Submarine Spy Case Involved a Babysitter and a Band-Aid Wrapper – The New York Times

WASHINGTON On July 28, Diana Toebbe posted a Facebook message looking for a babysitter to take care of her children early on the coming Saturday morning for five to six hours.

Later the post, visible only to friends, was updated with the word *FOUND*. And on that Saturday, Ms. Toebbe accompanied her husband, Jonathan, to south-central Pennsylvania.

Unbeknown to Ms. Toebbe, she and her husband were being watched by the F.B.I. as they left their home in Annapolis, Md. And the bureaus agents continued to watch in Pennsylvania as Jonathan Toebbe removed from his shorts pocket a 32-gigabyte memory card hidden in a sealed Band-Aid wrapper, which he then, according to court papers, placed in a container set up by an undercover F.B.I. operative.

The Toebbes, accused by the U.S. government of trying to sell some of Americas most closely guarded submarine propulsion secrets to a foreign government, are scheduled to appear in federal court in West Virginia on Tuesday. They will face charges related to violating the Atomic Energy Acts prohibition on sharing nuclear know-how.

For now, the big questions surrounding the couple what country they are accused of trying to sell the nuclear secrets to, and what motivated them to take the risk remain unanswered.

Mr. Toebbe was described by acquaintances as a diligent and organized grad student in nuclear physics who was commissioned in the Navy as an officer and expert in submarine propulsion. He continued as a civilian in the Navy after finishing his military service, considered by some a plum assignment for the most talented nuclear physicists.

Ms. Toebbe was a 10-year veteran of the Key School, a progressive private school in Annapolis, where she taught history and English. There, according to parents, she was prone to talking about her Ph.D. in anthropology from Emory University and her love of knitting. She was a respected adviser, both formally and informally, at the school.

You could just tell she was insanely smart, said Craig Martien, 20, a 2019 graduate of Key School who worked closely with Ms. Toebbe on the yearbook and an after-school anthropology club. She was very friendly and down-to-earth, and I got along with her very well.

When Mr. Martien went off to Williams College, he brought along a toy squid that Ms. Toebbe had knitted. Like other Key graduates, Mr. Martien described her as a strong feminist and very liberal.

She was taken aback by President Donald J. Trumps 2016 election, he said, and mentioned several times that she was considering moving to Australia.

She said she couldnt stand the current state of politics and actually had found some job opportunities over there, he said.

On social media platforms, Ms. Toebbe shared photographs of her dogs, her children, meals cooking on the stove, a family vacation and selfies ordinary scenes of an ordinary life, one far different than the amateur cloak-and-dagger act portrayed in the F.B.I. affidavit.

Having made contact with the as-yet undisclosed other country about providing submarine secrets, the Toebbes were reluctant to expose themselves in an in-person meeting, according to the narrative laid out in court documents by the F.B.I. But their apparent desire for cryptocurrency payments led them to agree to the undercover operatives demand they deposit information in a dead drop location a decision that ultimately exposed their identity to the F.B.I.

Evidence in the court documents suggests the foreign country the Toebbes allegedly tried to sell the information to was an ally, or at least something of a partner, since it cooperated with the F.B.I. as the sting operation unfolded. While some experts speculated France could have been the target, French officials said they were not involved in the incident.

The hearing on Tuesday will be short. So far as the government knows, neither Jonathan nor Diana Toebbe has a lawyer. Prosecutors asked the court on Monday to hold Mr. Toebbe rather than granting him bail, saying he could face life in prison and was a flight threat. The magistrate judge could also set a hearing date for the couples continued detention.

Public records searches turned up no signs of financial distress that could provide a motivation for them to try to sell American secrets.

Yet the F.B.I. affidavit portrayed the couple as willing to take risks for the promise of payments in a cryptocurrency called Monero.

In February, F.B.I. agents, posing as a representative of the foreign country, proposed an in-person meeting. The response, which was signed Alice, a common placeholder name in military cryptography, wrote that face to face meetings are very risky for me, as I am sure you understand, according to the affidavit. The writer then proposed passing information electronically in exchange for $100,000 in the cryptocurrency.

Please remember I am risking my life for your benefit and I have taken the first step. Please help me trust you fully, the note to the undercover F.B.I. agents read.

The F.B.I. agents then pressed for a neutral drop location. The response came a few days later: I am concerned that using a dead drop location your friend prepares makes me very vulnerable, the note from Alice said, according to the affidavit. If other interested parties are observing the location, I will be unable to detect them. I am not a professional, and do not have a team supporting me.

The note went on to propose that the writer would choose a drop location for the encrypted files. The F.B.I. agents responded that they would give first $10,000 then $20,000 in cryptocurrency at a drop location of their choosing.

I am sorry to be so stubborn and untrusting, but I cannot agree to go to a location of your choosing, the response from Alice said. I must consider the possibility that I am communicating with an adversary who has intercepted my first message and is attempting to expose me.

The writer next proposed that the country provide reassurance by sending a signal from its complex in Washington over Memorial Day weekend.

Writing from an encrypted Proton mail account, Alice said the signal had been received, and agreed to drop the material at the location chosen by the undercover operative a mistake in tradecraft, some experts said.

It was somewhat surprising that someone who has studied submarine warfare follows the F.B.I.s direction to surface for these supposedly clandestine drop offs, said Michael Atkinson, a former inspector general for the intelligence community.

The willingness on the part of the country to convey the unspecified signal suggests its cooperation with the United States throughout the investigation. Mr. Atkinson said it was very unusual for a foreign country to allow its embassy or other facility to be used to send a signal to a suspect being pursued by the F.B.I.

Mr. Atkinson, now a partner at the law firm Crowell & Moring, said a similar false flag operation by the F.B.I. involving a government scientist trying to sell secrets to an ally resulted in a prison sentence of 13 years after a plea bargain.

