ChatGPT has taken the world by storm, setting a record for the fastest app to reach a 100 million users, which it hit in two months. The implications of this tool are far-reaching, universities...

ChatGPT is used most widely among those between ** and ** around the world. The youngest group, those under **, are the second largest userbase, and together those under ** account for over ** percent of ChatGPT users. It is perhaps unsurprising that the younger age brackets use the chatbot more than older as that is the common trend with new technologies. Male users were far more numerous than female users, with males representing over ** percent of total users in 2023.

In March 2025, ChatGPT.com received approximately *** billion visits from users worldwide. The most recent year under analysis has seen an increase in traffic to OpenAI's artificial intelligence chatbot. This is the highest traffic volume achieved by the site to date, with values for the most recent analyzed month exceeding twice the average monthly visits for the entire examined period between April 2023 and April 2024.

Introduction

OpenAI Statistics: OpenAI, Inc. is an AI company based in San Francisco, California, and was started in December 2015. Its main goal is to build powerful and safe AI systems. OpenAI wants to create smart machines, called AGI, that can do most jobs better than humans, especially the ones that add economic value. This is also best known for developing advanced AI tools like ChatGPT, designed to solve real-world problems and improve daily life. Its mission is to make powerful AI available to everyone in a way that benefits society.

This article includes several current statistical analyses that are taken from different insights, which will guide in understanding the topic effectively as it covers the overall market, sales, user demographics, usage shares, website traffic, and many other factors.

A chatbot from Chinese AI lab DeepSeek sent shockwaves through the market in January, due to its ability to perform mathematics, coding and reasoning at a similar level to ChatGPT and other top-tier...

IntroductionIn recent years, numerous AI tools have been employed to equip learners with diverse technical skills such as coding, data analysis, and other competencies related to computational sciences. However, the desired outcomes have not been consistently achieved. This study aims to analyze the perspectives of students and professionals from non-computational fields on the use of generative AI tools, augmented with visualization support, to tackle data analytics projects. The focus is on promoting the development of coding skills and fostering a deep understanding of the solutions generated. Consequently, our research seeks to introduce innovative approaches for incorporating visualization and generative AI tools into educational practices.MethodsThis article examines how learners perform and their perspectives when using traditional tools vs. LLM-based tools to acquire data analytics skills. To explore this, we conducted a case study with a cohort of 59 participants among students and professionals without computational thinking skills. These participants developed a data analytics project in the context of a Data Analytics short session. Our case study focused on examining the participants' performance using traditional programming tools, ChatGPT, and LIDA with GPT as an advanced generative AI tool.ResultsThe results shown the transformative potential of approaches based on integrating advanced generative AI tools like GPT with specialized frameworks such as LIDA. The higher levels of participant preference indicate the superiority of these approaches over traditional development methods. Additionally, our findings suggest that the learning curves for the different approaches vary significantly. Since learners encountered technical difficulties in developing the project and interpreting the results. Our findings suggest that the integration of LIDA with GPT can significantly enhance the learning of advanced skills, especially those related to data analytics. We aim to establish this study as a foundation for the methodical adoption of generative AI tools in educational settings, paving the way for more effective and comprehensive training in these critical areas.DiscussionIt is important to highlight that when using general-purpose generative AI tools such as ChatGPT, users must be aware of the data analytics process and take responsibility for filtering out potential errors or incompleteness in the requirements of a data analytics project. These deficiencies can be mitigated by using more advanced tools specialized in supporting data analytics tasks, such as LIDA with GPT. However, users still need advanced programming knowledge to properly configure this connection via API. There is a significant opportunity for generative AI tools to improve their performance, providing accurate, complete, and convincing results for data analytics projects, thereby increasing user confidence in adopting these technologies. We hope this work underscores the opportunities and needs for integrating advanced LLMs into educational practices, particularly in developing computational thinking skills.

