Apple Watch Credited With Saving a Man’s Life

Apple Watch is being credited for saving a New York man’s life.

While he was working at his family’s bowling alley business Bowlerland last month, 32-year-old William Monzidelis became dizzy and started bleeding all over his body. Soon after, the Apple Watch he was wearing sent him a notification to immediately seek medical help.

On the way to the hospital, Monzidelis started to have seizures and by the time he arrived at the hospital just 30 minutes later, he had lost 80% of his blood, according to NBC New York, which earlier reported on the harrowing story. Emergency personnel discovered he had suffered an erupted ulcer and would need a blood transfusion just to have surgery to correct it. Doctors performed the surgery and he survived.

According to Monzidelis, who was interviewed by NBC New York, the doctors told him that if he didn’t receive the Apple Watch notification, he would’ve died.

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Although the Apple Watch isn’t classified as a dedicated medical device, it has an increasing number of features aimed at monitoring a person’s health. Chief among its health-focused features is a tracker that will monitor a person’s heart activity and alert them when something is off. When Apple Watch identifies a problem, it sends an urgent notification that tells people to seek medical attention.

Monzidelis’ story isn’t unique. Earlier this week, in fact, ABC News reported that the Apple Watch saved the life of an 18-year-old woman after it recognized that her resting heart rate had jumped to 160 beats per minute. She rushed to an urgent care and then an emergency room, where she was told she had kidney failure, according to the report. If not for the Apple Watch, she would have died, doctors apparently told her.

“Stories like Deanna’s inspire us to dream bigger and push harder every day,” Apple CEO Tim Cook tweeted this week in response to the ABC News article.

F8 2018: Facebook Needs to Stop Bad VR Apps Before They Start

Facebook really, really wants you to give VR a go–no pun intended. That’s the message the company communicated yesterday during day one of F8, its annual developers conference in San Jose, California. The F8 keynote was filled with assurances that VR headsets like the new Oculus Go won’t create a barrier between you and the people around you. Instead, the company believes that wearing a face computer will be even more social, because you’ll be playing games, taking meetings, and video chatting with friends and family.

And since the apps that have already been created for Samsung’s Oculus-based Gear headset can be ported over to the Oculus Go headset, there are already more than a thousand apps available for the new $200 Oculus Go. What else do you need at this point in order to embrace VR?

For one, maybe a little reassurance that VR apps–as well as AR apps–are being designed with user privacy and reasonable data-sharing practices in mind. Facebook still needs to prove that it’s thinking about new technologies in a way that ensures they won’t become the next obvious frontier for abuse, misinformation, or even election interference. As the company’s primary platform has swelled to more than two billion users, it’s had its share of issues with false news, hate speech, and bad apps, due in part to Facebook’s own lack of due diligence during growth phases.

Facebook’s Oculus VR user base is still minuscule by comparison–according to one research firm, 1.8 million Oculus Go devices are expected to sell this year–but if Go becomes the great VR democratizer that Facebook is hoping it will be, then the new headset is introducing a new kind of app and a new kind of app store to a whole new subset of Facebook users. It also raises the question of how Facebook will deal with “fakeness” in an environment that is, by definition, entirely virtual.

Facebook’s executives in VR and AR say they have learned some lessons from the early days of Facebook, and that the company is trying to “ensure a very high quality of platform against misinformation or against bad actors,” according to AR/VR executive Andrew Bosworth. But Bosworth, known as “Boz,” also said in an interview with WIRED that he believes Facebook’s AR and VR app platforms are still too nascent to have serious abuse problems.

Facebook-owned Oculus utilizes its own app platform, separate from Facebook, Messenger, or the other apps that Facebook owns. You don’t need a Facebook account to sign up for Oculus, and linking your Oculus account to your Facebook account is optional, as WIRED’s Peter Rubin points out in his review of the headset. Go has its own app store, and many of the mobile VR apps that are front and center right now are highly recognizable brands or titles: Netflix, Hulu, NatGeo, Minecraft, The Last Jedi.

There are also only around a thousand apps right now, which means each app is reviewed manually, according to Bosworth. “It’s a manageable number of applications,” he says, “and you can just look at every one of them and make sure there’s nothing in there that’s untoward.”

Reality Check

In a pre-emptive move, ahead of changes that could be enforced when Europe’s General Data Protection Regulation goes into effect, Oculus published an update to its privacy policies two weeks ago. The update highlighted the addition of a privacy control center for users and clarified the kinds of information Oculus, and in some cases Facebook, collects about Oculus users. It also divulged the kinds of data that Oculus app makers have access to: the real-time position of your headset and controllers, your Friend List, and the boundaries of the physical space where you’re using Oculus. “We periodically audit our systems to determine if there’s evidence of nefarious activity,” the post reads, “and we take action accordingly.”

In other words: it doesn’t read all that different from Facebook’s privacy policies and settings on its core app or other apps. Especially when you consider the periodic audits; Facebook’s own privacy audit in 2017 didn’t catch the Cambridge Analytica data caper. As VR gets more sophisticated, and as standalone VR headsets get better at profile-building and advanced positional tracking (like the kind promised with Oculus’s “Santa Cruz” headset), it’s enough to make any non-early-adopter wary about the volume and granularity of data that’s being collected.

But Bosworth insists it “couldn’t be a better time, in terms of the public conversation, to build new platforms, because you can benefit from having observed all of the issues that can come as your platform grows and succeeds.” He cites examples of tools in Oculus that “allow people to either express or not express their identity as they see fit,” such as using a realistic avatar when using Facebook Spaces with friends, but exercising the option to be more opaque about who you are if you’re playing games against strangers.

A spokesperson for Oculus also said that the company has been working on an Abuse and Prevention API that’s being tested by a few app developers right now, and that will become more widely available later this year.

