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세계의 AI 이미지 생성기 시장 규모, 점유율 및 동향 분석 보고서 : 구성요소별, 최종 사용자별, 지역별 전망 및 예측(2023-2030년)
Global AI Image Generator Market Size, Share & Trends Analysis Report By Component (Software, and Services), By End-user (Media & Entertainment, Social Media, E-commerce, Fashion, Healthcare, and Others), By Regional Outlook and Forecast, 2023 - 2030
상품코드 : 1431298
리서치사 : KBV Research
발행일 : 2024년 02월
페이지 정보 : 영문 164 Pages
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한글목차

AI 이미지 생성기 시장 규모는 2030년까지 9억 9,680만 달러에 달할 것으로 예상되며, 예측 기간 동안 연평균 17.1%의 시장 성장률을 나타낼 것으로 예상됩니다.

그러나 훈련 데이터 세트의 품질과 다양성은 이러한 생성기의 일반화 효과와 능력에 직접적인 영향을 미칩니다. 훈련 데이터가 불충분하거나 편향된 경우, 모델은 견고성이 떨어지고 정확하고 다양한 이미지를 생성하는 데 어려움을 겪을 수 있습니다. 또한 훈련 데이터가 가능한 입력의 전체 스펙트럼을 대표하지 않는 시나리오에서 이러한 생성기는 다양하거나 특이한 상황에 직면했을 때 어려움을 겪을 수 있습니다. 따라서 이러한 요인은 향후 몇 년동안 이러한 발전기에 대한 수요를 방해할 수 있습니다.

목차

제1장 시장 범위와 조사 방법

제2장 시장 요람

제3장 시장 개요

제4장 세계 시장 : 구성별

제5장 세계 시장 : 최종사용자별

제6장 세계 시장 : 지역별

제7장 기업 개요

제8장 AI 이미지 생성기 시장을 위한 성공 필수 조건

LSH
영문 목차

영문목차

The Global AI Image Generator Market size is expected to reach $996.8 million by 2030, rising at a market growth of 17.1% CAGR during the forecast period.

These generators played a pivotal role in revolutionizing personalized styling recommendations. AI algorithms generated tailored styling suggestions by analyzing user preferences, past purchases, and trends. This improved the overall shopping experience for consumers and helped fashion retailers optimize their inventory management based on real-time insights. Consequently, the fashion segment would acquire nearly 15% of the total market share by 2030. Additionally, these generators contribute to virtual try-on experiences, enabling customers to visualize how clothing items will look on them before making a purchase. By seamlessly integrating AI image generation into the fashion workflow, the industry can streamline design processes, reduce time-to-market, and engage consumers with visually compelling and personalized content.

The driving force behind the evolution of these generators lies in the continuous refinement of generative models. These models are designed to generate new, synthetic data that closely resembles existing datasets. In addition, complementing GANs, variational autoencoders (VAEs) bring a different approach to generative modeling. VAEs operate on the principles of encoding and decoding latent representations of data. Hence, these factors will boost the demand in the market. Additionally, the accelerated pace of AI innovation is significantly influenced by the widespread proliferation of high-performance computing (HPC) resources. These resources encompass supercomputers, clusters, and cloud-based infrastructures with robust processing capabilities. In addition, at the heart of this computational revolution are advanced Graphics Processing Units (GPUs). Initially developed to render graphics in video games, GPUs have since evolved into multipurpose processors that are exceptionally suitable for the parallel processing requirements of machine learning tasks. Therefore, these factors will lead to increased demand in the market.

However, the quality and diversity of the training dataset directly impact the efficacy and capacity for the generalization of these generators. Insufficient or biased training data may result in a model that lacks robustness and struggles to generate accurate and diverse images. In addition, in scenarios where the training data is not representative of the full spectrum of possible inputs, these generators may encounter difficulties when faced with diverse or uncommon situations. Therefore, these factors can hamper the demand for these generators in the coming years.

By Component Analysis

Based on component, the market is segmented into software and services. In 2022, the services segment garnered a significant revenue share in the market. The increasing demand for customized AI image generation solutions has fueled the rise of services catering to the specific needs of businesses. Service providers offer customization to integrate these generators seamlessly into existing workflows, aligning technology with clients' unique requirements across industries. Thus, the segment will expand rapidly in the coming years.

By End-user Analysis

On the basis of end-user, the market is divided into media & entertainment, healthcare, fashion, social media, e-commerce, and others. In 2022, the social media segment witnessed a substantial revenue share in the market. The essence of social media lies in visual content, and platforms are constantly vying for attention through captivating images. These generators, with their ability to produce high-quality and visually appealing content, have become instrumental for individuals, influencers, and businesses aiming to stand out in the crowded social media space. Hence, these factors will pose lucrative growth prospects for the segment.

By Regional Analysis

By region, the market is segmented into North America, Europe, Asia Pacific, and LAMEA. The North America segment procured the highest revenue share in the market in 2022. North America, particularly the United States, boasts a robust technological ecosystem with a concentration of leading tech companies, research institutions, and skilled professionals. This technological prowess was pivotal in driving the development and implementation of AI image-generator technologies. Therefore, the segment will expand rapidly in the upcoming years.

List of Key Companies Profiled

Global AI Image Generator Market Report Segmentation

By Component

By End-user

By Geography

Table of Contents

Chapter 1. Market Scope & Methodology

Chapter 2. Market at a Glance

Chapter 3. Market Overview

Chapter 4. Global AI Image Generator Market by Component

Chapter 5. Global AI Image Generator Market by End-user

Chapter 6. Global AI Image Generator Market by Region

Chapter 7. Company Profiles

Chapter 8. Winning Imperatives of AI Image Generator Market

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