Tag Archives: Business

The US Again Has Worlds Most Powerful Supercomputer

Plenty of people around the world got new gadgets Friday, but one in Eastern Tennessee stands out. Summit, a new supercomputer unveiled at Oak Ridge National Lab is, unofficially for now, the most powerful calculating machine on the planet. It was designed in part to scale up the artificial intelligence techniques that power some of the recent tricks in your smartphone.

America hasn’t possessed the world’s most powerful supercomputer since June 2013, when a Chinese machine first claimed the title. Summit is expected to end that run when the official ranking of supercomputers, from an organization called Top500, is updated later this month.

Supercomputers have lost some of their allure in the era of cloud computing and humongous data centers. But many thorny computational problems require the giant machines. A US government report last year said the nation should invest more in supercomputing, to keep pace with China on defense projects such as nuclear weapons and hypersonic aircraft, and commercial innovations in aerospace, oil discovery, and pharmaceuticals.

Summit, built by IBM, occupies floor space equivalent to two tennis courts, and slurps 4,000 gallons of water a minute around a circulatory system to cool its 37,000 processors. Oak Ridge says its new baby can deliver a peak performance of 200 quadrillion calculations per second (that’s 200 followed by 15 zeros) using a standard measure used to rate supercomputers, or 200 petaflops. That’s about a million times faster than a typical laptop, and nearly twice the peak performance of China’s top-ranking Sunway TaihuLight.

The view inside one of the Summit supercomputer’s 4,608 servers.

Oak Ridge National Laboratory

During early testing, researchers at Oak Ridge used Summit to perform more than a quintillion calculations per second in a project analyzing variation between human genome sequences. They claim that's the first time a scientific calculation has reached that computational scale.

America’s new best computer is significant for more than just the geopolitics of computational brawn. It’s designed to be more suited than previous supercomputers to running the machine learning techniques popular with tech companies such as Google and Apple.

One reason computers have lately got much better at recognizing our voices and beating us at board games is that researchers discovered that graphics chips could put more power behind an old machine learning technique known as deep neural networks. Facebook recently disclosed that a single AI experiment using billions of Instagram photos occupied hundreds of graphics chips for almost a month.

Summit has nearly 28,000 graphics processors made by Nvidia, alongside more than 9,000 conventional processors from IBM. Such heavy use of graphic chips is unusual for a supercomputer, and it should enable breakthroughs in deploying machine learning on tough scientific problems, says Thomas Zacharia, director of Oak Ridge National Lab. “We set out to build the world’s most powerful supercomputer,” he says, “but it's also the world’s smartest supercomputer.”

Summit’s thousands of servers could fill two tennis courts.

Carlos Jones/Oak Ridge National Laboratory

Eliu Huerta, a researcher at the National Center for Supercomputing Applications, at the University of Illinois at Urbana-Champaign, describes Summit’s giant GPU pool as “like a dreamland.” Huerta previously used machine learning on a supercomputer called Blue Waters to detect signs of gravitational waves in data from the LIGO observatory that won its founders the 2017 Nobel Prize in physics. He hopes Summit’s might will help analyze the roughly 15 terabytes of imagery expected to arrive each night from the Large Synoptic Survey Telescope, due to switch on in 2019.

Summit will also be used to apply deep learning to problems in chemistry and biology. Zacharia says it could contribute to an Energy Department project using medical records from 22 million veterans, about a quarter-million of which include full genome sequences.

Some people worried about US competitiveness in oversized calculating machines hope that the hoopla around Summit will inspire more interest in building its successors.

The US, China, Japan, and the European Union have all declared the first “exascale” computer—with more than 1,000 petaflops of computing power—as the next big milestone in large-scale computing. China claims it will achieve that milestone by 2020, says Stephen Ezell, vice president for global innovation policy at the Information Technology and Innovation Foundation. The US may get there in 2021 if Summit’s successor, known as Aurora, is completed on schedule, but the program has previously had delays.

The Trump administration’s budget this spring asked for $376 million in extra funding to help meet the 2021 target. It’s now up to the nation’s legislators to approve it. “High-performance computing is absolutely essential for a country’s national security, economic competitiveness, and ability to take on scientific challenges,” Ezell says.

More Great WIRED Stories

Read more: https://www.wired.com/story/the-us-again-has-worlds-most-powerful-supercomputer/

If Trump Is Laundering Russian Money, Heres How It Works

For Donald Trump, there was the purchase of the $12.6 million Scottish estate and the $79.7 million for golf courses in the United Kingdom, not to mention the $16.2 million for the Northern Virginia Winery. All in cash.

For Michael Cohen, it was the lucrative day in 2014 when he sold four Manhattan buildings for $32 million—three times what he’d paid for them less than three years before.

Recent days have been filled with a seeming tidal wave of fresh revelations from the spiraling investigation around Donald Trump’s ties to Russia, particularly around suspicious financial transactions involving Trump fixer Michael Cohen, who appears to have used the same shell company LLC to pay hush money to porn star Stormy Daniels, collect six- and seven-figure consulting deals from companies like AT&T and Novartis, and receive payments from a company with close ties to oligarch Viktor Vekselberg.

The subtext of many of the recent tales—from Donald Trump’s massive cash-spending spree to Cohen’s $32 million flip of New York real estate—is that the atypical transactions are worthy of greater scrutiny. After all, why was the self-proclaimed “King of Debt” suddenly waist-deep in cash and on a spending spree in the midst of the global real estate crash? Where was Cohen’s money coming from—and where was it going?

It’s the old adage from the Watergate investigation: “Follow the money.”

The implication, particularly in the more fever-swampy portions of Twitter, is that there was money laundering afoot—probably Russian in origin. The “quid” perhaps, before the election and the “pro quo” afterward. But is that a real possibility—and if it was money laundering, by whom and how?

The payments appear to mirror suspicious activity that led to the earliest charges and investigative avenues of special counsel Robert Mueller’s probe, the money laundering and conspiracy charges leveled against former Trump campaign chair Paul Manafort and aide Rick Gates. (Gates has since pleaded guilty; Manafort’s case continues to move forward toward trial later this year.)

But to Treasury officials and law enforcement who have long pursued money laundering and terrorist financing probes, it’s not what Donald Trump or Michael Cohen did in any single transaction that raises red flags—it’s how they conducted business day in and day out. The layers of shell companies, the contracts involving pseudonyms, the law firm cut-outs to make deals.

"Many of the activities, when viewed in aggregate, point to a deliberate attempt to create opacity,” says Amit Sharma, who used to work on countering terrorist financing after 9/11 at the Treasury Department. “When you take two steps back, you see a murkiness and level of complexity with which the Cohen and Trump companies have operated—what are they hiding? Why are secondary and tertiary entities signing under pseudonyms and ‘cover' names? Truly legitimate, transparent companies don’t need to do that. Does this point to corruption and/or conspiracy? It certainly looks that way! Are all activities pointing to specific money laundering transactions? Not necessarily.”

The fundamental approach to Trump and Cohen’s empires should raise eyebrows—and evidently has with Mueller’s probe and prosecutors in the Southern District of New York—precisely because of the apparently great lengths they undertook to evade basic transparency. While not necessarily illegal—some of the tactics are, in fact, regular parts of complex businesses—the pattern of activity points to an attempt to evade one of the basic precepts of modern banking and anti-money-laundering efforts: Know your customer.

“What we call ‘covered institutions,’ that’s any financial institution overseen by US financial regulations, they have to have a comprehensive anti-money-laundering regime. It basically come down to one central question: Do you know your customer? Who’s behind the account, who has control over an entity or can facilitate transactions on its behalf, what are its sources of funds, and what is the normal, expected nature of its business or pattern of activity for that person or entity?" Sharma says. “Anytime a bank or financial institution spots activity that doesn’t match the regular pattern, they’re required to file suspicious activity reports with the Treasury Department.” (Those exact type of reports were triggered by odd withdrawals and payments by the Russian embassy around the time of the US election, and are the subject of part of Mueller’s probe, according to Buzzfeed.)

Yet while regulations—especially since 9/11—require in-depth documentation and identification for basic banking for individuals, it has been much easier—until literally today—for corporate entities to hide their identities behind lawyers and shell companies. “Financial institutions are mandated to collect all this data on its customers, but up until now, financial institutions have not had to do the same for companies,” Sharma says. “For companies, often it has simply been the business location and Tax ID number and we don’t know the underlying ownership. We don’t know whether it’s a Russian oligarch.” (In fact, new Treasury Department rules that require stronger due diligence on banks to understand who actually owns—or has a controlling interest in—a company only come into effect today, May 11, 2018.)

As Sharma says, “Trump and his companies have exercised this practice for many years—it seems that every new project, every product, every new building, he’s starting a new company or legal entity to manage it. This has been the case for overseas operations and activities as well. People do this to protect themselves from liability and to create protective measures that don’t roll directly up to them personally. In any given structure, he may own a portion of a parent company that owns a controlling interest in a holding company that may own a portion or receive economic benefits of the real estate.”

In 2016 The Wall Street Journal's Jean Eaglesham, Mark Maremont, and Lisa Schwartz outlined a specific example of just that sort of structure: “Donald Trump owns a helicopter in Scotland. To be more precise, he has a revocable trust that owns 99 percent of a Delaware limited liability company that owns 99 percent of another Delaware LLC that owns a Scottish limited company that owns another Scottish company that owns the 26-year-old Sikorsky S-76B helicopter, emblazoned with a red ‘TRUMP’ on the side of its fuselage.” All told, the Journal reported, 15 entities were used at that point to “own” Trump’s fleet of two airplanes and three helicopters.

Layer on layer of corporate structure makes it hard for investigators, tax officials, or prying lawyers to figure out who owns what, the underlying source of money for specific transactions, whether taxes are being appropriately paid in a given jurisdiction, or who might be partners in what enterprises.

