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Archivo del Autor: Belen De Leon

2019 BMW X7 Prototype first drive review: Super-sized split personality – Roadshow

BMW’s first proper three-row SUV strikes an excellent balance between comfort and engagement.
Source: CNET

How Google’s Pixelbook broke the laptop mold with a Swedish design

Most laptops look the same, but the second we first saw the Pixelbook, we knew there something different about it. We sat down with the people who designed it to see how and why it was made.

The post How Google’s Pixelbook broke the laptop mold with a Swedish design appeared first on Digital Trends.


Source: Digital trends

Cambridge Analytica must hand data to US citizen, says British regulator – CNET

An American turns to the UK’s Data Protection Act to find out what info CA had on him. The company was at the center of the storm over Facebook data and privacy.
Source: CNET

MoviePass keeps playing with my heart, but I'll never cancel – CNET

Commentary: Even though being a MoviePass owner is a roller coaster ride, I’m too in love to abandon it now.
Source: CNET

World Video Game Hall of Fame welcomes John Madden and Lara Croft

The inductees for the 2018 World Video Game Hall of Fame have been revealed, and they include a boisterous sportscaster, a daring archaeologist, a blue-haired adventurer, and even a historic relic from the sixties.

The post World Video Game Hall of Fame welcomes John Madden and Lara Croft appeared first on Digital Trends.


Source: Digital trends

Kentucky Derby 2018: How to watch, stream live – CNET

The horses hit the raceway today, and watching it is simple.
Source: CNET

Lobe’s ridiculously simple machine learning platform aims to empower non-technical creators

Machine learning may be the tool de jour for everything from particle physics to recreating the human voice, but it’s not exactly the easiest field to get into. Despite the complexities of video editing and sound design, we have UIs that let even a curious kid dabble in them — why not with machine learning? That’s the goal of Lobe, a startup and platform that genuinely seems to have made AI models as simple to put together as LEGO bricks.

I talked with Mike Matas, one of Lobe’s co-founders and the designer behind many a popular digital interface, about the platform and his motivations for creating it.

“There’s been a lot of situations where people have kind of thought about AI and have these cool ideas, but they can’t execute them,” he said. “So those ideas just like shed, unless you have access to an AI team.”

This happened to him, too, he explained.

“I started researching because I wanted to see if I could use it myself. And there’s this hard to break through veneer of words and frameworks and mathematics — but once you get through that the concepts are actually really intuitive. In fact even more intuitive than regular programming, because you’re teaching the machine like you teach a person.”

But like the hard shell of jargon, existing tools were also rough on the edges — powerful and functional, but much more like learning a development environment than playing around in Photoshop or Logic.

“You need to know how to piece these things together, there are lots of things you need to download. I’m one of those people who if I have to do a lot of work, download a bunch of frameworks, I just give up,” he said. “So as a UI designer I saw the opportunity to take something that’s really complicated and reframe it in a way that’s understandable.”

Lobe, which Matas created with his co-founders Markus Beissinger and Adam Menges, takes the concepts of machine learning, things like feature extraction and labeling, and puts them in a simple, intuitive visual interface. As demonstrated in a video tour of the platform, you can make an app that recognizes hand gestures and matches them to emoji without ever seeing a line of code, let alone writing one. All the relevant information is there, and you can drill down to the nitty gritty if you want, but you don’t have to. The ease and speed with which new applications can be designed and experimented with could open up the field to people who see the potential of the tools but lack the technical know-how.

He compared the situation to the early days of PCs, when computer scientists and engineers were the only ones who knew how to operate them. “They were the only people able to use them, so they were they only people able to come up with ideas about how to use them,” he said. But by the late ’80s, computers had been transformed into creative tools, largely because of improvements to the UI.

Matas expects a similar flood of applications, even beyond the many we’ve already seen, as the barrier to entry drops.

“People outside the data science community are going to think about how to apply this to their field,” he said, and unlike before, they’ll be able to create a working model themselves.

A raft of examples on the site show how a few simple modules can give rise to all kinds of interesting applications: reading lips, tracking positions, understanding gestures, generating realistic flower petals. Why not? You need data to feed the system, of course, but doing something novel with it is no longer the hard part.

