Artificial intelligence (AI) has captured the imagination of a wide variety of businesses. I have this image of CEOs in boardrooms around the globe declaring, "We must have AI! Our competitors use AI! We can't be left behind!" There might be some table-pounding associated with this scenario. There will certainly be corporate minions scurrying around to fulfill the AI dreams of their CEO.

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Minister of State for Fisheries George Kurian launches project; 10 lakh pompano, cobia fingerlings to be deposited in 10 selected locations

Recent investments in contact center AI are reshaping the industry with better response times, issue resolution and enhanced customer service experiences.

Artificial Intelligence is everywhere and being discussed by everyone it seems. But, what is AI? By definition, it is a field of computer science that is focusing on creating intelligence systems; AI is making computers capable of performing tasks that require human intelligence. We have been using computers for decades, but the introduction of AI […]

Berlin-based x-cardiac GmbH is pleased to announce that Freiburg University Hospital has become the second pilot customer for its AI-based software "x-c-bleeding" for predicting severe bleeding complications after cardiac surgery. With the implementation of "x-c-bleeding", the University Hospital Freiburg takes another important step towards AI-based medicine.

Dubai is increasingly becoming a global center for artificial intelligence. To this end, the metropolis of the day after tomorrow on the Gulf has pledged to train one million people in AI prompting over the next three years. It is the first program of its kind in the world.

(EMAILWIRE.COM, November 01, 2024 ) Artificial Intelligence Chipset Market size was valued US$ 20.76 Bn in 2023 and the total revenue is expected to grow at 40% from 2024 to 2030, reaching US$ 218.85 Bn. by 2030. The AI chipset market is experiencing rapid growth, driven by increasing adoption...

Provides detailed information on various types of artificial and natural sweeteners and provides guidance on which sweeteners are safe to consume and which to avoid.

DesktopMates are animated human like characters that live on your desktop as your personal interactive companion & assistant capable of speech & doing tasks for you using Microsoft Agent and Artificial Intelligence Technology ... Free Start Up!

For the past several months I’ve been co-writing a book that was recently published by O’Reilly. Called Getting Started with Artificial Intelligence: A Practical Guide to Building Enterprise Applications, the book is currently offered by IBM as a free download. Written with Josh Zheng to introduce developers and technical managers to using artificial intelligence when […]

The post Getting Started with Artificial Intelligence: A Practical Guide to Building Applications in the Enterprise first appeared on Tom Markiewicz.

Imagine giving a chatbot the power to control and manage your computer. This exciting, but potentially dangerous idea is making people nervous.

Recent research has begun to reveal the extent of AI's impact on electronic waste and pollution, prompting concerns among scientists and environmentalists.

Paula MacDowell, Kristin Moskalyk, Katrina Korchinski, Dirk Morrison, Canadian Journal of Learning and Technology, Nov 13, 2024

This paper reports on a process where thirty-five teachers enrolled in an elective three-credit multimedia design course "engaged in experiential activities focussed on developing artificial intelligence (AI) literacy, alongside a collaborative assignment to co-author an open-access textbook, Teaching and Creating With Generative Artificial Intelligence." In the process, "the Student Artificial Intelligence Literacy (SAIL) framework was developed (illustrated)." The paper concludes with the usual recommendations ('do no harm', 'develop communication skills', etc.). Each participant wrote a chapter, though a common template was used. I very much like the idea of producing a useful open resource as part of class activities. Oddly, the article doesn't provide a link to the textbook, but I found it here. It's a nice selection of 'how-to' articles that readers, I think, will find useful. One chapter (chapter 20 1/2?) is missing.

The Advertising Standards Authority rules an artificial grass firm's billboard "objectified" women.

Although artificial intelligence provides a new method to gather, process, analyse data, generate insights, and offer customised solutions, such methods could change how marketers deal with customers, and there is a lack of literature to portray the application of artificial intelligence in marketing. This study aims to recognise and portray the use of artificial intelligence from a marketing standpoint, as well as to provide a conceptual framework for the application of artificial intelligence in marketing. This study uses a systematic literature review analysis as a research method to achieve the aims. Data from 142 articles were extracted from the Scopus database using relevant search terms for artificial intelligence and marketing. The systematic review identified significant usage of artificial intelligence in conversational artificial intelligence, content creation, audience segmentation, predictive analytics, personalisation, paid ads, sales forecasting, dynamic pricing, and recommendation engines and the bibliometric analysis produced the trend in co-authorship, citation, bibliographic coupling, and co-citation analysis. Practitioners and academics may use this study to decide on the marketing area in which artificial intelligence can be invested and used.

