A slew of recent studies indicate that AI isn’t dramatically displacing workers. At the same time, there were no indicators that the fast-moving technology is creating a lot of jobs, even as AI skills remain in high demand.

Stanford University researchers in an August study found that any AI-related job declines were concentrated among young workers aged 22–25. But for older and more experienced workers that wasn’t the case.

“Claims of economy-wide AI-driven job losses are not visible in payroll data through June 2026,” the researchers said, citing ADP payroll information. Stanford partnered with ADP to conduct the research.

The decline for young workers is more often related to the automation of some work tasks by AI, as opposed to its use to complement work. In contrast, AI is more often used by experienced workers to augment what they do. 

According to the Stanford report, workers between 22 and 25 and employed in jobs highly exposed to disruption by AI are falling behind their older counterparts. Their employment levels in June were about 19% below the same age group in less-exposed occupations. That’s compared to where they would be if both groups had kept pace with each other.

“Experienced workers show no comparable gap,” the researchers said, adding that “this is consistent with recent reports of a worsening job market for entry-level workers.”

Employment of younger workers in AI-exposed jobs fell about 11% from late 2022, while the same age group in less-exposed jobs actually grew about 10%. “For older age groups, we find much less marked differences in employment growth across AI exposure quintiles,” the researchers said.

Stanford, which created a lab last year to study AI’s impact amid heightened fears of the technology’s economic effects, said its numbers were based on available indicators.

AI’s adverse impact on young workers has been well documented, with many of them laid off in the initial wave of AI automation. AI has also suppressed wages for entry-level workers.

AI was cited for 116,175 job cuts in 2026, but that number is declining. The technology  was blamed for 3,462 cuts in August, according to data from Challenger, Gray and Christmas.

It’s the “lowest monthly total since December 2025 when 142 cuts were attributed to AI,” the company wrote in a blog entry. The research firm also noted aggressive hiring plans for companies in 2027.

AI is adding value to companies in different ways, and humans are an important part of that process, said Michael Chui, a senior fellow at QuantumBlack, AI at McKinsey. “The night shift is real now,” he said. “People are sending off their agents to write code and checking in the morning.”

MIT late last year established an AI labor index to determine how agents are affecting the workforce. The school’s Project Iceberg looks at how the coordination and interaction with agentic AI changes how work is done.

Despite the disruptions, demand for AI-related talent continues to rise, tech industry consortium CompTIA said last week. About 320,000 job listings in August required AI-related capabilities, a 4.5% increase from July.

AI-related hiring is outperforming the broader tech market, with demand for AI skills up 96% year-over-year, said Kye Mitchell, head of Experis North America, which is part of ManpowerGroup.

“We’re seeing real growth…in marketing management and project management roles, suggesting employers are looking beyond the people building AI to the people applying it,” Mitchell said.

More broadly, the US economy added 162,000 jobs in August, according to US Department of Labor figures released last week. CompTIA noted that tech employment across all sectors rose by 86,000 workers in August.

But within the tech sector, 14,700 positions were cut, CompTIA said.

Late-breaking reports suggest Apple has built a new Siri AI ‘Recaps’ feature that summarizes your day for you. The idea sounds great until you recognize that this summary will also include overheard conversations. 

Suspending the huge red flag of concern over privacy and data protection for a moment or two, why would this be useful and who is it for?

How it’s supposed to work

First, it is being described as an Apple Watch feature that will only be available on the latest models: Apple Watch Series 12 and Apple Watch Ultra 4, as these allegedly include secure audio processing hardware. Reading between the lines, that suggests the devices will be able to listen to and process audio on device, which implies that the information won’t need to leave your smartwatch, not even to your iPhone.

The report also says the feature doesn’t make a transcript, nor does it store the audio; it instead gathers key datapoints from what is said to include in the summary, deleting all the remaining information in the process. You can have the feature working all day, on-demand, or only in specific locations. The idea seems to be to provide some kind of actionable summary of events and key conversations that take place during the day. I imagine the subtext is to digitize as much as possible of your daily existence as Apple thinks you will be comfortable with to create the kind of datapoints contextual AI requires if it is going to help with your life.

The case for it

That sounds fine, up to a point — the idea that a digital assistant will be able to recognize key events, moments, and requirements to remind us of them, act on them, or suggest next steps concerning them is certainly a notion that’s gained currency in tech circles. They see it as augmenting human achievement, enabling people to become more productive, more efficient, and capable of doing more with less effort. At least, that’s part of the argument.

What is wrong with that (other than concerns over privacy or a desire not to have one’s entire waking life transformed into a series of datapoints that can be measured, tested, or surveyed by entities outside of our control), right? If you have nothing to hide, you have nothing to fear, at least, not until times change and what didn’t need to be hidden in the past becomes something that must be shrouded in future.

Apple’s privacy defense

Apple, of course, has its strong privacy story to lean into as it introduces this surveillance-as-a-service solution; it’s an argument that says it recognizes how this tech can be abused, and wants to deploy it correctly. It will point to that record as it promises its system doesn’t gather data, doesn’t collect it, and doesn’t keep any form of transcript on or off the device. The company should be commended for building a system that works this way, recognizing as it does that the best way to protect confidential information is not to gather it in the first place.

The warning

But what Apple has also done with this new speculated upon — and as-yet-unconfirmed product — is to show us what these tools can already do. Much of this is already visible; take recent news that LG smart TVs constantly collect and upload user data as an illustration of the seemingly egregious ways in which such tech is used. (LG denies the claim.) What Apple shows us is that with AI in the picture, all your waking moments can be collated, curated, analyzed, digitized and rendered into actionable data. Apple may not be doing that, but others will not be equally cautious, so we owe Apple a debt for warning us of what’s at stake.

Though we don’t know whether Apple will actually introduce this new service, the source of the claims is one of the strongest in the industry. What we do know is that the technology required to build systems like this exists, along with AI systems capable of sourcing, sharing, and sifting through that information. What we don’t yet know is how to remove ourselves from the data stack.

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

AI note-taking applications are increasingly used by workers to record meetings, generate conversation summaries and suggest post-meeting action items. 

Along with the promised productivity benefits — enabling users to focus on meetings rather than actively taking notes — the emergence of these AI tools has raised privacy questions, particularly around obtaining prior consent by meeting participants for their use. Those concerns, in turn, have prompted a spate of lawsuits against software vendors that sell AI notetaking tools.

