Industry 4.0 why smart manufacturing is moving closer to the edge – The Register

Sponsored Feature In the first two of three articles on why and how service providers and enterprises are taking advantage of the edge, we outlined edge market growth, and how open source software plays a key role in delivering the data processing advantages of edge working.

We also outlined edge use cases and laid out how pre-configured and validated configurations of Red Hat software for edge deployments were freely available from the open source software vendor through its Validated Patterns reference architectures.

In this third and final piece, we will take a close look at Industry 4.0, and why smart manufacturing is moving closer to the edge, with the help of key industry partnerships.

But first, let's recap the reasons why enterprises are adopting edge infrastructure in increasing numbers.

For many enterprises, it may be more efficient and cost-effective to process data close to where it is needed, at the edge. Edge computing enables quicker decisions as the data is processed and analyzed where it is generated - ie not in a remote datacenter or in the cloud. Edge installations also mitigate the intermittent connectivity and network latency issues that remote data processing often entails.

Edge deployments also aid operational resiliency and efficiency. For example, the network capacity costs fall as the amount of traffic generated by the organization is reduced. That can be supplemented by improvements in sustainability and overall energy efficiency, both of which can contribute to meeting strategic carbon neutrality targets. And of course, edge computing allows sensitive or proprietary data to remain within the organization, as opposed to traversing to the cloud.

Open source edge solutions are key to modernizing infrastructure, improving productivity and easing the management of operations, as they better support the integration between services and usually prove to be more scalable and cost-efficient.

This is no different when it comes to the transformation of operations technology environments that is the hallmark of the Fourth Industrial Revolution, often dubbed Industry 4.0. Advances in manufacturing have been driven by the development of various emerging technologies over the last few years.

With Industry 4.0, new technologies are being built into the factory to drive increased automation. This all leads to potentially smart factories that can, for instance, benefit from predictive maintenance, as well as improved quality assurance and worker safety.

At the same time, existing data challenges can be overcome. Companies operating across multiple locations often struggle to remove data silos and bring IT and OT (operational technology) together. An edge based on an open hybrid infrastructure can help them do this, as well as solving other problems.

These problems include reducing latency as a result of supporting a horizontal data framework across the organization's entire IT infrastructure, instead of relying on data being funneled through a centralized network that can cause bottlenecks. Edge computing opens hybrid-aligned to cloud services can also reduce the amount of mismatched and inefficient hardware that has gradually built up, and which is located in often tight remote spaces too.

Mark Wohlfarth, Vertical GTM Strategy, Edge Computing at Red Hat, says: "Industry 4.0 is fundamentally about transforming operational technology environments, delivering cheaper and more effective computing, with improved decision-making from better analytics - all from locally deployed sensors deployed at the edge."

He adds: "But to deliver the potential benefits, you need more than just robust infrastructure, you need the full power of the existing OT ecosystem to support the transformation."

In February 2021, Siemens, IBM and Red Hat came together to deliver an open, flexible and more secure solution for manufacturers and plant operators, which drives real-time value from operational data at the edge. In one month, a single manufacturing site can generate more than 2,200 terabytes of data, according to a report from IBM. Yet most of that data usually goes unanalyzed.

Through the joint initiative, Siemens Digital Industries Software is applying IBM's open hybrid cloud approach, built on Red Hat OpenShift, to extend the deployment flexibility of Siemens' MindSphere, an industrial IoT as-a-service.

Customers use MindSphere to collect and analyze real-time sensor data from products, plants, systems and machines, in order to drive optimization across production assets, manufacturing processes and products along the entire value chain. The partners said they will enable customers to run MindSphere on-premises at the edge to unlock speed and agility benefits in factory and plant operations.

In November 2021, Intel and Red Hat collaborated to bring Industry 4.0 transformation to smart manufacturing and the energy sector. This combined Red Hat's open source software and Intel's hardware architecture and software tool-sets.

The aim, they said, is to improve the management and performance of industrial control systems (ICS). The target areas include private 5G networks; open manufacturing platforms (OMP); software-defined automation and control functions at utilities, to help reduce the number of devices in substations, for instance; and autonomous mobile robotics (AMR), by integrating customer automation software with an edge server.

By coupling Intel Edge Controls for Industrial (Intel ECI) and Intel Edge Insights for Industrial (Intel EII) with Red Hat open hybrid cloud technologies, said the partners, ICS vendors, hardware providers, software developers and solution providers are being offered a "holistic solution". This spans from real-time shop floor control and artificial intelligence/machine learning (AI/ML) to full IT manageability -through fully integrating OT and IT systems.

Intel has developed a software reference architecture with Intel ECI that creates an open, portable platform to power autonomous operations and support AI/ML models at the edge. This, it says, can be updated "without impacting the reliability or resilience of the organization." Red Hat is helping ICS vendors to integrate Intel ECI into their offerings.

Along with Red Hat Enterprise Linux and Red Hat OpenShift, Red Hat Advanced Cluster Management for Kubernetes and Red Hat Ansible Automation Platform are bundled with the Intel platforms, to provide the management and automation needed to "drive visibility and consistency across the organization's entire domain", says Red Hat.

In the energy sector, for instance, how do you manage edge computing sensors at scale, moving from many thousands of deployments to perhaps millions of them? And, in the remote environments that have to be managed, how do you know that every edge device is even still there?

Oil and gas companies commonly use temperature, flow rate and pressure sensors to aid upstream exploration and production by monitoring the operational status of rigs and wells used in the drilling and extraction process, for example. Connected plungers and liquid level sensors can also improve efficiency by helping to clear the clogged pipes which impede natural gas production.

These firms also have to work out how to patch device vulnerabilities, as well as efficiently install new applications in the field.

Recently, an oil supermajor needed to determine how an operating system (OS) could provide IT capabilities while also solving field-level issues encountered during exploration and production. The IT team also needed to devise a way to load an OS, designed to run in the datacenter, onto smaller devices that live in the field.

