerate the development of new and innovative generative AI technologies. The two companies could work together to develop new text-to-image diffusion models that are more powerful and versatile than the models that are available today. These new models could be used to generate realistic and creative images for a variety of applications, such as advertising, design, and entertainment.