U.S. warship stuck in Montreal since December due to ice resumes trip home

Navy thanked Montreal for the hospitality it showed the stranded crew

March 31, 2018

USS Little Rock Montreal 20180121
The USS Little Rock is shown moored in Montreal’s Old Port Sunday, Jan. 21, 2018. The newly commissioned Navy warship spent the winter in Montreal after its journey to Florida was interrupted by cold and ice. (Graham Hughes/Canadian Press)

An American warship stuck in Montreal since Christmas Eve has finally resumed its trip to its home port in Florida.

Port of Montreal spokesperson Mélanie Nadeau said the ship left around 6:15 a.m. Saturday.

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The USS Little Rock was commissioned in Buffalo on Dec. 16 but was trapped by ice at the Port of Montreal less than two weeks into its maiden voyage.

A spokeswoman for the Navy said officials decided to wait until weather conditions improved before allowing the ship to continue its journey to Mayport, Fla., out of concern for the safety of the ship and crew.

Lt. Cmdr. Courtney Hillson confirmed the ship finally left the city early on Saturday after spending more than three months in Montreal.

It is expected to arrive in Florida early next month after making several port visits along the way.

In a statement, the Navy thanked the city for the hospitality it showed the stranded crew.

“We greatly appreciate the support and hospitality of the city of Montreal, the Montreal Port Authority and the Canadian Coast Guard,” said the USS Little Rock Commanding Officer Cmdr. Todd Peters.

“We are grateful for the opportunity to further enhance our strong partnerships.”

The 118-metre Freedom-variant Little Rock is described as a fast and agile combat ship that is capable of operating near shore as well as on the open ocean.

It’s the second vessel to bear the name, and was commissioned in December alongside its Second World War-era namesake — a U.S. naval first.

The warship was equipped with temporary heaters and 16 de-icers designed to reduce ice accumulation on the hull, and the crew was provided with cold-weather clothing in light of the change to their winter plans.

The ship’s departure may be a relief to some nearby condo dwellers, who complained over the winter about the constant rumble emanating from the vessel’s generators.

In response, the lights illuminating the ship were dimmed and adjustments were made in February to a soundproofing, acoustic barrier wall surrounding the generators, the Port of Montreal said at the time.

Settling the Controversy Over Photo of Lee Harvey Oswald

A new study by Dartmouth researchers helps to refute one of the most famous conspiracy theories in U.S. history.

Dartmouth researchers built and posed a physiologically plausible 3-D model of Lee Harvey Oswald to match his appearance in the famous photo. By adding the appropriate mass to each part of the 3-D model, they were able to perform a balance analysis that revealed that although Oswald appears off-balance, his pose is stable. (Computer images courtesy of Hany Farid; Photo of Oswald from the Warren Commission)

Whether Lee Harvey Oswald acted alone to assassinate President John F. Kennedy has been the subject of countless articles, books, and movies. Conspiracy theories point to purported inconsistencies in the events of Nov. 22, 1963, and in the evidence collected against Oswald. One such example is a photograph of Oswald in his backyard holding a rifle in one hand and Marxist newspapers in the other. The photo was particularly damning because it showed Oswald holding the same type of rifle that was used to assassinate Kennedy.

At the time of his arrest, Oswald claimed the photo was fake. In addition, it has long been argued that the lighting and shadows in the photo are inconsistent; that Oswald’s facial features are inconsistent with other photos of him; that the size of the rifle is inconsistent with the known length of that type of rifle; and that Oswald’s pose is physically implausible (it appears as if he is standing off balance).

But research led by Hany Farid, a professor of computer science, uses a new digital image forensics technique and a 3-D model of Oswald to show that the photo is authentic.

“Our detailed analysis of Oswald’s pose, the lighting and shadows, and the rifle in his hands refutes the argument of photo tampering,” Farid says. A pioneering researcher in digital forensics whose team develops mathematical and computational techniques to detect tampering in photos, videos, audio recordings, and other documents, Farid has examined the photo closely before in studies in 2009 and 2010, but these studies did not address questions about Oswald’s pose. In the new study, Farid and his team conducted a 3-D stability analysis, concluding that, in fact, Oswald’s stance does not support claims of photo-tampering. The study appears in the Journal of Digital Forensics, Security and Law.

Farid teamed with Assistant Professor Emily Whiting, who specializes in architectural geometry, computer-aided design, and 3-D fabrication. With the help of graduate student Srivamshi Pittala, they built a 3-D model of Oswald and posed this model to match his appearance in the backyard photo. By adding the appropriate mass to each part of the 3-D model, they were able to perform a balance analysis, revealing that although Oswald appears off-balance, his pose is stable. The analysis also showed that the lighting and shadows are physically plausible and that the length of the rifle is consistent with the length of the rifle used to kill the president.

“Our analysis refutes purported evidence of manipulation in the Oswald photo, but more generally, we believe that the type of detailed 3-D modeling performed here can be a powerful forensic tool in reasoning about the physical plausibility of an image,” Farid says. “With a simple adjustment to the height and weight, the 3-D human model that we created can be used to forensically analyze the pose, stability, and shadows in any image of people.”

