The Linux Foundation Public Health initiative has chosen the Covid Tracker Ireland app as one of its first two open-source Covid-19 projects. From a report: Since its launch, more than 1.3m people have downloaded the Covid Tracker Ireland app, which was developed to help track the future spread of the coronavirus. Now, the app has been chosen as one of the first two open-source contact-tracing projects by the newly established Linux Foundation Public Health (LFPH) initiative. Nearform, the Waterford-based company that developed the app with the HSE, has been made one of the initiative's seven premium members, along with Cisco, Doc.ai, Geometer, IBM, Tencent and VMware. Under the project name 'Covid Green', the source code of the Irish app is being made available for other public health authorities and their developers across the world to use and customise. As part of the agreement, Nearform will manage the source code repository on GitHub. In its announcement, the LFPH pointed to the "extraordinarily high" adoption rate of the Covid Tracker Ireland app.

Google's announcement of a new open source initiative called the Open Usage Commons "caused some consternation among other open source proponents," according to Diginomica: IBM's reaction is typical. In a statement, the company said that "the creation of the Open Usage Commons (OUC) is disappointing because it doesn't live up to the community's expectation for open governance... Without this vendor-neutral approach to project governance, there will be friction within the community of Kubernetes-related projects...."

Google's underlying reason was that the management of trademarks was an area for legal specialists — something beyond the competence of open source project maintainers. According to Google, the new initiative would address this knowledge gap. "The Open Usage Commons is therefore dedicated to creating a model where everyone in the open source chain — from project maintainers to downstream users to ecosystem companies — has peace of mind around trademark usage and management. The projects in the Open Usage Commons will receive support specific to trademark protection and management, usage guidelines, and conformance testing...."

The Linux Foundation's response... "When trademarks of an open source project are owned by a single company within a community, there is an imbalance of control... The reservation of this exclusive right to exercise such control necessarily undermines the level playing field that is the basis for open governance. This is especially the case where the trademark is used in association with commercial products or solutions."

Red Monk analyst James Governor says that while Google's actions can be seen as provocative, it has gone down an interesting route. "The CNCF community is perhaps justifiably upset given expectations about Google's direction of travel for open source projects, but the creation of a trademark commons is an interesting one. We shall have to see how this plays out. There could be a fork ahead, or it all might be a storm in a teacup."

An anonymous reader quotes a report from Wired: Researchers at IBM's X-Force security team revealed today that they've obtained roughly five hours of video footage that appears to have been recorded directly from the screens of hackers working for a group IBM calls ITG18, and which other security firms refer to as APT35 or Charming Kitten. It's one of the most active state-sponsored espionage teams linked to the government of Iran. The leaked videos were found among 40 gigabytes of data that the hackers had apparently stolen from victim accounts, including U.S. and Greek military personnel. Other clues in the data suggest that the hackers targeted U.S. State Department staff and an unnamed Iranian-American philanthropist.

The IBM researchers say they found the videos exposed due to a misconfiguration of security settings on a virtual private cloud server they'd observed in previous APT35 activity. The files were all uploaded to the exposed server over a few days in May, just as IBM was monitoring the machine. The videos appear to be training demonstrations the Iran-backed hackers made to show junior team members how to handle hacked accounts. They show the hackers accessing compromised Gmail and Yahoo Mail accounts to download their contents, as well as exfiltrating other Google-hosted data from victims. This sort of data exfiltration and management of hacked accounts is hardly sophisticated hacking. It's more the kind of labor-intensive but relatively simple work that's necessary in a large-scale phishing operation. But the videos nonetheless represent a rare artifact, showing a first-hand view of state-sponsored cyberspying that's almost never seen outside of an intelligence agency.

IBM's Global Technology Services has posted a job ad calling for candidates with a "minimum 12+ years' experience in Kubernetes administration and management." From a report: Which is a little odd because the first GitHub commit for the project was made on June 7, 2014. And the feature freeze for version 1.0 was announced on May 22, 2015. Sharp-minded Reg readers will have recognised that -- absent time travel -- it is therefore not possible for anyone to have 12 years' experience with Kubernetes. The ad is sadly silent on just how IBM expects candidates will have found the time to accumulate a dozen years' experience in a six-year-old project.

The world's fastest computer is now part of "a vast supercomputer-powered search for new findings pertaining to the novel coronavirus' spread" and "how to effectively treat and mitigate it," according to an emerging tech journalist at Nextgov.

