Despite a global decline in tobacco use,smoking remains a leading cause of preventable death,with rising vaping rates among adolescents and young adults further complicating nicotine cessation efforts.Digital interven...Despite a global decline in tobacco use,smoking remains a leading cause of preventable death,with rising vaping rates among adolescents and young adults further complicating nicotine cessation efforts.Digital interventions,particularly chatbots,have gained attention for their potential to support tobacco and vaping cessation by simulating human-like conversations and providing instant feedback.However,evidence of their effectiveness is limited.The emergence of generative artificial intelligence(AI)chatbots,such as ChatGPT,offers a promising avenue for more personalised and effective cessation support.This article reviews existing literature on traditional chatbot interventions for cessation services,explores the potential of AI chatbots,namely ChatGPT,in continuing to support tobacco and vaping cessation efforts,and identifies areas for future research.It highlights the need to further monitor the reliability and accuracy of AI-generated content and to develop frameworks ensuring healthcare professionals receive adequate training in using these new tools effectively to support patients in quitting smoking and/or vaping.展开更多
Intelligent chatbots powered by large language models(LLMs)have recently been sweeping the world,with potential for a wide variety of industrial applications.Global frontier technology companies are feverishly partici...Intelligent chatbots powered by large language models(LLMs)have recently been sweeping the world,with potential for a wide variety of industrial applications.Global frontier technology companies are feverishly participating in LLM-powered chatbot design and development,providing several alternatives beyond the famous ChatGPT.However,training,fine-tuning,and updating such intelligent chatbots consume substantial amounts of electricity,resulting in significant carbon emissions.The research and development of all intelligent LLMs and software,hardware manufacturing(e.g.,graphics processing units and supercomputers),related data/operations management,and material recycling supporting chatbot services are associated with carbon emissions to varying extents.Attention should therefore be paid to the entire life-cycle energy and carbon footprints of LLM-powered intelligent chatbots in both the present and future in order to mitigate their climate change impact.In this work,we clarify and highlight the energy consumption and carbon emission implications of eight main phases throughout the life cycle of the development of such intelligent chatbots.Based on a life-cycle and interaction analysis of these phases,we propose a system-level solution with three strategic pathways to optimize the management of this industry and mitigate the related footprints.While anticipating the enormous potential of this advanced technology and its products,we make an appeal for a rethinking of the mitigation pathways and strategies of the life-cycle energy usage and carbon emissions of the LLM-powered intelligent chatbot industry and a reshaping of their energy and environmental implications at this early stage of development.展开更多
Clinical applications of Artificial Intelligence(AI)for mental health care have experienced a meteoric rise in the past few years.AIenabled chatbot software and applications have been administering significant medical...Clinical applications of Artificial Intelligence(AI)for mental health care have experienced a meteoric rise in the past few years.AIenabled chatbot software and applications have been administering significant medical treatments that were previously only available from experienced and competent healthcare professionals.Such initiatives,which range from“virtual psychiatrists”to“social robots”in mental health,strive to improve nursing performance and cost management,as well as meeting the mental health needs of vulnerable and underserved populations.Nevertheless,there is still a substantial gap between recent progress in AI mental health and the widespread use of these solutions by healthcare practitioners in clinical settings.Furthermore,treatments are frequently developed without clear ethical concerns.While AI-enabled solutions show promise in the realm of mental health,further research is needed to address the ethical and social aspects of these technologies,as well as to establish efficient research and medical practices in this innovative sector.Moreover,the current relevant literature still lacks a formal and objective review that specifically focuses on research questions from both developers and psychiatrists in AI-enabled chatbotpsychologists development.Taking into account all the problems outlined in this study,we conducted a systematic review of AI-enabled chatbots in mental healthcare that could cover some issues concerning psychotherapy and artificial intelligence.In this systematic review,we put five research questions related to technologies in chatbot development,psychological disorders that can be treated by using chatbots,types of therapies that are enabled in chatbots,machine learning models and techniques in chatbot psychologists,as well as ethical challenges.展开更多
