There is no current evidence that AI can be controlled safely, according to an extensive review, and without proof that AI can be controlled, it should not be developed, a researcher warns.There is no current evidence that AI can be controlled safely, according to an extensive review, and without proof that AI can be controlled, it should not be developed, a researcher warns.Machine learning & AI[#item_full_content]
In a world where you can create a virtual clone of a person in a matter of minutes, how do we know what’s real? It may sound like dystopian science fiction, but deepfakes are a reality causing serious social, financial and personal harm.In a world where you can create a virtual clone of a person in a matter of minutes, how do we know what’s real? It may sound like dystopian science fiction, but deepfakes are a reality causing serious social, financial and personal harm.Security[#item_full_content]
The landscape of artificial intelligence (AI) applications has traditionally been dominated by the use of resource-intensive servers centralized in industrialized nations. However, recent years have witnessed the emergence of small, energy-efficient devices for AI applications, a concept known as tiny machine learning (TinyML).The landscape of artificial intelligence (AI) applications has traditionally been dominated by the use of resource-intensive servers centralized in industrialized nations. However, recent years have witnessed the emergence of small, energy-efficient devices for AI applications, a concept known as tiny machine learning (TinyML).[#item_full_content]
The landscape of artificial intelligence (AI) applications has traditionally been dominated by the use of resource-intensive servers centralized in industrialized nations. However, recent years have witnessed the emergence of small, energy-efficient devices for AI applications, a concept known as tiny machine learning (TinyML).The landscape of artificial intelligence (AI) applications has traditionally been dominated by the use of resource-intensive servers centralized in industrialized nations. However, recent years have witnessed the emergence of small, energy-efficient devices for AI applications, a concept known as tiny machine learning (TinyML).Computer Sciences[#item_full_content]
In several applications of computer vision, such as augmented reality and self-driving cars, estimating the distance between objects and the camera is an essential task. Depth from focus/defocus is one of the techniques that achieve such a process using the blur in the images as a clue. Depth from focus/defocus usually requires a stack of images of the same scene taken with different focus distances, a technique known as “focal stack.”In several applications of computer vision, such as augmented reality and self-driving cars, estimating the distance between objects and the camera is an essential task. Depth from focus/defocus is one of the techniques that achieve such a process using the blur in the images as a clue. Depth from focus/defocus usually requires a stack of images of the same scene taken with different focus distances, a technique known as “focal stack.”[#item_full_content]
In several applications of computer vision, such as augmented reality and self-driving cars, estimating the distance between objects and the camera is an essential task. Depth from focus/defocus is one of the techniques that achieve such a process using the blur in the images as a clue. Depth from focus/defocus usually requires a stack of images of the same scene taken with different focus distances, a technique known as “focal stack.”In several applications of computer vision, such as augmented reality and self-driving cars, estimating the distance between objects and the camera is an essential task. Depth from focus/defocus is one of the techniques that achieve such a process using the blur in the images as a clue. Depth from focus/defocus usually requires a stack of images of the same scene taken with different focus distances, a technique known as “focal stack.”Computer Sciences[#item_full_content]
Artificial intelligence (AI) tools aimed at the general public, such as ChatGPT, Bard, CoPilot and Dall-E have incredible potential to be used for good.Artificial intelligence (AI) tools aimed at the general public, such as ChatGPT, Bard, CoPilot and Dall-E have incredible potential to be used for good.Security[#item_full_content]
With the ability to analyze large datasets to identify patterns and predict outcomes, all at the click of a button, artificial intelligence (AI) is revolutionizing how we live and work. From offering personalized recommendations to automating tedious tasks, AI can help us make better decisions, work smarter and reduce the likelihood of errors.With the ability to analyze large datasets to identify patterns and predict outcomes, all at the click of a button, artificial intelligence (AI) is revolutionizing how we live and work. From offering personalized recommendations to automating tedious tasks, AI can help us make better decisions, work smarter and reduce the likelihood of errors.Machine learning & AI[#item_full_content]
A team of AI researchers at Google’s DeepMind project, working with a colleague from the University of Southern California, has developed a vehicle for allowing large language models (LLMs) to find and use task-intrinsic reasoning structures as a means for improving returned results.A team of AI researchers at Google’s DeepMind project, working with a colleague from the University of Southern California, has developed a vehicle for allowing large language models (LLMs) to find and use task-intrinsic reasoning structures as a means for improving returned results.[#item_full_content]
A team of AI researchers at Google’s DeepMind project, working with a colleague from the University of Southern California, has developed a vehicle for allowing large language models (LLMs) to find and use task-intrinsic reasoning structures as a means for improving returned results.A team of AI researchers at Google’s DeepMind project, working with a colleague from the University of Southern California, has developed a vehicle for allowing large language models (LLMs) to find and use task-intrinsic reasoning structures as a means for improving returned results.Computer Sciences[#item_full_content]
