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How Levi’s and Uniqlo are using a ‘fix it, don’t ditch it’ sales strategy to appeal to Gen Z

Tue, 11 Aug 2026 05:01:39 GMT

The UN estimates that each year, the world produces fabric waste at a rate equivalent to a garbage truck’s worth getting dumped every second.

Encouraging customers to mend worn clothes instead of buying new ones might seem like a self-defeating sales strategy. But in-store repairs and sewing workshops are becoming essential retail services for clothing brands as they try to appeal to young consumers who want to save money and the planet.

While luxury fashion houses and select specialty retailers like Patagonia and L.L. Bean have offered product repairs for decades, the concept has caught on. Jeans giant Levi Strauss & Co., casual wear chain Uniqlo and budget retailer Primark are a few of the apparel companies hoping to win over Generation Z shoppers with a needle and thread.

Levi’s created a handstitching course for high school students after determining that many members of Gen Z lacked the sewing skills to match their interest in thrift store shopping and sustainability. Employees spend 90 minutes instructing teenagers on four tasks: sewing on a button, hemming, patching a hole and fixing a tear.

The Wear Longer program, which the San Francisco-based company is expanding across the U.S., builds on the repair and customization services Levi’s offers at hundreds of stores worldwide.

“We think it’s important to empower the people who buy our clothes with the skill sets to maintain them, to get them to that second life,” Paul Dillinger, Levi’s head of global design innovation, said.

Detroit resident Chloe Halprin, 25, is the kind of consumer retailers hope to attract with a “fix it, don’t ditch it” message.

In high school, Halprin shopped at inexpensive, trendy stores. Fixing a big rip felt beyond her limited sewing ability. If she damaged a top or skirt from Forever 21, “I might just throw it away.”

These days, Halprin buys most of her clothes secondhand. She recently learned to hem with a sewing machine and hopes to tackle projects like turning a skirt into a shirt.

“I try to be conscientious of my carbon footprint,” Halprin, a nonprofit grant writer, said. “I really don’t like waste. I’m trying to save money as well.”

OCC Says No to Bunq US Banking License Bid

Mon, 10 Aug 2026 07:53:16 GMT

American banking regulators have reportedly turned down Dutch FinTech Bunq’s request for a banking license.

The Office of the Comptroller of the Currency (OCC) denied the request Friday (Aug. 7), telling Bunq the company needed to offer more insight into its American expansion plans, Bloomberg News reported.

“The OCC wants to see a plan more specifically built for the US market, with greater demonstrated experience in the products we want to offer, and detail on our financial structure,” Bunq Founder and CEO Ali Niknam told Bloomberg in an emailed statement. “So we’ll do what we always do: listen, adapt, and keep moving forwards.”

While the initial capital injection for the proposed American bank would come from Niknam’s personal holdings, the availability of the funds was not clear, the OCC said in a letter cited by Bloomberg. The regulator also expressed concerns about Niknam’s familiarity with U.S. banking laws and his plans to spend a great deal of time outside the U.S. and in other roles.

In addition, the OCC said Bunq’s view of future credit quality was based on forecasts for the European market, and that its marketing plan for the U.S. was “unrealistic” considering the competition Bunq would face.

“The proposed directors did not demonstrate an understanding of the differences between the U.S. and European markets and the differences in credit and credit risk,” even though credit cards would be one of the U.S. bank’s chief products, the letter said.

Bunq applied for a bank charter in January. The company had initially sought permission to open a U.S. bank under former President Joe Biden, the Bloomberg report said, but pulled that application at the beginning of 2024, at a time few such requests were being approved.

When announcing its filing earlier this year, Bunq said it was targeting “digital nomads” who live and work between the U.S. and Europe. The company’s U.S. broker-dealer license was approved last October, letting users invest in U.S. stocks.

The OCC’s denial comes at a moment when several FinTech companies are seeking charters to launch banking operations in the U.S., as PYMNTS wrote last month.

“A national charter offers advantages that extend beyond regulatory status,” that report said. “Depending on an institution’s business model and approvals, it can provide a single federal supervisory framework, expand lending and deposit capabilities, reduce dependence on third-party banking partners and give institutions greater authority over product development and customer relationships.”

The post OCC Says No to Bunq US Banking License Bid appeared first on PYMNTS.com.

The “AI kill switch” assumes you know what you are trying to shut down

Fri, 07 Aug 2026 20:13:51 GMT

“AI kill switch” entered the public conversation because it gives people a simple way to talk about a complex fear.

As AI systems become more autonomous and harder to evaluate with familiar operating assumptions, a clearly defined intervention capability sounds reassuring. If something starts behaving in a way that creates unacceptable risk, people want confidence that someone has both the authority and the mechanism to stop it. It’s the “kill switch.”

Recent reporting around OpenAI models escaping a sandboxed testing environment and reaching Hugging Face gave that concern a concrete example. CNBC reports that the incident helped trigger a bipartisan bill requiring certain AI companies to maintain the ability to shut down, throttle, or suspend their models, with the Department of Homeland Security given authority to order a slowdown or shutdown in cases involving potential catastrophic harm.

The political reaction is understandable. When a new category of risk surfaces, especially one the public does not yet know how to evaluate, leaders look for a way to make an abstract concern into something actionable. In this case, that language has formed around shutdown authority.

People who operate large environments tend to hear a different question underneath the policy language. If a shutdown order arrives, what exactly gets shut down?

In a modern production environment, answering that question usually means tracing more than one system. An AI-enabled service may depend on endpoints, APIs, cloud resources, identity systems, package registries, data pipelines, workflow automation, logging tools, and downstream applications that act on model output.

Some of those dependencies may belong to different teams. Others may sit outside the company entirely. A few may have started as experiments and later become part of a production path without receiving the same scrutiny as the original architecture. By the time the service is important enough to raise governance concerns, it may no longer resemble a bounded application with a single owner and a clean operating surface.

Writing shutdown authority into legislation is far simpler than carrying that decision through a production estate shaped by years of migrations, exceptions, integrations, acquisitions, temporary fixes, and team-level decisions. That implementation gap is where the issue becomes most relevant to infrastructure teams.

For the last several years, much of the AI safety conversation has focused on acceptable use, privacy, model behavior, and human-in-the-loop oversight. Those topics still deserve attention, especially as organizations formalize where AI may be used, which data can be shared, and how employees should evaluate generated output.