Among other considerations, the team looked at how to perform patching, maintain the security of the OS itself, and ensure recoverability. These, and other challenges, would require new approaches, because IT staff could not just walk to a server as they would in a datacenter.

The company turned to Red Hat for help. The Red Hat team then worked with the energy firm to define the necessary components needed to address its needs and achieve its IoT vision.

Furthermore, the partners said they created a blueprint for these improved edge capabilities for the entire oil and gas industry in an open way.

Here, we have shown why smart manufacturing is moving closer to the edge, and how key industry partnerships are allowing it to happen, through an open hybrid infrastructure that ties all data together - to deliver faster, reliable and more comprehensive business insights.

Sponsored by Red Hat.

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Industry 4.0 why smart manufacturing is moving closer to the edge - The Register

The Fallout of Edward Snowden and his Leaked Documents …

On June 21, 2021, Edward Snowden celebrated his 38th birthday in Russia. Hes been in the country for over eight years, having been granted permanent residence in the country in October 2020 [1]. Snowden, an American, has not returned to his native country since leaking millions of classified documents detailing the massive surveillance programs that the United States undertook.

While many have heard Edward Snowdens name, the programs that he uncovered have seemingly faded in the public consciousness in recent years. Snowdens reveal of massive global surveillance programs in 2013 was a wake-up call for many Americans, when modern technology and digital communication were truly becoming everyday tools at work and home. His leaked documents highlighted how so many Internet activities are never truly private.

Snowdens Career Beginnings and Disillusionment

Snowden began his career by joining the Army in May 2004, but was discharged four months later due to broken legs he suffered in a training accident [2]. Following his short time in the Armed Forces, he gained a position as a security specialist at an NSA-contracted facility, beginning his time in the intelligence community. He then joined the CIA in 2006 until 2009, years that disillusioned his faith in Americas intelligence community [3]. He described an incident where the CIA purposefully intoxicated a Swiss banker and encouraged him to drive home. When the banker was arrested for drunk driving, the CIA offered him help in exchange for becoming an informant.

Following his resignation from the CIA, Snowden worked as an NSA contractor in Japan with high-level security clearance for three years before moving to Hawaii to join Booz Allen Hamilton, another private contractor. He joined Booz Allen Hamilton with the sole intent of gaining clearance to new classified files. After just a few weeks on the job, Snowden gained access to the classified material, downloaded it on a flash drive, and fled the United States shortly afterward. Finally, he distributed the materials to media outlets he trusted, particularly The Guardian, with the first revelations posted publicly in June 2013.

What Programs Did Snowden Reveal?

The biggest revelation in Snowdens leaked documents was the existence of a National Security Agency program called PRISM. Under the program, the NSA had direct access to the servers of the biggest tech companies, including Google, Apple and Facebook without their knowledge [4]. Using this direct access, the NSA could collect users emails, search history, and file transfers without a court order. Even if you were an American citizen, you could have been subject to this surveillance if your messages ever touched a non-American server.

Snowden explained the horrifying simplicity of the NSAs programs, stating I, sitting at my desk, [could] wiretap anyone, from you or your accountant, to a federal judge or even the president, if I had a personal email [5]. This allegation was initially denied by government officials, yet leaked documents showed a program called XKeystore allowed analysts to search enormous databases with just one piece of identifying information [5].

In addition, Snowden revealed NSA phone-tapping of allied leaders, including German Chancellor Angela Merkel and then-Israeli Prime Minister Benjamin Netanyahu [6]. These revelations caused an uproar among American allies, particularly in Europe. The NSA also monitored various charity organizations and businesses including UNICEF, the United Nations agency dedicated to providing aid to children worldwide and Petrobras, Brazils largest oil company.

The Legal Justification

All of these programs were justified by Section 702 of the FISA Amendments Act, a bill signed in 2008 that amended the original Foreign Intelligence Surveillance Act of 1978. The 2008 amendment rid FISA of its warrant requirement, allowing the NSA to spy on any foreign communications without a court order. In practice, this meant any communications that touched a foreign server were legally allowed to be collected.

Snowden explained Even if you sent [a message] to someone within the United States, your wholly domestic communication between you and your wife can go to New York to London and back and get caught up in the database [7]. Because the data had reached a foreign server, no matter how short of a time, the NSA was able to collect, store and potentially analyze that data through Section 702s legal framework.

The Effects

A Washington Post investigation found that approximately 90% of account holders in a leaked data cache were ordinary Internet users, with just a tenth of the account holders being NSA targets [8]. These account holders were subject to daily tracking, with NSA analysts having access to intimate conversations unrelated to national security. Put simply, the NSA had access to millions of Americans personal data, able to be perused by low-level analysts with little more than an email address.

In addition, government officials responses to Snowdens leaks were swift and severe. Then-Secretary of State John Kerry stated that Snowdens leaks told terrorists what they can now do to (avoid) detection [9]. Various other officials agreed with Kerrys assessment, stating that suspected terrorists had begun changing their communication tactics following Snowdens revelations [10]. While the NSA claimed that digital surveillance helped prevent over 50 potential terrorist events, then-President Obama stated that other methods could have prevented those attacks [11].

Data Privacy vs. Protection

Above all, the NSA has been criticized for conducting digital surveillance beyond the scope of national security. While government officials have stated that the surveillance saved countless lives by preventing terrorist attacks, claims that these programs solely stopped potential terror attacks are dubious. The inappropriate collection of everyday Americans data, however, is undeniable. Millions of Americans emails, video calls and search histories were readily available to low-level NSA analysts. While Edward Snowden remains a highly controversial figure today, his revelations of mass global surveillance undoubtedly increased Americans concern for data privacy. And while some still view Snowden as a criminal or traitor, some see him as a brave whistleblower who revealed just how exposed our data, and our lives, can be.

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The Fallout of Edward Snowden and his Leaked Documents ...