In some ways, the underlying questions are not new: It’s long been possible to record a phone call with a dictaphone, and laws around surreptitious recording have been around for decades. Yet widespread access to AI notetakers via desktop or smartphone apps means that it’s easier than ever to record a conversation for future reference. 

Among the thorny questions arising from the technology’s use: what happens to conversation data sent to a software vendor’s servers for processing? Are the recording and transcript used to train those vendors’ AI models, for example, or create biometric voiceprints? Those practices are among the issues being considered in US courts. 

Otter, which claims to have 35 million users, was subject to a class-action complaint in a federal court in California last year. That complaint accused Otter of recording individuals without consent and using their voices to train its speech recognition AI tools. Last month, a judge rejected Otter’s attempt to dismiss the main claims, though the scope of the case was narrowed.

A lawsuit filed against another vendor, Fireflies, in an Illinois court late last year, alleges the company collects and stores biometric voiceprints without user consent, in violation of the Illinois Biometric Information Privacy Act (BIPA). Fireflies claims to have more than 20 million individuals and 1 million organizations as customers.

Earlier this year, a class-action complaint in a Washington court claimed that a live transcription feature in Microsoft’s Teams collaboration application also violates BIPA by collecting biometric data without consent. 

And most recently, a complaint alleged that Granola, a well-funded startup, designed its product to be used without the knowledge of all meeting participants, in violation of the Electronic Communications Privacy Act (ECPA). That complaint also claims Granola trains its AI models on conversation data without consent. 

None of these cases has yet been resolved, and it’s unclear whether any of the vendors broke the law in the design and delivery of their products and services. But the lawsuits highlight considerations for businesses that allow the use of AI notetakers, both in terms of prior consent for recordings and understanding how conversation data is handled.

More broadly, the lawsuits raise questions about how existing privacy and consent rules apply to new technologies that make it easier to record others, whether through AI note-taking apps, smartglasses, or other recording devices.

Computerworld spoke with Brian McGinnis, partner at law firm Barnes & Thornburg and a founding member and co-chair of the firm’s Data Security and Privacy Law practice group, about the focus of the lawsuits, potential outcomes, and how businesses can deploy AI notetaking apps safely.

Several cases have already been brought against popular AI note-taking apps. What are some of the main commonalities between these? Which laws are the vendors accused of breaching? “The common allegation is that these companies capture communications of people who did not agree to the recording or receive adequate notice. Some of the lawsuits also allege that meeting data is used to train AI models and that consent cannot meaningfully be withdrawn once the data has been processed.

“There are various federal and state claims. You’ve got the Electronic Communications Privacy Act, a federal wiretapping statute. As a general matter, the Electronic Communications Privacy Act permits an interception when one party consents, subject to statutory exceptions and questions about whether the technology constitutes an unlawful interception or third-party eavesdropping. In other words, if you, as the user, provide consent, you can be on a meeting with 20 other people and it’s deemed to be sufficient; you don’t necessarily need to get the consent of other people. 

“But California and a minority of other states are what we call ‘two-party consent’ states, meaning each individual on the call has to give consent; it’s not sufficient for you as the person who turns the notetaker on to provide the consent — you also have to get the consent of others that are being recorded. There are state laws around that.

“There’s a law called CIPA, the California Invasion of Privacy Act, that’s being utilized in this context.  We see a lot of suits being brought under that law — it’s a wiretapping statute designed for telephone wiretapping that’s now being applied to the internet.”

What about the use of biometric data? “A growing number of states regulate biometric data, with Illinois’ BIPA being particularly prominent because it provides a private right of action. This means an individual can sue a company for violation of the law.  

“That law covers biometric information. With an audio recording or recording of ‘dumb’ video that isn’t running any algorithms, you’re not necessarily collecting any biometrics. But when you start identifying people, you’re recording things like faceprints or voiceprints, which are in the definition of biometric information within the statute. Now you’re not only collecting personal information, but also biometric information, which is considered very sensitive and much more highly regulated. 

“Then you’ve got the private right of action that goes against it. Part of the argument here is that recordings taken by the AI notetakers can be used to produce some form of biometric information, such as a voiceprint.  

“We’ve seen a lot of cases, and a lot of changes in industry as a result of this law. Shutterfly had a famous case about scanning for people’s faces and things like that in Illinois that changed the photo storage and processing industry a little bit. 

“A lot of companies stay out of Illinois to avoid this law specifically. But a customer organization might not know exactly who’s in a meeting and where a person is located at the time of the meeting. So, you need to either follow that law and get individual consent, or stay out of states with biometric laws if you want to use some of these tools. 

“It’s just a further challenge for these applications if the goal is to be used as much as possible with as little detection as possible.”

What are some of the potential outcomes for these cases? “I think it’d be unlikely to get an outright ban, absent passing some kind of new law that says these tools are per se illegal for use. It’s much more likely the outcome will require some changes and controls over the way that they get used. The clearest case would be some kind of a pop-up notice: ‘Hey, this meeting’s being recorded, here’s who it is, here’s their privacy policy, here’s their terms of service – do you consent to it?’ And getting opt-in consent from anybody who wants to be recorded. 

“The notion that only one person in the meeting has to say it’s okay and you can just automatically record everybody else, I think that’s probably at risk, and could potentially be replaced with a standard that requires everybody to consent before it’s considered legal.

“But the newer —and more interesting — wave of these is the Granola case, where part of its marketing is that people aren’t aware that it’s there. The Granola complaint alleges that the product was designed to operate without alerting other participants. It’s possible that kind of activity could result in a decision that would ultimately ban it outright. In other words, that it’s illegal to utilize these tools if you aren’t providing notice to everybody and/or aren’t getting consent from everyone on the call. That’s a possible outcome that we could see.

“To me, that’s interesting when you think beyond AI note-taking and into the broader world, with conversations around, like, Meta Glasses, or any of these kinds of AI wearables. Granola in particular has an Apple Watch app, and there are other wearable or physical devices — there’s one [Plaud Note] that sticks on the back of your phone and is essentially an always-on recording device. 

“With these devices, you’re going from an online meeting where you can provide notice and there’s a structure to obtain consent, to walking down the sidewalk and recording people and casual conversations. Maybe it’s somebody you’re having a conversation with, maybe it’s somebody at the table next to you in the coffee shop that you have no relationship with whatsoever — what are the laws around consent and notice in those cases, where there’s no digital interface to put that up in front of people? Do you have to go around with a pad of paper and a pen and get people to sign consent to use these things? Do you have to physically tell them?

