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I once had a friend who gave $1,000 to an online fraudster who claimed to be a tax assessor. My own father (bless his soul) once managed to hand over several hundred pounds to a lawyer from Africa promising to send him funds. 

We know it happens. 

We know people impersonate trusted entities to trick us into giving them our money. It’s a scam, one that’s taking place at every level of digital existence. 

Apple is here to help.

Yet another great feature new to iOS 27, Apple’s new scam-prevention tool is a welcome intervention, giving individuals and businesses another line of defense against social engineering scams. While it’s not perfect, it is here, and every Apple user — particularly those working in or managing regulated industries, or any business at all that feels it may be a target for scams, fraud, or socially-engineered crimes — should take a look. According to most security reports, that effectively includes all of us. 

What is Impersonation Risk Detection?

On its support site, Apple explains several hypothetical attack scenarios the feature is designed to protect against, such as when an attacker convincingly poses as a government agency or some other trusted entity to trick you into making a payment or changing account or login details. 

These things are very hard for traditional security protection to spot, in part because you are choosing to take the action — security can’t tell you’ve been tricked. Apple’s new system works to bridge the gap. It looks at information it knows about your device and your Apple Account and tries to spot when you’re being scammed, delivering its own risk assessment.

While Impersonation Risk Detection is a new system-level tool, it does require user consent to permit supported apps to ask the operating system for a risk assessment if the user does something that could be in response to a scam. 

That assessment takes the form of a risk level that helps the app decide what to do next. This will usually trigger additional security steps on the part of that third-party app, including a request for identification, a delay in a transaction, or a warning to let you know you might be being scammed.

Supported apps may request one of these risk assessments when you do things like make a payment or change security settings for your account. Apple tells us these assessments come in the form of one of three levels: Unknown, Medium, or High, with High meaning significant signs of suspicious activity have been detected. It is important to note that while Apple raises these flags, it’s the app that makes the decision on what to do next. Apple’s part ends once it raises the warning.

The settings for the feature also let you take a look at which apps have requested a risk assessment, and why. At least, it will once the feature is activated and has been running for a while. You’ll find a list of requesters in Recent Activity, while the Reasons for Access will show you what actions prompted the request. 

Who sees what?

If you do choose to share information with developers, they will only get the scam warning signals generated using information about your device and Apple Account. Apple, however, will learn the type of action you attempted in the app, and may also learn relevant details such as the number of calls or emails you’ve made. 

This is what Apple says it checks:

• On the device, Apple analyzes interaction patterns, timing, context, and basic sensor data to generate the risk level. 
• Apple never analyzes the content of your Photos, Messages, or Mail.
• Apple learns the type of action you attempted in the app only when the app requests the risk assessment.
• Apps receive only the risk level, not the data.

How to enable Impersonation Risk Detection

Because the tool requires that some of your information is shared, Apple has left Impersonation Risk Detection off by default. Here’s how to enable it or just take a look:

• Open Settings > Privacy & Security.
• Scroll down the pane to find the Impersonation Risk Detection section, which sits beneath the App Advertising item. 
• Tap this, and on the next page you’ll find a toggle to share information with developers of apps that support the feature. 
• Toggle this to on for the protection to kick in. Apple warns it may take four hours to come into effect. 

Once approved, compatible apps can request Apple’s Impersonation Risk Detection signals to see if your device or account shows signs that you’re being scammed. And hopefully you — or my dad — won’t get fooled again.

Now please subscribe to my daily, human-curated Apple-related news headline feed at The Core, or follow me on BlueSky, LinkedIn, or Mastodon.

Anthropic now allows you to run Claude Code via cloud sessions without signing up for the research preview, and it's offering up to $250 in free usage credits, so more users can give it a try. [...]