The AI Image Generator Market size was valued at USD 356.1 USD Million in 2023 and is projected to reach USD 1094.58 USD Million by 2032, exhibiting a CAGR of 17.4 % during the forecast period. AI image generator refers to a software application for generating image data by means of artificial intelligence, utilizing such models as deep learning, neural networks, and others. Some of them are GANs which stand for Generative Adversarial Networks, VAEs which stand for Variational Autoencoders, and diffusion models. Essential characteristics include crystal clear display of the resultant image, conversion of the source image to another style, and image improvement. It makes use for the generation of art, designing, virtual fitting, and even in-game design . These generators facilitate the quickly and cheaply generated visualization and image modifications depending on certain parameters or styles, hence changing the creative landscapes of various industries by improving efficiency and creativity. Recent developments include: September 2023 - OpenAI, a company specializing in the generative AI industry, introduced DALL-E 3, the latest version of its image generator. This upgrade, powered by the ChatGPT controller, produces high-quality images based on natural-language prompts and incorporates ethical safeguards., May 2023 - Stability AI introduced StableStudio, an open-source version of its DreamStudio AI application, specializing in converting text into images. This open-source release enabled developers and creators to access and utilize the technology, creating a wide range of applications for text-to-image generation., April 2023 - VanceAI launched an AI text-to-image generator called VanceAI Art Generator, powered by Stable Diffusion. This tool could interpret text descriptions and generate corresponding artworks. Users could combine image types, styles, artists, and adjust sizes to transform their creative ideas into visual art., March 2023 - Adobe unveiled Adobe Firefly, a generative AI tool in beta, catering to users without graphic design skills, helping them to create images and text effects. This announcement coincided with Microsoft’s launch of Copilot, offering automatic content generation for 365 and Dynamics 365 users. These advancements in generative AI provided valuable support and opportunities for individuals facing challenges related to writing, design, or organization., March 2023 - Runway AI introduced Gen-2, a combination of AI models capable of producing short video clips from text prompts. Gen-2, an advancement over its predecessor Gen-1, would generate higher-quality clips and provide users with increased customization options.. Key drivers for this market are: Growing Adoption of Augmented Reality (AR) and Virtual Reality (VR) to Fuel the Market Growth. Potential restraints include: Concerns related to Data Privacy and Creation of Malicious Content to Hamper the Market. Notable trends are: Growing Implementation of Touch-based and Voice-based Infotainment Systems to Increase Adoption of Intelligent Cars.

The global Artificial Intelligence (AI) in Supply Chain Market size was valued at USD 51.35 billion in 2025 and is projected to expand at a compound annual growth rate (CAGR) of 7.80% from 2025 to 2033, reaching a value of USD 93.47 billion by 2033. The growth of the market is attributed to the increasing adoption of AI technologies by businesses to improve their supply chain efficiency and optimize operations. Factors such as the rising demand for real-time data analysis, predictive analytics, and automation in the supply chain are driving the market growth. Additionally, government initiatives and investments in AI research and development are further contributing to the market expansion. The market for AI in Supply Chain is segmented based on component, end-user, and technology. The software segment held the largest market share in 2025, owing to the increasing adoption of software solutions for data analysis, forecasting, and optimization in the supply chain. The manufacturing end-user segment is expected to witness the highest growth rate during the forecast period due to the increasing implementation of AI technologies to improve production efficiency and reduce costs. Machine learning and natural language processing are the key technologies driving the growth of the AI in Supply Chain Market. Recent developments include: The recent rise of artificial intelligence (AI) has given the sector fresh optimism, and one particular technology, ChatGPT, is showing a lot of potential. The ChatGPT language model was developed by OpenAI to generate human-like responses to questions posed in natural language. It has been trained on a large amount of data, identifying patterns and producing solutions that are extremely accurate and pertinent to the situation. Just a few months after going live, the site had more than 100 million signups. ChatGPT has already shown enormous promise in the fields of healthcare and finance, and it is ready to change supply chain management for startups., Actyv.ai, a category pioneer in the enterprise SaaS with embedded B2B BNPL and insurance arena with headquarters in Singapore, announced a strategic agreement with PwC India in March 2023 to promote embedded finance adoption in supply chain ecosystems for their clients. In addition to facilitating access to pertinent embedded financial and insurance products, the partnership seeks to concentrate on using the potential of artificial intelligence to spur growth prospects in the global supply chain ecosystem.. Key drivers for this market are: Increasing market growth of E-commerce, Increasing growth in big data technology; High demand for advanced solutions for transparency in supply chain process. Potential restraints include: Lack of technical expertise.