“Those are the more interesting conversations that this line of cases is just at the beginning of helping us get some answers on. In other words; how do you get consent? How do you provide notice in a world where we don’t have documents or screens in front of us to easily handle that? Those are interesting questions that the law will have to figure out here.”

These tools are increasingly used in the workplace. How can businesses be sure they deploy the technologies safely? “We’re getting a lot of questions from our clients about this topic, because they’re really unsure and uncertain of how to handle these tools.

“Obviously, there’s a push for broad use of AI within their companies, for productivity increases within their company. People like the tools; they want to be able to use them. But then we also hear a lot of stories about ‘I jumped on a meeting; I didn’t even know it was being recorded, then I got an email afterward with a transcript of it,’ and ‘half of what it recorded wasn’t actually what I said, or it was interpreted incorrectly’ — things like that. So there’s a lot of consternation amongst our clients about the people within their organizations using it. 

“I can’t tell clients definitively that they’re legal as they are; there are ways to use this legally and safely that aren’t going to get your organization sued, but you probably have to do some things that are beyond what’s provided ‘out of the box’ by the software providers. 

“With Granola, for example, my understanding is that certain notice features may not be enabled by default. You can turn on video or audio watermarking, and you can turn on the notice that pops up in these things, but I think it ships without those features enabled. That puts the responsibility on the individual user to determine and then implement their own legal privacy and legal compliance mechanisms using their settings.

“You really have to play to the most stringent state’s law. I would advise a company that, to decrease your chances of getting in trouble for use of these tools, you need to obtain consent of all parties on the call. You can do that verbally, as well; written is even better. 

“Then it’s about having an internal AI note-taking policy. Think of a BYOD policy, which all these companies have, or an AI usage policy — this could be part of that policy, or a standalone policy: ‘Here’s how our organization thinks about these tools:  you can only use these approved tools and, if you’re going to use them, you have to turn on these features. You have to get consent from everyone. Here are limits on what you can do with the output of those transcripts or recordings.’ 

“If you set all that up and do the compliance and governance work, I think you can use these tools and most likely stay on the right side of the law. Certainly, the law doesn’t prevent consenting adults from consenting to the use of these kinds of tools.  

“But the further you get away from that written consent standard, the more problematic it becomes. If you just want to go to a notice standard and not obtain actual opt-in consent, or, even worse, if you want to try and do this without anybody knowing, that potentially could get challenged.”

By now, you probably know my stance on Gemini and other generative AI gobbledegook — right?

In short: It’s an insanely powerful form of technology (obviously). But it’s also wildly inaccurate and ineffective as an all-purpose answer engine, and by cramming it into every last nook and cranny, Google is doing a serious disservice to its users — and to itself.

That being said, generative AI can be incredibly useful. The key is simply to frame it as a purpose-specific tool for the right type of limited task as opposed to treating it as the end-all answer for everything, as most tech players seem overly eager to do these days.

Here in the land of Android, I’m always looking for purpose-specific ways Gemini can make our lives easier. Over time, I’ve found those ideas often aren’t the big headline-making features Google and other tech companies market but rather random little off-the-beaten-path possibilities that rarely get emphasized.

Today, I’ve got a new Gemini Android advantage for you to explore — another one that I’ve never seen advertised anywhere but that works brilliantly well and solves a long-standing limitation of our modern mobile gizmos.

It’ll take you all of a minute to master and cost you precisely $0 to pull off. Ready?

[Get next-level knowledge in your inbox with my free Android Intelligence newsletter — one useful new thing to try every Friday, straight from me to ye.]

Gemini’s custom sound advantage

This Gemini-provided power-up very much follows the path of thinking about AI as a limited, purpose-specific tool for a narrow task — the exact sort of area where AI excels.

I won’t keep you waiting: Gemini, as I discovered whilst poking around within it recently, is really good at generating unique, custom ringtones and notification sounds based on your personal preferences and specifications.

It almost seems obvious, once you think about it. But I sure hadn’t thought about it up until now — and I suspect most other folks haven’t, either.

The advantage here goes beyond just superficial silliness, too: By creating your own custom ringtones and notification noises, you can know exactly what event your phone is alerting you to within a split second of hearing the associated sound — without having to rely on the same limited and often underwhelming pool of default options that everyone else uses (or, worse yet, having to lean on shady, ad-ridden “ringtone apps” to find mediocre alternatives). That means you’ll know within a heartbeat when your boss or an especially important client is calling or if an incoming call is a random unknown number.

On the notification front, you can create a specific, memorable sound to accompany a new message in an important work-related Slack channel and a different distinctive sound for a high-priority email. They’ll all be sounds that you make and identity with and that no one else in the world uses. That’s pretty powerful.

And creating these custom sounds couldn’t be much easier, either, once you realize it’s possible:

First, just fire up Gemini on your phone (or on any device you’re using) and tell it what you want. So, for instance…

• Create a soft, subtle ringtone that’s reminiscent of an old office phone sound.
• Create a ringtone that sounds like an 8-bit version of The Final Countdown.
• Create a one-second high-pitched notification sound that brings to mind the Super Mario Bros theme song.
• Create a short notification sound that mimics the Back to the Future time circuits noise.
• Create a notification sound that sounds like a robot saying “ALERT, ALERT!”

The only limit is your imagination. And if you’re not feeling especially imaginative, you can even ask Gemini to give you a list of ideas for distinctive, memorable ringtones or notification sounds based on geeky nostalgia, 80s pop-metal, or whatever it is that tickles your fancy.

Once you’ve sent a request, Gemini will — somewhat confusingly — spit back a big honkin’ block of HTML code. This is because, for reasons unknown, the system can’t or won’t just provide a sound file directly. Go figure.

But from there, it’s just one more quick step to get the file you need: Click or tap the copy icon in the upper-right corner of that code block — the icon that looks kinda like two stacked, rounded rectangles — to copy the entire chunk of code onto your system clipboard.

Then open up your browser and go to the website JSFiddle.net. It’s a well-known, long-standing tool for running code like HTML right in your browser and seeing the result, and it works entirely in the browser and without any downloads or special permissions required.

Tap or click into the “HTML” field, then paste in the code from your clipboard (by long-pressing any open space, on Android, and selecting “Paste” from the menu that appears). Click or tap the “Run” button, and — ta-da: You’ll see a player to listen to your custom Gemini-generated sound and a button to download it.