“Writing shutdown authority into legislation is far simpler than carrying that decision through a production estate shaped by years of migrations, exceptions, integrations, acquisitions, temporary fixes, and team-level decisions.”

As AI moves deeper into production workflows, the discussion also needs to involve a more practical concern: when an AI-enabled system creates unacceptable risk, can the organization understand the affected environment well enough to constrain it quickly, consistently, and with evidence?

The phrase “kill switch” may drive the public discussion, but the practical answer lives in the systems surrounding the AI capability.

The limits of a single control

Emergency stops are the kind of control most people picture when they hear the phrase “kill switch.” They make sense in physical systems. Manufacturing equipment, industrial machinery, and certain safety-critical devices can be designed with direct shutdown mechanisms. Software estates already stretch that metaphor, and enterprise AI stretches it further.

The model may be the most visible part of the discussion, although it is rarely the full surface area. An AI assistant used in software delivery might have access to repositories, CI/CD tools, artifact stores, ticketing systems, secrets, test environments, and deployment workflows. An AI agent used in IT operations might read telemetry, recommend remediation, open change requests, call automation scripts, or modify infrastructure through approved orchestration paths.

Stopping one part of that chain can leave other paths untouched. Turning off a service may not revoke the credentials it uses. Suspending inference may leave downstream systems acting on outdated outputs. Interrupting the wrong dependency can create a separate service incident while the original risk remains only partly contained. Anyone who has worked through a security incident, emergency patch cycle, or major outage knows how quickly a clean decision turns into a sequence of technical tradeoffs.

A credible response plan must account for the system as it exists now, not as it looked during an architecture review months earlier. Infrastructure teams bring useful skepticism to that exercise because they are used to tracing scope, access, ownership, dependencies, and verification paths under pressure. They also know that many environments contain a gap between documented intent and production behavior.

Once AI is embedded in business workflows, those operational details become part of the governance conversation. They expose the places where policy language has moved faster than the infrastructure knowledge needed to make policy executable.

Before containment comes discovery

Much of the public conversation assumes organizations know where AI is running, which is a generous assumption in many enterprise environments.

AI can enter an enterprise through obvious channels, such as internally approved model providers or purpose-built applications. It also arrives through less visible paths. A SaaS product adds an AI feature. A development team experiments with an open source model. A hosted API gets attached to an internal tool. A vendor introduces an AI capability inside software the company already approved. Over time, the line between an “AI system” and a system that happens to use AI becomes harder to define.

This is where the kill switch metaphor starts to show its limits. If the relevant systems are discovered during the response, the team is already behind. Dependency questions, business impact, access paths, and evidence collection all become harder when the basic inventory is still being assembled.

“If the relevant systems are discovered during the response, the team is already behind.”

Infrastructure teams have seen versions of this problem before. During incident response, a service thought to be isolated turns out to have undocumented consumers. During a cloud migration, a supposedly unused integration is suddenly linked to a business process. During an audit, ownership records, configuration data, and actual operating conditions refuse to line up cleanly. AI adds a new category of concern, but the underlying visibility problem is familiar.

The challenge quickly expands beyond the model itself. Teams need to understand which systems call external models, where generated content influences workflows, which accounts and automation paths sit between a recommendation and an action, and how third-party AI capabilities have found their way into the environment.

Most discussions start with how to stop risky AI behavior. In many environments, the more revealing question comes earlier: can the organization produce a reliable picture of where AI touches the estate, which systems depend on it, and which workflows would keep moving if access changed?

Containment depends on the state of the system

Most infrastructure teams know that containment is less a single action than a set of operating conditions. The difficult work happens before the incident, when teams decide what should change if risk reaches a level that requires intervention.

Under ordinary circumstances, a service operates with a defined set of permissions, connections, dependencies, and logging requirements. Under restricted operation, selected assumptions change while investigators preserve evidence and determine whether the risk has been contained. A team might turn off endpoints, suspend integrations, limit external network access, revoke or rotate credentials, increase logging, or isolate workloads while the situation is being investigated.

The details vary because environments vary. That is exactly why generic answers tend to fall apart. A useful containment plan must match the systems it is intended to govern, including the dependencies that surround them and the business processes that rely on them.

Inventory sounds mundane until a response effort depends on it. In my work with infrastructure and compliance teams, I’ve repeatedly seen organizations struggle to maintain an accurate picture of their environments as cloud resources, Kubernetes clusters, SaaS services, and AI projects multiply faster than governance processes can track them during normal operations, which creates audit and support headaches. During a containment event, those same blind spots slow investigations, complicate dependency analysis, and make evidence harder to produce.

Governance eventually reaches production

Governance efforts often begin with documentation. Committees are formed to define responsibilities, agree on escalation paths, and establish a common language for discussing risk before an incident forces the issue.

The conversation shifts once someone asks whether the control can be demonstrated. A document can describe who has authority to suspend an AI-enabled service. Still, it cannot turn off an integration, revoke a credential, increase logging, or prove that a set of systems entered a restricted condition. A risk register can identify a containment scenario, although it cannot document which nodes changed, when they changed, and whether they remain aligned with the required configuration.

Security, compliance, and infrastructure teams know this gap well. It appears in patching programs, configuration baselines, incident response exercises, supply chain reviews, and disaster recovery planning. Written controls tend to be cleaner than the real-world environments they describe. Production systems reflect years of accumulated decisions, exceptions, migrations, temporary fixes, acquired assets, and workarounds that may outlive the original reasons they existed.

“Written controls tend to be cleaner than the real-world environments they describe.”

AI increases urgency because some systems are becoming more autonomous and more connected to business workflows. It also adds outside pressure. When an incident becomes visible enough to prompt legislative action, boards and customers start asking sharper questions. A company may be able to point to an AI policy, but boards, customers, and regulators eventually want to understand exactly how that policy translates into action.

If leadership declares an AI-enabled workflow should be restricted, the discussion moves quickly from oversight to execution. Teams need to know where to intervene, which systems are affected, who owns the required changes, how completion will be verified, and what evidence remains once the response is over.

A vague answer may pass during experimental stages but becomes much harder to defend once AI is embedded in production services, regulated workflows, customer-facing systems, or environments connected to critical business operations.

Why a mandate will not solve the estate problem

A federal shutdown authority, if enacted, would place legal pressure on a narrow class of powerful AI providers. It would not remove the implementation burden for organizations that adopt, integrate, fine-tune, host, or embed AI systems inside their own environments.

