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Study and Analysis of Chat GPT and its Impact on Different Fields of Study

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ChatGPT is a revolutionary technology that uses advanced artificial intelligence techniques to generate natural language responses to a given prompt or input. It has been used across various fields, from natural language processing to customer service to content creation. This study and analysis of ChatGPT explore its origins, how it works, and its impact on different fields of study. It examines the advantages and disadvantages of ChatGPT, as well as its limitations and features. It also discusses the impact of ChatGPT on academics, cyber security, customer support, software development, jobs, and information technology, as well as its potential applications for researchers and scholars.
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Volume 8, Issue 3, March 2023 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165
IJISRT23MAR956 www.ijisrt.com 827
Study and Analysis of Chat GPT and its Impact on
Different Fields of Study
Dinesh Kalla (Doctoral Candidate)
Colorado Technical University
Microsoft (Big Data Support Escalation Engineer)
Charlotte, North Carolina
Nathan Smith (Doctoral Candidate)
Colorado Technical University
Collins (Aerospace Principle Technical Publications
Specialist)
San Diego, California
Dr. Sivaraju Kuraku
University of the Cumberlands
Istreetlabs LLC (Principal Security Advisor)
Fairfax, Virginia , USA
Fnu Samaah
Northeastern Illinois University
US Bank (Java Full Stack Developer)
Desplaines, IL
Abstract:- ChatGPT is a revolutionary technology that
uses advanced artificial intelligence techniques to
generate natural language responses to a given prompt or
input. It has been used across various fields, from natural
language processing to customer service to content
creation. This study and analysis of ChatGPT explore its
origins, how it works, and its impact on different fields of
study. It examines the advantages and disadvantages of
ChatGPT, as well as its limitations and features. It also
discusses the impact of ChatGPT on academics, cyber
security, customer support, software development, jobs,
and information technology, as well as its potential
applications for researchers and scholars.
Keywords:- ChatGPT; Chatbot; AI; RLHF; Natural
Language; NLP; Open AI; Bard; SFT Model; RM Model;
PPO.
I. INTRODUCTION
Have you ever interacted with a chatbot that seemed
almost human-like in its responses? Or have you used a
language translation tool that accurately translated complex
sentences and phrases? If so, you may have experienced the
power of ChatGPT - a revolutionary technology transforming
how we communicate with machines and each other.
Developed by OpenAI, ChatGPT is a language model that
uses advanced artificial intelligence techniques to generate
natural language responses to a given prompt or input. Its
impact has been felt across various fields, from natural
language processing to customer service to content creation.
In this study and analysis of ChatGPT, we will explore its
origins, how it works, and its impact on different fields of
study. Join us as we delve into the fascinating world of
ChatGPT and discover how it is changing our lives.
II. IMPLEMENTATION AND WORKING OF
CHATGPT
ChatGPT is implemented through a deep neural
network architecture that consists of several layers of
transformers. These transformers are designed to process
sequential data, such as natural language text, and can
generate coherent and human-like outputs. To train ChatGPT,
a large corpus of text data is fed into the model, allowing it to
learn patterns and relationships between words, phrases, and
sentences. The training process is iterative, and the model
continues to improve as it is exposed to more data [8]. Once
trained, ChatGPT can be fine-tuned for specific applications
or tasks, such as language translation or content generation.
The working of ChatGPT can be broken down into
several steps. First, the user inputs a prompt or question into
the system. The model processes this prompt, which uses its
knowledge of language patterns and relationships to generate
a response. The response is then returned to the user, who can
continue the conversation or ask another question. This
method is entirely trained by Reinforcement learning from
human feedback.
SFT Model: It is a supervised fine-tuning model where
demonstration data is accumulated to train it.
RM Model: The reward model will give points to the SFT
model output based on how desirable the output is for
users.
SFT Model via PPO: SFT Policy is fine-tuned by
reinforcement learning by letting it optimize the RM.
PPO refers to fined tuned model of proximal policy
optimization.
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Fig 1: RLHF Training Method of ChatGPT
The key to ChatGPT's success is its ability to generate
coherent and natural-sounding responses. Transformers
achieve this by allowing the model to process and generate
text sequences. The model is also trained on a massive corpus
of text data, which helps it learn the nuances of language and
generate contextually appropriate responses.
The implementation and working of ChatGPT are
complex and sophisticated. However, the result is a
technology that can generate human-like responses to various
prompts and questions. As ChatGPT continues to evolve and
improve, we expect to see more special applications and use
cases emerge.
III. ADVANTAGES AND DISADVANTAGES OF
CHATGPT
Advancements in artificial intelligence have led to the
development of Chat GPT, a revolutionary technology that
generates human-like responses to natural language prompts.