Constrained programming is the concept used to select possible alternatives from an incredibly diverse range of candidates. This paper proposes an AI-assisted Backtracking Scheme (AI-BS) by integrating the generic backtracking algorithm with Artificial Intelligence (AI). The detailed study observes that the extreme dual ray associated with the infeasible linear program can be automatically extracted from minimum unfeasible sets. Constraints are used in artificial intelligence to list all possible values for a group of variables in a given universe. To put it another way, a solution is a way of assigning a value to each variable that these values satisfy all constraints. Furthermore, this helps the study reach a decreased search area for smart backtracking without paying high costs. The evaluation results exhibit that the IB-BC algorithm-based smart electricity schedule controller performs better electricity bill during the scheduled periods than comparison approaches such as binary backtracking and binary particle swarm optimiser.

In order to reduce the challenges encountered by learners and educators in engaging in educational activities, this paper classifies learners' roles in virtual learning communities, and explores the role of behaviour characteristics and their positions in collaborative knowledge construction networks in promoting the process of knowledge construction. This study begins with an analysis of the relationship structure among learners in the virtual learning community and then applies the FCM algorithm to arrange learners into various dimensional combinations and create distinct learning communities. The test results demonstrate that the FCM method performs consistently during the clustering process, with less performance oscillations, and good node aggregation, the ARI value of the model is up to 0.90. It is found that they play an important role in the social interaction of learners' virtual learning community, which plays a certain role in promoting the development of artificial intelligence.

Physiological indicators are an important basis for reflecting the physiological health status of the human body and play an important role in medical practice. Association rules have also been one of the important research hotspots in recent years. This study aims to create a data mining system of association rules and artificial intelligence in biochemical indicators of sports training. This article uses Markov logic for network creation and system training, and tests whether the Markov logic network can be associated with the training system. The results show that the accuracy and recall rate obtained are about 90%, which shows that it is feasible to establish biochemical indicators of sports training based on Markov logic network, and the system has universal, guiding and constructive significance, ensuring that the construction of training system indicators will not go in the wrong direction.

The supply chains of the Canadian forest products industry are largely dependent on accurate demand forecasts. The USA is the major export market for the Canadian forest products industry, although some Canadian provinces are also exporting forest products to other global markets. However, it is very difficult for each province to develop accurate demand forecasts, given the number of factors determining the demand of the forest products in the global markets. We develop multi-layer feed-forward artificial neural network (ANN) models for demand forecasting of the Canadian forest products industry. We find that the ANN models have lower prediction errors and higher threshold statistics as compared to that of the traditional models for predicting the demand of the Canadian forest products. Accurate future demand forecasts will not only help in improving the short-term profitability of the Canadian forest products industry, but also their long-term competitiveness in the global markets.

With the rapid development of Artificial Intelligence (AI) technology, significant breakthroughs have been made in its application in many fields. Especially, in the field of enterprise human resource management and employee performance evaluation, AI has demonstrated its powerful ability to optimise and improve performance. This study explores the application of AI in enterprise human resource management and how to use AI to evaluate employee performance. The research includes analysing and comparing existing AI-driven human resource management models, evaluating how AI can help improve employee performance and leadership styles, and designing and developing human resource management computer systems for enterprise employees. Through empirical research and case analysis, this study proposes a new AI-optimised employee performance evaluation model and explores its application and effect in practice. In general, the application of AI can improve the efficiency and accuracy of enterprise human resource management, and provide new possibilities for employee performance evaluation. At present, artificial intelligence technology has been widely used in various fields of daily life, especially in corporate human resource management, providing better support for the development of enterprises.