The application of artificial intelligence(AI)in customer service becomes ubiquitous.In response to the advocacy in the“2021 Coordinated Plan on Artificial Intelligence”,it is crucial to understand how to leverage A...The application of artificial intelligence(AI)in customer service becomes ubiquitous.In response to the advocacy in the“2021 Coordinated Plan on Artificial Intelligence”,it is crucial to understand how to leverage AI customer service chatbots for societal welfare.Across two scenario studies and one lab experiment,this research investigates the impact of AI chatbots’communication styles on consumers’subsequent prosocial intentions irrelevant to the AI-human interaction contents.The combined evidence suggests that consumers exhibit higher prosocial intentions after interacting with social-oriented(vs.task-oriented)AI chatbots.The findings reveal the chain-mediating roles of social presence and empathy.Moreover,the current research investigates the boundary effect of consumers’goal focus(process focus vs.outcome focus),and shows that AI chatbots’communication styles have stronger impact on prosocial intentions for customers with outcome focus.These results revealed the important externality of the AI application in marketplace and provide a novel perspective for companies to implement the corporate social responsibility(CSR)strategy.展开更多
AIM:To investigate the capabilities of large language models(LLM)for providing information and diagnoses in the field of neuro-ophthalmology by comparing the performances of ChatGPT-3.5 and-4.0,Bard,and Bing.METHODS:E...AIM:To investigate the capabilities of large language models(LLM)for providing information and diagnoses in the field of neuro-ophthalmology by comparing the performances of ChatGPT-3.5 and-4.0,Bard,and Bing.METHODS:Each chatbot was evaluated for four criteria,namely diagnostic success rate for the described case,answer quality,response speed,and critical keywords for diagnosis.The selected topics included optic neuritis,nonarteritic anterior ischemic optic neuropathy,and Leber hereditary optic neuropathy.RESULTS:In terms of diagnostic success rate for the described cases,Bard was unable to provide a diagnosis.The success rates for the described cases increased in the order of Bing,ChatGPT-3.5,and ChatGPT-4.0.Further,ChatGPT-4.0 and-3.5 provided the most satisfactory answer quality for judgment by neuro-ophthalmologists,with their sets of answers resembling the sample set most.Bard was only able to provide ten differential diagnoses in three trials.Bing scored the lowest for the satisfactory standard.A Mann-Whitney test indicated that Bard was significantly faster than ChatGPT-4.0(Z=-3.576,P=0.000),ChatGPT-3.5(Z=-3.576,P=0.000)and Bing(Z=-2.517,P=0.011).ChatGPT-3.5 and-4.0 far exceeded the other two interfaces at providing diagnoses and were thus used to find the critical keywords for diagnosis.CONCLUSION:ChatGPT-3.5 and-4.0 are better than Bard and Bing in terms of answer success rate,answer quality,and critical keywords for diagnosis in ophthalmology.This study has broad implications for the field of ophthalmology,providing further evidence that artificial intelligence LLM can aid clinical decision-making through free-text explanations.展开更多
This study proposes a virtual healthcare assistant framework designed to provide support in multiple languages for efficient and accurate healthcare assistance.The system employs a transformer model to process sophist...This study proposes a virtual healthcare assistant framework designed to provide support in multiple languages for efficient and accurate healthcare assistance.The system employs a transformer model to process sophisticated,multilingual user inputs and gain improved contextual understanding compared to conventional models,including long short-term memory(LSTM)models.In contrast to LSTMs,which sequence processes information and may experience challenges with long-range dependencies,transformers utilize self-attention to learn relationships among every aspect of the input in parallel.This enables them to execute more accurately in various languages and contexts,making them well-suited for applications such as translation,summarization,and conversational Comparative evaluations revealed the superiority of the transformer model(accuracy rate:85%)compared with that of the LSTM model(accuracy rate:65%).The experiments revealed several advantages of the transformer architecture over the LSTM model,such as more effective self-attention,the ability for models to work in parallel with each other,and contextual understanding for better multilingual compatibility.Additionally,our prediction model exhibited effectiveness for disease diagnosis,with accuracy of 85%or greater in identifying the relationship between symptoms and diseases among different demographics.The system provides translation support from English to other languages,with conversion to French(Bilingual Evaluation Understudy score:0.7),followed by English to Hindi(0.6).The lowest Bilingual Evaluation Understudy score was found for English to Telugu(0.39).This virtual assistant can also perform symptom analysis and disease prediction,with output given in the preferred language of the user.展开更多
