Category: Tech news

The indictment filed today against 12 Russians accused of, among other things, hacking the DNC and undermining Hillary Clinton’s campaign also notes that the alleged hackers paid for their nefarious deeds with bitcoin and other cryptocurrencies. This unsavory application of one of tech’s current darlings will almost certainly be wielded against it by opportunists of all stripes.

It is perhaps the most popular and realistic argument against cryptocurrency that it enables anonymous transactions globally and at scale, no exception made for Russian intelligence or ISIS. So the news that a prominent and controversial technology was used to fund state-sponsored cyber attacks will not be passed over by its critics.

You can expect bluster on cable news and some sharp words from lawmakers, who will also probably issue some kind of public denouncement of cryptocurrencies and call for more stringent regulation. It’s only natural: their constituencies will hear that Russians are using bitcoin to hack the election systems and take it at face value. They have to say something.

But this knee-jerk criticism is misguided and hypocritical for several reasons.

First is that it’s not as anonymous and mysterious as critics make out. The details in the indictment actually provide an interesting example (far from the first) of the limits of cryptocurrency’s ability to obscure its users’ activities.

The painstaking research of the special investigator’s team revealed the approximate amounts and methods involved, and although there is a veneer of anonymity in that addresses are not inherently tied to identities, it is far from impossible to establish ownership. Not that they didn’t try, as the indictment shows:

The Defendants conspired to launder the equivalent of more than $95,000 through a web of transactions structured to capitalize on the perceived anonymity of cryptocurrencies such as bitcoin.

They also enlisted the assistance of one or more third-party exchangers who facilitated layers transactions through digital currency exchange platforms providing heightened anonymity.

But the process of laundering, after all, becomes rather difficult when there is an immutable, peer-maintained record of every penny being pushed around. Small slip-ups in the team’s operational security allowed investigators to tie, for example, an email address used to access a given bitcoin wallet with the one used to pay for a VPN.

[U]sing funds in a bitcoin address, the Conspirators purchased a VPN account, which they later used to log into the @Guccifer_2 Twitter account. The remaining funds from that bitcoin address were then used […] to lease a Malaysian server that hosted the dcleaks.com website.

It’s likely that the very same distributed ledger technology that allows for anonymous international payments in the first place also creates an invaluable investigative tool for those savvy enough to take advantage of it. So although bitcoin has its shady side, it’s far from perfect secrecy, especially when exposed to the privileges of a federal investigative team.

The second reason the criticism will be hollow is that it doesn’t provide much in the way of new capabilities for those who wish to keep secret their activities online.

There are established methods used by nation-states and garden-variety hackers and criminals alike that minimize or eliminate the possibility of tracking. Money laundering is performed at huge volumes worldwide and there are shady banks, loopholes and puppet organizations peppered across the globe.

Cryptocurrencies are convenient for paying for things online because there are a number of vendors (dwindling, but they exist) that accept it straight, or if one is not available it is reasonably liquid and can be shifted easily. I feel sure that our own intelligence services are making good use of it.

On that note is the third reason this FUD will be risible: If we are going to address the problem of dark money influencing politics, using bitcoin for hacking activities doesn’t even amount to a rounding error and it is cynical prestidigitation that makes it appear more than such.

I won’t belabor the point, because it is surely topmost in many an American’s mind that cash funneled through Super PACs and offshore accounts, backroom deals and stock trades, favors for lobbyists and corporate “donators” and 20 other forms of pay-for-play in Washington are more of a clear and present danger than a handful of Russian operatives ineffectually obscuring peanuts payments for hosting fees and bribes.

Perhaps the administration would prefer scripture: “Why do you see the speck that is in your brother’s eye, but do not notice the log that is in your own eye?”

If anything these indictments are evidence only that cryptocurrency is here to stay, usable by you, or me, or an rival nation-state, or our own — just like any other financial instrument.

When one of the main selling points for your service is the ability to stream live sports, the last thing you want is a full-on service meltdown during a huge game.

Alas, that’s exactly what happened on Wednesday to YouTube TV. Just as the World Cup semi-finals game between Croatia and England started heating up, the service went dark.