Pentagon releases blueprint for accelerating artificial intelligence

Photo illustration: Yahoo News; photos: AP, Patra Kongsirimongkolchai/EyeEm/Getty Images
Photo illustration: Yahoo News; photos: AP, Patra Kongsirimongkolchai/EyeEm/Getty Images

The Pentagon made public for the first time on Feb. 12 the outlines of its master plan for speeding the injection of artificial intelligence (AI) into military equipment, including advanced technologies destined for the battlefield.

By declassifying key elements of a strategy it had adopted last summer, the Defense Department appeared to be trying to address disparate criticism that it was not being heedful enough of the risks of using AI in its weaponry or not being aggressive enough in the face of rival nations’ efforts to embrace AI.

The 17-page strategy summary said that AI — a shorthand term for machine-driven learning and decision-making — held out great promise for military applications, and that it “is expected to impact every corner of the Department, spanning operations, training, sustainment, force protection, recruiting, healthcare, and many others.”

It depicted AI’s embrace in solely positive terms, asserting that “with the application of AI to defense, we have an opportunity to improve support for and protection of U.S. service members, safeguard our citizens, defend our allies and partners, and improve the affordability and speed of our operations.”

Stepping back from AI in the face of aggressive AI research efforts by potential rivals would have dire — even apocalyptic — consequences, it further warned. It would “result in legacy systems irrelevant to the defense of our people, eroding cohesion among allies and partners, reduced access to markets that will contribute to a decline in our prosperity and standard of living, and growing challenges to societies that have been built upon individual freedoms.”

The publication of the Pentagon strategy’s core concepts comes eight months after a Silicon Valley revolt against the military’s premier AI research program. After thousands of Google employees signed a petition protesting the company’s involvement in an effort known as Project Maven, meant to speed up the analysis of videos taken by a drone so that military personnel could more readily identify potential targets, Google announced on June 1 that it would back out of it.

But the release of the strategy makes clear that the Trump administration isn’t having second thoughts about the utility of AI. It says the focus of the Defense Department’s Joint Artificial Intelligence Center (JAIC), created last June, will be on “near-term execution and AI adoption.” And in a section describing image analysis, the document suggests there are some things machines can do better than humans can. It says that “AI can generate and help commanders explore new options so that they can select courses of action that best achieve mission outcomes, minimizing risks to both deployed forces and civilians.”

The JAIC is still adding staff, and its new director Lt. Gen. Jack Shanahan was confirmed by the Senate only two months ago. Shanahan’s last posting before taking over the JAIC was running Project Maven. While the Center’s budget in 2019 was only $90 million, it is responsible for overseeing hundreds of AI programs costing more than $15 million, and total Defense Department spending on AI over the next five years has been projected at $1.7 billion.

The summary repeatedly states that the military has an ethical obligation to conscientiously use AI by publicly discussing guidelines for its use and by ensuring that it’s employed only when safe. But thatbenchmark is not precisely defined in the unclassified summary, and it reiterates an earlier, vague policy that the department will require “appropriate levels of human judgment over the use of force” by machines.

The strategy does calls for the development of new defense “principles” to guide how the military will use AI, mirroring what companies like Google have done in announcing a set of ethics for the use of its own technology. The Pentagon has said it will develop these principles through the Defense Innovation Board, an advisory group made up of outside technology experts, including some top executives from Silicon Valley, which will conduct meetings across the country as part of its outreach. The board is due to give the secretary of defense recommendations for principles this summer.

During his two years in office, former Secretary of Defense James Mattis repeatedly said that his main goal was to make the military “more lethal,” including through the use of AI. But groups like the Campaign to Stop Killer Robots have been working to promote the idea of an arms control ban for autonomous technologies in weapons and have been working to increase public support. The group sponsored a poll released in January that found 52 percent of Americans opposed the idea of armed weapons systems that could choose to kill.

Although the strategy summary describes other countries, particularly Russia and China, as investing heavily in AI and “eroding” the U.S. technical advantage, others are warning that the U.S. is already behind. “I think that both Russia and China are in a better position than we are. I think they’re ahead of us,” Senate Armed Services Committee Chairman James Inhofe, R-Okla., said speaking to reporters Tuesday morning before the release of the strategy.

China’s State Council released a report in 2017 calling for the country to become the global leader in AI by 2030. That includes broad applications of AI and the development of a domestic industry targeted to be worth $150 billion.

Despite his concern, Inhofe, who shapes defense spending through Congress’s annual defense policy bill, said that AI wasn’t his top priority. “There are other things that need to be done first,” he said.

The summary was released a day after President Trump announced the American AI Initiative, which focuses on broader commercial interest in artificial intelligence. Neither of the two documents outlined any new proposed funding. for accelerating artificial intelligence

Photo illustration: Yahoo News; photos: AP, Patra Kongsirimongkolchai/EyeEm/Getty Images
Photo illustration: Yahoo News; photos: AP, Patra Kongsirimongkolchai/EyeEm/Getty Images

The Pentagon made public for the first time on Feb. 12 the outlines of its master plan for speeding the injection of artificial intelligence (AI) into military equipment, including advanced technologies destined for the battlefield.