It's part of a consortium currently facilitating over 65 active research projects, for which "Dozens of national and international members are volunteering free compute time...providing at least 485 petaflops of capacity and steadily growing, to more rapidly generate new solutions against COVID-19."

"What started as a simple concept has grown to span three continents with over 40 supercomputer providers," Dario Gil, director of IBM Research and consortium co-chair, told Nextgov last week. "In the face of a global pandemic like COVID-19, hopefully a once-in-a-lifetime event, the speed at which researchers can drive discovery is a critical factor in the search for a cure and it is essential that we combine forces...."

[I]ts resources have been used to sort through billions of molecules to identify promising compounds that can be manufactured quickly and tested for potency to target the novel coronavirus, produce large data sets to study variations in patient responses, perform airflow simulations on a new device that will allow doctors to use one ventilator to support multiple patients — and more. The complex systems are powering calculations, simulations and results in a matter of days that several scientists have noted would take a matter of months on traditional computers.
The Undersecretary for Science at America's Energy Department said "What's really interesting about this from an organizational point of view is that it's basically a volunteer organization."

The article identifies some of the notable participants:

• IBM was part of the joint launch with America's Office of Science and Technology Policy and its Energy Department.
• The chief of NASA's Advanced Supercomputing says they're "making the full reserve portion of NASA supercomputing resources available to researchers working on the COVID-19 response, along with providing our expertise and support to port and run their applications on NASA systems."
• Amazon Web Services "saw a clear opportunity to bring the benefits of cloud... to bear in the race for treatments and a vaccine," according to a company executive.
• Japan's Fugaku — "which surpassed leading U.S. machines on the Top 500 list of global supercomputers in late June" — also joined the consortium in June.

Other consortium members:

• Google Cloud
• Microsoft
• Massachusetts Institute of Technology
• Rensselaer Polytechnic Institute
• The National Science Foundation
• Argonne, Lawrence Livermore, Los Alamos, Oak Ridge and Sandia National laboratories.
• National Center for Atmospheric Research's Wyoming Supercomputing Center
• AMD
• NVIDIA
• Dell Technologies. ("The company is now donating cycles from the Zenith supercomputer and other resources.")

Over the past two years, thousands of tech company employees have taken a stand: they do not want their labor and technical expertise to be used for projects with the military or law enforcement agencies. Knowledge of such contracts, however, hasn't been easy for tech workers to come by. From a report: On Wednesday, newly published research from the technology accountability nonprofit Tech Inquiry revealed that the Department of Defense and federal law enforcement agencies including Immigration and Customs Enforcement, the FBI, the Drug Enforcement Agency and the Federal Bureau of Prisons, have secured thousands of deals with Google, Amazon, Microsoft, Dell, IBM, Hewlett Packard and even Facebook that have not been previously reported. The report offers a new window into the relationship between tech companies and the U.S. government, as well as an important detail about why such contracts are often difficult to find.

Tech Inquiry's research was led by Jack Poulson, a former Google research scientist who quit the company in 2018 after months of internal campaigning to get clarity about plans to deploy a censored version of its search engine in China called Project Dragonfly. Poulson has publicly opposed collaborations between American technology companies and the U.S. and foreign governments that aid in efforts to track immigrants, dissenters, and bolster military activity. Poulson analyzed more than 30 million government contracts signed or modified in the past five years. The Department of Defense and federal law enforcement agencies accounted for the largest share of those contracts, with tech companies accounting for a fraction of the total number of contracts.

One of the two leading manufacturers of tape cartridge storage, FujiFilm, claims that they have a technology roadmap through to 2030 which builds on the current magnetic tape paradigm to enable 400 TB per tape. AnandTech reports: As reported by Chris Mellor of Blocks and Files, Fujifilm points to using Strontium Ferrite grains in order to enable an areal data density on tape of 224 Gbit-per-square-inch, which would enable 400 TB drives. IBM and Sony have already demonstrated 201 Gbit-per-square-inch technology in 2017, with a potential release of the technology for high volume production in 2026. Current drives are over an order of magnitude smaller, at 8 Gbit-per-square-inch, however the delay between research and mass production is quite significant.