What is a Whistleblower? – The National Law Review

Wednesday, April 27, 2022

When hearing the term whistleblower, some of the names that may automatically come to mind include famous whistleblowers that have been covered in the news: Edward Snowden, the controversial whistleblower who leaked documents regarding National Security Agency surveillance programs; to Deep Throat of Watergate, the FBI whistleblower who would later be named as Mark Felt; and even Frances Haugen, the recent Facebook whistleblower.

These whistleblower cases may have been highly publicized across news stations, but they are some of the many whistleblowers across a number ofdifferent industrieswho help uncover fraud and corruption and in turn, help make America a more equitable place.

Awhistlebloweris a private individual who comes forward with evidence regarding fraud, corruption, waste, or abuse and reports it to law enforcement or the appropriate government agency. Whistleblowers help expose illegal or unethical behavior by providing inside information that otherwise would not have become known to the public.

Whistleblowers are also known as qui tam relators and are usually employees, former employees, contractors, freelancers, or other individuals with non-public information regarding crimes, unethical behavior, corruption, or fraud against the government. Common examples of whistleblowers include a healthcare worker that witnesses medical billing fraud or a defense contractor employee noticing inferior products being substituted and sold to the U.S. government.

Whistleblowers are incentivized to come forward with the potential of receiving a financial reward by various state and federal laws which also serve to provide whistleblowers with protection against retaliation.

Abraham Lincoln passed the False Claims Act (FCA) in 1863 as a way to encourage citizens to report the fraud and waste that was taking place during the Civil War. The FCA, also known as Lincolns Law, contains a qui tam provision that allows private citizens to bring forth lawsuits on behalf of the government against entities who have committed fraud and share in the financial recovery if the case is successful. According to theDepartment of Justice, the government recovered more than $70 billion in FCA lawsuits between 1986 and 2021.

Whistleblowers throughout history have helped to exposehealthcare fraud, environmental regulation violations, government contract fraud, violations of the Motor Vehicle Safety Act,tax fraud, and more. These types of illegal and unethical activities can harm taxpayers that fund government programs as well as the general public, and these crimes may otherwise go unknown without the bravery of whistleblowers.

Whistleblower lawsuits that are filed under the FCA usually involve healthcare fraud andgovernment contractor fraud. Other types of whistleblower lawsuits involvesecurities fraud,customs/tariffs fraud, tax fraud, and environmental crimes.

Some of the most common whistleblower claims include:

Submitting false claims and information to procure unwarranted government funds, grants, loans, and contracts

Violating the terms of a government contract by providing substandard goods or services

Gross waste of funds, including using grant money or PPP loans for personal gain

Healthcare billing fraud, including billing for services not provided, double billing, upcoding, and more

Offering bribes or providing kickbacks in exchange for government-funded business

Presenting a danger to public health or safety, including designing and/or failing to recall dangerous automobiles and parts

The majority of whistleblowers are not splashed across the news like Ed Snowden. In fact, most remain anonymous, which helps protect them from retaliation.

The U.S. has many laws on the federal and state levels that are meant to protect both private and public sector employees from employer retaliation for becoming a whistleblower. The FCA protects whistleblowers who report fraud against the government from retaliation, while federal employees who report corruption or misconduct are protected from retaliation by theWhistleblower Protection Act. Other whistleblower laws that afford protections include but are not limited to theSarbanes-Oxley Act, theOccupational Health and Safety Act, theClean Air Act, and theToxic Substances Control Act.

Types of employer retaliation prohibited by whistleblower protection laws include termination, suspension, demotion, threats, harassment, withholding pay or benefits, or any other discrimination directed at an employee or contractor for their actions as a whistleblower. Whistleblowers who are retaliated against have the right to bring a separate lawsuit against their employer for damages relating to the retaliation, including reinstatement, back pay, attorneys fees, and more.

While the whistleblower does not specifically have to witness the fraud or crime take place, it is vital in all qui tam lawsuits that the whistleblower has thorough and specific evidence that proves the fraudulent or illegal behavior took place. Ideally, the evidence the whistleblower gathers should answer the following questions:

Who is committing fraud or a crime, and who knows about it?

What fraud, crime, or violation took place?

When and where did the fraud or illegal behavior occur?

How was the crime or fraud committed, and is it ongoing?

How was the public affected by what took place?

Under the FCA as well as other whistleblower programs including the IRS, SEC, CFTC, and NHTSA, whistleblowers who provide information that leads to the government successfully settling the matter are rewarded between 15 and 30 percent of the recovery. In a multi-million dollar qui tam settlement, thewhistleblowers financial rewardcan be significant.

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What is a Whistleblower? - The National Law Review

Pegasus in Downing Street? Commercial Spyware and Espionage Competition – The National Interest Online

States spy on each other. This fact is neither shocking nor surprising in itself. There are plenty of good reasons why states do it, even if not all states are equal in their relative intelligence power. So, you would think by now that we would have a high bar for being surprised or shocked by revelations about states spying on each other.

Certainly, when states become victims of espionage their responses are shaped by a number of factors, including the strategic context (is the transgressor an adversary or an ally?) and the severity of the case (a one-off or a sustained campaign?). Domestic public opinion might be inflamed by revelations of espionage victimhood, or else barely flicker with quickly-fading attention. Throughout, victim states will recognize that the basic problemthat they are targets of foreign espionage operationsis the mirror image of their own pursuit of intelligence gain against other states. States are not, therefore, shocked or surprised by the existence of foreign espionage: they do their best to counter it and remediate and respond to it where they have to. As indicated by recent comments from FBI director Christopher Wray about the magnitude of the threat posed by Chinese espionage, recognizing the perennial nature of espionage doesnt necessarily imply complacency towards it.

The high bar to surprise or shock holds good even in the case of newer forms of espionage, such as digital or cyber spyingthat is, establishing access to digital data for intelligence gain, whether that data is stored at rest somewhere (on a device like a mobile phone or laptop), or else by intercepting data whilst it is traversing a network. Nearly a decade after Edward Snowdens revelations, few people can be surprised that some states have not only the ambition but also the capabilities to derive significant intelligence gains from information and communications technology.