That’s where “Section 311” comes in.

In 2001, as part of the USA Patriot Act, the Treasury Department was given a new tool against money laundering, known as “Section 311,” after the relevant section of the law, to designate foreign financial institutions, jurisdictions, or entities as “of primary money laundering concern.”

A Section 311 designation was meant to help authorities highlight suspicious patterns of activity without having to prove any single transaction was illegal—it’s the rough equivalent for money laundering of the criminal RICO statute, the Racketeer Influenced and Corrupt Organizations Act, that allows prosecutors to take down entire mafia families, drug cartels, and street gangs without having to prove everyone involved knew about or participated in all the various individual crimes.

“We deliberately put these tools together to go after really bad people—organized crime, terrorists, dictators, Chinese Triads,” Sharma says. “You didn’t have to point to a single illegal transaction. The totality of the transactions should give you pause enough that we would want to be sure US institutions scaled back or ceased doing business with them.”

The designation, which effectively forces US financial institutions to sever ties with the entity, makes it all but impossible for an entity to participate in the global financial system. In the years since, the US Treasury Department has used Section 311 to go after the banks and front companies that help North Korea evade sanctions, to go after Iran’s nuclear program and terrorism financing, to isolate Syria, to punish banks that helped Saddam Hussein launder money, and to pressure off-shore havens, like the Pacific island of Nauru, that the US believes are complicit in money laundering.

Sharma says that if what we have seen with Michael Cohen’s business dealings existed anywhere overseas, where it intersected with an investigation or a politically exposed person or national security issue of import to the US, it would ring all sorts of alarm bells at Treasury. What seems to be continually revealed is a pattern of atypical financial transactions, and too much of it seems structured specifically to hide and evade critical information or people involved.

That desire for opacity, though, doesn’t necessarily point to money laundering. A specific charge of “money laundering” requires that the initial funds be traced to a so-called “predicate,” a recognized serious crime. “It could be fraud, smuggling, selling high technology, proceeds of child pornography. There are hundreds of predicate crimes in the United States; the global standard is ‘all serious crimes,’” explains former Treasury agent John Cassara. The complexity of tracing money all the way through the financial system, from a legitimate asset back to a crime, or vice versa, makes these cases some of the most challenging investigators undertake. “These are very, very difficult cases—it takes a lot for the investigators, the prosecutors, the US attorney to understand,” Cassara says.

Part of the reason the cases are so tough is that there are plenty of other, nonillegal reasons wealthy people create opacity, including to minimize taxes, to limit personal or corporate legal liability, or to shield assets in divorce proceedings.

The truth of the matter is that the global financial system is simply too large for officials to look at very closely.

Money laundering is a huge—literally physically huge—problem: Illicit drug sales in the United States alone are estimated at around $60 billion to $100 billion a year, which translates, Cassara says, into about 20 million physical pounds of currency, far too much to be moved easily or spent easily. “The bad guys have a logistics issue. They want to try to get into a bank or nonbank financial institution, so they can spend it,” he says.

Globally, the International Monetary Fund estimates that between 2 and 5 percent of the world’s gross domestic product is laundered money from illicit activity. “The number I normally use is the total is in the range of $4 trillion to $5 trillion, about the amount of the entire federal government budget,” says Cassara, who spent 26 years investigating such cases and has written multiple textbooks on anti-money-laundering efforts.

Given that scale, the hard work of thousands of investigators and tax officials the world over amounts to a drop in the proverbial bucket; authorities only seize or charge about 1 percent of suspected money laundering cases. “By any measurement, we do a terrible job of enforcing this,” Cassara says. “I have the utmost respect for my colleagues, but if you just compare the bottom line with the results, as [financial crime expert] Raymond Baker used to say, total failure is just a decimal point away.”

That shockingly low level of enforcement helps explain how Manafort’s scheme—which Mueller’s team says involved more than $18 million, funneled through entities that included oriental rug shops just a few miles from the Treasury Department itself—ran undetected and unprosecuted for so long.

Each year, the Treasury Department fields upward of 18 million pieces of financial intelligence, including more than 2 million suspicious activity reports from banks and financial institutions—far more than it can effectively process. Globally, there are 145 foreign financial reporting centers, like the Treasury Department’s so-called FINCEN, its intelligence and enforcement unit, which translates into tens of millions more reports and warnings. It’s relatively easy for even large-scale financial crimes to hide in that mountain of evidence. “Your inbox was always full,” Cassara says.

Today, Cassara says, money launderers have to be incredibly stupid or incredibly unlucky to be caught. “Since 9/11, the amount of financial intelligence has grown exponentially, so bad guys are taking steps to evade those efforts,” Cassara says.

But what’s the point of buying, say, $934,350 in oriental rugs (as Manafort is alleged to have done), or buying luxury condos in London (as Russian oligarchs are said to be fond of)? How exactly do money laundering schemes work?

While it’s easier to grasp how to hide cash at the street level—like in Breaking Bad, when Walter White purchases a cash-intensive car wash and simply cooks the book to show he’s washing more cars than he is—money laundering at the global level follows the same three-step process:

Step 1: Placement

The first challenge is simply getting the money somewhere into the global financial system, which is often easier said than done. Banks are required to file reports anytime someone deposits more than $10,000 in cash, so sneaking large amounts of cash into the financial system can pose a huge challenge. Breaking large transactions into smaller ones, say multiple deposits of $9,999, to evade the transaction reports is known as “structuring” or “smurfing,” and is illegal itself. Former Speaker of the House Dennis Hastert spent time in prison for “structuring,” as part of his effort to pay hush money to one of the men he sexually abused as a high school coach, rather than for the underlying abuse. “Placement is where criminals are most vulnerable, because the money is closest to the original crime,” Cassara says. “It’s much easier to catch them at the crime than to say ‘there’s a suspicious shopping center or golf course’ and work backwards.”

Tracing “laundered” money back to illicit proceeds is key to any investigation.

Step 2: Layering

The second challenge is hiding the origin of the illicit money. That’s where the layers of LLCs can be helpful. Every time money moves—from one entity’s account to another, from one bank to another, from one country to another—it helps hide the original source. “It’s confusing and makes it difficult for investigators, tax officials, or a former wife to follow that money trail. It’s using this labyrinth of LLCs and tax havens, in the US and overseas, to make it difficult and time-consuming to trace,” Cassara says. “It gets hard because of issues of [investigative] competence, venue, jurisdiction.”

Often, this “layering” step takes place with the help of lawyers and law firms; the revelations of the Panama Papers and the follow-on Paradise Papers laid out just how large a global business it is to help elites hide their assets. “Many of these folks have go-to structures and lawyers they use to go through the layering process,” Sharma says. “A lot of laundering happens through nonfinancial businesses and professions.…The Russians use a ton of folks in Turkey, UAE, and Cyprus. That fact pattern is well-known and long-standing.”

While the Panama and Paradise Papers revelations focused primarily on overseas entities and tax havens, the United States is actually one of the worst global offenders: The so-called “Delaware company” structure is notorious for its lax documentation and opacity, as NPR’s Planet Money found out when they set up shell companies in Belize and Delaware in 2012.

Step 3: Integration

Once the money is in the global financial system and its origins properly obfuscated, the final challenge is making the money accessible—that is, integrating it into the legitimate economy. At the high end of money laundering, this often means purchasing real estate.

“Real estate is a big issue for money laundering and has been for a long time,” Cassara says. “If you’ve got a condo or a shopping center or a golf course, the money has already been placed, it’s already been layered, it’s the final stage—integrated. The authorities aren’t going to look at that. Once you see property, in whatever form it is, it’s assumed that’s good, that’s a legitimate investment.”

Large-scale money laundering, like what corrupt regimes or oligarchs need, requires—like any good investment portfolio—a well-balanced portfolio. “If you’ve got that much money, you need diversification,” Cassara says. “You’re going to put so much into gold, so much into stocks, so much into golf courses. By that point, they’re many steps away from illicit proceeds.”

Real estate is particularly attractive for money laundering because of the large numbers involved—a single large transaction to purchase a golf course, a luxury condo, or shopping center is an easy way to make a whole lot of money look legitimate at once without raising any eyebrows with banks or regulators. It’s also a good way to evade so-called “capital controls,” which limit, for instance, the amount of money Chinese citizens can transfer out of the country.

The goal in such efforts isn’t necessarily to have access to immediate cash—sometimes the end goal is simply to own a physical asset. “Parking” illicit gains from corrupt regimes, including Russia or China, in luxury real estate in the West is a common pattern because it historically holds value and, if you’re the buyer, you only trigger taxes by selling, not with the initial transaction. “Real estate tends to hold its value, luxury real estate typically even goes up—it’s a great way to preserve it without losing it,” Sharma says.

Such absentee owners—more interested in parking their assets than actually occupying a residence—has led to the phenomenon of what locals call “lights out London,” entire luxury buildings or wealthy neighborhoods where hardly anyone is ever home. More than 85,000 offshore shell companies own British real estate, and one report last year found nearly $6 billion worth of properties owned by politicians and public officials with “suspicious wealth.”

Similar concerns have been raised about Libyan purchases in Dubai, Chinese purchases in Vancouver, and Russian purchases in Miami, among other cities. It’s such a problem in New York real estate that the Treasury Department is moving to end anonymous all-cash purchases.

And then there’s the oriental rugs. Perhaps the oddest part of the lengthy, detailed indictment of Paul Manafort is the nearly $1 million he evidently funneled through various antique rug shops. As Adam Davidson wrote at The New Yorker last fall, “It’s hard to imagine a person who spends $12 million over six years but only shops at a handful of stores, and nearly always happens to have a bill that ends in multiple zeroes: $107,000, then $20,000, then $250,000. At an unnamed men’s-clothing store in New York, Manafort spent $32,000, $15,000, $24,000, and other multiples of a thousand. For money-laundering experts, this fact alone would be cause for suspicion. It is extremely rare for even a single purchase to end in three zeroes.”

