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Google opens up Glass Enterprise Edition 2 for direct purchases

Having launched a revamped version of its Glass Enterprise Edition last May, Google now wants to spur wider usage of its smartglasses among businesses. It has now made the device available for developers to buy directly through its hardware resellers for $999. 

The first iteration of Glass, launched in 2013, was aimed at consumers. But it proved to be a flop amid criticism over the device’s power needs and concerns about the ability to record other people without their consent. 

Google next targeted the technology for business use where hands-free computing is advantageous, such as in manufacturing. It unveiled the first Glass Enterprise Edition in 2017, as Glass graduated from Alphabet’s ‘X’ division to a fully fledged product due to demand for wearables in the workplace, Google said. 

This was followed by an updated version in 2019, featuring a faster processor, larger battery and USB-C connection. The Glass Enterprise Edition 2 was priced starting at $999, though pricing was subject to customization and support upon consultation with Google partners selling the devices.

On Tuesday, Google announced an option to buy individual devices through hardware partners, including CDWMobile Advance and SHI.

The idea is to make it easier for developers to test the smartglasses – which run on Android – within their organization. Google has also shared new open source tools and code samples, such as examples of UI components, to help developers get started with building their own apps for Glass.

“We’re excited to see what kinds of new experiences and solutions developers will make for Glass to shape the future of work,” said Jay Kothari, project lead at Glass.

“Opening up the Glass Enterprise Edition means that Google wants to broaden the types of applications that can use it and increase the user base,” said Anshel Sag, an analyst at Moor Insights & Strategy. 

“While it is unclear what Google’s long-term strategy is, it is clear they learned some lessons from the first Google Glass flop,” Sag said.

Although augmented and mixed reality systems have yet to gain much traction with consumers, Google is one of a number of companies targeting smartglasses at the enterprise. It competes with others such as Vuzix and Epson, which also provide lightweight AR smartglasses, while Microsoft targets workers with its heavier, more powerful – and pricier – HoloLens 2.

“Right now, the developers and hardware vendors are heavily focused on enterprise and I don’t see that changing drastically in 2020,” said Sag.

Copyright © 2020 IDG Communications, Inc.



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How the Xnor.ai purchase opens Apple’s AI future

Apple’s $200 million acquisition of Xnor.ai provides tools for evolution in imaging, edge-based AI, HomeKit and more.

What does Xnor.ai do?

Xnor.ai was spun out of the Allen Institute for AI by Professor Ali Farhadi and Dr. Mohammed Rastegari in 2017. These men were also responsible for YOLO, YOLO9000, Label Refinery and other machine intelligence achievements.

The company developed machine learning and image recognition models that combined accuracy with the ability to work locally on the device, rather than sending those images to a server.

One client, Wyze Labs, used the tech for person detection in CCTV videos, though that feature was withdrawn earlier this month, before news of Apple’s purchase broke.

Xnor.ai was more ambitious than on-device image recognition. Its website states:

“Transform your business with on-device AI.”

On YouTube, a video is still available that explains its aims, including AI on smart home devices, on cameras and on agricultural drones. The intention seems to be to create self-learning AI that works on the device and does so without need of an internet connection.

In other words: no cloud required.

Independent self-learning devices

“We’re building a future where AI is available on almost every device,” The Xnor.ai voice over claims. “We call this AI Everywhere, for Everyone. And it’s the beginning of something truly transformational that will reshape how we work, live and play.”

Within this work, the company developed a solution called AI2GO, a self-serve platform to easily deploy advanced deep learning models onto edge devices.

(You can still watch an interesting account of what this does here.)

It is also important to note that the company has previously demonstrated an AI chip that used so little energy it could run off solar power.

There is an obvious symmetry between the two company’s visions: Xnor.ai’s AI models that can be installed on edge devices and Apple’s strategy to invest its devices with on-board intelligence that don’t need cloud servers.

The notion also fits current trends. Edge-based intelligence is seen as a bastion against the privacy and security risks of cloud-based systems – particularly in industrial deployments.

You’ll already find Apple working with models like this in Photos, which identifies faces, places and things in your images with analysis on your device. It may be possible that Xnor.Ai’s tech may help the company further reduce the quantity of information it needs to gather in order to make services work.

A stepping stone to homeOS?

Where things become more interesting is around smart home devices.

We already know that Apple is looking a little more deeply at HomeKit. It set the scene at WWDC 2019 with HomeKit Secured Routers and support for CCTV systems. It reprised the commitment in 2020 at CES.

