Experiment confirms 50-year-old theory describing how black holes could generate energy

In 1969, British physicist Roger Penrose suggested that energy could be generated by lowering an object into the black hole’s ergosphere—the outer layer of the black hole’s event horizon, where an object would have to move faster than the speed of light in order to remain still.

Penrose predicted that the object would acquire a negative energy in this unusual area of space. By dropping the object and splitting it in two so that one half falls into the black hole while the other is recovered, the recoil action would measure a loss of negative energy—effectively, the recovered half would gain energy extracted from the black hole’s rotation. The scale of the engineering challenge the process would require is so great, however, that Penrose suggested only a very advanced, perhaps alien, civilisation would be equal to the task.

Two years later, another physicist named Yakov Zel’dovich suggested the theory could be tested with a more practical, earthbound experiment. He proposed that “twisted” light waves, hitting the surface of a rotating metal cylinder turning at just the right speed, would end up being reflected with additional energy extracted from the cylinder’s rotation thanks to a quirk of the rotational doppler effect.

But Zel’dovich’s idea has remained solely in the realm of theory since 1971 because, for the experiment to work, his proposed metal cylinder would need to rotate at least a billion times a second—another insurmountable challenge for the current limits of human engineering.

Now, researchers from the University of Glasgow’s School of Physics and Astronomy have finally found a way to experimentally demonstrate the effect that Penrose and Zel’dovich proposed by twisting instead of light—a much lower frequency source, and thus much more practical to demonstrate in the lab.

[…]

Marion Cromb, a Ph.D. student in the University’s School of Physics and Astronomy, is the paper’s lead author. Marion said: “The linear version of the doppler effect is familiar to most people as the phenomenon that occurs as the pitch of an ambulance siren appears to rise as it approaches the listener but drops as it heads away. It appears to rise because the sound waves are reaching the listener more frequently as the ambulance nears, then less frequently as it passes.

“The rotational doppler effect is similar, but the effect is confined to a circular space. The twisted sound waves change their pitch when measured from the point of view of the rotating surface. If the surface rotates fast enough then the sound frequency can do something very strange—it can go from a positive frequency to a negative one, and in doing so steal some energy from the rotation of the surface.”

As the speed of the spinning disc increases during the researchers’ experiment, the pitch of the sound from the speakers drops until it becomes too low to hear. Then, the pitch rises back up again until it reaches its previous pitch—but louder, with amplitude of up to 30% greater than the original sound coming from the speakers.

Marion added: “What we heard during our experiment was extraordinary. What’s happening is that the frequency of the is being doppler-shifted to zero as the spin speed increases. When the sound starts back up again, it’s because the waves have been shifted from a positive frequency to a negative frequency. Those negative-frequency waves are capable of taking some of the from the spinning foam disc, becoming louder in the process—just as Zel’dovich proposed in 1971.”

Professor Daniele Faccio, also of the University of Glasgow’s School of Physics and Astronomy, is a co-author on the paper. Prof Faccio added: “We’re thrilled to have been able to experimentally verify some extremely odd physics a half-century after the theory was first proposed. It’s strange to think that we’ve been able to confirm a half-century-old theory with cosmic origins here in our lab in the west of Scotland, but we think it will open up a lot of new avenues of scientific exploration. We’re keen to see how we can investigate the effect on different sources such as electromagnetic waves in the near future.”

The research team’s paper, titled “Amplification of waves from a rotating body,” is published in Nature Physics.


Explore further

Reversal of orbital angular momentum arising from an extreme Doppler shift


More information: Marion Cromb et al. Amplification of waves from a rotating body, Nature Physics (2020). DOI: 10.1038/s41567-020-0944-3

Source: Experiment confirms 50-year-old theory describing how an alien civilization could exploit a black hole

Depixelizing Video Game Characters using AI Creates Monsters

A new digital tool built to depixelize photos sounds scary and bad. Another way to remove privacy from the world. But this tool is also being used for a sillier and not terrible purpose: Depixelizng old game characters. The results are…nevermind, this is also a terrible use of this tool.

“Face Depixelizer” is a tool Created by Alex Damian, Sachit Menon, and Denis Malimonov. It does exactly what you expect with a name like that. Users can upload a pixelated photo of a face and the tool spits out what that person might look like based on algorithms and all that stuff. In the wrong hands, this type of tech can be used to do some bad shit and will make it harder to hide in this world from police and other powerful and dangerous groups.

But it can also be used to create monsters out of old game characters. Look what this thing did to Mario, for example.

Illustration for article titled Depixelizing Video Game Characters Creates Monsters
Screenshot: Twitter

Steve from Minecraft turns into a dude who doesn’t wear a mask because “It’s all a hoax dude.”

Illustration for article titled Depixelizing Video Game Characters Creates Monsters
Screenshot: Twitter

Guybrush changed quite a bit and also grew weirdly disturbing hair…

Illustration for article titled Depixelizing Video Game Characters Creates Monsters
Screenshot: Twitter

These might be strange or even a bit monstrous, but things start getting much worse when you feed the tool images that don’t look like people at all. For example, this is what someone got after uploading an image of a Cacodemon from Doom.