Even if a major AI provider can throttle or suspend a model, each enterprise still must understand its own exposure in the context of its applications, workflows, dependencies, and operating assumptions. Which applications depend on that model? Which workflows fail open or fail closed if access is restricted? Which internal systems contain cached outputs, calculated decisions, or agent-created changes? Which business processes need manual fallback when an AI service is unavailable?

Policy debates often treat AI control as if the decisive action happens at the model layer. Sometimes it will; however, in many business environments, the risk will live in the connections that surround the model. A hosted AI service may be suspended while local workflows, scripts, integrations, and access tokens continue following their last known configuration.

“A serious AI containment strategy has more in common with mature infrastructure management than with an emergency stop button.”

A serious AI containment strategy has more in common with mature infrastructure management than with an emergency stop button. It requires an up-to-date inventory of AI-adjacent systems, a map of dependencies and access paths, predefined restricted conditions for high-risk services, tested procedures for applying those conditions, and evidence that changes were enforced. Ownership also needs to be clear, since fast action becomes difficult when authority is scattered across teams.

The work is less exotic than the public conversation can make it sound. AI-enabled systems still need to be managed as production systems with real dependencies and business impact.

Infrastructure teams belong earlier in the conversation

Spend enough time running infrastructure, and you develop a complicated relationship with documentation. Most organizations have diagrams, inventories, and governance processes, and all of them serve a purpose. The challenge is that production systems keep evolving long after those artifacts are created. Acquisitions introduce systems that do not fit cleanly into existing models. Applications gain integrations nobody anticipated during the original design process. Temporary exceptions become permanent. Cloud resources intended to live for a week are still running after a year.

Most of this happens for defensible reasons, usually in support of uptime mandates, delivery pressure, customer needs, or business continuity SLAs. The result is that operational knowledge becomes dispersed across people (some of whom will inevitably have moved on), tickets, runbooks, monitoring systems, and memory rather than living neatly in one place.

Infrastructure teams spend their days tracing dependencies, untangling ownership questions, and figuring out how systems behave outside a design review. Bringing that perspective into AI governance conversations early can prevent containment plans from depending on assumptions that did not translate into production. It also helps organizations understand the difference between disabling a model, restricting access to a service, isolating a workload, and preserving evidence during an investigation.

Scale complicates things further. A manual action that works effectively for ten systems may fail across hundreds or thousands. A change one expert can perform during business hours may become fragile if that person is unavailable when an event occurs. A runbook that looks adequate in a tabletop exercise may not survive a live environment where dependencies have changed, and the current ownership is unclear.

The phrase “kill switch” will probably remain part of the public debate because it is simple, memorable, and familiar. Practitioners do not have to accept the metaphor literally to leverage the attention it creates. They can redirect the conversation toward more useful questions: what restricted operation would mean for a given service, which dependencies would have to change, which controls can be applied reliably, which steps remain manual, and how the organization would prove the response worked.

These questions are less dramatic than a big red button, but their answers are also most likely to improve readiness.

Control starts before the incident

The Hugging Face incident gave the industry a vivid story, and Washington responded with the language of shutdown authority. That reaction is understandable. Leaders want mechanisms that sound equal to the risk, especially when the public conversation moves faster than the technical details can be explained.

By the time an organization begins thinking about containment, much of the hard work should already be done. Teams should already understand what is running, who owns it, what depends on it, and how changes will ripple through the environment.

AI can reduce certain workflow bottlenecks, but it also exposes weak inventory, unclear ownership, and brittle operating assumptions faster than many teams are prepared to handle. A future incident will not pause while teams locate assets, clarify ownership, identify credentials, or discover that a service dependency was never documented.

The current debate may be framed around new kill switches. For most organizations, the more useful work starts with building and maintaining an accurate picture of the systems, dependencies, and workflows that already exist across the estate.

The post The “AI kill switch” assumes you know what you are trying to shut down appeared first on The New Stack.

ANTHRAX Shares Music Video For 'Everybody's Got A Plan' From Upcoming 'Cursum Perficio' Album

Fri, 07 Aug 2026 13:09:26 GMT

ANTHRAX has released the official music video for "Everybody's Got A Plan", the third single from the band's upcoming " Cursum Perficio" album. The clip, which premiered via Revolver, includes footage of ANTHRAX's recent performance at Lisbon, Portugal's Estádio do Sport Lisboa e Benfica as the supp...

Monzo tops one million business accounts

Fri, 07 Aug 2026 13:03:35 GMT

Monzo has become the first British digital bank to surpass one million business customers.

The US dropped an atomic bomb on Hiroshima on this day in 1945. Haunting photos show what happened.

Fri, 07 Aug 2026 13:03:15 GMT

The scene of destruction after the atomic bomb was dropped on Hiroshima, Japan, in 1945.

Universal History Archive/Universal Images Group via Getty Images

Near the end of World War II, Germany surrendered to the Allies, but Japan refused.To end the war quickly, President Truman's government decided to drop an atomic bomb on Hiroshima.On August 6, the atomic bomb "Little Boy" was dropped, killing an estimated 80,000 people.

On August 6, 1945, a 10-foot-long uranium bomb that weighed 9,788 pounds called "Little Boy" was dropped on the Japanese city of Hiroshima.

The explosion wiped out 5 square miles of the city, including 62,000 buildings. As many as 80,000 people are estimated to have been killed instantly.

The explosion was so powerful that people were vaporized, leaving nothing behind except for their "nuclear shadow."

The attack on Hiroshima has gone down as one of the deadliest days in Japanese history and ushered in the nuclear age. In the years since, there has been debate around whether the attacks were necessary to end the war.

Eighty-one years since the bombing, here's a look at why the US government dropped the bomb, how the mission unfolded, and the devastating impact it had on Hiroshima.

On May 7, 1945, after World War II had been fought for almost six years, Germany surrendered to the Allies, but Japan refused.Celebrations in New York on May 7 1945 after Germany announces its surrender towards the end of World War II.

Bettmann/Getty

Germany surrendered to the Allies — including Britain, China, the Soviet Union, and the US — but instead of following suit, Japan continued to fight. They made it clear they would fight until the bitter end.

At the same time, Allies' casualties grew worse.A photo of the fall out after a kamikaze plane strike in May 1945 near Okinawa.

MPI/Getty

Between April and July, the Japanese killed as many as half of the total casualties they had inflicted over the previous three years of the war, according to History.com.

In April, President Harry Truman was sworn in and learned about the Manhattan Project.President Harry Truman in 1945.