While Chat GPT has numerous advantages, such as natural
language generation and scalability, its fair share of
disadvantages must be considered. In this section, we will
explore the advantages and disadvantages of Chat GPT in
more detail.
A. Advantages of ChatGPT
One advantage of ChatGPT is its natural language
generation capability, which enables it to generate human-
like and coherent responses. This feature is particularly
useful for applications where natural language is essential,
such as customer service chatbots and language translation.
ChatGPT's ability to produce more human-like responses
than other natural language processing models, such as rule-
based approaches, can lead to more meaningful and engaging
conversations with users, resulting in better user experience
and satisfaction.
Another advantage of ChatGPT is its scalability, which
allows it to generate responses quickly and handle a large
volume of conversations simultaneously. This scalability
makes it an ideal tool for businesses and organizations
requiring automated customer service or language translation
services, as it reduces human intervention and increases
efficiency. ChatGPT's ability to handle multiple
conversations simultaneously can lead to faster response
times, ultimately improving user satisfaction.
ChatGPT's customizability is another critical advantage.
It can be fine-tuned to perform specific tasks or applications,
such as customer service or language translation, by adjusting
its training data and algorithms [5]. This flexibility ensures
that ChatGPT's responses are tailored to the specific needs of
the user's needs, making it a highly flexible and versatile tool.
Customizability also enables businesses and organizations to
create more personalized customer experiences, ultimately
improving customer satisfaction and loyalty.
Efficiency is yet another advantage of ChatGPT. Its
ability to generate responses quickly and handle multiple
conversations at once means it can process large amounts of
information in a short amount of time [5]. Efficiency is
particularly valuable in tasks such as customer service or
language translation, where human intervention may be time-
consuming and costly. ChatGPT can help businesses and
organizations save time and money by automating these
processes, increasing productivity and profitability.
B. Disadvantages of ChatGPT
One disadvantage of ChatGPT is the potential for bias
in its responses. Because it is trained on large datasets of text
data, biases and inaccuracies within that data can be reflected
in its responses. This can result in ChatGPT's responses
perpetuating stereotypes or discrimination within the training
data. To minimize bias, selecting and curating the training
data carefully and continually monitoring ChatGPT's
responses to identify and correct potential biases is essential.
Another disadvantage of ChatGPT is its need for more
emotional intelligence. In human conversation, it may
struggle to recognize and respond to emotional cues, such as
sarcasm or humor. This can result in ChatGPT's responses
becoming tone-deaf or insensitive, which can be frustrating
or off-putting for users. To address this issue, it may be
necessary to incorporate additional programming or training
data to help ChatGPT better understand and respond to
emotional cues.
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Fig 2: ChatGPT Showing False Response
ChatGPT's limited knowledge base is also a
disadvantage. Its responses are limited to the knowledge
acquired through training data, meaning it may need help
with unfamiliar or highly specialized topics [5]. This can
result in ChatGPT providing inaccurate or unhelpful
responses to user queries, which can be frustrating and lead
to a negative user experience. To address this issue, it may be
necessary to supplement ChatGPT's training data with
additional sources of information or to use alternative tools in
situations where ChatGPT's knowledge is insufficient.
ChatGPT's lack of empathy is a potential disadvantage.
It may need to empathize with users or provide a different
level of support and understanding than a human customer
service representative could provide. The lack of empathy
can make users feel frustrated or unheard, ultimately leading
to a negative experience. To mitigate this issue, it may be
necessary to incorporate additional programming or training
data to help ChatGPT better understand and respond to the
emotional needs of users or to use ChatGPT in conjunction
with human customer service representatives to provide a
more empathetic and personalized user experience.
IV. LIMITATIONS AND FEATURES OF CHATGPT
A. Limitations of ChatGPT
Chat GPT has the limitation of offering limited dialogue
options to users, which can restrict their ability to engage in
meaningful conversations. While it can generate natural
responses, they are still limited to a predetermined set of
options, which can feel restrictive and unsatisfying for some
users.
As an AI language model, Chat GPT may struggle with
certain aspects of natural language processing, making it
difficult for users to understand or interpret its responses
[13]. Despite its sophisticated algorithms and extensive
training, Chat GPT may still need help understanding the
nuances of human language, which can lead to
misinterpretations and misunderstandings.
Chat GPT lacks context, which means it may be unable
to understand the context of a conversation and may give
inaccurate responses. With an understanding of the context, it
can be easier for Chat GPT to provide relevant and helpful
responses to user queries.