Illustration for article titled Depixelizing Video Game Characters Creates Monsters
Screenshot: Twitter

Poor Peppy turns into a demon from a horror film.

Illustration for article titled Depixelizing Video Game Characters Creates Monsters
Screenshot: Twitter

And the Creeper from Minecraft somehow becomes even scarier.

Illustration for article titled Depixelizing Video Game Characters Creates Monsters
Screenshot: Twitter

There’s a bunch more in this thread. There’s also a bunch of Tweets all about uploading Black people’s faces and learning that the tool isn’t great at dealing with them. Almost seems like you should have diverse teams working on tech projects so as to not overlook a small detail like an entire group of people. Though in this case, I’m fine with the creators screwing up.

Maybe if people keep uploading video game images to tools like this we can eventually make them worthless.

Source: Depixelizing Video Game Characters Creates Monsters

Big Tech on the hook for billions in back taxes after US Supreme Court rejects Altera stock options case hearing

Google, Apple, Facebook, Amazon and a host of other tech giants will have to pay billions of dollars in extra tax after the Supreme Court refused to hear an appeal on a stock-option case.

America’s top court said [PDF] on Monday it will not review a decision by the Ninth Circuit of Appeals that stock-based compensation should be considered a US taxable asset.

The case concerns the tax years 2004-2007 and Intel-owned tech company Altera, which provided its employees with the ability to buy company shares at a set price in future – a common practice in the tech industry. But that benefit was not included in an accounting of an Altera subsidiary based in a Cayman Islands tax haven just prior to Intel’s purchase.

The shifting of intangible assets has become a common tax-reducing tactic by large tech companies and saves those companies billions of dollars every year that they would otherwise pay to US tax authorities.

However, the Internal Revenue Service (IRS) insisted that Altera’s stock-option compensation be taxed under US tax rules. Facing a massive tax bill- Altera refused to accept the rule and challenged it in court, arguing that “the amount of money at stake is enormous.”

The company accused the IRS of over-reach and claimed it had not provided sufficient evidence to prove its case. And Altera won with a unanimous decision in tax court.

But the IRS appealed and the Ninth Circuit then found in the IRS’ favor, arguing in its 2-1 decision [PDF] in June 2019 that it was “uncontroversial” that stock options should be treated as accounting costs. It then refused a request for the whole court to rehear the case. So Altera appealed the decision to the Supreme Court.

Big Tech weighs in

Among the companies that urged the Supreme Court to take up the case were Apple, Google and Facebook – all of which now face massive tax bills for having done exactly the same thing.

The tech giants argued that the Ninth Circuit decision threatened to ruin “the hard-won but fragile international consensus on treatment of hundreds of billions of dollars of intercompany payments.” In other words, land them with massive, unexpected tax bills.

Ranged against the tech giants were a clump of law professors who argued that the IRS was right to make stock-option compensation a taxable asset.

It’s hard to know the true impact on those companies but the bills are expected to run to billions of dollars, possibly tens of billions. But in a sign of just how big those companies have become the Supreme Court judgment had no impact on share prices this morning – Wall Street knows quite how much cash these companies are sitting on.

If that news wasn’t bad enough however, there is a bigger tax issue hovering over Big Tech: the so-called digital tax threatened by the European Union, which is also fed up with companies like Google, Apple and Facebook paying almost no tax in their countries because of creative accounting through subsidiaries.

That digital tax became more likely this month after the US walked away from discussions at the Organisation for Economic Co-operation and Development (OECD) that were focused on developing a global tax agreement for digital companies.

With the OECD approach faltering, the EU has already made it clear that it will introduce its own version of a digital tax that is likely to make tech giants pay much more to countries in which they operate. Those new taxes are expected to kick in at the start of 2021.

Source: Big Tech on the hook for billions in back taxes after US Supreme Court rejects Altera stock options case hearing • The Register

‘BlueLeaks’ Exposes Files, personal and banking details, emails from Hundreds of Police Departments spanning 24 years

Hundreds of thousands of potentially sensitive files from police departments across the United States were leaked online last week. The collection, dubbed “BlueLeaks” and made searchable online, stems from a security breach at a Texas web design and hosting company that maintains a number of state law enforcement data-sharing portals.

The collection — nearly 270 gigabytes in total — is the latest release from Distributed Denial of Secrets (DDoSecrets), an alternative to Wikileaks that publishes caches of previously secret data.

A partial screenshot of the BlueLeaks data cache.

In a post on Twitter, DDoSecrets said the BlueLeaks archive indexes “ten years of data from over 200 police departments, fusion centers and other law enforcement training and support resources,” and that “among the hundreds of thousands of documents are police and FBI reports, bulletins, guides and more.”

Fusion centers are state-owned and operated entities that gather and disseminate law enforcement and public safety information between state, local, tribal and territorial, federal and private sector partners.

KrebsOnSecurity obtained an internal June 20 analysis by the National Fusion Center Association (NFCA), which confirmed the validity of the leaked data. The NFCA alert noted that the dates of the files in the leak actually span nearly 24 years — from August 1996 through June 19, 2020 — and that the documents include names, email addresses, phone numbers, PDF documents, images, and a large number of text, video, CSV and ZIP files.

