Power

Google wants to (try to) make Google Glass cool again

Also this week: savvy virtual assistants, surveillance without violating people's privacy, and more patents from Big Tech.

Google Glass Enterprise 2

Is making these cool even possible?

Image: Google

This week was so full of fun patent applications that I didn't know where to start. We've got a throwback to 2013, a virtual assistant that knows when I've stopped talking, and headphones that can determine a user's hearing abilities.

But as always, remember that the big tech companies file all kinds of crazy patents for things, and though most never amount to anything, some end up defining the future

Alphabet

A cooler-looking Google Glass

Released in 2013, Google Glass, Google's stab at smart glasses, hit a fever pitch before quietly dying two years later. When it first came out, everyone thought it was the coolest thing on earth: a head-up display! On your face! That can show you your calendar! Countless articles were written about how it looked, what it did, how it worked, how it might violate privacy, and why it failed. The term Glasshole was conceived. My former colleague Kyle Russell was even assaulted while wearing a pair.

Google released version 2.0 to business users in 2019, but the initial excitement over the hardware died down and lost in the annals of tech history. Until now, it seems, at least according to this patent, which outlines a process for making Glass look better and work with glasses and prescription glasses. The original Glass had a tiny display attached to lensless glasses. But by placing a photopolymer lens in between the two pieces of glass that make up typical eyeglasses, Google hopes that the wearer doesn't look as dorky. Jury's still out on that, though.

More-savvy virtual assistants

My home is a smart home. I have a Google speaker or display in every room, I have Nest Cams, I have a Nest Hello and a Nest Learning Thermostat. I never really consider that my house is listening to me, even though I know that it is. At its simplest, I use my devices to turn on lights and play music, and at its most extreme, I use the speakers to enhance books that I'm reading to my kid, using the Read Along with Google feature. But sometimes I wonder if it's still listening even if I've stopped reading or talking to it — and especially when I've started talking about something private.

This patent takes that into consideration and offers a better way for the system to know that I've stopped talking by using various data points — such as my reading speed, other noises that imply I've moved to do something else, coughing — to signal that I've stopped reading.

Identifying explicit video content

YouTube is notorious for allowing objectionable content to seep into various parts of the app: This study shows that its algorithms often recommend false or sexualized content, explicit content is recommended to children, and YouTube still includes health misinformation. YouTube uses machine learning to try to catch some of the objectionable content before it's served up to users, and it's even hired moderators to try tackling the problem. Moderation efforts are working somewhat — in April, the company boasted that "violative view rate" was down 70% from 2017 — but clearly more work needs to be done.

This patent looks at improving how neural networks find objectionable content, using various combinations of inputs, such as comparing it to other videos that contain explicit content; analyzing the tags or title of the video; analyzing certain aspects of the video; and using various machine learning methods, such as triplet loss, to determine whether the video should be flagged.

Amazon

Hey machine, I'm talking to you

You can set up virtual assistants, like the Nest Hub and the Echo, to recognize certain voices at home. That allows the device to serve up personalized information, depending on who's asking it the questions.

This patent takes that scenario and expands on it, laying out a way for voice assistants to recognize different people outside of the home and can use natural language to give it commands. One of the examples provided imagines a coffee shop. A patron walks in, says three words to a voice assistant that's maybe installed in a POS; the machine recognizes that person's voice and pulls up account information.

Once everything is confirmed, the person could say, "I'd like a latte with an extra shot," and the system makes and then serves the coffee drink. At the same time, the computer sends a purchase order to the coffee shop's system. A hot cup of coffee without having to talk to anyone before I've had the coffee sounds like a dream.

Apple

Rejoice, copy editors!

I've been a copy editor for most of my journalism career, which means I'm expected to know how things are spelled, various grammar rules, and how to make sentences sound better. But when I write out a text or email on an iPhone, you'd think that I've never written a sentence in my entire life. My fat fingers often hit the wrong keys, and sometimes if I'm in a hurry, even my sentence structure is embarrassing.

This patent aims to help me and my fellow copy editors by teaching a machine to look out for errors, as well. Using a neural network, my phone would be able to not only correct my spelling, but also compare it to various other words that are spelled the same, and make sure I'm using the appropriate one.

Facebook

Determining hearing abilities

This patent makes so much sense, I'm surprised it hasn't been done yet (and if it has, please email me and let me know!). Headphones as they are made now are pretty much configured for people who have no hearing loss. This patent imagines a set of headphones that can be customized to the user, by doing a hearing assessment right on the spot. After receiving the data, the headphones could automatically adjust to turn up or turn down certain frequency levels or otherwise enhance the audio to help the wearer feel comfortable.

Microsoft

Surveillance without the privacy violations

Cameras are everywhere, monitoring our every move. But when capturing this information, certain steps must be taken to ensure privacy. Blacklisting, or providing rules around what can't be seen, are often prone to errors, which can not only violate people's privacy, but can violate laws as well.

This patent lays out how to improve these methods, using whitelisting methods instead. Teaching the machine to recognize what is allowed, rather than what is not, can help improve this functionality in more-precise ways. In fact, the patent references tests where whitelisting was around 5,000 times more accurate than blacklisting.