As something of a mea culpa, YouTube has sent out an email to subscribers promising a free week of YouTube TV service. With most users paying ~$40 a month for the service, that works out to about $10 off their next bill. Curiously, user reports suggest the refund is going out to most, if not all, YouTube TV users — not just those who were watching (or, you know, trying to watch) the game in question.

Meanwhile, some users have noted that reaching out directly to customer service lead to them getting a full month for free — so if you’re still feeling a bit burned by the whole thing, that might be something worth pursuing.

If you’re a subscriber but aren’t seeing the notice, check your spam box — some users in this Reddit thread are mentioning finding the notice hiding in there, or tucked away in the “social” tab in Gmail’s split view.

The current world speed record for riding a bike down a straight, flat road was set in 2012 by a Dutch team, but the Swiss have a plan to topple their rivals — with a little help from machine learning. An algorithm trained on aerodynamics could streamline their bike, perhaps cutting air resistance by enough to set a new record.

Currently the record is held by Sebastiaan Bowier, who in 2012 set a record of 133.78 km/h, or just over 83 mph. It’s hard to imagine how his bike, which looked more like a tiny landbound rocket than any kind of bicycle, could be significantly improved on.

But every little bit counts when records are measured down a hundredth of a unit, and anyway, who knows but that some strange new shape might totally change the game?

To pursue this, researchers at the École Polytechnique Fédérale de Lausanne’s Computer Vision Laboratory developed a machine learning algorithm that, trained on 3D shapes and their aerodynamic qualities, “learns to develop an intuition about the laws of physics,” as the university’s Pierre Baqué said.

“The standard machine learning algorithms we use to work with in our lab take images as input,” he explained in an EPFL video. “An image is a very well-structured signal that is very easy to handle by a machine-learning algorithm. However, for engineers working in this domain, they use what we call a mesh. A mesh is a very large graph with a lot of nodes that is not very convenient to handle.”

Nevertheless, the team managed to design a convolutional neural network that can sort through countless shapes and automatically determine which should (in theory) provide the very best aerodynamic profile.

“Our program results in designs that are sometimes 5-20 percent more aerodynamic than conventional methods,” Baqué said. “But even more importantly, it can be used in certain situations that conventional methods can’t. The shapes used in training the program can be very different from the standard shapes for a given object. That gives it a great deal of flexibility.”

That means that the algorithm isn’t just limited to slight variations on established designs, but it also is flexible enough to take on other fluid dynamics problems like wing shapes, windmill blades or cars.

The tech has been spun out into a separate company, Neural Concept, of which Baqué is the CEO. It was presented today at the International Conference on Machine Learning in Stockholm.

A team from the Annecy University Institute of Technology will attempt to apply the computer-honed model in person at the World Human Powered Speed Challenge in Nevada this September — after all, no matter how much computer assistance there is, as the name says, it’s still powered by a human.

The team at Octi says it’s building a crucial piece of the augmented reality puzzle — the ability to understand the human body and its movement.

Co-founder and CEO Justin Fuisz told me that most existing AR technologies (including Apple’s ARKit) tend to be “plane-based” — in other words, while they can make something cool appear against a real-world background, it’s usually on a flat surface, like a table or the floor.

Octi, on the other hand, recognizes where people are in-camera, and it can use that understanding to apply a variety of different effects.

For example, Fuisz and his team showed me how they could dance around their office while bright, squiggly lines overlaid their bodies — and then they erased their bodies entirely. They also showed me how effects could be tied to different gestures, like how a “make it rain” motion could result in dollar bills flying out of their hands.

To do this, Octi says it’s built sophisticated machine learning and computer vision technology. For starters, it looks at a human being and detects key points, like eyes, nose, hips and elbows, then uses those points to construct a model of a skeleton.

Fuisz suggested that the technology could be applied to a number of different industries, including fashion, fitness, entertainment and gaming. In fact, the company is announcing a partnership and strategic investment from the OneTeam Collective, the accelerator of the NFL Players Association. As a result, Octi plans to create and distribute avatars of more than 2,000 NFL players.