Strontium Ferrite would replace Barium Ferrite in current LTO cartridges. Strontium sits on a row above Barium in the periodic table, indicating a much smaller atom. This enables for much smaller particles to be placed into tracks, and thankfully according to Fujifilm, Strontium Ferrite exhibits properties along the same lines as Barium Ferrite, but moreso, enabling higher performance while simultaneously increasing particle density. [...] Fujifilm states that 400 TB is the limit of Strontium Ferrite, indicating that new materials would be needed to go beyond. That said, we are talking about only 224 Gbit-per-square-inch for storage, which compared to mechanical hard disks going beyhind 1000 Gbit-per-square-inch today, there would appear to be plenty of room at the top if the technologies could converge.

Leading universities and major technology companies agreed on Tuesday to back a new project intended to give academics and other scientists access to the computing resources now available mainly to a few tech giants. From a report: The initiative, the National Research Cloud, has received bipartisan support in both the House and the Senate. Lawmakers in both houses have proposed bills that would create a task force of government science leaders, academics and industry representatives to outline a plan to create and fund a national research cloud. This program would give academic scientists access to the cloud data centers of the tech giants, and to public data sets for research. Several universities, including Stanford, Carnegie Mellon and Ohio State, and tech companies including Google, Amazon and IBM backed the idea as well on Tuesday. The organizations declared their support for the creation of a research cloud and their willingness to participate in the project.

The research cloud, though a conceptual blueprint at this stage, is another sign of the largely effective campaign by universities and tech companies to persuade the American government to increase government backing for research into artificial intelligence. The Trump administration, while cutting research elsewhere, has proposed doubling federal spending on A.I. research by 2022. Fueling the increased government backing is the recognition that A.I. technology is essential to national security and economic competitiveness. The national cloud legislation will be proposed as an amendment to this year's defense budget authorization. "We have a real challenge in our country from China in terms of what they are doing with A.I.," said Representative Anna G. Eshoo, Democrat of California, a sponsor of the bill.

Friday IBM Research updated their open source "IBM Differential Privacy Library," a suite of new lightweight tools offering "an array of functionality to extract insight and knowledge from data with robust privacy guarantees."

"Most tasks can be run with only a single line of code," brags a new blog post (shared by Slashdot reader IBMResearch), explaining how it works: This year for the first time in its 230-year history the U.S. Census will use differential privacy to keep the responses of its citizens confidential when the data is made available. But how does it work? Differential privacy uses mathematical noise to preserve individuals' privacy and confidentiality while allowing population statistics to be observed.

This concept has a natural extension to machine learning, where we can protect models against privacy attacks, while maintaining overall accuracy. For example, if you want to know my age (32) I can pick a random number out of a hat, say ±7 — you will only learn that I could be between 25 and 39. I've added a little bit of noise to the data to protect my age and the US Census will do something similar.

While the US government built its own differential privacy tool, IBM has been working on its own open source version and today we are publishing our latest release v0.3. The IBM Differential Privacy Library boasts a suite of tools for machine learning and data analytics tasks, all with built-in privacy guarantees. Our library is unique to others in giving scientists and developers access to lightweight, user-friendly tools for data analytics and machine learning in a familiar environment... What also sets our library apart is our machine learning functionality enables organisations to publish and share their data with rigorous guarantees on user privacy like never before...

Also included is a collection of fundamental tools for data exploration and analytics. All the details for getting started with the library can be found at IBM's Github repository.

An anonymous reader quotes ADTmag: The Eclipse Foundation this week announced Jakarta EE 9 Milestone 1, the final version of the enterprise Java specification before the first Release Candidate (RC). The Jakarta EE 9 release marks the final transition away from the javax.* namespace (which Oracle refused to give up) to Eclipse's jakarta.*. This release updates all the APIs to use jakarta.* in package names. In fact, Mike Milinkovich, executive director of the Eclipse Foundation, says that transition is really what this release is all about.

"The main purpose...is to provide a release that is very similar to Java EE 8," Milinkovich told ADTmag, "with everything converted to the jakarta.* namespace. We're providing a stable technical conversion platform, so all the tools and frameworks in the ecosystem that are using, say, javax.servlet, can make the change with confidence." Giving the ecosystem solid footing for the transition from the Java EE coffee cup to the Jakarta EE sailboat is the Foundation's way of setting the stage for rapid innovation, Milinkovich said, once the transition is largely complete.

"These technologies have been around for an awfully long time," he added, "and we had to provide folks with a stable platform for the conversion. At the same time, thanks to a contribution from IBM, we have the Eclipse Transformer Project, which is going to provide runtime enablement. If someone has an application they don't want to recompile, and that application is using the javax.* namespace, they will be able to run it on top of a Jakarta-compatible app server. That's going to provide binary compatibility for apps, going forward..."