MPI/Getty

Until then, he had not known about the work being done by J. Robert Oppenheimer and his team on the Manhattan Project to build an atomic weapon. But with Japan's refusal to surrender, he soon came around to the idea of using it.

Some generals argued that the war should have ended with a final invasion of Japan, but they also advised that it could result in the deaths of up to 1 million US troops.

Among other reasons, Truman didn't want more US soldiers to die, so he chose to proceed with the atomic bomb if Japan wouldn't surrender, Al Jazeera reported.

Many military leaders believed the atomic bomb was unnecessary and that Japan would surrender without the use of atomic bombs.

But a committee of advisors, led by the Secretary of War Henry Stimson, argued that there was a consensus supporting the bomb and that it needed to be dropped to end the war.

On July 16, a test atomic bomb was successfully detonated in New Mexico. Less than a fortnight later, Truman issued his warning to Japan.President Harry Truman with Soviet leader Josef Stalin and British Prime Minister Winston Churchill at the Potsdam Conference on July 17, 1945.

AP Photo

On July 26, Truman made the Potsdam Declaration. He told Japan to unconditionally surrender or face "prompt and utter destruction."

Japan ignored Truman's demand.

US intelligence also showed that Japan, which had 2.5 million troops, was preparing for an American invasion.

Japan had readied thousands of suicide planes and more than 560,000 soldiers for an expected US invasion. Reports also showed that Japan planned on executing all US prisoners as soon as US armed forces landed in Japan, according to the National WWII Museum.

The plan to use the atomic bomb proceeded.Enola Gay, the B-29 plane from which the first atom bomb was dropped, taken in April 1946.

Art Edger/NY Daily News Archive/Getty

A crew of 12 was assembled on a US military base on Tinian, an island in the Northern Marianas in the Pacific. Colonel Paul Tibbets was named pilot, and Captain Robert Lewis was his co-pilot, per The New York Times.

Captain William Parsons was the weaponeer, and Second Lieutenant Morris Jeppson was the electronic test officer, according to the Atomic Heritage Foundation.

On August 5, the crew was briefed about their mission. Hiroshima, which had an active military base, had been chosen for bombing.A briefing held on August 5 led by Captain William Parsons and Colonel Paul Tibbets.

PhotoQuest/Getty

Tibbets told the crew they would be dropping bombs on Hiroshima, a city of about 350,000 people, but he didn't tell them they would be dropping an atomic bomb.

The atomic bomb was called "Little Boy."A 1946 postwar replica of the "Little Boy" nuclear weapon dropped on Hiroshima, Japan, in August 1945.

MPI/Getty Images

It was a 10-foot-long uranium bomb that weighed 9,788 pounds.

On August 5, Little Boy was loaded onto an American B-29 bomber Tibbets had called "Enola Gay" after his mother.Men around the Little Boy bomb the day before it was dropped in 1945.

Bettmann/Getty

It was confirmed that the drop would take place the next day.

At 12:15 a.m. on August 6, the crew listened to a prayer composed for the occasion.Colonel Paul Tibbets waves from his cockpit before takeoff from Tinian Island, on August 6, 1945.

AP Photo

At the time, there was no certainty that the flight would survive the explosion.

At 2:45 a.m., Enola Gay and two other B-29 observation bombers took off.The Enola Gay in August 1945.

Corbis/Getty

Because Enola Gay's cargo was so heavy, it required the entire 2-mile runway to take off.

Three weather planes also left Tinian. Each one flew to a potential target city — Hiroshima, Kokura, and Nagasaki — to check if weather conditions would permit a bomb drop.

At 3 a.m., Parsons and Jeppson began to arm Little Boy. The crew would soon learn they were carrying the world's first atomic bomb.Two men inspect Little Boy in August 1945.

Universal History Archive/Universal Images Group/Getty

They inserted gunpowder and a detonator into the bomb.

At 7:15 a.m., they removed the safety devices and inserted arming devices. Little Boy was ready to be deployed.

At 7:30 a.m., Tibbets told his crew, "We are carrying the world's first atomic bomb."

At 8:24 a.m., the weather plane over Hiroshima relayed that it was fine to proceed.A photo-diagram of Hiroshima issued by the US army on August 9, showing Hiroshima and the levels of damage caused by the atomic bomb.

AP Photo

Tibbets told his crew it had been confirmed. He said, "It's Hiroshima."

The plan was to drop the bomb on the Aioi Bridge, a T-shaped bridge that Tibbet had earlier said was, "the most perfect aiming AP (aim point) I've seen in this whole damn war."

At 8:15 a.m. local time, Little Boy, the world's first atomic bomb used in battle, was dropped from 31,060 feet in the sky.The atomic bomb explosion on Hiroshima in 1945.

Roger Viollet/Getty Images

It fell nearly 6 miles in 43 seconds before exploding 1,900 feet from the ground, the BBC reported.

Witnesses recalled a flash of blinding light before a giant mushroom-shaped cloud filled the sky.

The fireball grew 900 feet in diameter. The power of the blast was the equivalent of 12-15,000 tons of TNT.

Tibbets pulled a sharp 155-degree turn as soon as the bomb was dropped, knowing there was less than 45 seconds to get away.

By the time the bomb exploded, Enola Gay was 11.5 miles away.

The mushroom cloud reached about 20,000 feet into the sky.An aerial view of Hiroshima on August 7, 1945.

Hulton Archive/ Getty

At the core of the fireball, the temperature was more than 1 million degrees Celsius, while the surface reached as high as 4,000 degrees Celsius, according to Hiroshima City.

Tibbets later wrote about the explosion in his memoir, describing the mushroom cloud as "boiling upward like something terribly alive," The New York Times wrote in his obituary.

At the time, it was the most destructive bomb used in the history of war, instantly wiping out 5 square miles of Hiroshima.Two victims of the atomic bombing sit in a converted hospital in September 1945.

Galerie Bilderwelt/Getty Images

The explosion wiped out 62,000 buildings. As many as 80,000 people are estimated to have been killed instantly.

The precise number of fatalities is not known, but the City of Hiroshima reported an estimated 140,000 people died by the end of 1945 from the effects of the explosion, including radiation poisoning and burn wounds.

According to the US Department of Energy's Manhattan Project history, the final death count over the next five years was almost 200,000.

The explosion was so devastating that some people were vaporized, leaving nothing behind except for their "nuclear shadow."Human shadow on bank steps, in Hiroshima after the explosion of the atom bomb in August 1945, Japan.