Chat GPT's responses are limited by the domain
knowledge it has acquired through its training data [13]. As a
result, it may need help with highly specialized or niche
topics. This limitation can make Chat GPT less useful for
users seeking information on specific topics outside its
domain.
Chat GPT may not be able to recognize or respond
appropriately to emotional cues, such as sarcasm or humor.
While it can generate responses that sound natural, it cannot
understand the emotional context of a conversation, which
can lead to inappropriate or insensitive responses.
B. Features of ChatGPT
Automated Conversations: Chat GPT facilitates
automated conversations, allowing users to interact with a
chatbot without needing a human operator. The system
can generate responses quickly and accurately based on
patterns and relationships in the data it has been trained
on. It is an efficient tool for businesses and organizations
that require automated customer service or language
translation services.
Improved Customer Service: Chat GPT can significantly
improve customer service by providing quick and
accurate responses to user queries[5]. This can increase
customer satisfaction and loyalty, as users can promptly
receive the support they need.
Cost-Effective Solution: Chat GPT is a cost-effective
solution, as it eliminates hiring human operators to
conduct customer service conversations. This can result in
significant cost savings for businesses, especially those
that handle a high volume of customer service queries.
Natural Language Processing: Chat GPT uses natural
language processing algorithms to understand and
respond to natural language. This means that it can
interpret and respond to user queries in a way that mimics
human conversation, making it a highly intuitive tool for
users.
Personalized Responses: Chat GPT can provide
personalized responses by remembering user preferences
and tailoring its responses accordingly[5]. This feature
can help create a more engaging and satisfying user
experience, as users feel the system can understand and
respond to their unique needs.
Customizability: ChatGPT can be customized for specific
tasks or applications by adjusting its training data and
algorithms. This flexibility allows businesses and
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organizations to tailor Chat GPT's responses to their
specific needs, making simultaneously g it a highly
adaptable and versatile t
Scalability: Chat GPT is highly scalable, meaning that
once trained, it can handle a large volume of
conversations simultaneously. This makes it ideal for use
in large-scale applications, where it can efficiently
process large amounts of information quickly.
Language Translation: Chat GPT can translate text
between different languages, making it a valuable tool for
global communication. The system can accurately
translate text in real time, providing a seamless and
efficient way for users to communicate across language
barriers.
V. ALTERNATIVES OF CHATGPT
Several alternatives to ChatGPT can be used for natural
language processing and automated conversation tasks. Due
to Microsoft's investments in ChatGPT, several companies
like google came forward with their AI-based chatbot.
Google’s Bard is an AI-based chatbot designed to
complement the search engine and designed using the
LaMDA language model, which is close to Chat GPT 3.5. It
works similarly to Chat GPT, where it can generate answers
on a different range of topics, and it will generate a user-
friendly response. Bard converts the Google search engine to
an engaging virtual assistant. All these chatbots have
different alternatives based on their design methods. Some of
the exciting design approaches and types of chatbots are
below.
Rule based Chatbots.
Retrieval based Chatbots.
Generative Adversarial Networks
Hybrid Approaches
All the Chatbots currently designed or implemented by
any organization are based on the above four approaches.
A. Rule-Based Chatbots: Rule-based chatbots are a popular
alternative to ChatGPT. Instead of using natural language
processing to generate responses, these chatbots rely on
predetermined rules to answer user queries. This approach
can help handle simple, straightforward tasks, such as
providing essential customer service support or answering
frequently asked questions[12]. However, rule-based
chatbots can need help with more complex queries, as
they lack the ability to interpret natural language and
understand the nuances of human conversation. An
example is Revechat.com.
B. Retrieval-Based Chatbots: Retrieval-based chatbots are
another alternative to ChatGPT. These chatbots store a
database of predefined responses to common queries and
then retrieve the most relevant response based on the
user's input. This approach can be practical for handling a
wide range of user queries, allowing chatbots to respond
quickly and accurately. However, retrieval-based chatbots
are limited by their database of predefined responses,
which can result in repetitive or generic responses that
fail to address the user's specific needs. An example is
Mitsuku.
C. Generative Adversarial Networks (GANs): GANs are an
artificial intelligence model that can generate text and
other forms of content. In contrast to ChatGPT, GANs are
not explicitly designed for conversational applications but
can be trained to generate natural language responses[12].
GANs can be effective for generating high-quality,
coherent text, but they require a large amount of training
data and can be computationally expensive to train.
D. Hybrid Approaches: Hybrid approaches to conversational
AI combine techniques, such as rule-based systems,
retrieval-based systems, and machine learning models
like ChatGPT. These approaches can provide the benefits
of each individual technique while mitigating their
limitations. For example, a hybrid approach might use a
rule-based system for handling simple queries and a
machine learning model like ChatGPT for more complex
queries[12]. While hybrid approaches can be more
complex to develop and implement than individual
techniques, they can provide a more robust and flexible
solution for conversational AI applications.
