With a single focus, Intel’s Vaunt has more potential than Google Glass

Back in October of 2013, I got my own pair of Google Glass in order to cover the technology. The site where I worked at the time paid the $ 1,500 cost, and I later spent my own $ 225 to add custom frames that could handle my eyeglass prescription. Given the fate of Glass, we clearly didn’t get a good return on those investments.

Still, there were some things to like about the experience. Glass brought contextual information “closer” to me a relatively non-intrusive way. And that’s exactly what Intel’s smart glasses prototype, known as Vaunt, can do.

When I first read about Vaunt over at The Verge earlier this week, I thought less about the hardware and more about that vision of context and personally important data. That’s because all of our technological advances in mobile computing have impacted this theme.

I look at it this way:

  • In the desktop age, the web brought us closer to data on other computers.
  • Connected laptops brought us closer to data when away from the desktop.
  • Phones put that data in our hand and pocket almost wherever we were.
  • Smartwatches let us wear that data, bringing it even closer
  • Smart glasses can beam that data — at least in the case of Vaunt — directly on our retinas.

Every step of that progression gets us physically closer to contextual information. I suppose the next, or maybe final, step is a Matrix-like jack that simply ports that data directly into our brains, but who knows? Regardless, this is an important theme as more devices around us create gobs of data. The fewer barriers there are between us and the information we want, the faster we can use or act upon it.

And that’s why I’m excited about Vaunt’s potential, perhaps more so than I was about that of Google Glass.

To contrast the two at a high level, Vaunt isn’t trying to take smartphone functions — such as taking photos and videos, a key reason Glass never had a chance of mainstream success — and move them to your eyes. Instead, the product is singularly focused on very specific information that you will want at a specific time and/or place.

That approach has benefits from a hardware perspective too. t’s why you essentially can’t tell the difference between Vaunt and a traditional pair of glasses. They appear to be standard eyeglass frames to both you and the people around you.

Without the need to include a camera sensor, microphone or speaker, the small chips and display components fit inside the frames. Eliminating the camera also allows for a smaller battery since powering an image sensor typically uses a lot of energy. Using a low-powered, single color laser for the retina projection helps with battery life too when compared to the color display used in Google Glass.

By distilling potential product features into essentially one — simple but very useful information — Vaunt actually solves a problem; something Glass sort of did but other extra features came along for the distracting ride. In fact, I don’t see much of a distraction factor with Vaunt because they don’t look like some technological device nor will people even realize that your retina is receiving information.

Clearly, this doesn’t mean Vaunt will be successful. In fact, Intel isn’t even sure of how Vaunt will be used. That’s why the company will be launching an early access program for developers at some point this year. Intel is just providing the technology while developers will provide the functions that they think people will want.

Think of Vaunt then as a new hardware platform with a very limited feature set. That feature is very powerful though: It takes us one step even closer to the information that personally matters most to us..

Stacey on IoT | Internet of Things news and analysis

Intel’s Vision for the Future of Smart Video

What is sight without the power to understand what’s being seen? As the Internet of Things  (loT) revolution continues, smart video technology keeps creating huge amounts of data. But even as these video technologies become more prevalent in cities, industrial facilities, retail stores, and even private homes, it’s still a major challenge to store and analyze that data. Intel answers this challenge with a scalable end-to-end (E2E) solution for secure collection, storage, and analysis of vast volumes of loT video data.

Smarter Industries and Smart Home

Can a better world exist without the proper resources to manage the exponential increase in 1/0?

Smart cameras are critical for making cities safer and more secure. Depending on the size of the city, this metadata can stack up into terabytes— and it all has to be analyzed in order to derive useful results. Within smart cities, smart transportation systems are generating tremendous amounts of data about vehicles, passengers and roads—often creating a full terabyte that needs to be securely collected, processed and stored every single day.

In a wide range of manufacturing sectors, virtualization technology is helping raise efficiency while  lowering the costs of doing business. Smart factories that use this technology can generate a terabyte of data every day. In smart retail,  video generated by digital security and surveillance systems helps keep stores secure and efficient—but  with  more than  75 million video surveillance cameras being sold to retailers in 2018, demand enormous storage capacity.

The loT transformation doesn’t end at the commercial space. The smart home revolution is already well underway. By 2020, the global market for smart home technology is projected to reach 100 billion, and most households will have more than 50 connected devices in the home. As smart homes become commonplace, the amount of data generated by smart devices will grow  exponentially—as will the storage and analysis systems required to deal with that data.

 

E2E Solutions

Fragmentation is a developer’s nightmare. That’s why Intel believes the only solution, is a holistic E2E approach.

As more industries adopt IP cameras, Intel’s integrated; hardware accelerators deliver the performance needed to process high-definition media in real time. These solutions ensure secure transmission and accurate analysis of data, with the help of a unique architecture in which connectivity, analytics and performance can all expand as needed.

Intel’s “develop first, port fast” toolset powers Intel’s Computer Vision software development kit (SDK). This SDK enables easy video processing, whether for in-store footage or handling security and surveillance applications. All Intel Xeon processors come ready to work with an entire portfolio of specialized libraries, saving developers significant time.

In the loT, security is at a premium. As many security experts know, hackers have already penetrated the ordinary layers of software security, and are now focusing their attacks on connected devices like IP cameras and network video recorders (NVRs). Intel’s entire architecture is designed from the ground up to defend against common forms of attack.

 

A Future with Intel

Intel technologies are making video data more accessible, analyzable, manageable and actionable for an entire ecosystem of developers. Each one of Intel’s video security and surveillance solutions delivers the performance required to process bandwidth-intensive video at the fastest rates possible.