Před 16 lety Steve Jobs odpovídal novinářům na dotazy ke kauze Antennagate • Až nyní se však objevila nahrávka z této akce, která následovala hned po keynote • I po letech je vidět profesionalita Jobse ve všech ohledech

EVENT: The Register is hosting a private dinner in New York on Tuesday 27 October for senior technology, infrastructure and data leaders, with LucidLink. Joe Fay takes the chair, it runs under the Chatham House Rule, and nothing said leaves the table. Distributed teams are producing more unstructured file data than ever, and most of them reach it through infrastructure designed for an office: legacy NAS, a VPN, and a sync-and-download habit nobody actually chose. It rarely fails outright. It charges rent somewhere else instead, in duplicated storage, in waiting, in governance gaps, and in the hour somebody loses working out which version of a file is current. The conversation worth having about that is not the architecture diagram. It is what a team did when it stopped being in one building. Which workaround somebody has quietly been paying for ever since. What broke when they tried to retire the NAS, and what they would do differently now. People say that over dinner. They do not say it on a recorded webinar. So this is dinner. Drinks, a handful of questions across the table, then more drinks. Everyone there as a peer, and a chair whose job includes stopping anyone who starts to pitch. The premise is deliberately not rip and replace. The evening is about modernizing around the storage and governance investments an organization already has, rather than pretending they are not there, which is usually the point at which these conversations stop being useful to the people who have to pay for them. On the table: handling the growth in unstructured data, supporting distributed teams without paying for the same file three times, sync and version control, and whether any of it holds up against a security incident. Holly Bossert, Commercial Sales US at LucidLink, joins the conversation. Joe Fay of The Register moderates. The table is for senior technology, infrastructure and data leaders carrying this now, not planning for it later. Dinner runs from 6.00pm to 8.30pm at The Capital Grille, 120 W 51st Street. Places are limited and go by invitation. Request one here.

OpenAI appears to be preparing a new ChatGPT Pro Max subscription that could cost $500 per month, but it's unclear when it'll begin rolling out. [...]

AI agents can operate through human credentials and take actions that existing SOC 2 controls may not distinguish from human activity. Token Security explains why SOC 2 needs to adapt to address the security gaps created by agent identities. [...]

OpenAI v prosinci skončí s podporou uživatelsky vytvořených GPT asistentů • Tvůrci musí své konfigurace včas migrovat na nový systém pluginů • Převod nepřenáší vlastní akce ani předchozí konverzace a nastavení sdílení

Two actions-cool GitHub Actions have been disabled for a second time after the repositories became accessible last week, months after they were compromised during the May 2026 Mini Shai-Hulud campaign. The affected GitHub Actions are listed below - actions-cool/issues-helper actions-cool/maintain-one-comment Visiting either of the repositories now shows the message: "Access to this Ravie Lakshmananhttp://www.blogger.com/profile/[email protected]

There’s no shortage of fantastical possibilities, most involving the speculative concept of superintelligent AI.

Earlier this month, artificial intelligence researcher Jacob Coxon resigned from Anthropic after just four months. In an announcement on X, he stated: “The people building AI earnestly believe that it could kill us all by the end of the decade.”

A senior member of Anthropic’s staff, Evan Hubinger, actually agreed with Coxon, adding he personally thinks the chance of this happening in the next decade is more than 10 percent.

Understandably, these statements made waves. There’s now lots of talk about slowing down AI research and increasing “human control” over the technology.

But how exactly might AI kill us all? There’s no shortage of fantastical scenarios, and most of them involve the concept of “superintelligent” AI—that is, AI that’s more capable than humans.

I’ve distilled these scenarios down to the top five, ordering them roughly from most vague to most precise. And I’d argue the list is also ordered from least probable to most probable.

1. We’ll Never Know

AI doomers often justify their concerns by means of an annoying catch-22 paradox: how can we possibly imagine what a superintelligence might do to take out less intelligent beings like us?

We’d have to be superintelligent to predict what a superintelligence would be able to do. It’s like asking your family dog to imagine thermonuclear war.

The good news here is that superintelligence is still perhaps some distance away. Current AI models are really good at solving particular problems, but that’s not the same as being more intelligent than a human in all domains.

However, AI did recently solve one of the seven most challenging maths problems known. It’s apparently closing in on others, which might leave you feeling less optimistic here.

2. Paperclips

A superintelligent AI would likely be extraordinarily competent at achieving its goals. But it might be indifferent to human survival.

A classic example of such indifference comes from Oxford philosopher Nick Bostrom’s imagined superintelligent AI that’s been designed to optimize paperclip production. To produce its preferred form of office supplies, it quickly converts all available matter—including humans, planets and stars—into paperclips.