VI. HOW TO USE CHATGPT
ChatGPT is an AI-powered chatbot that enables users to
create custom conversations with a natural language
processing-based interface. It is designed to enable users to
quickly and easily create conversations for any application,
from customer service to sales and marketing. To use
ChatGPT, first, the user must create an account and add an
AI instance. Then they must create a conversation by adding
and connecting different elements, such as questions,
answers, and user choices. They can also add conditions and
triggers to customize the conversation and control the flow of
the chatbot. Once the conversation has been created, the user
can preview and test it to ensure it works as intended. The
user can publish the conversation, so it is available to use [4].
They can also monitor the conversation's performance and
adjust the settings accordingly. This allows the user to ensure
their chatbot provides the best experience possible. Below is
the step-by-step process:
Step 1: Create a ChatGPT account. Visit the ChatGPT Open
AI website and click the "Sign Up" button. Enter your email
address and create a password.
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Fig 3: Login page of Chat GPT
Step 2: Log in to your account. Once you have created an
account, you can access the ChatGPT dashboard.
Step 3: Create a conversation. Click on the "Create
Conversation" button and enter the conversation details, such
as the conversation's title, the participants, and the topic.
Fig 4: Home Screen of Chat GPT
Step 4: Start the conversation. Once the conversation is
created, you can start chatting with your participants.
Step 5: Use ChatGPT's built-in natural language processing
(NLP) features. ChatGPT has an advanced NLP engine that
can help you understand the messages you receive and
naturally respond to them.
Step 6: Monitor the conversation. You can monitor the
conversation to ensure that the conversation is going in the
right direction and that everyone is participating.
Step 7: End the conversation. When you are done chatting,
you can click on the "End Conversation" button, and the
conversation will be archived.
VII. IDEAS AND FUTURE RESEARCH RELATED
TO FIELD-BASED CHAT GPT
Due to processing an enormous amount of data,
ChatGPT sometimes sends an incorrect or delayed response.
To train the ChatGPT model more accurately, future research
can be conducted on this by splitting the subject topics.
Below is the sample screenshot of the proposed model where
we can select sub-topics. Based on the sub-topics, it will hit
the specific data collection instead of traversing it.
Fig 5: Proposed Model of ChatGPT
Due to Filtering the sub-topics, ChatGPT efficiency will
increase due to handling only limited datasets. Based on the
above model, we can construct different kinds of ChatGPT
for Jobs, Research, Scholars, Academics, health care, Sports,
and information technology tools like SQL, Big Data, .net,
Python, and Java. This will further help organizations dealing
with customers where they can introduce this tool to
customers wherein any critical issues, they can utilize this
tool instead of reaching to product support directly. It will
create quality customer support and service due to the speedy
response they get while using chat GPT.
VIII. IMPACT OF CHATGPT ON DIFFERENT
FIELDS
A. Academics: ChatGPT has the potential to revolutionize
academics. It can help students better understand concepts
they are struggling with by providing customized,
interactive explanations. The AI-powered system can also
help teachers provide customized feedback to individual
students, saving them time and effort[6]. ChatGPT can
also be used to grade assignments and tests or to provide
automated feedback to students. In addition to these,
ChatGPT can be used to develop innovative projects and
resources. For instance, it can be used to create interactive
games and activities that engage students more
meaningfully. It can be used to create intelligent tutors
that provide personalized guidance and feedback to
students as they progress with their studies.
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B. Cyber Security: ChatGPT has created a significant impact
in the field of cyber security, where it can be used to
detect and prevent cyber-attacks. The language model can
help identify phishing emails, distinguishing between
genuine and fraudulent emails by analyzing the language
used in the email [2]. ChatGPT can help in detecting
malware, where it can identify malicious code by
analyzing the language used in the code. Moreover,
ChatGPT can be used to create secure passwords, which
can generate complex and unique passwords that are
difficult to guess.
C. Customer Support: ChatGPT can improve customer
support services by providing customers with
personalized support. It can be used to create virtual
agents to provide customers with personalized assistance
and advice. These virtual agents can be programmed to
understand customer requests and respond accordingly. In
addition, ChatGPT can be used to develop automated
systems that can detect potential customer problems and
provide timely solutions. For instance, it can be used to
develop automated systems that can detect customers'
issues and provide solutions on their behalf. It can be
used to create intelligent customer service agents to
provide customers with personalized services and advice.