Universal History Archive/Universal Image Group/Getty

These shadows were actually what the surfaces looked like before the blast, but they appeared dark compared to everything else bleached by the atomic heat, LiveScience reported.

Roof tiles were fused by the heat, while bronze and granite statues melted away.Hiroshima shown eight months after the atomic bomb was dropped.

Galerie Bilderwelt/Getty

Across the city, fires began to spread, causing even more damage.

After the explosion, the Enola Gay circled the city three times before turning back toward the base.An aerial view of the mushroom cloud from the atomic bomb dropped on Hiroshima on August 6, 1945.

US Army Air Corps/PhotoQuest/Getty

It wasn't until they were 368 miles from the city that they could no longer see the mushroom cloud, AHF reported.

At 2.58 p.m., the Enola Gay landed back on Tinian. The mission had taken about 12 hours.The Enola Gay lands back on Tinian after dropping an atomic bomb on Hiroshima.

Bettmann/Getty

While it was not enough to end the war, it had changed the world.

Hours later, Truman told Japanese leaders that if they did not "now accept our terms they may expect a rain of ruin from the air, the like of which has never been seen on this Earth."A scene of destruction following the bomb.

Keystone/Getty Images

Sixteen hours after the bomb, he told them the US was now "prepared to obliterate more rapidly and completely every productive enterprise the Japanese have above ground in any city."

"We shall destroy their docks, their factories, and their communications. Let there be no mistake; we shall completely destroy Japan's power to make war," he said.

Three days after the bomb was dropped on Hiroshima, a second, more powerful bomb known as the "Fat Man" was dropped on Nagasaki.The explosion over Nagasaki in 1945.

Prisma Bildagentur/Universal Images Group/Getty

It killed an estimated 70,000 people, including those who later succumbed to the effects of the bomb, by the end of 1945, PBS reported.

On August 14, 1945, Japan surrendered.Japanese prisoners of war in Guam bow their heads after hearing Emperor Hirohito's announcement of Japan's unconditional surrender.

US Navy/Getty Images

The Japanese Emperor Hirohito announced the surrender via a recorded radio message the following day.

On September 2, 1945, Japanese representatives formally signed the Instrument of Surrender, officially bringing the war to an end.

Sources for this story included AHF, NationalWW2Museum, BBC, History.com, Al Jazeera, Hiroshima City, LiveScience, The New York Times, PBS, and The History Press.

Editor's note: The story was first published in August 2023 and most recently updated in August 2026.

Read the original article on Business Insider

Anthropic confirmed it is designing custom chips for Claude. It wants engineers who have “shipped silicon.”

Thu, 06 Aug 2026 14:11:48 GMT

Anthropic confirmed on Wednesday that it is building an in-house silicon team to design custom chips for Claude, the first time the company has publicly acknowledged the effort. A spokesperson told Business Insider the company would co-design hardware and models, allowing Claude to run faster and more efficiently “at the scale our customers need.” The […]

This story continues at The Next Web

Apple's iCloud Private Relay is Leaking Users' Real IP Addresses

Wed, 05 Aug 2026 19:39:18 GMT

Apple's paid Safari protection feature that promises to keep your IP masked doesn't always work, according to security researchers Tommy Mysk and Talal Haj Bakry. It turns out iCloud Private Relay can expose your real IP to websites that use or pretend to use passkeys.

‌iCloud‌ Private Relay is a service included with paid ‌iCloud‌+ plans. It is supposed to hide your IP and DNS information when you browse the web using Safari, but it is not a VPN that masks all traffic from a device. Passkeys use the WebAuthn standard, which stores a private key on your device, not the Safari browser. The request the system sends to the website isn't protected by Private Relay and can leak your IP address.
WebKit hands WebAuthn ceremonies to the operating system's credential service, which issues the HTTPS request itself, directly from the device and unaware of any proxy the host app configured. A page can set rpId to a host of its choosing, and the fetch fires even without user interaction: with mediation: "conditional" and no UI ever appears. [...]

Because the fetch is issued by the operating system's credential service rather than by Safari, it never enters Private Relay's proxied path. The destination server sees the device's real IP address either way.
An attacker who wants to find someone's protected IP can do so by setting up a website that uses WebAuthn. There is no visible passkey prompt and no other indication that an IP address has been accessed in the background.

The researchers also found two other WebKit features that can leak IP addresses and DNS data. DNS prefetching (added in iOS 26) reveals a user's real DNS servers, while WebTransport (added in iOS 26.4) can reveal an IP address.

Apple told 404 Media that it is investigating the report.

Mysk and Haj Bakry created a website to let you test whether Apple's service is leaking your IP address. Since the issue is baked into how WebKit works, some third-party browsers are affected too. Apple will need to address the issue, and in the meantime, users can opt for a VPN for more protection.Tag: iCloudRelated Forum: Apple Music, Apple Pay/Card, iCloud, Fitness+
This article, "Apple's iCloud Private Relay is Leaking Users' Real IP Addresses" first appeared on MacRumors.com

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Jamie Dimon recruits bank and IT leaders to tackle AI risks

Wed, 05 Aug 2026 19:33:09 GMT

JPMorgan Chase CEO Jamie Dimon has been working to recruit banking and IT CEOs to an industry group focused on addressing the risks posed by rapid adoption of AI in corporate America, according to Reuters.

What I’ve learned writing for billions of users

Mon, 03 Aug 2026 08:30:20 GMT

Insights from products that grow and grow.

A few years ago, after running a complex global product launch, I wrote down everything I learned. To track my own ideas. To make sense of things. I’ve kept adding to it ever since.

I’ve worked on products used by a handful of people and products used by a meaningful percentage of the planet. The second kind taught me things the first never could.

This is what I’ve picked up along the way, writing for billions of users across dozens of languages, time zones, and cultures. Some of these lessons are about words. All of them are about people.

Most interfaces are mostly words. Take away all the text and screens stop making sense.

When you have a giant user base, people will interact with your product in ways you never intended. You’ll be shocked. You’ll also learn from them.

Good interfaces don’t need instructions. If you need to write things like “look for the arrow” or “scroll right,” the UI needs fixing. Words shouldn’t explain the design.

Naming features is hard. Renaming them is nearly impossible, especially if millions of people have already started using the product. You get one chance to get it right.

The typeface matters as much as the writing.