In addition, Octi is announcing that it has raised $7.5 million in seed funding from Shasta Ventures, I2BF Ventures, Bold Capital Partners, Day One Ventures, Human Ventures Live Nation and AB InBev, plus individuals, including former Pandora and Snap executive Tom Conrad, WeWork Chief Product Officer of Technology Shiva Rajaraman, Adobe Chief Product Officer Scott Belsky, A&D Networks Chairman Abbe Raven and Joshua Kushner.

If you want to try this out for yourself, the startup has its own iOS app — Fuisz described the app as a technology showcase for potential partners, but he added, “The app is available to the public and is totally awesome.”

Netflix has broken HBO’s 17-year streak as the most nominated network at the Emmy Awards.

In the nominations released this afternoon, Netflix came out slightly ahead, with 112 nominations compared to HBO’s 108. Those include Best Comedy nods for GLOW and Unbreakable Kimmy Schmidt, as well as Best Drama nominations for The Crown and Stranger Things.

Other Netflix shows got some love as well. Jordan Crook, my co-host on the Original Content podcast, will be glad to know that Jason Bateman was nominated for his work as both actor and director on Ozark. Meanwhile, Black Mirror‘s “USS Callister” episode was nominated for Best Television Movie.

The other big streaming services had good news, too. Hulu received 27 nominations, with last year’s Best Drama winner The Handmaid’s Tale up for the big award again. Handmaid’s Tale was one of the most-nominated shows overall, although its 20 nominations were just shy of Westworld‘s 21 and Game of Thrones’ 22. (These are nominations for GoT’s seventh season, which aired last summer.)

Meanwhile, Amazon’s shows received 22 nominations, including a Best Comedy nod for The Marvelous Mrs. Maisel.

The winners will be announced in a ceremony hosted by Colin Jost and Michael Che on Sept. 17.

As Elon Musk proposes water filters for Flint, the city’s mayor and others outline what would actually help.

The U.S. Department of Justice has filed to appeal a federal judge’s decision to approve AT&T’s acquisition of Time Warner.

Back when he was campaigning for the presidency, Donald Trump said his administration would block the deal, and indeed, the DOJ sued to stop the merger, arguing it would hurt competition.

Last month, however, U.S. District Court Judge Richard J. Leon ruled that the deal could move forward without conditions. He said from the bench, “The court has now spoken. … The defendants have won” — and the deal closed later that week.

In fact, we’re already starting to see some of the fallout, with AT&T’s reported plans for Time Warner-owned HBO leading to a flurry of worried headlines in just the past couple days.

The deal also seemed to set the stage for even more consolidation between telecom and media companies, leading Comcast to challenge Disney for ownership of Fox’s film and TV assets. (TechCrunch was already a very small part of this trend, since we’re owned by Verizon.)

“The Court’s decision could hardly have been more thorough, fact-based, and well-reasoned,” said AT&T General Counsel David McAtee in a statement. “While the losing party in litigation always has the right to appeal if it wishes, we are surprised that the DOJ has chosen to do so under these circumstances. We are ready to defend the Court’s decision at the D.C. Circuit Court of Appeals.”

To put it mildly, news media has been on the sidelines in AI development. As a consequence, in the age of AI-powered personalized interfaces, the news organizations don’t anymore get to define what’s real news, or, even more importantly, what’s truthful or trustworthy. Today, social media platforms, search engines and content aggregators control user flows to the media content and affect directly what kind of news content is created. As a result, the future of news media isn’t anymore in its own hands. Case closed?

The (Death) Valley of news digitalization

There’s a history: News media hasn’t been quick or innovative enough to become a change maker in the digital world. Historically, news used to be the signal that attracted and guided people (and advertisers) in its own right. The internet and the exponential explosion of available information online changed that for good.

In the early internet, the portals channeled people to the content in which they were interested. Remember Yahoo? As the amount of information increased, the search engine(s) took over, changing the way people found relevant information and news content online. As the mobile technologies and interfaces started to get more prominent, social media with News Feed and tweets took over, changing again the way people discovered media content, now emphasizing the role of our social networks.