By declassifying key elements of a strategy it had adopted last summer, the Defense Department appeared to be trying to address disparate criticism that it was not being heedful enough of the risks of using AI in its weaponry or not being aggressive enough in the face of rival nations’ efforts to embrace AI.

The 17-page strategy summary said that AI — a shorthand term for machine-driven learning and decision-making — held out great promise for military applications, and that it “is expected to impact every corner of the Department, spanning operations, training, sustainment, force protection, recruiting, healthcare, and many others.”

It depicted AI’s embrace in solely positive terms, asserting that “with the application of AI to defense, we have an opportunity to improve support for and protection of U.S. service members, safeguard our citizens, defend our allies and partners, and improve the affordability and speed of our operations.”

Stepping back from AI in the face of aggressive AI research efforts by potential rivals would have dire — even apocalyptic — consequences, it further warned. It would “result in legacy systems irrelevant to the defense of our people, eroding cohesion among allies and partners, reduced access to markets that will contribute to a decline in our prosperity and standard of living, and growing challenges to societies that have been built upon individual freedoms.”

The publication of the Pentagon strategy’s core concepts comes eight months after a Silicon Valley revolt against the military’s premier AI research program. After thousands of Google employees signed a petition protesting the company’s involvement in an effort known as Project Maven, meant to speed up the analysis of videos taken by a drone so that military personnel could more readily identify potential targets, Google announced on June 1 that it would back out of it.

But the release of the strategy makes clear that the Trump administration isn’t having second thoughts about the utility of AI. It says the focus of the Defense Department’s Joint Artificial Intelligence Center (JAIC), created last June, will be on “near-term execution and AI adoption.” And in a section describing image analysis, the document suggests there are some things machines can do better than humans can. It says that “AI can generate and help commanders explore new options so that they can select courses of action that best achieve mission outcomes, minimizing risks to both deployed forces and civilians.”

The JAIC is still adding staff, and its new director Lt. Gen. Jack Shanahan was confirmed by the Senate only two months ago. Shanahan’s last posting before taking over the JAIC was running Project Maven. While the Center’s budget in 2019 was only $90 million, it is responsible for overseeing hundreds of AI programs costing more than $15 million, and total Defense Department spending on AI over the next five years has been projected at $1.7 billion.

The summary repeatedly states that the military has an ethical obligation to conscientiously use AI by publicly discussing guidelines for its use and by ensuring that it’s employed only when safe. But thatbenchmark is not precisely defined in the unclassified summary, and it reiterates an earlier, vague policy that the department will require “appropriate levels of human judgment over the use of force” by machines.

The strategy does calls for the development of new defense “principles” to guide how the military will use AI, mirroring what companies like Google have done in announcing a set of ethics for the use of its own technology. The Pentagon has said it will develop these principles through the Defense Innovation Board, an advisory group made up of outside technology experts, including some top executives from Silicon Valley, which will conduct meetings across the country as part of its outreach. The board is due to give the secretary of defense recommendations for principles this summer.

During his two years in office, former Secretary of Defense James Mattis repeatedly said that his main goal was to make the military “more lethal,” including through the use of AI. But groups like the Campaign to Stop Killer Robots have been working to promote the idea of an arms control ban for autonomous technologies in weapons and have been working to increase public support. The group sponsored a poll released in January that found 52 percent of Americans opposed the idea of armed weapons systems that could choose to kill.

Although the strategy summary describes other countries, particularly Russia and China, as investing heavily in AI and “eroding” the U.S. technical advantage, others are warning that the U.S. is already behind. “I think that both Russia and China are in a better position than we are. I think they’re ahead of us,” Senate Armed Services Committee Chairman James Inhofe, R-Okla., said speaking to reporters Tuesday morning before the release of the strategy.

China’s State Council released a report in 2017 calling for the country to become the global leader in AI by 2030. That includes broad applications of AI and the development of a domestic industry targeted to be worth $150 billion.

Despite his concern, Inhofe, who shapes defense spending through Congress’s annual defense policy bill, said that AI wasn’t his top priority. “There are other things that need to be done first,” he said.

The summary was released a day after President Trump announced the American AI Initiative, which focuses on broader commercial interest in artificial intelligence. Neither of the two documents outlined any new proposed funding.

Pew: Immigrants Will Account For 88% of US Population Growth by 2065

By Sam Dorman | October 21, 2015 | 12:22 PM EDT

(AP photo)

(CNSNews.com) — If current demographic trends continue, over 100 million future immigrants and their descendants will account for 88 percent of population growth in the U.S. over the next 50 years, according to a recent report by the Pew Research Center.

Pew’s analysis of U.S. Census Bureau data projects that the total population of the United States will increase by 117 million people, from 324 million in 2015 to 441 million people in 2065.

