Information Technology Hardware


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Engadget

Tech's biggest players have fully embraced the AI revolution. Apple, Qualcomm and Huawei have made mobile chipsets that are designed to better tackle machine learning tasks, each with a slightly different approach. Huawei launched its Kirin 970 at IFA this year, calling it the first chipset with a dedicated neural processing unit (NPU). Then, Apple unveiled the A11 Bionic chip, which powers the iPhone 8, 8 Plus and X. The A11 Bionic features a neural engine that the company says is "purpose-built for machine learning," among other things.


Worker Says Colleague Faked Out Her iPhone X's Facial Recognition ID

Huffington Post

Apple hasn't yet confirmed a case of an unrelated adult cracking the phone's facial recognition software, according to the Apple spokesman. The company insists that the probability of a random person accessing someone else's iPhone X using the Face ID passcode is 1 in 1 million, versus 1 in 50,000 for Touch ID. Phil Schiller, Apple's vice president of product marketing, conceded in September: "Of course, the statistics are lowered if that person shares a close genetic relationship with you."


Machine Learning Engineer posted by Lenovo on DigitalMediaJobsNetwork.com

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Lenovo is a $46 billion global Fortune 250 company and leader in providing innovative consumer, commercial and enterprise technology. Our portfolio of high-quality, secure products and services covers PCs, workstations, servers, storage, smart TVs and a family of mobile products like smartphones (including the Motorola brand), tablets and apps. Everyone here at Lenovo is an integral part of the company, working together, across continents, cultures and innovations, all comprised in a friendly, fast-paced, work environment that focuses on one common goal: to be known as the best in what we do.


Google Brain co-founder teams with Foxconn to bring AI

Daily Mail

Andrew Ng, co-founder of some of Alphabet Inc-owned Google's most prominent artificial intelligence projects, launches a new venture with iPhone assembler Foxconn to bring AI and so-called machine learning onto the factory floor. Consumers now experience AI mostly through image recognition to help categorize digital photographs and speech recognition that helps power digital voice assistants such as Apple Inc's Siri or Amazon.com Google Brain founder Andrew Ng said Foxconn has already signed up for his new firm, using AI for visual inspection in a factory's quality control efforts. Pictured, Chinese workers assemble electronic components at the Taiwanese technology giant Foxconn's factory in Shenzhen, in the southern Guangzhou province. In many factories, workers look over parts coming off an assembly line for defects.


Computer systems predict objects' responses to physical forces

MIT News

Josh Tenenbaum, a professor of brain and cognitive sciences at MIT, directs research on the development of intelligence at the Center for Brains, Minds, and Machines, a multiuniversity, multidisciplinary project based at MIT that seeks to explain and replicate human intelligence. Presenting their work at this year's Conference on Neural Information Processing Systems, Tenenbaum and one of his students, Jiajun Wu, are co-authors on four papers that examine the fundamental cognitive abilities that an intelligent agent requires to navigate the world: discerning distinct objects and inferring how they respond to physical forces. By building computer systems that begin to approximate these capacities, the researchers believe they can help answer questions about what information-processing resources human beings use at what stages of development. Along the way, the researchers might also generate some insights useful for robotic vision systems. "The common theme here is really learning to perceive physics," Tenenbaum says.


Wearable Tech Trends for 2017 - Amyx Internet of Things (IoT)

@machinelearnbot

In the next few years, expect smart clothing and accessories to become more fashionable and integrate more seamlessly into our daily lives. The wearable tech market is still relatively young and in flux. Fitbit, the company that arguably led the first wave of interest in wearables, didn't start making a wrist-based fitness tracker until 2013. Now, just about every major tech firm – and a slew of scrappy startups – has its own "smart" garment or accessory to peddle, whether in the form of a watch, ring, pendant, sports bra, shoe or something else. By 2020, the global appetite for wearable devices is expected to grow to around $34 billion, with roughly 411 million of the smart devices sold, according to industry analyst firm CCS Insight.


20 gift ideas that are perfect for stylish techies

USATODAY

If you make a purchase by clicking one of our links, we may earn a small share of the revenue. However, our picks and opinions are independent from USA TODAY's newsroom and any business incentives. There are gifts that are practical, gifts that are functional, and then there are gifts that are just… wowsers, that's beautiful. If you're looking to impress someone with a show-stopping present, this list of gadgets has been imbued with great design, and they're all really useful to boot. Good news: Beautiful does not always mean budget-breaking (though there are a few splurge-worthy items here too).


What goes into the right storage for AI? - IBM IT Infrastructure Blog

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Artificial intelligence (AI), machine learning and cognitive analytics are having a tremendous impact in areas ranging from medical diagnostics to self-driving cars. AI systems are highly dependent on enormous volumes of data--both at rest in repositories and in motion in real time--to learn from experience, make connections and arrive at critical business decisions. Usage of AI is also expected to expand significantly in the not-so-distant future. As a result, having the right storage to support the massive amounts of data required for AI workloads is an important consideration for an increasing number of organizations. Availability: When a business leader uses AI for critical tasks such as understanding how best to run their manufacturing process or to optimize their supply chain, they cannot afford to risk any loss of availability in the supporting storage system.


Man v. Machine: Deep Learning in Manufacturing

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Machines excel at performing a large number of varying tasks. Computers, for example, excel at performing mathematical computations. Even today's slowest personal computer has more computational power than the average human being by a wide margin. As an example, the Apple iPhone 4, released in 2010, had the computational power to perform roughly 1.6 Billion Floating Point Operations per second. As you can imagine, computational power has only increased since then.


9 Technology Mega Trends That Will Change The World In 2018

@machinelearnbot

Some tech trends fizzle out and die a quiet death, while others are so significant that they transform our world and how we live in it. Here are the top nine tech mega-trends that I believe will define 2018 and beyond. From chatting to friends in a messaging app or buying a coffee, to tapping in and out with an Oyster card or streaming music, today almost everything we do leaves a trail of data breadcrumbs. And this increasing datafication of our world has led to an unprecedented explosion in data. Just in the average minute, Facebook receives 900,000 logins, more than 450,000 Tweets are posted, and 156 million emails and 15 million texts are sent.With numbers like that, it's no wonder we're essentially doubling the amount of data created in the world roughly every two years.