Provided you like what you hear, hit the button to download the file, then head into the Sound section of your Android system settings to save it and make it available for applying as any kind of alert or ringtone. The exact steps for doing that will vary from one type of Android device to another, but on a Pixel or another phone that follows Google’s core Android interface, you’ll tap on either “Ringtone” or “Notification,” then tap “My Sounds” and tap the plus icon to import your own custom file from your phone’s local storage.

On a Samsung device, you’ll start the same way but look for the plus icon within the “Ringtone” section of the settings, then tap the “Folders” tab to find your locally downloaded files. Samsung doesn’t make it easy to add in your own custom notification sounds, annoyingly, so what you’ll have to do is open up the Google Files app, find the file you downloaded in your “Downloads” folder, then tap the three-dot icon alongside it to copy it to the folder called “Notifications.” Once the file is in that folder, it should show up as a notification noise option within the Samsung Android settings.

And remember: You can use Android’s notification channels to set specific sounds to be used for different types of alerts, even within a single app — and you can use the Google Contacts app to set custom ringtones for different people, too.

With Gemini as your personal composer, you’ll never be stuck with generic overused sounds again — and you’ll always know exactly what’s happening from the first note of whatever noise you hear.

Keep the experience-enhancing wisdom coming with my free Android Intelligence newsletter. One new useful trick in your inbox every Friday!

For decades, global time experts have mapped atomic clock time to the earth’s rotation, periodically adding a second (aka a leap second) as rotation slowed. But the planet’s rotation has now slightly sped up, which could mean that a negative adjustment will be required. 

The problem is that computer systems have not been programmed to do that.

To avoid this issue, the General Conference on Weights and Measures (GCWM) in October will vote on a proposal to maintain the Coordinated Universal Time (UTC) as a continuous time from May 20, 2027, without adjustment via leap seconds, allowing UT1, the measure of time based on the earth’s rotation, and UTC to drift apart by up to one hour.

It pointed out, “a negative leap second has not previously been applied, and it is considered to pose a high risk of causing anomalies and disruption to critical infrastructures that are largely unprepared, and the preparation would create, for the industries that rely on time synchronization, a need for financial investment, whose amount is estimated to be similar to their preparations for the millennium bug.”

The group said that a 2025 workshop which included experts on Earth rotation estimated that the probability of a negative leap second will increase rapidly in the near future, reaching 30% by 2035. Acceptance of the proposal, it said, will ensure the long-term continuity for UTC for several centuries.

Unexpected requirement

Jeremy Roberts, senior director at Info-Tech Research Group, said that authorities never expected the need to reverse time. 

“We have been adding leap seconds for decades, basically to keep atomic time in line with observed time, but this is the first time we’d have to take one away. The problem is that computer systems aren’t designed to work this way,” Roberts said. “Rather than introduce a negative leap second, the proposal here is to let the two clocks go out of sync rather than keep adjusting to keep synchronicity with UT1 time and atomic time, which is much more consistent and not impacted by changes in the Earth’s rotation. This would make it easier for those building and maintaining infrastructure, because the clock would behave in a predictable way.”

Still, Roberts stressed that the proposed approach might eventually cause problems. 

“As with all things, this will require work to implement, and because the proposal includes a provision that allows for the clocks to go up to an hour out of sync, that would presumably create a problem for our descendants when we eventually reach that point,” Roberts said. “[But] being indecisive could cause fragmentation in standard time as different entities move to different standards, which could come with its own set of problems.”

Frank Dickson, principal analyst at Dickson Research, added that this proposed move is revolutionary in time-keeping circles.

“This is the biggest change to civil timekeeping since the leap second itself was adopted in 1972,” Dickson said. “Earth’s rotation has historically been slowing down, so that’s the only direction the system has ever had to handle. What’s crazy is that the Earth’s rotation has been speeding up in recent years, requiring a negative leap second, subtracting a second instead of adding one. Nobody has ever run that in production, at global scale, on the systems the world actually depends on.”

Dickson said that it is critically important that the vote pass, because the IT community has seen what happens when clocks malfunction.

“In a world of interlocking software applications, you cannot always predict how a global change will impact digital systems. In 2012, one ordinary positive leap second took down Reddit, LinkedIn, and Qantas’s booking system,” Dickson said. “It also triggered a race condition in the Linux kernel that spiked CPU load across servers worldwide. Nobody had tested for it because it had never happened before.”

And another incident involving timekeeping took down the Telstra network in Australia just last month. 

A ‘more rational’ engineering decision

Mike Wilkes, enterprise CISO at Aikido Security, pointed out that the consequences of a negative leap second could be significant. “Skipping a second can expose assumptions buried in databases, distributed systems, authentication systems, schedulers, market infrastructure and logging platforms,” he said. “The CGPM proposal is effectively saying that, rather than forcing the entire digital economy to prepare for a novel failure mode, we should make UTC continuous. That seems like a far more rational engineering decision.”

Most consultants and analysts agreed that if the vote to adjust current time procedures fails, the resultant problems would likely happen gradually, and possibly dramatically.

“The most likely problem would not necessarily be one spectacular global outage. I would be more concerned about thousands of smaller inconsistencies occurring simultaneously,” said Boris Kolev, global head of technology at JA Worldwide. The problems he anticipated included timestamps appearing out of order, distributed transactions behaving unexpectedly, authentication tokens being interpreted incorrectly, monitoring and audit trails becoming inconsistent, or different systems disagreeing about the sequence of events.

Systemic technology risk

But Kolev warned of a potentially more severe problem, as different companies sharing varied technology dependencies with enterprises try tackling the time problem differently.

“That means an enterprise does not only have to worry about what its own servers do. It has to consider what happens when its cloud provider, operating system, identity provider, database, external APIs, and on premises systems interpret the same moment differently,” Kolev said. “This is precisely the type of systemic technology risk that concerns CIOs: individually, every dependency may look manageable, but globally there are millions of interconnected systems maintained by different organizations, written in different eras, and operating under different assumptions.”

Justin Greis, CEO of consulting firm Acceligence, also said that he hoped the proposal would pass. 

“I think this is one of those cases where delaying what appears to be the technically correct answer may actually be the more responsible engineering decision. At some point, you have to ask whether preserving the relationship between civil time and the Earth’s rotation to within a second is worth introducing operational risk across financial systems, telecommunications networks, cloud platforms, power infrastructure, transportation systems and countless other technologies that depend on precise synchronization,” Greis said. “For the overwhelming majority of enterprise technology, I don’t think it is.”

This article originally appeared on Network World.