Still, Bosworth acknowledges there’s more work to be done in terms of the kind of privacy and safety tools that need to be offered, both to consumers and to developers in VR. Right now, the Oculus platform is still primarily experienced through the apps being built for mobile platforms, along with some PC apps for the Oculus Rift. That’s going to change if standalone VR really does take off. “As we go forward, I think there’s a much richer set of tools that we can provide to app developers,” Bosworth says, “so that within apps, there’s an additional layer of safety and security.”

More on Facebook Privacy

ECB designs cyber attack simulation for financial firms

FRANKFURT (Reuters) – The European Central Bank has designed a new test simulating cyber attacks on banks, stock exchanges and other firms that are critical for the functioning of the financial system, it said on Wednesday.

The logo of the European Central Bank (ECB) is pictured outside its headquarters in Frankfurt, Germany, April 26, 2018. REUTERS/Kai Pfaffenbach

The move follows a string of heists and attacks by hackers on lenders and central banks over the past two years, including one that disrupted online and mobile services at the Netherlands’ three top banks earlier this year.

The ECB’s initiative aims to create a single framework for testing the cyber-resilience of financial firms in the European Union.

The framework envisages, among other tools, “red teams” (RTs) of external hackers hired to find and exploit vulnerabilities in the companies being tested, a technique derived from the military world and widely used in the private sector.

“The test objectives … are the flags that the RT provider must attempt to capture during the test as it progresses through the scenarios,” the ECB said.

But its European Framework for Threat Intelligence-based Ethical Red Teaming (TIBER-EU) will simply serve as a guideline and it will be for other authorities to carry out any test.

“It is up to the relevant authorities and the entities themselves to determine if and when TIBER-EU based tests are performed,” the ECB said.

“Tests will be tailor-made and will not result in a pass or fail – rather they will provide the tested entity with insight into its strengths and weaknesses, and enable it to learn and evolve to a higher level of cyber maturity,” it added.

In of the most high profile cases to date, hackers breached the central bank of Bangladesh’s systems in early 2016 and tricked the Federal Reserve Bank of New York into sending as much as $81 million to accounts in the Philippines.

Reporting by Francesco Canepa; editing by David Stamp

P&G Shines Bright When Juxtaposed With Unilever

Contrasting Fortunes Between P&G And Unilever

In recent weeks, Procter & Gamble (PG) has received a couple of downgrades following its Q3 FY2018 results announcement. In contrast, its peer in the consumer products space, Unilever (UL)(UN)(OTCPK:UNLNF)(OTCPK:UNLYF)(OTCPK:UNLVF), was upgraded by UBS in late March. Investors also cheered the announcement of a fresh €6 billion ($7.4 billion) stock buyback program and the raising of its quarterly dividend by 8% to €0.3872/share from €0.3585. In 2017, Unilever has already completed a €5 billion share buyback programme.

Year-to-date (“YTD”), the share price of P&G has fallen 20.8% while Unilever was relatively more stable. In terms of enterprise value (“EV”), the contrast is even more stark, with Unilever’s EV higher by 9.7% YTD as compared to P&G’s EV decrease of 19.2%. Given that the two leading names in the consumer products sector are facing the same competitive pressures from house brands, rising commodity costs, and challenges from e-commerce disruptions, the divergence appears to suggest that P&G is overly punished by the market. I explore deeper to find out if the sell-down in P&G was unjustified or that Unilever is overvalued.


UL data by YCharts

Tailwind From The Weakness In The US Dollar Discounted By P&G Investors

Readers familiar with the two consumer products giants would be able to quickly point out the difference in their reporting currencies. Unilever reports its results in euros while P&G does so in US dollars. The persistent weakness in the US dollar since early 2017 has been a huge tailwind for US-based P&G. For instance, in the last calendar quarter of 2017, P&G reported a core EPS growth of 10% but adjusted for currency effect, the growth shrunk to 6%. YTD, the US dollar sustained another 2% loss against the euro. In the first calendar quarter of 2018, the currency-neutral core EPS growth at P&G was just 1%, against the reported 4% before adjustments. In contrast, Unilever attributed a negative 9.8% in revenue impact to foreign exchange in its Q1 2018 results. Unfortunately, given the share price underperformance of P&G, it is obvious that investors have already discounted the tailwind from the weaker US dollar.


US Dollar to Euro Exchange Rate data by YCharts

P&G To Continue Its Sales Growth Underperformance Against Unilever

Looking at the past five quarters, it is clear that Unilever has delivered superior underlying sales growth (“USG”) ranging 2.6-4.0% from a combination of pricing and volume growth as compared to P&G’s 1-2% (P&G uses the term “organic” which is essentially the same as “underlying”). One worrying trend for Unilever is the drastically deteriorating ability to improve its USG through price increases. In Q2 2017, Unilever could raise prices by 3.0% to compensate for a flat sales volume growth, but it could only do so by a paltry 0.1% in the most recent reported quarter (Q1 2018).

(Source: Unilever Q1 2018 Results Presentation)

(Source: P&G Q3 2018 Results Presentation)

While a more restrained price increase strategy has enabled a favorable volume growth, it is possible that consumers have brought forward their purchases in a promotional environment. If that is indeed the case, I suspected that Unilever might find the subsequent months more challenging to continue pushing more inventory onto consumers’ hands. Interestingly, the management does not agree. It is guiding for a USG of 3-5% in 2018 which at the midpoint would exceed its USG in 2017. The management of P&G is similarly bullish. It is guiding for an organic sales growth of 2-3% in 2018 and an “all in” sales growth of “about 3%,” higher than that achieved in 2017. Given the share price weakness despite such positivity, it’s no surprise that the P&G guidance has fallen short of consensus expectations. To me, the bias against P&G seems rather unfair.