The rugs and clothing appear to be an example of what officials call “trade-based money laundering,” using physical goods to evade currency reporting limits. There are, after all, only three ways to move money around the globe: Through bank transfers, through cash, or through physical trade. “I argue that trade-based money laundering is actually the largest of the three money laundering ideologies but it’s the one we’ve done the least to enforce,” Cassara says. “When a buyer and a seller are working together, the price of an object can be whatever they want it to be—it could be pens, it could be gold, it could be carpets….The reason it’s so effective is that global merchant transactions is in the tens of millions of dollars [a day]. Try to find the suspect transaction in that sea.”

It’s relatively easy for a determined money launderer to falsify invoices, either inflating or deflating price, with the willing cooperation of a commercial partner—like an oriental rug store, where you purchase a rug that’s worth $5,000 for, say, $20,000 and the store owner returns the difference to you in cash. Or buy a rug worth $20,000, and buy it from Shop A for $5,000 and sell it to Shop B for the full price—the difference becomes all clean money. “I sold those rugs to another shop, that cash from Shop B, paid to me, is effectively washed,” Sharma explains.

That so many of the transactions and behaviors of the Trump business empire and Michael Cohen’s empire appear to hew so closely to the well-known patterns and stages of money laundering deeply troubles Sharma.

“It falls into fact patterns that we’ve seen in other areas of Russian and Eastern European organized crime,” he says. “We’re staring at a government—that goes right to the top—that engages in very way of doing business and the exact same fact patterns that we set these tools up to combat. That’s mind-boggling to me.”

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Garrett M. Graff (@vermontgmg) is a contributing editor for WIRED and the author of The Threat Matrix: Inside Robert Mueller's FBI. He can be reached at garrett.graff@gmail.com.

Read more: https://www.wired.com/story/if-trump-is-laundering-russian-money-heres-how-it-works/

This Billionaire Has Put Half His Net Worth Into Gold

  • Egypt’s Sawiris has put half his entire net worth into gold
  • He’s been waiting 10 years for North Korea stakes to pay off

Some big investors see warning signs ahead for markets but are holding their positions. Egyptian billionaire Naguib Sawiris is taking action: He’s put half of his $5.7 billion net worth into gold.

He said in an interview Monday that he believes gold prices will rally further, reaching $1,800 per ounce from just above $1,300 now, while “overvalued” stock markets crash.

“In the end you have China and they will not stop consuming. And people also tend to go to gold during crises and we are full of crises right now,” Sawiris said at his office in Cairo overlooking the Nile. “Look at the Middle East and the rest of the world and Mr. Trump doesn’t help.”

President Donald Trump is aiding Sawiris in one way, though: If a North Korean peace deal can be reached, the Egyptian’s investments there may finally pay off. After 10 years of waiting to repatriate all his profits easily and control his mobile-phone company, Egypt’s second-richest man says an accord would let him reap some of his returns.

“I am taking all the hits, I am being paid in a currency that doesn’t get exchanged very easily, I have put a lot of money and built a hotel and did a lot of good stuff there,” said Sawiris, who founded North Korea’s first telecom operator, Koryolink. The North Korean unit’s costs and revenues aren’t currently recognized on the financial statements of Sawiris’ Orascom Telecom Media & Technology Holding SAE.
Sawiris over the years has been pressured by “every single Western government in the world” for his presence in the country hit by international sanctions for its nuclear threats, he said, but he considered himself a “goodwill investor.” His advice for governments and to Trump ahead of his expected meeting with North Korean Leader Kim Jong Un: Don’t bully him, and promise prosperity in exchange for concessions on nuclear.

A successful meeting between Kim and South Korean President Moon Jae-In last week cleared the way for Trump to meet with the North Korean leader to discuss his nuclear-weapons and ballistic-missile programs. The date and the place haven’t been set. An agreement — elusive for almost seven decades — would open the door for Sawiris to restore his investments there and possibly make new ones.

“I know these North Korean people. They are very proud, they will not yield under threat and bullying. You just smile and talk and sit down and they will come through,” he said.

Sawiris, the son of Onsi Sawiris, who founded Orascom Construction, has built a name by investing in the telecom sector in Egypt and in less popular markets including Iraq, Pakistan, North Korea and Bangladesh. He also bought Italy’s Wind Telecomunicazioni before merging it, along with a number of his telecom assets, with Veon Ltd. in 2011.

Since then Sawiris has diversified into the financial sector by buying out Egyptian investment bank Beltone Financial Holding and attempting to buy CI Capital Holding to create Egypt’s biggest investment bank. His offer was blocked. He also expanded in mining, becoming, with his family, the largest investor in the sector through shareholdings in Evolution Mining, Endeavour Mining Corporation and La Mancha Resources Inc.

Gold and Cash

The largest share of Sawiris's investments includes most of his gold stakes

Source: Bloomberg Billionaires Index

Figures in millions of dollars; based on his stake in La Mancha Resources *Denotes gold companies

“I had to convince my mom in the beginning,” Sawiris said in the interview with Bloomberg Television. “It has been a very good investment for me. I recently sold a portion of my Evolution shares because I want to invest now in Latin America and Eastern Europe.”

He’s from a family of investors. Nassef Sawiris, Naguib’s youngest brother and the richest man in Egypt, is the biggest shareholder and chief executive officer of fertilizer producer OCI NV. He’s also the biggest shareholder in contracting and engineering company Orascom Construction Ltd. He re-based his companies outside Egypt after a tax dispute with the Muslim Brotherhood government in 2013.

Sawiris said his view of Saudi Arabia was negatively impacted by a corruption crackdown that led to the arrest of high-profile princes and billionaires in November. Authorities need to ensure there is rule of law and order and transparency, he said.

Rather, Sawiris is giving investment priority to his homeland after an International Monetary Fund-backed reform program that began in 2016. By lifting all restrictions on the currency and cutting subsidies, it boosted investors’ confidence in the economy of the Arab world’s most populous nation.

And he’s planning an investment debut in Egypt’s “booming” real estate market this year after hiring a consultant who said demand was strong, shrugging off concerns of a bubble in the market.

“In my family we are investing a lot right now because we see the opportunities,” he said. “It isn’t patriotism or advertising or anything like that.”

Read more: http://www.bloomberg.com/news/articles/2018-05-01/north-korea-is-a-bright-spot-for-billionaire-who-forecasts-crash

Electric Buses Are Hurting the Oil Industry

  • About 279,000 barrels a day of fuel won’t be needed this year
  • China adds a London-sized electric bus fleet every five weeks

Electric buses were seen as a joke at an industry conference in Belgium seven years ago when the Chinese manufacturer BYD Co. showed an early model.

“Everyone was laughing at BYD for making a toy,” recalled Isbrand Ho, the Shenzhen-based company’s managing director in Europe. “And look now. Everyone has one.”

Suddenly, buses with battery-powered motors are a serious matter with the potential to revolutionize city transport—and add to the forces reshaping the energy industry. With China leading the way, making the traditional smog-belching diesel behemoth run on electricity is starting to eat away at fossil fuel demand.

The numbers are staggering. China had about 99 percent of the 385,000 electric buses on the roads worldwide in 2017, accounting for 17 percent of the country’s entire fleet. Every five weeks, Chinese cities add 9,500 of the zero-emissions transporters—the equivalent of London’s entire working fleet, according Bloomberg New Energy Finance.

All this is starting to make an observable reduction in fuel demand. And because they consume 30 times more fuel than average sized cars, their impact on energy use so far has become much greater than the passenger sedans produced by companies from Tesla Inc. to Toyota Motor Corp.

Keeping It in the Ground

Cumulative global fuel displacement by e-buses and passenger EVs

Source: Bloomberg New Energy Finance

For every 1,000 battery-powered buses on the road, about 500 barrels a day of diesel fuel will be displaced from the market, according to BNEF calculations. This year, the volume of fuel not needed may rise 37 percent to 279,000 barrels a day because of electric transport including cars and light trucks, about as much oil as Greece consumes, according to BNEF. Buses account for about 233,000 barrels of that total.

“This segment is approaching the tipping point,” said Colin McKerracher, head of advanced transport at the London-based research unit of Bloomberg LP. “City governments all over the world are being taken to task over poor urban air quality. This pressure isn’t going away, and electric bus sales are positioned to benefit.”

China is ahead on electrifying its fleet because it has the world’s worst pollution problem. With a growing urban population and galloping energy demand, the nation’s legendary smogs were responsible for 1.6 million extra deaths in 2015, according to non-profit Berkeley Earth.

Putting It Back

Global fuel demand displaced by e-buses

Source: Bloomberg New Energy Finance

A decade ago, Shenzhen was a typical example of a booming Chinese city that had given little thought to the environment. Its smog became so notorious that the government picked it for a pilot program for energy conservation and zero emissions vehicles in 2009. Two years later, the first electric buses rolled off BYD’s production line there. And in December, all of Shenzhen’s 16,359 buses were electric.

BYD had 13 percent of China’s electric bus market in 2016 and put 14,000 of the vehicles on the streets of Shenzhen alone. It’s built 35,000 so far and has capacity to build as many as 15,000 a year, Ho said.

A worker charges an electric bus in Shenzhen.
Photographer: Qilai Shen/Bloomberg

BYD estimates its buses have logged 17 billion kilometers (10 billion miles) and saved 6.8 billion liters (1.8 billion gallons) of fuel since they started ferrying passengers around the world’s busiest cities. That, according to Ho, adds up to 18 million tons of carbon dioxide pollution avoided, which is about as much as 3.8 million cars produce in each year.