Conversational systems have come a long way since their inception in the 1960 s.After decades of research and development,we have seen progress from Eliza and Parry in the 1960 s and 1970 s,to task-completion systems ...Conversational systems have come a long way since their inception in the 1960 s.After decades of research and development,we have seen progress from Eliza and Parry in the 1960 s and 1970 s,to task-completion systems as in the Defense Advanced Research Projects Agency(DARPA) communicator program in the 2000 s,to intelligent personal assistants such as Siri,in the 2010 s,to today's social chatbots like Xiao Ice.Social chatbots' appeal lies not only in their ability to respond to users' diverse requests,but also in being able to establish an emotional connection with users.The latter is done by satisfying users' need for communication,affection,as well as social belonging.To further the advancement and adoption of social chatbots,their design must focus on user engagement and take both intellectual quotient(IQ) and emotional quotient(EQ) into account.Users should want to engage with a social chatbot;as such,we define the success metric for social chatbots as conversation-turns per session(CPS).Using Xiao Ice as an illustrative example,we discuss key technologies in building social chatbots from core chat to visual awareness to skills.We also show how Xiao Ice can dynamically recognize emotion and engage the user throughout long conversations with appropriate interpersonal responses.As we become the first generation of humans ever living with artificial intelligenc(AI),we have a responsibility to design social chatbots to be both useful and empathetic,so they will become ubiquitous and help society as a whole.展开更多
Prompt engineering, the art of crafting effective prompts for artificial intelligence models, has emerged as a pivotal factor in determining the quality and usefulness of AI (Artificial Intelligence)-generated outputs...Prompt engineering, the art of crafting effective prompts for artificial intelligence models, has emerged as a pivotal factor in determining the quality and usefulness of AI (Artificial Intelligence)-generated outputs. This practice involves strategically designing and structuring prompts to guide AI models toward desired outcomes, ensuring that they generate relevant, informative, and accurate responses. The significance of prompt engineering cannot be overstated. Well-crafted prompts can significantly enhance the capabilities of AI models, enabling them to perform tasks that were once thought to be exclusively human domain. By providing clear and concise instructions, prompts can guide AI models to generate creative text, translate languages, write different kinds of creative content, and answer your questions in an informative way. Moreover, prompt engineering can help mitigate biases and ensure that AI models produce outputs that are fair, equitable, and inclusive. However, prompt engineering is not without its challenges. Crafting effective prompts requires a deep understanding of both the AI model’s capabilities and the specific task at hand. Additionally, the quality of the prompts can be influenced by factors such as the model’s training data [1] and the complexity of the task. As AI models continue to evolve, prompt engineering will likely become even more critical in unlocking their full potential.展开更多
COVID-19 pandemic restrictions limited all social activities to curtail the spread of the virus.The foremost and most prime sector among those affected were schools,colleges,and universities.The education system of en...COVID-19 pandemic restrictions limited all social activities to curtail the spread of the virus.The foremost and most prime sector among those affected were schools,colleges,and universities.The education system of entire nations had shifted to online education during this time.Many shortcomings of Learning Management Systems(LMSs)were detected to support education in an online mode that spawned the research in Artificial Intelligence(AI)based tools that are being developed by the research community to improve the effectiveness of LMSs.This paper presents a detailed survey of the different enhancements to LMSs,which are led by key advances in the area of AI to enhance the real-time and non-real-time user experience.The AI-based enhancements proposed to the LMSs start from the Application layer and Presentation layer in the form of flipped classroom models for the efficient learning environment and appropriately designed UI/UX for efficient utilization of LMS utilities and resources,including AI-based chatbots.Session layer enhancements are also required,such as AI-based online proctoring and user authentication using Biometrics.These extend to the Transport layer to support real-time and rate adaptive encrypted video transmission for user security/privacy and satisfactory working of AI-algorithms.It also needs the support of the Networking layer for IP-based geolocation features,the Virtual Private Network(VPN)feature,and the support of Software-Defined Networks(SDN)for optimum Quality of Service(QoS).Finally,in addition to these,non-real-time user experience is enhanced by other AI-based enhancements such as Plagiarism detection algorithms and Data Analytics.展开更多
The problematic use of social media has numerous negative impacts on individuals'daily lives,interpersonal relationships,physical and mental health,and more.Currently,there are few methods and tools to alleviate p...The problematic use of social media has numerous negative impacts on individuals'daily lives,interpersonal relationships,physical and mental health,and more.Currently,there are few methods and tools to alleviate problematic social media,and their potential is yet to be fully realized.Emerging large language models(LLMs)are becoming increasingly popular for providing information and assistance to people and are being applied in many aspects of life.In mitigating problematic social media use,LLMs such as ChatGPT can play a positive role by serving as conversational partners and outlets for users,providing personalized information and resources,monitoring and intervening in problematic social media use,and more.In this process,we should recognize both the enormous potential and endless possibilities of LLMs such as ChatGPT,leveraging their advantages to better address problematic social media use,while also acknowledging the limitations and potential pitfalls of ChatGPT technology,such as errors,limitations in issue resolution,privacy and security concerns,and potential overreliance.When we leverage the advantages of LLMs to address issues in social media usage,we must adopt a cautious and ethical approach,being vigilant of the potential adverse effects that LLMs may have in addressing problematic social media use to better harness technology to serve individuals and society.展开更多