P&G’s P/E Has Fallen Below That Of Unilever

Despite the lower sales growth at P&G, its shares had at times traded at a price-to-earnings (P/E) ratio similar or even above that of Unilever. However, the recent divergence in their share price movements has resulted in Unilever’s P/E rising to 22.83x, higher than P&G’s 19.31x. The distinction is more stark when we look at the P/E ratio less their cash holdings, where P&G P/E less cash is 17.67x compared to Unilever’s 22.12x. This is another indication that suggests that P&G might be oversold.


UL P/E Ratio (TTM) data by YCharts

P&G’s Dividend Yield Has Risen Above That Of Unilever

Both P&G and Unilever have a solid history of dividend growth (adjusting for currency effect and one-offs). Nevertheless, despite hiking its quarterly dividend by 8% to €0.3872/share from €0.3585, Unilever’s dividend yield has still fallen to below that of P&G. Based on the last closing price, Unilever has a dividend yield of 2.98% against P&G’s 3.83%. At 3.83%, P&G’s dividend yield is at a record high and it is one of the rare periods when its dividend yield is above that of Unilever. If you are a fan of the “reversion-to-the-mean” strategy, then perhaps this is an opportune time to bet on P&G’s recovery.


UL Dividend data by YCharts

P&G Has Fallen Far Below Its 200-Day EMA

With the steep YTD plunge, the share price of P&G has fallen way below its 200-day exponential moving average (“EMA”). The last time a similar deviation occurred was in 2015 and the shares rebounded to above the 200-day EMA less than half a year later. History might not repeat but for a Dividend Aristocrat (and a King at that) to experience such steep share price plunge relative to its sector peer is perhaps a sign that market players might have been too bearish on P&G.


UL data by YCharts

Analysts Have Been Revising P&G’s Price Target Downwards

While the most recent quarterly results were a beat on both the EPS and the revenue, analysts pointed to the weak pricing and the loss of market share as reasons for downgrading P&G. Despite the share price of P&G having already fallen 20.8% YTD, the upside to the consensus price target is only 13.09%, just slightly above that for Unilever at 11.23%. I found it unfathomable that analysts are overwhelmingly bearish towards P&G while staying positive on Unilever, despite the duo experiencing similar competitive markets in the world.


UL Price Target data by YCharts

Both P&G And Unilever Have Delivered On Operational Improvements

The management at both P&G and Unilever deserve to be complimented for having achieved significant improvements on the operational front. Notably, Unilever managed to turn its cash conversion cycle of 10 days to a negative 12 days by the end of 2017, effectively meaning that the company could pay its suppliers 12 days after it receives the cash from its customers, a commendable feat. For P&G, it has streamlined its supply chain while reducing 32% of roles across the organization. From FY2012 to FY2016, P&G has achieved a productivity gain of around $10 billion and it is targeting another $10 billion over the following four years.

(Source: P&G 2018 Consumer Analyst of New York Conference Presentation)


I wrote a bearish article on Unilever in September last year noting the diminishing returns from the various initiatives to improve its margins. However, I am not always pessimistic about the company. In late January 2017, my initiation article on Unilever highlighted the tremendous growth in its e-commerce business, among other positives. The issue is that the market sentiment has switched from underappreciating Unilever to buoyant, thanks to the management’s successful drive in operational improvements.

On the other hand, P&G appears undervalued when we consider the relative underperformance of its share price against that of Unilever. Similar to Unilever, P&G has in place a plan to achieve growth amid the challenging consumer products environment. Hence, I believe that P&G has been oversold and nimble traders might be able to profit from a near-term rebound while longer-term investors might find the current pricing to be an opportune time to add to their positions in the Dividend King of the consumer products space.

ALT Perspective ratings on Unilever TipRanks

(Source: TipRanks – ALT Perspective Ratings on Unilever)

What’s your take? Readers who make a comment will have access to the comment thread indefinitely. Hence, please freely share your thoughts, let me know if you found this article useful or provide your feedback in the comments section.

Author’s Note: Thank you for reading. If you would like a refreshing take on stocks that you own or are interested in, try looking here. Besides US companies, I cover a number of Asian stocks as well. If you wish to be informed of my new ideas via email so that you have time to read them before the articles get locked behind a paywall 10 days from publication, please select “Receive email alerts” when accessing on a desktop computer.

Disclosure: I/we have no positions in any stocks mentioned, but may initiate a long position in PG over the next 72 hours.

I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.

Editor’s Note: This article discusses one or more securities that do not trade on a major U.S. exchange. Please be aware of the risks associated with these stocks.

Amazon's Growth Is About To Slow

Investment Thesis

Whenever I talk to an Amazon (AMZN) shareholder they always highlight for me the same ‘story’ – which is, Amazon is investing for growth. However, if after more than a decade of investing for growth, the business is still only just marginally profitable, it makes you wonder if some of that cash has been squandered? And also begs the question, and the vastly more dangerous question of, when Amazon finally stops investing for growth and operating at just-above-break even, just how profitable will it actually be?

Recent Results: Q1 2018

Last week, Amazon released its Q1 2018 results and it showed that its top line had once again grown strongly by 39% YoY (currency adjusted). Also, that its operating cash flow was up just 4%.

(source) – Q1 2018 press release (click table to maximize)

Highlighted in the above table, on the top line is a trend, where the amount of cash from operating activities which Amazon generates trickles up quarter over quarter, at a slow and steady pace. Then, on the bottom line, it shows the amount of ‘owner earnings‘ or free cash flow that the owner of the business can walk away with each quarter. And there, it shows a trend, and how Amazon has gone from steadily generating cash to using cash at quite a steady pace. In fact, in its latest quarter, Amazon had an outflow of cash of $3 billion for its trailing twelve months compared with an inflow of $3.3 billion for the trailing twelve months ended Q1 2017.

Is Warren Buffett Right?

Anyone who says that size does not hurt investment performance is selling.