Another obvious point is that, given much of this global technological infrastructure is built, owned, and operated by the private sector, the practice of states spying on each other inevitably involves relationshipscommercial, collaborative, or competitivebetween governments and companies. These relationships might be transactionalthe procurement by governments of a service or toolor they might be framed by legal requirement, compelling companies to comply with lawful requests for access. Equally, they might involve the non-consensual acquisition of data from companies by government intelligence agencies, or indeed the recognition that these companies are useful vectors of attack, so-called supply chain attacks such as the SolarWinds case.

The private sectors importance also extends to digital spying by the state on its own citizens: sovereign capabilities for domestic surveillance are more likely to be developed by the private sector than the state itself. States with a thriving tech sector undoubtedly have had an advantage in this respect, with a domestic network of trusted companies to develop surveillance tools and systems. But, over decades, the market for commercial spyware has become truly global.

At its best, this global market helps to fill an important gapproviding those states that would otherwise lack the technical capabilities with the ability to counter severe national security threats such as terrorism or serious crime. But at its worst, the capabilities procured from the global marketplace can enable repressive states to target dissidents, either passively or to enable operations against them.

Many companies are active in this marketplace, but one, in particular, has become a focal point for global criticism of commercial spyware: the Israeli company NSO Group and particularly its Pegasus spyware. Pegasus is reportedly so good at what it doesfor example, providing zero-click access to a targeted iPhone, meaning no need for targets to fall for malware-laden messagesthat many states were lining up to procure its services. This customer interest was great for the companyand presumably also for the Israeli government. The government issued export licenses for the spyware and potentially was able to integrate this commercial success into its wider diplomatic strategyessentially, what many states would do in a similar position.

The problem facing the companywhether it was recognized as such or notwas how to contain the potentially negative consequences of this burgeoning customer interest. New contracts were one thing, but would its values, future sales, and potentially its continued existence as a company be compromised if its new customers used Pegasus to spy on innocent subjects, to enable victimization and human rights abuses? To this questionwe can add one other, perhaps more strategically pertinent for the Israeli government, and potentially devastating in repercussions for businesses like NSO Group: what if Pegasus was used, not against a clients domestic targets, but against foreign governments, including governments with which Israel has close diplomatic ties?

This is indeed what recent reporting suggests has happened, with revelations in December 2021 that Pegasus had been used to target U.S. diplomats working overseas, and in more recent reporting that a range of European officials, including someone from the UK government working in the prime ministers office (10 Downing Street), had also been targeted. In the UK case, independent researchers suspected the state client using Pegasus to target the UK was the United Arab Emirates (UAE). In diplomatic terms, the UAE is a relatively close regional partner of the UKone with a controversial and widely-reported broader strategy of harnessing commercial spyware services to enhance its national intelligence power.

The same reports that highlighted the reported breach of communications in 10 Downing Street also indicated that Pegasus customers had also successfully used it in 2020 and 2021 against UK diplomatswith the UAE, India, and Cyprus identified as the potential state actors. All these states are regarded as partnersindeed, just this month the UK prime minister, Boris Johnson, signed agreements with his Indian counterpart, Narendra Modi, including an agreement to improve cybersecurity cooperation.

This juxtaposition suggests that states take a broad view of such revelations, placing them in broader strategic context. This is similar in the U.S. case, where bilateral relations with Pegasus-customer states appear relatively unharmed. In contrast, the United States has pursued more targeted responses against NSO Group and other firms, and might go further to address foreign commercial spyware more generally.

Collectively, this might suggest that we are at some kind of transitional point in the relationship between states and commercial spyware. A global market that has developed quickly and in the shadows is now very much more salient and starting to provoke some pushback from states. And yet, whilst the fates of a single company like NSO Group can rise and fall, it is very difficult to see the wider industry enjoying anything other than continued success.

States are not going to stop wanting to spy on each other, or on other, non-state targets. The market that has grown to cater to this perennial state practice is too valuable, too globally dispersed, and likely also too covert to be readily amenable to collective, verifiable efforts to curb it. And, in the absence of effective constraints, commercial spyware will continue to level the playing field between state actors in the competition for intelligence gains. This will create both opportunities to be exploited and challenges that must be overcomean ever-present feature of intelligence competition between states throughout history.

Joe Devanny is a Lecturer in the Department of War Studies at Kings College London. He writes here in a personal capacity. He can be contacted on Twitter @josephdevanny.

Image: Reuters.

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Pegasus in Downing Street? Commercial Spyware and Espionage Competition - The National Interest Online

Assange and Trump, Partners – The Bulwark

Following an extradition order issued yesterday by a British court, Julian Assangefounder of WikiLeaks and willing agent of Russian active measuresis one step closer to facing American justice.

Assange is just the latest Donald Trump satellite to face criminal charges, after Michael Cohen, Steve Bannon, Roger Stone, Paul Manafort, and others. The question cannot be avoided: What about the ringleader himself? It must be counted an irony of history that a sizable fraction of dyed-in-the-wool leftists, assisted by a few preposterous libertarians, who labored to turn Assangeand later Edward Snowdeninto folk heroes during the Obama administration found themselves cheering Trump and lauding his socialist principles. It is fitting and proper that Assange answer for his crimes, but Trump presents a larger political problem that mere criminal justice cannot solve.

The Trump-Assange fringe has found its primary cause in the rejection of American empire and has been sympathetic to Americas enemies around the world. Bizarrely for a movement proclaiming fidelity to transparent government, it has greeted with enthusiasm and even active support Vladimir Putins hostility to free government, sabotage of democracy in the West, subversion of democracy in (and war on) Ukraine, and extinguishing of democracy in Russia. (Little wonder that ever since Snowden quit his country with his ill-gotten goods, he has enjoyed a welcome refuge in Putins Russia.)