Significantly, news media didn’t play an active role in any of these key developments. Quite the opposite, it was late in utilizing the rise of the internet, search engines, content aggregators, mobile experience, social media and other new digital solutions to its own benefit.

The ad business followed suit. First news organizations let Google handle searches on their websites and the upcoming search champion got a unique chance to index media content. With the rise of social media, news organizations, especially in the U.S., turned to Facebook and Twitter to break the news rather than focusing on their own breaking news features. As a consequence, news media lost its core business to the rising giants of the new digital economy.

To put it very strongly, news media hasn’t ever been fully digital in its approach to user experience, business logic or content creation. Think paywalls and e-newspapers for the iPad! The internet and digitalization forced the news media to change, but the change was reactive, not proactive. The old, partly obsolete, paradigms of content creation, audience understanding, user experience and content distribution still actively affect the way news content is created and distributed today (and to be 110 percent clear — this is not about the storytelling and the unbelievable creativity and hard work done by ingenious journalists all around the globe).

Due to these developments, today’s algorithmic gatekeepers like Google and Facebook dominate the information flows and the ad business previously dominated by the news media. Significantly, personalization and the ad-driven business logic of today’s internet behemoths isn’t designed to let the news media flourish on its own terms ever again.

From observers to change makers

News media have been reporting the rise of the new algorithmic world order as an outside observer. And the reporting has been thorough, veracious and enlightening — the stories told by the news media have had a concrete effect on how people perceive our continuously evolving digital realities.

However, as the information flows have moved into the algorithmic black boxes controlled by the internet giants, it has become obvious that it’s very difficult or close to impossible for an outside observer to understand the dynamics that affect how or why a certain piece of information becomes newsworthy and widely spread. For the mainstream news media, Trump’s rise to the presidency came as a “surprise,” and this is but one example of the new dynamics of today’s digital reality.

And here’s a paradox. As the information moves closer to us, to the mobile lock screen and other surfaces that are available and accessible for us all the time, its origins and background motives become more ambiguous than ever.

The social media combined with self-realizing feedback loops utilizing the latest machine learning methods, simultaneously being vulnerable for malicious or unintended gaming, has led us to the world of “alternative facts” and fake news. In this era of automated troll-hordes and algorithmic manipulation, the ideals of news media sound vitally important and relevant: Distribution of truthful and relevant information; nurturing the freedom of speech; giving the voice to the unheard; widening and enriching people’s worldview; supporting democracy.

But, the driving values of news media won’t ever be fully realized in the algorithmic reality if the news media itself isn’t actively developing solutions that shape the algorithmic reality.

The current course won’t be changed by commenting on or criticizing the actions of the ruling algorithmic platforms. #ChangeFacebook is not on the table for news media. New AI-powered Google News is controlled and developed by Google, based on its company culture and values, and thus can’t be directly affected by the news organizations.

After the rise of the internet and today’s algorithmic rule, we are again on the verge of a significant paradigm shift. Machine learning-powered AI solutions will have an increasingly significant impact on our digital and physical realities. This is again a time to affect the power balance, to affect the direction of digital development and to change the way we think when we think about news — a time for news media to transform from an outside observer into a change maker.

AI solutions for news media

If the news media wants to affect how news content is created, developed, presented and delivered to us in the future, they need to take an active role in AI development. If news organizations want to understand the way data and information are constantly affected and manipulated in digital environments, they need to start embracing the possibilities of machine learning.

But how can news media ever compete with today’s AI leaders?

News organisations have one thing that Google, Facebook and other big internet players don’t yet have: news organizations own the content creation process and thus have a deep and detailed content understanding. By focusing on appropriate AI solutions, they can combine the data related to the content creation and content consumption in a unique and powerful way.

News organizations need to use AI to augment you and me. And they need to augment journalists and the newsroom. What does this mean?

Augment the user-citizen

Personalization has been around for a while, but has it ever been designed and developed in the terms of news media itself? The goal for news media is to combine great content and personalized user experience to build a seamless and meaningful news experience that is in line with journalistic principles and values.