What we have here is the perfect execution of improperly specified objectives. The AI doesn’t hate humanity; it simply recognizes we’re composed of atoms that could be better utilized for paperclips. It’s not personal.

The good news here is that this scenario confuses intelligence with power. A superintelligent AI doesn’t necessarily have the power to achieve its goals. Turning the planet into paperclip factories would require planning permissions.

Even if it got the permissions, building too many paperclip factories would lead to inevitable public outcry. Interest groups would block the proceedings in the courts. Environmental activists would block the bulldozers.

There’s a lot of friction in the world that prevents even the very intelligent from imposing their will on the rest of us. In fact, you could think of data centers as a current embodiment of the theoretical paperclip scenario. And humans are increasingly pushing back against turning the planet over to data centers.

3. Bioweapons

Humanity could be killed by a superintelligent AI making and releasing some dangerous new bioweapon into the atmosphere. This is, in fact, one outcome of the AI 2027 scenario by the AI Futures Project, a non-profit dedicated to forecasting the impacts of advanced AI.

This risk was made more concrete last month, when researchers at Stanford University announced they’d used a genetic language AI model to synthesize 16 new viruses.

Worryingly, they just sent the genetic sequences off to a mail-order lab and it sent the viruses back in test tubes. The whole experiment cost a couple of hundred thousand dollars at most.

The good news here is that it’s remarkably hard to kill everyone with a new virus. To do that, you need a virus that’s very transmissible, so it spreads far and wide. But it’s a rule of biology—viruses that spread easily are typically less fatal. By contrast, if a virus is very fatal, transmissibility tends to go down, as most people infected die before there’s time to spread the infection.

COVID killed less than 1% of humanity. The deadliest pandemic in recorded history was the Black Death, when the plague killed more than one-third of Europe’s population in the 13th century. However, even the plague would likely be much less deadly today due to our increased medical knowledge and better sanitation.

4. Nuclear War

What if AI got into the nuclear command and control chain and started a nuclear war? We’ve come close to nuclear war by mistake several times in the past 50 years.

We’re told that nuclear command and control is completely disconnected from the internet. But, as we saw in 2010, Iran’s nuclear centrifuges got taken out by a computer worm called Stuxnet, thought to have been brought in on a USB stick. AI can also give the military false intelligence, which could lead to irreparable actions.

The good news here is that nuclear stockpiles are down. But they are still enough perhaps to take out half of us. And it wouldn’t be by the nuclear blast itself, but the famine in the nuclear winter that would follow.

5. Other Humans

Perhaps the most likely risk is that we take ourselves out. And AI might precipitate this.

Imagine—and it doesn’t take a lot of imagination—that AI causes massive job losses, pollutes the information space with misinformation, fractures our politics, and destroys human relationships with fake synthetic companionship.

Society might easily break. Slowly but surely, we’d stop being able to support human life at any scale.

What then to take away from all these scenarios? There are some things to be worried about for sure. But not to be too worried, I hope.

Toby Walsh is the author of God AI: boom or doom? What to expect when the machines outsmart us, published by La Trobe University Press.

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

The post How Would AI Actually Kill All Humans? Here Are the Top 5 Scenarios appeared first on SingularityHub.

Americký letecký úřad spustil nový AI systém pro předcházení zpoždění • Technologie SMART analyzuje stovky datových toků v reálném čase • Lidští dispečeři přesto zůstávají plně odpovědní za bezpečnost provozu

Cybersecurity researchers have flagged a new version of PamStealer that ensures that the main payload can only be recovered using a server-side decryption chain. The latest artifacts, per Jamf Threat Labs, continue to rely on the same JavaScript for Automation (JXA) dropper mechanism, but modify the lure and the delivery method. "Where earlier variants embedded their payload key material Ravie Lakshmananhttp://www.blogger.com/profile/[email protected]

The 7,000 km (4,350 mile) cable, called Petal, will connect the US and France. Meta is partnering with NEC and Sumitomo Electric Industries to build it, and working with French telecommunications company Orange to coordinate the landing of the cable on the French coast.