Without immigration, the projected U.S. population in 2065 would be 338 million, according to Pew.

Sen. Jeff Sessions (R-AL) recently released a chart, using Pew data, showing that for every native-born American added to the country’s current population, immigration will add seven more over the next half century. One in five immigrants worldwide currently reside in the U.S.

With 103 million first- or second-generation immigrants comprising 36 percent of the U.S. population by 2065, Pew estimates that in 50 years, a record 17.7 percent of the U.S. population will be foreign-born – compared to the current 14 percent and five percent in 1965.

Pew also reports that since 1965, foreign-born immigrants have been the main driver of U.S. population growth as well as demographic change. The report argues that 1965 saw a major shift in immigration policy with the passage of the U.S. Immigration and Nationality Act signed by President Lyndon B. Johnson.

The 1965 law changed the criteria for immigrants admitted to the United States. Before 1965, quotas were assigned to countries based on how nationalities were represented in the census. According to Pew, 70 percent of visas were reserved for immigrants from Europe, primarily the United Kingdom, Ireland, and Germany. Prior to 1965, 80 percent of immigrants were white.

However, the new immigration system abandoned national origin quotas, and  instead focused on bringing in relatives of U.S. citizens, as well as taking in immigrants based on their skills in the workplace.

Since the 1965 changes in the law, three quarters of immigrants to the U.S. have been Hispanics and Asians. Hispanics currently represent 47 percent of immigrants, while Asians represent 26 percent.

While whites currently comprise the majority of Americans (62 percent), Pew projects that they will only make up 46 percent of the population in 2065. Hispanics are expected to make up 24 percent, a six percent increase from 2015, while Asians are expected to make up 14 percent of the population.

Meanwhile, the black percentage of the U.S. population is expected to grow slightly from 12 to 13 percent. Similarly, the black percentage of immigrants is expected to rise only one percent in the next 50 years, from eight percent to nine percent.

By 2055, “no racial or ethnic group will constitute a majority of the U.S. population,” Pew predicts.

Huawei Indictment Deep State Extortion against China

High level extortions are made of this. China is considered far more dangerous than Russia by the Deep State CIA and State Department. It’s no wonder that the Trump administration is giving in to the pressure from sections inside the US government that are far beyond his executive control, to pin down civilian executives with close ties to the Chinese government.

The US Department of Justice is ramping up its pressure against China’s most priced tech giant Huawei for having the edge in 5G and AI technologies that will be the foundation of the next stage of our devolution, i.e. Technocratic Dictatorship.

Unsealed indictments include collusion with Iran to bypass US sanctions against the latter.

The Huawei technology company is also being accused of stealing trade secrets, including a robot’s hand for possible replication, and has committed bank fraud in its business with Iran.

Of course, there was no violation prior to the US sanctions on “terrorist exporter” Iran. So, with the sanctions against Iran, the US created its own pretext for arm twisting the Chinese leadership in the hope that it will give in to more “trade concessions” from them.

In recent years, China has been investing heavily in real estate and tech companies in the US that are otherwise could not stand the competition coming from abroad simply because of its high operational costs. However, these investments are considered as nothing but Chinese acquisitions for the purpose of establishing an imperial foothold in America.

Eerily, the US is afraid having its own method being used against it.  Objectively, China really is just using value in exchange for value with these investments, and not dirty tricks like economic sanctions and black propaganda in pursuit of regime change like what the US is trying to accomplish in oil-rich Venezuela, which is in tangent with British robber barons’ desire to hostage the entire Venezuelan economy.

As far as espionage is concerned, every country is doing it against everyone it deemed a threat to its national and corporate security. The Five Eyes countries have been doing their surveillance on their own citizens 24 hours a day, for decades now, as per Edward Snowden revelations.

Either way, China is now sending high level personalities to settle the issue, and free a Chinese national Huawei CFO Meng Wanzhou.

Otherwise, China could always unload more of its $1.2 trillion worth of US treasury bonds to bring the Deep State down for good. Already, some Deep State companies are already reporting end of year meltdowns.

Caterpillar’s 4Q earnings fell short, making it the first miss in almost two years, with the construction segment’s weakness in part due to an unexpected decline in China a worrisome development.

–Karen Ubelhart and Christina Constantino, Bloomberg Intelligence analysts

Shares of Japanese rivals Komatsu Ltd. and Hitachi Construction Machinery Co. each lost more than 5 percent in Tokyo on Tuesday. In China, Sany Heavy Industry Co. and other heavy equipment makers fell at the open.

Stanley Black & Decker CEO Jim Loree wasn’t shy about raising the alarm bells on China last week, saying it was facing slowing economic growth there, along with most of the rest of the world. The previous week, paint maker PPG talked about “sluggish industrial activity in China” among pressures that the company will hit the first half of 2019.

Technology

Santa Clara, California-based Intel Corp., whose processors are the main component in most of the world’s personal computers and servers, cited softness in China among the reasons for its lower-than-expected full-year forecast last week. Nvidia, the biggest maker of chips for computer graphics cards, echoed those comments on Monday, saying that “deteriorating macroeconomic conditions,particularly in China, impacted consumer demand” for its products.