A Japanese supercomputer has taken the top spot in the biannual Top500 supercomputer speed ranking. Fugaku, a computer in Kobe co-developed by Riken and Fujitsu, makes use of Fujitsu's 48-core A64FX system-on-chip. It's the first time a computer based on ARM processors has topped the list. From a report: Fugaku turned in a Top500 HPL result of 415.5 petaflops, 2.8 times as fast as IBM's Summit, the nearest competitor. Fugaku also attained top spots in other rankings that test computers on different workloads, including Graph 500, HPL-AI, and HPCG. No previous supercomputer has ever led all four rankings at once. While fastest supercomputer rankings normally bounce between American- and Chinese-made systems, this is Japan's first system to rank first on the Top500 in nine years since Fugaku's predecessor, Riken's K computer. Overall there are 226 Chinese supercomputers on the list, 114 from America, and 30 from Japan. US-based systems contribute the most aggregate performance with 644 petaflops.

IBM's research blog shares an article about "polyphonic music prediction using the Johann Sebastian Bach chorales dataset" achieved by using "biologically plausible neurons," a new approach to deep learning "that incorporates biologically-inspired neural dynamics and enables in-memory acceleration, bringing it closer to the way in which the human brain works." At IBM Research Europe we have been investigating both Spiking Neural Networks (SNNs) and Artificial Neural Networks (ANNs) for more than a decade, and one day we were struck with the thought: "Could we combine the characteristics of the neural dynamics of a spiking neuron and an ANN?" The answer is yes, we could. More specifically, we have modelled a spiking neuron using a construct comprising two recurrently-connected artificial neurons — we call it a spiking neural unit (SNU)... It enables a reuse of architectures, frameworks, training algorithms and infrastructure. From a theoretical perspective, the unique biologically-realistic dynamics of SNNs become available for the deep learning community...

Furthermore, a spiking neural unit lends itself to efficient implementation in artificial neural network accelerators and is particularly well-suited for applications using in-memory computing. In-memory computing is a promising new approach for AI hardware that takes inspiration from the architecture of the brain, in which memory and computations are combined in the neurons. In-memory computing avoids the energy cost of shuffling data back and forth between separate memory and processors by performing computations in memory — phase change memory technology is a promising candidate for such implementation, which is well understood and is on its way to commercialization in the coming years. Our work involves experimental demonstration of in-memory spiking neural unit implementation that exhibits a robustness to hardware imperfections that is superior to that of other state-of-the-art artificial neural network units...

The task of polyphonic music prediction on the Johann Sebastian Bach dataset was to predict at each time step the set of notes, i.e. a chord, to be played in the consecutive time step. We used an SNU-based architecture with an output layer of sigmoidal neurons that allows a direct comparison of the obtained loss values to these from ANNs. The SNU-based network achieved an average loss of 8.72 and set the SNN state-of-the-art performance for the Bach chorales dataset. An sSNU-based network further reduced the average loss to 8.39 and surpassed corresponding architectures using state-of-the-art ANN units.
Slashdot reader IBMResearch notes that besides being energy-efficient, the results "point towards the broad adoption of more biologically-realistic deep learning for applications in artificial intelligence."

Microsoft joined the list of tech giants who've decided to limit the use of its facial-recognition systems, announcing that it will not sell the controversial technology to police departments until there is a federal law regulating the technology. From a report: The move, announced by Microsoft president Brad Smith at a Post Live event Thursday morning, follows similar decisions by Amazon and IBM, and comes as protesters across the nation press for an end to police brutality and racial profiling. Smith said that Microsoft has not sold its facial-recognition technology to law enforcement. "We will not sell facial-recognition technology to police departments in the United States until we have a national law in place, grounded in human rights that will govern this technology," Smith said. The company also plans to put in place "review factors" that Smith said would "go even beyond what we already have" to determine the use of the technology beyond law enforcement.

An anonymous reader quotes a report from Reuters: Amazon on Wednesday said it was implementing a one-year moratorium on police use of its facial recognition software, reversing its long-time support of selling the technology to law enforcement. Civil liberties activists have voiced concern that facial recognition could lead to unjust arrests during demonstrations against police brutality, racial injustice and the death of George Floyd. Critics also have questioned the software's accuracy, pointing to a past study showing Amazon's "Rekognition" service struggled to identify the gender of individuals with darker skin tones. Amazon has taken issue with that research.