We’re hurtling toward the loss of something big. Finally, after months of speculation, Apple is about to introduce its first-ever folding smartphone. And once it does, the conversation will change as the annual iPhone rumor season is replaced with the reality of whatever Apple unveils.

Except, it won’t quite be the same as in the past. Because no sooner will new Apple CEO John Ternus finish his iPhone announcement keynote speech tomorrow than the speculation will shift to next year’s 20^th-anniversary iPhone, what’s coming to the iPhone 18 and e-series iPhones, and expectations around Apple’s upcoming wave of smart home products, including health and home security services. There’s a lot going on.

Meet John Ternus

Having a lot going on is one of the prime expectations of Apple under its new boss. A family man with a wife and kids, he’s led Apple’s hardware division for five years after an eight-year stint running hardware engineering. He joined the company in 2001 and is described as a highly competent, hugely talented, and modest by nature. 

His hobby is quite revealing — he drives race cars, is a regular at California’s Laguna Seca Raceway, and owns an incredibly rare 2019 Porsche 935. To me it suggests a calm, competent, individual with excellent mental and physical reflexes who can make life or death decisions at speed. He’s also deeply committed to good product design.

He’ll need that calm embrace of speed and adrenaline to manage the company his predecessor, Tim Cook, led to become the world’s most valuable firm. 

A hard act to follow

He’s also got a hard act to follow, as while Cook had to carve out his reputation in the shadow of Steve Jobs, Ternus must sculpt his own destiny in the shadow of Cook, who managed to make shareholders of record in 2011 around 20 times richer by the time he quit. (Apple stock rose from $13.74 per share on a split adjusted basis to $319.97 per share today.)

While Cook was frequently criticized for not being a product guy, he presided over the launch of the Apple Watch, AirPods, Apple Silicon, and the Vision Pro, and helped grow Apple’s services income to become its second-biggest product category, diversifying Apple’s revenue and creating financial stability. That’s no easy task.

Building his own team

Can Ternus improve on that? He’s certainly being positioned as someone who can. His deep experience in hardware has led to expectations that Apple will double down on product under his watch, so a great deal is expected of him in consequence. He is also putting together a hardware-focused team, including Laura Legros, former vice president of hardware engineering, as a direct report.

What will we see of this tomorrow? To be fair, while he will lead the announcement on the keynote stage, development of this first tranche of products took place under the leadership of Cook, and while Ternus will have had a big hand in development, this year’s Apple event should be seen as a moment of transition. 

“I’m just as excited about what lies beyond that, including the incredible products already in the works and the ones we haven’t even imagined yet that we’ll dream up and create together. There’s no team in the world I’d rather build the future with,” Ternus told Apple staff in his first memo as CEO.

It’s what Apple does in the next couple of years that will truly define the new leadership. He’s literally been CEO for a week!

What to expect on Sept. 9

Here’s my TL; DR list:

• First folding iPhone: Apple’s response to folding devices from Samsung, Google, Huawei, Xiaomi. It’s expected to have a highly durable, near invisible hinge and a powerful 2nm A20 chip around 20% more performant than the 17 series devices; Touch ID; a 48MP camera; and be able to unfold from a 5.5-in. to a 7.8-in. display. Potentially called iPhone Ultra, some predict it might be the “iPhone Duo” or “iPhone Fold.” It’s likely to cost $2,000+.
• iPhone 18 Pro series: Equipped with a fantastic new display, smaller Dynamic Island, 48MP main camera, and telescopic lens and supported by a fresh tranche of pro-photography features, the 18 Pro/Pro Max range will also use A20 chips. Both the fold and Pro devices will carry significantly more RAM, enabling them to handle on-device AI tasks. Apple is expected to introduce the iPhone 18, iPhone Air 2, and iPhone 18e devices at a spring 2027 event. Prices on all iPhones are expected to increase by $100 or more, depending on model.
• Apple Watch Series 12, Apple Watch Ultra 4: While Apple is thought to be working on new designs for next year, this year’s models will — for the first time in years — include an improved processor, better networking, and more accurate heart monitors. A model with a ceramic body is expected, while the devices will be equipped with additional storage, and integrated satellite emergency features. 
• AirPods 5: Earlier speculation about cameras inside AirPods remains, but these aren’t expected at the launch. Instead, Apple’s AirPods 5 will be boosted with a new H3 Wireless Chip for better voice isolation, noise cancellation, and spatial audio. They may also provide some basic health monitoring features with a built-in temperature sensor and heart rate monitoring.
• Smart home products: Apple is still expected to introduce additional products for smart homes, including an Apple TV with a faster processor and SiriAI support, a HomePod mini upgrade, and — potentially — a new home hub. The latter could effectively be a combination of an iPad with a HomePod to run apps, control smart devices, take and make calls, and run Siri.

Finding the next big thing

While all these products are important to the company, the smart home devices should demand attention (if they appear at all), as the indicators suggest Apple intends to explore the smart home space with a range of future hardware, including domestic robotics, security services, and smart devices. This hardware proliferation in new markets could end up becoming one of the hallmarks of Ternus’ Apple leadership, as will Apple’s AR spectacles (once they are introduced). 

Equally, it cannot be ignored that one of Ternus’ main tasks since becoming vice president of hardware has been the introduction of new Macs and the transition to Apple Silicon. So he’ll be expected to strike a balance between improving Apple’s traditional product lines while racing his company toward new and emerging opportunities in hardware. (I believe Apple should pay much more attention to the enterprise space within that.) 

Apple’s little AI problem

The biggest challenge to all of this will be Apple’s success in implementing AI that’s good enough to get things done while avoiding the unexpected dangers of poor implementation. We don’t want AI agents corroding smart home security, for example, which is why Ternus seems likely to maintain Cook’s focus on security and privacy as enabling technologies to support trusted hardware/software product designs.

Another thing? Tomorrow’s keynote will likely begin with the single word, “Hello,” and feels very likely to also include that classic Apple keynote line, “…One more thing.”

We’ll find out more as the conversation moves from speculation to reality after the 10am (PT) keynote.

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

Swiss authorities have launched a pilot project to determine whether it is possible to replace Microsoft 365 with similar open-source services, RTS reports. This follows a proof-of-concept project in which 172 civil servants tested the German open-source platform openDesk.

According to Matthias Stürmer, a professor at the University of Bern, there are three main reasons for the switch: to reduce dependence on US services, to improve operational reliability, and to reduce costs.

In the first phase, the migration involves 3,000 computers, which corresponds to 7% of Switzerland’s federal workforce. The government has more than 54,000 workstations in operation. The pilot will prioritize employees who have access to highly sensitive data, according to RTS.