Anti-communist crusaders like Richard Nixon used to accuse their political opponents of being pinki.e., half red, or sympathetic to communism. It is remarkable that one of the most consequential allies of the anti-American reactionary left leads the American right. Before Trumps ascendancy, the Republican party championed American global leadership. Now its an illiberal cult espousing the narrow nationalist themes of America First. Trumps political movement remains committed to the ruination of Americas institutions and the retreat of its global influence. Under his sway, the Republican party views Joe Biden as a greater threat to the country than Putins Russia. Far from believing, as Republican presidents used to believe, that America was and ought to be a beacon of democracy in the world, Trumps Republicans are intent on destroying democracy at home while admiring foreign scourges like Viktor Orbn.

The alliance between the reactionary left and the unhinged right has sought to corrupt the American republic and inhibit its power in the world. It should come as no surprise that the greatest opponents of American activism on the world stage are also the most corrosive to its internal politics: At its noblest, Americas foreign policy is based, however imperfectly, on the principles of freedom and democracy. Although not guided entirely by altruistic considerations, U.S. foreign policy is beyond comparison with the paranoid, vicious realpolitik that characterizes Russian or Chinese behavior in the world. It is the distinctly American internationalism, blending realism with idealismcoercion against despots and a basic concern for human rightsthat leaves the new left and the old right out of sorts.

Both Assange and Trumpthe two were practically teammates in 2016are unburdened by any thoughtful consideration of the national interest and lack any moral constraints in the pursuit of their overriding objectivesthe end of American hegemony and personal enrichment at the expense of the country, respectively. Assange faces charges as a dangerous foreign agent for attacking the republic from without as Trump subverted it from within.

Assange evidently aspires to live in a world without authority and in which no country (save, one imagines, his Russian benefactors) can act to protect its interests. The proper response to foreign agents who filch official secrets and interfere with elections is to arraign them for judgment before a court of law.

Trump, too, evidently aspires to live in a world without any authority but his own, or those of his role models: Putin, Xi, Kim, and his favorite dictator, Sisi. In this sense, Trumps first impeachmentover withholding foreign aid to Ukraine in exchange for personal political favorsrevealed the same deep-seated contempt for democracy that was on display in his second impeachment. The proper response to such anti-democratic politicians is for responsible parties and citizens to pass them over.

The cause of democracy and the rule of law will soon be offered two opportunities, one legal and the other political. In short order, Assange will find himself in an American courtroom, answering for his outrages. And voters will have another opportunity to reject Trumpor whoever is elevated by the anti-democratic faction ascendant on the rightat the voting booth.

In the realm of law and of politics, legitimate power finds itself under several forms of overt and covert attack. Its partisans dare not squander the opportunity to offer it a vigorous defense.

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Assange and Trump, Partners - The Bulwark

Russia Is Losing a War Against Hackers Stealing Huge Amounts of Data – The Intercept

Russia isknown for itsarmy of hackers, but sincethe start of itsinvasion of Ukraine, dozens of Russian organizations including government agencies, oil and gas companies, and financial institutions have been hacked,with terabytes of stolen data leaked onto the internet.

Distributed Denial of Secrets, the transparency collective thats best known for its 2020release of 270gigabytes of U.S. law enforcement data (in the midst of racial justice protests following the murder of George Floyd),has become the de facto home of the hacked datasets from Russia.The datasets are submitted to DDoSecretsmostly by anonymous hackers, and those datasets are then made available to the public on the collectives website and distributed using BitTorrent. (I am an adviser to DDoSecrets).

The flood of Russian data has meant a lot of sleepless nights, and its truly overwhelming, Emma Best, co-founder of DDoSecrets, told The Interceptvia an encrypted messaging app. In its first 10 years, WikiLeaks claimed to publish 10 million documents. In the less than two months since the invasion began, weve published over 6 million Russian documents and it absolutely feels like it.

After receiving a dataset, DDoSecrets organizes and compresses the data; it then starts distributingthe data using BitTorrent for public consumption, publicizes it, and helps journalists at a wide range of newsrooms access and report on it. DDoSecrets has published about 30 hacked datasets from Russia sinceits invasion of Ukraine began in late February.

The vast majority of sources who provided the hacked Russian data appear to be anonymous individuals, many self-identifying as part of the Anonymous hacktivist movement. Some sources provide email addresses or other contact information as part of the dumped data, and some, like Network Battalion 65, have their own social media presence.

Still, with so many datasets submitted by anonymous hackers, its impossible to be certain about their motives or if theyre even truly hacktivists. For instance, in 2016 hackers compromised the network of the Democratic National Committee and leaked stolen emails to WikiLeaks in an attempt to hurt Hillary Clintons presidential campaign. Guccifer 2.0, the hacker persona responsible, claimed to be a loneactor but was later revealed to be an invention of the GRU, Russias military intelligence agency.

For this reason, the recent Russian datasets published by DDoSecrets includea disclaimer: This dataset was released in the buildup to, in the midst of, or in the aftermath of a cyberwar or hybrid war. Therefore, there is an increased chance of malware, ulterior motives and altered or implanted data, or false flags/fake personas. As a result, we encourage readers, researchers and journalists to take additional care with the data.

On February 26, two days after Russias invasion started, DDoSecrets published 200 gigabytes of emails from the Belarus weapons manufacturer Tetraedr, submitted by the hacktivist persona Anonymous Liberland and the Pwn-Br Hack Team. Belarus is a close ally to Russia in its war against Ukraine. A message published with the dataset announced #OpCyberBullyPutin.

OnFebruary 25, the notorious Russian ransomware gang known as Conti publicly expressed its support for Russias war, and two days later, onFebruary 27, an anonymous Ukrainian security researcher who had hacked Contis internal infrastructure leaked two years of Conti chat logs,along withtraining documentation, hacking tools, and source code from the criminal hackers. I cannot shoot anything, but I can fight with a keyboard and mouse, the anonymous researcher told CNN on March 30 before he safely slipped out of Ukraine.