The AI audio glasses market is experiencing rapid growth, driven by increasing demand for hands-free communication and smart assistance features. The market, estimated at $2 billion in 2025, is projected to exhibit a robust Compound Annual Growth Rate (CAGR) of 25% from 2025 to 2033, reaching an estimated $12 billion by 2033. This expansion is fueled by several key drivers. Firstly, technological advancements in AI processing power and miniaturization enable sophisticated features like real-time translation, noise cancellation, and personalized audio experiences within compact wearable devices. Secondly, the growing adoption of smart assistants and the increasing integration of AI into everyday life are significantly boosting demand. Furthermore, the rising popularity of augmented reality (AR) and virtual reality (VR) applications is creating new use cases for AI audio glasses, particularly in fields like gaming and professional training. While high initial costs and potential privacy concerns pose certain restraints, the market’s overall trajectory remains positive. The market is segmented by application (personal and commercial) and type (ChatGPT-based, PanGu AI-based, and others), with the ChatGPT-based segment currently leading in terms of market share due to its extensive functionalities and established user base. Key players like Meta, Huawei, and Amazon are actively investing in research and development, driving innovation and competition within this burgeoning sector. The North American market currently holds a significant share, followed by Asia-Pacific, with growth expected across all regions, particularly in emerging economies driven by increasing smartphone penetration and rising disposable incomes. The diverse applications of AI audio glasses span various sectors. In the personal sphere, they provide enhanced convenience and accessibility for communication and information access. Commercial applications are rapidly expanding, finding utility in logistics, healthcare, and manufacturing for hands-free operation and improved worker efficiency. The "other" category encompasses emerging technologies and niche applications that are likely to gain prominence in the coming years, including advanced biometric sensing and integration with other wearables. Future growth will depend on continued innovation in AI algorithms, improved battery life, refined design, and addressing concerns related to data privacy and security to ensure widespread adoption. The competitive landscape is dynamic, characterized by established tech giants and innovative startups vying for market dominance through product differentiation and strategic partnerships. The ongoing evolution of AI capabilities and the ever-expanding demand for seamless integration of technology into daily life are poised to propel further growth in this exciting and evolving market.

The AI office software market is experiencing explosive growth, driven by the increasing adoption of artificial intelligence across various business functions. The market, currently estimated at $15 billion in 2025, is projected to achieve a Compound Annual Growth Rate (CAGR) of 25% from 2025 to 2033, reaching approximately $75 billion by 2033. This significant expansion is fueled by several key factors. Businesses are increasingly leveraging AI-powered tools for content creation, enhancing efficiency and productivity. Knowledge management systems incorporating AI are improving information retrieval and collaboration, streamlining workflows and reducing operational costs. The automation of tasks such as meeting minutes generation through AI is also contributing to market growth, freeing up employee time for more strategic activities. The shift towards cloud-based solutions simplifies deployment and accessibility, further boosting market adoption. While data security concerns and the need for skilled personnel to manage AI systems present some challenges, the overall market trajectory remains strongly positive. The market segmentation reveals a strong preference for cloud-based solutions over on-premise software, reflecting the growing trend towards flexible and scalable IT infrastructure. Within applications, content creation tools are currently leading the market, but we anticipate significant growth in knowledge management and meeting minutes applications in the coming years. North America and Europe currently dominate the market share, reflecting the higher adoption rates of AI technologies in these regions. However, rapidly developing economies in Asia-Pacific are expected to show substantial growth, contributing significantly to the overall market expansion. The competitive landscape is highly dynamic, with both established tech giants (like Google and Meta) and innovative startups (like Jasper and Anyword) vying for market share. The continuous development of more sophisticated and user-friendly AI office software will continue to drive this market’s impressive growth trajectory.