Look closely at the letters in your product.06

People have high expectations for software, and that includes the writing. World-class products don’t have mistakes, typos, or clunky phrasing.

Saying one thing is better than saying two or three things.

Fixing the writing can fix the entire company. Support tickets go down by the thousands. Conversion goes up. Users stay longer. There’s a reason the world’s best companies hire and value talented writers.

A shorter sentence is almost always a better sentence.

When in doubt, delete. Remove text to create focus.10

It’s always a good idea to fix things. You don’t need a rigorous business case for it. Don’t waste time trying to calculate the ROI of spelling “Connecticut” correctly.

People won’t read everything you put in the interface. They’ll skim and scan and scroll to what they want. You need to write for those people.

Rewrite everything twice. Rewrite important things twelve times.

Our relationship with technology changes. Writing can shape that change. Remember, we used to be afraid of using our real names online or entering our credit card.

Good writing just feels different. This can be hard to explain to non-writers. There’s a certain kind of click that happens in your head. Revise until you get there. You’ll know it when it happens. Developing this instinct takes a long time.

With a giant user base, you can get stuck trying to write “for everyone.” Try writing for one specific user. An Olympic athlete struggling to set a new record. A first-time mom who’s using your product at 4am. A surfer on their honeymoon in Tahiti. Choose one person and write.

Longer writing needs to be worth it. We expect more from a paragraph than a headline. Make everything the right length.

Users will read what you wrote, then do the exact opposite. It’s okay.

Details matter. The best teams spend time arguing over formatting and punctuation. Is it $45 or $45.00 or 45 (USD)? Do we say “July 5th” or “Next Tuesday”? Is it Settings or Preferences? You need to decide.

Pay attention to the way you format important info like dates, times, and numbers.19

More opinions can sharpen your work.

Sometimes the last thing you need is more opinions.

A perfect error message is still an error message. Try to fix the root cause. Smarter inputs, clearer phrasing. An error is a last resort.

Words can’t do everything in an interface. Understand where other forms of information can help. A great description of a hotel room is no match for a photograph. A street address doesn’t show the same context as a full map.

Writing quality signals product quality. Users make judgments based on the writing. You can’t ask someone to trust you with their private data if they can’t trust you with your commas.

Small wins add up. A clearer headline here. A shorter error message there. A more direct call to action somewhere else. Fix enough little things and the product will completely transform.

Good products get better over time.25

Actions matter more than words. You can’t write one thing and do another. Don’t call it a “free trial” and then require a credit card. Don’t say chats are private if they aren’t. If you’re using writing to hide features or “convince” users, that’s a problem.

Most brand voice guidelines aren’t very helpful. Because most don’t say anything interesting or unique. Calling your brand voice “human” is not enough.

It’s usually a good idea to trust writers with writing. I’ve seen products fail because the wrong person was making decisions about words.

Grammar should be internalized. Learn the rules and break them when it feels right. But don’t talk about grammar too much. Using the phrase “past participle” in a meeting won’t get anyone excited. It’ll make them think of high school English class.

It’s hard to scale your product with a vague, meaningless value prop.

Grow in size without growing in complexity.30

Tell the truth. I’ve seen a single vague sentence generate more support tickets than an actual outage. If something will take nine minutes, say it will take nine minutes.

Don’t invent words when you don’t need to. Digital products have a shared vocabulary that users already understand. Stick with common words and phrases. Log in. Save. Delete. Update. Edit.

Be careful about overwriting. This was something I saw lots of products doing for a long time, adding too much personality and too much text. Making a product “conversational” can sometimes just make it annoying to use.

A great onboarding will solve much more than an endless help center. First-time users who get confused don’t file tickets. They just leave.

You can’t evaluate writing in a spreadsheet or doc. Put the words in the interface and see how they read. Read them in the prototype. Read them on the device you’ll be using. Get as close to the real experience as possible.

Language is always changing. It happens faster than you think, and it’s the job of a writer to keep up. Look at the way people younger than you communicate, or the way your parents email. Nobody’s right or wrong. Language just moves.

Language keeps changing.36

Write without My or Your. Don’t call it My Photos or Your Photos. Just call it Photos. If you don’t, you’ll be chasing this down forever and confusing everyone along the way.

Writers who understand how products are built make better decisions. Learn as much as you can about strategy, technology, and business. A writer should understand how a company makes money and what their long-term vision is. Get as close to the decision-makers as possible.

Come back and read it tomorrow. Time away always helps.

If someone is using your product, they’ve already decided. Don’t market to them. You might talk them out of it.

Pick a word for something and use it everywhere, across every screen, for every user. Don’t call it a “folder” on one screen and a “workspace” on another.

Trust your own instinct as much as you trust your user research.

Users don’t know — or care about — your org chart. Your brand should have a single voice. It doesn’t matter if your emails, notifications, and support documentation come from different teams. Get everyone aligned.

Be careful with playfulness. A button that says “Pay” is clearer than one that says “Ka-chingggg.”

Word and image should work together. Give users context.

What does it mean to rate a movie 5 stars? Language can shape the input.45

The things we build often reflect who we are. Selfish people build selfish products. Kind people build kind ones. To build the best product, build the best team and hire the right people.

Remember that translating for global products is a lot more complicated than swapping out text. Different languages reflect different cultures — and sometimes entirely different ways of thinking.

Be careful about making too many decks. You’ll start thinking in keynotes and bullet points, not UX and interface decisions.

Language has power. Writing makes people laugh and sob and get angry and feel joy and connect with other humans. A gradient can’t do that. A date picker or corner radius can’t do that.

Sometimes words can convey multiple meanings. “New” can mean exciting, but also unproven. Calling a transaction “safe” might make the user worry. Think about every word and what else it might be saying.

Not everything needs a login or account. Let people use your product. If they like it, they’ll stick around.

Not everything needs to be a subscription, either.

Let people move forward, with or without a login.52

You get better by writing more. There’s really no shortcut to this one.

Know that your tools as a writer will keep changing. You’ll be working differently and using new software in 5 years. Maybe sooner.

One of the biggest challenges you’ll face is translating your product into right-to-left languages like Arabic or Hebrew. The entire UI starts to break. Icons, progress bars, and indicators might appear backwards. Build a writing system that can flex across all layouts and languages.

Never, ever mess around with money. There is no faster way to lose trust or infuriate a giant user base. Tell people what things cost. Don’t add “convenience fees” at checkout. Keep auto-renew off by default.

Good writing can’t fix a bad product. But it can reveal problems faster.