The company, which sells cloud computing technology via its Amazon Web Services division, said in a statement it has pushed for regulations to ensure the software was used ethically. "We hope this one-year moratorium might give Congress enough time to implement appropriate rules, and we stand ready to help if requested," Amazon said. The company said it would continue to permit use of its technology by customers Thorn and Marinus Analytics to help law enforcement find human trafficking victims. The decision follows IBM's announcement earlier this week that it was getting out of the facial recognition business entirely. It's also urging Congress to enact reforms to advance racial justice and combat systemic racism.

IBM CEO Arvind Krishna called on Congress Monday to enact reforms to advance racial justice and combat systemic racism while announcing the company was getting out of the facial recognition business. CNBC reports: "IBM firmly opposes and will not condone uses of any technology, including facial recognition technology offered by other vendors, for mass surveillance, racial profiling, violations of basic human rights and freedoms, or any purpose which is not consistent with our values and Principles of Trust and Transparency," Krishna wrote in the letter delivered to members of Congress late Monday. "We believe now is the time to begin a national dialogue on whether and how facial recognition technology should be employed by domestic law enforcement agencies."

IBM decided to shut down its facial recognition products and announce its decision as the death of George Floyd brought the topic of police reform and racial inequity into the forefront of the national conversation, a person familiar with the situation told CNBC. IBM's facial recognition business did not generate significant revenue for the company, the person familiar with the situation said, but the decision remains notable for a technology giant that counts the U.S. government as a major customer. The decision was both a business and an ethical one, the person familiar with the situation said. The company heard in the past few weeks concerns from many constituencies, including employees, about its use of the technology, the person added.

"Artificial Intelligence is a powerful tool that can help law enforcement keep citizens safe. But vendors and users of Al systems have a shared responsibility to ensure that Al is tested for bias, particularly when used in law enforcement, and that such bias testing is audited and reported," Krishna wrote. The letter was addressed to sponsors and co-sponsors of a sweeping police reform bill unveiled by Democrats Monday -- Black Caucus Chair Rep. Karen Bass (D-CA), House Judiciary Committee Chair Rep. Jerry Nadler (D-NY), Sen. Corey Booker (D-NJ), Sen. Kamala Harris (D-CA) and Rep. Hakeem Jeffries (D-NY).

New submitter IBMResearch shares a report from ZDNet: IBM's new toolkit aims to give developers easier access to fully homomorphic encryption (FHE), a nascent technology with significant promise for a number of security use cases. "Today, files are often encrypted in transit and at rest but decrypted while in use, creating a security vulnerability," reports ZDNet. "This often compels organizations to make trade-offs and go through long vetting processes in order to ensure they can keep their valuable data protected while still gaining some value out of it. FHE aims to resolve that issue."

"While the technology holds great potential, it does require a significant shift in the security paradigm," the report adds. "Typically, inside the business logic of an application, data remains decrypted, [Flavio Bergamaschi, FHE pioneer and IBM Researcher] explained. But with the implementation of FHE, that's no longer the case -- meaning some functions and operations will change."

The toolkit is available today in GitHub for MacOS and iOS, and it will soon be available for Linux and Android.

Slack is partnering with Amazon in a multi-year agreement that means all Amazon employees will start to use Slack. The Verge reports: The deal comes just as Slack faces increased competition from Microsoft Teams, and it will also see Slack migrate its voice and video calling features over to Amazon's Chime platform alongside a broader adoption of Amazon Web Services (AWS). Amazon's roll out of Slack to all of its employees is a big part of the deal, thanks to an enterprise-wide agreement. It's not immediately clear how many of Amazon's 840,000 employees will be using Slack, though. Up until today, Slack's biggest customer has been IBM, which is rolling out Slack to its 350,000 employees.

While Slack has long used AWS to power parts of its chat app, it's now committing to using Amazon's cloud services as its preferred partner for storage, compute, database, security, analytics, machine learning, and future collaboration features. The deal means it's unlikely we'll see Slack turn to Microsoft's Azure cloud services or Google Cloud to power parts of its service in the foreseeable future. [...] Slack and Amazon are also promising better product integration and interoperability for features like AWS Chatbot, a service that pushes out Slack channel alerts for AWS instances. In the coming months, Slack and AWS will improve its Amazon AppFlow integration to support bi-directional transfer of data between AWS services and Slack channels.