The major technological developments have changed the traditional way of doing business. These developments have facilitated whistle-blowing. Access to data is easier and faster and communicating with the public can be done in seconds. Another development is the artificial intelligence (AI) which enters the business workplace in different forms challenging the traditional working relations. The combination of these concepts gives the idea of artificial whistle-blowing or robot whistle-blowing. The concept is that a machine should conceive and report relevant wrongdoing avoiding the traditional model of whistle-blowing where the employee is the person who should report. This concept, yet unexplored, presents interesting positive and negative aspects. The purpose of this contribution is to present the idea of artificial whistle-blowing and its advantages and disadvantages for the business sector. As a conclusion, this paper suggests that the concept of artificial whistle-blowing needs still to be researched and an optimal solution, for the time being, is to permit artificial whistle-blowing as a helping tool for the employees to detect wrongdoings but report them themselves.

Aim/Purpose: This paper aims to empirically quantify the financial distress caused by the COVID-19 pandemic on companies listed on Amman Stock Exchange (ASE). The paper also aims to identify the most important predictors of financial distress pre- and mid-pandemic. Background: The COVID-19 pandemic has had a huge toll, not only on human lives but also on many businesses. This provided the impetus to assess the impact of the pandemic on the financial status of Jordanian companies. Methodology: The initial sample comprised 165 companies, which was cleansed and reduced to 84 companies as per data availability. Financial data pertaining to the 84 companies were collected over a two-year period, 2019 and 2020, to empirically quantify the impact of the pandemic on companies in the dataset. Two approaches were employed. The first approach involved using Multiple Discriminant Analysis (MDA) based on Altman’s (1968) model to obtain the Z-score of each company over the investigation period. The second approach involved developing models using Artificial Neural Networks (ANNs) with 15 standard financial ratios to find out the most important variables in predicting financial distress and create an accurate Financial Distress Prediction (FDP) model. Contribution: This research contributes by providing a better understanding of how financial distress predictors perform during dynamic and risky times. The research confirmed that in spite of the negative impact of COVID-19 on the financial health of companies, the main predictors of financial distress remained relatively steadfast. This indicates that standard financial distress predictors can be regarded as being impervious to extraneous financial and/or health calamities. Findings: Results using MDA indicated that more than 63% of companies in the dataset have a lower Z-score in 2020 when compared to 2019. There was also an 8% increase in distressed companies in 2020, and around 6% of companies came to be no longer healthy. As for the models built using ANNs, results show that the most important variable in predicting financial distress is the Return on Capital. The predictive accuracy for the 2019 and 2020 models measured using the area under the Receiver Operating Characteristic (ROC) graph was 87.5% and 97.6%, respectively. Recommendations for Practitioners: Decision makers and top management are encouraged to focus on the identified highly liquid ratios to make thoughtful decisions and initiate preemptive actions to avoid organizational failure. Recommendation for Researchers: This research can be considered a stepping stone to investigating the impact of COVID-19 on the financial status of companies. Researchers are recommended to replicate the methods used in this research across various business sectors to understand the financial dynamics of companies during uncertain times. Impact on Society: Stakeholders in Jordanian-listed companies should concentrate on the list of most important predictors of financial distress as presented in this study. Future Research: Future research may focus on expanding the scope of this study by including other geographical locations to check for the generalisability of the results. Future research may also include post-COVID-19 data to check for changes in results.

Nowadays, we are surrounded by artifacts that are capable of adaptive behavior, such as electric pots, boiler timers, automatic doors, and robots. The literature concerning human beings’ conceptions of “traditional” artifacts is vast, however, little is known about our conceptions of behaving artifacts, nor of the influence of the interaction with such artifacts on cognitive development, especially among children. Since these artifacts are provided with an artificial “mind,” it is of interest to assess whether and how children develop a Theory of Artificial Mind (ToAM) which is distinct from their Theory of Mind (ToM). The study examined a new theoretical scheme named ToAM (Theory of Artificial Mind) by means of qualitative and quantitative methodology among twenty four 5-7 year old children from central Israel. It also examined the effects of interacting with behaving artifacts (constructing versus observing the robot’s behavior) using the “RoboGan” interface on children’s development of ToAM and their ToM and looked for conceptions that evolve among children while interacting with behaving artifacts which are indicative of the acquisition of ToAM. In the quantitative analysis it was found that the interaction with behaving artifacts, whether as observers or constructors and for both age groups, brought into awareness children’s ToM as well as influenced their ability to understand that robots can behave independently and based on external and environmental conditions. In the qualitative analysis it was found that participating in the intervention influenced the children’s ToAM for both constructors and for the younger observer. Engaging in building the robot’s behavior influenced the children’s ability to explain several of the robots’ behaviors, their understanding of the robot’s script-based behavior and rule-based behavior and the children’s metacognitive development. The theoretical and practical importance of the study is discussed.