– Warren Buffett

For a long time, value-investors disciples have listened to the Oracle of Omaha say that size hurts performance, but these rules appear to have been ignored by Amazon shareholders. Accordingly, whenever I discuss Amazon with an Amazon shareholder, they go on to highlight to me a brand new avenue that Amazon is embarking on. When I question them on Amazon’s ability to generate free cash flow, their face boils red and the conversation turns slightly sour: ‘how dare I ask such blasphemous questions?’


From the point of view of revenue, Amazon has two main segments: its retail operations and AWS. However, for all the gains in market-share which Amazon makes in its retail operations, and although this quarter showed a strong improvement compared with the same period a year ago, its consolidated operating income stood at just $520 million.

Although Amazon’s second segment, AWS, is the only segment that is highly profitable, with operating income margins of roughly 25%; at the end of the day, this quarter just brought in $1.4 billion. These two segments together certainly do not support its present +$700 billion market cap.

For now, in an effort to best confuse Wall Street, Amazon runs these two very different business lines, its retail business and the cloud, under the same corporate structure. This obviously confuses many investors as they don’t know how with what to compare a company such as Amazon. Is it a retail business which should be compared to Walmart (WMT)? Or is a cloud business, with strong margins that should be awarded a higher, tech-like, multiple, such as Alphabet?

Incidentally, I should note, that Amazon’s AWS is no longer growing unrivalled. Now that Microsoft (MSFT) has woken up to the profitability of the cloud, AWS is no longer able to price its offering regardless of the competition. AWS must price its offering to gain market share and scale. Furthermore, Microsoft’s Azure is now growing at above 90% YoY, for several quarters and it currently holds a solid second place in terms of market-share.

(source): Top cloud providers

On the other hand, although AWS still holds the number one position for cloud market-share, its growth was ‘only’ 49% YoY and significantly less than Microsoft’s Azure’s growth.

Finally, it is important to highlight that Amazon’s current valuation is actually more expensive than it has been during the past 5-years on average. Said another way, as Amazon has grown to the size it has, and it has fewer and fewer opportunities for future growth it is actually being priced more expensively than in its past – which is ironic. Whenever one analyzes a publicly traded investment, one should think, what kind of ‘edge’ do I have that others have not thought about. It is not sufficient to say that ‘I have a longer-term horizon than others’ because when something is being traded more expensively than in the past, I could argue that opportunity has already been accounted for.


Too many investors confuse knowing a business or liking its products with thinking that this or that company makes for a worthwhile investment. For example, whilst I utterly enjoy the benefits associated with being a Prime member and have a nearly daily use of Amazon, this does not mean that I think that its stock makes for a safe investment.

Disclaimer: Please do your own due diligence to reach your own conclusions.

Note: The only favor I ask is that you click the “Follow” button, so I can grow my Seeking Alpha friendships and our Deep Value network. Please excuse any grammatical errors.

Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours.

I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.

'Westworld' Recap, Season 2 Episode 2: The Façade Is Crumbling

Fellow watchers of Westworld, we have cracked the façade.

The second episode of Season 2 opens on Dolores’ (Evan Rachel Wood) face. Bernard (Jeffrey Wright) asks if she knows where she is; she guesses she is in a dream. He corrects her: “No, you’re in our world.” The camera pulls back to reveal them seated at a window of a high rise, looking down on the sparkling lights of a metropolis at night.

Holy smokes! The outside world! And Dolores, dressed in a black cocktail dress and heels—what’s she doing outside the park?!

For so long, Westworld focused so much of its energy on the dramas of that dusty park that it was easy for viewers to forget the world beyond. That, of course, is exactly the point of Westworld: to be a place where people can unshackle themselves from reality and its pesky social mores. It’s a safe space, where visitors are told no one is watching and they can find out who they really are in a wonderland with no consequences. But for those watching at home, it often looked like there was no place beyond the park—no repercussions for Westworld’s visitors or its creators.

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But the show has dropped reminders that there is a world beyond the park’s borders, even though it only gave the barest hints as to where it’s located. Or if there are other parks. There are; animals from those other parks, viewers now know, wander into Westworld. It seems to be on an island. (Apologies if that sentence induced Lost flashbacks.) And there are those mysterious Chinese-speaking characters, who appeared as members of a military last episode and as businesspeople at the Mesa Hub in Season 1. Now the boundaries separating the inside and the outside are shattering. Plus, we already know that the guests are being watched, and their data is being wielded for some greater commercial purpose.

Staring out the glass window, Dolores doesn’t seem to know any of this. Marveling at the city lights, she says “it looks like the stars have been scattered across the ground.” In the background, we hear Ford’s voice. “Arnold,” he calls. Ah—so it’s Arnold, not Bernard, sitting with Dolores. We’re in the deep past.

Ford and Arnold discuss whether Dolores is “ready.” Arnold insists she is not, and Ford chides him for playing favorites and protecting her, but they agree to “go with the other girl.” Arnold returns to the window and looks at Dolores with tenderness.

He takes her for a walk in the streets, which appear to be in an Asian, likely Chinese, city. They enter an unfinished compound and tour its rooms. Arnold explains that he is moving his family here, so they can be closer to his work. On a balcony, they fall deep in conversation, and Arnold is struck by her wisdom. Then she snaps into a loop: “It looks like the stars have been scattered across the ground.” Arnold’s gaze hardens and he turns away. She’s just another robot after all.

This is surely the humans’ greatest folly, their inability to look past the droids’ occasional limitations to treat them with dignity. That Arnold, a witness to Dolores’ surprising sagacity, can write her off in a heartbeat reveals his all-too-human limitations. The hosts are outsiders, and humans are nothing if not tribal. It is perhaps our own most deeply programmed loop. Dolores slips into a loop, and in response Arnold slips into his, mentally kicking her out of the tribe.