With the development of cities and the prevalence of networks,interpersonal relationships have become increasingly distant.When people crave communication,they hope to find someone to confide in.With the rapid advance...With the development of cities and the prevalence of networks,interpersonal relationships have become increasingly distant.When people crave communication,they hope to find someone to confide in.With the rapid advancement of deep learning and big data technologies,an enabling environment has been established for the development of intelligent chatbot systems.By effectively combining cutting-edge technologies with humancentered design principles,chatbots hold the potential to revolutionize our lives and alleviate feelings of loneliness.A multi-topic chat companion robot based on a state machine has been proposed,which can engage in fluent dialogue with humans and meet different functional requirements.It can chat with users about movies,music,and other related topics,and recommend movies and music that may interest them to alleviate their loneliness and provide companionship.The interaction platform of the companion robot is realized through the QQ communication platform,with two chat modes:Conversation mode and recommendation mode.First,the KdConv open-source corpus was selected,and Python was used to crawl information on movies and music from Douban and QQ Music to establish and pre-process the dataset.Then,the dialogue function was implemented using generative language models and retrieval systems,while the recommendation function was achieved using user profiling and collaborative filtering.Finally,a state machine algorithm was used to achieve real-time switching between the two chat modes of the companion robot.In conclusion,test participants gave high ratings for the accuracy of the companion robot’s responses and the satisfaction with its content recommendations.Compared to traditional large-scale integrated models,this robot employs a state-machine framework to achieve diverse functions through seamless state transitions,thereby enhancing computational speed and precision.Additionally,the robot can recommend movies and music,providing companionship and alleviating loneliness for users,which is of great significance in modern society where interpersonal relationships are increasingly alienated.展开更多
气象短信服务在气象部门已有十多年的历史并有较广的覆盖面,由于一直以来受运营商传统短信网关的技术能力限制,仅能提供70个字的文字服务。2020年随着三大运营商联合发布《5G消息(5GMC)白皮书》,推出了RCS(Rich Communication Suite,富...气象短信服务在气象部门已有十多年的历史并有较广的覆盖面,由于一直以来受运营商传统短信网关的技术能力限制,仅能提供70个字的文字服务。2020年随着三大运营商联合发布《5G消息(5GMC)白皮书》,推出了RCS(Rich Communication Suite,富媒体通信),该技术具备融合语音、消息、视频、社区网络等多种功能,为传统短信业务的全面升级提供了技术支撑。本文立足现阶段手机终端普遍支持的RCS UP1.0标准,研究建立“5G天气罗盘制作发布支撑系统”提供以图片、视频等形式的服务内容将天气消息多媒体化,并通过Chatbot的NFS(Network File System)回落技术实现非5G用户以彩信回落的方式接收5G消息,对传统气象短信进行迭代升级,取得了较好的运行效果。展开更多
Banks daily interact with a vast number of customers and are still depending on a legacy system. With today’s advances in technology, regarding lifting almost all processes to automation, from start of production to ...Banks daily interact with a vast number of customers and are still depending on a legacy system. With today’s advances in technology, regarding lifting almost all processes to automation, from start of production to finish, there is a need for revolution in archaic monetary management institutes. By not being in tune with the contemporary trends and times, banks are losing on an opportunity to transform some of their business models and relieve humans of repetitive work, prevent frauds, make better decisions and consequently gain losses. Banks can engage in implementation of new Virtual Assistants and Artificial Intelligence (A.I.) machine learning technologies, just as the other industries have engaged in modernizing <i>i.e. </i> medical checks, medical reports and evaluations, and this research paper will elaborate and emphasize the impact of artificial intelligence implementation on the banking sector processes. This research is based on both quantitative and model-based proofs of system performance by using several analytical tools, such as SPSS. The automation process helps institutions to enhance profitability, performance and to reduce human dependency. In a nutshell, Virtual Assistants powered with Artificial Intelligence improve the business process performance in every sector of business, especially the banking sector making it fast, reliable and not human dependent.展开更多