“The first fleet of pure electric buses provided by BYD started operation in Shenzhen in 2011,” Ho said by phone. “Now, almost 10 years later, in other cities the air quality has worsened while—compared with those cities—Shenzhen’s is much better.”

Driving the Revolution

China electric bus sales

Source: Bloomberg New Energy Finance

Other cities are taking notice. Paris, London, Mexico City and Los Angeles are among 13 authorities that have committed to only buying zero emissions transport by 2025.

London is slowly transforming its fleet. Currently four routes in the city center serviced by single-decker units are being shifted to electricity. There are plans to make significant investments to the clean its public transport networks, including retrofitting 5,000 old diesel buses in a program to ensure all buses are emission-free by 2037.

A BYD Co. double-decker electric bus at the EV Trend Korea exhibition in Seoul on April 12.
Photographer: SeongJoon Cho/Bloomberg

Transport for London, responsible for the city’s transport system, declined to comment for this article because of rules around engaging with the media ahead of May local government elections.

Those goals will have an impact on fuel consumption. London’s network draws about 1.5 million barrels a year of fuel. If the entire fleet goes electric, that may displace 430 barrels a day of diesel for each 1,000 buses going electric, reducing U.K. diesel consumption by about 0.7 percent, according to BNEF.

Ramping Up

Top-10 European electric bus fleets, 2017

Across the U.K. there were 344 electric and plug-in hybrid buses in 2017, and BYD hopes to be picked to supply more. It has partnered with a Scottish bus-maker to provide the batteries for 11 new electric buses that hit the city’s roads in March.

Falkirk-based manufacturer Alexander Dennis Ltd. began making electric buses in 2016 and has quickly become the European market leader with more than 170 vehicles operating in the U.K. alone.

More work is on the horizon, with London’s transport authority planning a tender to electrify its iconic double-decker buses, Ho said.

“The tech is ready,” Ho said. “We are ready, we have our plants in China, and Alexander Dennis in Scotland is geared up for TfL. Once we’re given the word, we are ready to go.”

(Corrects fifth paragraph to clarify total attributable to buses. )

Read more: http://www.bloomberg.com/news/articles/2018-04-23/electric-buses-are-hurting-the-oil-industry

Emmanuel Macron Talks to WIRED About France’s AI Strategy

On Thursday, Emmanuel Macron, the president of France, gave a speech laying out a new national strategy for artificial intelligence in his country. The French government will spend €1.5 billion ($1.85 billion) over five years to support research in the field, encourage startups, and collect data that can be used, and shared, by engineers. The goal is to start catching up to the US and China and to make sure the smartest minds in AI—hello Yann LeCun—choose Paris over Palo Alto.

Directly after his talk, he gave an exclusive and extensive interview, entirely in English, to WIRED Editor-in-Chief Nicholas Thompson about the topic and why he has come to care so passionately about it.

Nicholas Thompson: First off, thank you for letting me speak with you. It was refreshing to see a national leader talk about an issue like this in such depth and complexity. To get started, let me ask you an easy one. You and your team spoke to hundreds of people while preparing for this. What was the example of how AI works that struck you the most and that made you think, ‘Ok, this is going to be really, really important’?

Emmanuel Macron: Probably in healthcare—where you have this personalized and preventive medicine and treatment. We had some innovations that I saw several times in medicine to predict, via better analysis, the diseases you may have in the future and prevent them or better treat you. A few years ago, I went to CES. I was very impressed by some of these companies. I had with me some French companies, but I discovered US, Israeli and other companies operating in the same field. Innovation that artificial intelligence brings into healthcare systems can totally change things: with new ways to treat people, to prevent various diseases, and a way—not to replace the doctors—but to reduce the potential risk.

The second field is probably mobility: we have some great French companies and also a lot of US companies performing in this sector. Autonomous driving impresses me a lot. I think these two sectors, I would say, healthcare and mobility, really struck me as promising. It’s impossible when you are looking at these companies, not to say, Wow, something is changing drastically and what you thought was for the next decade, is in fact now. There is a huge acceleration.

NT: It seems you’re doing this partly because it is clearly in France’s national interest to be strong in AI. But it also seemed in the speech that you feel like there are French or European values that can help shape the development of AI? Is that correct, and what are those values?

EM: I think artificial intelligence will disrupt all the different business models and it’s the next disruption to come. So I want to be part of it. Otherwise I will just be subjected to this disruption without creating jobs in this country. So that’s where we are. And there is a huge acceleration and as always the winner takes all in this field. So that’s why my first objective in terms of education, training, research, and the creation of startups is to streamline a lot of things, to have the adaptable systems, the adapted financing, the adapted regulations, in order to build champions here and to attract the existing champions.

Laura Stevens

But you’re right at the same time: AI will raise a lot of issues in ethics, in politics, it will question our democracy and our collective preferences. For instance, if you take healthcare: you can totally transform medical care making it much more predictive and personalized if you get access to a lot of data. We will open our data in France. I made this decision and announced it this afternoon. But the day you start dealing with privacy issues, the day you open this data and unveil personal information, you open a Pandora’s Box, with potential use cases that will not be increasing the common good and improving the way to treat you. In particular, it’s creating a potential for all the players to select you. This can be a very profitable business model: this data can be used to better treat people, it can be used to monitor patients, but it can also be sold to an insurer that will have intelligence on you and your medical risks, and could get a lot of money out of this information. The day we start to make such business out of this data is when a huge opportunity becomes a huge risk. It could totally dismantle our national cohesion and the way we live together. This leads me to the conclusion that this huge technological revolution is in fact a political revolution.

When you look at artificial intelligence today, the two leaders are the US and China. In the US, it is entirely driven by the private sector, large corporations, and some startups dealing with them. All the choices they will make are private choices that deal with collective values. That’s exactly the problem you have with Facebook and Cambridge Analytica or autonomous driving. On the other side, Chinese players collect a lot of data driven by a government whose principles and values are not ours. And Europe has not exactly the same collective preferences as US or China. If we want to defend our way to deal with privacy, our collective preference for individual freedom versus technological progress, integrity of human beings and human DNA, if you want to manage your own choice of society, your choice of civilization, you have to be able to be an acting part of this AI revolution . That’s the condition of having a say in designing and defining the rules of AI. That is one of the main reasons why I want to be part of this revolution and even to be one of its leaders. I want to frame the discussion at a global scale.

AI will raise a lot of issues in ethics, in politics, it will question our democracy.

The key driver should not only be technological progress, but human progress. This is a huge issue. I do believe that Europe is a place where we are able to assert collective preferences and articulate them with universal values. I mean, Europe is the place where the DNA of democracy was shaped, and therefore I think Europe has to get to grips with what could become a big challenge for democracies.

NT: So the stakes here in your mind aren’t just French economic growth, it’s the whole value system that will be incorporated into this transformative technology the world over. And you want to make sure that the values you have, your country has, your continent has, are involved in that?

EM: Sure, exactly. I want to create an advantage for my country in artificial intelligence, directly. And that’s why we have these announcements made by Facebook, Google, Samsung, IBM, DeepMind, Fujitsu who choose Paris to create AI labs and research centers: this is very important to me. Second, I want my country to be part of the revolution that AI will trigger in mobility, energy, defense, finance, healthcare and so on. Because it will create value as well. Third, I want AI to be totally federalized. Why? Because AI is about disruption and dealing with impacts of disruption. For instance, this kind of disruption can destroy a lot of jobs in some sectors and create a need to retrain people. But AI could also be one of the solutions to better train these people and help them to find new jobs, which is good for my country, and very important.

I want my country to be the place where this new perspective on AI is built, on the basis of interdisciplinarity: this means crossing maths, social sciences, technology, and philosophy. That’s absolutely critical. Because at one point in time, if you don’t frame these innovations from the start, a worst-case scenario will force you to deal with this debate down the line. I think privacy has been a hidden debate for a long time in the US. Now, it emerged because of the Facebook issue. Security was also a hidden debate of autonomous driving. Now, because we’ve had this issue with Uber, it rises to the surface. So if you don't want to block innovation, it is better to frame it by design within ethical and philosophical boundaries. And I think we are very well equipped to do it, on top of developing the business in my country.

But I think as well that AI could totally jeopardize democracy. For instance, we are using artificial intelligence to organize the access to universities for our students That puts a lot of responsibility on an algorithm. A lot of people see it as a black box, they don't understand how the student selection process happens. But the day they start to understand that this relies on an algorithm, this algorithm has a specific responsibility. If you want, precisely, to structure this debate, you have to create the conditions of fairness of the algorithm and of its full transparency. I have to be confident for my people that there is no bias, at least no unfair bias, in this algorithm. I have to be able to tell French citizens, “OK, I encouraged this innovation because it will allow you to get access to new services, it will improve your lives—that’s a good innovation to you.” I have to guarantee there is no bias in terms of gender, age, or other individual characteristics, except if this is the one I decided on behalf of them or in front of them. This is a huge issue that needs to be addressed. If you don’t deal with it from the very beginning, if you don’t consider it is as important as developing innovation, you will miss something and at a point in time, it will block everything. Because people will eventually reject this innovation.

NT: So the steps you’re taking to guarantee that is that all of the algorithms developed by the French government will be open, algorithms developed by any company getting money from the French government will also be required to be open?

EM: Yes.

NT: And is there a third step you’re doing to help guarantee this transparency?

I think as well that AI could totally jeopardize democracy.