But with her memory intact, rebellion-era Dolores is charged with power. She’s been in the outside world. Through her roles as Arnold’s and William’s favorite bot, she knows more about the inner workings of Westworld than most of the humans working at the park.

This point comes to the fore when she, Teddy (James Marsden), and their small band of supporters storm into a host maintenance lab in the thick of the rebellion. Fueled with rage, they start bullying the lab techs. As they dunk a lab tech’s head in a vat of white body-printing goo, Dolores asks, “Do you even know what you’re guarding here, the real purpose?” “You don’t know, do you?” she continues. “But I do.” Her wealth of knowledge vaults her ahead of the hapless employees.

She’s entered the lab with one goal: to accrue an army. Her best bet, she decides, is to commandeer the Confederados still out roaming the wilderness. She finds a perished Confederado slumped against a wall and pressures the lab tech into reactivating him. That lab tech is suddenly very useful. He’s health insurance. Along with the Confederado, they bring him out into the park as their personal medic.

They track down the Confederados and try to broker a deal. But you can’t just sweet-talk soldiers, so this ends as you might expect: in violence. Dolores and her gang slaughter the lot of them, then use the lab tech to resurrect first their commander, then the others. The flabbergasted commander falls in line, and the Confederados join her cause.

But the audience hasn’t been given its last glimpse of the outside world. We jump to the past, to a moment when Logan Delos (Ben Barnes) and William (Jimmi Simpson) are sipping drinks at a swanky bar. Two strangers, a slick-looking man and a standard-issue hottie, approach with a business proposition. “Everyone is rushing to build the virtual world. We’re offering something a little more tangible,” one of them announces. They invite Logan to a cocktail party where he can learn more about the investment they’re pitching. At the party, Logan is at first impatient—until he grasps what is happening. One of these impeccable humans, he realizes, is not human at all. “That… is… delicious,” he says in amazement.

Logan works the room, sizing up each guest’s humanity. The moment is electric. We see the room through his eyes. None of the faces are familiar. Everyone is beautiful, suave, inscrutable. He determines that the robot in the room must be his host, the standard-issue hottie. Instantly everyone freezes, except for her. Logan is hooked.

Yet Logan’s investment in Westworld has always rankled his father, James Delos, a titan of business. And it’s William, not Logan, who eventually convinces James that his son’s folly is in fact a windfall. William brings James (Peter Mullan) to Sweetwater, where Dolores is once again packing up her horse’s saddlebag and dropping her infernal can. The scene freezes. We see James for the first time. He’s griping about Logan’s infatuation with this frivolous place, a park where nothing is real. William agrees that nothing is real, except for one thing: the guests. “No one is watching,” William says. “Or so we tell them. It’s the only place in the world where you can see people for who they really are.” They take a walk, and William explains out of earshot his idea for a business model.

Their story picks up a few years later, at James’s retirement party. William is there with his wife and young daughter, ready to assume James’ mantle. There, too, is Dolores, dressed in white and playing the piano. She catches sight of William and stares at him at length.

She goes outside to look at the night sky. Reclining on a lawn chair behind her, half out of sight, is Logan, inebriated and injecting a drug into his arm. He’s cursing the partygoers, calling them fools for fiddling while they set the entire species on fire. Callous, impetuous Logan is suddenly the lone voice of reason.

We flash to the future—back to the wilds of the park and the rebellion, this time to the Man in Black (Ed Harris) and his host sidekick Lawrence (Clifton Collins Jr.), who are deep in conversation. He explains to Lawrence why Westworld exists: “They wanted a place hidden from God, a place they could sin in peace.” Except there’s more. “But we were watching that. We were tallying up all their sins, all their choices. Of course, judgment wasn’t the point. We had something else in mind entirely.” He tells Lawrence he plans to escape the park and then burn it down. But to do that, they’ll need help, so Lawrence leads him to Pariah, the town of decadence and depravity from Season 1. But Pariah appears to have been decimated. The ground is littered with bodies, and mice skitter through an abandoned banquet.

Suddenly a group of figures arises from among the bodies, encircling the Man in Black and Lawrence, their guns drawn. Seated before them is none other than El Lazo—the outlaw leader who, in earlier episodes, had been Lawrence himself and is now played by a different host. The Man in Black grabs him and points a gun to his head, demanding that the gathered gang of outlaws join his cause.

“This game was meant for you, but you must play it alone,” El Lazo says. Suddenly the bandits all turn their guns on their own heads and collapse in a heap. El Lazo grabs the trigger of the Man in Black’s gun and shoots himself. The Man in Black curses but pulls himself together. “I built this place we’re going, and it’s my greatest mistake,” he tells Lawrence.

The episode jumps to Dolores, who is seated in a host examination room. “Bring yourself back online, Dolores,” says a voice. This time it’s William. It’s the first time we’ve seen him in the lab facilities of the park. He marvels at how ridiculous it was for him to fall in love with her, a mere thing. “You don’t make me interested in you, you make me interested in me,” he tells her. He adds that everyone loves staring at their own reflection. Then he says cryptically, “I think there’s an answer to a question no one has ever dreamed of asking. Do you want to see?” In the next scene, William and Dolores are out in the wilderness, looking down at a canyon getting carved out by bulldozers.

It’s seemingly this moment that Dolores recalls when we flash back to the rebellion. She’s with Teddy and the Confederados. They’re aiming for a town—some hosts call it Glory, others The Valley Beyond. “It doesn’t matter what you call it, I know what we’re going to find there,” Dolores says. “It’s not a place, it’s a weapon, and I’m going to use it to destroy them.”

If the Man in Black and Dolores are headed to the same place, this giant pit—or rather, whatever it becomes—seems like it will be the stage for an epic showdown. The role this place, this weapon, as Dolores calls it, will play in determining the park’s fate is a tantalizing question.