Nidec Corp., a Japanese maker of precision motors used in computer drives, cut its profit outlook by 26 percent for the year ending March 31, blaming it on the U.S.-China trade war. It reported a 43 percent drop in operating profit for the quarter through December.

Samsung Electronics Co.’s quarterly profit and revenue missed estimates on sputtering demand for memory chips during the last three months of 2018, the same period Apple saw anemic sales in China. The South Korean company has been losing share for its smartphones for years in China, but the slowdown there is now threatening to hurt its important chips business.

In Japan, chip-equipment manufacturer Tokyo Electron Ltd. dropped as much as 4 percent, while Advantest Corp. slid 7.1 percent. Samsung Electronics Co. fell 1.6 percent in Seoul, while Taiwan Semiconductor Manufacturing Co. declined 3.1 percent.

Car sales in China fell last year for the first time in more than 20 years.

“China is under threat, for sure,” Volkswagen AG Chief Executive Officer Herbert Diess said in a Bloomberg TV interview in Davos, Switzerland, last week. “This year will be challenging.”

Ford Motor Co. posted a fourth-quarter loss of $534 million in China last quarter. Wholesales by the carmaker’s China joint ventures — a measure of how many vehicles are shipped to dealers — plunged 57 percent during the period. By the end of last year, only about a third of the company’s dealers were profitable, Jim Farley, Ford’s president of global markets, said on a Jan. 23 earnings call.

U.S. auto-parts supplier Lear Corp. offered more color on China. Lear, whose biggest customer is Ford, said it expected orders for parts like seating systems to fall more than 10 percent this year.” – Bloomberg Asia

The US financial and industrial bankruptcy are reaching  unsustainable levels, and all America needs to do is to rid itself of parasites, and make way for positive development that the rest of the world is more than willing to assist.

The proposal is to write off all individual debts when all corporate vultures, Deep State embedded SES operators, are indicted and put in jails, everyone of them.  Obviously, this effort cannot be accomplished by one man alone. The US President is never in full control of the government.

Therefore, Americans must put in place real patriotic officials in charge of their government rather than just poking around the keyboards and uploading their daily news online about how their country is controlled by the bankers.

Each of them already knows the extent of the problem, now it’s time to act on their possible solutions. American needs to understand that their failure to preserve the Republic entrusted  to them a long time ago is the root cause of its corporate decadence right now.

This is not a hopeless case, but they must learn something from China and the rest of Asia.

If a small country like the Philippines can put in office a decisive and courageous leader by virtue of a grassroots campaign, so too can Americans choose their own leaders that are truly committed to lead the states for the better, and put them all in the office without a costly campaign.

The vernaculars simply said, that Duterte has no other choice but to give in to the pressure and demand of the people for him to run as for president in 2016.

Here’s another look at what happened 3 years ago…

There are 3.5 American for every Pinoy, surely you can find better government officials in your flock. Do something starting today, and make no excuses later.

The Chinese, on the other hand, are not boastful. They just let their actions do the talking for them. Yet, we wonder and protest how much they have achieved is such a short time. Now, they are collectively reaping the fruits of their own “cheap” labor, e.g. more than 700 million lifted from poverty, and still counting.

Can we, therefore, expect the return of high quality American made goods anytime soon?

Here’s a short documentary from a Western independent medium about why we can trust the Chinese more than the Western oligarchy in these issues.

Google’s true origin partly lies in CIA and NSA research grants for mass surveillance

 

Google’s true origin partly lies in CIA and NSA research grants for mass surveillance

Jeff Nesbit
By Jeff Nesbit

Former director of legislative and public affairs, National Science Foundation

Two decades ago, the US intelligence community worked closely with Silicon Valley in an effort to track citizens in cyberspace. And Google is at the heart of that origin story. Some of the research that led to Google’s ambitious creation was funded and coordinated by a research group established by the intelligence community to find ways to track individuals and groups online.

The intelligence community hoped that the nation’s leading computer scientists could take non-classified information and user data, combine it with what would become known as the internet, and begin to create for-profit, commercial enterprises to suit the needs of both the intelligence community and the public. They hoped to direct the supercomputing revolution from the start in order to make sense of what millions of human beings did inside this digital information network. That collaboration has made a comprehensive public-private mass surveillance state possible today.

The story of the deliberate creation of the modern mass-surveillance state includes elements of Google’s surprising, and largely unknown, origin. It is a somewhat different creation story than the one the public has heard, and explains what Google cofounders Sergey Brin and Larry Page set out to build, and why.

But this isn’t just the origin story of Google: It’s the origin story of the mass-surveillance state, and the government money that funded it.

Backstory: The intelligence community and Silicon Valley

In the mid 1990s, the intelligence community in America began to realize that they had an opportunity. The supercomputing community was just beginning to migrate from university settings into the private sector, led by investments from a place that would come to be known as Silicon Valley.