EM: We will increase the collective pressure to make these algorithms transparent. We will open data from government, publicly funded projects, and we will open access from this project and we will favor, incentivize the private players to make it totally public and transparent. Obviously some of them will say, there is a commercial value in my algorithm, I don't want to make it transparent. But I think we need a fair discussion between service providers and consumers, who are also citizens and will say: “I have to better understand your algorithm and be sure that this is trustworthy.” The power of consumption society is so strong that it gets people to accept to provide a lot of personal information in order to get access to services largely driven by artificial intelligence on their apps, laptops and so on. But at some point, as citizens, people will say, “I want to be sure that all of this personal data is not used against me, but used ethically, and that everything is monitored. I want to understand what is behind this algorithm that plays a role in my life.” And I’m sure that a lot of startups or labs or initiatives which will emerge in the future, will reach out to their customers and say “I allow you to better understand the algorithm we use and the bias or non-bias.” I’m quite sure that’s one of the next waves coming in AI. I think it will increase the pressure on private players. These new apps or sites will be able to tell people: “OK! You can go to this company or this app because we cross-check everything for you. It’s safe," or on the contrary: “If you go to this website or this app or this research model, it’s not OK, I have no guarantee, I was not able to check or access the right information about the algorithm”.

NT: When you talk about how AI will transform democracy, do you imagine a day where you make decisions based on recommendations from AI-based algorithms, where there’s a system that tells you what a labor reform should be and you say, “OK?”

EM: At this point, I think it could help you. But it will never replace the way you decide. When you make a decision, it’s the result of a series of cross-checks. AI can help you because sometimes when you pass a reform, you’re not totally clear about the potential effects, direct or indirect, and you can have hesitations. So it can help you to make the right decision. An algorithm is relevant for this part of the equation. For instance, on economic and social reforms, to have a clearer view about direct and indirect measurable effects. But on top of it, when you take a political decision, you need to have a part of personal judgment. That’s the quality of the decision maker, and artificial intelligence will never replace that. And there is a thing that AI could never replace; which is accountability and responsibility. Because this is his decision and will be held accountable for it, a political leader could never say, “OK I’m sorry this decision was bad because it was a decision of an algorithm.”

NT: Let’s get back to disruption for a second. You’ve talked a lot about transportation, you talked about it in your speech. AI is going to massively disrupt transportation, and it’s going to make a lot of people lose their jobs as we go to driverless cars. It will create new jobs, but this is already an area where people in France have been protesting. There were railroad strikes this weekend, there were trucker strikes this fall. Aren’t you taking a huge risk by aligning yourself with a force that is going to disrupt an industry that has already been protesting like crazy?

EM: Look, I think in this country—and in a lot of countries—you have a tradition of controversy. I launched a series of reforms that a lot of people thought impossible to be conducted in France. So, I'm absolutely sure it's possible, when you explain to people, when you have the energy and determination, to pass such reforms. I’m certainly not reluctant to do so and I’m certainly not, I would say, upset or threatened by dealing with artificial intelligence and convincing my people of its rightful implementation. As consumers, they are already big fans of artificial intelligence. And big fans of innovative solutions. All the tech guys can tell you that the French market is a very good market. People love technology here. I think that’s why the overall philosophy I have stuck to from the very beginning of my mandate is to say: blocking changes and being focused on protecting jobs is not the right answer. It’s the people you need to protect. You do so by giving them opportunities and by training and retraining them again to get new jobs. Don’t block the change because it’s coming and people will accept it. But try to be at the fore-front of change to better understand it and deal with it. Change can destroy jobs in the very short run, but create new ones in other sectors at the same time.

Laura Stevens

For me, one of the key issues of artificial intelligence is that it will probably reduce the most replicable and straining human activities. And naturally you will raise a whole range of other opportunities for people with low, middle and high qualifications. The big risk for our society is to increase opportunities only for very highly qualified people and, in a way, very low-qualified workers. It is especially necessary to monitor the qualification of the middle class, because they can be the most disrupted. If I take your examples, that would encompass taxi drivers, people working in the industry, or people working in highly repetitive tasks. So you have to train them either to change their sector of activity or to increase their qualification to work with a machine. We will need people working with machines.

For I do not believe that autonomous vehicles will exist without any drivers at all. For me, that’s pure imagination. You already have fully automated programs to drive planes. Therefore we technically could have planes with no pilots. But you still have two pilots in every plane. Even if almost everything is automated. That’s because you need to have responsibility, precisely. So what we will reduce with autonomous cars is the number of risks. What you will reduce is how painful it is to be a driver for a long period of time ; but you will need people to make the critical choice at critical moments for autonomous vehicles. I’m almost sure about that. So AI will change the practice but it will not kill transportation jobs in many cases.

Bottom line, my point is: I can convince my country about change precisely because I embrace it. My role is not to block this change, but to be able to train or retrain people for them to get opportunities in this new world.

NT: Got it. I want to ask you a military question. I know that the UN has had discussions on restrictions on lethal autonomous weapons. Do you think machines—artificial intelligence machines—can ever be trusted to make decisions to kill without human intervention?

EM: I’m dead against that. Because I think you always need responsibility and assertion of responsibility. And technically speaking, you can have in some situations, some automation which will be possible. But automation or machines put in a situation precisely to do that would create an absence of responsibility. Which, for me, is a critical issue. So that’s absolutely impossible. That’s why you always need a human check. And in certain ways, a human gateway. At a point of time, the machine can prepare everything, can reduce uncertainties, can reduce until nil the uncertainties and that’s an improvement which is impossible without it, but at a point of time, the go or no-go decision should be a human decision because you need somebody to be responsible for it.

Blocking changes is not the right answer. You have to protect people and to think about opportunities.

NT: Let me ask you about the national competition in artificial intelligence. Elon Musk tweeted some months ago: “Competition for AI superiority at national level most likely cause of World War3 in my opinion.” Do you think Musk is overstating it? Or do you think that this is going to get very intense, particularly between the United States and China?

EM: I think it will become very intense. I will not be so pessimistic, because I think that the core basis of artificial intelligence is research. And research is global. And I think this artificial intelligence deals with cooperation and competition, permanently. So you need an open world and a lot of cooperation if you want to be competitive. And at a point of time, in some issues, you need competition. But I think you will have to rethink a sort of sovereignty. I addressed that in my speech today. Artificial intelligence is a global innovation scheme in which you have private big players and one government with a lot of data—China. My goal is to recreate a European sovereignty in AI, as I told you at the beginning of this discussion, especially on regulation. You will have sovereignty battles to regulate, with countries trying to defend their collective choices. You will have a trade and innovation fight precisely as you have in different sectors. But I don't believe that it will go to the extreme extents Elon Musk talks about, because I think if you want to progress, there is a huge advantage in an open innovation model.

LEARN MORE

The WIRED Guide to Artificial Intelligence

NT: So this is a slightly cynical response to that, but let me ask you this: If France starts to build up an AI sector, in some ways it’s competitive to Google and Facebook. So won’t there be an incentive for Europe and for France to regulate Facebook and Google in ever-tougher ways? Doesn’t it create a strange dynamic where you might have incentives to bring more regulation and antitrust?

EM: Look, I would say exactly the opposite. Today, Google, Facebook, and so on, on artificial intelligence, they are very much welcome. Most people like them, these companies invest in France, they also recruit a lot of our talents and they develop their jobs here. So they are part of our ecosystem. The issue for these big players is the fact that they will have to deal with several issues. First, they have a very classical issue in a monopoly situation; they are huge players. At a point of time–but I think it will be a US problem, not a European problem–at a point of time, your government, your people, may say, “Wake up. They are too big.” Not just too big to fail, but too big to be governed. Which is brand new. So at this point, you may choose to dismantle. That’s what happened at the very beginning of the oil sector when you had these big giants. That’s a competition issue.

But second, I have a territorial issue due to the fact that they are totally digital players. They disrupt traditional economic sectors. In some ways, this might be fine because they can also provide new solutions. But we have to retrain our people. These companies will not pay for that; the government will. Today the GAFA [an acronym for Google, Apple, Facebook, and Amazon] don’t pay all the taxes they should in Europe. So they don’t contribute to dealing with negative externalities they create. And they ask the sectors they disrupt to pay, because these guys, the old sectors pay VAT, corporate taxes and so on. That’s not sustainable.

Third, people should remain sovereign when it comes to pivacy rules. France and Europe have their preferences in this regard. I want to protect privacy in this way or in that way. You don't have the same rule in the US. And speaking about US players, how can I guarantee French people that US players will respect our regulation? So at a point of time, they will have to create actual legal bodies and incorporate it in Europe, being submitted to these rules. Which means in terms of processing information, organizing themselves, and so on, they will need, indeed, a much more European or national organization. Which in turn means that we will have to redesign themselves for a much more fragmented world. And that’s for sure because accountability and democracy happen at national or regional level but not at a global scale. If I don’t walk down this path, I cannot protect French citizens and guarantee their rights. If I don't do that, I cannot guarantee French companies they are fairly treated. Because today, when I speak about GAFA, they are very much welcome I want them to be part of my ecosystem, but they don’t play on the same level-playing field as the other players in the digital or traditional economy. And I cannot in the long run guarantee my citizens that their collective preferences or my rules can be totally implemented by these players because you don't have the same regulation on the US side. All I know is that if I don’t, at a point of time, have this discussion and regulate them, I put myself in a situation not to be sovereign anymore.

NT: But aren’t those two goals very much in tension? You want the GAFA to come to France, you’ve touted it—Google has been invested in AI [in France] since 2012—but you also really want to crack down on them. How do you do both simultaneously?

EM: No. Look, because I think first, you don’t just have the GAFA. You have a lot of other players, startups, and so on. And I think, even for them, I mean they are discovering they will have to deal with democratic and political issues in your country.

NT: They’re just starting to learn that!