“Additionally, the data dump contains emails and associated attachments,” the alert reads. “Our initial analysis revealed that some of these files contain highly sensitive information such as ACH routing numbers, international bank account numbers (IBANs), and other financial data as well as personally identifiable information (PII) and images of suspects listed in Requests for Information (RFIs) and other law enforcement and government agency reports.”

[…]


22
Jun 20

‘BlueLeaks’ Exposes Files from Hundreds of Police Departments

Hundreds of thousands of potentially sensitive files from police departments across the United States were leaked online last week. The collection, dubbed “BlueLeaks” and made searchable online, stems from a security breach at a Texas web design and hosting company that maintains a number of state law enforcement data-sharing portals.

The collection — nearly 270 gigabytes in total — is the latest release from Distributed Denial of Secrets (DDoSecrets), an alternative to Wikileaks that publishes caches of previously secret data.

A partial screenshot of the BlueLeaks data cache.

In a post on Twitter, DDoSecrets said the BlueLeaks archive indexes “ten years of data from over 200 police departments, fusion centers and other law enforcement training and support resources,” and that “among the hundreds of thousands of documents are police and FBI reports, bulletins, guides and more.”

Fusion centers are state-owned and operated entities that gather and disseminate law enforcement and public safety information between state, local, tribal and territorial, federal and private sector partners.

KrebsOnSecurity obtained an internal June 20 analysis by the National Fusion Center Association (NFCA), which confirmed the validity of the leaked data. The NFCA alert noted that the dates of the files in the leak actually span nearly 24 years — from August 1996 through June 19, 2020 — and that the documents include names, email addresses, phone numbers, PDF documents, images, and a large number of text, video, CSV and ZIP files.

“Additionally, the data dump contains emails and associated attachments,” the alert reads. “Our initial analysis revealed that some of these files contain highly sensitive information such as ACH routing numbers, international bank account numbers (IBANs), and other financial data as well as personally identifiable information (PII) and images of suspects listed in Requests for Information (RFIs) and other law enforcement and government agency reports.”

The NFCA said it appears the data published by BlueLeaks was taken after a security breach at Netsential, a Houston-based web development firm.

“Preliminary analysis of the data contained in this leak suggests that Netsential, a web services company used by multiple fusion centers, law enforcement, and other government agencies across the United States, was the source of the compromise,” the NFCA wrote. “Netsential confirmed that this compromise was likely the result of a threat actor who leveraged a compromised Netsential customer user account and the web platform’s upload feature to introduce malicious content, allowing for the exfiltration of other Netsential customer data.”

Source: ‘BlueLeaks’ Exposes Files from Hundreds of Police Departments — Krebs on Security

Machine-learning models trained on pre-COVID data are now completely out of whack, says Gartner

Machine learning models built for doing business prior to the COVID-19 pandemic will no longer be valid as economies emerge from lockdowns, presenting companies with new challenges in machine learning and enterprise data management, according to Gartner.

The research group has reported that “the extreme disruption in the aftermath of COVID-19… has invalidated many models that are based on historical data.”

Organisations commonly using machine learning for product recommendation engines or next-best-offer, for example, will have to rethink their approach. They need to broaden their machine learning techniques as there is not enough post-COVID-19 data to retrain supervised machine learning models.

Advanced modelling techniques can help

In any case the ‘new normal’ is still emerging, making the validity of prediction models a challenge, said Rita Sallam, distinguished research vice president at Gartner.

“It’s a lot harder to just say those models based on typical data that happened prior to the COVID-19 outbreak, or even data that happened during the pandemic, will be valid. Essentially what we’re seeing is [a] complete shift in many ways in customer expectations, in their buying patterns. Old processing, products, customer needs and wants, and even business models are being replaced. Organisations have to replace them at a pace that is just unprecedented,” she said.

Source: Machine-learning models trained on pre-COVID data are now completely out of whack, says Gartner • The Register

Beidou: China completes rival to the US-owned GPS system

China sent the last satellite to space on Tuesday to complete its global navigation system that will help wean it off U.S. technology in this area.

The network known as Beidou, which has been in the works for over two decades, is a significant step for China’s space and technology ambitions.

Beidou is a rival to the U.S. government-owned Global Positioning System (GPS), which is widely-used across the world.

Experts previously told CNBC that Beidou will help China’s military stay online in case of a conflict with the U.S. But the launch is also part of Beijing’s push to increase its technological influence globally.

Source: Beidou: China completes rival to the US-owned GPS system

tens of thousands of mobile numbers of 50+ year olds sold for whatsapp fraud

Names, adresses and mobile numbers have been sold for fraud using WhatsApp. Most of these numbers come from callcentres, mainly those selling energy contracts. The fresher a lead is, the more they are worth: betwween 25 cents and 2 euros. The money is usually transferred through mules, who keep a percentage of the proceeds.

Source: ’06-nummers van tienduizenden vijftigplussers doorverkocht voor WhatsAppfraude’ – Emerce