The intelligence community wanted to shape Silicon Valley’s efforts at their inception so they would be useful for homeland security purposes.

A digital revolution was underway: one that would transform the world of data gathering and how we make sense of massive amounts of information. The intelligence community wanted to shape Silicon Valley’s supercomputing efforts at their inception so they would be useful for both military and homeland security purposes. Could this supercomputing network, which would become capable of storing terabytes of information, make intelligent sense of the digital trail that human beings leave behind?

Answering this question was of great interest to the intelligence community.

Intelligence-gathering may have been their world, but the Central Intelligence Agency (CIA) and the National Security Agency (NSA) had come to realize that their future was likely to be profoundly shaped outside the government. It was at a time when military and intelligence budgets within the Clinton administration were in jeopardy, and the private sector had vast resources at their disposal. If the intelligence community wanted to conduct mass surveillance for national security purposes, it would require cooperation between the government and the emerging supercomputing companies.

To do this, they began reaching out to the scientists at American universities who were creating this supercomputing revolution. These scientists were developing ways to do what no single group of human beings sitting at work stations in the NSA and the CIA could ever hope to do: gather huge amounts of data and make intelligent sense of it.

A rich history of the governments science funding

There was already a long history of collaboration between America’s best scientists and the intelligence community, from the creation of the atomic bomb and satellite technology to efforts to put a man on the moon.

The internet itself was created because of an intelligence effort.

In fact, the internet itself was created because of an intelligence effort: In the 1970s, the agency responsible for developing emerging technologies for military, intelligence, and national security purposes—the Defense Advanced Research Projects Agency (DARPA)—linked four supercomputers to handle massive data transfers. It handed the operations off to the National Science Foundation (NSF) a decade or so later, which proliferated the network across thousands of universities and, eventually, the public, thus creating the architecture and scaffolding of the World Wide Web.

Silicon Valley was no different. By the mid 1990s, the intelligence community was seeding funding to the most promising supercomputing efforts across academia, guiding the creation of efforts to make massive amounts of information useful for both the private sector as well as the intelligence community.

They funded these computer scientists through an unclassified, highly compartmentalized program that was managed for the CIA and the NSA by large military and intelligence contractors. It was called the Massive Digital Data Systems (MDDS) project.

The Massive Digital Data Systems (MDDS) project 

MDDS was introduced to several dozen leading computer scientists at Stanford, CalTech, MIT, Carnegie Mellon, Harvard, and others in a white paper that described what the CIA, NSA, DARPA, and other agencies hoped to achieve. The research would largely be funded and managed by unclassified science agencies like NSF, which would allow the architecture to be scaled up in the private sector if it managed to achieve what the intelligence community hoped for.

“Not only are activities becoming more complex, but changing demands require that the IC [Intelligence Community] process different types as well as larger volumes of data,” the intelligence community said in its 1993 MDDS white paper. “Consequently, the IC is taking a proactive role in stimulating research in the efficient management of massive databases and ensuring that IC requirements can be incorporated or adapted into commercial products. Because the challenges are not unique to any one agency, the Community Management Staff (CMS) has commissioned a Massive Digital Data Systems [MDDS] Working Group to address the needs and to identify and evaluate possible solutions.”

Over the next few years, the program’s stated aim was to provide more than a dozen grants of several million dollars each to advance this research concept. The grants were to be directed largely through the NSF so that the most promising, successful efforts could be captured as intellectual property and form the basis of companies attracting investments from Silicon Valley. This type of public-to-private innovation system helped launch powerful science and technology companies like Qualcomm, Symantec, Netscape, and others, and funded the pivotal research in areas like Doppler radar and fiber optics, which are central to large companies like AccuWeather, Verizon, and AT&T today. Today, the NSF provides nearly 90% of all federal funding for university-based computer-science research.

The CIA and NSAs end goal

The research arms of the CIA and NSA hoped that the best computer-science minds in academia could identify what they called “birds of a feather:” Just as geese fly together in large V shapes, or flocks of sparrows make sudden movements together in harmony, they predicted that like-minded groups of humans would move together online. The intelligence community named their first unclassified briefing for scientists the “birds of a feather” briefing, and the “Birds of a Feather Session on the Intelligence Community Initiative in Massive Digital Data Systems” took place at the Fairmont Hotel in San Jose in the spring of 1995.

The intelligence community named their first unclassified briefing for scientists the “birds of a feather” briefing.

Their research aim was to track digital fingerprints inside the rapidly expanding global information network, which was then known as the World Wide Web. Could an entire world of digital information be organized so that the requests humans made inside such a network be tracked and sorted? Could their queries be linked and ranked in order of importance? Could “birds of a feather” be identified inside this sea of information so that communities and groups could be tracked in an organized way?

By working with emerging commercial-data companies, their intent was to track like-minded groups of people across the internet and identify them from the digital fingerprints they left behind, much like forensic scientists use fingerprint smudges to identify criminals. Just as “birds of a feather flock together,” they predicted that potential terrorists would communicate with each other in this new global, connected world—and they could find them by identifying patterns in this massive amount of new information. Once these groups were identified, they could then follow their digital trails everywhere.