Petal will have more than double the capacity of today’s fastest transoceanic cables. Last November, AWS laid plans for a 320 Tbit/s cable between the US and Ireland, while a cable connecting Australia and the US, announced in January this year, will deliver 400 terabits per second.

The need for greater data connectivity has prompted a boom in subsea cable deployment, but their existence is making some US lawmakers rather twitchy, as they are fearful of the security implications. There have been calls for the big service providers to provide details of all the cables they have in place. The concerns are warranted given the number of incidents involving subsea cables.

This article first appeared on Network World.

Fanoušci ergonomických klávesnic vám potvrdí, že najít dokonale vyhovující model hraničí se zázrakem. Nejnovější pokus se jmenuje Genius Ergo KB-7000BT a nakročeno má dobře – klávesnice je rozdělená klínem a mírně zvlněná, aby na ni ruce padly v přirozeném úhlu. Zápěstí podepře měkká integrovaná ...

Microsoft announced it will deprecate the Windows Deployment Services (WDS) server role starting with the next Windows Server release. [...]

Google’s Gemini 4 AI model is in the early days of post-training, the phase in which a base AI model is refined to behave reliably, and should be released “much earlier” than the end of this year, Google DeepMind head Koray Kavukcuoglu told The Information at its AI Agenda Live Summit. Some Google observers have speculated that this could be as early as October.

Kavukcuoglu recently replaced DeepMind founder Demis Hassabis as head of the Google business unit.

The launch of Gemini 4 may lay to rest concerns about the delayed release of Gemini 3.5 Pro, which Google was originally expected to announce at its May 2026 developer conference.

While less capable models in the Gemini 3 family have been frequently updated, Gemini 3 Pro has only been updated once since its November 2025 released. In contrast, OpenAI — spurred on by Sam Altman’s “Code Red” memo — has released three updates to its frontier AI model since then: GPT 5.5 Pro, GPT 5.6 Astro, and GPT 6 Astro. Anthropic, too, has updated its most powerful Claude model several times.

Google has not been entirely idle in the AI arena, concentrating its efforts on updating less powerful, more affordable Gemini versions. In July, it announced three Gemini Flash models, aimed at more routine AI tasks, but the company remained silent about its high-end alternative.

V Xboxu končí dalších 268 lidí. • Vývoj Halo přebírá Activision, pod který přechází také Rare. • Studio Obsidian míří pod křídla Bethesdy.

A Kosovar national has pleaded guilty to operating Rydox, a large illegal online marketplace that sold stolen personal information, login credentials, credit card details, and cybercrime tools. [...]

Security leaders keep debating whether AI will produce an entirely new class of cyberattack. The nearer change is quieter and already visible: AI has made a failed attack cheap to retry. The routine version looks like this. An attacker lands on a low-privilege cloud account, and the first try at privilege escalation goes nowhere. That dead end used to cost hours of documentation reading, [email protected]

AI PCs that cut token costs? That may appeal to enterprises.

A new breed of agentic AI PCs promises to do exactly that. The powerful laptops can cut token costs by completing AI work locally instead of sending it to expensive LLMs in the cloud.

HP’s newly announced ZBook Ultra G3a mobile workstation and upcoming laptops from other PC makers have powerful GPUs and large memory pools designed for AI and graphics. The ZBook Ultra G3a uses an AMD Ryzen AI Max Pro processor, while laptops from other PC makers will feature Nvidia’s RTX Spark superchip.

Nvidia’s Blackwell GPUs have dominated data centers, but the company is now targeting a larger chunk of the PC market with the RTX Spark, which includes a Blackwell RTX GPU. The first wave of RTX Spark laptops coming from Asus, Dell, Lenovo, and other PC makers is targeted at consumers, with enterprise models planned for later. HP’s ZBook Ultra PC, on the other hand, is squarely aimed at enterprises.

Without connecting to the internet, the PCs can run agents and chatbots, generate video, and write code on AI models with billions of parameters.

“It’s the only PC where you have enough memory to run the large models, enough compute to run them fast, and at the same time, all of your tools that we’ve accelerated for years… are all working,” said Gerardo Delgado, senior director of product management at Nvidia.

To be sure, cloud-based AI models are more powerful and capable. But AI in the cloud is expensive, and these PCs can take some of the heat off those bills.