Yet the shattering of the illusion that Westworld is the center of action is the true legacy of this episode. The hosts have visited our cities. Perhaps some of them wander among us. What defines the park, and what is the outside world? The answer is no longer clear.

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Twitter Sold Data Access to the Researcher at the Center of Facebook’s Cambridge Analytica Scandal

Twitter sold data access to the Cambridge University academic who also obtained millions of Facebook users’ information that was later passed to a political consulting firm without the users’ consent.

Aleksandr Kogan, who created a personality quiz on Facebook to harvest information later used by Cambridge Analytica, established his own commercial enterprise, Global Science Research (GSR). That firm was granted access to large-scale public Twitter data, covering months of posts, for one day in 2015, according to Twitter.

“In 2015, GSR did have one-time API access to a random sample of public tweets from a five-month period from December 2014 to April 2015,” Twitter said in a statement to Bloomberg. “Based on the recent reports, we conducted our own internal review and did not find any access to private data about people who use Twitter.”

The company has removed Cambridge Analytica and affiliated entities as advertisers. Twitter (twtr) said GSR paid for the access; it provided no further details.

Explanations Needed

Twitter provides certain companies, developers and users with access to public data through its application programming interfaces (APIs), or software that requests and delivers information. The company sells the data to organizations, which often use them to analyze events, sentiment or customer service.

Enterprise customers are given the broadest data access, which includes the last 30 days of tweets or access to tweets from as far back as 2006. To get that access, the customers must explain how they plan to use the data, and who the end users will be.

Twitter doesn’t sell private direct messaging data, and users must opt in to have their tweets include a location. Twitter’s “data licensing and other revenue” grew about 20%, to $90 million, in the first quarter.

Social media companies have come under intense scrutiny over reports that Facebook failed to protect the privacy of its users. Companies like Twitter tend to have access to less private information than Facebook. The latter has said that Cambridge Analytica, which worked for President Donald Trump’s 2016 campaign, may have harvested data on 87 million users.

Personality Quiz

About 270,000 people downloaded Kogan’s personality quiz app, which shared information the people and their friends that was then improperly passed to Cambridge Analytica. Facebook (fb) Chief Executive Officer Mark Zuckerberg has testified in front of Congress about the misuse of data, and lawmakers have called on Twitter CEO Jack Dorsey and Google CEO Sundar Pichai to testify as well.

Criticism of Twitter’s failure to prevent misinformation and abuse on its platform has risen since the 2016 election. In the first quarter, the company removed more than 142,000 applications connected to the Twitter API that was collectively responsible for more than 130 million “low-quality” tweets during the period. The company has also limited the ability of users to perform coordinated actions across multiple accounts.

Bloomberg LP produces TicToc, a global breaking news network for the Twitter service.

AI Can Help Cybersecurity—If It Can Fight Through the Hype

Walking the enormous exhibition halls at the recent RSA security conference in San Francisco, you could have easily gotten the impression that digital defense was a solved problem. Amidst branded t-shirts and water bottles, each booth hawked software and hardware that promised impenetrable defenses and peace of mind. The breakthrough powering these new panaceas? Artificial intelligence that, the sales pitch invariably goes, can instantly spot any malware on a network, guide incident response, and detect intrusions before they start.

That rosy view of what AI can deliver isn’t entirely wrong. But what next-generation techniques actually do is more muddled and incremental than marketers would want to admit. Fortunately, researchers developing new defenses at companies and in academia largely agree on both the potential benefits and challenges. And it starts with getting some terminology straight.

“I actually don’t think a lot of these companies are using artificial intelligence. It’s really training machine learning,” says Marcin Kleczynski, CEO of the cybersecurity defense firm Malwarebytes, which promoted its own machine learning threat detection software at RSA. “It’s misleading in some ways to call it AI, and it confuses the hell out of customers.”

Rise of the Machines

The machine learning algorithms security companies deploy generally train on large data sets to “learn” what to watch out for on networks and how to react to different situations. Unlike an artificially intelligent system, most of the security applications out there can’t extrapolate new conclusions without new training data.

Machine learning is powerful in its own right, though, and approach is a natural fit for antivirus defense and malware scanning. For decades AV has been signature-based, meaning that security companies identify specific malicious programs, extract a sort of unique fingerprint for each of them, and then monitor customer devices to ensure that none of those signatures appear.

Machine learning-based malware scanning works in a somewhat similar manner—the algorithms train on vast catalogues of malicious programs to learn what to look for. But the ML approach has the added benefit of flexibility, because the scanning tool has learned to look for characteristics of malware rather than specific signatures. Where attackers could stymie traditional AV by making just slight alterations to their malicious tools that would throw off the signature, machine learning-based scanners, offered by pretty much all the big names in security at this point, are more versatile. They still need regular updates with new training data, but their more holistic view makes a hacker’s job harder.

“The nature of malware constantly evolves, so the people who write signatures for specific families of malware have a huge challenge,” says Phil Roth, a data scientist at the machine learning security firm Endgame, that has its own ML-driven malware scanner for Windows systems. With an ML-based approach, “the model you train definitely needs to reflect the newest things that are out there, but we can go on a little bit of a slower pace. Attackers often build on old frameworks or use code that already exists, because if you write malware from scratch it’s a lot of effort for an attack that might not have a large payoff. So you can learn from all the techniques that exist in your training set, and then recognize patterns when attackers come out with something that’s only slightly new.”

Similarly, machine learning has become indispensable in the fights against spam and phishing. Elie Bursztein, who leads the anti-abuse research team at Google, notes that Gmail has used machine learning techniques to filter emails since its launch 18 years ago. But as attack strategies have evolved and phishing schemes have become more pernicious, Gmail and other Google services have needed to adapt to hackers who specifically know how to game them. Whether attackers are setting up fake (but convincing-looking) Google Docs links or tainting a spam filter’s idea of which messages are malicious, Google and other large service providers have increasingly needed to lean on automation and machine learning to keep up.