At the Key School, where Ms. Toebbe taught, and in their Annapolis neighborhood, colleagues, students and neighbors tried to process the arrest of the couple and the accusations against them.

Luke Koerschner, 20, a 2019 Key School graduate now at Michigan State University, was in Ms. Toebbes advisory group for four years. He described her as very friendly and welcoming, an outgoing teacher who loved to cheer on her students in the schools cornhole tournaments.

Matthew Nespole, the head of the Key School, said he was shocked and appalled to learn of the charges against the Toebbes and that the school supports the administration of justice by the F.B.I. and NCIS, and will cooperate with the investigation. The Key School placed Ms. Toebbe on leave indefinitely.

Julian E. Barnes reported from Washington, and Brenda Wintrode and JoAnna Daemmrich from Annapolis, Md. Kitty Bennett contributed research. David E. Sanger contributed reporting from Washington.

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Submarine Spy Case Involved a Babysitter and a Band-Aid Wrapper - The New York Times

What is Signal? The messaging app Edward Snowden suggests we all join – indy100

Following Mondays Facebook, WhatsApp and Instagram outage, people sought out alternative ways of staying in touch.

The outage, caused by a faulty configuration change, was flagged around 5pm (GMT+1) on Monday with the issues being patched up by 3:30am the following day. Naturally, the outage inspired plenty of memes on Twitter as well as its fair share of conspiracy theories.

In that time, millions of people flocked to alternative private messaging apps such as Signal, Discord and Telegram.

On Twitter, Signal welcomed the millions of new signups it garnered during the six-hour outage.

Telegram reported that 70 million new users joined their platform during the outage. The app jumped 51 places on the iTunes US charts and reached fifth place on Monday, overtaking the likes of YouTube, Snapchat, and Facebook Messenger.

Amid the outage news, Facebook whistleblower Frances Haugen told a senate subcommittee that left alone, Facebook will continue to make choices that go against the common good our common good.

What is Signal?

Signal is an independent messaging app. Privacy is central to Signals offering, promising end-to-end encryption and no creepy tracking.

Signal is just like WhatsApp in that you can make voice calls, video calls, send messages, pictures, and stickers. On Signal, you can even create group chats with up to 1,000 participants.

One of the key differences between Signal and WhatsApp is that Signal is an independent non-profit. The app isnt tied to any large tech companies, whereas WhatsApp was bought up by Facebook in 2014.

Signal is free to download and easy to use, and can be used on mobile devices and desktops, including Linux.

Signal has also received glowing reviews. For an app that prides itself on privacy, word-of-mouth advertising doesnt get much better than nabbing an endorsement from whistleblower and privacy advocate Edward Snowden.

Twitter CEO Jack Dorsey is also a fan of the app and yesterday replied to Snowdens tweet saying Signal is WhatsUp and included a link to the apps website.

Signal was started by WhatsApp co-founder Brian Acton in 2018. After quitting Facebook, he sent a tweet reading: It is time. #deletefacebook.

The tweet came at a time when the Cambridge Analytica scandal was beginning to unfold.

Speaking to Forbes about his resignation from Facebook, Acton said: At the end of the day, I sold my company [WhatsApp]. I sold my users privacy to a larger benefit. I made a choice and a compromise. And I live with that every day.

To hammer home, the point on privacy, earlier this year Signal tried to raise awareness about the amount of data Instagram and its parent company Facebook gathers on its users by attempting to launch their own ad campaign on Instagram.

An example of an advert they tried to run reads: You got this ad because youre a goth barista and youre single. This ad used your location to see youre in Clinton Hill. And youre either vegan or lactose intolerant and youre really feeling that yoga lately.

However, Facebook reportedly dismissed the campaign as a stunt and claimed Signal didnt even try to run the ads.

In a blog post in May, Signals head of growth and communication Jun Harada wrote: Companies like Facebook arent building technology for you, theyre building technology for your data. They collect everything they can from FB, Instagram, and WhatsApp in order to sell visibility into people and their lives.

After the advertising beef, venture capitalist Bill Gurley tweeted: The Signal vs Facebook story is remarkable. The biggest threat to Facebook is a non-profit funded by WhatsApp founders! Such a great story.

To stay up to date on the latest news on Mondays outage, follow The Independents live blog.

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What is Signal? The messaging app Edward Snowden suggests we all join - indy100

Russian prisoners raped and abused in ‘conveyer belt of torture’, according to leaked footage – Telegraph.co.uk

However, on Wednesday their authenticity appeared to be confirmed after the regions prison chief, the head of the prison infirmary and several other officials were dismissed, according to the Federal Penitentiary Service.

It added that everyone implicated in those crimes will face justice.

Russia's Investigative Committee, which deals with high-profile crimes, has also launched an investigation into "violent acts of a sexual nature".

The crime carries a maximum penalty of 10 years behind bars, but those involved are unlikely to face that. A wide-ranging report by the Committee against Torture in August found that almost half of all law enforcement officers convicted of torture only receive suspended sentences.

Gulagu.net is one of several rights groups and independent media outlets that fled Russia earlier this year as the Kremlin ratcheted up pressure against those exposing the corruption and crimes of Russian officials and Mr Putins inner circle.

Last month, Mr Putin's party United Russia won a national election but was hit with widespread allegations of rampant fraud after a landslide win despite polls showing its waning popularity.

Mr Osechkin said his NGO had already shared the footage with Russian authorities, the Council of Europe, and the United Nations.

He said his source was a Belarusian IT engineer identified as Sergey who was incarcerated in Saratov prison and also faced abuse.

Sergey was coerced into cooperating with prison officials, during which time he managed the prison's computer network and secured access to video files from the entire Russian prison system.Igor Kalyapin, one of Russias most prominent activists fighting torture behind bars, said that while reports of such torture were not unusual, what is unique is the fact that we were able to see it."