Aim/Purpose: Using Artificial Intelligence with Deep Learning (DL) techniques, which mimic the action of the brain, to improve a student’s grammar learning process. Finding the subject of a sentence using DL, and learning, by way of this computer field, to analyze human learning processes and mistakes. In addition, showing Artificial Intelligence learning processes, with and without a general overview of the problem that it is under examination. Applying the idea of the general perspective that the network gets on the sentences and deriving recommendations from this for teaching processes. Background: We looked for common patterns of computer errors and human grammar mistakes. Also deducing the neural network’s learning process, deriving conclusions, and applying concepts from this process to the process of human learning. Methodology: We used DL technologies and research methods. After analysis, we built models from three types of complex neuronal networks – LSTM, Bi-LSTM, and GRU – with sequence-to-sequence architecture. After this, we combined the sequence-to- sequence architecture model with the attention mechanism that gives a general overview of the input that the network receives. Contribution: The cost of computer applications is cheaper than that of manual human effort, and the availability of a computer program is much greater than that of humans to perform the same task. Thus, using computer applications, we can get many desired examples of mistakes without having to pay humans to perform the same task. Understanding the mistakes of the machine can help us to under-stand the human mistakes, because the human brain is the model of the artificial neural network. This way, we can facilitate the student learning process by teaching students not to make mistakes that we have seen made by the artificial neural network. We hope that with the method we have developed, it will be easier for teachers to discover common mistakes in students’ work before starting to teach them. In addition, we show that a “general explanation” of the issue under study can help the teaching and learning process. Findings: We performed the test case on the Hebrew language. From the mistakes we received from the computerized neuronal networks model we built, we were able to classify common human errors. That is, we were able to find a correspondence between machine mistakes and student mistakes. Recommendations for Practitioners: Use an artificial neural network to discover mistakes, and teach students not to make those mistakes. We recommend that before the teacher begins teaching a new topic, he or she gives a general explanation of the problems this topic deals with, and how to solve them. Recommendations for Researchers: To use machines that simulate the learning processes of the human brain, and study if we can thus learn about human learning processes. Impact on Society: When the computer makes the same mistakes as a human would, it is very easy to learn from those mistakes and improve the study process. The fact that ma-chine and humans make similar mistakes is a valuable insight, especially in the field of education, Since we can generate and analyze computer system errors instead of doing a survey of humans (who make mistakes similar to those of the machine); the teaching process becomes cheaper and more efficient. Future Research: We plan to create an automatic grammar-mistakes maker (for instance, by giving the artificial neural network only a tiny data-set to learn from) and ask the students to correct the errors made. In this way, the students will practice on the material in a focused manner. We plan to apply these techniques to other education subfields and, also, to non-educational fields. As far as we know, this is the first study to go in this direction ‒ instead of looking at organisms and building machines, to look at machines and learn about organisms.

Aim/Purpose: This paper examines the transformative impact of Artificial Intelligence (AI) on professional skills in organizations and explores strategies to address the resulting challenges. Background: The rapid integration of AI across various sectors is automating tasks and reducing cognitive workload, leading to increased productivity but also raising concerns about job displacement. Successfully adapting to this transformation requires organizations to implement new working models and develop strategies for upskilling and reskilling their workforce. Methodology: This review analyzes recent research and practice on AI's impact on human skills in organizations. We identify key trends in how AI is reshaping professional competencies and highlight the crucial role of transversal skills in this evolving landscape. The paper also discusses effective strategies to support organizations and guide workers through upskilling and reskilling processes. Contribution: The paper contributes to the existing body of knowledge by examining recent trends in AI's impact on professional skills and workplaces. It emphasizes the importance of transversal skills and identifies strategies to support organizations and workers in meeting upskilling and reskilling challenges. Our findings suggest that investing in workforce development is crucial for ensuring that the benefits of AI are equitably distributed among all stakeholders. Findings: Our findings indicate that organizations must employ a proactive approach to navigate the AI-driven transformation of the workplace. This approach involves mapping the transversal skills needed to address current skill gaps, helping workers identify and develop skills required for effective AI adoption, and implementing processes to support workers through targeted training and development opportunities. These strategies are essential for ensuring that workers' attitudes and mental models towards AI are adaptable and prepared for the changing labor market. Recommendation for Researchers: We emphasize the need for researchers to adopt a transdisciplinary approach when studying AI's impact on the workplace. Given AI's complexity and its far-reaching implications across various fields including computer science, mathematics, engineering, and behavioral and social sciences, integrating diverse perspectives is crucial for a holistic understanding of AI's applications and consequences. Future Research: Looking ahead, further research is needed to deepen our understanding of AI's impact on human skills, particularly the role of soft skills in AI adoption within organizations. Future studies should also address the challenges posed by Industry 5.0, which is expected to bring about even more extensive integration of new technologies and automation.