For news, the upcoming real-time machine learning methods, such as online learning, offer new possibilities to understand the user’s preferences in their real-life context. These technologies provide new tools to break news and tell stories directly on your lock screen.

An intelligent notification system sending personalized news notifications could be used to optimize content and content distribution on the fly by understanding the impact of news content in real time on the lock screens of people’s mobile devices. The system could personalize the way the content is presented, whether serving voice, video, photos, augmented reality material or visualizations, based on users’ preferences and context.

Significantly, machine learning can be utilized to create new forms of interaction between people, journalists and the newsroom. Automatically moderated commenting is just one example already in use today. Think if it would be possible to build interactions directly on the lock screen that let the journalists better understand the way content is consumed, simultaneously capturing in real time the emotions conveyed by the story.

By opening up the algorithms and data usage through data visualizations and in-depth articles, the news media could create a new, truly human-centered form of personalization that lets the user know how personalization is done and how it’s used to affect the news experience.

And let’s stop blaming algorithms when it comes to filter bubbles. Algorithms can be used to diversify your news experience. By understanding what you see, it’s also possible to understand what you haven’t seen before. By turning some of the personalization logic upside down, news organizations could create a machine learning-powered recommendation engine that amplifies diversity.

Augment the journalist

In the domain of abstracting and contextualizing new information and unpredictable (news) events, human intelligence is still invincible.

The deep content understanding of journalists can be used to teach an AI-powered news assistant system that would become better over time by learning directly from the journalists using it, simultaneously taking into account the data that flows from the content consumption.

A smart news assistant could point out what kinds of content are connected implicitly and explicitly, for example based on their topic, tone of voice or other meta-data such as author or location. Such an intelligent news assistant could help the journalist understand their content even better by showing which previous content is related to the now-trending topic or breaking news. The stories could be anchored into a meaningful context faster and more accurately.

AI solutions could be used to help journalists gather and understand data and information faster and more thoroughly. An intelligent news assistant can remind the journalist if there’s something important that should be covered next week or coming holiday season, for example by recognizing trends in social media or search queries or highlighting patterns in historic coverage. Simultaneously, AI solutions will become increasingly essential for fact-checking and in detecting content manipulation, e.g. recognizing faked images and videos.

An automated content production system can create and annotate content automatically or semi-automatically, for example by creating draft versions based on an audio interview, that are then finished by human journalists. Such a system could be developed further to create news compilations from different content pieces and formats (text, audio, video, image, visualization, AR experiences and external annotations) or to create hyper-personalized atomized news content such as personalized notifications.

The news assistant also could recommend which article should be published next using an editorial push notification, simultaneously suggesting the best time for sending the push notification to the end users. And as a reminder, even though Google’s Duplex is quite a feat, natural language processing (NLP) is far from solved. Human and machine intelligence can be brought together in the very core of the content production and language understanding process. Augmenting the linguistic superpowers of journalists with AI solutions would empower NLP research and development in new ways.

Augment the newsroom

Innovation and digitalization doesn’t change the culture of news media if it’s not brought into the very core of the news business concretely in the daily practices of the newsroom and business development, such as audience understanding.

One could start thinking of the news organization as a system and platform that provides different personalized mini-products to different people and segments of people. Newsrooms could get deeper into relevant niche topics by utilizing automated or semi-automated content production. And the more topics covered and the deeper the reporting, the better the newsroom can produce personalized mini-products, such as personalized notifications or content compilations, to different people and segments.

In a world where it’s increasingly hard to distinguish a real thing from fake, building trust through self-reflection and transparency becomes more important than ever. AI solutions can be used to create tools and practices that enable the news organization and newsroom to understand its own activities and their effects more precisely than ever. At the same time, the same tools can be used to build trust by opening the newsroom and its activities to a wider audience.

Concretely, AI solutions could detect and analyze possible hidden biases in the reporting and storytelling. For example, are some groups of people over-presented in certain topics or materials? What has been the tone of voice or the angle related to challenging multi-faceted topics or widely covered news? Are most of the photos depicting people with a certain ethnic background? Are there important topics or voices that are not presented in the reporting at all? AI solutions also can be used to analyze and understand what kind of content works now and what has worked before, thus giving context-specific insights to create better content in the future.