In early March, DDoSecrets published 817 gigabytes of hacked data from Roskomnadzor, the Russian federal agency responsible for monitoring, controlling, and censoring Russian mass media. This data specifically came from the regional branch of the agency in the Republic of Bashkortostan. The Intercept made this dataset searchable and shared access with independent Russian journalists from Meduza who reported that Roskomnadzor had been monitoring the internet for antimilitarism since at least 2020. In early March, Roskomnadzor began censoring access to Meduza from inside Russia due to systematic spread of fakes about the special operation in Ukraine, a spokesperson for the agency told the Russian news site RIA Novosti.

Thehacks continued. In mid-March, DDoSecrets published 79 gigabytes of emails from the Omega Co., the research and development wing of the worlds largest oil pipeline company, Transneft, which is state-controlled in Russia.In the second half of March, hacktivism against Russia began to heat up. DDoSecrets published an additional five datasets:

On the last day of March, the transparency collective also published 51.9 gigabytes of emails from the Marathon Group, an investment firm owned by sanctioned Russian oligarch Alexander Vinokurov.

On the first day of April, DDoSecrets published 15 gigabytes of emails from the charity wing of the Russian Orthodox Church. Because the emails might include sensitive and privateinformation from individuals, DDoSecrets isnt distributing thisdatato the public. Instead, journalists and researchers can contact DDoSecrets to request a copy of it.

On April 3, DDoSecrets published 483 gigabytes of emails and documents from Mosekspertiza, a state-owned corporation that provides expert services to the business community in Russia.On April 4, DDoSecrets published 786 gigabytes of documents and emails from the All-Russia State Television and Radio Broadcasting Co., referred to with the English acronym VGTRK. VGTRK is Russias state-owned broadcaster; itoperates dozens of television and radio stations across Russia, including regional, national, and international stations in several languages. Former employees of VGTRK told thedigital publication Colta.ru that the Kremlin frequently dictated how the news should be covered.Network Battalion 65 is the source for both the VGTRK and Mosekspertiza hacks.

Russias legal sector also got hacked. On April 8, DDoSecrets published 65 gigabytes of emails from the law firm Capital Legal Services. The persona wh1t3sh4d0wsubmitted the data to the transparency collective.

In the following days, DDoSecrets published three more datasets:

By April 11, DDoSecrets had published another three datasets:

In mid-April, DDoSecrets published several datasets from the oil and gas industries:

On April 16, DDoSecrets published two more datasets:

Just during the last week, DDoSecrets published these datasets:

Earlier today, DDoSecrets published 342 gigabytes of emails from Enerpred, the largest producer of hydraulic tools in Russia that works in the energy, petrochemical, coal, gas and construction industries.

Despite the massive scale of these Russian data leaks, very few journalists have reported on them so far. Since the war began, Russia has severely clamped down onits domestic media, introducing penalties of years in prison for journalistswho use the wrong words when describingthe war in Ukraine like calling it a war instead of a special military operation. Russia has also ramped up its censorship efforts, blocking Twitter and Facebook and censoring access to international news sites, leaving the Russian public largely in the dark when it comes to views that arent sanctioned by the state.

One of the barriers for non-Russian news organizations is language: The hacked data is principally in Russian. Additionally, hacked datasets always come with considerable technical challenges. The Intercept, which was founded in part to report on the archive of National Security Agency documents leaked by Edward Snowden, has been using our technical resources to build out tools to make these Russian datasets searchable and then sharing access to these tools with other journalists. Russian-speaking journalists from Meduza which is forced to operate in Latvia to avoid the Kremlins reach have already published a story based on one of the datasets indexed by The Intercept.

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Russia Is Losing a War Against Hackers Stealing Huge Amounts of Data - The Intercept

Baseten Gives Data Science and Machine Learning Teams the Superpowers They Need to Build Production-Grade Machine Learning-Powered Apps -…

Baseten formally launched with its product that makes going from machine learning model to production-grade applications fast and easy by giving data science and machine learning teams the ability to incorporate machine learning into business processes without backend, frontend or MLOps knowledge. The product has been in private beta since last summer with well-known brands that have used it for everything from abuse detection to fraud prevention.It is in public beta at this time.

Its clear that the performance and capabilities of machine learning models are no longer the limiting factor to widespread machine learning adoption instead, practitioners are struggling to integrate their models with real world business processes because of the enormous engineering effort required to do so. With Baseten, were reducing this burden and accelerating time to value by productizing the various skills needed to bring models to the real world, said Tuhin Srivastava, co-founder and CEO of Baseten.

Over the last decade, theres been enormous progress in advancing the capabilities of machine learning, driven primarily by new model architectures and the ever-decreasing cost of compute. But the critical step of integrating models with real-world business processes is still a lengthy, expensive process that prevents the majority of businesses from seeing a return on machine learning investments. While a typical machine learning model may take just a few weeks to train, building the infrastructure, APIs and UI so that the model can be used by businesses can take more than six months and requires additional resources in the form of MLOps, backend and frontend engineers.

This is a problem that Basetens co-founders Tuhin Srivastava (CEO), Amir Haghighat (CTO) and Philip Howes (Chief Scientist) encountered first hand at Gumroad. There Haghighat was the head of engineering and Srivastava and Howes were both data scientists who had to learn to become full-stack engineers so they could use machine learning to detect fraud and moderate content. The systems they built at Gumroad are still in use and have screened hundreds of millions of dollars of transactions to date.

The trio founded Baseten so that data scientists dont have to learn to become full-stack engineers in order to build web applications for their machine learning models. Baseten lowers the barrier to usable machine learning by enabling data science and machine learning teams to incorporate their machine learning models into production-grade applications within hours instead of months. With Baseten, data science and machine learning teams can easily serve their models, build backends and frontends and ship applications that solve critical business problems including operations optimization, content moderation, fraud detection and lead scoring.

