Can you imagine yourself having a conversation with Windows about what your PC is doing? Microsoft's Windows chief can, and is trying to build a future where those interactions are the norm. In an interview with Microsoft AI product manager Christiaan Brinkhoff, the chief of Microsoft's Windows Devices group, Pavan Davuluri, explained that the company is trying to work toward a future where you can access Windows pretty much anywhere via the cloud, then use AI to fine-tune what you're trying to accomplish. Microsoft described the conversation as "the next chapter of Windows," with an eye toward delivering the changes within the next few years. Davuluri described what he hoped the Windows team could accomplish from a strategic level, without targeting any future version of Windows with these goals in mind.

Advances in sensor technology and automation have ushered in an era of data abundance, where the ability to identify and extract relevant information in real time has become increasingly critical. Traditional filtering approaches, which depend on a priori knowledge, often struggle to adapt to dynamic or unanticipated data features. Machine learning offers a compelling alternative-particularly when training can occur directly at or near the detector. This paper presents a digital hardware architecture designed for real-time neural network training, specifically optimized for high-throughput data ingestion. The design is described in an implementation-independent manner, with detailed analysis of each architectural component and their performance implications. Through system parameterization, the study explores trade-offs between processing speed, model complexity, and hardware resource utilization. Practical examples illustrate how these parameters affect applicability across various use cases. A proof-of-concept implementation on an FPGA demonstrates in-situ training, confirming that computational accuracy is preserved relative to conventional software-based approaches. Moreover, resource estimates indicate that current-generation FPGAs can train networks of approximately 3,500 neurons per chip. The architecture is both scalable and adaptable, representing a significant advancement toward integrating learning directly within detector systems and enabling a new class of extreme-edge, real-time information processing.

Human beings have a hard time dealing with numbers that get really big. The speed of light, the number of atoms in apparently small amounts of matter, the energy being burned every time you ask ChatGPT how many days there are in July. It doesn't really fit into our meat brains. Take, for example, Seagate's latest industrial hard drive, which holds 30 terabytes of data. The new Exos M and IronWolf Pro are the most dense drives single I've ever seen in the standard form factor, narrowly beating out existing 28TB models by leveraging Seagate's innovative Heat-Assisted Magnetic Recording (HAMR) technology.

Ready to turn your house into a smart home? Replacing your dumb bulbs with smart ones is perhaps the easiest way to start. Many smart bulbs can be screwed into existing light sockets, and they can be controlled remotely, put on schedules, change colors, and more. If you're feeling more ambitious, you can venture into smart string lights, light strips, wall and ceiling fixtures, smart lamps, and even smart lighting for the yard or other outdoor areas. Our guide to the best smart lighting can help you navigate the thicket of options, from the various smart light manufacturers (like Philips Hue, LIFX, Nanoleaf, and Wyze) to the connectivity standards (Wi-Fi, Bluetooth, Zigbee, and Matter). We'll also let you know which voice assistants (like Alexa, Apple's Siri, and Google Assistant) work with which lights. TechHive's editors and contributors have been testing smart bulbs and lighting products practically since the category was invented. We continuously test the latest smart lights, accessories, and the apps that control them.