“People are starting to get either burned or really concerned when they’re starting to get their AI token bills,” said Brian Allen, manager for Global Z workstation products at HP.

At least 20%-25% of high-end AI workloads in the next two to three years will be running on AI PCs versus totally in the cloud, said Jack Gold, principal analyst at J. Gold Research.

The agentic AI machines won’t be inexpensive, but they will cut recurring cloud costs, which is especially important in the ongoing research and engineering work that produces multiple versions of a project, Gold said.

“We will continue to see more offerings in this space in the next six months, particularly as more vendors release chips specifically targeting this space,” Gold said.

Early AI PCs, notably Windows machines with Microsoft’s Copilot+ branding, offloaded some basic assistant tasks, but the ZBook Ultra G3a is an AI mobile workstation aimed at high-end enterprise workloads.

“I’m actually building large language AI models. I’m doing fine tuning. I’m doing inferencing,” Allen said.

For example, designers can use AI in Autodesk Revit 3D modeling software at an airport without an internet connection. That is made possible by the inclusion of Perplexity’s Portable Computer offering.

Designers can then connect to frontier models in the cloud to advance the project. Perplexity taps across roughly 19 frontier models to find the right fit.

Model Context Protocol (MCP) servers bridge the AI models with applications on the PC with a user’s permission. AI on PCs can keep sensitive data within the company’s boundaries.

HP has partnered with Perplexity on Revit, but “you’re going to see those MCP connectors really start growing and tying into more software applications,” Allen said.

HP’s laptop, expected to be available in October, has packed up the CPU, memory, and AMD’s GPU tightly on one chip, so data moves quickly between the components. That’s important for AI and different from regular PC designs that offer upgradable memory.

HP hasn’t shared pricing for the mobile workstation, but Gold said it will be far costlier than regular AI PCs such as Microsoft’s recently upgraded Surface Laptop 13-inch and Surface Pro 12-inch models with Qualcomm’s Snapdragon X2 Plus chips, which start at $1,199 and $1,149, respectively.

HP provides an “ROI calculator” that lets curious shoppers play around with the cost of running AI locally versus the cloud-based cost. “You can sort of say, ‘hey, this PC pays for itself in nine months based upon this type of usage,’” Allen said.

ROI calculators like HP’s “have a number of assumptions built in that may not be applicable to every workplace,” said analyst Gold. “But calculators like these are still valuable for companies to do some higher-level evaluation of options.” In some cases, enduring high cloud-based token costs could be worth it for complex workloads and bringing products to market quicker, he said.

Nvidia received an intense wave of customer requests for mobile workstations after models surpassing Opus 4.6 excelled at coding and rocked the AI world. “That is the poster child right now, in development teams, coding teams, moving really quickly into local hardware,” Nvidia’s Delgado said.

Delgado said agents on AI PCs are driving engineering apps like AutoCAD. “The idea is not to replace the architect,” he added.

Enterprises will take a hybrid approach to AI, with work being done on PCs, the edge, and in the cloud, Delgado said. “Everyone that tells you that everything is local is just trying to avoid the fact that the cloud models are improving at an exponential rate,” he said.

Most of the work doesn’t need cloud-level intelligence, and a lot of it can be done locally. Nvidia has tools that can redirect inferencing to idle PCs on a network — such as Macs and Windows PCs with Nvidia GPUs — to keep data in-house. It can also redirect to the cloud when needed.

“The next big thing in agents is inference routers that just point you to local hardware when it’s good enough, to cloud hardware when you need a bigger model,” Delgado said.

New hardware with fancy specifications is great, but it won’t deliver much if the AI engineer isn’t smart, said Deepak Seth, senior director analyst at Gartner. “You can give them the best tool, and they will still come up with the stupid stuff,” he said.

The solution to every problem is not just having more power, but “more power with the right people will lead to better results,” Seth said.

Čína pravděpodobně staví mateřskou loď pro vypouštění velkých robotických ponorek bez posádky. Vojenští a námořní experti objevili její základy na satelitních snímcích v loděnici Hudong-Zhonghua v Šanghaji. Ke stejným závěrům dospěl také The Telegraph, který měl k dispozici družicové záběry od ...