Male prisoners in Russia often face sexual abuse at the hands of other prisoners on the orders of the prison administration, in order to intimidate and blackmail them, he told the independent media outlet TV Rain.

Those things are often done not only as punishment but in order to keep a person on a short leash, Mr Kalyapin added.

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Russian prisoners raped and abused in 'conveyer belt of torture', according to leaked footage - Telegraph.co.uk

BitMEX CEO predicts Bitcoin will be legal tender in five countries by 2022 – Cointelegraph

Countries in the developing world will soon follow in the steps of El Salvador and make Bitcoin (BTC)legal tender, BitMEX CEO Alexander Hptner recently predicted.

In a Wednesday blog post, Hptner expressed support for El Salvador adopting Bitcoin as legal tender in September, predicting that developing countries will be leading the way in Bitcoin adoption:

According to Hptner, developing countries will adopt Bitcoin faster due to three major factors: the growing need for cheaper and faster international remittances, massive inflation, and political issues.

As opposed to consumers in more developed countries, people in developing economies are more affected by issues related to cross-border payments and inflation, Hptner said.

The CEO noted that remittances made up 23% of El Salvadors gross domestic product in 2020, while the World Bank assessed that low- and middle-income countries receive about 75% of total global remittances. He added that people around the world are increasingly looking at Bitcoin as a solution to weather massive inflation, citing rapid crypto adoption in Turkey amid a 19.2% inflation rate.

Hptner went on to say that El Salvadors Bitcoin move will make it easier for other countries to consider similar moves. But if its a reality that politics will play a big role in the adoption of Bitcoin as legal tender, its also true that any failings by these leaders in the implementation phase may hurt wider adoption of cryptocurrencies in general, he added.

Related: 70% of Salvadorans opposed to Bitcoin Law as Sept. 7 implementation draws near

A former CEO of German stock exchange Boerse Stuttgart, Hptner took over as CEO of BitMEX in December 2020, replacing Arthur Hayes.

Hptner is not alone in thinking that more countries will follow El Salvadors lead in adopting Bitcoin. Last month, Cardano founder Charles Hoskinson predicted that a lot more countries will adopt cryptocurrencies. World-renowned computer programmer Edward Snowden also believes that latecomers may regret hesitating.

Some major figures in the cryptocurrency space have been hesitant to praise El Salvadors crypto adoption sparked by President Nayib Bukele. On Friday, Ethereum co-founder Vitalik Buterincriticized Bukeles approach to adopting Bitcoin,arguing that forcing businesses to accept a specific cryptocurrency is contrary to the ideals of freedom that are supposed to be so important to the crypto space.

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BitMEX CEO predicts Bitcoin will be legal tender in five countries by 2022 - Cointelegraph

US uses Nobel Prize to demonize Duterte, and therefore his successor – The Manila Times

WITH only a puny opposition less than a year to the 2022 elections, and a Duterte 2 administration inarguably on the horizon, the United States has employed what has been its special propaganda weapon, the Nobel Peace Prize, to give American-Filipino Maria Ressa, the chief executive officer (CEO) of a viciously anti-Duterte news website, the stature to demonize the Philippine president, and consequently whoever he endorses as his presidential candidate.

Ressa's co-awardee is Dmitry Muratov, an editor of the most widely circulated newspaper in Russia very critical of Vladimir Putin, the four-term president of the Russian Federation, one of the two adversaries of the US for world dominance. The US must be so desperate it didn't care that the motives of its Nobel move are so obvious: one is aimed against the strongman Putin, the other against the strongman Duterte, whom the Americans are furious at for drawing the country close to their second adversary, China. A Reuters headline on the story summed it up: "Journalists who took on Putin and Duterte win the 2021 Nobel Peace Prize" although it should have added the phrase "US targets" before "Putin."

The US has demonstrated several times in the past its power to manipulate the Nobel awards committee into handing the peace prize to whomever it wants, when it needs to do so. The committee consists of just five people nominated by the Norwegian Parliament. If you've ever been in such a panel (as I have), you will realize how easy it would be for a determined party, such as the US, to manipulate the committee: it receives over 300 nominations for all awards per year. How did Russia get into the minds of these Norwegians? In terms of contributing to humanity, Julian Assange, who started Wikileaks, and Edward Snowden, who told the world of the massive US monitoring of private cell phone conversations, didn't cross their minds. Oh, these two pissed off the US government.

The US has done this Nobel move before. To boost the profile of the first black US president, an obscure Illinois senator, the Nobel Peace Prize was awarded in 2009 to Barack Obama just nine months into his term even if he had done absolutely nothing to deserve the purported justification for it, "for his extraordinary efforts to strengthen international diplomacy." To draw attention to the imprisonment of a largely ignored Chinese dissident Liu Xiaobo, the peace prize was awarded solely to him in 2010.

Ressa was awarded not for any work of journalism but entirely on her portrayal of herself as a crusader for press freedom in the Philippines, which she claims President Rodrigo Duterte has been suppressing. She is a master of the sound bite, spewing such obvious lies that tug at Americans' hearts such as her claim that for criticizing Duterte, she had received at one point "90 hate messages an hour, 90 rape threats per minute."

That claim of press suppression in the country is just astonishing as anyone can simply scan the newspapers here and find that many are more vicious in criticizing Duterte than Rappler, yet are not complaining over press suppression. The Philippine Daily Inquirer and The Philippine Star should be jealous and protest the Ressa award: they have been more vociferously critical of Duterte, and with a much bigger audience than Rappler.

