Collaborating Authors


AI Hardware Technology Imitates Changes in Neural Network Topology


A group of researchers at The Korea Advanced Institute of Science and Technology (KAIST) has proposed a new system inspired by the neuromodulation of the brain, which is called a "stashing system." This newly proposed system requires less energy consumption.

Google partners with Asus IoT to spread availability of Coral on-device AI hardware


Coral is Google's platform for adding on-device AI and inferencing capabilities to hardware. To make it more widely available, especially for Internet of Things use cases, Google is partnering with Asus IoT. Asus IoT is a sub-brand of Asus, and Google wants to scale manufacturing, distribution, and support for Coral with this agreement. With decades of experience in electronics manufacturing at a global scale, ASUS IoT will provide Coral with the resources to meet our growth demands while we continue to develop new products for edge computing. This will see Asus IoT "become the primary channel for sales, distribution and support" for Coral, with customers getting "dedicated teams for sales and technical support" in the process.

Low-Code AI Model Development with the NVIDIA TAO Toolkit


Chintan Shah is a senior product manager at NVIDIA, focusing on AI products for intelligent video analytics. Chintan manages an end-to-end toolkit for efficient deep learning training and real-time inference. Previously, he developed hardware IPs for NVIDIA GPUs. Chintan holds a master's degree in electrical engineering from North Carolina State University.

Modern Computing: A Short History, 1945-2022


Inspired by A New History of Modern Computing by Thomas Haigh and Paul E. Ceruzzi. But the selection of key events in the journey from ENIAC to Tesla, from Data Processing to Big Data, is mine. This was the first computer made by Apple Computers Inc, which became one of the fastest growing ... [ ] companies in history, launching a number of innovative and influential computer hardware and software products. Most home computer users in the 1970s were hobbyists who designed and assembled their own machines. The Apple I, devised in a bedroom by Steve Wozniak, Steven Jobs and Ron Wayne, was a basic circuit board to which enthusiasts would add display units and keyboards. April 1945 John von Neumann's "First Draft of a Report on the EDVAC," often called the founding document of modern computing, defines "the stored program concept." July 1945 Vannevar Bush publishes "As We May Think," in which he envisions the "Memex," a memory extension device serving as a large personal repository of information that could be instantly retrieved through associative links.

Recommender Systems, Not Just Recommender Models


One of the biggest challenges facing people new to building recommender systems is the lack of understanding around what these systems look like in the real world. The majority of the online content around recommender systems focuses on models and is often limited to a simple example of collaborative filtering. For new practitioners, there is an enormous gap between examples of simple models and a production system that serves recommendations. In this blog post we'll share a pattern that we feel covers the majority of recommender systems deployed today with examples from companies like Meta, Netflix, and Pinterest. This pattern is central to how we think about building end-to-end recsys within the NVIDIA Merlin team and we're excited to share it with the broader community and help build an understanding and consensus of what recommender systems (not just models) look like in production.

Benchmark test of AI's performance, MLPerf, continues to gain adherents


Wednesday, the MLCommons, the industry consortium that oversees a popular test of machine learning performance, MLPerf, released its latest benchmark test report, showing new adherents including computer makers ASUS, H3C, and ZhejiangLab, a research institute formed by the Zhejiang province government in China, Zhejiang University and Chinese retail and AI giant Alibaba. Those parties join frequent submitters Nvidia, Qualcomm, Dell, and Microsoft. The MLCommons's executive director, David Kanter, lauded the record number of submissions, over 3,900. Those results span a wide range of computing, from data centers down to what is known as "TinyML," running on devices such as embedded microchips that sip fractions of a watt of power. "This is a huge dynamic range," said Kanter.

That big deal for Nvidia to buy computer chip giant Arm has come crashing down

NPR Technology

The logo of SoftBank Corp. is seen at a shop in Tokyo on Monday. Profit at the Japanese technology investor has tumbled as the value of its sprawling investments declined and its planned sale of British company Arm collapsed. The logo of SoftBank Corp. is seen at a shop in Tokyo on Monday. Profit at the Japanese technology investor has tumbled as the value of its sprawling investments declined and its planned sale of British company Arm collapsed. TOKYO -- SoftBank's planned sale of the British semiconductor and software design company Arm to U.S. chipmaker Nvidia has fallen through, but the Japanese technology investor immediately turned bullish on taking it public.

Best streaming device deals for Super Bowl LVI: Roku, Fire Stick, Apple TV


Streaming devices may seem redundant in an era where smart TVs are king of home entertainment. But they can breathe new life into older, "dumb" TVs and even older smart TVs that no longer support newer versions of your favorite apps. They're incredibly easy to use: just plug them into a free HDMI port, connect to your home's Wi-Fi, and sign into your apps, and many work with virtual assistants like Alexa, Hey Google, and Siri for hands-free controls and integration into your smart home network. Just in time for the Super Bowl, you can take advantage of some great markdown deals and device bundles from retailers like Amazon, Best Buy, and Walmart, so you don't miss a second of the action (and commercials). These devices are also great if you want to plunk the kids in another room to watch Encanto for the 11th time while you try to figure out exactly where Cincinnati is and why their fans yell "Who Dey" (hint from an Ohioan: I don't know either.

Challenges of Artificial Intelligence -- From Machine Learning and Computer Vision to Emotional Intelligence Artificial Intelligence

Artificial intelligence (AI) has become a part of everyday conversation and our lives. It is considered as the new electricity that is revolutionizing the world. AI is heavily invested in both industry and academy. However, there is also a lot of hype in the current AI debate. AI based on so-called deep learning has achieved impressive results in many problems, but its limits are already visible. AI has been under research since the 1940s, and the industry has seen many ups and downs due to over-expectations and related disappointments that have followed. The purpose of this book is to give a realistic picture of AI, its history, its potential and limitations. We believe that AI is a helper, not a ruler of humans. We begin by describing what AI is and how it has evolved over the decades. After fundamentals, we explain the importance of massive data for the current mainstream of artificial intelligence. The most common representations for AI, methods, and machine learning are covered. In addition, the main application areas are introduced. Computer vision has been central to the development of AI. The book provides a general introduction to computer vision, and includes an exposure to the results and applications of our own research. Emotions are central to human intelligence, but little use has been made in AI. We present the basics of emotional intelligence and our own research on the topic. We discuss super-intelligence that transcends human understanding, explaining why such achievement seems impossible on the basis of present knowledge,and how AI could be improved. Finally, a summary is made of the current state of AI and what to do in the future. In the appendix, we look at the development of AI education, especially from the perspective of contents at our own university.

Chromebooks versus Windows laptops: Which should you buy?


Should I buy a Chromebook or a Windows laptop? It's a common question, whether asked by parents weighing the best computer option for back-to-school or by people who just want an inexpensive computer for themselves. We'll help you choose the right one. Our latest update includes more answers to questions you might have: such as, how slow (and inexpensive) can a Chromebook be before it stops being usable? What does Windows 11 and Windows 11 SE mean for laptops? Read on for the answers, plus our up-to-date buying guide for November 2021 and Black Friday, plus more details and what to buy. A notebook PC or laptop powered by Microsoft Windows offers several advantages. Windows offers the most flexibility to run just about any app, your choice of any browser, and configure antivirus options, utilities, and more. You can tweak and configure your PC as you choose. That convenience demands more computing horsepower, and often a higher price compared to most Chromebooks. Prices can soar into the thousands of dollars, and if you need a powerful PC for gaming or video editing, Chromebooks can't compete, and they don't try to. But you'll find some great deals among our more affordably priced, top Windows picks. See our buying guide to the best laptops for even more options.