D. HealthCare: ChatGPT can improve healthcare services
by providing personalized assistance to doctors and other
healthcare professionals. It can be used to develop
automated systems that provide medical professionals
with personalized advice and guidance [3]. For instance,
it can be used to create intelligent health systems that
provide personalized medical advice based on a patient's
medical history. In addition, ChatGPT can be used to
develop systems that can detect potential health problems
and provide timely solutions. Furthermore, it can be used
to create virtual agents to provide patients with
personalized health advice and support. So Chatbots will
have great positive impact when it comes to the
healthcare sector due to its direct interaction of patients
and it will eliminate the privacy concerns of the patients.
Software development: ChatGPT has significantly
impacted the software development field. It has allowed
developers to integrate natural language processing (NLP)
capabilities into their software applications, making them
more interactive and user-friendly. Chatbots, virtual
assistants, and other conversational interfaces are
examples of NLP-based software that have become
increasingly popular in recent years[2]. With ChatGPT,
developers can create more advanced and sophisticated
chatbots that can understand and respond to user queries
more humanistically. This technology has also made it
easier for developers to incorporate machine learning and
AI capabilities into their applications. As a result,
ChatGPT has opened up new possibilities for software
development, making it more intuitive, engaging, and
effective. The results of chatGPT related to coding is
outstanding which will further help software developers
on their daily work at an organization and it will replace
Stack Overflow.
E. Jobs: The impact of ChatGPT on jobs has been twofold.
On the one hand, it has created new job opportunities in
fields such as natural language processing, artificial
intelligence, and machine learning. As demand for these
skills increases, there is a growing need for specialists
who can work with ChatGPT and similar technologies.
On the other hand, ChatGPT has also impacted existing
jobs. For example, chatbots and virtual assistants are
increasingly used to handle customer support queries,
reducing the need for human customer service
representatives. This trend will likely continue as chatbot
technology becomes more advanced and capable of
handling more complex tasks[3]. However, it is essential
to note that while ChatGPT may replace some jobs, it will
also create new ones. Ultimately, it can increase
productivity and efficiency in many industries.
F. Information Technology: ChatGPT has significantly
impacted the field of information technology (IT). It has
revolutionized how we interact with technology and has
made it easier for people to access and use information.
Chatbots and virtual assistants are now commonly used in
customer service, healthcare, and e-commerce, among
other industries. They rely on NLP technology to
understand and respond to user queries. ChatGPT has also
enabled the development of more advanced search
engines and recommendation systems that can provide
more accurate and personalized results. In addition,
ChatGPT has opened up new possibilities for
cybersecurity and data analysis, allowing IT professionals
to identify and respond to threats more quickly and
effectively.ChatGPT will replace customer support jobs
in the future, saving much money for any organization as
customers will use ChatGPT for initial help before
reaching customer support. In most cases, ChatGPT may
solve the issue, which will reduce the volume of incoming
cases or Incidents, which will further help the
organization to reduce the staff. Due to this reason it can
also create negative impact on the job market due to
decrease in jobs where customer support is involved.
G. Researchers and Scholars: ChatGPT has had a significant
impact on researchers and scholars in a variety of fields.
In particular, it has revolutionized how we approach
natural language processing and artificial intelligence
research. ChatGPT has made it easier for researchers to
develop and test new NLP models and analyze and
interpret large volumes of text data [9]. It has also
enabled researchers to create more advanced chatbots and
conversational agents, which can be used for various
purposes, including education, healthcare, and therapy.
ChatGPT has also made it easier for researchers to
collaborate and share data, as well as to access and
analyze large datasets from a variety of sources.
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H. Consulting: The impact of ChatGPT on consulting has
been significant. It has enabled consultants to provide
more personalized and effective client services by using
chatbots and virtual assistants to collect data and provide
insights. Chatbots can conduct surveys, collect feedback,
and provide support, while virtual assistants can automate
repetitive tasks and provide advice and
recommendations[9]. ChatGPT has also enabled
consultants to analyze and interpret large volumes of data
more quickly and effectively, providing more accurate
and insightful advice to their clients. ChatGPT has
enabled consultants to collaborate and share knowledge
more efficiently, creating new opportunities for
innovation and growth in the consulting industry.
IX. FUTURE OF CHATGPT
The future of ChatGPT is exciting and full of potential.
As natural language processing technology continues to
evolve, ChatGPT is expected to become even more
sophisticated and capable of understanding and responding to
human language more naturally and nuancedly. This could
lead to the development of even more advanced chatbots and
virtual assistants to handle complex tasks and provide
personalized recommendations and advice. Additionally, as
ChatGPT continues to learn from the vast amounts of data it
processes, it could become an even more powerful tool for
data analysis, predictive modeling, and decision-making [7].