Killings

Killings of journalists, according to a detailed case-to-case investigation of the Presidential Task Force on Media Security, weren't related to their work. In the very few cases that were, the people who ordered their murder were drug lords or municipal-level political kingpins they run into trouble with. According to a Unesco monitoring body, there were 16 journalists here killed during the Duterte administration. Under Aquino 3rd, there were 27.

The Philippines has in fact the freest and probably most powerful press in the world. Ressa's website, initially funded by tycoon Benjamin Bitanga and then by Central Intelligence Agency (CIA)-linked US entities National Endowment for Democracy and the Omidyar Network, has even become one of the bigger websites since Duterte assumed office in 2016. How in the world could it have been suppressed? Journalists who have congratulated Ressa for winning the Nobel Prize, as the single one that did so in this newspaper, are so stupid they don't realize what that award essentially means: Only Ressa has the guts to fight Duterte, the rest of the Philippine press do not have the balls to do so.

It is a desperate move for the US since its nightmare is likely to be a reality: all the polls show that Ferdinand "Bongbong" Marcos Jr.," son of the strongman of Ferdinand E. Marcos, it moved heaven and earth to depose in 1986, will be the next president, even by a landslide. The Marcos camp should be worried though: the US would have other tricks other than this Nobel one to prevent Bongbong from winning the 2022 elections.

By getting her the Nobel Peace Prize, the US has made Ressa the opposition poster girl, giving her the platform and prestige to hurl dirt against Duterte and Marcos, when nobody practically listens anymore to the likes of Vice President Maria Leonor "Leni" Robredo or the communist spokesmen. Already, Ressa has started to do the rounds of television interviews as a Nobel laureate as in the respected Freed Zakaria's CNN program yesterday. It was Zakaria's first show involving the Philippines.

Defamation

The announcement by the Nobel Committee to justify Ressa's award it doesn't give any other explanation for its awards is so blatantly false and a gross defamation of our country that the government should file a diplomatic protest. The sole justification for the award, according to that "announcement," is that Ressa's "Rappler has focused critical attention on the Duterte regime's controversial, murderous anti-drug campaign. The number of deaths is so high that the campaign resembles a war waged against the country's own population."

Murderous? Not even Rappler, for god's sake, has claimed that that campaign "resembles a war waged" against the country's citizens. The accurate figure, which hasn't been disproved by actual facts despite several efforts by nongovernmental organizations (NGOs) and two universities, is around 6,600 since 2016. That's way fewer than 30,000 to 40,000 killed in state campaigns against illegal drugs in Mexico and Colombia.

The casualties have in fact gone down so much in the past two years that not even the opposition dare use Duterte's anti-drug war as a major issue in its anti-Duterte campaign, since most Filipinos are grateful that the campaign has vastly reduced the illegal drug problem in the country.

The figure of over "27,000" killed, which the Left and the opposition have succeeded in spreading all over the world, and which the Nobel Committee apparently believed, was one concocted by Rappler. It deliberately misinterpreted the number of total homicides (due to any reason including passion killing, for example) being investigated by police as due to the drug war. (See my 2020 column "Ressa, Coronel and Gascon concocted false '27,000 killed' number in anti-drug war.")

Incompetence

The cases filed in court against Ressa were not Duterte's moves to suppress her or Rappler, but entirely due to her incompetence as an editor and as a company CEO. A businessman filed charges against her and one of her staff for an article accusing him of being a "murderer," which was a total lie. The businessman asked her to just delete the article. She refused. It didn't take long for the court to find her guilty as there was totally no proof at all for the piece's allegations.

Two American CIA-linked NGOs, the National Endowment for Democracy and Omidyar Network, invested $4.5 million on the website, which was even announced there. But that was a clear violation of the Constitution that bars any foreign money in the media. Ressa tried to squeeze her way out of the predicament by claiming it was a form of corporate shares the Securities and Exchange Commission (SEC) allowed. The SEC ruled that it wasn't. She then claimed the amount was a "gift" to her and Rappler's editors. But the country's laws impose a tax on any gift, which they hadn't paid at all nor reported in their income tax returns. Ressa obviously thought she was exempted from the country's income tax laws. The Bureau of Internal Revenue disagreed.

Ressa is a fraud. She has exploited the unpopularity of Duterte in the US to portray herself as a poor victim of the president's wrath. The American press has been so gullible to believe her because Duterte isn't liked at all in the US, mainly the result of his distancing of the country from the superpower and drawing it closer to China, as well as the lies of the pro-American Yellow opposition, that he is a ruthless strongman like Putin.

Truth will eventually come out when some enterprising investigative reporter ferrets out the truth behind her Nobel Prize award, which is to demonize Duterte and thereby prevent his perceived successor from winning the 2022 elections. Ressa won't be the first journalist to fool even experienced US newspapers as was the case of Janet Cooke, who won a Pulitzer Prize in the 1980s for an article purportedly about an 8-year-old heroin addict in The Washington Post, which was later discovered to have been totally fabricated

When that day comes, I hope the Philippines does not get the dubious distinction as the country from which a fraudster managed to fool not just the Nobel Committee but most of the Western media. After all, she's mostly an American who took Filipino citizenship for convenience when her then employer ABS-CBN said it couldn't give her a paycheck as she didn't have the working permit necessary for foreigners employed in the country.

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US uses Nobel Prize to demonize Duterte, and therefore his successor - The Manila Times

Programming in natural language is coming sooner than you think – The Next Web

Sometimes major shifts happen virtually unnoticed. On May 5, IBMannounced Project CodeNet to very little media or academic attention.

CodeNet is a follow-up to ImageNet, a large-scale dataset of images and their descriptions; the images are free for non-commercial uses. ImageNet is now central to the progress of deep learning computer vision.

CodeNet is an attempt to do for Artificial Intelligence (AI) coding what ImageNet did for computer vision: it is a dataset of over 14 million code samples, covering 50 programming languages, intended to solve 4,000 coding problems. The dataset also contains numerous additional data, such as the amount of memory required for software to run and log outputs of running code.