Artificial Intelligence (AI) experienced significant advancements in recent years, and its potential power is already recognized across various industries. Yet, the rise of AI has led to a growing concern about its im...Artificial Intelligence (AI) experienced significant advancements in recent years, and its potential power is already recognized across various industries. Yet, the rise of AI has led to a growing concern about its impact on meeting the Sustainable Development Goals (SDGs). The aim of this paper was to evaluate contributions and the potential influence of AI to sustainable development in the society domain. Furthermore, the study analyzed GPT-3 responses, as one of the largest language models developed by OpenAI, descriptively. We conducted a set of queries on the SDGs to gather information on GPT-3’s perceptions of AI impact on sustainable development. Analysis of GPT-3’s contribution potential towards the SDGs showcased its broad range of capabilities for contributing to the SDGs in areas such as education, health, and communication. The study findings provide valuable insights into the contributions of AI to sustainable development in the society domain and highlight the importance of proper regulations to promote the responsible use of AI for sustainable development. We highlighted the potential for improvement in neural language processing skills of GPT-3 by avoiding imitating weak human writing styles with more mistakes in longer texts.展开更多
How organizations analyze and use data for decision-making has been changed by cognitive computing and artificial intelligence (AI). Cognitive computing solutions can translate enormous amounts of data into valuable i...How organizations analyze and use data for decision-making has been changed by cognitive computing and artificial intelligence (AI). Cognitive computing solutions can translate enormous amounts of data into valuable insights by utilizing the power of cutting-edge algorithms and machine learning, empowering enterprises to make deft decisions quickly and efficiently. This article explores the idea of cognitive computing and AI in decision-making, emphasizing its function in converting unvalued data into valuable knowledge. It details the advantages of utilizing these technologies, such as greater productivity, accuracy, and efficiency. Businesses may use cognitive computing and AI to their advantage to obtain a competitive edge in today’s data-driven world by knowing their capabilities and possibilities [1].展开更多
文摘Despite a global decline in tobacco use,smoking remains a leading cause of preventable death,with rising vaping rates among adolescents and young adults further complicating nicotine cessation efforts.Digital interventions,particularly chatbots,have gained attention for their potential to support tobacco and vaping cessation by simulating human-like conversations and providing instant feedback.However,evidence of their effectiveness is limited.The emergence of generative artificial intelligence(AI)chatbots,such as ChatGPT,offers a promising avenue for more personalised and effective cessation support.This article reviews existing literature on traditional chatbot interventions for cessation services,explores the potential of AI chatbots,namely ChatGPT,in continuing to support tobacco and vaping cessation efforts,and identifies areas for future research.It highlights the need to further monitor the reliability and accuracy of AI-generated content and to develop frameworks ensuring healthcare professionals receive adequate training in using these new tools effectively to support patients in quitting smoking and/or vaping.
基金supported by the National Natural Science Foundation of China(72061127004 and 72104164)the System Science and Enterprise Development Research Center(Xq22B04)+1 种基金financial support from the Engineering and Physical Sciences Research Council(EPSRC)Programme(EP/V030515/1)financial support from the Science and Technology Support Project of Guizhou Province([2019]2839).
文摘Intelligent chatbots powered by large language models(LLMs)have recently been sweeping the world,with potential for a wide variety of industrial applications.Global frontier technology companies are feverishly participating in LLM-powered chatbot design and development,providing several alternatives beyond the famous ChatGPT.However,training,fine-tuning,and updating such intelligent chatbots consume substantial amounts of electricity,resulting in significant carbon emissions.The research and development of all intelligent LLMs and software,hardware manufacturing(e.g.,graphics processing units and supercomputers),related data/operations management,and material recycling supporting chatbot services are associated with carbon emissions to varying extents.Attention should therefore be paid to the entire life-cycle energy and carbon footprints of LLM-powered intelligent chatbots in both the present and future in order to mitigate their climate change impact.In this work,we clarify and highlight the energy consumption and carbon emission implications of eight main phases throughout the life cycle of the development of such intelligent chatbots.Based on a life-cycle and interaction analysis of these phases,we propose a system-level solution with three strategic pathways to optimize the management of this industry and mitigate the related footprints.While anticipating the enormous potential of this advanced technology and its products,we make an appeal for a rethinking of the mitigation pathways and strategies of the life-cycle energy usage and carbon emissions of the LLM-powered intelligent chatbot industry and a reshaping of their energy and environmental implications at this early stage of development.
基金This work was supported by the grant“Development of an intellectual system prototype for online-psychological support that can diagnose and improve youth’s psychoemotional state”funded by the Ministry of Education of the Republic of Kazakhstan.Grant No.IRN AP09259140.