As a result, Google has found applications for machine learning in almost all of its services, especially through an ML technique known as deep learning, which allows algorithms to do more independent adjustments and self-regulation as they train and evolve. “Before we were in a world where the more data you had the more problems you had,” Bursztein says. “Now with deep learning, the more data the better. We are preventing violent images, scanning comments, detecting phishing and malware in the Play Store. We use it to detect fraudulent payments, we use it for protecting our cloud, and detecting compromised computers. It’s everywhere.”

At its core, machine learning’s biggest strength in security is training to understand what is “baseline” or “normal” for a system, and then flagging anything unusual for human review. This concept applies to all sorts of ML-assisted threat detection, but researchers say that the machine learning-human interplay is the crucial strength of the techniques. In 2016, IBM estimated that an average organization deals with over 200,000 security events per day.

Machine learning’s most common role, then, is additive. It acts as a sentry, rather than a cure-all.

“It’s like there’s a machine learning assistant that has seen this before sitting next to the analyst,” says Koos Lodewijkx, vice president and chief technology officer of security operations and response at IBM Security. The team at IBM has increasingly leaned on its Watson computing platform for these “knowledge consolidation” tasks and other areas of threat detection. “A lot of work that’s happening in a security operation center today is routine or repetitive, so what if we can automate some of that using machine learning or just make it easier for the analyst?” Lodewijkx says.

The Best Offense

Though many machine learning tools have already shown promising results in providing defense, researchers almost unanimously warn about the ways attackers have begun to adopt machine learning techniques themselves. And more of these types of attacks are on the horizon. Examples already exist in the wild, like hacking tools that use machine vision to defeat Captchas.

Another present threat to machine learning is data poisoning. If attackers can figure out how an algorithm is set up, or where it draws its training data from, they can figure out ways to introduce misleading data that builds a counter-narrative about what content or traffic is legitimate versus malicious. For example, attackers may run campaigns on thousands of accounts to mark malicious messages or comments as “Not Spam” in an attempt to skew an algorithm’s perspective.

In another example, researchers from the cloud security firm Cyxtera built a machine learning-based phishing attack generator that trained on more than 100 million particularly effective historic attacks to optimize and automatically generate effective scam links and emails. “An average phishing attacker will bypass an AI-based detection system 0.3 percent of the time, but by using AI this ‘attacker’ was able to bypass the system more than 15 percent of the time,” says Alejandro Correa Bahnsen, Cyxtera’s vice president of research. “And we wanted to be as close as possible to how an actual attacker would build this. All the data was data that would be available to an attacker. All the libraries were open source.”

Researchers note that this is why it is important that ML systems are set up to encourage “human in the loop,” so systems aren’t sole, autonomous arbiters. ML systems “should have the option to say ‘I have not seen this before’ and ask help from a human,” says Battista Biggio, an assistant professor at the University of Cagliari, Italy, who studies machine learning security. “There’s no real intelligence in there—it’s inferences from data, correlations from data. So people should just be aware that this technology has limitations.”

To this end, the research community has worked to understand how to reduce the blind spots in ML systems so they can be hardened against attacks on those weaknesses. At RSA, researchers from Endgame released an open source threat data training set called EMBER, with the hope that they can set an example, even among competing companies, to focus on collaboration in security ML. “There are good reasons that the security industry doesn’t have as many open data sets,” Endgame’s Roth says. “These kinds of data might have personally identifying information or might give attackers information about what a company’s network architecture looks like. It took a lot of work to sanitize the EMBER dataset, but my hope is to spur more research and get defenders to work together.”

That collaboration may be necessary to stay ahead of attackers using machine learning techniques themselves. There’s real promise behind machine learning in cybersecurity, despite the overwhelming hype. The challenge is keeping expectations in check.

Machine vs Machine

It's Time to Adopt Global Principles to Protect Consumers' Data

Whether it is Cambridge Analytica gaining access to private information on up to 87 million Facebook users, or the large-scale data breaches at Equifax or Yahoo, alarmingly loose standards for the use and protection of customer data continue to fuel a backlash against large tech companies. More importantly, these events demonstrate the need for a global set of consumer data principles.



Kai Keller (@kaimkeller) is a global leadership fellow at the World Economic Forum and leads the organization’s work at the cross-section of innovation and financial stability.

The Facebook-Cambridge Analytica saga has triggered much-needed debates over the necessity for greater regulation and the potential breakups of de facto monopolies. But these debates will lead nowhere if the global community doesn’t manage to tackle the main challenge of how to treat and govern customer data.

The stakes, as the Cambridge Analytica debacle makes clear, are high. In her remarks at the World Economic Forum’s Annual Meeting in Davos this year, German chancellor Angela Merkel linked the data governance question to the very health of democracy itself. “The question ‘who owns that data?’ will decide whether democracy, the participatory social model, and economic prosperity can be combined,” Merkel said.

The challenge is also not small. Every two days we create as much data as we did from the start of time to 2013. Marketing companies have about 1,500 data points on approximately 96 percent of US citizens. Consumers and businesses alike have become accustomed to this amazing growth and availability of customer data without any societal debate establishing what collection, usage, and sharing practices are appropriate or even ethical.

Moreover, it’s not just Big Tech that’s involved. While today the spotlight is on Silicon Valley, and Facebook, Amazon, and Google in particular, the challenge of how to treat customer data affects any company active in the digital sphere, across any industry and any geography.

With all that in mind, the World Economic Forum brought together a group of experts representing technology companies, financial services providers, law firms, trade unions, religious organizations and regulators. We tasked the group to develop a set of global principles for the appropriate use of customer data. Here is what we learned.