And in keeping with the machine learning community’s commitment to openness and sharing, Lobe models aren’t some proprietary thing you can only operate on the site or via the API. “Architecturally we’re built on top of open standards like Tensorflow,” Matas said. Do the training on Lobe, test it and tweak it on Lobe, then compile it down to whatever platform you want and take it to go.

Right now the site is in closed beta. “We’ve been overwhelmed with responses, so clearly it’s resonating with people,” Matas said. “We’re going to slowly let people in, it’s going to start pretty small. I hope we’re not getting ahead of ourselves.”


Source: TechCrunch

A fresh crop of new music to tickle your ears – CNET

Some rock, a lot of jazz, and a bunch of truly eclectic music that’ll make you want to get better speakers or headphones to hear how amazing this music really is.
Source: CNET

UK watchdog orders Cambridge Analytica to give up data in US voter test case

Another big development in the personal data misuse saga attached to the controversial Trump campaign-linked UK-based political consultancy, Cambridge Analytica — which could lead to fresh light being shed on how the company and its multiple affiliates acquired and processed US citizens’ personal data to build profiles on millions of voters for political targeting purposes.

The UK’s data watchdog, the ICO, has today announced that it’s served an enforcement notice on Cambridge Analytica affiliate SCL Elections, under the UK’s 1998 Data Protection Act.

The company has been ordered to give up all the data it holds on one US academic within 30 days — with the ICO warning that: “Failure to do so is a criminal offence, punishable in the courts by an unlimited fine.”

The notice follows a subject access request (SAR) filed in January last year by US-based academic, David Carroll after he became suspicious about how the company was able to build psychographic profiles of US voters. And while Carroll is not a UK citizen, he discovered his personal data had been processed in the UK — so decided to bring a test case by requesting his personal data under UK law.

Carroll’s complaint, and the ICO’s decision to issue an enforcement notice in support of it, looks to have paved the way for millions of US voters to also ask Cambridge Analytica for their data (the company claimed to have up to 7,000 data points on the entire US electorate, circa 240M people — so just imagine the class action that could be filed here… ).

The Guardian reports that Cambridge Analytica had tried to dismiss Carroll’s argument by claiming he had no more rights “than a member of the Taliban sitting in a cave in the remotest corner of Afghanistan”. The ICO clearly disagrees.

Cambridge Analytica/SCL Group responded to Carroll’s original SAR in March 2017 but he was unimpressed by the partial data they sent him — which ranked his interests on a selection of topics (including gun rights, immigration, healthcare, education and the environment) yet did not explain how the scores had been calculated.

It also listed his likely partisanship and propensity to vote in the 2016 US election — again without explaining how those predictions had been generated.

So Carroll complained to the UK’s data watchdog in September 2017 — which began sending its own letters to CA/SCL, leading to further unsatisfactory responses.

“The company’s reply refused to address the ICO’s questions and incorrectly stated Prof Caroll had no legal entitlement to it because he wasn’t a UK citizen or based in this country. The ICO reiterated this was not legally correct in a letter to SCL the following month,” the ICO writes today. “In November 2017, the company replied, denying that the ICO had any jurisdiction or that Prof Carroll was legally entitled to his data, adding that SCL did “.. not expect to be further harassed with this sort of correspondence”.”

In a strongly worded statement, information commissioner Elizabeth Denham further adds:

The company has consistently refused to co-operate with our investigation into this case and has refused to answer our specific enquiries in relation to the complainant’s personal data — what they had, where they got it from and on what legal basis they held it.

The right to request personal data that an organisation holds about you is a cornerstone right in data protection law and it is important that Professor Carroll, and other members of the public, understand what personal data Cambridge Analytica held and how they analysed it.

We are aware of recent media reports concerning Cambridge Analytica’s future but whether or not the people behind the company decide to fold their operation, a continued refusal to engage with the ICO will potentially breach an Enforcement Notice and that then becomes a criminal matter.

Since mid-March this year, Cambridge Analytica’s name (along with the names of various affiliates) has been all over headlines relating to a major Facebook data misuse scandal, after press reports revealed in granular detail how an app developer had used the social media’s platform’s 2014 API structure to extract and process large amounts of users’ personal data, passing psychometrically modeled scores on US voters to Cambridge Analytica for political targeting.