AI solutions would help reflect the reporting and storytelling and their effects more thoroughly, also giving new tools for decision-making, e.g. to determine what should be covered and why.

Also, such data and information could be visualized to make the impact of reporting and content creation more tangible and accessible for the whole newsroom. Thus, the entire editorial and journalistic decision-making process can become more open and transparent, affecting the principles of news organizations from the daily routines to the wider strategical thinking and management.

Tomorrow’s news organizations will be part human and part machine. This transformation, augmenting human intelligence with machines, will be crucial for the future of news media. To maintain their integrity and trustworthiness, news organizations themselves need to able to define how their AI solutions are built and used. And the only way to fully realize this is for the news organizations to start building their own AI solutions. The sooner, the better — for us all.

Robinhood has gone from being a little consumer-facing fintech app to an absolutely giant consumer-facing fintech app.

The company, which launched in 2013, has ballooned to a $5.6 billion valuation on the heels of a $363 million Series D financing round led by DST Global. The app has also grown to 5 million users, as of today, with more than $150 billion in transaction volume.

But the app, which lets people trade stocks and options for free, is also dabbling in the wondrous world of cryptocurrencies, setting the stage for a potential transition from “fun app” to legitimate financial institution.

That’s why we’re absolutely thrilled to have Robinhood co-founder and CEO Baiju Bhatt join us on the Disrupt SF 2018 stage.

The key to everything here is that Robinhood offered a simple consumer demand: free transactions on financial services. Unlike incumbents E*Trade and Scottrade, there are no trading fees on Robinhood, giving average consumers the chance to dip their toes in the market without any added barriers to entry.

At Disrupt, we’ll ask Bhatt about how Robinhood Crypto is progressing and what the company has in store as we head into next year.

Bhatt joins a wide array of big name speakers, from Dara Khosrowshahi to Reid Hoffman to Kirsten Green. It’s going to be an absolutely terrific show and we sincerely hope to see you there.

Tickets are available here.

Container ships sometimes have a handful of passenger cabins—the peak of carbon emissions frugality.

Now that Elon Musk’s car company is finally putting out the more affordable Model 3, it could be a problem.

The prize isn’t a charting single; it’s becoming the soundtrack to a nation’s memories.

For the first time in 18 years, HBO isn’t at the top of the Television Academy heap.

Google acquired API management service Apigee back in 2016, but it’s been pretty quiet around the service in recent years. Today, however, Apigee announced a number of smaller updates that introduce a few new integrations with the Google Cloud platform, as well as a major new partnership with cloud data management and integration firm Informatica that essentially makes Informatica the preferred integration partner for Google Apigee.

Like most partnerships in this space, the deal with Informatica involves some co-selling and marketing agreements, but that really wouldn’t be all that interesting. What makes this deal stand out is that Google is actually baking some of Informatica’s tools right into the Apigee dashboard. This will allow Apigee users to use Informatica’s wide range of integrations with third-party enterprise applications while Informatica users will be able to publish their APIs through Apigee and have that service manage them for them.

Some of Google’s competitors, including Microsoft, have built their own integration services. As Google Cloud director of product management Ed Anuff told me, that wasn’t really on Google’s road map. “It takes a lot of know-how to build a rich catalog of connectors,” he said. “You could go and build an integration platform but if you don’t have that, you can’t address your customer’s needs.” Instead, Google went to look for a partner who already has this large catalog and plenty of credibility in the enterprise space.

Similarly, Informatica’s senior VP and GM for big data, cloud and data integration Ronen Schwartz noted that many of his company’s customers are now looking to move into the cloud and this move will make it easier for Informatica’s customers to bring their services into Apigee and open them up for external applications. “With this partnership, we are bringing the best of breed of both worlds to our customers,” he said. “And we are doing it now and we are making it available in an integrated, optimized way.”

Photographer Rogers Grasas spent seven years traveling the Middle East to capture these stunning images.