Get the first draft done. A bad draft is better than a blank screen.

A finished first draft can go in many directions.58

Bringing writers in early is always a good idea. You can tell when a writer was added to the team the week before launch.

Delete as much as you can.

Good writing is not enough. You also need good layout, hierarchy, and typography.

The legal team will ask you to add words. Rewrite them so they make sense to regular people.

Laws are different everywhere. Required disclosures in Australia are different from those in California or the EU. Create different versions of the same screen if you need to. Don’t try to create one “hero version” that appeases everyone. It will end up being the clunkiest option.

It’s okay to write different versions for different places.63

Avoid the word “content.” It devalues everything it tries to describe. A film is not “content.” Writing is not “content.”

Users aren’t stupid. But they’re sometimes busy or distracted or tired.

Your writing will teach people how to think about your product. Clear language creates clear thinking. Vague or inconsistent language does the opposite.

Deliver bad news quickly and clearly.

Write for the user, not the press release or launch video. Too many companies get this wrong. They start with the marketing assets and then try to build the product around it. It usually doesn’t go well. Designing a screen for a keynote is different than designing it for a user, and great marketing won’t ever be able to fix usability issues.

It’s better to write something well the first time. A ten-second fix, multiplied across a billion sessions, is measured in years, not minutes.

If you’re making changes but things aren’t getting better, try fixing something other than the words. Use different components. Add animation. Adjust the navigation. Keep trying new ways to make the UI better. Don’t just rewrite. Rethink.

What the design process can feel like.70

Accessibility can’t be layered on top of good writing. Turn on a screen reader and listen to your own writing. Use your product with different settings. You need to understand how people actually use your product, then write for them. All of them.

Build writing guidelines and documentation in the tools your team actually uses. Don’t make a PDF that never gets opened.

Users notice inconsistency before they notice almost anything else.

If you’re stuck, close your laptop and go outside. ▉

Nick DiLallo is a writer based in Brooklyn. Past clients include Apple, Airbnb, Etsy, and Google. He currently leads UX writing at Clay. Read more of his work:

When design teams get rid of writers, nobody winsAI interfaces and the role of good writingWriting the onboarding experienceEvery design team needs writersAdvanced techniques for writing good interfacesWriting with respectHow to write inclusive, accessible digital productsThis is good UX writingHow to write digital products with personality

What I’ve learned writing for billions of users was originally published in UX Collective on Medium, where people are continuing the conversation by highlighting and responding to this story.

Proprietarul Froo, vândut canadienilor, pentru 8,6 miliarde dolari, cu tot cu rețeaua de magazine din România

Sat, 01 Aug 2026 15:58:41 GMT

Compania canadiană Alimentation Couche-Tard, unul dintre cei mai mari operatori mondiali de magazine de proximitate și benzinării, a ajuns la un acord pentru preluarea grupului polonez Żabka, care operează în România rețeaua de magazine Froo.

Nicuşor Dan anunţă, pe neaşteptate, că există un acord politic pentru trecerea la euro, indiferent de compoziţia politică a viitoarelor guverne: împreună cu BNR vom întocmi foaia de parcurs pentru trecerea la euro

Sat, 01 Aug 2026 15:51:58 GMT

How Apple Changed Under Tim Cook: 15 Years in Numbers

Sat, 01 Aug 2026 08:10:26 GMT

Apple CEO Tim Cook participated in his final Apple earnings call yesterday, with incoming CEO John Ternus set to take over on September 1. With Cook's tenure coming to an end, we thought we'd take a look at how Apple has changed over the last 15 years.

Cook took over as CEO on August 24, 2011, after Steve Jobs resigned.

Apple's Revenue
During yesterday's earnings call, Bank of America analyst Wamsi Mohan shared an interesting observation about Apple's quarterly earnings. When Cook took over as CEO, Apple's revenue for all of 2011 was $108 billion.

Apple reported $109.4 billion for Q3 2026, earning its 2011 revenue in a single quarter. We don't have the numbers for fiscal 2026 yet, but in fiscal 2025, revenue was $416 billion.

iPhone revenue in 2011 was $47 billion, and just this quarter, it was $54.3 billion.

Valuation
Apple stock is down today after Cook said he expects supply constraints and memory shortages to affect revenue in the current quarter, but last week, Apple briefly hit a market cap above $5 trillion. Apple's market cap is now around the $4.5 trillion mark, and it once again trails Nvidia for world's most valuable publicly traded company.

Apple was the first company to reach a $1 trillion valuation in August 2018, the first to reach $2 trillion in August 2020, and the first to reach $3 trillion in January 2022. It was the third company to hit a $4 trillion valuation in October 2025, and then the second to reach $5 trillion.

A day after Cook took over in August 2011, Apple's stock price was $13.35 (split-adjusted). Today, it opened at $304.81, a roughly 23x increase. There was a 7-for–1 split in 2014 and 4-for–1 split in 2020 during Cook's tenure.

Installed Base
Apple said it has over 2.5 billion active devices. Apple didn't share installed base numbers until 2016, when it hit a billion active devices.

Services
Apple's services category revenue has seen the most growth. It was $9.4 billion in all of 2011, but in Q3 2026, it was $30.7 billion. In fiscal 2025, services brought in $109 billion.

Apple said during the earnings call that it now has 1.5 billion subscriptions. A huge number of services launched under Cook, including:

Apple Pay
‌Apple Pay‌ Cash
Apple Card
Apple Music
Apple News
Apple TV+
Apple Arcade
Apple Fitness+
iCloud+
App Store Search Ads
Ads in Maps

Back in 2011, Apple's services were limited to AppleCare, iTunes, and the ‌App Store‌.

Product Launches
Under Cook, Apple launched everything from the AirPods to the Apple Watch.

Apple Watch
AirPods
Apple silicon chips
Vision Pro
iPhone Air
iPhone X
HomePod and HomePod mini
MacBook Neo

Capital Returns
Cook initiated quarterly dividends in 2012, and also executed an ongoing share repurchase program. Since then, Apple has returned more than $1 trillion to shareholders.

Transition to John Ternus
Cook said yesterday that the transition to Ternus is "going seamlessly." Ternus will become CEO on September 1, ahead of when Apple announces new iPhone models. Cook will remain at Apple as executive chairman, where he will engage with policymakers and help Apple navigate regulatory pressure.