The Large Language Model (LLM) market is experiencing explosive growth, driven by advancements in deep learning and the increasing availability of large datasets. The market, currently estimated at $15 billion in 2025, is projected to achieve a Compound Annual Growth Rate (CAGR) of 40% from 2025 to 2033, reaching an impressive $200 billion by 2033. This rapid expansion is fueled by several key factors. Firstly, the diverse applications of LLMs across various sectors, including chatbots, content creation, language translation, code generation, and even medical diagnosis, are driving substantial demand. Secondly, the continuous improvement in model accuracy and efficiency, with the emergence of models exceeding 100 billion parameters, is attracting significant investment and accelerating adoption. Finally, major tech giants like Google, OpenAI, and Microsoft, along with numerous emerging players, are fueling innovation and competition, making LLMs increasingly accessible and affordable. However, several challenges remain. The high computational cost associated with training and deploying large LLMs presents a significant barrier to entry for smaller companies. Ethical concerns surrounding bias, misinformation, and misuse of LLMs also need careful consideration and mitigation. Regulatory uncertainty around data privacy and intellectual property rights could further impact market growth. Despite these hurdles, the long-term prospects for the LLM market remain exceptionally positive. Ongoing research and development, coupled with increasing demand from diverse industries, suggest that the market will continue its rapid expansion in the coming years, with substantial opportunities for innovation and investment. The segmentation by application and parameter size allows for a nuanced understanding of the market, with the ‘Above 100 Billion Parameters’ segment expected to dominate due to its superior performance capabilities. Geographical expansion, particularly in rapidly developing economies like India and China, will also play a significant role in the market’s overall growth.

The AI Chatting Software market is experiencing robust growth, driven by increasing demand for automated customer service, personalized learning experiences, and advanced healthcare solutions. The market, estimated at $15 billion in 2025, is projected to expand at a Compound Annual Growth Rate (CAGR) of 25% from 2025 to 2033, reaching approximately $75 billion by 2033. This significant expansion is fueled by several key factors. The rising adoption of AI-powered chatbots across various industries, including e-commerce, education, and healthcare, is a primary driver. Businesses are leveraging these chatbots to enhance customer engagement, streamline operations, and reduce costs. Furthermore, advancements in Natural Language Processing (NLP) and Machine Learning (ML) are leading to more sophisticated and human-like chatbot interactions, improving user experience and satisfaction. The increasing availability of cloud-based platforms and APIs is also facilitating wider adoption, lowering the barrier to entry for businesses of all sizes. However, challenges such as data privacy concerns, the need for continuous model training and improvement, and the potential for bias in AI algorithms represent constraints to market growth. Market segmentation reveals strong growth across all application areas, with Commercial Customer Service and Educational Assistance currently leading the way. Key players such as ChatGPT, Dialogflow, and others are actively competing to innovate and capture market share through enhanced features, improved performance, and wider integration capabilities. The geographical distribution of the AI Chatting Software market is diverse, with North America and Europe currently holding significant market share due to early adoption and technological advancements. However, rapid growth is anticipated in the Asia-Pacific region, driven by increasing digitalization and a burgeoning tech-savvy population. Future growth will depend on continued technological advancements in areas like sentiment analysis, emotional intelligence, and multilingual support, as well as the successful addressing of ethical considerations related to AI bias and data security. The market’s future trajectory will also be shaped by regulatory changes and evolving user expectations concerning the level of personalization and human-like interaction. Ultimately, the continued refinement of AI-powered chatbots and their integration into everyday applications promises to drive sustained market expansion in the coming years.