文摘Clinical applications of Artificial Intelligence(AI)for mental health care have experienced a meteoric rise in the past few years.AIenabled chatbot software and applications have been administering significant medical treatments that were previously only available from experienced and competent healthcare professionals.Such initiatives,which range from“virtual psychiatrists”to“social robots”in mental health,strive to improve nursing performance and cost management,as well as meeting the mental health needs of vulnerable and underserved populations.Nevertheless,there is still a substantial gap between recent progress in AI mental health and the widespread use of these solutions by healthcare practitioners in clinical settings.Furthermore,treatments are frequently developed without clear ethical concerns.While AI-enabled solutions show promise in the realm of mental health,further research is needed to address the ethical and social aspects of these technologies,as well as to establish efficient research and medical practices in this innovative sector.Moreover,the current relevant literature still lacks a formal and objective review that specifically focuses on research questions from both developers and psychiatrists in AI-enabled chatbotpsychologists development.Taking into account all the problems outlined in this study,we conducted a systematic review of AI-enabled chatbots in mental healthcare that could cover some issues concerning psychotherapy and artificial intelligence.In this systematic review,we put five research questions related to technologies in chatbot development,psychological disorders that can be treated by using chatbots,types of therapies that are enabled in chatbots,machine learning models and techniques in chatbot psychologists,as well as ethical challenges.
基金supported in part by the National Natural Science Foundation of China(NSFC),under Grants Nos.72301034 and 72272016Fundamental Research Funds for the Central Universities under Grant No.2025ZZ048.
文摘The application of artificial intelligence(AI)in customer service becomes ubiquitous.In response to the advocacy in the“2021 Coordinated Plan on Artificial Intelligence”,it is crucial to understand how to leverage AI customer service chatbots for societal welfare.Across two scenario studies and one lab experiment,this research investigates the impact of AI chatbots’communication styles on consumers’subsequent prosocial intentions irrelevant to the AI-human interaction contents.The combined evidence suggests that consumers exhibit higher prosocial intentions after interacting with social-oriented(vs.task-oriented)AI chatbots.The findings reveal the chain-mediating roles of social presence and empathy.Moreover,the current research investigates the boundary effect of consumers’goal focus(process focus vs.outcome focus),and shows that AI chatbots’communication styles have stronger impact on prosocial intentions for customers with outcome focus.These results revealed the important externality of the AI application in marketplace and provide a novel perspective for companies to implement the corporate social responsibility(CSR)strategy.
文摘AIM:To investigate the capabilities of large language models(LLM)for providing information and diagnoses in the field of neuro-ophthalmology by comparing the performances of ChatGPT-3.5 and-4.0,Bard,and Bing.METHODS:Each chatbot was evaluated for four criteria,namely diagnostic success rate for the described case,answer quality,response speed,and critical keywords for diagnosis.The selected topics included optic neuritis,nonarteritic anterior ischemic optic neuropathy,and Leber hereditary optic neuropathy.RESULTS:In terms of diagnostic success rate for the described cases,Bard was unable to provide a diagnosis.The success rates for the described cases increased in the order of Bing,ChatGPT-3.5,and ChatGPT-4.0.Further,ChatGPT-4.0 and-3.5 provided the most satisfactory answer quality for judgment by neuro-ophthalmologists,with their sets of answers resembling the sample set most.Bard was only able to provide ten differential diagnoses in three trials.Bing scored the lowest for the satisfactory standard.A Mann-Whitney test indicated that Bard was significantly faster than ChatGPT-4.0(Z=-3.576,P=0.000),ChatGPT-3.5(Z=-3.576,P=0.000)and Bing(Z=-2.517,P=0.011).ChatGPT-3.5 and-4.0 far exceeded the other two interfaces at providing diagnoses and were thus used to find the critical keywords for diagnosis.CONCLUSION:ChatGPT-3.5 and-4.0 are better than Bard and Bing in terms of answer success rate,answer quality,and critical keywords for diagnosis in ophthalmology.This study has broad implications for the field of ophthalmology,providing further evidence that artificial intelligence LLM can aid clinical decision-making through free-text explanations.
文摘This study proposes a virtual healthcare assistant framework designed to provide support in multiple languages for efficient and accurate healthcare assistance.The system employs a transformer model to process sophisticated,multilingual user inputs and gain improved contextual understanding compared to conventional models,including long short-term memory(LSTM)models.In contrast to LSTMs,which sequence processes information and may experience challenges with long-range dependencies,transformers utilize self-attention to learn relationships among every aspect of the input in parallel.This enables them to execute more accurately in various languages and contexts,making them well-suited for applications such as translation,summarization,and conversational Comparative evaluations revealed the superiority of the transformer model(accuracy rate:85%)compared with that of the LSTM model(accuracy rate:65%).The experiments revealed several advantages of the transformer architecture over the LSTM model,such as more effective self-attention,the ability for models to work in parallel with each other,and contextual understanding for better multilingual compatibility.Additionally,our prediction model exhibited effectiveness for disease diagnosis,with accuracy of 85%or greater in identifying the relationship between symptoms and diseases among different demographics.The system provides translation support from English to other languages,with conversion to French(Bilingual Evaluation Understudy score:0.7),followed by English to Hindi(0.6).The lowest Bilingual Evaluation Understudy score was found for English to Telugu(0.39).This virtual assistant can also perform symptom analysis and disease prediction,with output given in the preferred language of the user.