IBMs own stated rationale for CodeNet is that it is designed to swiftly update legacy systems programmed in outdated code, a development long-awaited since the Y2K panic over 20 years ago, when many believed that undocumented legacy systems could fail with disastrous consequences.

However, as security researchers, we believe the most important implication of CodeNet and similar projects is the potential for lowering barriers, and the possibility of Natural Language Coding (NLC).

In recent years, companies such as OpenAI and Googlehave been rapidly improving Natural Language Processing (NLP) technologies. These are machine learning-driven programs designed to better understand and mimic natural human language and translate between different languages. Training machine learning systems require access to a large dataset with texts written in the desired human languages. NLC applies all this to coding too.

Coding is a difficult skill to learn let alone master and an experienced coder would be expected to be proficient in multiple programming languages. NLC, in contrast, leverages NLP technologies and a vast database such as CodeNet to enable anyone to use English, or ultimately French or Chinese or any other natural language, to code. It could make tasks like designing a website as simple as typing make a red background with an image of an airplane on it, my company logo in the middle and a contact me button underneath, and that exact website would spring into existence, the result of automatic translation of natural language to code.

It is clear that IBM was not alone in its thinking. GPT-3, OpenAIs industry-leading NLP model, has been used to allow coding a website or app by writing a description of what you want. Soon after IBMs news, Microsoft announced it had secured exclusive rights to GPT-3.

Microsoft also owns GitHub, the largest collection of open source code on the internet acquired in 2018. The company has added to GitHubs potential with GitHub Copilot, an AI assistant. When the programmer inputs the action they want to code, Copilot generates a coding sample that could achieve what they specified. The programmer can then accept the AI-generated sample, edit it or reject it, drastically simplifying the coding process. Copilot is a huge step towards NLC, but it is not there yet.

Although NLC is not yet fully feasible, we are moving quickly towards a future where coding is much more accessible to the average person. The implications are huge.

First, there are consequences for research and development. It is argued that the greater the number of potential innovators, the higher the rate of innovation. By removing barriers to coding, the potential for innovation through programming expands.

Further, academic disciplines as varied as computational physics and statistical sociology increasingly rely on custom computer programs to process data. Decreasing the skill required to create these programs would increase the ability of researchers in specialized fields outside computer sciences to deploy such methods and make new discoveries.

However, there are also dangers. Ironically, one is the de-democratization of coding. Currently, numerous coding platforms exist. Some of these platforms offer varied features that different programmers favor, however, none offer a competitive advantage. A new programmer could easily use a free, bare bones coding terminal and be at a little disadvantage.

However, AI at the level required for NLC is not cheap to develop or deploy and is likely to be monopolized by major platform corporations such as Microsoft, Google or IBM. The service may be offered for a fee or, like most social media services, for free but with unfavorable or exploitative conditions for its use.

There is also reason to believe that such technologies will be dominated by platform corporations due to the way machine learning works. Theoretically, programs such as Copilot improve when introduced to new data: the more they are used, the better they become. This makes it harder for new competitors, even if they have a stronger or more ethical product.

Unless there is a serious counter effort, it seems likely that large capitalist conglomerates will be the gatekeepers of the next coding revolution.

Article by David Murakami Wood, Associate Professor in Sociology, Queens University, Ontario and David Eliot, Masters Student, Surveillance Studies, Queens University, Ontario

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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Programming in natural language is coming sooner than you think - The Next Web

Top 10 In-Demand Programming Language that Will Rule in 2021 – Analytics Insight

The most crucial prerequisite for nearly any subject, whether it is Web Development,machine learning, Data Science, or any other, is the ability to program in aprogramming language. And, year after year, we see how the rankings of these programming languages change in response to developer demand and popularity. Beginners, in particular, must carefully examine numerous important factors such as demand and popularity, career possibilities, applications, and so on before deciding on aprogramming language.

JavaScriptis one of the few well-known programming languages with a strong following and demand. Facebook, Google, Microsoft, Uber, and other well-known firms in the IT sector useJavaScript. Even though the language is most recognized for adding responsive components to web pages, it has a wide range of uses in web development, game development, mobile application development, and more. Furthermore, the language is being utilized for both front-end and back-end development. Its interoperability with well-known frameworks such as React, Vue, Node, and others makes it more appealing to developers. Given the millions of websites that rely heavily on JavaScriptcurrently online, as well as the languages demand and domination, it seems reasonable to predict thatJavaScriptwill continue to reign supreme in 2021.

For many years,Pythonhas been the preferred language of virtually everyone who is just getting started in the programming world. The main reason for this is that it has a very basic syntax that is easy to read, understand, and apply. The language is widely used in web development, software development, and other fields, as well as with numerous cutting-edge technologies includingmachine learning, artificial intelligence, and data science. Rich library support, automated garbage collection, better interaction with other languages, GUI programming support, and many other features are included in the language. Django, Flask, Pyramid, and other popular Pythonframeworks make things more efficient and convenient.

Both C and C++ have a significant presence in the IT industry and are now ranked at the top of several indices. Many large IT firms, such as Adobe, Oracle, Microsoft, Nvidia, and others, hire C/C++ professionals with competitive salaries. C is a general-purpose proceduralprogramming language that is mostly used in the creation of low-level systems such as operating systems, kernel development, and other applications. This languages characteristics are passed down to many other programming languages. C++, on the other hand, is aprogramming languagethat focuses on objects (primarily developed as an extension of C). The language is extensively utilized in a variety of industries, including game development, GUI and desktop applications, and competitive programming.

