The Eufy S4 Max NVR is a serious system for users who want smart features without giving up privacy or flexibility. Most home security systems force you to choose between smart features and local control. As its name indicates, this is a PoE (Power over Ethernet), NVR (Network Video Recorder) system with a built-in AI agent that runs on its own local hardware--there's no cloud storage and no subscription fees required to unlock key features. The bundle includes four of Eufy's PoE Cam S4 triple-lens cameras. Each of these has a fixed-position camera with a single wide-angle lens (122-degree field of view) that's fused to the dual-lens, pan/tilt/zoom camera beneath it.

Lenovo's Project Crystal is definitely sci-fi tech come to life. Currently, there are no plans to turn the concept laptop into a retail product. Instead, its ThinkPad division commissioned an exploration into the potential of transparent microLED panels and, sigh, AI integration. The most obvious use for the transparent laptop display would be sharing info at a doctor's office or hotel desk. Instead of needing to flip a screen around, you could simply reverse the device's output via software.

Just ahead of Mobile World Congress, NVIDIA unveiled its latest laptop GPUs and, what a surprise, they're designed largely to assist with AI processing. The RTX 500 and 1000 Ada Generation graphics cards are primarily for thin and light laptops. While they won't offer as much TOPS AI performance as current higher-end mobile GPUs, they could be a handy option for on-the-go AI processing for the likes of researchers, content creators and video editors. It's worth noting they're workstation GPUs rather than ones designed for gaming. NVIDIA says the GPUs, which are based on the Ada Lovelace architecture, offer up to twice the ray-tracing performance of previous-gen GPUs (they employ third-gen ray-tracing cores).

The company's event-based digital Neuromorphic IP can add efficient AI processing to SoCs. Edge AI is becoming a thing. Instead of using just an embedded microprocessor in edge applications and sending the data to a cloud for AI processing, many edge companies are considering adding AI at the edge itself, and then communicating conclusions about what the edge processor is "seeing" instead of sending the raw sensory data such as an image. To date, this dynamic has been held back by the cost and power requirements of initial implementations. What customers are looking for is proven AI tech that can run under a watt, and that they can add to a microcontroller for on-board processing.

Well, we are already at the end of February and after two months back at work people are now starting to think "should I look for a new role?" You have come back to the office and reality is – nothing has changed. So February/March are a great time to put your feelers out. Nowadays, a lot of large organisations use artificial intelligence (AI) to work out who they would like to interview. So creating a resume that is enhanced for AI processing can be a powerful tool in your job search.

As artificial intelligence (AI) rapidly works its complex magic on one sector of the economy after another, there is an increasingly pressing need for compute resources to power all this machine intelligence. Training a model like ChatGPT costs more than $5 million, and running the early ChatGPT demo, even before usage increased to its current level, costs OpenAI around $100,000 per day. And AI is more than just text generation; applying AI to practical problems across multiple industries requires similar large neural models trained on a diversity of data types -- medical, financial, customer information, geospatial and so forth. Moving beyond the limitations of current neural net AI toward systems with higher levels of artificial general intelligence will almost surely be even more compute intensive. It's only natural that a small but increasing number of crypto miners are now looking at how to leverage their own compute infrastructures to help push forward the AI revolution.

As new technology is constantly being developed, trends are merged and combined to enhance functionality and improve old systems. The future of fifth-generation cellular technology and artificial intelligence is a perfect example of how today's innovators can apply two separate concepts together to develop new use cases and refine the inventions of the past to better serve the needs of the future. Read on to learn more about how 5G and AI technology will work together to produce exciting new developments. With their powers combined, AI and 5G technologies are a superforce. This dynamic duo has the potential to transform many different industries -- from healthcare and transportation to entertainment and beyond.

As companies increase the use of automation technologies in their factories, warehouses and other locations, they recognize the need for artificial intelligence technologies (such as machine vision to inspect for defects) that can guide decisions in real time. But in practice, companies are finding that cloud-based AI technologies are taking too long, and they need to move this decision-making process to the edge of the network. "We often see industrial use cases where manufacturers or OEMs tell me that they have to make that entire round trip, including the network, in a very small number of milliseconds," says Rita Wouhaybi, Senior AI Principal Engineer at Intel. "It makes it impossible against the law of physics to actually send that request to the cloud." Reducing the time for decisions and reducing the expense of data movement are two of the big reasons why companies are now deploying AI technologies at the edge.

At its Build conference in May, Microsoft debuted Project Volterra, a device powered by Qualcomm's Snapdragon platform designed to let developers explore "AI scenarios" via Qualcomm's Neural Processing SDK for Windows toolkit. Today, Volterra -- now called Windows Dev Kit 2023 -- officially goes on sale, priced at $599 and available from the Microsoft Store in Australia, Canada, China, France, Germany, Japan, the U.K. and the U.S. Here's how Microsoft describes it: With Windows Dev Kit 2023, developers will be able to bring their entire app development process onto one compact device, giving them everything they need to build Windows apps for Arm, on Arm. As previously announced, the Windows Dev Kit 2023 contains a dedicated AI processor, called the Hexagon processor, complimented by an Arm-based chip -- the Snapdragon 8cx Gen 3 -- both supplied by Qualcomm. It enables developers to build Arm-native and AI-powered apps alongside and with tools such as Visual Studio (version 17.4 runs natively on Arm), .NET 7 (which has Arm-specific performance improvements), VSCode, Microsoft Office and Teams and machine learning frameworks including PyTorch and TensorFlow. Microsoft's Windows Dev Kit 2023, which packs an Arm processor plus an AI accelerator chip. The Windows Dev Kit 2023 arrives alongside support in Windows for neural processing units (NPU), or dedicated chips tailored for AI- and machine learning-specific workloads.

Whenever people take photos or speak to a digital assistant using a mobile phone, they often don't realize that they just took advantage of Artificial Intelligence (AI). If they think of AI at all, it is typically in the context of Autonomous Vehicles or perhaps Facebook's (Meta's) massive data centers. While AI is becoming ubiquitous and distributed across edge devices and cloud servers, many challenges remain to realize the connected intelligent edge vision CEO Cristiano Amon has for AI to enable automated perception, reasoning, and action. For AI to enable the levels of automation and personalization Qualcomm AI Research VP Jilei Hou believes that AI hardware and software must become much smaller, faster, more efficient, lower power, and able to learn continuously at the edge in the real world. This provides the perfect complement to remote processing in the cloud, whose reach has been further advanced through Qualcomm's 5G technology.