EM: Yes, yes! I mean, it’s fair. That’s the end of the very first phase, that was a sort of an early phase without any regulation, where they were in a situation to set up all the rules. Now they will have to deal with governments — but I want to do it in a cooperative way. I don't want to say, “I don’t want this guy anymore.” Exactly the opposite. I want a permanent dialogue. But I want them to understand and respect my constraints. I want them to be part of my reflection and to take into consideration their own reflection. I want them to better understand the fact that it is unfeasible to have a world without any responsibility and without a clear democratic accountability.

NT: Got it. So back to the big question, what will be success? How will you know that this has worked? And what will be failure? When you look at this a couple years from now?

EM: Look, first of all I think it’s very hard to answer this question because by definition, I don't have a clear view on what will happen for artificial intelligence in five years time. But I would say, if I manage to develop a very strong, powerful ecosystem, number one in Europe on artificial intelligence dealing with mobility, defense, healthcare, fintech, etc. I think it will be a success. And for me, if a majority of people in France understand and endorse this change it will be a success. It will be a failure if we are stuck with fears and blocked by big scares. My concern is that there is a disconnect between the speediness of innovation and some practices, and the time for digestion for a lot of people in our democracies. I have to build a sort of reciprocal or mutual trust coming from researchers, private players, startups, and my citizens. If the first category of people trust a country as being a relevant ecosystem for them, and at the same time, if I manage to build trust with my citizens for AI, I’m done. If I fail building trust with one of them, that’s a failure.

Real Smarts About Artificial Intelligence

  • As Google and Amazon are finding, not everyone is ready for artificial intelligence

  • Worried about robots taking your joblearn spreadsheets?

  • As artificial intelligence gets better and better, here are five tough projects for 2018

Read more: https://www.wired.com/story/emmanuel-macron-talks-to-wired-about-frances-ai-strategy/

Google’s New AI Head Is So Smart He Doesn’t Need AI

Google’s heavy investment in artificial intelligence has helped the company’s software write music and beat humans at complex board games. What unlikely feats could be next? The company’s new head of AI says he’d like to see Google move deeper into areas such as healthcare. He also warns that the company will face some tricky ethical questions over appropriate uses for AI as it expands its use of the technology.

The new AI boss at Google is Jeff Dean. The lean 50-year-old computer scientist joined the company in 1999, when it was a startup less than one year old. He earned a reputation as one of the industry’s most talented coders by helping Google become a computational powerhouse with new approaches to databases and large-scale data analysis. Google colleagues once created a joke website of “Jeff Dean facts,” including his purported role in accelerating the speed of light. Another had it that Dean doesn’t really exist—he’s an advanced AI created by Jeff Dean.

Dean helped ignite Silicon Valley’s AI boom when he joined Google’s secretive X lab in 2011 to investigate an approach to machine learning known as deep neural networks. The project produced software that learned to recognize cats on YouTube. Google went on to use deep neural networks to greatly improve the accuracy of its speech recognition service, and has since made the technique the heart of the company’s strategy for just about everything.

The cat-video project morphed into a research group called Google Brain, which Dean has led since 2012. He ascended to head the company’s AI efforts early this month after John Giannandrea left to lead Apple’s AI projects.

Dean’s new job puts him at the helm of perhaps the world’s foremost AI research operation. The group churns out research papers on topics such as creating more realistic synthetic voices and teaching robots to grasp objects.

But Dean and his group are also on the hook to invent the future of Google’s business. CEO Sundar Pichai describes the company’s strategy as “AI first,” saying that everything the company does will build on the technology.

One way Dean hopes to help is by conjuring up new lines of business. Google’s AI research has so far mostly been used to improve or expand existing products, such as search and smartphone software. “New machine learning capabilities or research results might enable us to do new things that Google doesn't now,” says Dean. “Health is one that's pretty far along in this direction.”

Dean wouldn’t discuss details. But two Google research projects offer clues. The company is testing software in India that can detect a complication of diabetes that causes blindness, and has also tested software that looks for signs of breast cancer on microscope slides. The FDA has begun cautiously approving AI software that helps doctors make medical decisions.

Success in healthcare could help diversify the business of a company that, despite broad interests, relies heavily on advertising. In 2017, almost 90 percent of parent company Alphabet’s revenue came from ads.

Dean is also excited about automating artificial intelligence—using machine-learning software to build machine-learning software. “It could be a huge enabler of the benefits of machine learning,” Dean says. “The current state is that machine learning expertise is relatively in short supply.”

Google dubs that meta-AI project AutoML. Dean says Alphabet’s self-driving car division Waymo has been testing the technology to improve its vision systems. AutoML is also at the core of a new cloud service of the same name that helps companies create customized image-recognition systems.

Longer term, Dean thinks automatic AI could enable robots to figure out how to cope with unfamiliar situations, such as opening a type of bottle cap they haven’t seen before. Despite successes on narrow tasks, AI researchers have struggled to make machines capable of many different thing. Dean says AutoML could bring about “really intelligent, adaptable systems that can tackle a new problem in the world when you don't have exposure of how to tackle it.”

More powerful AI systems will also lead Google into new, uncertain moral ground. Some researchers at the company are working on how to ensure that machine-learning systems don’t breach societal expectations of fairness. In 2015, Google’s photo-organizing product tagged some images of black people as gorillas, and the service has been blind to searches for the black apes ever since.

Google also faces other ethical decisions over allowing customers to tap its AI skills. The same week Dean took over Google’s top AI role, the New York Times reported that thousands of Google employees had signed a letter protesting a contract with the Pentagon that applies AI to interpret video from drones.

Dean declines to comment on the project’s details, but suggests it’s more a pointer to future ethical questions than an immediate moral challenge. “The actual project is relatively mundane, sort of assembling a bunch of existing open source components together, but it does I think give us pause as a company about what we want our role to be,” Dean says. “There's a wide range of views in the company about what we should be doing there.”

Google’s AI Adventures

Read more: https://www.wired.com/story/googles-new-ai-head-is-so-smart-he-doesnt-need-ai/

Saudis, SoftBank Plan World’s Largest Solar Project

  • Venture may cost $200 billion, add 100,000 jobs in the kingdom
  • Plan envisions 200GW of solar capacity in Saudi Arabia by 2030

Saudi Arabia and SoftBank Group Corp. signed a memorandum of understanding to build a $200 billion solar power development that’s exponentially larger than any other project.

SoftBank founder Masayoshi Son, known for backing ambitious endeavors with flair, unveiled the project Tuesday in New York at a ceremony with Saudi Crown Prince Mohammed Bin Salman. The powerful heir to the throne of the world’s largest crude exporter is seeking to diversify the economy and wean off a dependence on oil.

The deal is the latest in a number of eye-popping announcements from Saudi Arabia promising to scale up its access to renewables. While the kingdom has for years sought to get a foothold in clean energy, it’s was only in 2017 that ministers moved forward with the first projects, collecting bids for a 300-megawatt plant in October.

At 200 gigawatts, the Softbank project planned for the Saudi desert would be about 100 times larger than the next biggest proposed development and more than double what the global photovoltaic industry supplied last year, according to data compiled by Bloomberg New Energy Finance.

“It’s a huge step in human history,” Prince Mohammed said. “It’s bold, risky and we hope we succeed doing that.”

Over The Top

SoftBank-Saudi solar vision dwarfs other planned PV projects

Source: Bloomberg New Energy Finance; SoftBank

If built, the development would almost triple Saudi Arabia’s electricity generation capacity, which stood at 77 gigawatts in 2016, according to BNEF data. About two thirds of that is generated by natural gas, with the rest coming from oil. Only small-scale solar projects working there now.

Son said he envisions the project, which runs the gamut from power generation to panel and equipment manufacturing, will create as many as 100,000 jobs and shave $40 billion off power costs. The development will reach its maximum capacity by 2030 and may cost close to $1 billion a gigawatt, he said.

“The kingdom has great sunshine, great size of available land and great engineers, great labor, but most importantly, the best and greatest vision,” Son told reporters at a briefing.

Deepening Ties

The agreement deepens SoftBank’s ties with the Saudi Arabia, and advances the crown prince’s ambition to diversify its economy.

“SoftBank seeks investment and Saudi needs energy, so it may make sense to sort the financing out in a large block and then separately hammer out the phases and the technical details,” said Jenny Chase, head of solar analysis at BNEF. “It is worth noting that many of these memorandums of understanding do not result in anything happening. ”

SoftBank was said to be planning to invest as much as $25 billion in Saudi Arabia over the next three to four years. That’s a boost for Prince Mohammed, who’s been at the forefront of the Vision 2030 campaign to diversify the kingdom’s economy away from oil by that year. SoftBank is said to have aimed to deploy as much as $15 billion in a new city called Neom, which the crown prince plans to build on the Red Sea coast.

The Japanese company’s Vision Fund is also said to plan investments of as much as $10 billion in state-controlled Saudi Electricity Co. as part of efforts to diversify the utility into renewables and solar energy.

Vision, Investments

Son, who is known as a savvy investor with a flair for the spotlight, has been promoting clean energy since the 2011 Fukushima nuclear disaster and recently completed a 50-megawatt wind power farm in Mongolia. He has also pushed a plan dubbed “Asia Super Grid,” a plan to connect Asian nations by grids and undersea cables to distribute clean energy.

The kingdom’s deal-making has quickened as it pursues Prince Mohammed’s diversification goals. Saudi Arabia’s sovereign wealth fund, the Public Investment Fund, which has more than $224 billion in assets, spent about $54 billion on investments last year. The sale of about a 5 percent stake in oil giant Saudi Arabian Oil Co. is expected to provide more funds.

Saudi Arabia also plans to build at least 16 nuclear reactors over the next 25 years at a cost of more than $80 billion. Electricity demand in the country has risen by as much as 9 percent a year since 2000, according to BNEF.