A move by the Swiss Armed Forces from Microsoft 365 to openDesk is already underway, with that migration expected to be completed in October, It’s FOSS reports.

Switzerland’s move is part of a larger ‘digital sovereignty’ effort in the European Union that aims to retain local control over data, applications, and infrastructure. In January, lawmakers directed the European Commission to map critical technology dependencies and then develop policies to reduce reliance on foreign providers.

This article originally appeared on Computer Sweden.

More on the EU’s digital sovereignty push:

• European tech leaders advise caution on tech sovereignty drive
• EuroStack: Europe’s path to digital independence?
• US orders diplomats to push back on data sovereignty

Back in April 2025, the US Department of Justice (DoJ) proudly proclaimed that it had prevailed in a landmark antitrust case against Google’s ad business. Yeah. Right.

You see, just last week, US District Judge Leonie M. Brinkema rejected the DoJ’s effort to force Google to sell its AdX ad exchange. What began as a major anti-monopoly victory has become a mouse-sized settlement. 

[ Google US antitrust trials: A timeline ]

Does any of this this sound familiar? It should. We’ve seen this show before. Last year, Google had also been convicted of abusing its search business. At first, all the talk was about how Google might be forced to divest itself of the Chrome browser and/or the Android operating system. 

Instead, Google was allowed to keep making search deals and only had to share some search data with its rivals. 

I say rivals, but in fact Google still dominates the search market. Indeed, its control has actually expanded a bit. By StatCounter’s numbers, in August 2025, Google search owned 89.89% of the market. By last month, almost a year after the company had been slapped on the wrist, its share had grown to 91.1%. 

Boy, wasn’t that a win?

The remedies phase of the government’s ad-tech antitrust case order is a similar Google win. No, it doesn’t overturn the April 2025 finding that Google unlawfully maintained monopolies in the publisher ad-server and ad-exchange markets, or that it illegally tied its ad server and exchange together. Instead, it determines how the company must change its conduct.

The DoJ wanted Google to divest itself of AdX, the company’s ad exchange for matching publisher inventory with advertiser demand. It also sought to require Google to open-source the final-auction logic in its DoubleClick for Publishers (DFP) ad server and, if necessary, divest its DFP business. 

Brinkema rejected all three requests. Instead, her short order accepts “most” of the parties’ proposed behavioral remedies, subject to modifications described in a memorandum opinion that remains sealed while the parties identify confidential information for redaction.

Specifically, the court directed Google and the plaintiffs to meet and submit a joint proposed final judgment within 30 days. If they cannot agree on the details, each side must submit its own proposed version.

Google — as it should — sees this as a win. As Lee-Anne Mulholland, Google’s vice president of regulatory affairs, said in a statement, “We’re very pleased the Court rejected the DOJ’s proposal to break apart tools that help small businesses reach new customers and grow.”

Far less convincing is the DOJ’s characterizing the decision as a win. “The Antitrust Division is pleased that the court ordered substantial relief in the Google ad-tech case. We are one step closer to restoring competition and bringing relief for the American people in online advertising markets.” 

Oh please! It does nothing of the sort.

To quote Laurel Kilgour, research manager at the American Economic Liberties Project, an anti-monopoly, nonprofit group: “Judges keep finding Google guilty, but Google keeps walking away with both its ill-gotten gains and its empire intact. Without actual structural remedies, antitrust rulings are just inconvenient speed bumps that allow Google to lock down search and ad tech markets today while using that same unchecked power to monopolize tomorrow’s AI frontier.”

Exactly so. 

The specific obligations Google will face are not yet public, because Brinkema’s explanatory opinion remains under seal. Earlier, Google had proposed making real-time bidding responses from AdX available to rival ad servers, removing Unified Pricing Rules, and accepting a monitoring trustee for a three-year supervision period. None of that will even dent Google’s ad business.  

When all’s said and done, Google is still in charge of both its exchange and publisher ad-server operations. I expect the minor changes required won’t amount to a hill of beans. Restoring competition in markets where the company was found to have used its vertically integrated position unlawfully? Give me a break. 

Public Knowledge, a free speech and internet advocacy group, described the decision as one that leaves Google’s monopoly power substantially intact. 

As Public Knowledge Legal Director John Bergmayer said, “The court found that Google illegally acquired and maintained monopolies in publisher ad servers and ad exchanges, and used its control of DFP and AdX to shut out rivals.” He concluded, “Telling a monopolist to do better is not the same as restoring competition.… A finding of liability means little if the remedy leaves the market fundamentally unchanged.”

Ya think? 

In Google’s last reported quarter, the company reported $81.6 billion in advertising revenue. Next year, when Google is being “punished,” I expect its revenue will be even higher. 

A phishing-as-a-service operation targeting Microsoft 365 users has harvested thousands of session cookies that could be used to hijack authenticated sessions after victims complete multifactor authentication, CloudSEK said.

The cybersecurity firm said in a report that it uncovered the operation, known as BigBear 2.0, in June after gaining access to its administrative panel.

The panel contained 5,137 credential records linked to 461 targeted organizations across more than 40 countries. CloudSEK also reported 4,148 captured session cookies and 1,032 plaintext passwords. The firm said 474 records showed completed logins in which attackers captured the authenticated session created after MFA.

BigBear 2.0 is built on Evilginx2, a framework that places an attacker-controlled reverse proxy between the victim and Microsoft’s legitimate authentication service. The victim signs in through the proxied page and completes MFA as usual. Once Microsoft issues an authenticated session cookie, the phishing infrastructure can intercept it and allow the attacker to reuse the session without completing the authentication process again.

The operation also uses residential proxies selected according to the victim’s country, which can make malicious authentication traffic appear geographically consistent with the user. CloudSEK said this technique can weaken location-based checks used in Conditional Access policies.

Researchers also found custom code designed to disable FIDO2/WebAuthn authentication on the phishing pages, potentially steering users toward weaker, phishable authentication methods.

CloudSEK described BigBear 2.0 as a multi-user service with at least five identified affiliate operators. The company said it observed 42 virtual private server (VPS) nodes over the campaign, with 26 deleted from the panel since late July.

IT services and managed service providers accounted for 151 of the organizations identified by CloudSEK, making them the most heavily represented sector in its data. Such organizations can present especially valuable targets because employees may hold privileged access to customer environments and administrative systems.

