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.

chatgpt.com is ranked #10 in US with 5.24B Traffic. Categories: AI. Learn more about website traffic, market share, and more!

In March 2025, ChatGPT’s mobile app recorded over 64.26 million App Store and Google Play downloads worldwide. Google's Gemini AI Assistant mobile app was released on February 8, 2024, and was initially available in the U.S. market only. In the same month, the app registered around 13.92 million downloads. Regional preferences shape AI app adoption ChatGPT has a strong global presence with over 400.61 million monthly active users in February 2025, but regional preferences vary. In the United States, ChatGPT had a 45 percent download market share, compared to Google Gemini's 11 percent. However, Gemini emerged as the preferred generative AI app in India, representing a 52 percent market share. This competitive landscape now also includes Chinese-based players like ByteDance's Doubao and DeepSeek, indicating an even more diverse and evolving AI worldwide ecosystem. The AI-powered revolution in online search The global AI market has experienced substantial growth, exceeding 184 billion U.S. dollars in 2024 and projected to surpass 826 billion U.S. dollars by 2030. This expansion is mirrored in user behavior, with around 15 million adults in the United States using AI-powered tools as their first option for online search in 2024. Additionally, 68 percent of U.S. adults reported the use of AI-powered search engines for exploring new topics in 2024, with another 44 percent of respondents utilizing these tools to learn or explain concepts.

Background/Objectives: Advances in artificial intelligence now allow combined use of large language and vision models; however, there has been limited evaluation of their potential in dietary assessment. This data arose from a study that aimed to evaluate the accuracy of ChatGPT-4 in estimating nutritional content of commonly consumed meals from meal photographs.Methods: Meal photographs (n=114) were uploaded to ChatGPT, and it was asked to identify the foods in each meal, estimate their weight, and estimate the nutrient content of the meals for 16 nutrients for comparison with the known values. There were a total of 39 unique meals with each one photographed 3 times for 3 different portion sizes giving rise to 114 photographs. This dataset is in the form of an excel workbook containing four worksheets. The worksheet titled "ChatGPT Foods & Weights" contains the foods identified by ChatGPT in each of the 114 meal photographs as well as its estimate for the weight of each of those foods. The worksheet titled "Actual Foods & Weights" contains the true foods and weights for each of the meal photographs. The worksheet "ChatGPT Nutrition Estimates" contains ChatGPT's estimates of the nutrition content of each of the 114 meal photographs for 16 different nutrients. The worksheet "Actual Nutrition Content" contains the true nutrition content of the meals in the photographs.

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.

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...

Dataset Card for Dataset Name

  Name

ChatGPT Jailbreak Prompts

  Dataset Summary

ChatGPT Jailbreak Prompts is a complete collection of jailbreak related prompts for ChatGPT. This dataset is intended to provide a valuable resource for understanding and generating text in the context of jailbreaking in ChatGPT.

  Languages

[English]

The development of argumentative text and information comprehension (CoI) skills related to the critical reconstruction of meaning (CT) is crucial in undergraduate education. Especially now in the era of social media and AI-mediated information. Generative AI aids in information creation, but its unconscious use can complicate complex information navigation. Argument maps (AM), commonly used for analyzing analog and static texts, can help visualize, understand, and rework multimodal and dynamic arguments and information.

Stemming from the Vygotskian idea, our study used a design-based research approach on the use of AMs and ChatGPT as socio-technical artifacts to stimulate and support the understanding of information (CoI) and thus the development of critical thinking (CT). The workshop introduced the multimodal element through a 3-group quasi-experiment. The first group dealt with fully analog texts, the second group used maps with multimodal textual modes, and the third group only interacted with ChatGPT. The research focused on comparing the three groups and focusing on the two experimental groups (experimental macro-focus).

The research had three main objectives: 1) to test whether AMs improved students' CoI enhancement and critical processing (CT); 2) to determine whether interaction with ChatGPT supported information reprocessing and critical construction of opinions and assessment tools; and 3) to determine whether interaction with ChatGPT alone, without AMs, still fostered greater integration of information and viewpoints.

Our preliminary analysis showed that AMs improved students' CoI and CT, especially when exposed to multimodal information. ChatGPT interaction increased critical reflection and awareness of AI's role in education. Students using only ChatGPT performed well in argumentative reworking, suggesting that interaction with the chatbot can be effective. However, integrating AMs and ChatGPT could provide optimal support for comprehension and critical thinking skills.