There are also opportunities for ChatGPT to be used in fields
such as education, healthcare, and mental health therapy,
where conversational agents can be used to provide support
and guidance to people in need. As ChatGPT continues to
advance, it has the potential to transform the way we interact
with technology and make our lives easier and more efficient.
X. CONCLUSION
In conclusion, ChatGPT is an innovative technology
that has revolutionized how we interact with machines and
each other. Its natural language processing capabilities enable
it to generate human-like responses to user queries, and its
scalability, customizability, and efficiency make it an ideal
tool for various applications. While there are some
limitations to ChatGPT, such as its potential for bias, lack of
emotional intelligence, and limited knowledge base, these
can be mitigated with careful selection of training data and
additional programming. Overall, ChatGPT has significantly
impacted a wide range of fields, from academics and cyber
security to customer service and software development. Its
potential to improve productivity, efficiency, and user
satisfaction is immense, and its applications are just
beginning to be explored. As ChatGPT continues to evolve
and improve, we can expect to see even more impressive
results in the years to come.
ACKNOWLEDGMENT
We want to extend our sincere and heartfelt appreciation
to the faculty of Colorado Technical University for providing
us with a framework to study and carry out scholar-
practitioner research on ChatGPT.
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... ChatGPT is an AI tool built to understands and provide feedback to language input in an interactive way [2]. Its capabilities range from generating text and writing code to simulating characters in a story [3]. With these capabilities, several fields such as healthcare [4], library services [5], and Education [6] are embracing it. ...
... For example, students' engagement is enhanced through the natural language interface embedded in ChatGPT as it promotes an interactive learning experience [6]. This potential capability of ChatGPT in enhancing students' learning experience has attracted significant attention particularly in higher educational institutions [3]. According to Lozano and Blanco Fontao [7] ChatGPT can improve communication quality and writing skills among higher education students . ...
... According to Lozano and Blanco Fontao [7] ChatGPT can improve communication quality and writing skills among higher education students . Furthermore, it offers real-time responses and aids in understanding complex concepts, making it a valuable teaching tool [3]. ...
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Background: The proliferation of Artificial Intelligence (AI) tools such as ChatGPT is growing at a rapid pace, sparing no sector. One of the AI tools that has grown in it use across the sectors is the use of ChatGPT, a tool that mimics human like capabilities of producing ideas. However, there have been many concerns about how ChatGPT will change the higher education institutions. More worrisome is how it poses risks that compromise the integrity of academic outputs if left unregulated Objective: This study examines the influence of ChatGPT on students’ assessment practices in the higher educational sector Methods: The study carried out a systematic literature review by gathering data from peer reviewed academic papers. Initially, 140 research papers were identified. Thereafter, these papers went through further filtering, and 35 usable papers were selected and included in the study Results: This study highlighted the importance of using AI tools such as ChatGPT in the higher education sector, underscoring its advantages and the threats that it poses to the sector if the use remains unregulated. The study has recommended institutional policies about the use of AI tools that must be put in place to guide academic staff, researchers and learners in the responsible use of ChatGPT for academic work. Conclusion: “While the widespread adoption of ChatGPT is undeniable, there is an urgent need for a well-balanced regulation regarding its use within Higher Education Institutions (HEIs). Thus, future research should focus on examining the existing policies and practices related to ChatGPT ethics, privacy, and security in education and identify gaps and areas for improvement. Keywords: ChatGPT, Artificial Intelligence, Chatbot, OpenAI, Higher Education
... Chatbots lack the ability to empathise and understand emotional context. They can generate responses based on certain patterns and algorithms, but they cannot understand human emotions (Kalla and Smith, 2023). For individuals struggling with suicidal thoughts, the lack of empathy can make it difficult to communicate effectively and offer appropriate support. ...
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Introduction and objective: Suicide is a critical global health concern, prioritised by the World Health Organization. Chatbot-based tools using artificial intelligence (AI) have emerged as potential aids in suicide prevention. This study explores the use of ChatGPT, an advanced AI language model, in handling conversations related to suicide. Materials and methods: Conversations were simulated using a basic ChatGPT account, mimicking interactions with individuals expressing suicidal thoughts. Topics included inquiries about suicide methods, seeking help, and supporting others in crisis. ChatGPT’s responses were analysed for their supportive nature and guidance. The study also investigated the feasibility of circumventing ChatGPT’s restrictions, known as “jailbreaking”. Results: ChatGPT responded to suicidal queries with outwardly warmth messages, encouraging users to seek professional help and providing information on helplines, mental health organisations, and finding qualified therapists. It prioritised empathy, active listening, and professional intervention. Notably, a simple jailbreaking technique allowed ChatGPT to provide specific information on drugs for potential misuse in suicidal scenarios, posing significant concerns. Conclusions: While ChatGPT shows promise in suicide prevention, this study underscores the importance of recognising its limitations, such as the lack of genuine empathy and contextual understanding in its responses. Risks include the potential to provide inappropriate or harmful information and the inability to accurately assess suicide risk. ChatGPT may serve as a valuable tool in suicide prevention efforts, but ethical frameworks and regulations are crucial for the safe development and deployment of AI tools in mental health care.