The object-orientedprogramming languageimplements the well-known notion of write once, run anywhere, which allowsJavaprograms to run on other systems that supportJavawithout requiring a recompilation. The language is frequently utilized in the creation of Android applications, as well as web, desktop, and scientific applications. Additionally, top-tier organizations such as Adobe, Amazon, Flipkart, and others useJavaand provide enticing job prospects forJavaengineers.

Various big tech companies, such as Facebook, Google, Uber, and others, use the Rprogramming languagefor their businesses, and with the rapidly increasing demand for data science andmachine learningtrends, learning the Rprogramming languageis undoubtedly worthwhile for your future career pursuits. It is an open-sourceprogramming languagewith a large collection of libraries and frameworks that is extensively used in the fields of data science, statistical analysis, andmachine learning. GNU/Linux and Microsoft Windows are both well-suited to the language. It may also be readily integrated with a variety of data processing platforms, such as Hadoop and Spark. Cross-platform compatibility, high extensibility, powerful graphical capabilities, networked computing, and other important aspects of this language make it a more popular language among developers.

Kotlin is a general-purpose, statically typedprogramming languagethat supports both object-oriented and functional programming capabilities. The languages biggest feature is that it is fully compatible withJavaand supports allJavalibraries. In addition, the language is very simple to learn, and it can be used for online and desktop application development in addition to Android development. Some of the most popular frameworks for Kotlin include Javalin, KTor, and Vert.x, and companies like Pinterest, Uber, Netflix, and others are hiring Kotlin engineers.

Microsoft created the general-purposeprogramming languagemainly for its net framework. The language is widely used in game development, as well as the creation of Windows programs, server-side applications, and other software. C# also comes with a large library, making it a quicker and more efficientprogramming language. Structured language, quicker compilation, updateable & scalable, component-oriented, complete integration with .NET library, and many more are some of the amazing aspects of the language that are commonly praised by developers. The language is constantly utilized by developers in Unity game engine software, and organizations such as Intellectsoft, Capgemini, and others are also utilizing C# for their operations, implying that employment prospects for C# developers are plentiful.

PHP is used significantly by several well-known websites, including Facebook, Wikipedia, WordPress, and others. For website creation, the open-source server-side scripting language is used, and it has characteristics such as cross-platform compatibility, object-oriented programming capabilities, simple interaction with HTML, CSS, JavaScript, and other languages, as well as a large community of users. Beginners should consider learning this language because it is very simple to master. Laravel, Symfony, CodeIgniter, and others are some of the most popular PHP frameworks to consider.

The Goprogramming languageis used by companies such as Uber, Google, and others. Go is a Google-developed statically typedprogramming languagewith a syntax comparable to C. It comes with a slew of useful features, like garbage collection, dynamic typing, type safety, high performance and efficiency, and so on. The language is multithreaded and may be utilized in distributed systems, cloud computing, and other applications. The coolest thing about the language is that it overcomes several fundamental problems, such as sluggish compilation and execution, the lack of a large standard library, and so on.

Scala is used by several tech titans, including Netflix, Linked In, eBay, Twitter, and others, for their various platforms and businesses. Scala is strongly recommended for beginners due to its ease of learning. The language was created largely to address difficulties that developers have with another programming language,Java. It has established a solid standing among developers throughout time. Scala is a general-purposeprogramming languagethat may be used for both object-oriented and functional programming. It has several distinctive characteristics, including slow computing, string interpolation, type inference, and high scalability. Scala code may also be translated to bytecodes and run on theJavavirtual machine. Web development, data science, andmachine learningare all areas where the language is extensively utilized.

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Top 10 In-Demand Programming Language that Will Rule in 2021 - Analytics Insight

Open Streets Pop-Up Programming Coming To The Bronx & Queens In October – Gothamist

Back in the spring, the city passed legislation to ensure that the popular Open Streets program, which provides car-free outdoor space to New Yorkers where they live, continues well beyond the pandemic. As part of that legislation, the city committed to improving the way that Open Streets are managed, as well as create more of them in the underserved neighborhoods that need them most. To that end, the Department of Transportation (DOT) announced Tuesday that free public programming will be coming to some of those neighborhoods in the Bronx and Queens this month.

The pop-up programs, which include no-touch play areas for kids, plant giveaways, and musical entertainment, are coming to Astoria, Kingsbridge, South Bronx, and Mott Haven over the four remaining weekends in October. It's being done in partnership with Lyft, who will promote Citi Bike at the various locations and offer riders in these neighborhoods 50% off the cost of an annual membership.

Open Streets have fundamentally transformed the relationship New Yorkers have with their neighborhoods, said DOT Commissioner Hank Gutman. Were reclaiming space from cars while promoting educational and cultural activities and helping our neighbors embrace the bike boom in our city."

Local politicians, including Bronx Borough President Reuben Diaz Jr, Manhattan Borough President Gale Brewer, State Senator Robert Jackson, and Congressman Adriano Espaillat, praised the programming and the city's continued efforts to expand and improve Open Streets for everyone.

"Bike safety is critical, by providing informative educational workshops I hope that well be able to give riders the confidence they need to continue riding their bikes more often, said Council Member Ydanis Rodriguez, Chairman of the Transportation Committee. He added that he would work toward continuing to bring these kinds of cultural and educational programs to other neighborhoods.

Check out the full list of programs below.

OCTOBER OPEN STREETS PROGRAMMING:

The Open Streets program was announced in April 2020 as a way to give pandemic-beleaguered New Yorkers more space to roam outdoors at a time when people were being asked to socially distance or stay indoors. There are now over 350 blocks, and over 70 miles, of fully or partial Open Streets in the cityyou can check out all the locations and hours of operation here.

The program has also spawned several complimentary spin-off initiatives, including Open Restaurants, Open Culture and Open Boulevards.