In a future conflict, American troops will direct the newest war machines not with sprawling control panels or sci-fi-inspired touchscreens, but controls familiar to anyone who grew up with an Xbox or PlayStation in their home. Over the past several years, the US Defense Department has been gradually integrating what appear to be variants of the Freedom of Movement Control Unit (FMCU) handsets as the primary control units for a variety of advanced weapons systems, according to publicly available imagery published to the department's Defense Visual Information Distribution System media hub. Those systems include the new Navy Marine Corps Expeditionary Ship Interdiction System (NMESIS) launcher, a Joint Light Tactical Vehicle–based anti-ship missile system designed to fire the new Naval Strike Missile that's essential to the Marine Corps' plans for a notional future war with China in the Indo-Pacific; the Army's new Maneuver-Short Range Air Defense (M-SHORAD) system that, bristling with FIM-92 Stinger and AGM-114 Hellfire missiles and a 30-mm chain gun mounted on a Stryker infantry fighting vehicle, is seen as a critical anti-air capability in a potential clash with Russia in Eastern Europe; the Air Force's MRAP-based Recovery of Air Bases Denied by Ordnance (RADBO) truck that uses a laser to clear away improvised explosive devices and other unexploded munitions; and the Humvee-mounted High Energy Laser-Expeditionary (HELEX) laser weapon system currently undergoing testing by the Marine Corps. The FMCU has also been employed on a variety of experimental unmanned vehicles, and according to a 2023 Navy contract, the system will be integral to the operation of the AN/SAY-3A Electro-Optic Sensor System (or "I-Stalker") that's designed to help the service's future Constellation-class guided-missile frigates track and engage incoming threats. Produced since 2008 by Measurement Systems Inc. (MSI), a subsidiary of British defense contractor Ultra that specializes in human-machine interfaces, the FMCU offers a similar form factor to the standard Xbox or PlayStation controller but with a ruggedized design intended to safeguard its sensitive electronics against whatever hostile environs American service members may find themselves in.

This paper introduces a novel approach to interactive robots by leveraging the form-factor of cards to create thin robots equipped with vibrational capabilities for locomotion and haptic feedback. The system is composed of flat-shaped robots with on-device sensing and wireless control, which offer lightweight portability and scalability. This research introduces a hardware prototype. Applications include augmented card playing, educational tools, and assistive technology, which showcase CARDinality's versatility in tangible interaction.

When Boston Dynamics announced on Tuesday it was retiring the hydraulic version of Atlas, there were a few hints that the company wasn't done with humanoid robots entirely. Sure enough, one day later, Boston Dynamics has unveiled an all-electric model. Atlas was originally envisioned as a search-and-rescue robot and Boston Dynamics claims the latest model is designed for real-world applications. It calls Atlas "the world's most dynamic humanoid robot" and it certainly looks limber. A video shows Atlas lying prostrate and flipping its feet over to push itself up into a standing position.

With the recent advancements in the field of robotics and the increased focus on having general-purpose robots widely available to the general public, it has become increasingly necessary to pursue research into Human-robot interaction (HRI). While there have been a lot of works discussing frameworks for teaching HRI in educational institutions with a few institutions already offering courses to students, a consensus on the course content still eludes the field. In this work, we highlight a few challenges and opportunities while designing an HRI course from an Indian perspective. These topics warrant further deliberations as they have a direct impact on the design of HRI courses and wider implications for the entire field.

In both animals and robots, locomotion capabilities are determined by the physical structure of the system. The majority of legged animals and robots are bilaterally symmetric, which facilitates locomotion with consistent headings and obstacle traversal, but leads to constraints in their turning ability. On the other hand, radially symmetric animals have demonstrated rapid turning abilities enabled by their omni-directional body plans. Radially symmetric tripedal robots are able to turn instantaneously, but are commonly constrained by needing to change direction with every step, resulting in inefficient and less stable locomotion. We address these challenges by introducing a novel design for a tripedal robot that has both frictional and rolling contacts. Additionally, a freely rotating central sphere provides an added contact point so the robot can retain a stable tripod base of support while lifting and pushing with any one of its legs. The SKating, Omni-Oriented, Tripedal Robot (SKOOTR) is more versatile and stable than other existing tripedal robots. It is capable of multiple forward gaits, multiple turning maneuvers, obstacle traversal, and stair climbing. SKOOTR has been designed to facilitate customization for diverse applications: it is fully open-source, is constructed with 3D printed or off-the-shelf parts, and costs approximately $500 USD to build.

Of course, we knew that AI would figure prominently at this year's CES. But as CES veterans, we've seen such sparkling promises of the next big thing eventually fizzle. Thankfully there was plenty of meat-and-potatoes PC tech on display in Las Vegas to satisfy the cravings of PC enthusiasts here and now. Whether you're a road warrior, a PC builder, a lover of games both old and new, or a content creator, we saw some truly exciting products for PC users of every stripe, and, yes, some of it even includes AI. MSI could've left well alone with the MEG 321URX QD-OLED monitor.