May 23rd marks the 25th anniversary of the day Sun Microsystems introduced Java to the world, notes InfoWorld.

Looking at both the present and the future, they write that currently Java remains popular "with enterprises even as a slew of rival languages, such as Python and Go, now compete for the hearts and minds of software developers." Java continues to rank among the top three programming languages in the most prominent language popularity indexes — Tiobe, RedMonk, and PyPL. Java had enjoyed a five-year stint as the top language in the Tiobe index until this month, when it was overtaken by the C language, thanks perhaps to the combination of C's wide use in medical equipment and the urgency of the COVID-19 pandemic.

Nevertheless, Java represents a huge ecosystem and source of jobs. There were an estimated nine million Java developers worldwide in 2017, according to Oracle. A recent search of jobs site Dice.com found nearly 12,000 Java-related jobs in the USA, compared to roughly 9,000 jobs in JavaScript and 7,600 in Python. Plus, Java has spawned an enormous ecosystem of tools ranging from the Spring Framework to application servers from companies such as IBM, Red Hat, and Oracle to the JavaFX rich media platform.

The developers behind Java — including Oracle and the broader OpenJDK community — have kept the platform moving forward. Released two months ago, Java 14, or Java Development Kit (JDK) 14, added capabilities including switch expressions, to simplify coding, and JDK Flight Recorder (JFR) Event Streaming, for continuous consumption of JFR data. Up next for Java is JDK 15, set to arrive as a production release in September 2020, with capabilities still being lined up for it. So far, the features expected include a preview of sealed classes, which provide more-granular control over code, and records, which provide classes that act as transparent carriers for immutable data. Also under consideration for Java is a plan dubbed Project Leyden, which would address "longterm pain points" in Java including resource footprint, startup time, and performance issues by introducing static images to the platform.

"Having re-open-sourced MS-DOS on GitHub in 2018, Microsoft has now released the source code for GW-BASIC, Microsoft's 1983 BASIC interpreter," reports ZDNet, adding that GW-BASIC "can trace its roots back to Bill Gates' and Paul Allen's implementation of Microsoft's first product, the BASIC interpreter for the Altair 8800 computer."

"Interested to look at thousands of lines of glorious 8088 assembly code for the original 1983 GW-BASIC...?" writes Slashdot reader sonofusion82, adding "there are not Makefiles or build scripts, just a bunch of 8088 ASM files."

Or as Hackaday jokes, "Microsoft releases the source code you wanted almost 30 years ago." In the late 1970s and early 1980s, if you had a personal computer there was a fair chance it either booted into some version of Microsoft Basic or you could load and run Basic... Now you can get the once-coveted Microsoft Basic source code...

They put up a read only GW-BASIC repository, presumably to stop a flood of feature requests for GPU acceleration...

From what we understand, GW-Basic was identical to IBM's BASICA, but didn't require certain IBM PC ROMs to operate. Of course, BASICA, itself, came from MBASIC, Microsoft's CP/M language that originated with Altair Basic... We did enjoy the 1975 copyright message, though:

ORIGINALLY WRITTEN ON THE PDP-10 FROM FEBRUARY 9 TO APRIL 9 1975

BILL GATES WROTE A LOT OF STUFF.
PAUL ALLEN WROTE A LOT OF OTHER STUFF AND FAST CODE.
MONTE DAVIDOFF WROTE THE MATH PACKAGE (F4I.MAC).
Bill Gates was 19 years old, Paul Allen was 22.

IBM cut an unspecified number of jobs across the U.S., eliminating employees in at least five states. The company declined to comment on the total number, but the workforce reductions appear far-reaching. From a report: "IBM's work in a highly competitive marketplace requires flexibility to constantly add high-value skills to our workforce. While we always consider the current environment, IBM's workforce decisions are in the interest of the long-term health of our business," company spokesman Ed Barbini said Thursday in a statement. "Recognizing the unique and difficult situation this business decision may create for some of our employees, IBM is offering subsidized medical coverage to all affected U.S. employees through June 2021." Based on a review of IBM internal communications on the Slack corporate messaging service, the number of affected employees is likely to be in the thousands, said a North Carolina-based worker who lost his job along with his entire team of 12. "This was far ranging -- and historical employment ratings, age and seniority did not seem to matter," he said. The person asked not to be identified on concern that speaking publicly may impact his severance package.