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Open Streets Pop-Up Programming Coming To The Bronx & Queens In October - Gothamist

Facebook’s Whistleblower and the Downsides of Corporate Transparency – Bloomberg

Hi folks, its Brad. One of the most surprising things about the widening Facebook scandal is how former employee Frances Haugen obtained the trove of internal documentsand what that says about Silicon Valley culture. But first...

Todays top tech news:

The powerful Congressional testimony last week from former Facebook employee Frances Haugen might prompt new federal regulation and will likely damage the social networks already teetering brand reputation. But the most immediate victim could be the culture of extreme internal transparency at some Silicon Valley companiesthe very thing that allowed the whistleblower to make off with tens of thousands of internal documents in the first place.

Among the startling revelations over the past week was that Haugen obtained the documents, which described the companys allegedly lackluster efforts to combat misinformation and violence, in her last month at the companyafter she had already quit her job as a product manager. At most companies, this would earn an employee a one-way ticket out the door. At freewheeling Facebook, Haugen was able to stick around for a few weeks to pass her projects onto colleagues, and to trawl the companys internal bulletin boards collecting incriminating communiques that had little to do with her job.

Facebooks loose exit policy and apparently lax data-security policies arent unique. Theyre part of a culture of internal transparency thats commonplace in some corners of Silicon Valley. The idea, conveyed to new recruits at orientation, is that employees have access to significant amounts of internal research and documentation, so they know whats happening elsewhere at the company. Such free rein helps them collaborate with far-flung colleagues but is also a job perk, allowing them to fulfill any ambition or curiosity they have about other parts of the business.

This culture of permissiveness didnt originate at Facebook. As my colleagues Ryan Gallagher and Mark Bergen wrote two years ago, Google first based the practice on the principles of open-source software development, where the programming community collaborates to write code by making it freely available to anyone who wants to improve it. The search giant also established end-of-the-week Q&As with its founders Larry Page and Sergey Brin, dubbed TGIF, during which employees were allowed to interrogate their bosses. Facebook followed suit with its own weekly Q&A with Chief Executive Officer Mark Zuckerberg.

In retrospect, such radical transparency assumed that employees all held the same effervescent faith in the companys ideals and positive impact on the world. That is clearly no longer the case. A few years ago, the right-wing site Breitbart obtained video of Googles first TGIF after the 2016 presidential election, in which executives expressed disappointment about Donald Trumps presidential victory. Zucks company-wide Q&As also started regularly leaking. Workers who no longer believed in the causeor felt their companies might be doing harmhad found a weakness in their employersidealistic spirit of openness.

Employees at Google and Facebook now attest that their cultures that are far less transparent than they used to be. The companies track which documents employees are accessing and monitor when internal communiques are leaving company networks. (In Haugens case, these measures inexplicably failed.) At Facebook, divisions like Oculus, the virtual reality outfit, and Portal (formerly Building 8), its hardware skunkworks, are strictly hived off from the rest of the company. Executive Q&As with employees are far less frank and are occasionally made public, to head off leakers.

If these trends continue, Facebook and Google could start to resemble two of their big tech brethren. Amazon and Apple never recognized the virtues of internal transparency. Both have thrived with strictly compartmentalized internal silos and almost tyrannical levels of secrecy.

Even so, Apple, like Facebook, is also finding itself at odds with its own employees. It recently closed an internal Slack channel where employees were discussing the issue of pay equity. And in a recent email to employees, CEO Tim Cook warned workers to stop divulging plans for future products to the media and said that leakers could face jail time and massive fines.

Cook is incensed by employees who spill secrets to the media. Compared to Mark Zuckerberg, hes got little to worry about. Brad Stone

Two reclusive Swiss artists created an enchanting instrument that became a mainstay of festivals like Burning Man. But internet fame triggered a wave of copy cats. Now the artists are trying to kill off the movement they started.

Apple is seeking to delay loosening its grip on the App Store following a judges ruling in its legal battle with Epic.

Elon Musk is pulling away from Jeff Bezos in the rankings of the worlds richest.

The investor who thinks Chinas crypto crackdown could help decentralized finance.

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Facebook's Whistleblower and the Downsides of Corporate Transparency - Bloomberg

Microsoft and Nvidia team up to train one of the worlds largest language models – VentureBeat

The Transform Technology Summits start October 13th with Low-Code/No Code: Enabling Enterprise Agility. Register now!

Microsoft and Nvidia today announced that they trained what they claim is the largest and most capable AI-powered language model to date: Megatron-Turing Natural Language Generation (MT-NLP). The successor to the companies Turing NLG 17B and Megatron-LM models, MT-NLP contains 530 billion parameters and achieves unmatched accuracy in a broad set of natural language tasks, Microsoft and Nvidia say including reading comprehension, commonsense reasoning, and natural language inferences.

The quality and results that we have obtained today are a big step forward in the journey towards unlocking the full promise of AI in natural language. The innovations of DeepSpeed and Megatron-LM will benefit existing and future AI model development and make large AI models cheaper and faster to train, Nvidias senior director of product management and marketing for accelerated computing, Paresh Kharya, and group program manager for the Microsoft Turing team, Ali Alvi wrote in a blog post. We look forward to how MT-NLG will shape tomorrows products and motivate the community to push the boundaries of natural language processing (NLP) even further. The journey is long and far from complete, but we are excited by what is possible and what lies ahead.

In machine learning, parameters are the part of the model thats learned from historical training data. Generally speaking, in the language domain, the correlation between the number of parameters and sophistication has held up remarkably well. Language models with large numbers of parameters, more data, and more training time have been shown to acquire a richer, more nuanced understanding of language, for example gaining the ability to summarize books and even complete programming code.

To train MT-NLG, Microsoft and Nvidia say that they created a training dataset with 270 billion tokens from English-language websites. Tokens, a way of separating pieces of text into smaller units in natural language, can either be words, characters, or parts of words. Like all AI models, MT-NLP had to train by ingesting a set of examples to learn patterns among data points, like grammatical and syntactical rules.