Sergey Brin and Larry Page, computer-science boy wonders 

In 1995, one of the first and most promising MDDS grants went to a computer-science research team at Stanford University with a decade-long history of working with NSF and DARPA grants. The primary objective of this grant was “query optimization of very complex queries that are described using the ‘query flocks’ approach.” A second grant—the DARPA-NSF grant most closely associated with Google’s origin—was part of a coordinated effort to build a massive digital library using the internet as its backbone. Both grants funded research by two graduate students who were making rapid advances in web-page ranking, as well as tracking (and making sense of) user queries: future Google cofounders Sergey Brin and Larry Page.

The research by Brin and Page under these grants became the heart of Google: people using search functions to find precisely what they wanted inside a very large data set. The intelligence community, however, saw a slightly different benefit in their research: Could the network be organized so efficiently that individual users could be uniquely identified and tracked?

This process is perfectly suited for the purposes of counter-terrorism and homeland security efforts: Human beings and like-minded groups who might pose a threat to national security can be uniquely identified online before they do harm. This explains why the intelligence community found Brin’s and Page’s research efforts so appealing; prior to this time, the CIA largely used human intelligence efforts in the field to identify people and groups that might pose threats. The ability to track them virtually (in conjunction with efforts in the field) would change everything.

It was the beginning of what in just a few years’ time would become Google. The two intelligence-community managers charged with leading the program met regularly with Brin as his research progressed, and he was an author on several other research papers that resulted from this MDDS grant before he and Page left to form Google.

The grants allowed Brin and Page to do their work and contributed to their breakthroughs in web-page ranking and tracking user queries. Brin didn’t work for the intelligence community—or for anyone else. Google had not yet been incorporated. He was just a Stanford researcher taking advantage of the grant provided by the NSA and CIA through the unclassified MDDS program.

Left out of Googles story

The MDDS research effort has never been part of Google’s origin story, even though the principal investigator for the MDDS grant specifically named Google as directly resulting from their research: “Its core technology, which allows it to find pages far more accurately than other search engines, was partially supported by this grant,” he wrote. In a published research paper that includes some of Brin’s pivotal work, the authors also reference the NSF grant that was created by the MDDS program.

Instead, every Google creation story only mentions just one federal grant: the NSF/DARPA “digital libraries” grant, which was designed to allow Stanford researchers to search the entire World Wide Web stored on the university’s servers at the time. “The development of the Google algorithms was carried on a variety of computers, mainly provided by the NSF-DARPA-NASA-funded Digital Library project at Stanford,” Stanford’s Infolab says of its origin, for example. NSF likewise only references the digital libraries grant, not the MDDS grant as well, in its own history of Google’s origin. In the famous research paper, “The Anatomy of a Large-Scale Hypertextual Web Search Engine,” which describes the creation of Google, Brin and Page thanked the NSF and DARPA for its digital library grant to Stanford. But the grant from the intelligence community’s MDDS program—specifically designed for the breakthrough that Google was built upon—has faded into obscurity.

Google has said in the past that it was not funded or created by the CIA. For instance, when stories circulated in 2006 that Google had received funding from the intelligence community for years to assist in counter-terrorism efforts, the company told Wired magazine founder John Battelle, “The statements related to Google are completely untrue.”

Did the CIA directly fund the work of Brin and Page, and therefore create Google? No. But were Brin and Page researching precisely what the NSA, the CIA, and the intelligence community hoped for, assisted by their grants? Absolutely.

The CIA and NSA funded an unclassified, compartmentalized program designed from its inception to spur something that looks almost exactly like Google.

To understand this significance, you have to consider what the intelligence community was trying to achieve as it seeded grants to the best computer-science minds in academia: The CIA and NSA funded an unclassified, compartmentalized program designed from its inception to spur the development of something that looks almost exactly like Google. Brin’s breakthrough research on page ranking by tracking user queries and linking them to the many searches conducted—essentially identifying “birds of a feather”—was largely the aim of the intelligence community’s MDDS program. And Google succeeded beyond their wildest dreams.

The intelligence communitys enduring legacy within Silicon Valley

Digital privacy concerns over the intersection between the intelligence community and commercial technology giants have grown in recent years. But most people still don’t understand the degree to which the intelligence community relies on the world’s biggest science and tech companies for its counter-terrorism and national-security work.

Civil-liberty advocacy groups have aired their privacy concerns for years, especially as they now relate to the Patriot Act. “Hastily passed 45 days after 9/11 in the name of national security, the Patriot Act was the first of many changes to surveillance laws that made it easier for the government to spy on ordinary Americans by expanding the authority to monitor phone and email communications, collect bank and credit reporting records, and track the activity of innocent Americans on the Internet,” says the ACLU. “While most Americans think it was created to catch terrorists, the Patriot Act actually turns regular citizens into suspects.”