But Carroll’s curiosity about what data Cambridge Analytica might hold about him predates the scandal blowing up last month. Although journalists had actually raised questions about the company as far back as December 2015 — when the Guardian reported that the company was working for the Ted Cruz campaign, using detailed psychological profiles of voters derived from tens of millions of Facebook users’ data.

Though it was not until last month that Facebook confirmed as many as 87 million users could have had personal data misappropriated.

Carroll, who has studied the Internet ad tech industry as part of his academic work, reckons Facebook is not the sole source of the data in this case, telling the Guardian he expects to find a whole host of other companies are also implicated in this murky data economy where people’s personal information is quietly traded and passed around for highly charged political purposes — bankrolled by billionaires.

“I think we’re going to find that this goes way beyond Facebook and that all sorts of things are being inferred about us and then used for political purposes,” he told the newspaper.

Under mounting political, legal and public pressure, Cambridge Analytica claimed to be shutting down this week — but the move appears more like a rebranding exercise, as parent entity, SCL Group, maintains a sprawling network of companies and linked entities. (Such as one called Emerdata, which was founded in mid-2017 and is listed at the same address as SCL Elections, and has many of the same investors and management as Cambridge Analytica… But presumably hasn’t yet been barred from social media giants’ ad platforms, as its predecessor has.)

Closing one of the entities embroiled in the scandal could also be a tactic to impede ongoing investigations, such as the one by the ICO — as Denham’s statement alludes, by warning that any breach of the enforcement notice could lead to criminal proceedings being brought against the owners and operators of Cambridge Analytica’s parent entity.

In March ICO officials obtained a warrant to enter and search Cambridge Analytica’s London offices, removing documents and computers for examination as part of a wider, year-long investigation into the use of personal data and analytics by political campaigns, parties, social media companies and other commercial actors. And last month the watchdog said 30 organizations — including Facebook — were now part of that investigation.

The Guardian also reports that the ICO has suggested to Cambridge Analytica that if it has difficulties complying with the enforcement notice it should hand over passwords for the servers seized during the March raid on its London office – raising questions about how much data the watchdog has been able to retrieve from the seized servers.

SCL Group’s website contains no obvious contact details beyond a company LinkedIn profile — a link which appears to be defunct. But we reached out to SCL Group’s CEO Nigel Oakes, who has maintained a public LinkedIn presence, to ask if he has any response to the ICO enforcement notice.

Meanwhile Cambridge Analytica continues to use its public Twitter account to distribute a stream of rebuttals and alternative ‘facts’.


Source: TechCrunch

The formula behind San Francisco’s startup success

Why has San Francisco’s startup scene generated so many hugely valuable companies over the past decade?

That’s the question we asked over the past few weeks while analyzing San Francisco startup funding, exit, and unicorn creation data. After all, it’s not as if founders of Uber, Airbnb, Lyft, Dropbox and Twitter had to get office space within a couple of miles of each other.

We hadn’t thought our data-centric approach would yield a clear recipe for success. San Francisco private and newly public unicorns are a diverse bunch, numbering more than 30, in areas ranging from ridesharing to online lending. Surely the path to billion-plus valuations would be equally varied.

But surprisingly, many of their secrets to success seem formulaic. The most valuable San Francisco companies to arise in the era of the smartphone have a number of shared traits, including a willingness and ability to post massive, sustained losses; high-powered investors; and a preponderance of easy-to-explain business models.

No, it’s not a recipe that’s likely replicable without talent, drive, connections and timing. But if you’ve got those ingredients, following the principles below might provide a good shot at unicorn status.

First you conquer, then you earn

Losing money is not a bug. It’s a feature.

First, lose money until you’ve left your rivals in the dust. This is the most important rule. It is the collective glue that holds the narratives of San Francisco startup success stories together. And while companies in other places have thrived with the same practice, arguably San Franciscans do it best.

It’s no secret that a majority of the most valuable internet and technology companies citywide lose gobs of money or post tiny profits relative to valuations. Uber, called the world’s most valuable startup, reportedly lost $4.5 billion last year. Dropbox lost more than $100 million after losing more than $200 million the year before and more than $300 million the year before that. Even Airbnb, whose model of taking a share of homestay revenues sounds like an easy recipe for returns, took nine years to post its first annual profit.