Customers on Baseten:

Analysts on Baseten:

Baseten Raises $20 Million in Seed and Series A Funding

Baseten also announced that it has raised $8 million in seed funding co-led by Greylock and South Park Commons Fund and $12 million in Series A funding led by Greylock. Baseten is using the funding to expand its engineering and go-to-market teams.

Greylock General Partner and Baseten Board Member Sarah Guo said: Despite the broad understanding that AI has the capability to revolutionize business, most organizations struggle to drive real ROI from theirmachine learning efforts, stymied by the high upfront investment required. Baseten radically reduces the time, specialized expertise, cost and cross-team coordination required to successfully ship machine learning apps to production. Its end-to-end platform frees data science and machine learning teams from grunt work and empowers them to spend more time innovating and iterating to maximize impact. The Baseten team has experienced this pain first-hand, and that authenticity and care shows in the solution theyve designed. Were thrilled to partner with them to democratize access to the revolution in machine learning.

Other participants in the seed round include AI Fund, Caffeinated Capital and angel investors Lachy Groom (ex-Stripe), Greg Brockman (co-founder and CTO of OpenAI), Dylan Field (co-founder and CEO of Figma), Mustafa Suleyman (co-founder of DeepMind) and DJ Patil (ex-Chief Data Scientist of the United States Office of Science and Technology Policy).

Other participants in the A round include South Park Commons and angel investors Lachy Groom, Cristina Cordova (ex-Stripe), Dev Ittycheria (CEO of MongoDB), Jay Simon (ex-President of Atlassian) and Jean-Denis Greze (CTO of Plaid).

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AI Dynamics Will Employ Machine Learning to Triage TB Patients More Accurately, Quickly, Simply and Inexpensively Using Cough Sound Data, Bringing…

Selected by QB3 and UCSF for R2D2 TB Networks Scale Up Your TB Diagnostic Solution Program

BELLEVUE, Wash., April 26, 2022 (GLOBE NEWSWIRE) -- AI Dynamics, an organization founded on the belief that everyone should have access to the power of artificial intelligence (AI) to change the world, has been selected for the Rapid Research in Diagnostics Development for TB Networks (R2D2 TB Network) Scale Up Your TB Diagnostic Solution Program, hosted by QB3 and the UCSF Rosenman Institute. With 1.5 million deaths reported each year, Tuberculosis (TB) is the worldwide leading cause of death from a single infectious disease agent. The goal of the program is to harness machine learning technology for triaging TB using simple and affordable tests that can be performed on easy-to-collect samples such as cough sounds.

Currently, two weeks of cough sound data is widely used to determine who requires costly confirmatory testing, which delays the initiation of the treatment. AI Dynamics will build a proof-of-concept machine learning model to triage TB patients more accurately, quickly, simply and inexpensively using cough sounds, relieving patients from paying for unnecessary molecular and culture TB tests. Due to the prevalence of TB in under-resourced and remote locations, access to affordable early detection options is necessary to prevent disease transmissions and deaths in such countries.

At the core of AI Dynamics mission is providing equal access to the power of AI to everyone and we are committed to working with like-minded companies that recognize the positive impact innovative technology can have on the world, Rajeev Dutt, Founder and CEO of AI Dynamics said. The collaboration and accessible datasets that the R2D2 TB Network provides help to facilitate life-changing diagnostics for the most vulnerable populations.

The R2D2 TB Network offers a transparent and partner-engaged process for the identification, evaluation and advancement of promising TB diagnostics by providing experts and data and facilitating rigorous clinical study evaluation. AI Dynamics will build and validate a model using cough sounds collected from sites worldwide through the R2D2 TB Network.

About AI Dynamics:

AI Dynamics aims to make artificial intelligence (AI) accessible to organizations of all sizes. The company's NeoPulse Framework is an intuitive development and management platform for AI, which enables companies to develop and implement deep neural networks and other machine learning models that can improve key performance metrics. The company's team brings decades of experience in the fields of machine learning and artificial intelligence from leading companies and research organizations. For more information, please visit aidynamics.com.

About The R2D2 TB Network:

The Rapid Research in Diagnostics Development for TB Network (R2D2 TB Network) brings together various TB experts with highly experienced clinical study sites in 10 countries. For further information, please visit their website at https://www.r2d2tbnetwork.org/.

Media Contact:

Justine GoodielUPRAISE Marketing + PR for AI Dynamicsaidynamics@upraisepr.com

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Applied BioMath, LLC to Present on Machine Learning in Drug Discovery at Bio-IT World Conference and Expo – PR Newswire

CONCORD, Mass., April 27, 2022 /PRNewswire/ -- Applied BioMath (www.appliedbiomath.com), the industry-leader in providing model-informed drug discovery and development (MID3) support to help accelerate and de-risk therapeutic research and development (R&D), today announced their participation at the Bio-IT World Conference and Expo occurring May 3-5, 2022 in Boston, MA.

Kas Subramanian, PhD, Executive Director of Modeling at Applied BioMath will present "Applications of Machine Learning in Preclinical Drug Discovery" within the conference track, AI for Drug Discovery and Development on Thursday, May 5, 2022 at 1:05 p.m. E.T. In this presentation, Dr. Subramanian will discuss how machine learning methods can improve efficiency in therapeutic R&D decision making. He will review case studies that demonstrate machine learning applications to target validation and lead optimization.

"Traditionally, therapeutic R&D requires experiments on many different targets, hits, leads, and candidates that are based on best guesses," said John Burke, PhD, Co-founder, President and CEO of Applied BioMath. "By utilizing artificial intelligence and machine learning, project teams can computationally work with more data to better inform experiments and develop better therapeutics."

To learn more about Applied BioMath's presence at the Bio-IT World Conference and Expo, please visit http://www.appliedbiomath.com/BioIT22.

