ChatGPT is a conversational artificial intelligence model developed by OpenAI, which was introduced in 2019. It employs a transformer-based neural mesh to produce human being responses in real-time, allowing for natural language conversations with a machine. ChatGPT is instructed on huge quantities of data captured using the internet, making it knowledgeable in an extensive span of topics, from news & entertainment to politics and sports. This allows it to generate contextually relevant responses to questions and statements, making the conversation seem more lifelike. The model can be used in various applications, including customer service, personal assistants, and virtual assistants. ChatGPT has also shown promising results in generating creative content, such as jokes and poetry, showcasing its versatility and potential for future applications.This paper provides a comprehensive review of the existing literature on ChatGPT, highlighting its key advantages, such as improved accuracy and flexibility compared to traditional NLP tools, as well as its limitations and the need for further research to address potential ethical concerns. The review also highlights the potential for ChatGPT to be used in NLP applications, including question-answering and dialogue generation, and highlights the need for further research and development in these areas.
In the year 2020, the word “pandemic” has become quite popular. A pandemic is a disease that spreads over a wide geographical region. The massive outbreak of coronavirus popularly known as COVID-19 has halted normal life worldwide. On 11th March 2020, the World Health Organization (WHO) quoted the COVID-19 outbreak as a “Pandemic”. The outbreak pattern differs widely across the globe based on the findings discovered so far; however, fever is a common and easily detectable symptom of COVID-19 and the new COVID strain. After the virus outbreak, thermal scanning is done using infrared thermometers in most public places to detect infected persons. It is time-consuming to track the body temperature of each person. Besides, close contact with infected persons can spread the virus from the infected persons to the individual performing the screening or vice-versa. In this research, we propose a device architecture capable of automatically detecting the coronavirus or new COVID strain from thermal images; the proposed architecture comprises a smart mask equipped with a thermal imaging system, which reduces human interactions. The thermal camera technology is integrated with the smart mask powered by the Internet of Things (IoT) to proactively monitor the screening procedure and obtain data based on real-time findings. Besides, the proposed system is fitted with facial recognition technology; therefore, it can also display personal information. It will automatically measure the temperature of each person who came into close contact with the infected humans or humans in public spaces, such as markets or offices. The new design is very useful in healthcare and could offer a solution to preventing the growth of the coronavirus. The presented work hasa key focus on the integration of advanced algorithms for the predictive analytics of parameters required for in-depth evaluations. The proposed work and the results are pretty effectual and performance cognizant for predictive analytics. The manuscript and associated research work integrate the IoT and Internet of Everything (IoE) based analytics with sensor technologies with real-time data so that the overall predictions will be more accurate and integrated with the health sector. Supplementary Information The online version contains supplementary material available at 10.1007/s12652-022-04395-7.
Information is the key component towards success when it comes to controlling the decision-makers performance with the quality of a decision. In the modern era, an absolute amount of data is available to organizations for analysis usage. Data is the most important component of the business in the 21st century and a significant number of devices are already equipped with the internet. Based on this the solutions should be studied in order to control and capture the knowledge value pair out of the datasets. Following this, the decision-makers should have access to insightful and valuable data based on the dynamic high volume & velocity using big data analytics. Our research focuses on how to integrate big data analytics into the decision-making process. The B-DAD (big data analytics and decision) framework was created to map the big data tools, its architecture, and analytics for the several decision-making steps by the adoption of methodology based on design science. The ideal goal and offerings of the framework are adopting big data analytics in order to intensify & aid decision making for the organization using an integration of big data analytics into the corresponding decision-making process. Thus, the experiment was carried out in the retail domain to test the framework. As an end result, the results showcased the value-added if big data analytics is integrated with corresponding decision-making activity.
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