Not making money can be the ultimate competitive advantage, if you can afford it.

Industry stalwarts lose money, too. Salesforce, with a market cap of $88 billion, has posted losses for the vast majority of its operating history. Square, valued at nearly $20 billion, has never been profitable on a GAAP basis. DocuSign, the 15-year-old newly public company that dominates the e-signature space, lost more than $50 million in its last fiscal year (and more than $100 million in each of the two preceding years). Of course, these companies, like their unicorn brethren, invest heavily in growing revenues, attracting investors who value this approach.

We could go on. But the basic takeaway is this: Losing money is not a bug. It’s a feature. One might even argue that entrepreneurs in metro areas with a more fiscally restrained investment culture are missing out.

What’s also noteworthy is the propensity of so many city startups to wreak havoc on existing, profitable industries without generating big profits themselves. Craigslist, a San Francisco nonprofit, may have started the trend in the 1990s by blowing up the newspaper classified business. Today, Uber and Lyft have decimated the value of taxi medallions.

Not making money can be the ultimate competitive advantage, if you can afford it, as it prevents others from entering the space or catching up as your startup gobbles up greater and greater market share. Then, when rivals are out of the picture, it’s possible to raise prices and start focusing on operating in the black.

Raise money from investors who’ve done this before

You can’t lose money on your own. And you can’t lose any old money, either. To succeed as a San Francisco unicorn, it helps to lose money provided by one of a short list of prestigious investors who have previously backed valuable, unprofitable Northern California startups.

It’s not a mysterious list. Most of the names are well-known venture and seed investors who’ve been actively investing in local startups for many years and commonly feature on rankings like the Midas List. We’ve put together a few names here.

You might wonder why it’s so much better to lose money provided by Sequoia Capital than, say, a lower-profile but still wealthy investor. We could speculate that the following factors are at play: a firm’s reputation for selecting winning startups, a willingness of later investors to follow these VCs at higher valuations and these firms’ skill in shepherding portfolio companies through rapid growth cycles to an eventual exit.

Whatever the exact connection, the data speaks for itself. The vast majority of San Francisco’s most valuable private and recently public internet and technology companies have backing from investors on the short list, commonly beginning with early-stage rounds.

Pick a business model that relatives understand

Generally speaking, you don’t need to know a lot about semiconductor technology or networking infrastructure to explain what a high-valuation San Francisco company does. Instead, it’s more along the lines of: “They have an app for getting rides from strangers,” or “They have an app for renting rooms in your house to strangers.” It may sound strange at first, but pretty soon it’s something everyone seems to be doing.

It’s not a recipe that’s likely replicable without talent, drive, connections and timing. 

list of 32 San Francisco-based unicorns and near-unicorns is populated mostly with companies that have widely understood brands, including Pinterest, Instacart and Slack, along with Uber, Lyft and Airbnb. While there are some lesser-known enterprise software names, they’re not among the largest investment recipients.

Part of the consumer-facing, high brand recognition qualities of San Francisco startups may be tied to the decision to locate in an urban center. If you were planning to manufacture semiconductor components, for instance, you would probably set up headquarters in a less space-constrained suburban setting.

Reading between the lines of red ink

While it can be frustrating to watch a company lurch from quarter to quarter without a profit in sight, there is ample evidence the approach can be wildly successful over time.

Seattle’s Amazon is probably the poster child for this strategy. Jeff Bezos, recently declared the world’s richest man, led the company for more than a decade before reporting the first annual profit.

These days, San Francisco seems to be ground central for this company-building technique. While it’s certainly not necessary to locate here, it does seem to be the single urban location most closely associated with massively scalable, money-losing consumer-facing startups.

Perhaps it’s just one of those things that after a while becomes status quo. If you want to be a movie star, you go to Hollywood. And if you want to make it on Wall Street, you go to Wall Street. Likewise, if you want to make it by launching an industry-altering business with a good shot at a multi-billion-dollar valuation, all while losing eye-popping sums of money, then you go to San Francisco.


Source: TechCrunch

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