文摘Conversational systems have come a long way since their inception in the 1960 s.After decades of research and development,we have seen progress from Eliza and Parry in the 1960 s and 1970 s,to task-completion systems as in the Defense Advanced Research Projects Agency(DARPA) communicator program in the 2000 s,to intelligent personal assistants such as Siri,in the 2010 s,to today's social chatbots like Xiao Ice.Social chatbots' appeal lies not only in their ability to respond to users' diverse requests,but also in being able to establish an emotional connection with users.The latter is done by satisfying users' need for communication,affection,as well as social belonging.To further the advancement and adoption of social chatbots,their design must focus on user engagement and take both intellectual quotient(IQ) and emotional quotient(EQ) into account.Users should want to engage with a social chatbot;as such,we define the success metric for social chatbots as conversation-turns per session(CPS).Using Xiao Ice as an illustrative example,we discuss key technologies in building social chatbots from core chat to visual awareness to skills.We also show how Xiao Ice can dynamically recognize emotion and engage the user throughout long conversations with appropriate interpersonal responses.As we become the first generation of humans ever living with artificial intelligenc(AI),we have a responsibility to design social chatbots to be both useful and empathetic,so they will become ubiquitous and help society as a whole.
文摘Prompt engineering, the art of crafting effective prompts for artificial intelligence models, has emerged as a pivotal factor in determining the quality and usefulness of AI (Artificial Intelligence)-generated outputs. This practice involves strategically designing and structuring prompts to guide AI models toward desired outcomes, ensuring that they generate relevant, informative, and accurate responses. The significance of prompt engineering cannot be overstated. Well-crafted prompts can significantly enhance the capabilities of AI models, enabling them to perform tasks that were once thought to be exclusively human domain. By providing clear and concise instructions, prompts can guide AI models to generate creative text, translate languages, write different kinds of creative content, and answer your questions in an informative way. Moreover, prompt engineering can help mitigate biases and ensure that AI models produce outputs that are fair, equitable, and inclusive. However, prompt engineering is not without its challenges. Crafting effective prompts requires a deep understanding of both the AI model’s capabilities and the specific task at hand. Additionally, the quality of the prompts can be influenced by factors such as the model’s training data [1] and the complexity of the task. As AI models continue to evolve, prompt engineering will likely become even more critical in unlocking their full potential.
文摘COVID-19 pandemic restrictions limited all social activities to curtail the spread of the virus.The foremost and most prime sector among those affected were schools,colleges,and universities.The education system of entire nations had shifted to online education during this time.Many shortcomings of Learning Management Systems(LMSs)were detected to support education in an online mode that spawned the research in Artificial Intelligence(AI)based tools that are being developed by the research community to improve the effectiveness of LMSs.This paper presents a detailed survey of the different enhancements to LMSs,which are led by key advances in the area of AI to enhance the real-time and non-real-time user experience.The AI-based enhancements proposed to the LMSs start from the Application layer and Presentation layer in the form of flipped classroom models for the efficient learning environment and appropriately designed UI/UX for efficient utilization of LMS utilities and resources,including AI-based chatbots.Session layer enhancements are also required,such as AI-based online proctoring and user authentication using Biometrics.These extend to the Transport layer to support real-time and rate adaptive encrypted video transmission for user security/privacy and satisfactory working of AI-algorithms.It also needs the support of the Networking layer for IP-based geolocation features,the Virtual Private Network(VPN)feature,and the support of Software-Defined Networks(SDN)for optimum Quality of Service(QoS).Finally,in addition to these,non-real-time user experience is enhanced by other AI-based enhancements such as Plagiarism detection algorithms and Data Analytics.
文摘The problematic use of social media has numerous negative impacts on individuals'daily lives,interpersonal relationships,physical and mental health,and more.Currently,there are few methods and tools to alleviate problematic social media,and their potential is yet to be fully realized.Emerging large language models(LLMs)are becoming increasingly popular for providing information and assistance to people and are being applied in many aspects of life.In mitigating problematic social media use,LLMs such as ChatGPT can play a positive role by serving as conversational partners and outlets for users,providing personalized information and resources,monitoring and intervening in problematic social media use,and more.In this process,we should recognize both the enormous potential and endless possibilities of LLMs such as ChatGPT,leveraging their advantages to better address problematic social media use,while also acknowledging the limitations and potential pitfalls of ChatGPT technology,such as errors,limitations in issue resolution,privacy and security concerns,and potential overreliance.When we leverage the advantages of LLMs to address issues in social media usage,we must adopt a cautious and ethical approach,being vigilant of the potential adverse effects that LLMs may have in addressing problematic social media use to better harness technology to serve individuals and society.
