Garrett Butts details military drone innovation effort aimed at speeding deployment and reducing cost in an exclusive interview with Fox News Digital. As the war between Israel and Iran intensifies, one Army drone expert is warning that the U.S. must stay ready, and fast. Garrett Butts is helping lead the charge by building smarter, cheaper unmanned aircraft systems (UAS) in-house for the battlefield. In an exclusive interview with Fox News Digital on Tuesday, Butts described how his team is creating drone technology from scratch, often using parts it took nearly a year to legally obtain. "We're a transformation and contact unit," said Butts, who serves with the 1st Cavalry Division.

Not only has China's largest EV maker BYD unveiled good, better, and best tiers for its advanced driver-assistance system (ADAS), it announced last week that the tech--marketed somewhat immodestly as "God's Eye"--will now be fitted as standard to 21 of BYD's 30 cars split across four brands. Even the 9,500 Seagull hatchback, the cheapest of BYD's EVs, will ship with the base level of God's Eye at no extra cost, while the 233,500 Yangwang U9 electric supercar will get the top-tier iteration. However, BYD's ADAS system could be as misleadingly named as Tesla's Full Self-Driving (FSD). Including ADAS for free will no doubt rile BYD's smaller rivals in China's innovative but cutthroat auto market. Comparatively low-tech Toyota, VW, and Nissan may weaken further, and Tesla--which has yet to gain permission for FSD in China--could also struggle.

From cheeky aubergines to friendly smiley faces, emoji now form a staple part of many of our day-to-day messages. Emoji are particularly popular on dating apps, with as many as 81 per cent of Tinder members opting to use the characters while messaging potential dates. Now, Tinder has revealed the top emoji used by its members in their dating app bios. The'face with tears of joy' tops the list, with daters including it in their bio to indicate they're looking for someone who can make them laugh. However, some of the other top emoji have slightly more cryptic meanings - here's what they really indicate daters are looking for.

Artificial Intelligence is more and more pervasive in our lives. Many important decisions are delegated to AI algorithms: accessing higher education, determining prison sentences, autonomously driving vehicles... Engineers and researchers are educated to this field, while the general population has very little knowledge about AI. As a result, they are very sensitive to the (more or less accurate) ideas disseminated by the media: an AI that is unbiased, infallible, and will either save the world or lead to its demise. We therefore believe, as highlighted by UNESCO, that it is essential to provide the population with a general understanding of AI algorithms, so that they can choose wisely whether to use them (or not). To this end, we propose a serious game in the form of a civic debate aiming at selecting an AI solution to control a pandemic. This game is targeted at high school students, it was first experimented during a science fair, and is now available freely.

Google combines language models with a physics simulator. This is a central fact in the debate about the role of Deep Learning on the way to more general forms of artificial intelligence. Methods like chain-of-thought prompting, more training data and larger models like PaLM led to better results in benchmarks, but not to a fundamental breakthrough. Researchers are therefore experimenting with hybrid approaches that use the language capabilities of AI models to issue queries to specialized, external libraries or systems. Check your inbox or spam folder to confirm your subscription.

Adobe's Lightroom software uses new AI technology to select objects, people, clothing and facial features in an attempt to make photo editing faster and more powerful. The technology can remove some of the drudgery of photo editing, picking out portions of an image pixel by pixel. The new technology is available in Lightroom, Lightroom Classic and the smartphone versions of the photo cataloging and editing software, the company said Tuesday at its Max conference. The new tools for selecting objects and people expand earlier AI tools that select subjects and skies. By signing up, you agree to our Terms of Use and acknowledge the data practices in our Privacy Policy.

Successful and effective communication between humans and AI relies on a shared experience of the world. By training solely on written text, current language models (LMs) miss the grounded experience of humans in the real-world -- their failure to relate language to the physical world causes knowledge to be misrepresented and obvious mistakes in their reasoning. We present Mind's Eye, a paradigm to ground language model reasoning in the physical world. Given a physical reasoning question, we use a computational physics engine (DeepMind's MuJoCo) to simulate the possible outcomes, and then use the simulation results as part of the input, which enables language models to perform reasoning. Experiments on 39 tasks in a physics alignment benchmark demonstrate that Mind's Eye can improve reasoning ability by a large margin (27.9% zero-shot, and 46.0% few-shot absolute accuracy improvement on average). Smaller language models armed with Mind's Eye can obtain similar performance to models that are 100x larger. Finally, we confirm the robustness of Mind's Eye through ablation studies.

The world is getting more and more digitized with each passing day, especially with the augmentation of hybrid working spaces. Millions of lines of data are being processed and stored online with an increasing need to protect and secure that data. In a digital world such as this, the threat to a company's cybersecurity is massive, especially given the large volume of data. The question that arises is, can humans handle the task of securing the data effectively? That's where Artificial intelligence (AI) comes into the picture – to bridge the gaps when it comes to a robust cybersecurity mechanism.

Artificial intelligence (AI) systems power the world we live in. Deep neural networks (DNNs) are able to solve tasks in an ever-expanding landscape of scenarios, but our eagerness to apply these powerful models leads us to focus on their performance and deprioritises our ability to understand them. Current research in the field of explainable AI tries to bridge this gap by developing various perturbation or gradient-based explanation techniques. For images, these techniques fail to fully capture and convey the semantic information needed to elucidate why the model makes the predictions it does. In this work, we develop a new form of explanation that is radically different in nature from current explanation methods, such as Grad-CAM.

The Internet of Things (IoT) industry has grown tremendously in 2022. IoT connects all objects to interact with each other using a wireless protocol to add seamless connectivity in human life. It's the world where devices of every shape and size are manufactured with "smart" capabilities that allow them to communicate and interact with other devices, exchange data, make autonomous decisions and perform useful tasks based on preset conditions. It's the world where technology will make life richer, easier, safer and more comfortable. IoT is a giant network of things and people communicating with each other using various wired and wireless technologies.