Intel RealSense cameras are the “eyes” of this intelligent visual system. From handheld devices to snap-on PC cameras and beyond, RealSense makes 3D scanning and interior mapping simple, with imaging-and-feature tracking that make it easy to capture 3D models of real-world objects and rooms.

Movidius MyriadX vision processors (VPUs) are the “visual cortex” of the system, delivering top shelf performance with a very low power thermal footprint. In fact, MyriadX processors offer the best performance per watt of power of any processor under 1.5 watts—a full five times the capacity of Myriad 2 processors. These efficiencies allow more cameras to be installed, increasing in the amount of data captured, stored, and analyzed.

Finally, Intel CPUs act as the system’s “brain,” delivering best-in-class processing power packed into an ultra-thin and lightweight chip. Intel Xeon processors, for example, help deliver real-time analytics, processing for mission-critical tasks and big data insights.

Intel’s diverse portfolio of cameras, vision processors and CPUs provide the tools to make massive amounts of data easy to access, manage, analyze and transform into actionable insights.

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Samsung’s semiconductor revenues overshadow Intel’s, says IHS Markit

Though Samsung seems to have taken the number one position in the semiconductor manufacturing sector, analyst firm IHS Markit states that the picture could be slightly different if the data is analysed closely.

Len Jelinek, senior director for semiconductor manufacturing at IHS Markit, is of the opinion that by looking closer at the actual revenues generated by the individual companies from the sale of their own products, a slightly different and more interesting picture emerges.

Data provided by individual companies show only a portion of the ‘actual’ total picture. In ranking the semiconductor industry companies’ revenues, IHS believes the focus should be on merchant market revenue, the revenue obtained by a company through the sale of their own semiconductor components. This means that in a market share calculation the sale of components to third parties should not be included since a third party will be credited with the component sale into the market.

According to IHS, the semiconductor revenues Intel achieved in the second quarter of 2017 were $ 14.7 billion. If the third-party sales or foundry operations and other non-semiconductor revenue are deducted, then the company’s merchant market semiconductor revenues stand at $ 14.4 billion.

Samsung announced total semiconductor revenues of $ 15.5 billion in the same quarter, which includes an estimated $ 1.1 billion of foundry services revenues. If subtracted the foundry revenues, Samsung’s merchant market sales end up at $ 14.4 billion.

Thus, since neither company formally discloses its actual third-party sales or other non-semiconductor revenues, both companies end up separated by a mere $ 57 million with Intel remaining as the leader. IHS believes that the rapid growth in revenues by Samsung is more a reflection on market supply-and-demand issues rather than a successful long-term strategic plan by either company.

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Intel’s big bets on autonomous driving unveiled: “Unwavering confidence” in success

Intel has opened the doors to its Silicon Valley Innovation Center for Autonomous Driving and, with a slew of partners in tow, gave further insight into its push towards the connected car space.

Among the announcements was a reveal of one of the first highly automated vehicles developed in partnership with BMW and Mobileye, which Intel acquired for $ 15.3 billion in March, alongside demonstrating with Ericsson. over the air data moving across a 5G network between the car and the cloud.

The company also opened its Advanced Vehicle Lab, which alongside labs in Arizona, Germany, and Oregon will research the requirements and technologies needed to power self-driving vehicles, from artificial intelligence (AI) to supporting cloud services, while the Autonomous Garage Labs will focus more on the tools and testing side.

Doug Davis, senior vice president and general manager of the automated driving group at Intel, penned an editorial outlining his passion for the project, saying he postponed his retirement to lead the initiative.

“The chance to solve one of the most complex technology challenges of our time, the opportunity to help the auto industry reinvent transportation, the potential to save a million lives every year – those things are unlike anything I’ve done before,” he wrote.

“I have unwavering confidence that Intel will succeed in autonomous driving”, he added. “We have an astounding breadth and depth of experience and the world’s finest technology toolkit to apply to this challenge. We have tapped resources from across the company and have added experienced talent from the automotive industry. Our teams are operating in high gear and will deliver the necessary technology breakthroughs.”

In July last year, BMW, Intel and Mobileye announced plans to bring self-driving vehicles onto the road by 2021 through a common platform. The companies outlined their strategy to come up with solutions which continually went up the scale of automation, from level 3 (‘eyes off’), to level 4 (‘mind off’) and then eventually to level 5, ‘driver off’, when a human is not required inside the vehicle. Davis added that plans were afoot to bring the platform to market for other OEMs and tier one suppliers.

Davis also riffed on the importance of AI in autonomous vehicle development. “Mastering AI both inside the car and in the data centre will be essential to the autonomous driving data challenge,” he wrote. “Here it’s important to remember that autonomous driving isn’t a game. When cars are thinking and acting without human intervention, they must be able to do so in a safe and trustworthy way.”

Plenty of research is taking place, and plenty of data is being collected to gauge what autonomous cars should do in certain situations. The MIT’s ‘moral machine’ program, which gives participants the choice between “the lesser of two evils”, such as killing two passengers or five pedestrians, is an example of this. As Davis noted: “If all we needed was a supercomputer to handle the autonomous driving data challenge, our work would be done.”

Intel’s acquisition of Mobileye showed how seriously the firm was taking this sector, particularly, as this publication pointed out, the difference in price compared to the $ 8.9bn Samsung is paying for Harman. “The faster we can deliver autonomous driving technology and take humans out of the driver’s seat, the faster we can save lives,” wrote Davis. “It’s that’s simple – and that important…and I am confident Intel will not only succeed in helping our partners put self-driving cars on the roads, we will do so in the fastest, smartest way possible.”

You can take a look at the full list of announcements here.

Picture credits: Intel

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