Among the major internet milestones that have appeared in the last few decades ChatGPT, as an online sensation, has been markedly faster at accumulating a million users than any other. This list of, albeit slightly different, major internet services and pieces of technology, demonstrates how quickly ChatGPT accumulated a userbase. While the two leading services discussed here, Netflix and Airbnb, were both competing with existing market structures, ChatGPT has few, if any, rivals in its capacity as a chatbot.

ChatGPT

As a chatbot service, ChatGPT has taken the internet by storm in recent days. Made by the small but successful startup OpenAI, also well known for their art generative artificial intelligence Dall-E, it has accumulated a large number of users and funding, as well as several controversies. Universities have been struggling to tackle essays generated by ChatGPT, with some in Australia claiming that a return to pen and paper might be needed.

iphone As Apple’s most successful product, the iPhone is one of the most heavyweight players in the smartphone market, with dozens of millions of iPhones being shipped every quarter. Indeed, when it comes to smartphone vendor share, Apple is the second largest smartphone vendor in the world after Samsung. Before ChatGPT it had been the phenomenon fastest to one million users.

IntroductionThe recent advances of large language models (LLMs) have opened a wide range of opportunities, but at the same time, they pose numerous challenges and questions that research needs to answer. One of the main challenges are the quality and correctness of the output of LLMs as well as the overreliance of students on the output without critically reflecting on it. This poses the question of the quality of the output of LLMs in educational tasks and what students and teachers need to consider when using LLMs for creating educational items. In this work, we focus on the quality and characteristics of conceptual items developed using ChatGPT without user-generated improvements.MethodsFor this purpose, we optimized prompts and created 30 conceptual items in kinematics, which is a standard topic in high-school level physics. The items were rated by two independent experts. Those 15 items that received the highest rating were included in a conceptual survey. The dimensions were designed to align with the ones in the most commonly used concept inventory, the Force Concept Inventory (FCI). We administered the designed items together with the FCI to 172 first-year university students. The results show that ChatGPT items have a medium difficulty and discriminatory index but they overall exhibit a slightly lower average values as the FCI. Moreover, a confirmatory factor analysis confirmed a three factor model that is closely aligned with a previously suggested expert model.Results and discussionIn this way, after careful prompt engineering, thorough analysis and selection of fully automatically generated items by ChatGPT, we were able to create concept items that had only a slightly lower quality than carefully human-generated concept items. The procedures to create and select such a high-quality set of items that is fully automatically generated require large efforts and point towards cognitive demands of teachers when using LLMs to create items. Moreover, the results demonstrate that human oversight or student interviews are necessary when creating one-dimensional assessments and distractors that are closely aligned with students' difficulties.

The synthetic media software market is experiencing rapid growth, driven by increasing demand for realistic and engaging digital content across various sectors. The market, currently estimated at $2 billion in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 25% from 2025 to 2033, reaching a substantial market value. This robust growth is fueled by several key factors. Firstly, advancements in artificial intelligence (AI) and machine learning (ML) are leading to more sophisticated and cost-effective synthetic media creation tools. Secondly, the rising adoption of synthetic media in advertising, entertainment, and e-learning is significantly boosting market demand. Businesses are leveraging these tools for personalized marketing campaigns, immersive gaming experiences, and interactive educational content. Thirdly, the increasing availability of cloud-based solutions is making synthetic media technology more accessible to small and medium-sized enterprises (SMEs), further fueling market expansion. However, ethical concerns surrounding deepfakes and the potential for misuse of synthetic media remain significant restraints, requiring the development of robust verification and authentication technologies. The market segmentation reveals a strong preference for cloud-based solutions due to their scalability and cost-effectiveness. Large enterprises are leading the adoption, followed by a rapidly growing SME segment. Geographically, North America currently holds the largest market share, driven by early adoption and technological advancements. However, Asia-Pacific is poised for significant growth, fueled by expanding digital economies and increasing investment in AI and related technologies. Key players in the market, including Synthesia, ChatGPT, and Jasper, are continuously innovating and expanding their offerings to meet the evolving needs of diverse industries. Future market growth will hinge on addressing ethical concerns, enhancing the realism and quality of synthetic media, and expanding its applications across new sectors. The continued advancements in AI and ML are expected to further drive market expansion and innovation in the coming years.

