New York, United States, Nov. 29, 2023 (GLOBE NEWSWIRE) -- Generative artificial intelligence (AI), also referred to as generative adversarial networks (GANs), is a subset of artificial intelligence (AI) techniques that involves the creation of new and original content from existing data. In contrast to conventional AI models trained on labeled data for classification or prediction tasks, generative AI focuses on generating new data samples that resemble the original training data. Generative AI has numerous applications in numerous industries. It can create innovative and unique designs, paintings, and sculptures in art and design. It can generate computer-generated imagery (CGI) for movies, video games, and virtual reality experiences. It can assist with drug discovery, genetics research, and medical imaging analysis in healthcare.
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Innovation of Cloud Storage and Government Initiatives Drive the Global Market
Cloud storage altered data storage, retrieval, and management. It influenced numerous industries and markets. Cloud servers remotely store data. Online data can be accessed without the need for storage devices. Consumers and businesses widely utilize cloud storage due to its convenience. Dropbox, Google Drive, and OneDrive pioneer cloud storage innovations. These technologies facilitate the storage, sync, and sharing of device data. Users can share files, communicate in real time, and recover data from malfunctioning devices.
According to Straits Research, "The global generative AI market size was valued at USD 10.3 billion in 2022 and is projected to reach USD 136 billion by 2031, registering a CAGR of 33.2% during the forecast period (2023-2031)." The expansion of the market for generative AI affects cloud storage. As machine learning and deep learning are gaining popularity, numerous governments assist end users in developing new technologies, such as generative AI, for use in various industries. The U.S. General Services Administration (GSA) implemented generative AI and machine learning in August 2022 to improve, manage, and advance procurement. AI and ML with generative capabilities enhance procurement procedures, disclose crucial metrics, and predict procurement patterns. The Chinese government is interested in generative AI due to new funding for COVID-19 advancements. In January 2023, the government assisted Chinese tech companies in developing their AI universe. IDEA, a research institute owned by the Chinese Communist Party, finances numerous local Chinese government programs. Chinese IT companies have also demonstrated AI programs compatible with the country's politics and preferences.
Nevertheless, deep neural networks, such as Generative Adversarial Networks, are indispensable to Generative AI. It frequently disregards fundamental machine learning models that remain pertinent for fraud detection, information security, and business recommendation systems. This results in more data breaches. The CEO of Drizly was culpable for security breaches that exposed the data of 2.5 million users. The FTC will subject Drizly to unprecedented individual data privacy penalties. Consequently, restricting the market expansion of generative AI.
Acceleration of Large Language Models (LLMs) Creates Tremendous Opportunities
LLM implementation enhances market potential. GPT-3, OpenAI's LLM, is capable of human-like writing and comprehension. LLMs may have an impact on numerous industries and applications. LLMs improve content creation, translation, sentiment analysis, and data analysis. LLMs save time and money by creating quality articles, journals, and reports. Real-time language translation also facilitates global business and individual communication. LLMs may aid sentiment analysis, which analyses vast text data to estimate public opinion and consumer feedback. This data may enhance business decisions and customer satisfaction. LLMs are commercially viable due to the expanding market for generative AI and the demand for AI-powered chatbots and virtual assistants. The enhanced infrastructure of hardware makes LLM deployment feasible and scalable.
Regional Insights
North America topped the industry with the largest share in 2022 and is projected to grow at a significant CAGR over the forecast period due to factors such as the rise of pseudo-imagination and medical care and banking fraud. Numerous market participants and government support have made North America the main region for adopting and advancing generative AI. The United States, specifically the Silicon Valley region of California, has been at the forefront of research and development in generative artificial intelligence. Numerous prominent U.S. technology companies and research institutions, including OpenAI, Google, Facebook, NVIDIA, and IBM, have contributed substantially to advancing generative AI technologies. In addition, the National Science Foundation (NSF) of the United States announced the establishment of eleven new NSF National Artificial Intelligence Research Institutes and a USD 140 million investment for their establishment, expanding their reach to forty states and the District of Columbia. In addition, Goldman Sachs Research suggests that advances in Generative artificial intelligence could significantly impact the global economy. As tools utilizing breakthroughs in natural language processing make their way into businesses and society, they could increase the global GDP by 7% (or nearly USD 7 trillion) and enhance economic development by 1.5% over ten years.
The Asia-Pacific region is anticipated to have the maximum CAGR during the forecast period. The increasing number of government initiatives in AI and the rising adoption of AI applications are driving the growth of the AI Market in the Asia-Pacific region. The expansion of the regional Market can also be attributed to the rapid digitization of businesses, which burdens cloud networks and data centers. In addition, AI adoption helps organizations empower civil society members to be knowledgeable and responsible AI device users.
Key Highlights
- Based on the component, the market is divided into Software and Services. The software category will likely generate the most revenue during the forecast period.
- Based on end-user, the market is divided into Media and Entertainment, BFSI, IT and Telecommunication, Healthcare, Automotive, Gaming, and Others. The media and entertainment segment generated the most revenue and is anticipated to grow significantly during the forecast period.
- Based on technology, the market is divided into Generative Adversarial Networks, Transformers, Variational Auto-Encoders, and Diffusion Networks. The transformers segment is the highest contributor to the Market and is estimated to grow significantly during the forecast period.
- Based on application, the market is divided into Computer Vision, NLP, Robotics 7 Automation, Content Generation, Chatbots and Intelligent Virtual Assistants, Predictive Analytics, and Others. The Natural Language Processing (NLP) segment owns the largest market share and is anticipated to grow significantly during the forecast period.
- Based on the model, the market is divided into Large Language Models, Image and Video Generative Models, Multi-Model Generative Models, and Others. Large Language Models are the leading Market and are estimated to grow significantly during the forecast period.
- The global generative AI market is bifurcated based on region into North America, Europe, Asia-Pacific, Latin America, Middle East and Africa. North America dominates the global market.
Competitive Landscape
The key players in the global generative AI market are Google LLC, IBM Corporation, Amazon Web Services, Inc., D-ID, MOSTLY AI Inc., Microsoft Corporation, Rephrase.ai, Genie AI Ltd., Synthesia, Adobe., and Adobe Inc.
Market News
- In July 2023, GA Cloud CDN supported private origin authentication. Allowing only trusted connections to access your private material and prohibiting people from directly accessing it increases security.
- In July 2023, IBM and Truist worked on quantum computing and emerging technology.
Global Generative AI Market: Segmentation
By Component
- Software
- Service
By Technology
- Generative Adversarial Networks (GANs)
- Transformers
- Variational Auto-encoders
- Diffusion Networks
By End-use
- Media and Entertainment
- BFSI
- IT and Telecommunication
- Healthcare
- Automotive and Transportation
- Gaming
- Others
By Application
- Computer Vision
- NLP
- Robotics 7 Automation
- Content Generation
- Chatbots and Intelligent Virtual Assistants
- Predictive Analytics
- Others
By Model
- Large Language Models
- Image and Video Generative Models
- Multi-modal Generative Models
- Others
By Regional
- North America
- Europe
- Asia-Pacific
- Latin America
- The Middle East and Africa
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