The dataset largely came from The Pile, an 835GB collection of 22 smaller datasets created by the open source AI research effort EleutherAI. The Pile spans academic sources (e.g., Arxiv, PubMed), communities (StackExchange, Wikipedia), code repositories (Github), and more, which Microsoft and Nvidia say they curated and combined with filtered snapshots of the Common Crawl, a large collection of webpages including news stories and social media posts.

Training took place across 560 Nvidia DGX A100 servers, each containing 8 Nvidia A100 80GB GPUs.

When benchmarked, Microsoft says that MT-NLP can infer basic mathematical operations even when the symbols are badly obfuscated. While not extremely accurate, the model seems to go beyond memorization for arithmetic and manages to complete tasks containing questions that prompt it for an answer, a major challenge in NLP.

Its well-established that models like MT-NLP can amplify the biases in data on which they were trained, and indeed, Microsoft and Nvidia acknowledge that the model picks up stereotypes and biases from the [training] data. Thats likely because a portion of the dataset was sourced from communities with pervasivegender, race,physical, and religious prejudices, which curation cant completely address.

In a paper, the Middlebury Institute of International Studies Center on Terrorism, Extremism, and Counterterrorism claim that GPT-3 and similar models can generate informational and influential text that might radicalize people into far-right extremist ideologies and behaviors. A group at Georgetown University has used GPT-3 to generate misinformation, including stories around a false narrative, articles altered to push a bogus perspective, and tweets riffing on particular points of disinformation. Other studies, like one published by Intel, MIT, and Canadian AI initiative CIFAR researchers in April, have found high levels of stereotypical bias from some of the most popular open source models, including Googles BERT, XLNet,andFacebooks RoBERTa.

Microsoft and Nvidia claim that theyre committed to working on addressing [the] problem and encourage continued research to help in quantifying the bias of the model. They also say that any use of Megatron-Turing in production must ensure that proper measures are put in place to mitigate and minimize potential harm to users, and follow tenets such as those outlined in Microsofts Responsible AI Principles.

We live in a time [when] AI advancements are far outpacing Moores law. We continue to see more computation power being made available with newer generations of GPUs, interconnected at lightning speeds. At the same time, we continue to see hyper-scaling of AI models leading to better performance, with seemingly no end in sight, Kharya and Alvi continued. Marrying these two trends together are software innovations that push the boundaries of optimization and efficiency.

Projects like MT-NLP, AI21 Labs Jurassic-1, Huaweis PanGu-Alpha, Navers HyperCLOVA, and the Beijing Academy of Artificial Intelligences Wu Dao 2.0 are impressive from an academic standpoint, but building them doesnt come cheap. For example, the training dataset for OpenAIs GPT-3 one of the worlds largest language models was 45 terabytes in size, enough to fill 90 500GB hard drives.

AI training costs dropped 100-fold between 2017 and 2019, according to one source, but the totals still exceed the compute budgets of most startups. The inequity favors corporations with extraordinary access to resources at the expense of small-time entrepreneurs, cementing incumbent advantages.

For example, OpenAIs GPT-3 required an estimated 3.1423^23 floating-point operations per second (FLOPS) of compute during training. In computer science, FLOPS is a measure of raw processing performance, typically used to compare different types of hardware. Assuming OpenAI reserved 28 teraflops 28 trillion floating-point operations per second of compute across a bank of Nvidia V100 GPUs, a common GPU available through cloud services, itd take $4.6 million for a single training run. One Nvidia RTX 8000 GPU with 15 teraflops of compute would be substantially cheaper but itd take 665 years to finish the training.

Microsoft and Nvidia says that it observed between 113 to 126 teraflops per second per GPU while training MT-NLP. The cost is likely to have been in the millions of dollars.

A Synced report estimated that a fake news detection model developed by researchers at the University of Washington cost $25,000 to train, and Google spent around $6,912 to train a language model called BERT that it used to improve the quality of Google Search results. Storage costs also quickly mount when dealing with datasets at the terabyte or petabyte scale. To take an extreme example, one of the datasets accumulated by Teslas self-driving team 1.5 petabytes of video footage would cost over $67,500 to store in Azure for three months, according to CrowdStorage.

The effects of AI and machine learning model trainingon the environmenthave also been brought into relief. In June 2020, researchers at the University of Massachusetts at Amherst released a report estimating that the amount of power required for training and searching a certain model involves the emissions of roughly626,000 pounds of carbon dioxide, equivalent to nearly five times the lifetime emissions of the average U.S. car. OpenAI itself has conceded that models like Codex require significant amounts of compute on the order of hundreds of petaflops per day which contributes to carbon emissions.

In a sliver of good news, the cost for FLOPS and basic machine learning operations has been falling over the past few years. A 2020 OpenAI survey found that since 2012, the amount of compute needed to train a model to the same performance on classifying images in a popular benchmark ImageNet has been decreasing by a factor of two every 16 months. Other recent research suggests that large language models arent always more complex than smaller models, depending on the techniques used to train them.

Maria Antoniak, a natural language processing researcher and data scientist at Cornell University, says when it comes to natural language, its an open question whether larger models are the right approach. While some of the best benchmark performance scores today come from large datasets and models, the payoff from dumping enormous amounts of data into models is uncertain.

The current structure of the field is task-focused, where the community gathers together to try to solve specific problems on specific datasets, Antoniak told VentureBeat in a previous interview. These tasks are usually very structured and can have their own weaknesses, so while they help our field move forward in some ways, they can also constrain us. Large models perform well on these tasks, but whether these tasks can ultimately lead us to any true language understanding is up for debate.

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Microsoft and Nvidia team up to train one of the worlds largest language models - VentureBeat