Session theft moves into the mainstream

The significance of BigBear 2.0 is not just its ability to capture authenticated sessions after MFA, but the way it packages techniques once associated with more skilled attackers into a service that can be used at scale, said Keith Prabhu, founder and CEO of Confidis.

The underlying technique is not new, said Akshat Tyagi, associate practice leader at HFS Research. “What BigBear 2.0 changes is accessibility and scale,” Tyagi said. “It packages AiTM phishing, residential proxies and automated cookie replay into a service that lowers the expertise needed to run these attacks.”

That shift means enterprises need to think beyond protecting the authentication event itself, he said, because a captured session may give an attacker access to Microsoft 365 without another password or MFA challenge.

Prabhu added that successful MFA should no longer be treated as proof that an account or session remains secure.

Session cookies and access and refresh tokens should be treated as high-value authentication material rather than technical artifacts behind the password, said Sakshi Grover, senior research manager for cybersecurity products and services at IDC Asia Pacific.

The risk, she said, is that many enterprise controls are still geared toward detecting credential theft rather than the hijacking of an already authenticated session.

Phishing-resistant authentication becomes critical

OTP, SMS, and push-based MFA should not be relied on as standalone defenses against this type of attack, Tyagi said, because the attacker can allow the legitimate user to complete authentication before stealing the resulting session.

Tyagi said enterprises should enforce phishing-resistant authentication such as FIDO2/WebAuthn passkeys rather than merely making it available alongside weaker alternatives. Prabhu pointed to Windows Hello for Business and certificate-based authentication as additional options, with stronger methods enforced through Conditional Access authentication strengths.

Grover said organizations should also use Continuous Access Evaluation and token protection where Microsoft 365 supports them, but cautioned against treating token protection as a complete solution because coverage varies across platforms, clients and workloads.

The problem is also operational, Grover said. Identity and access tools are not always sufficiently integrated with security operations or SIEM platforms, leaving potentially useful identity signals disconnected from the analysts responsible for detecting attacks.

Password resets are not enough

“Treat the event as an active session compromise, not merely a stolen-password incident,” Prabhu said.

He recommended disabling or containing the affected account, revoking Entra sign-in sessions and refresh tokens, and forcing reauthentication. Incident responders should then examine Microsoft 365 logs for evidence of mailbox access, malicious inbox rules, unusual OAuth consent, newly registered MFA devices, privilege changes, and access to other cloud applications.

Tyagi cautioned that IP location may provide limited reassurance in such investigations because residential proxies can make attacker activity appear geographically consistent with the legitimate user. Responders should instead focus on reconstructing what occurred during the compromised session, he said.

Investigators should also determine whether the stolen session was used to reach other employees, customers, or external contacts, Prabhu added.

Grover said organizations should also include session hijacking in tabletop exercises, testing how identity, security operations, messaging, and cloud teams would coordinate during an authenticated-session compromise. Such exercises can expose gaps that may not emerge in simulations centered on conventional credential theft or ransomware, she said.

The article originally appeared on CSO.

OpenAI’s rollout of its GPT-6 Astra model ran into early access issues after paying ChatGPT users were unable to use the system shortly after launch, prompting CEO Sam Altman to apologize and say the release had been “messy.”

“First, sorry for the messy rollout,” OpenAI CEO Sam Altman acknowledged the issue in a post on X. “Second, when we screw up, we try to make it right.”

OpenAI had said GPT-6 Astra would be rolled out across ChatGPT tiers and APIs, positioning it as its most advanced model to date. However, the initial rollout did not translate into immediate access for all users, highlighting the gap between model launch and availability across subscription tiers.

Only the organizations enrolled in its Daybreak cybersecurity program were able to access the model, whereas Plus, Pro, Business, and Enterprise ChatGPT subscribers, along with developers using the OpenAI API, were left out.

“Third, we should be able to begin broad rollout to API customers and ChatGPT subscribers in the near future. As usual, we will start with pro subscribers,” Altman continued in the post.

Altman wrote in a follow-up X post on Friday that OpenAI had extended Astra to Pro, Enterprise, and Business Premium users in ChatGPT’s Work and Codex products and had opened it up through the API.

“It might take a few days to roll out to our Plus and Business users,” OpenAI’s official X account posted on September 5.

The company did not immediately respond to a request for comment.

Phased rollout continues without firm timelines

OpenAI introduced GPT-6 Astra on September 4, stating that availability would expand over time rather than being enabled simultaneously for all users.

Altman’s post followed complaints about access during the initial rollout window, although OpenAI has not disclosed how many users were affected or how access varied across tiers.

In a subsequent post on X, Altman said: “We are working towards getting Astra in everyone’s hands as quickly as we can; I know it is frustrating,” indicating that access was being expanded incrementally.

OpenAI technical staff member Thibault Sottiaux confirmed in a separate X post that Plus and Business users had gained access too, crediting the company’s infrastructure: “more scalable than we anticipated.”

The rollout approach is consistent with OpenAI’s initial communication that Astra would be made available over several days, rather than at once. Gartner also noted that the model was first released to a limited set of organizations before broader expansion.

Rollout highlights the gap between launch and access

Analysts said the sequence reflects a distinction between model announcement and actual availability.

Greyhound Research said the Astra rollout should be treated as an operational signal rather than a confirmation of readiness.

“Announced, available, entitled, and production-ready are four separate states,” said Sanchit Vir Gogia, chief analyst at Greyhound Research. “This must be treated as operational evidence, neither dismissed as theatre nor inflated into proof that Astra has failed.”

He added that staged availability reinforces the need for enterprises to verify what level of access they actually receive, rather than assume uniform rollout across users or environments.

Gartner said enterprises will need to strengthen governance as they evaluate Astra’s capabilities.

“CIOs must balance Astra’s advanced automation with stronger cybersecurity, governance, and cost controls before adoption,” Gartner analysts said in an initial note on the launch shared with Computerworld

The firm said Astra’s ability to execute more autonomous workflows will require tighter evaluation controls and observability.

It also pointed to challenges around identity, security posture, and accountability as AI agents take on more complex roles.

Contracts and control models under scrutiny

Greyhound Research said the rollout raises questions about how enterprises define access and operational control.

“A conventional uptime SLA is too narrow for Astra,” said Gogia. “Critical describes the engine. It does not tell the buyer how much of that engine reaches the road.”

He said enterprises need to account for how such systems behave in production, particularly when access, interruption, or task continuity may vary.

“A stop leaves a state the enterprise did not choose, and that state needs a record it can defend,” Gogia said.