基金supported by the Guangxi Key Laboratory of Automatic Detecting Technology and Instruments(YQ21207)the Qinglan Project of Jiangsu Province.
文摘With the development of cities and the prevalence of networks,interpersonal relationships have become increasingly distant.When people crave communication,they hope to find someone to confide in.With the rapid advancement of deep learning and big data technologies,an enabling environment has been established for the development of intelligent chatbot systems.By effectively combining cutting-edge technologies with humancentered design principles,chatbots hold the potential to revolutionize our lives and alleviate feelings of loneliness.A multi-topic chat companion robot based on a state machine has been proposed,which can engage in fluent dialogue with humans and meet different functional requirements.It can chat with users about movies,music,and other related topics,and recommend movies and music that may interest them to alleviate their loneliness and provide companionship.The interaction platform of the companion robot is realized through the QQ communication platform,with two chat modes:Conversation mode and recommendation mode.First,the KdConv open-source corpus was selected,and Python was used to crawl information on movies and music from Douban and QQ Music to establish and pre-process the dataset.Then,the dialogue function was implemented using generative language models and retrieval systems,while the recommendation function was achieved using user profiling and collaborative filtering.Finally,a state machine algorithm was used to achieve real-time switching between the two chat modes of the companion robot.In conclusion,test participants gave high ratings for the accuracy of the companion robot’s responses and the satisfaction with its content recommendations.Compared to traditional large-scale integrated models,this robot employs a state-machine framework to achieve diverse functions through seamless state transitions,thereby enhancing computational speed and precision.Additionally,the robot can recommend movies and music,providing companionship and alleviating loneliness for users,which is of great significance in modern society where interpersonal relationships are increasingly alienated.
文摘Banks daily interact with a vast number of customers and are still depending on a legacy system. With today’s advances in technology, regarding lifting almost all processes to automation, from start of production to finish, there is a need for revolution in archaic monetary management institutes. By not being in tune with the contemporary trends and times, banks are losing on an opportunity to transform some of their business models and relieve humans of repetitive work, prevent frauds, make better decisions and consequently gain losses. Banks can engage in implementation of new Virtual Assistants and Artificial Intelligence (A.I.) machine learning technologies, just as the other industries have engaged in modernizing <i>i.e. </i> medical checks, medical reports and evaluations, and this research paper will elaborate and emphasize the impact of artificial intelligence implementation on the banking sector processes. This research is based on both quantitative and model-based proofs of system performance by using several analytical tools, such as SPSS. The automation process helps institutions to enhance profitability, performance and to reduce human dependency. In a nutshell, Virtual Assistants powered with Artificial Intelligence improve the business process performance in every sector of business, especially the banking sector making it fast, reliable and not human dependent.
文摘Artificial Intelligence (AI) experienced significant advancements in recent years, and its potential power is already recognized across various industries. Yet, the rise of AI has led to a growing concern about its impact on meeting the Sustainable Development Goals (SDGs). The aim of this paper was to evaluate contributions and the potential influence of AI to sustainable development in the society domain. Furthermore, the study analyzed GPT-3 responses, as one of the largest language models developed by OpenAI, descriptively. We conducted a set of queries on the SDGs to gather information on GPT-3’s perceptions of AI impact on sustainable development. Analysis of GPT-3’s contribution potential towards the SDGs showcased its broad range of capabilities for contributing to the SDGs in areas such as education, health, and communication. The study findings provide valuable insights into the contributions of AI to sustainable development in the society domain and highlight the importance of proper regulations to promote the responsible use of AI for sustainable development. We highlighted the potential for improvement in neural language processing skills of GPT-3 by avoiding imitating weak human writing styles with more mistakes in longer texts.
文摘How organizations analyze and use data for decision-making has been changed by cognitive computing and artificial intelligence (AI). Cognitive computing solutions can translate enormous amounts of data into valuable insights by utilizing the power of cutting-edge algorithms and machine learning, empowering enterprises to make deft decisions quickly and efficiently. This article explores the idea of cognitive computing and AI in decision-making, emphasizing its function in converting unvalued data into valuable knowledge. It details the advantages of utilizing these technologies, such as greater productivity, accuracy, and efficiency. Businesses may use cognitive computing and AI to their advantage to obtain a competitive edge in today’s data-driven world by knowing their capabilities and possibilities [1].