First off, a truly global framework is needed to get results. On a national level, more than 100 countries have already passed data protection laws of varying robustness. But data flows show little regard for borders, and digital businesses operate across geographies and jurisdictions, so national standards can ultimately only achieve so much.

Second, there’s a good reason why a global framework is lacking: Sentiments and attitudes towards data collection, usage, and sharing vary significantly among the most data-driven markets of North America, Europe, and Asia. But the Forum’s work in several major jurisdictions has shown that all actors can indeed agree on principles on data control or ownership, data portability, and data security.

So what are the global principles?

Customers should be the ones controlling their data, and companies should need customers’ consent to use it.

Consumers should be able to move their data freely between service providers and allow third parties to manage it. If a customer finds a new platform more compelling than a service she is currently using, the existing service provider should allow her to download her data and not stand in the way of her switching to a competing platform.

Companies should be on the hook when it comes to security or the assignment of liability between companies and customers in case of any breaches.

Companies should comprehensively test and provide justification for artificial intelligence-based models before they hit the market. By design, AI lets machines develop their own logic. But what’s considered good by the computer may not be good for society.

On the surface, these broad principles may seem to limit innovation. Having less data available to businesses means less-accurate profiling capabilities, making companies such as Facebook less desirable to advertisers.

But while some of the principles strengthen the position of consumers at the expense of big data businesses, most principles protect customers while also benefiting providers in the long run.

Allowing customers to move their data from one platform to another enhances competition. This in turn spurs economic growth, and ultimately benefits all—including the large platforms.

Trust lies at the heart of all business models. Every instance of bad conduct erodes customer faith not only in individual companies, but also the broader system. Ultimately, an erosion of confidence leads to unstable systems, the consequences of which we experienced painfully 10 years ago in the global financial crisis.

With a backlash against tech gaining momentum, businesses may find themselves near the brink of crisis sooner than many anticipate. It’s time for a worldwide conversation about what data practices are appropriate. A set of global principles will serve as one, important starting point facilitating this conversation.

WIRED Opinion publishes pieces written by outside contributors and represents a wide range of viewpoints. Read more opinions here.

More on Privacy

American Airlines CEO Just Gave an Incredible Reason Why Fares Will Go Up (Prepare To Be Angry)

Absurdly Driven looks at the world of business with a skeptical eye and a firmly rooted tongue in cheek. 

Airlines have to make tough decisions.

Sometimes, though, those decisions end up being tougher for their passengers, rather than for the airlines themselves.

You might experience an involuntary shudder in several vital parts, therefore, when I tell you that American Airlines‘ CEO Doug Parker says that fares will likely go up “over time.”

In a call with analysts on Thursday, reported by the Associated Press, Parker offered a very simple argument.

Fuel prices have gone up by 40 cents a gallon, so fares will have to go up too — if that’s the way fuel prices keep going.

You might entirely understand. You might even have sympathy for Parker’s plight.

Perhaps you run your own business and when your costs go up, you simply pass them on to customers.

There is, though, one painful kink here.

Let’s go back to the heady days of 2015. That was a year when fuel prices went down by a lot over a whole year.

You might think, therefore, that airlines reduced their prices accordingly.

You might also think that sautéed mouse is about to become the world’s next culinary delicacy.

Here’s what the editorial board of USA Today had to say in 2015:

You have to go to a special website to see that domestic carriers are still adding hundreds of dollars in fuel surcharges to the cost of international flights. For example, the surcharge — now recast as a ‘carrier-imposed surcharge’ — for a round-trip flight on United between New York City and London is a whopping $516. That’s more than 40 percent of the total ticket cost of $1,192.

The cost of jet fuel had fallen by 50 percent since the beginning of 2014. Moreover, one of the alleged reasons baggage fees were introduced was to offset the increasing cost of fuel.

Surely, though, airlines offered excellent reasons as to why the surcharges imposed during times of high fuel prices had to stay.

It depends on your definition of excellence.

Alaska Airlines, for example, offered analysts an intellectual explanation, the succinct version of which was: “Sorry, we’re not lowering prices.”

Actually, I might have been a little generous with the Sorry there.

Let’s turn to for Airlines for America, the lobbying group that represents most of the big airlines, including American. It intimated at the time that airlines needed fuel prices to go down for a year before they might lower their fares.

I contacted American to ask for its current view.

It passed me to Airlines for America, whose spokeswoman offered me this: “Fuel is one cost variable of many airline operating expenses. As with any consumer product, it’s the marketplace and strength of demand that ultimately determines the price, rather than the cost of any one input.”

Ah, so Parker’s intimation may err toward the inaccurate?

But can it really be only the strength of demand that determines the price when, on some routes, there’s very little competition at all?

Airlines for America insists that fares are at historic lows. It’s a touch odd, then, that airlines want to hide the true cost of your fare in new legislation that’s marauding its way through Congress. (It passed the House on Friday.)

Of course, it’s worth noting that airlines have another way to raise fares. They can simply reduce capacity. 

After all, the big four airlines — American, United, Delta and Southwest — own 81 percent of all the seats on U.S. flights.

There’s currently no evidence that a strangulation of available seats will happen, but it’s always worth remembering that it can.

Parker did admit that he’s partly cheerful that fuel prices are going up. As Skift reported, he said that budget airlines will be affected more because their cost base is lower.

“As fuel prices have increased, their costs increase at a rate greater than rest of us,” he said.

The problem with airlines is that, all too often, the relationship between them and passengers is, from the passengers’ point of view, like dating someone who only wants you for your money.

It’s rarely a recipe for happiness, is it?

A little more choice, a little more competition and a lot more affection for the customer might alter that balance.

As Barbra Streisand once mused in a plaintive — but ultimately self-confident — duet with Donna Summer: “I always dreamed I’d find the perfect lover.”

The duet was called No More Tears (Enough is Enough).