Background In recent years, expectant and breastfeeding mothers commonly use various breastfeeding-related social media applications and websites to seek breastfeeding-related information. At the same time, AI-based chatbots-such as ChatGPT, Gemini, and Copilot-have become increasingly prevalent on these platforms (or on dedicated websites), providing automated, user-oriented breastfeeding guidance. Aim The goal of our study is to understand the relative performance of three AI-based chatbots: ChatGPT, Gemini, and Copilot, by evaluating the quality, reliability, readability, and similarity of the breastfeeding information they provide. Methods Two researchers evaluated the information provided by three different AI-based breastfeeding chatbots: ChatGPT version 3.5, Gemini, and Copilot. A total of 50 frequently asked questions about breastfeeding were identified and used in the study, divided into two categories (Baby-Centered Questions and Mother-Centered Questions), and evaluated using five scoring criteria, including the Quality Information Provision for Patients (EQIP) scale, the Simple Measure of Gobbledygook (SMOG) scale, the Similarity Index (SI), the Modified Dependability Scoring System (mDISCERN), and the Global Quality Scale (GQS). Results The evaluation of AI chatbots’ answers showed statistically significant differences across all criteria (p

Comparison of Represents the average of coding benchmarks in the Artificial Analysis Intelligence Index (LiveCodeBench & SciCode) by Model

The automotive voice recognition system market is experiencing robust growth, projected to reach $3.06 billion in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 14.77% from 2025 to 2033. This expansion is driven by several key factors. Increasing consumer demand for enhanced in-car convenience and safety features fuels the adoption of voice-activated controls for navigation, infotainment, and vehicle settings. The integration of advanced features like natural language processing and AI-powered voice assistants further enhances user experience, boosting market appeal. Furthermore, the proliferation of connected cars and the rise of sophisticated telematics systems provide a fertile ground for voice recognition technology deployment. The automotive industry's continuous innovation in this space, coupled with decreasing hardware costs, is making voice recognition systems increasingly accessible across various vehicle segments, including passenger cars and commercial vehicles. The market is segmented by technology (embedded, cloud-based, hybrid) and vehicle class (economy, mid-priced, luxury), offering various options to suit diverse consumer preferences and technological capabilities. The leading players in this market, including established tech giants like Microsoft, Apple, and Google, alongside specialized automotive technology companies, are continuously investing in R&D to improve voice recognition accuracy, natural language understanding, and overall system reliability. This competitive landscape ensures rapid innovation and drives the market's ongoing growth trajectory. The geographical distribution of this market reveals significant regional variations. North America, particularly the United States, holds a substantial market share due to early adoption of advanced technologies and a high concentration of automotive manufacturers. However, the Asia-Pacific region, driven by strong growth in China and India, is expected to witness significant expansion in the coming years. Factors such as increasing vehicle ownership, rising disposable incomes, and the growing adoption of connected car technologies in these regions contribute to their accelerating market share. Europe also maintains a substantial presence, with significant contributions from Germany, the United Kingdom, and France. The market's continuous evolution will necessitate ongoing innovation in areas such as improved voice recognition accuracy in noisy environments, multilingual support, and seamless integration with other in-car systems to maintain its growth momentum. Recent developments include: January 2024: Cerence announced its collaboration with Microsoft to enhance in-car experiences by integrating Microsoft Azure AI Services, including OpenAI’s ChatGPT. This partnership aims to revolutionize voice and touch user interfaces in vehicles by combining Cerence’s automotive expertise with Microsoft’s advanced AI capabilities. The initial focus is on incorporating the ChatGPT model through Azure into Cerence’s in-car assistant platform, Cerence Assistant, to enhance post-purchase value and user experience., October 2023: Lexus introduced its new concept battery electric car, Lexus Future Zero-emission Catalyst, at the Japan Mobility Show 2023, which is equipped with a voice recognition system that employs advanced artificial intelligence technology so it can talk, act, and reply like a personal butler. Further, the company stated that the automated voice learns from the driver’s habits to predict what they want to happen the next time they drive. As soon as it picks up on the drivers' routines and the apps and car functionality they typically use, Butler will activate them without needing to ask them., June 2023: Mercedes-Benz announced that the drivers in the United States will be able to power some of their luxury vehicles with ChatGPT in a three-month test program, which is compatible with 900,000 vehicles with the automaker's "MBUX" voice recognition system. The ChatGPT feature can be downloaded over the air after drivers opt-in via a Mercedes app or by voice command., September 2022: Cerence Inc. and Microsoft Corp. collaborated to enable access to all Microsoft's tools, including Microsoft Teams, using Cerence's voice recognition technologies in the vehicles. Both companies will jointly promote this new solution to automobile OEMs looking to offer the latest voice recognition technologies in their upcoming vehicles.. Key drivers for this market are: Increasing Demand for Luxury and Premium Passenger Cars to Foster Market Growth. Potential restraints include: Increasing Demand for Luxury and Premium Passenger Cars to Foster Market Growth. Notable trends are: Passenger Cars Segment to Gain Traction During the Forecast Period.