About Applied BioMath

Founded in 2013, Applied BioMath's mission is to revolutionize drug invention. Applied BioMath applies biosimulation, including quantitative systems pharmacology, PKPD, bioinformatics, machine learning, clinical pharmacology, and software solutions to provide quantitative and predictive guidance to biotechnology and pharmaceutical companies to help accelerate and de-risk therapeutic research and development. Their approach employs proprietary algorithms and software to support groups worldwide in decision-making from early research through all phases of clinical trials. The Applied BioMath team leverages their decades of expertise in biology, mathematical modeling and analysis, high-performance computing, and industry experience to help groups better understand their therapeutic, its best-in-class parameters, competitive advantages, patients, and the best path forward into and in the clinic to increase likelihood of clinical concept and proof of mechanism, and decrease late stage attrition rates. For more information about Applied BioMath and its services and software, visitwww.appliedbiomath.com.

Applied BioMath and the Applied BioMath logo are registered trademarks of Applied BioMath, LLC.

Press Contact: Kristen Zannella ([emailprotected])

SOURCE Applied BioMath, LLC

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Politics, Machine Learning, and Zoom Conferences in a Pandemic: A Conversation with an Undergraduate Researcher – Caltech

In every election, after the polls close and the votes are counted, there comes a time for reflection. Pundits appear on cable news to offer theories, columnists pen op-eds with warnings and advice for the winners and losers, and parties conduct postmortems.

The 2020 U.S. presidential election in which Donald Trump lost to Joe Biden was no exception.

For Caltech undergrad Sreemanti Dey, the election offered a chance to do her own sort of reflection. Dey, an undergrad majoring in computer science, has a particular interest in using computers to better understand politics. Working with Michael Alvarez, professor of political and computational social science, Dey used machine learning and data collected during the 2020 election to find out what actually motivated people to vote for one presidential candidate over another.

In December, Dey presented her work on the topic at the fourth-annual International Conference on Applied Machine Learning and Data Analytics, which was held remotely and was recognized by the organizers as having the best paper at the conference.

We recently chatted with Dey and Alvarez, who is co-chair of the Caltech-MIT Voting Project, about their research, what machine learning can offer to political scientists, and what it is like for undergrads doing research at Caltech.

Sreemanti Dey: I think that how elections are run has become a really salient issue in the past couple of years. Politics is in the forefront of people's minds because things have gotten so, I guess, strange and chaotic recently. That, along with a lot of factors in 2020, made people care a lot more about voting. That makes me think it's really important to study how elections work and how people choose candidates in general.

Sreemanti: I've learned from Mike that a lot of social science studies are deductive in nature. So, you pick a hypothesis and then you pick the data that would best help you understand the hypothesis that you've chosen. We wanted to take a more open-ended approach and see what the data itself told us. And, of course, that's precisely what machine learning is good for.

In this particular case, it was a matter of working with a large amount of data that you can't filter through yourself without introducing a lot of bias. And that could be just you choosing to focus on the wrong issues. Machine learning and the model that we used are a good way to reduce the amount of information you're looking at without bias.

Basically it's a way of reducing high-dimensional data sets to the most important factors in the data set. So it goes through a couple steps. It first groups all the features of the data into these modules so that the features within a module are very correlated with each other, but there is not much correlation between modules. Then, since each module represents the same type of features, it reduces how many features are in each module. And then at the very end, it combines all the modules together and then takes one last pass to see if it can be reduced by anything else.

Mike: This technique was developed by Christina Ramirez (MS' 96, PhD '99), a PhD graduate of our program now at UCLA. Christina is someone who I've collaborated with quite a bit. Sreemanti and I were meeting pretty regularly with Christina and getting some advice from her along the way about this project and some others that we're thinking about.

Sreemanti: I think we got pretty much what we expected, except for what the most partisan-coded issues are. Those I found a little bit surprising. The most partisan questions turned out to be about filling the Supreme Court seats. I thought that it was interesting.

Sreemanti: It's really incredible. I find it astonishing that a person like Professor Alvarez has the time to focus so much on the undergraduates in lab. I did research in high school, and it was an extremely competitive environment trying to get attention from professors or even your mentor.

It's a really nice feature of Caltech that professors are very involved with what their undergraduates are doing. I would say it's a really incredible opportunity.

Mike: I and most of my colleagues work really hard to involve the Caltech undergraduates in a lot of the research that we do. A lot of that happens in the SURF [Summer Undergraduate Research Fellowship] program in the summers. But it also happens throughout the course of the academic year.

What's unusual a little bit here is that undergraduate students typically take on smaller projects. They typically work on things for a quarter or a summer. And while they do a good job on them, they don't usually reach the point where they produce something that's potentially publication quality.

Sreemanti started this at the beginning of her freshman year and we worked on it through her entire freshman year. That gave her the opportunity to really learn the tools, read the political science literature, read the machine learning literature, and take this to a point where at the end of the year, she had produced something that was of publication quality.

Sreemanti: It was a little bit strange, first of all, because of the time zone issue. This conference was in a completely different time zone, so I ended up waking up at 4 a.m. for it. And then I had an audio glitch halfway through that I had to fix, so I had some very typical Zoom-era problems and all that.

Mike: This is a pandemic-era story with how we were all working to cope and trying to maintain the educational experience that we want our undergraduates to have. We were all trying to make sure that they had the experience that they deserved as a Caltech undergraduate and trying to make sure they made it through the freshman year.

We have the most amazing students imaginable, and to be able to help them understand what the research experience is like is just an amazing opportunity. Working with students like Sreemanti is the sort of thing that makes being a Caltech faculty member very special. And it's a large part of the reason why people like myself like to be professors at Caltech.

Sreemanti: I think I would want to continue studying how people make their choices about candidates but maybe in a slightly different way with different data sets. Right now, from my other projects, I think I'm learning how to not rely on surveys and rely on more organic data, for example, from social media. I would be interested in trying to find a way to study their candidatepeople's candidate choice from their more organic interactions with other people.

Sreemanti's paper, titled, "Fuzzy Forests for Feature Selection in High-Dimensional Survey Data: An Application to the 2020 U.S. Presidential Election," was presented in December at the fourth-annual International Conference on Applied Machine Learning and Data Analytics," where it won the best paper award.

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