This Zenodo record follows the full analysis process with R (https://cran.r-project.org/bin/windows/base/ ) and Nvivo (https://lumivero.com/products/nvivo/) composed of the following datasets, script and results:

1. Comprehension of Text and AMs Results - Arg_Map.xlsx

2. Critical Thinking level - CriThink.xlsx

3. Descriptive and Inferential Statistics Comprehension and Critical Thinking - Preliminary Analysis.R

4. Elaboration and Integration Opinion - Opi_G1.xlsx; Opi_G2.xlsx & Opi_G3.xlsx

5. Descriptive and Inferential Statistics Opinion level - Preliminary Analysis_opi.R

6. Sentiment Analysis - Sentiment Analysis.R

7. Vocabulary Frequent words - Vocabulary.csv

8. Codebook qualitative Analysis with Nvivo (Codebook.xlsx)

9. Results Nvivo Analysis G1 & G2 - Codebook-ChatGPT_G1&G2.docx

Any comments or improvements are welcome!

Argumentative skills are indispensable both personally and professionally to process complex information (CoI) relating to the critical reconstruction of meaning through critical thinking (CT). This remains a particularly relevant priority, especially in the age of social media and artificial intelligence-mediated information. Recently, the public dissemination of what has been called generative artificial intelligence (GenAI), with the particular example of ChatGPT (OpenAI, 2022), has made it even easier today to access and disseminate information, written or not, true or not. New tools are needed to critically address post-digital information abundance.

In this context, argumentative maps (AMs), which are already used to develop argumentative skills and critical thinking, are studied for multimodal and dynamic information visualization, comprehension, and reprocessing. In this regard, the entry of generative AI into university classrooms proposes a novel scenario of multimodality and technological dynamism.

Building on the Vygotskian idea of mediation and the theory of "dual stimulation" as applied to the use of learning technologies, the idea was to complement AMs with the introduction of a second set of stimuli that would support and enhance individual activity: AI-mediated tools. With AMs, an attempt has been made to create a space for understanding, fixing, and reconstructing information, which is important for the development of argumentative skills. On the other hand, by arranging forms of critical and functional interaction with ChatGPT as an ally in understanding, reformulating, and rethinking one's argumentative perspectives, a new and comprehensive argumentative learning process has been arranged, while also cultivating a deeper understanding of the artificial agents themselves.

Our study was based on a two-group quasi-experiment with 27 students of the “Research Methods in Education” course, to explore the role of AMs in fixing and supporting multimodal information reprocessing. In addition, by predicting the use of the intelligent chatbot ChatGPT, one of the most widely used GenAI technologies, we investigated the evolution of students' perceptions of its potential role as a “study companion” in information comprehension and reprocessing activities with a path to build a good prompt.

Preliminary analyses showed that in both groups, AMs supported the increase in mean CoI and CT levels for analog and digital information. However, the group with analog texts showed more complete reprocessing.The interaction with the chatbot was analyzed quantitatively and qualitatively, and there emerged an initial positive reflection on the potential of ChatGPT and increased confidence in interacting with intelligent agents after learning the rules for constructing good prompts.

This Zenodo record follows the full analysis process with R (https://cran.r-project.org/bin/windows/base/ ) and Nvivo (https://lumivero.com/products/nvivo/) composed of the following datasets, script and results:

1. Comprehension of Text and AMs Results - Arg_G1.xlsx & Arg_G2.xlsx

2. Opinion and Critical Thinking level - Opi_G1.xlsx & Opi_G2.xlsx

3. Data for Correlation and Regression - CorRegr_G1.xlsx & CorRegr_G2.xlsx

4. Interaction with ChatGPT - GPT_G1.xlsx & GPT_G2.xlsx

5. Descriptive and Inferential Statistics Comprehension and AMs Building - Analysis_RES_Comprehension.R

6. Descriptive and Inferential Statistics Opinion and Critical Thinking level - Analysis_RES_Opinion.R

7. Correlation and Regression - Analysis_RES_CorRegr.R

8. Descriptive and Inferential Statistics Interaction with ChatGPT - Analysis_RES_ChatGPT.R

9. Sentiment Analysis - Sentiment Analysis_G1.R & Sentiment Analysis_G2.R

10. Vocabulary Frequent words - Vocabulary.csv

11. Codebook qualitative Analysis with Nvivo (Codebook.xlsx)

12. Results Nvivo Analysis G1 - Codebook - ChatGPT2 G1.docx

13. Results Nvivo Analysis G2 - Codebook - ChatGPT2 G2.docx

Any comments or improvements are welcome!

Comparison of Seconds to Output 500 Tokens, including reasoning model 'thinking' time; Lower is better by Model

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.

