Leading computer scientists from around the world have shared their vision for the future of artificial intelligence—and it resembles the capabilities of Star Trek character “The Borg.”Leading computer scientists from around the world have shared their vision for the future of artificial intelligence—and it resembles the capabilities of Star Trek character “The Borg.”[#item_full_content]

Walter Benjamin came up with aura and authenticity in “The Work of Art in the Age of Mechanical Reproduction” in 1936 to describe the value of original artworks created by artists instead of mechanical copies. He wanted to defend artificiality and support traditional fine arts.Walter Benjamin came up with aura and authenticity in “The Work of Art in the Age of Mechanical Reproduction” in 1936 to describe the value of original artworks created by artists instead of mechanical copies. He wanted to defend artificiality and support traditional fine arts.[#item_full_content]

Unmanned aerial vehicles (UAVs), also known as drones, have already proved to be valuable tools for tackling a wide range of real-world problems, ranging from the monitoring of natural environments and agricultural plots to search and rescue missions and the filming of movie scenes from above. So far, most of these problems have been tackled using one drone at a time, rather than teams of multiple autonomous or semi-autonomous UAVs.Unmanned aerial vehicles (UAVs), also known as drones, have already proved to be valuable tools for tackling a wide range of real-world problems, ranging from the monitoring of natural environments and agricultural plots to search and rescue missions and the filming of movie scenes from above. So far, most of these problems have been tackled using one drone at a time, rather than teams of multiple autonomous or semi-autonomous UAVs.[#item_full_content]

In our current age of artificial intelligence, computers can generate their own “art” by way of diffusion models, iteratively adding structure to a noisy initial state until a clear image or video emerges.In our current age of artificial intelligence, computers can generate their own “art” by way of diffusion models, iteratively adding structure to a noisy initial state until a clear image or video emerges.[#item_full_content]

A new method for classifying electronic music has been developed by researchers in China. The approach offers a novel solution in an age of exploding digital content to curating music libraries and streaming services.A new method for classifying electronic music has been developed by researchers in China. The approach offers a novel solution in an age of exploding digital content to curating music libraries and streaming services.[#item_full_content]

AI has long since surpassed humans in cognitive matters that were once considered the supreme disciplines of human intelligence like chess or Go. Some even believe it is superior when it comes to human emotional skills such as empathy. This does not just seem to be some companies’ talking big for marketing reasons; empirical studies suggest that people perceive ChatGPT in certain health situations as more empathic than human medical staff. Does this mean that AI is really empathetic?AI has long since surpassed humans in cognitive matters that were once considered the supreme disciplines of human intelligence like chess or Go. Some even believe it is superior when it comes to human emotional skills such as empathy. This does not just seem to be some companies’ talking big for marketing reasons; empirical studies suggest that people perceive ChatGPT in certain health situations as more empathic than human medical staff. Does this mean that AI is really empathetic?[#item_full_content]

A collaboration between AI researchers at Stanford University and Notbad AI Inc. has resulted in the development of an algorithm that allows current chatbots to mull over possible responses to a query before giving its final answer. The team has published a paper on the arXiv preprint server describing their new approach and how well their algorithm worked when paired with an existing chatbot.A collaboration between AI researchers at Stanford University and Notbad AI Inc. has resulted in the development of an algorithm that allows current chatbots to mull over possible responses to a query before giving its final answer. The team has published a paper on the arXiv preprint server describing their new approach and how well their algorithm worked when paired with an existing chatbot.[#item_full_content]

Researchers in Denmark are harnessing artificial intelligence and data from millions of people to help anticipate the stages of an individual’s life all the way to the end, hoping to raise awareness of the technology’s power, and its perils.Researchers in Denmark are harnessing artificial intelligence and data from millions of people to help anticipate the stages of an individual’s life all the way to the end, hoping to raise awareness of the technology’s power, and its perils.[#item_full_content]

The bustling streets of a modern city are filled with countless individuals using their smartphones for streaming videos, sending messages and browsing the web. In the era of rapidly expanding 5G networks and the omnipresence of mobile devices, the management of cellular traffic has become increasingly complex.The bustling streets of a modern city are filled with countless individuals using their smartphones for streaming videos, sending messages and browsing the web. In the era of rapidly expanding 5G networks and the omnipresence of mobile devices, the management of cellular traffic has become increasingly complex.[#item_full_content]

Indoor positioning is transforming with applications demanding precise location tracking. Traditional methods, including fingerprinting and sensor-based techniques, though widely used, face significant drawbacks, such as the need for extensive training data, poor scalability, and reliance on additional sensor information. Recent advancements have sought to leverage deep learning, yet issues such as low scalability and high computational costs remain unaddressed.Indoor positioning is transforming with applications demanding precise location tracking. Traditional methods, including fingerprinting and sensor-based techniques, though widely used, face significant drawbacks, such as the need for extensive training data, poor scalability, and reliance on additional sensor information. Recent advancements have sought to leverage deep learning, yet issues such as low scalability and high computational costs remain unaddressed.[#item_full_content]