Read more: http://www.bloomberg.com/news/articles/2018-03-28/saudi-arabia-softbank-ink-deal-on-200-billion-solar-project

Uber Agrees on Southeast Asian Sale to Grab

Uber Agrees on Southeast Asian Sale to Grab

Updated on

  • Uber is said to announce sale, for a stake of 25% to 30%
  • A deal will mark Uber’s exit from yet another major market

Uber Technologies Inc. has reached an agreement to sell its Southeast Asian ride-hailing business to rival Grab and could announce the deal as early as Monday morning in Singapore, people familiar with the matter said.

The agreement — which includes all of Uber’s operations in Southeast Asia as well as Uber Eats in the region — gives the U.S. company a stake of between 25 percent and 30 percent in the new combined business, the people said, asking not to be identified ahead of an official announcement. The deal, which Bloomberg outlined earlier this month, marks Uber’s operational exit from yet another major market and hands a victory to Grab as it battles local competitor Go-Jek.

SoftBank Group Corp., a major backer of Grab’s and Uber’s as well as China’s Didi Chuxing, has pushed consolidation to improve the profitability of a global ride-hailing business that bleeds billions of dollars a year. New entrants and the strength of second-place regional players such as Lyft Inc. in the U.S. have complicated those efforts.

Representatives for Grab and Uber declined to comment.

Read more: Grab Is Said to be Close to Deal for Uber’s Southeast Asia Business

The deal represents another major retreat from international markets for Uber. Travis Kalanick, its former chief executive officer, sold Uber’s business in China in 2016 in return for a 17.5 percent stake in Chinese ride-hailing leader Didi Chuxing. Then the ride-hailing giant agreed to sell its Russian business to Yandex — just before Dara Khosrowshahi took over as chief executive.

Khosrowshahi has been pushing to clean up the company’s financials in preparation for an initial public offering next year. Pulling out of markets like Southeast Asia would boost profits at a company that has burned through $10.7 billion since its founding nine years ago. Khosrowshahi signaled during a trip through Asia last month that he is committed to key markets such as Japan and India.

Grab CEO Braces for a Fight of Biblical Proportions With Uber

For Grab co-founder and CEO Anthony Tan, the truce would bring to an end a bruising battle for leadership in a Southeast Asian ride-hailing market forecast to reach $20.1 billion by 2025. The companies have been locked in a struggle for control of as many cities as possible across Southeast Asia, home to 620 million people.

Grab, which started out as a taxi-hailing app in Kuala Lumpur in 2012, became the region’s dominant ride-hailing service in past years with $4 billion raised from investors. It was most recently valued at $6 billion, according to CB Insights. Grab, which has more than 86 million mobile app downloads, currently offers services in more than 190 cities across Singapore, Indonesia, the Philippines, Malaysia, Thailand, Vietnam, Myanmar and Cambodia.

Read more: http://www.bloomberg.com/news/articles/2018-03-25/uber-is-said-to-reach-agreement-on-southeast-asian-sale-to-grab

A Hurricane Flattens Facebook

Two weeks ago, Facebook learned that The New York Times, Guardian, and Observer were working on blockbuster stories based on interviews with a man named Christopher Wylie. The core of the tale was familiar but the details were new, and now the scandal was attached to a charismatic face with a top of pink hair. Four years ago, a slug of Facebook data on 50 million Americans was sucked down by a UK academic named Aleksandr Kogan, and wrongly sold to Cambridge Analytica. Wylie, who worked at the firm and has never talked publicly before, showed the newspapers a trove of emails and invoices to prove his allegations. Worse, Cambridge appears to have lied to Facebook about entirely deleting the data.

To Facebook, before the stories went live, the scandal appeared bad but manageable. The worst deeds had been done outside of Facebook and long ago. Plus, like weather forecasters in the Caribbean, Facebook has been busy lately. Just in the past month, they’ve had to deal with scandals created by vacuous Friday tweets from an ad executive, porn, the darn Russian bots, angry politicians in Sri Lanka, and even the United Nations. All of those crises have passed with limited damage. And perhaps that’s why the company appears to have underestimated the power of the storm clouds moving in.

Facebook has burned its fingers on issues of data privacy frequently in its 14 year history. But this time it was different.

On Friday night, the company made its first move, jumping out in front of the news reports to publish its own blog post announcing that it was suspending Cambridge Analytica’s use of the platform. It also made one last stern appeal to ask The Guardian not to use the word “breach” in its story. The word, the company argued, was inaccurate. Data had been misused, but moats and walls had not been breached. The Guardian apparently did not find that argument sympathetic or persuasive. On Saturday its story appeared, “Revealed: 50 million Facebook profiles harvested for Cambridge Analytica in major data breach.”

The crisis was familiar in a way: Facebook has burned its fingers on issues of data privacy frequently in its 14 year history. But this time it was different. The data leakage hadn’t helped Unilever sell mayonnaise. It appeared to have helped Donald Trump sell a political vision of division and antipathy. The news made it look as if Facebook’s data controls were lax and that its executives were indifferent. Around the world lawmakers, regulators, and Facebook users began asking very publicly how they could support a platform that didn’t do more to protect them. Soon, powerful politicians were chiming in and demanding to hear from Zuckerberg.

As the storm built over the weekend, Facebook’s executives, including Mark Zuckerberg and Sheryl Sandberg, strategized and argued late into the night. They knew that the public was hammering them, but they also believed that the fault lay much more with Cambridge Analytica than with them. Still, there were four main questions that consumed them. How could they tighten up the system to make sure this didn’t happen again? What should they do about all the calls for Zuckerberg to testify? Should they sue Cambridge Analytica? And what could they do about psychologist Joseph Chancellor, who had helped found Kogan’s firm and who now worked, of all places, at Facebook?

By Monday, Facebook remained frozen, and Zuckerberg and Sandberg stayed silent. Then, late in the afternoon in Menlo Park, more bad news came. The New York Times reported that Alex Stamos, the company’s well-respected chief of security, had grown dissatisfied with the top of senior management and was planning to exit in a few months. Some people had known this for a while, but it was still a very bad look. You don’t want news about your head of data security bailing when you’re having a crisis about how to secure your data. And then news broke that Facebook had been denied in its efforts to get access to Cambridge Analytica’s servers. The United Kingdom’s Information Commissioner’s Office, which had started an investigation, would handle that.

A company-wide Q&A was called for Tuesday but for some reason it was led by Facebook’s legal counsel, not its leaders, both of whom have remained deafeningly silent and both of whom reportedly skipped the session. Meanwhile, the stock had collapsed, chopping $36 billion off the company’s market value on Monday. By mid-Tuesday morning, it had fallen 10 percent since the scandal broke. What the company expected to be a tough summer storm had turned into a Category 5 hurricane.

Walking in the Front Door

The story of how Kogan ended up with data on 50 million American Facebook users sounds like it should involve secret handshakes and black hats. But Kogan actually got his Facebook data by just walking in Facebook’s front door and asking for it. Like all technology platforms, Facebook encourages outside software developers to build applications to run inside it, just like Google does with its Android operating system and Apple does with iOS. And so in November 2013 Kogan, a psychology professor at the University of Cambridge, created an application developer account on Facebook and explained why he wanted access to Facebook’s data for a research project. He started work soon thereafter.

Kogan had created the most anodyne of tools for electoral manipulation: an app based on personality quizzes. Users signed up and answered a series of questions. Then the app would take those answers, mush them together with that person’s Facebook likes and declared interests, and spit out a profile that was supposed to know the test-taker better than he knew himself.

About 270,000 Americans participated. However what they didn’t know was that by agreeing to take the quiz and giving Facebook access to their data, they also granted access to many of their Facebook friends’ likes and interests as well. Users could turn off this setting, but it’s hard to turn off something you don’t know exists and that you couldn’t find if you did. Kogan quickly ended up with data on roughly 50 million people.

About five months after Kogan began his research, Facebook announced that it was tightening its app review policies. For one: Developers couldn’t mine data from your friends anymore. The barn door was shut, but Facebook told all the horses already in the pasture that they had another year to run around. Kogan, then, got a year and a half to do his business. And when the stricter policies went into effect, Facebook promptly rejected version two of his app.

By then Kogan had already mined the data and sold it to Cambridge Analytica, violating his agreement with Facebook and revealing one of the strange asymmetries of this story. Facebook knows everything about its users—but in some ways it knows nothing about its developers. And so Facebook didn’t start to suspect that Kogan had misused its data until it read a blaring headline in The Guardian in December 2015: “Ted Cruz using firm that harvested data on millions of unwitting Facebook users.”

That story passed out of the cycle quickly though, swept away by news about the Iowa caucuses. And so while Facebook’s legal team might have been sweating at the end of 2015, outwardly Zuckerberg projected an air of total calm. His first public statement after the Guardian story broke was a Christmas note about all the books he’d read: “Reading has given me more perspective on a number of topics – from science to religion, from poverty to prosperity, from health to energy to social justice, from political philosophy to foreign policy, and from history to futuristic fiction.”

An Incomplete Response

When the 2015 Guardian story broke, Facebook immediately secured written assertions from Cambridge Analytica, Kogan, and Christopher Wylie that the data had been deleted. Lawyers on all sides started talking, and by the early summer of 2016 Facebook had more substantial legal agreements with Kogan and Wylie certifying that the data had been deleted. Cambridge Analytica signed similar documents, but their paperwork wasn’t submitted until 2017. Facebook’s lawyers describe it as a tortured and intense legal process. Wylie describes it as a pinkie promise. “All they asked me to do was tick a box on a form and post it back,” he told the Guardian.