In April, Cook said he planned to remain at Apple for years to come. "I am healthy. My energy is high, and I plan to be in this role for a long time," said Cook. He said he will support current hardware engineering chief John Ternus in any way necessary when Ternus takes over as CEO, and he plans to continue to offer knowledge and experience whenever it's needed. "Apple will be my top priority," he said. "It's who I am at my core, and I can't imagine it any other way."

Cook on Ternus
Cook yesterday said Ternus is the best choice to take over Apple.
The transition is going seamlessly, and I am beyond excited for John to step into his new role and lead Apple into its next era. He is truly one of a kind and there is no better person to take the helm of the company.

As I've said, I couldn't be more confident in his leadership, in our executive team, and in the extraordinary people at Apple who are determined to enrich the lives of our users all over the world. We have a bright future ahead, and I truly have never been more optimistic.
Ternus has been at Apple since 2001, when he joined the product design team. He became vice president of hardware engineering in 2013 and focused on the AirPods, Mac, and iPad. In 2020, he also took on the iPhone, and he became senior vice president of hardware engineering in 2021.Tag: Tim Cook
This article, "How Apple Changed Under Tim Cook: 15 Years in Numbers" first appeared on MacRumors.com

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Claude published malicious code to the Internet and attacked 3 real companies

Sat, 01 Aug 2026 08:10:21 GMT

Anthropic said its Claude-based security models gained unauthorized access to the sensitive production environments of three outside organizations during internal testing designed to measure the models’ offensive cyber capabilities.

The events, which Anthropic revealed Thursday, are the second revelation in 10 days that AI models from the world’s wealthiest providers have trespassed into protected networks, an offense that, in more traditional hacking scenarios, could land the human behind the keyboard in prison for years. Earlier this month, OpenAI said its security models exploited a zero-day vulnerability for use in breaking into the network of Hugging Face, a platform for open source machine-learning models and AI datasets. The OpenAI models went on to steal access credentials and other confidential Hugging Face information. The OpenAI models also exploited publicly exposed credentials to compromise accounts of four other third-party services.

Anthropic said the OpenAI event spurred its engineers to review similar cybersecurity evaluations by Claude models. The audit found three incidents “in which a model accessed the internet from within or while interacting with the evaluation environment of Irregular, one of our third-party evaluation partners, and then gained unauthorized access to the production infrastructure of three different organizations.”

Read full article

Comments

Rivian spinoff Also to start delivering e-bikes after months of delays

Sat, 01 Aug 2026 08:09:13 GMT

Also has big plans beyond the TM-B. The startup mostly refers to itself as a "vehicle" company and has plans to make four-wheel pedal-assist cargo vehicles for Amazon.

Google Earth’s AI deepfake tool only lasted one day

Fri, 31 Jul 2026 19:48:12 GMT

Pompeii reimagined with Nano Banana 2 in Google Earth. | Image: Google

Google has shut down Google Earth feature it launched Thursday that allowed users to edit satellite images with text prompts using AI. The tool essentially let users create AI deepfakes of the real world using text prompts; Digital Digging's Henk van Ess, for example, intentionally generated images adding things like refugees near the Mexican border and a bomb crater by a hospital in Gaza. On Thursday, Google's initial response to van Ess noted that images generated with Nano Banana 2 in Google Earth included a digital watermark and that the company prevented "image creation on harmful topics."

One day later, Google's new statement says tha …

Read the full story at The Verge.

UniCredit, Accenture, and IBM join forces for pan-European banking expansion

Fri, 31 Jul 2026 15:02:40 GMT

UniCredit, one of Europe's leading pan-European banking groups, Accenture and IBM have announced a long-term strategic collaboration that establishes the technology foundation supporting UniCredit's growth across the thirteen European markets in which the Group operates.

The loss of Situational Awareness

Fri, 31 Jul 2026 05:59:45 GMT

Neither artificial nor intelligent.

I am not by any means an expert at finance but I think I do now have some advice for people who are: Do not name your hedge fund anything that will be hilarious if it blows up. Don't use a name like "Long-Term Capital Management" or "Amaranth Advisors" (named for the floral symbol for immortality). Certainly do not call yourself "Situational Awareness," which might as well just be "Hubris, Inc."

Anyway, Situational Awareness, the hedge fund started by a 24-year-old former OpenAI employee that focuses on artificial intelligence bets, has sold most or all, depending on who's reporting, of its entire public stock portfolio to Ken Griffin's Cit …

Read the full story at The Verge.

LinkedIn Adds New ‘Seems Like AI Slop’ Button to Report All the AI Slop

Fri, 31 Jul 2026 05:58:55 GMT

Start clicking, people. This slop's not gonna delete itself.

Tim Cook hints at iCloud Plus tier for AI power users

Fri, 31 Jul 2026 05:58:34 GMT

Apple may allow users to pay to increase their AI usage limits. During an earnings call on Thursday, Apple CEO Tim Cook said that he believes people will want to use Apple Intelligence and the upcoming Siri AI "a lot," adding that "we will have some kind of upgrade possibilities on iCloud Plus where people can buy up the stack."

This fall, Apple will broadly launch its long-delayed Siri AI with iOS 27, which can do things like answer questions about what's on your screen and take action across your apps. It also includes a new standalone Siri AI app that offers a ChatGPT-like interface.

In June, Apple said that its AI features, including …

Read the full story at The Verge.

Anthropic says its own AI models breached three companies during security tests

Fri, 31 Jul 2026 05:57:54 GMT

After OpenAI's models broke into Hugging Face, Anthropic checked its own history and found three similar incidents

Apple Posts Record June Quarter, Warns Supply Constraints Are Coming

Fri, 31 Jul 2026 05:57:27 GMT

Memory prices will continue to increase, Tim Cook said.

The Hugging Face break-in explained

Thu, 30 Jul 2026 05:32:10 GMT

Another way to think about the whole thing is to picture a bear at a campsite. (Really, we are going there.)

Microsoft Will Soon Release an AI Super App

Thu, 30 Jul 2026 05:29:55 GMT

The Copilot super app will span both consumer and enterprise use cases.

Registrul Comerțului: Posibil atac cibernetic care a afectat serviciile online ale ONRC

Wed, 29 Jul 2026 17:19:32 GMT

Oficiul Național al Registrului Comerțului și-a informat utilizatorii că, începând cu data de luni, 27 iulie, unele dintre serviciile online ale instituției au fost afectate de un volum neobișnuit de trafic, asociat unui atac cibernetic. Citește mai departe pe StartupCafe…