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Qualcomm's new Snapdragon chip promises more power, less battery drain


Qualcomm's chips are powering some of the most powerful Android phones around, and now the company has a new flagship chip that is both faster and more energy efficient than its predecessor. The awkwardly named Qualcomm Snapdragon 8 Gen 1 (seriously, what's wrong with just a simple number?) is up to 10% faster than its predecessor, the Snapdragon 8 Gen 1, while drawing 30% less power. These improvements should be visible both in mobile gaming and regular use, thanks to the chip's new Adreno GPU and the new Kryo CPU. For an idea of what you can expect performance-wise, some of the phones touting Snapdragon's last chip include the OnePlus 10 Pro and the Xiaomi 12 Pro. The new chip will enable phones to take 8K HDR video, with support for the HDR10 format.

Qualcomm Completes Auto Software Stack With Arriver Acquisition


Qualcomm continues its expansion into ADAS and autonomous control with the potential acquisition of ... [ ] Veoneer Qualcomm announced that it has completed its rather complicated acquisition of Arriver. The acquisition completes the software stack for Advanced Driver Assistance Systems (ADAS) and Autonomous Driving (AD) solutions. Qualcomm formally established a partnership with Veoneer to create Arriver in 2021. The intent was to develop a full automotive software stack that merged Veoneer's perception and driving policy software with Qualcomm's Snapdragon Ride platform. That was until Magna International made an unsolicited offer to acquire Veoneer in June 2021.

Robotics innovation infiltrates 2022 Consumer Electronics Show


It must be CES time! A few years ago, the only robots at CES were toys. And as the robot toy makers at Ologic can attest, having your robot featured as the leading image for CES was still no guarantee that your robot would make it into production (AMP is pictured above). Luckily Ologic have transferred their consumer electronics experience into building robots of every other kind. The 2022 CES Innovation Awards recognize a range of robotics technologies as Honorees, and feature three in the "Best of Innovation" category as well. See & Spray is a technologically advanced, huge robot for the agriculture industry that leverages computer vision and machine learning to detect the difference between plants and weeds, and precisely spray herbicide only on the weeds. This groundbreaking plant-level management technology gives a machine the gift of vision and reduces the use of herbicide by up to 80 percent, benefiting the farmer, the surrounding community and the environment.

Hottest of CES 2022: our 20 favorite launches from the show


While CES 2022 wasn't quite the full-blown, in-person event organizers were hoping for, the massive electronics show in Las Vegas, Nevada, still managed to deliver a stellar line-up of exciting technology. There's so much happening at CES, but there are always some announcements that really grab our attention and for those products, a highly coveted Hottest of CES 2022 TechRadar award is in sight. The TechRadar team spent all week voting on and debating over our favorite CES 2022 launches. What you'll find below are the results: The 20 hottest products from this year's show. LG came out swinging at CES 2022 by announcing a number of 8K and 4K OLEDs, several new QNED mini-LED TVs, and even a MicroLED TV.

Invisible headphones to chameleon cars: standout tech from CES 2022

The Guardian

From colour-shifting cars to digital art TVs and stress-predicting watches, the annual Consumer Electronics Show in Las Vegas, which opened on Wednesday, offered its usual mix of wacky, visionary and desirable goods. Here are some of the highlights. The non fungible token, which confers ownership of a unique digital item such as a work of art, became a multi-billion dollar market in 2021 and Samsung announced a new TV feature that allows enthusiasts to browse, display and buy NFT-based art. Given how much some NFTs cost, you may not have much left over to pay for the screen. Nowatch has produced a smartwatch that monitors your cortisol levels to predict stress.

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.

Machine Learning based CVD Virtual Metrology in Mass Produced Semiconductor Process Artificial Intelligence

A cross-benchmark has been done on three critical aspects, data imputing, feature selection and regression algorithms, for machine learning based chemical vapor deposition (CVD) virtual metrology (VM). The result reveals that linear feature selection regression algorithm would extensively under-fit the VM data. Data imputing is also necessary to achieve a higher prediction accuracy as the data availability is only ~70% when optimal accuracy is obtained. This work suggests a nonlinear feature selection and regression algorithm combined with nearest data imputing algorithm would provide a prediction accuracy as high as 0.7. This would lead to 70% reduced CVD processing variation, which is believed to will lead to reduced frequency of physical metrology as well as more reliable mass-produced wafer with improved quality.

The Role of Social Movements, Coalitions, and Workers in Resisting Harmful Artificial Intelligence and Contributing to the Development of Responsible AI Artificial Intelligence

There is mounting public concern over the influence that AI based systems has in our society. Coalitions in all sectors are acting worldwide to resist hamful applications of AI. From indigenous people addressing the lack of reliable data, to smart city stakeholders, to students protesting the academic relationships with sex trafficker and MIT donor Jeffery Epstein, the questionable ethics and values of those heavily investing in and profiting from AI are under global scrutiny. There are biased, wrongful, and disturbing assumptions embedded in AI algorithms that could get locked in without intervention. Our best human judgment is needed to contain AI's harmful impact. Perhaps one of the greatest contributions of AI will be to make us ultimately understand how important human wisdom truly is in life on earth.

To measure ultra-low power AI, MLPerf gets a TinyML benchmark


The world is about to be deluged by artificial intelligence software that could be inside of a sticker stuck to a lamppost. What's called TinyML, a broad movement to write machine learning forms of AI that can run on very-low-powered devices, is now getting its own suite of benchmark tests of performance and power consumption. The test, MLPerf, is the creation of the MLCommons, an industry consortium that already issues annual benchmark evaluations of computers for the two parts of machine learning, so-called training, where a neural network is built by having its settings refined in multiple experiments; and so-called inference, where the finished neural network makes predictions as it receives new data. Those benchmark tests, however, were focused on conventional computing devices ranging from laptops to supercomputers. MLPerf Tiny Inference, as the new exam is called, focuses on the new frontier of things running on smartphones down to things that could be thin as a postage stamp, with no battery at all.

The Morning After: Sony's portable speakers arrive just in time for summer


Meet Moxie, a companion robot made specifically for children to play with every day. As Devindra Hardawar notes, the idea of an R2-D2 of your own is interesting, until it gets dystopian. So which side of the line does this bot fall? According to company co-founder Paolo Pirjanian, two months after launch, customers are averaging 25 minutes of engagement every day -- although that the company knows that isn't exactly encouraging. Devindra's kid is (wisely) robot-averse, so he tried it himself for a few weeks and was surprised by how well the conversations flowed.