The problem with most smart home devices is that they are dumb. They may have sensors, but they are centrally controlled by mobile devices, hubs and the like. They are controlled devices that lack on-board intelligence.

Xnor.ai changes that.

A lot of its work focused on enhancing Raspberry Pi with on-device AI. Huge quantities of processing power aren’t required. This makes it feasible to imagine these technologies being used to help Apple carve out some form of homeOS platform upon which developers can build self-learning (yet still affordable) smart home devices. Or even for industrial IoT deployments.

(While industrial tech has never been a prime market for Apple, things have changed, and its devices are now in use across the enterprise. Why wouldn’t it want strategic positions in some industrial verticals?)

Combine such devices with low power local IP-based networking and you end up with self-learning systems that are smart, but not online. They’re smart, upgradeable and inherently secure because intelligence takes place at the edge.

Don’t get too excited – yet

Apple’s platform-wide implementation of the newly acquired tech will take time. In the near term, it makes sense to see slightly more prosaic improvements, such as easier AI model updates, smarter person and object identification in Photos and smart object recognition in ARKit.

Another place where Apple may be able to make a difference is in CCTV video, improving playback and person recognition systems in these.

Wyze delivered this using Xnor.ai. Apple’s interest in HomeKit Secure Video and its focus on HomeKit, along with its work in video editing, machine intelligence and recognition systems makes this a place in which it could make a difference.

Another possibility is that this tech could make it easier for third-party developers to create, install and upgrade their own AI models on Apple platforms – I can even imagine an AI Playgrounds solution (like Swift Playgrounds) to teach kids the principles of machine intelligence. “I just built a jellybean recognition system for my iPhone…”

But these things take time – Apple is only now rolling out the kind of Maps improvements it began working on in earnest in around 2016.

The road between “could happen” and “did happen” is long and full of stumbling blocks, and the company’s grand plan for the implementation of these technologies is not necessarily linear or obvious. But the implications of the newly-acquired tech could extend across Apple’s product and software lines.

Please follow me on Twitter, or join me in the AppleHolic’s bar & grill and Apple Discussions groups on MeWe.

Copyright © 2020 IDG Communications, Inc.





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EEA opens sandbox for blockchain development and collaboration

The Enterprise Ethereum Alliance (EEA) today launched a development sandbox that enables member companies to test and certify their blockchain or distributed ledger technology (DLT) projects.

The standards organization that oversees the Ethereum blockchain platform partnered with enterprise testing and development service provider Whiteblock to create the sandbox for the EEA members.

In addition to working with internal projects, EEA members can also use the TestNet to collaborate with partner companies on developing blockchain applications that can pass data back and forth, according DiMarzio

“One of the main objectives of the EEA is to provide interoperability in this marketplace to ensure products coming out on Ethereum work together. When you’re working together in the same test environment you’re going to make sure that’s happening – something you can’t do if you’re working alone,” said EEA Community Director Paul DiMarzio.

The EEA has more than 200 members, including Intel, Microsoft, FedEx, Pacific Gas & Electric Co.. JP Morgan Chase, Banco Santander, Citigroup and the John Hancock Life Insurance.

“We’ve got both IT providers and IT users in it – both companies making the technologies and the consumers of technology. We’ve got big guys and little guys,” DiMarzio said.

For example, JP Morgan Chase initially built its cryptocurrency JPM Coin on top of the Quorum blockchain platform, which is based on Ethereum; the EEA’s Quorum development team is participating in the Testing Working Group that developed the new testnet. There are 20 member companies that are part of the EEA TestNet and Certification Working Group.

An EEA certification program is planned for end of 2020.

“We are planning to test various scenarios that we are currently identifying. Some scenarios include public transactions, private transactions, permissioning, block validation, and the IBFT consensus mechanism,” said Dan Heyman, co-founder and director at blockchain company and EEA member PegaSys. Heyman was referring to the Istanbul Byzantine Fault Tolerant mechanism.

PagaSys developed a version of Ethereum that includes Hyperledger Besu, an open-source Java-based client. PegaSys plans to launch Hyperledger Besu in the  “upcoming weeks.” 

Their use of the TestNet demonstrates future opportunities for enterprise use cases, Heyman said. “We believe the EEA TestNet is a good starting point towards a certification and validating how current clients meet the EEA specification,” he said.

Research has shown testbeds are necessary for partnerships to thrive between governments hammering out new regulations and the businesses hoping to use blockchain. Testbeds help regulators better understand blockchain’s cybersecurity benefits and risks and offer a deeper understanding of the technology.