Carlo Lipizzi’s Societal impacts of artificial intelligence and machine learning offers a critical and comprehensive analysis of artificial intelligence (AI) and machine learning’s effects on society. This book provides a balanced perspective, cutting through the

The study shows that artificial intelligence (AI) has become highly important in contemporary computing because of its capacity to efficiently tackle intricate jobs that were typically carried out by people. The authors provide scientific literature that analyzes and

The Faculty of Geo-Information Science and Earth Observation (ITC) at the University of Twente has recently launched an investment programme to strengthen its international academic fields. For 11 pioneering-multidisciplinairy projects a PhD-position is made available, three of them already are filled in. The Department of Natural Resources (NRS) specialises in advanced spatial and temporal analysis and technique development for the environment as well as sustainable agriculture.

Job Description: 

For more information visit the official job offer.

“This year’s two Nobel Laureates in physics have used tools from physics to develop methods that are the foundation of today’s powerful machine learning,” said the Nobel committee.

The post Pioneers in artificial intelligence win the Nobel Prize in physics appeared first on Boston.com.

Adelaide, Australia — Exposing night shift workers to artificial light on the job may improve their sleep and reduce human error, a recent study shows.

As companies seek to enhance precision, increase efficiency and reduce costs, AI-driven computer numerical control (CNC) machining is emerging as a game-changing innovation.

Abstract Social work, as a human rights–based profession, is globally recognized as a profession committed to enhancing human well-being and helping meet the basic needs of all people, with a particular focus on those who are marginalized vulnerable, oppressed, or living in poverty. Artificial intelligence (AI), a sub-discipline of computer science, focuses on developing computers […]

The post Considering a Unified Model of Artificial Intelligence Enhanced Social Work: A Systematic Review was curated by information for practice.

The post CfP: Artificial Intelligence in Health Economics and Outcomes Research was curated by information for practice.

Western Fisheries Research Center scientists are studying the impacts of increased artificial light at night (ALAN) on aquatic ecosystems.  Here's an overview with recent pictures from the field!

Today the national science academies of the G-7 countries issued three joint statements to their respective governments, to inform discussions during the G-7 summit to be held in August in France, as well as to inform ongoing policymaking.

Much digital ink has been spilled on artificial intelligence taking over jobs, but what about AI shaking up the hiring process in the meantime?

A government official said that during the deliberations one of the leaders wondered if AI "replaced or enhanced human skills" and suggested that it should be used in an ethical manner.

Festo to introduce AI-based software for machine uptime, soft-robotic grippers, and economical electric motion at IBIE 2022.

The new tool captures and saves digital images of critical foreign material contaminants that the sorter detects and rejects from the product stream.

Businesses can achieve maximum success during the holiday season by utilizing AI and automation in their retail shipping operations. The holiday season is critical for companies, but the increased sales often come with shipping headaches. Luckily, artificial intelligence (AI) and automation provide key solutions for simplifying shipping for businesses and customers.

From offering consumer insights, enhancing product development to supply chain optimization, experts weigh in on how AI solutions are transforming the beverage industry. 

Rama Naga NV "Venky" Susarla is praised as a senior director and principal architect at Ness Digital Engineering

Ravi Tandon has found success as an Associate Director at HCLTech

Pär Edin is a seasoned strategy and artificial intelligence leader at KPMG LLP

Dan Simion excels in artificial intelligence (AI) in his leading role at Alvarez & Marshal Holdings LLC

Nina Mushiana is a seasoned Engineering Management expert with 20+ years in site reliability, information security, and service management