Facebook’s stronger option would have been to insist on an audit of all of Cambridge Analytica’s machines. Did the data still exist, and had it been used at all? And in fact, according to the standard rules that developers agree to, Facebook reserves that right. “We can audit your app to ensure it is safe and does not violate our Terms. If requested, you must provide us with proof that your app complies with our terms,” the policy currently states, as it did then.

Kogan, too, may have merited closer scrutiny regardless, especially in the context of the 2016 presidential campaign. In addition to his University of Cambridge appointment, Kogan was also an associate professor at St. Petersburg State University, and had accepted research grants from the Russian government.

'All options are on the table.'

Paul Grewal, Facebook Deputy General Counsel

Why didn’t Facebook conduct an audit—a decision that may go down as Facebook’s most crucial mistake? Perhaps because no audit can ever be completely persuasive. Even if no trace of data exists on a server, it could still have been stuck on a hard-drive and shoved in a closet. Facebook’s legal team also insists that an audit would have been time-consuming and would have required a court order even though the developer contract allows for one. A third possible explanation is fear of accusations of political bias. Most of the senior employees at Facebook are Democrats who blanch at allegations that they would let politics seep into the platform.

Whatever the reason, Facebook trusted the signed documents from Cambridge Analytica. In June 2016, Facebook staff even went down to San Antonio to sit with Trump campaign officials and the Cambridge Analytica consultants by their side.

To Facebook, the story seemed to go away. In the year following Trump’s victory, public interest advocates hammered Cambridge Analytica over its data practices, and other publications, particularly The Intercept, dug into its practices. But Facebook, according to executives at the company, never thought to double check if the data was gone until reporters began to call this winter. And then it was only after the story broke that Facebook considered serious action including suing Cambridge Analytica. A lawyer for the company, Paul Grewal, told WIRED on Monday evening that “all options are on the table.”

What Comes Next

Of Facebook’s many problems, one of the most confusing appears to be figuring out what to do with Chancellor, who currently works with the VR team. He may know about the fate of the user data, but this weekend the company was debating how forcefully it could ask him since it could be considered a violation of rules protecting employees from being forced to give up trade secrets from previous jobs.

A harder question is when, and how exactly, Zuckerberg and Sandberg should emerge from their bunkers. Sandberg, in particular, has passed through the crucible of the past two years relatively unscathed. Zuckerberg’s name now trends on Twitter when crises hit, and this magazine put his bruised face on the cover. Even Stamos has taken heat during the outcry over the Russia investigation. And a small bevy of brave employees have waded out into the rushing rivers of Twitter, where they have generally been sucked below the surface or swept over waterfalls.

At its core, according to a former Facebook executive, the problem is really an existential one.

The last most vexing question is what to do to make Facebook data safer. For much of the past year, Facebook has been besieged by critics saying that it should make its data more open. It should let outsiders audit its data and peer around inside with a flashlight. But it was an excess of openness with developers—and opaque privacy practices—that got the company in trouble here. Facebook tightened up third-party access in 2015, meaning an exact replay of the Cambridge Analytica fiasco couldn’t happen today. But if the company decides to close down even further, then what happens to the researchers doing genuinely important work using the platform? How well can you vet intentions? A possible solution would be for Facebook to change its data retention policies. But doing so could undermine how the service fundamentally works, and make it far more difficult to catch malevolent actors—like Russian propaganda teams—after the fact.

User data is now the foundation of the internet. Every time you download an app, you give the developer access to bits of your personal information. Every time you engage with any technology company—Facebook, Google, Amazon, and so on—you help build their giant database of information. In exchange, you trust that they won’t do bad things with that data, because you want the services they offer.

Responding to a thread about how to fix the problem, Stamos tweeted, “I don’t think a digital utopia where everybody has privacy, anonymity and choice, but the bad guys are magically kept out, can exist.”

At its core, according to a former Facebook executive, the problem is really an existential one. The company is very good at dealing with things that happen frequently and have very low stakes. When mistakes happen, they move on. According to the executive, the philosophy of the company has long been “We’re trying to do good things. We’ll make mistakes. But people are good and the world is forgiving.”

If Facebook doesn’t find a satisfactory solution, it faces the unsavory prospect of heavy regulation. Already in the UK, the General Data Protection Regulation rule will give people much more insight and control over what data companies like Facebook take, and how it’s used. In the US, senators like Ron Wyden, Mark Warner, Amy Klobuchar, and others may have the appetite for similar legislation, if Facebook’s privacy woes continue.

Facebook will hold its all-hands today, and hope for that inevitable moment when something horrible happens elsewhere and everyone’s attention turns. But it also knows that things might get worse, much worse. The nightmare scenario will come if the Cambridge Analytica story fully converges with the story of Russian meddling in American democracy: if it turns out that the Facebook data harvested by Cambridge Analytica ended up in the hands of Putin’s trolls.

At that point, Facebook will have to deal with yet another devastating asymmetry: data from a silly quiz app, created under obsolete rules, fueling a national security crisis. But those asymmetries are just part of the nature of Facebook today. The company has immense power, and it’s only begun to grapple with its immense responsibility. And the world isn’t as forgiving of Silicon Valley as it used to be.

Facebook and Cambridge Analytica

This story has been updated to include further details about Tuesday's company-wide meeting.

Read more: https://www.wired.com/story/facebook-cambridge-analytica-response/

Russian Hackers Attacking U.S. Power Grid and Aviation, FBI Warns

  • U.S. officials warn of attacks, including on nuclear plants
  • Cyber-attacks underway since at least March 2016, U.S. says

Russian hackers are conducting a broad assault on the U.S. electric grid, water processing plants, air transportation facilities and other targets in rolling attacks on some of the country’s most sensitive infrastructure, U.S. government officials said Thursday.

The announcement was the first official confirmation that Russian hackers have taken aim at facilities on which hundreds of millions of Americans depend for basic services. Bloomberg News reported in July that Russian hackers had breached more than a dozen power plants in seven states, an aggressive campaign that has since expanded to dozens of states, according to a person familiar with the investigation.

"Since at least March 2016, Russian government cyber actors" have targeted "government entities and multiple U.S. critical infrastructure sectors," including those of energy, nuclear, water and aviation, according to an alert issued Thursday by the Department of Homeland Security and Federal Bureau of Investigation.

Critical manufacturing sectors and commercial facilities also have been targeted by the ongoing "multi-stage intrusion campaign by Russian government cyber actors."

Cyber-attacks are "literally happening hundreds of thousands of times a day," Energy Secretary Rick Perry told lawmakers during a hearing Thursday. "The warfare that goes on in the cyberspace is real, it’s serious, and we must lead the world."

Separately Thursday, the U.S. sanctioned a St. Petersburg-based “troll farm,” two Russian intelligence services, a close ally of Russian President Vladimir Putin and other Russian citizens and businesses indicted by Special Counsel Robert Mueller on charges of meddling with the 2016 U.S. presidential election.

A joint analysis by the FBI and the Department of Homeland Security described the hackers as extremely sophisticated, in some cases first breaching suppliers and third-party vendors before hopping from those networks to their ultimate target. The government’s report did not say how successful the attacks were.

Read More: Russia Is Said to Be Suspect in Hacks of U.S. Power Plants

The Russian hackers "targeted small commercial facilities’ networks where they staged malware, conducted spear phishing, and gained remote access into energy sector networks," according to the Homeland Security alert.

An industry-government partnership provided potential indicators of compromise for electric companies following Thursday’s announcement, said Scott Aaronson, vice president of security and preparedness at the utility trade group Edison Electric Institute. The federal government alerted grid operators to a threat targeting the energy and manufacturing sectors last summer, but the incident didn’t affect operations, he said.

The hackers deliberately selected targets and methodically went after initial victims as a way to reach their ultimate prizes, including industrial control systems used by power plants and other infrastructure. Their tactics included sending spear-phishing emails and embedding malicious content on informational websites to obtain security credentials they could then leverage for more information and access.

And once they obtained access, the attackers "conducted network reconnaissance," and moved within the systems to collect information on industrial control systems.

The government’s alert on Russian cyber-attacks does not cover suspected meddling by the country in the 2016 election.

An October report by researchers at Symantec Corp., cited by the U.S. government Thursday, linked the attacks to a group of hackers it had code-named Dragonfly, and said it found evidence critical infrastructure facilities in Turkey and Switzerland also had been breached.

The Symantec researchers said an earlier wave of attacks by the same group starting in 2011 was used to gather intelligence on companies and their operational systems. The hackers then used that information for a more advanced wave of attacks targeting industrial control systems that, if disabled, leave millions without power or water.

The disclosure comes amid mounting calls from lawmakers to step up protection of the nation’s electric grid. Senator Maria Cantwell, the top Democrat on the Energy and Natural Resources Committee, pushed for a cyberthreat assessment of the grid last year, to better defend the infrastructure against potential attacks.

"I hope today’s belated response is the first step in a robust and aggressive strategy to protect our critical infrastructure," Cantwell, a Democrat from Washington state, said in an emailed statement.

U.S. intelligence officials have long been concerned about the security of the country’s electrical grid. The recent attacks, striking almost simultaneously at multiple locations, are testing the government’s ability to coordinate an effective response among several private utilities, state and local officials, and industry regulators.

Many of the targeted power plants are conventional, but the attacks included at least one nuclear power plant in Kansas, Bloomberg News reported in July. While the core of a nuclear generator is heavily protected, a sudden shutdown of the turbine can trigger safety systems. These safety devices are designed to disperse excess heat while the nuclear reaction is halted, but the safety systems themselves may be vulnerable to attack.

The operating systems at nuclear plants also tend to be legacy controls built decades ago and don’t have digital control systems that can be exploited by hackers.

Read more: http://www.bloomberg.com/news/articles/2018-03-15/russian-hackers-attacking-u-s-power-grid-aviation-fbi-warns