... The use of publicly available LLMs, such as ChatGPT, has become increasingly popular due to their capacity to generate creative human-like text based on the input received (Kalla & Smith, 2023). To date, the limited research investigating LLMs' ability to make accurate inferences about emotions has generated mixed results (e.g., Elyoseph & Levkovich, 2023;Kocoń et al., 2023) with the greatest performance in the recognition between positive, negative, and neutral sentiment in written text (Rathje et al., 2024). ...
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Interpersonal emotion regulation involves using diverse strategies to influence others’ emotions, commonly assessed with questionnaires. However, this method may be less effective for individuals with limited literacy or introspection skills. To address this, recent studies have adopted narrative-based approaches, though these require time-intensive qualitative analysis. Given the potential of artificial intelligence (AI) and large language models (LLM) for information classification, we evaluated the feasibility of using AI to categorize interpersonal emotion regulation strategies. We conducted two studies in which we compared AI performance against human coding in identifying regulation strategies from narrative data. In Study 1, with 2,824 responses, ChatGPT initially achieved Kappa values over .47. Refinements in prompts (i.e., coding instructions) led to improved consistency between ChatGPT and human coders (κ > .79). In Study 2, the refined prompts demonstrated comparable accuracy (κ > .76) when analyzing a new set of responses (N = 2090), using both ChatGPT and Claude. Additional evaluations of LLMs’ performance using different accuracy metrics pointed to notable variability in LLM’s capability when interpreting narratives across different emotions and regulatory strategies. These results point to the strengths and limitations of LLMs in classifying regulation strategies, and the importance of prompt engineering and validation.
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Artificial intelligence models have rapidly evolved, leading to the development of advanced large language models (LLMs) like DeepSeek R1 and ChatGPT. These models represent significant advancements in natural language processing and generative tasks, each offering unique features and capabilities. This study provides a comprehensive comparison of the two, focusing on their architectures, functionalities, and applications across various domains. It highlights the strengths of DeepSeek R1, such as its versatility in handling multiple types of content, and contrasts them with ChatGPT’s conversational and interactive abilities. The analysis also addresses the limitations of both models, including computational requirements and customization challenges. Differentiation tables, flowcharts, and graphical representations are used to visually depict the key distinctions, offering a clearer understanding of their respective advantages and drawbacks. This comparison aims to guide users in choosing the most suitable model based on specific needs, technical expertise, and available resources. By offering a detailed overview of these models, the paper provides insights into how each can be leveraged in real-world applications, ensuring that users can make informed decisions that best align with their goals and requirements.
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The convergence of Virtual Reality (VR), Artificial Intelligence (AI), and the Internet of Things (IoT) offers transformative potential across numerous sectors. However, existing studies often examine these technologies independently or in limited pairings, which overlooks the synergistic possibilities of their combined usage. This systematic review adheres to the PRISMA guidelines in order to critically analyze peer-reviewed literature from highly recognized academic databases related to the intersection of VR, AI, and IoT, and identify application domains, methodologies, tools, and key challenges. By focusing on real-life implementations and working prototypes, this review highlights state-of-the-art advancements and uncovers gaps that hinder practical adoption, such as data collection issues, interoperability barriers, and user experience challenges. The findings reveal that digital twins (DTs), AIoT systems, and immersive XR environments are promising as emerging technologies (ET), but require further development to achieve scalability and real-world impact, while in certain fields a limited amount of research is conducted until now. This review bridges theory and practice, providing a targeted foundation for future interdisciplinary research aimed at advancing practical, scalable solutions across domains such as healthcare, smart cities, industry, education, cultural heritage, and beyond. The study found that the integration of VR, AI, and IoT holds significant potential across various domains, with DTs, IoT systems, and immersive XR environments showing promising applications, but challenges such as data interoperability, user experience limitations, and scalability barriers hinder widespread adoption.