The Generative AI in Media and Entertainment Market is poised to experience exponential growth, with a projected market size of $19942.01 million by 2033, exhibiting a remarkable CAGR of 43.2%. This market is driven by the transformative capabilities of generative AI, which automates content creation and opens up new possibilities in storytelling, visual effects, and virtual experiences. The adoption of large language models, digital twins, and natural language generation technologies is revolutionizing content creation processes, enhancing efficiency, and enabling immersive experiences that captivate audiences. The Generative AI in Media and Entertainment Market is segmented into offerings (Solutions and Services), technologies (Natural Language Programming, Digital Twin, Natural Language Generation, Large Language Models, and Others), applications (Gaming, Film and Television, Advertising and Marketing, Music and Sound Production, Automatic Dubbing and Subtitling, Chatbots and Virtual Assistants, and Others), and regions (North America, South America, Europe, Middle East & Africa, and Asia Pacific). Key players in this market include Alphabet, Microsoft, Meta Platforms, Inc., IBM Corporation, Nvidia Corporation, Open AI, Inc., Epic Games, Inc., Amazon, Apple Inc., Adobe Inc., Unity Technologies, Cohere, and Anthropic. The study period extends from 2019 to 2033, with 2025 serving as the base year. Recent developments include: In November 2023, OpenAI has launched GPTs, customized versions of ChatGPT for specific purposes, allowing anyone to create and share tailored AI models without coding. This emphasizes privacy, safety, and community involvement in AI development. In August 2023, OpenAI unveiled ChatGPT Enterprise, providing top-tier security, GPT-4 access, extended context processing, advanced analytics, tailored customization, aiming to enhance productivity and creativity in workplaces. in November 2023, NVIDIA launched an AI foundry service on Microsoft Azure, empowering enterprises and startups to build custom generative AI models. SAP, Amdocs, Getty Images are early adopters, leveraging NVIDIA AI Foundation Models and DGX Cloud on Azure. The collaboration aims to refine, deploy, and optimize tailored large language models (LLMs) for diverse industry applications. . Potential restraints include: Legal and ethical concerns 34. Notable trends are: Growing number of wholesalers are adopting cloud-native software is expected to drive market growth..

Comparison of Represents the average of math benchmarks in the Artificial Analysis Intelligence Index (AIME 2024 & Math-500) by Model