Global Generative AI market growth report 2023-2028

Moreover, in healthcare, generative AI may facilitate the synthesis of new drug compounds, assist in medical imaging analysis, or help in the generation of personalized treatment plans. However, a significant concern is the potential for malicious use, such as generating realistic but fake media content for spreading misinformation or conducting scams. The generative AI landscape is rapidly evolving due to various developments by leading companies in the field. Nowadays, the Yakov Livshits leading market players are developing new models, refining existing ones, and introducing innovative techniques to enhance the quality and diversity of generated content. They are also investing in research and development efforts to improve image and video synthesis, enabling applications such as virtual reality, gaming, content creation, and special effects. Besides this, various key players are focused on making generative AI more accessible to a broader range of users.

Thus, implementing use cases such as VR games and VR training simulations has significant efficiencies. Therefore, the first deployments of AI in business will likely focus on augmenting human AI with a workforce (human employees working with intelligent virtual assistants or cobots). This could solve challenges in customer service, content creation, entertainment, e-commerce, etc. This could increase productivity in creative and content production, states Wavemaker India’s report.

Artificial Intelligence for IT Operations Platform Market

The multi-modal generative model is expected to witness the fastest growth rate of 41.6% during the forecast period. The multi-modal generative model can achieve greater accuracy and robustness by combining data from multiple modalities, Yakov Livshits propelling the segment’s growth. Image & video model will grow at a significant rate as it can assist in rapidly creating high-quality, realistic images & videos, which are difficult or impossible to achieve using traditional methods.

• In addition, generative AI systems consume large amounts of data that can be biased, poorly controlled, of dubious origin, or used without authorization.
• The rising innovation of cloud storage, thereby enabling easier access to data will also lead to an increase in the demand for generative AI.
• Generative AI models for image and art generation can quickly produce realistic images of high quality, which is challenging or impossible to achieve with conventional techniques.
• Deep learning techniques, such as generative adversarial networks (GANs) and recurrent neural networks (RNNs), have evolved greatly in recent years.

Generative AI is artificial intelligence technology that produces text, images, or other media based on user-generated inputs. Generative AI uses generative models to learn the pattern and structure of users’ input data and generate output that has similar characteristics. Generative AI finds applications Yakov Livshits in various industries, including art, writing, software development, product design, healthcare, finance, gaming, marketing, and fashion. Hence, by utilizing these models, companies can now automate and improve different processes, such as customer service, content creation, and data analysis.

Generative AI Market Size — Global Industry, Share, Analysis, Trends and Forecast 2022 — 2030

We at Polaris are obliged to serve PMR’s diverse customer base present across the industries of healthcare, technology, semi-conductors and chemicals among various other industries present around the world. Adept with a highly competent, experienced and extremely qualified team of experts comprising SMEs, analysts and consultants, we at Polaris endeavor to deliver value-added business solutions to PMR’s customers. In healthcare, generative AI is being used to expedite drug discovery, enhance medical imaging analysis, and assist in disease diagnosis. The finance sector has embraced generative AI for tasks like algorithmic trading, fraud detection, and risk assessment. In the entertainment industry, generative AI has revolutionized content creation, generating realistic images, videos, and music. Marketing and advertising have benefited from generative AI through personalized recommendations, customer segmentation, and creative content generation.

Yakov Livshits
Founder of the DevEducation project
A prolific businessman and investor, and the founder of several large companies in Israel, the USA and the UAE, Yakov’s corporation comprises over 2,000 employees all over the world. He graduated from the University of Oxford in the UK and Technion in Israel, before moving on to study complex systems science at NECSI in the USA. Yakov has a Masters in Software Development.

Such complex scenarios impede the demand for generative AI among organizations, which further hamper the market. In addition, the high cost of implementing advanced AI technology in organizations with limited financial systems further slows down market growth. Rapid Adoption of Generative AI for Interactive Experience in Media & Entertainment Industry — Generating AI has the potential to revolutionize the media & entertainment industry in the future. Due to this, the industry is rapidly adopting this technology to create captivating visuals, generate stories & music, program video games, etc., to offer an interactive experience that is more immersive, personal, and dynamic to the consumer. Therefore, media & entertainment companies are planning to invest in this technology to reduce the developing time of the content, which results in the low operation cost for the companies.

Consumer Technology Overview

The region is home to some of the world’s fastest-growing economies and has witnessed significant advancements in AI technologies, including Generative AI. Asia Pacific is a hub for AI startups and innovative companies focusing on AI technology. These startups are developing cutting-edge AI solutions, including generative adversarial networks (GANs), deep learning models, and creative AI platforms. Further, Asia Pacific has a significant population and large consumer base, creating demand for AI-powered products and services. The machine learning segment is expected to register a robust revenue CAGR during the forecast period.

Therefore, many data-centric productions necessitate generative AI because it improves the efficiency of almost any business operation. The Synthetic Data Generation segment is anticipated to be the fastest-growing segment during the forecast period. The growth is majorly due to the increasing demand for high-quality training data to build accurate and robust AI models to help organizations generate large and diverse datasets for a wide range of applications.

Transformers, which were initially developed for natural language processing tasks, have acquired popularity due to their capacity to capture long-range dependencies and generate coherence. During the generation process, they employ a self-attention mechanism that enables them to fixate on various parts of the input sequence. By leveraging generative AI, organizations can streamline processes, enhance decision-making, and automate tasks, leading to improved productivity and cost-effectiveness. The operations segment encompasses diverse areas such as supply chain management, logistics, resource allocation, and risk assessment, where generative AI’s capabilities offer transformative benefits. A significant focal point within the realm of generative AI revolves around the necessity to thoroughly scrutinize the data or content generated by specific models.