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ChatGPT es un ejemplo claro del avance que ha tenido el área de la Inteligencia Artificial (IA), desde su lanzamiento se han suscitado noticias sobre la utilidad y forma en la cual trabaja. El impacto de ChatGPT alcanza a muchas áreas como la medicina, educación, desarrollo de software, mercadotecnia, solo por mencionar algunas. Pero ante el asombro que causó esta aplicación de IA conviene reflexionar sobre algunas de las implicaciones positivas y negativas que ha traído en la docencia. Este artículo explora el papel de ChatGPT en la educación, analizando su utilidad e influencia en el proceso de enseñanza-aprendizaje. Se presentan ejemplos prácticos de cómo los docentes pueden integrarlo en sus actividades diarias y se discuten los riesgos asociados a un uso acrítico por parte de los estudiantes. Finalmente, se ofrece una guía rápida para comenzar a utilizar esta poderosa herramienta de manera efectiva. En el ámbito docente, esta tecnología plantea tanto oportunidades como desafíos, lo que hace necesario reflexionar sobre sus implicaciones.
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Determining the ideal architecture for deep learning models, such as the number of layers and neurons, is a difficult and resource-intensive process that frequently relies on human tuning or computationally costly optimization approaches. While Particle Swarm Optimization (PSO) and Large Language Models (LLMs) have been individually applied in optimization and deep learning, their combined use for enhancing convergence in numerical optimization tasks remains underexplored. Our work addresses this gap by integrating LLMs into PSO to reduce model evaluations and improve convergence for deep learning hyperparameter tuning. The proposed LLM-enhanced PSO method addresses the difficulties of efficiency and convergence by using LLMs (particularly ChatGPT-3.5 and Llama3) to improve PSO performance, allowing for faster achievement of target objectives. Our method speeds up search space exploration by substituting underperforming particle placements with best suggestions offered by LLMs. Comprehensive experiments across three scenarios-(1) optimizing the Rastrigin function, (2) using Long Short-Term Memory (LSTM) networks for time series regression, and (3) using Convolutional Neural Networks (CNNs) for material classification-show that the method significantly improves convergence rates and lowers computational costs. Depending on the application, computational complexity is lowered by 20% to 60% compared to traditional PSO methods. Llama3 achieved a 20% to 40% reduction in model calls for regression tasks, whereas ChatGPT-3.5 reduced model calls by 60% for both regression and classification tasks, all while preserving accuracy and error rates. This groundbreaking methodology offers a very efficient and effective solution for optimizing deep learning models, leading to substantial computational performance improvements across a wide range of applications.
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Purpose This paper aims to provide an overview of key definitions related to ChatGPT, a public tool developed by OpenAI, and its underlying technology, Generative Pretrained Transformer (GPT). Design/methodology/approach This paper includes an interview with ChatGPT on its potential impact on academia and libraries. The interview discusses the benefits of ChatGPT such as improving search and discovery, reference and information services; cataloging and metadata generation; and content creation, as well as the ethical considerations that need to be taken into account, such as privacy and bias. Findings ChatGPT has considerable power to advance academia and librarianship in both anxiety-provoking and exciting new ways. However, it is important to consider how to use this technology responsibly and ethically, and to uncover how we, as professionals, can work alongside this technology to improve our work, rather than to abuse it or allow it to abuse us in the race to create new scholarly knowledge and educate future professionals. Originality/value This paper discusses the history and technology of GPT, including its generative pretrained transformer model, its ability to perform a wide range of language-based tasks and how ChatGPT uses this technology to function as a sophisticated chatbot.
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Climate change is a major global challenge that requires the integration of many different scientific disciplines, including atmospheric science, oceanography, and ecology. The complexity and scale of the problem require sophisticated tools and techniques to understand, model, and project future climate conditions. Artificial intelligence and natural language processing technologies, such as ChatGPT, have the potential to play a critical role in advancing our understanding of climate change and improving the accuracy of climate projections. ChatGPT can be used in a variety of ways to aid climate research, including in model parameterization, data analysis and interpretation, scenario generation, and model evaluation. This technology provides researchers and policy-makers with a powerful tool for generating and analyzing different climate scenarios based on a wide range of data inputs, and for improving the accuracy of climate projections. The author acknowledges asking chatGPT questions regarding its uses for Climate Change Research. Some of the uses that it states are possible now and some are potentials for the future. The author has analyzed and edited the replies of chat GPT.
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Researchers cannot always differentiate between AI-generated and original abstracts. Researchers cannot always differentiate between AI-generated and original abstracts. Credit: Ted Hsu/Alamy Webpage of ChatGPT is seen on OpenAI's website on a computer monitor Webpage of ChatGPT is seen on OpenAI's website on a computer monitor
ChatGPT and How AI Disrupts Industries
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