When asked, the biggest technology and communications companies—from Verizon and AT&T to Google, Facebook, and Microsoft—say that they never deliberately and proactively offer up their vast databases on their customers to federal security and law enforcement agencies: They say that they only respond to subpoenas or requeststhat are filed properly under the terms of the Patriot Act.

But even a cursory glance through recent public records shows that there is a treadmill of constant requests that could undermine the intent behind this privacy promise. According to the data-request records that the companies make available to the public, in the most recent reporting period between 2016 and 2017, local, state and federal government authorities seeking information related to national security, counter-terrorism or criminal concerns issued more than 260,000 subpoenas, court orders, warrants, and other legal requests to Verizon, more than 250,000 such requests to AT&T, and nearly 24,000 subpoenas, search warrants, or court orders to Google. Direct national security or counter-terrorism requests are a small fraction of this overall group of requests, but the Patriot Act legal process has now become so routinized that the companies each have a group of employees who simply take care of the stream of requests.

In this way, the collaboration between the intelligence community and big, commercial science and tech companies has been wildly successful. When national security agencies need to identify and track people and groups, they know where to turn – and do so frequently. That was the goal in the beginning. It has succeeded perhaps more than anyone could have imagined at the time.

The illusion of reality television

The illusion of reality television

Reality television is in many ways a fiction

The front door of a white, expensive-looking house with pillars and balconies.
Source: Flickr

When the first series of reality show Made in Chelsea aired in 2011, it was clear from the beginning that the heart of it was the relationship between two young Londoners, Spencer Matthews and Caggie Dunlop.

Between them, their conventional good-looks and blasé affluence became the distilled essence of the show. He was a bad boy socialite, as much a charming womaniser as he was caught up by other women’s charms, a Restoration rake stuck in Belgravia; she was the vulnerable, uncertain girl-next-door, someone from his childhood who suddenly reappears as a beautiful adult. Her re-entry into the Chelsea bubble disrupts his relationship with his long-term girlfriend, and throws the whole series into a drawn-out will-they-won’t-they arc of constant romantic deferral. The plot is perfect – part fairytale, part realism, all performed against the backdrop of the mansions of Knightsbridge. But doesn’t it all sound a bit too good to be true?

Made in Chelsea is a reality television show, but it admits to being a ‘structured-reality’ television show. The true nature of Spencer and Caggie’s real-life relationship cannot be truly known, by virtue of the fact that nobody’s relationship can authentically exist in the public eye. But its depiction on the show cannot be the truth of it. For one, nobody can make genuine, heartfelt declarations of love with cameras shoved up close and a whole crew of directors, producers, and engineers leering round; for another, by claiming to offer a ‘structured-reality’, the show effectively concedes to the fact that it hires scriptwriters and story developers to construct the ‘reality’ we observe; they admit to using television magic to conjure illusion.

The great irony of reality television is that it is, of course, an illusion. The creators manage to construct this pretence in two ways. On set, producers are able to contrive circumstances that allow them to control the content of the show.

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For example, in the Love Island house, books and televisions are banned. The contestants’ phones are taken away from them, and they are instead given ones that are disabled from the internet. As it turns out, great television isn’t made by letting people watch it all day. It’s easy to imagine how this absence of mental stimulation cultivates an atmosphere of cabin fever, one in which tensions are raised to fever pitch and pack mentalities doggedly persist, when there isn’t a great deal else to do. Ironically, it’s the absence of activity that makes the show as voyeuristically entertaining as it is.

But when they have the footage, the producers then have to construct a narrative for the episode in the editing room. In the moment of filming, what happens can be manipulated to some extent through persuasion, creating high-pressure environments, or penning contestants in, but humans are still humans – they’re still prone to responding contingently, to behaving erratically, or simply to offering very mundane content. In order to make the show feel cohesive, well-structured, and logically episodic, the editors must work to construct narrative threads throughout each episode, whether it be that of conflict, romance, or failure.

Reality television is, then, in many ways a fiction. They tell us they are depicting something akin to an authentic reality, but flatten and stabilise the randomness and contingency of actual life, while refusing to overtly acknowledge the authorial voice behind it.

None of this manipulation would really matter if the content was actually fictional. But real people are implicated in this process, and their representations on national television won’t always help them when they leave the villa, or step back into the world of work.

Narrative arcs in reality television follow the tropes of folklore – good vs. bad, hero vs. enemy – and so those who are demonised in the editing process have their reputation soured. In an age of internet trolling and hyper-awareness about online reputation, this depiction isn’t easy to come out of. For all those celebrities who feed off of this gossip for their fame, like the Kardashians, for example, this concern is perhaps no issue.

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But for the average person thrust into the limelight, they will come out of reality television with bucket-loads of baggage that has been amped up by producers, dissected by the Twittersphere, and dumped unceremoniously on their CV.

The fact remains that people still tune in. People will happily block out that which disrupts their illusion, when the illusion is far too much fun to bother becoming disenchanted with.

It seems it might all be too good to be true – but it’s also too far good to ignore.