Comprehensive comparison of Latency (Time to First Token) vs. Output Speed (Output Tokens per Second) by Model

Comprehensive comparison of Output Speed (Output Tokens per Second) vs. Price (USD per M Tokens) by Model

Energy consumption of artificial intelligence (AI) models in training is considerable, with both GPT-3, the original release of the current iteration of OpenAI's popular ChatGPT, and Gopher consuming well over ********** megawatt hours of energy simply for training. As this is only for the training model it is likely that the energy consumption for the entire usage and lifetime of GPT-3 and other large language models (LLMs) is significantly higher.

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

Snapshot img

Chatbot Market Size 2025-2029

The chatbot market size is forecast to increase by USD 9.63 billion, at a CAGR of 42.9% between 2024 and 2029. Several benefits associated with using chatbots solutions will drive the chatbot market.

Major Market Trends & Insights

APAC dominated the market and accounted for a 37% growth during the forecast period.
By End-user - Retail segment was valued at USD 210.60 billion in 2023
By Product - Solutions segment accounted for the largest market revenue share in 2023

Market Size & Forecast

Market Opportunities: USD 1.00 billion
Market Future Opportunities: USD 9.63 billion 
CAGR : 42.9%
APAC: Largest market in 2023

Market Summary

The market is a dynamic and evolving landscape, characterized by the integration of advanced technologies and innovative applications. Core technologies such as natural language processing (NLP) and machine learning (ML) enable chatbots to understand and respond to user queries in a conversational manner, transforming customer engagement across industries. However, the lack of standardization and awareness surrounding chatbot services poses a challenge to market growth. As of now, chatbots are increasingly being adopted in various sectors, including healthcare, finance, and e-commerce, with customer service being the primary application. According to recent estimates, over 50% of businesses are expected to invest in chatbots by 2025.
In terms of service types, chatbots can be categorized into rule-based and AI-powered, each offering unique benefits and challenges. Key companies, such as Microsoft, IBM, and Google, are continuously pushing the boundaries of chatbot technology, introducing new features and capabilities. Regulatory frameworks, including GDPR and HIPAA, play a crucial role in shaping the market landscape. Looking ahead, the forecast period presents significant opportunities for growth, as chatbots continue to reshape the way businesses interact with their customers. Related markets such as voice assistants and conversational AI also contribute to the broader context of the market.
Stay tuned for more insights and analysis on this continuously unfolding market.

What will be the Size of the Chatbot Market during the forecast period?

Get Key Insights on Market Forecast (PDF) Request Free Sample

How is the Chatbot Market Segmented and what are the key trends of market segmentation?

The chatbot industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

End-user

  Retail
  BFSI
  Government
  Travel and hospitality
  Others


Product

  Solutions
  Services


Deployment

  Cloud-Based
  On-Premise
  Hybrid


Application

  Customer Service
  Sales and Marketing
  Healthcare Support
  E-Commerce Assistance


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    UK


  Middle East and Africa

    Egypt
    KSA
    Oman
    UAE


  APAC

    China
    India
    Japan


  South America

    Argentina
    Brazil


  Rest of World (ROW)

By End-user Insights

The retail segment is estimated to witness significant growth during the forecast period.

The market is experiencing significant growth, with adoption in various sectors escalating at a remarkable pace. According to recent reports, the chatbot industry is projected to expand by 25% in the upcoming year, while current market penetration hovers around 27%. This growth can be attributed to the increasing adoption of conversational AI platforms in customer service and e-commerce applications. Unsupervised learning techniques and machine learning models play a pivotal role in chatbot development, enabling natural language processing and understanding. Dialog management systems, including F1-score calculation and dialogue state tracking, ensure effective conversation flow. Human-in-the-loop training and contextual understanding further enhance chatbot performance.

Natural language generation, intent recognition technology, and knowledge graph integration are essential components of advanced chatbot systems. Multi-lingual chatbot support and speech-to-text conversion cater to a diverse user base. Reinforcement learning methods and deep learning algorithms enable chatbots to learn and improve from user interactions. Chatbot development platforms employ various data augmentation methods and active learning strategies to create training datasets for transfer learning applications. Question answering systems and voice-enabled chatbot features provide seamless user experiences. Sentiment analysis techniques and user interface design contribute to enhancing customer engagement and satisfaction. Conversational flow design and response generation models ensure e

Comparison of Image Input Price: USD per 1k images at 1MP (1024x1024) by Model

Comprehensive comparison of Artificial Analysis Intelligence Index vs. Output Speed (Output Tokens per Second) by Model

Comparison of Cost (USD) to run all evaluations in the Artificial Analysis Intelligence Index by Model