Fintech

Judge Zia Faruqui is trying to teach you crypto, one ‘SNL’ reference at a time

His decisions on major cryptocurrency cases have quoted "The Big Lebowski," "SNL," and "Dr. Strangelove." That’s because he wants you — yes, you — to read them.

The ways Zia Faruqui (right) has weighed on cases that have come before him can give lawyers clues as to what legal frameworks will pass muster.

Photo: Carolyn Van Houten/The Washington Post via Getty Images

“Cryptocurrency and related software analytics tools are ‘The wave of the future, Dude. One hundred percent electronic.’”

That’s not a quote from "The Big Lebowski" — at least, not directly. It’s a quote from a Washington, D.C., district court memorandum opinion on the role cryptocurrency analytics tools can play in government investigations. The author is Magistrate Judge Zia Faruqui.

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Veronica Irwin

Veronica Irwin (@vronirwin) is a San Francisco-based reporter at Protocol covering fintech. Previously she was at the San Francisco Examiner, covering tech from a hyper-local angle. Before that, her byline was featured in SF Weekly, The Nation, Techworker, Ms. Magazine and The Frisc.

The financial technology transformation is driving competition, creating consumer choice, and shaping the future of finance. Hear from seven fintech leaders who are reshaping the future of finance, and join the inaugural Financial Technology Association Fintech Summit to learn more.

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FTA
The Financial Technology Association (FTA) represents industry leaders shaping the future of finance. We champion the power of technology-centered financial services and advocate for the modernization of financial regulation to support inclusion and responsible innovation.
Enterprise

AWS CEO: The cloud isn’t just about technology

As AWS preps for its annual re:Invent conference, Adam Selipsky talks product strategy, support for hybrid environments, and the value of the cloud in uncertain economic times.

Photo: Noah Berger/Getty Images for Amazon Web Services

AWS is gearing up for re:Invent, its annual cloud computing conference where announcements this year are expected to focus on its end-to-end data strategy and delivering new industry-specific services.

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Donna Goodison

Donna Goodison (@dgoodison) is Protocol's senior reporter focusing on enterprise infrastructure technology, from the 'Big 3' cloud computing providers to data centers. She previously covered the public cloud at CRN after 15 years as a business reporter for the Boston Herald. Based in Massachusetts, she also has worked as a Boston Globe freelancer, business reporter at the Boston Business Journal and real estate reporter at Banker & Tradesman after toiling at weekly newspapers.

Image: Protocol

We launched Protocol in February 2020 to cover the evolving power center of tech. It is with deep sadness that just under three years later, we are winding down the publication.

As of today, we will not publish any more stories. All of our newsletters, apart from our flagship, Source Code, will no longer be sent. Source Code will be published and sent for the next few weeks, but it will also close down in December.

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Bennett Richardson

Bennett Richardson ( @bennettrich) is the president of Protocol. Prior to joining Protocol in 2019, Bennett was executive director of global strategic partnerships at POLITICO, where he led strategic growth efforts including POLITICO's European expansion in Brussels and POLITICO's creative agency POLITICO Focus during his six years with the company. Prior to POLITICO, Bennett was co-founder and CMO of Hinge, the mobile dating company recently acquired by Match Group. Bennett began his career in digital and social brand marketing working with major brands across tech, energy, and health care at leading marketing and communications agencies including Edelman and GMMB. Bennett is originally from Portland, Maine, and received his bachelor's degree from Colgate University.

Enterprise

Why large enterprises struggle to find suitable platforms for MLops

As companies expand their use of AI beyond running just a few machine learning models, and as larger enterprises go from deploying hundreds of models to thousands and even millions of models, ML practitioners say that they have yet to find what they need from prepackaged MLops systems.

As companies expand their use of AI beyond running just a few machine learning models, ML practitioners say that they have yet to find what they need from prepackaged MLops systems.

Photo: artpartner-images via Getty Images

On any given day, Lily AI runs hundreds of machine learning models using computer vision and natural language processing that are customized for its retail and ecommerce clients to make website product recommendations, forecast demand, and plan merchandising. But this spring when the company was in the market for a machine learning operations platform to manage its expanding model roster, it wasn’t easy to find a suitable off-the-shelf system that could handle such a large number of models in deployment while also meeting other criteria.

Some MLops platforms are not well-suited for maintaining even more than 10 machine learning models when it comes to keeping track of data, navigating their user interfaces, or reporting capabilities, Matthew Nokleby, machine learning manager for Lily AI’s product intelligence team, told Protocol earlier this year. “The duct tape starts to show,” he said.

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Kate Kaye

Kate Kaye is an award-winning multimedia reporter digging deep and telling print, digital and audio stories. She covers AI and data for Protocol. Her reporting on AI and tech ethics issues has been published in OneZero, Fast Company, MIT Technology Review, CityLab, Ad Age and Digiday and heard on NPR. Kate is the creator of RedTailMedia.org and is the author of "Campaign '08: A Turning Point for Digital Media," a book about how the 2008 presidential campaigns used digital media and data.

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