With that in mind, heavily regulated industries such as FinTech, healthcare, transportation and manufacturing can help develop a government’s understanding of blockchain through dialogue and the creation of joint regulatory sandboxes.

One of the distinctions between other industry sandboxes and the EEA’s TestNet is there’s no central coordination or management of the latter. The managing infrastructure is completely automated by Whiteblock’s Genesis, a blockchain, Web3 and distributed systems test/dev platform that alleviates overhead, according to Whiteblock CEO Zak Cole, who is also chair of the EEA Testing and Certification Working Group.

Each node on the EEA TestNet exists within its own logical environment (whitebox) and has its own IP address. The nodes communicate with others over a WAN. Links between nodes can also be manipulated to simulate packet loss, latency or bandwidth constraints to see how the network would operate upscaled within a controlled environment.

The software enables the automation of transactions over the network to measure throughput and enable the use of smart contracts.

“So, load testing, security tests, fault tolerance. You just get this private network of your own that allows you to do what you need to do and it’s all automated,” Cole said.

To participate in the testnet, EEA members don’t need to run their own servers (nodes), and instead can utilize distributed web application extensions, such as MetaMask, or any endpoint the EEA provides that allows users to run distributed apps (dApps) on their browser without running a full Ethereum node.

Since it’s a controlled testnet and the EEA can observe every node in the network, the standards group can gather deep insights into the results of any test, Cole said.

“So defining what the test criteria is going be, automating that entire process, sucking out all that data, aggregating it and then analyzing it is all going to be taken care of,” Cole said. “So, it’s much more than just a testnet; it’s kind of like a managed service.”

Copyright © 2020 IDG Communications, Inc.



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How to Stop Superhuman (and Other Apps) From Tracking Your Email Opens

Stylized new email alert from laptop.
Belozersky/Shutterstock

Superhuman’s email tracking informed someone when you opened their email—and from where. Even if Superhuman completely removed this feature in response to privacy pressure, other apps will still be able to track your email opens. Here’s how to stop it.

While Superhuman has now removed location tracking, it still supports email open tracking. And other email tracking apps could let someone who emails you find out your geographical location, too.

How Can an App Track Email Opens?

Superhuman is using a feature that’s existed for a long time. It embeds a tiny tracking pixel image in the emails it sends. When you open an email, your email client requests the image. The image is unique for each email, so Superhuman can see precisely when you opened the email and your general location, based on your IP address.

This isn’t unique to Superhuman! While it’s not normally part of a consumer email application, many email newsletters and other marketing emails have long used tracking pixels. They know how many people open each email—and they can see which people on their mailing list open each email.

Despite all the furor, Superhuman is just using an existing email feature and exposing it a new way—albeit one that seems creepier to many people. Superhuman has now disabled the open tracking feature by default, but anyone Superhuman user can enable it.

Even if Superhuman continues bowing to pressure and completely removes this feature, people will still be able to use other email tools—from dedicated email applications to browser extensions that integrate with Gmail—to track your email opens.

RELATED: How People Can See When You Open Emails (and How to Stop Them)

How to Stop Email Open Tracking

To stop email open tracking, you’ll just need to turn off the “automatically load images” setting in your email client of choice.

Superhuman’s CEO Rahul Vohra notes that there are browser extensions like Ugly Email and PixelBlock that can block tracking pixels—without blocking other images—in Gmail in your web browser. However, these will only work in Gmail in your browser and they aren’t guaranteed to block all tracking images. Disabling remote image loading is a foolproof method that will work everywhere—at least, it will work in every email client that lets you disable the loading of images.

After you disable this, you’ll likely see an option to load images whenever you open an email. It depends how your email client works. If you don’t agree, you won’t see images, and no one will be able to see you opened that email. Many email clients, like Gmail, will let you automatically load images from specific senders if you’re not worried about those senders tracking you.

For example, in Gmail, head to Settings > General. To the right of Images, select “Ask Before Displaying External Images.” Scroll down to the bottom of the page and save your changes.

Option to disable external images and thus email tracking in Gmail

If you’re using another email client, search the web for how to disable automatic image downloads in emails in your email client of choice.

Remember that, even if you choose to disable automatic image downloads, people will still be able to see you opened their emails if you choose to view images after opening an email.

Option to load images for an individual email in Gmail

Superhuman itself doesn’t let you disable remote image loading yet, which means that Superhuman users can’t yet block tracking pixels. Vohra promises this feature is being prioritized.





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