--The study "Prediction of Highway Traffic Flow Based on Artificial Intelligence Algorithms Using California Traffic Data" presents a machine learning-based traffic flow prediction model to address global traffic congestion issues. The study employed Multiple Linear Regression (MLR) and Random Forest (RF) algorithms, analyzing data collection intervals ranging from 30 seconds to 15 minutes. Using R, MAE, and RMSE as performance metrics, the analysis revealed that both MLR and RF models performed optimally with 10-minute data collection intervals. These findings are expected to contribute to future traffic congestion solutions and efficient traffic management. Currently, traffic congestion is one of the most pressing issues faced globally.

Cloud computing environments are increasingly vulnerable to security threats such as distributed denial-of-service (DDoS) attacks and SQL injection. Traditional security mechanisms, based on rule matching and feature recognition, struggle to adapt to evolving attack strategies. This paper proposes an adaptive security protection framework leveraging deep learning to construct a multi-layered defense architecture. The proposed system is evaluated in a real-world business environment, achieving a detection accuracy of 97.3%, an average response time of 18 ms, and an availability rate of 99.999%. Experimental results demonstrate that the proposed method significantly enhances detection accuracy, response efficiency, and resource utilization, offering a novel and effective approach to cloud computing security.

This paper elucidates the importance of governing an artificial intelligence model post-deployment and overseeing potential fluctuations in the distribution of present data in contrast to the training data. The concepts of data drift and concept drift are explicated, along with their respective foundational distributions. Furthermore, a range of metrics is introduced, which can be utilized to scrutinize the model's performance concerning potential temporal variations.

People in Texas sounded off on AI job displacement, with half of the people who spoke to Fox News convinced that the tech will rob them of work. Artificial intelligence algorithms can help predict a person's political ideology based on their facial characteristics, a study conducted in Denmark found. The tech found right-wing politicians were more likely to have happy facial expressions in photos while people pictured with neutral facial expressions were more likely to identify as left-wing, the study said. The study, "Using deep learning to predict ideology from facial photographs: expressions, beauty, and extra-facial information," found that AI can predict a person's political ideology with 61% accuracy when analyzing a photo of a person. Deep learning, a method in AI where computer scientists teach computers to learn and process information similar to humans, can be used to make predictions about people based on photographs alone, the researchers explained in their paper, which was published in Scientific Reports.

Artificial intelligence (AI) has revolutionized many industries, and healthcare is no exception. In recent years, AI has made significant strides in healthcare, from assisting doctors in diagnosing diseases to helping researchers develop new drugs. However, with the rapid advances in AI, there is growing concern about whether AI will take over healthcare jobs. Artificial Intelligence has many applications in healthcare, including medical imaging, drug discovery, and patient monitoring. One of the most significant benefits of Artificial Intelligence in healthcare is its ability to analyze vast amounts of data quickly and accurately. This allows doctors and researchers to make more informed decisions and identify patterns that would be difficult or impossible to detect manually.

Australian and Iraqi engineers have designed a system to remotely measure blood pressure by filming a person's forehead and extracting cardiac signals using artificial intelligence algorithms. Using the same remote-health technology they pioneered to monitor vital health signs from a distance, engineers from the University of South Australia and Baghdad's Middle Technical University have designed a non-contact system to accurately measure systolic and diastolic pressure. It could replace the existing uncomfortable and cumbersome method of strapping an inflatable cuff to a patient's arm or wrist, the researchers claim. In a new paper published in Inventions, the researchers describe the technique, which involves filming a person from a short distance for 10 seconds and extracting cardiac signals from two regions in the forehead, using artificial intelligence algorithms. The systolic and diastolic readings were around 90 per cent accurate, compared to the existing instrument (a digital sphygmomanometer) used to measure blood pressure, that is itself subject to errors.

New Delhi: Are you thinking about who is the sensational music composer on the latest trending songs? It might just be Artificial Intelligence. Progress in Artificial Intelligence and music is on fire, thanks to the creative researchers who are innovating and working hard to bring AI into the music world. A researcher from United States, have devised a new approach – Music Prediction method, using which music can be generated with a very high accuracy. Composer is the main backbone of any soothing or funky tunes that brings a song to life.

AI is behind many small advances such as optimising the ripening of fruit, an artificial sense of smell, a system that improves student performance, learning more about Don Quixote or creating a doll to accompany our elders. These are curious and lesser-known examples of how artificial intelligence can be applied to our benefit on a smaller scale. Fifteen examples of this are worth mentioning. The Tekniker technology centre, located in the Basque Country, has developed a tool to detect characteristics or defects in bananas and optimise their ripening through image processing based on artificial intelligence. Image processing based on neural networks is an artificial intelligence technique that can help develop solutions for sectors such as the food industry to identify errors in production and processing and improve product quality.

Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! Most computers and algorithms -- including, at this point, many artificial intelligence (AI) applications -- run on general-purpose circuits called central processing units or CPUs. Though, when some calculations are done often, computer scientists and electrical engineers design special circuits that can perform the same work faster or with more accuracy. Now that AI algorithms are becoming so common and essential, specialized circuits or chips are becoming more and more common and essential.

I believe that anyone who has seen the movie "Artificial Intelligence" was deeply impressed by the cute-looking, kind and soft-hearted robot, David, who longed for the love of human mother Monica. David was a robot made by a robot company that could love people. He replaced Monica's son Henry, who is terminally ill and falls into a vegetative state. When Henry wakes up, David is faced with the situation of being destroyed. He turns into a real human boy, and seeks to gain the love of his mother, Monica.