The rollout also highlights changes in how governance responsibilities are distributed.

Gogia said administrative controls alone do not address enterprise requirements.

“Admin opt-in is not a safety certificate,” he said. “It is the point at which accountability crosses from vendor release policy into an enterprise governance decision.”

He added that such controls do not extend automatically to API-based deployments, where enforcement depends on enterprise-level systems.

Capability gains introduce trade-offs

OpenAI has positioned GPT-6 Astra as an advance in reasoning, coding, and automation capabilities.

Gartner said these improvements introduce trade-offs that enterprises will need to evaluate in production settings.

While Astra may reduce token usage for some tasks, organizations must consider overall task costs, including validation and oversight, the firm noted.

Gartner also cautioned against over-indexing on early capability claims. “Without more evidence, CIOs should ignore the AGI hype for now and instead focus on use-case-specific evaluations, demonstrated business outcomes and reliable autonomy,” the firm said.

The story originally appeared on CSO.

You might not know it from looking, but Gmail is jam-packed with time-saving tricks.

Some of ’em are right there in front of your face, if you know how to find ’em — while others require a teensy bit of under-the-hood tinkering to activate. But all of ’em are built right into Gmail and have the potential to make managing your email a heck of a lot easier.

Check out these 16 splendid Gmail tips and get ready to master your inbox once and for all.

(Note that unless otherwise specified, these tips are specific to Gmail’s web-based desktop version.)

Inbox step-savers

1. You can actually view attachments right from your Gmail inbox. Provided you haven’t switched away from the service’s “default” interface arrangement, you’ll see small tiles for every file associated with an email right below the message’s subject line. And you can click on any of those tiles to open or preview the file’s contents and get directly to the info you need.

2. It’s easy to miss, but take note: When you hover your mouse over a message in your inbox, Gmail gives you a series of quick-access actions at the far-right side of the line. You can archive the email, delete it, mark it as read or unread, snooze it, or even RSVP to a meeting request right then and there — without ever having to open the message.

3. A super-useful keyboard shortcut I always forget to use: While viewing a multi-email thread of messages — a conversation in which you have numerous back-and-forth replies under the same subject — hit the semicolon key (;) to expand the entire conversation and show every message in the thread. And then hit the colon key (:) to collapse it back down so you see only the most recent email.

Just make sure you enable keyboard shortcuts first, if you haven’t already: Click the gear icon in the website’s upper-right corner, then click “See all settings” and look for the “Keyboard shortcuts” option midway down the screen that comes up. Select the “Keyboard shortcuts on” setting and then be sure to click the Save Changes button at the bottom of the screen.

4. Some of Gmail’s best keyboard shortcuts are the ones you create yourself. Go back into the website’s settings and this time, click the Advanced tab. See the line labeled “Custom keyboard shortcuts”? Click “Enable” next to that, then click the Save Changes button at the bottom of the screen.

Once Gmail refreshes itself to apply the changes, go back to the Settings area again and look for the newly present Keyboard Shortcuts tab. There, you can adjust any of the default keyboard settings to make them simpler to activate or easier to remember.

One of my favorite adjustments, for instance — and one I rely on constantly — is adding in a second command for the “Go to inbox” shortcut, which is typically gi by default. In Google’s old Inbox service, that shortcut was simplified down to just i, and once you get used to that shorter sequence, you won’t want to go back.

5. The panel at the right of Gmail’s web interface lets you pull up Google Calendar, Google Keep, Google Tasks, or Google Contacts right inside your inbox so you can manage info from each of those apps without having to switch tabs or open anything new. And here’s a handy hidden trick: With Tasks, you can drag messages directly from your inbox into the panel to create new tasks around them.

Unfortunately — and somewhat strangely — the same drag-and-drop behavior isn’t currently possible with Calendar or Keep, nor is it possible for Contacts.

6. Even with a miniature version of Contacts being available inside that handy side panel, you might sometimes want to pull up the full Google Contacts website for its complete set of features. Provided you’ve got Gmail’s keyboard shortcuts enabled now, commit this workaround to memory: Pressing g and then c will open up Contacts in a separate tab, no matter what else you’re doing in your inbox.

Composing shortcuts

Editor’s note: Assuming you’ve enabled keyboard shortcuts (see tip 3), the following keyboard shortcuts work in any browser on any desktop operating system. Mac users, just swap in the ⌘ key for “Ctrl” wherever you see it.

7. Ever like marking messages as unread after you’ve opened ’em? Gmail makes that incredibly easy to do: Anytime you have an email open, look for the envelope icon directly to the right of the trash can in the horizontal row of icons above your message (in the area directly beneath the search bar). That’ll let you mark the message as unread with a single click. Or, for a faster and more powerful one-two punch, just type an underscore (_) while viewing any message. That’ll mark it as unread and zap you back to your main inbox.

8. Speaking of combining multiple actions into a single command, simplify your inbox organization process by enabling Gmail’s convenient Send & Archive button. It places a second button alongside the regular Send button whenever you’re responding to an existing message, and clicking that button (or, even better yet, hitting Ctrl-Enter on your keyboard) will send your response and archive the thread in one fell swoop.

To enable it, look for the “Send and Archive” option within the General tab of Gmail’s settings. Click “Show ‘Send & Archive’ button in reply,” hit the Save Changes button at the bottom of the screen, and then get ready to save yourself steps the next time you type a reply.

9. I don’t know about you, but I frequently start typing an email and then decide against sending it. (Rather fittingly, I started typing out a lengthy explanation of the reasons but then decided against including it.) If the same thing ever happens to you, remember this: Hitting Ctrl-Shift-D while you’re in the Gmail compose tool will close the compose window and discard your draft. And it works whether you’re writing a new email or a reply.

10. Another awesome time-saver: In addition to the obvious Ctrl-B for bold and Ctrl-I for italics email formatting shortcuts, Gmail has hotkeys for doing some advanced forms of text formatting — things that’d otherwise require multiple clicks and much menu-hunting to accomplish.

The ones I use the most:

• Ctrl-Shift-8 will add a bulleted list into your email (just like this list!), and Ctrl-Shift-7 will add a numbered one.
• Ctrl-Shift-9 will offset text in a blockquote style.
• Ctrl-] will indent text, while Ctrl-[ will remove any indentation.
• And Ctrl-\ will remove any formatting on your selected text and make it as plain as can be.

11. You’d never know it, but the Gmail compose tool itself can take on various forms, depending on your preferences. Make a mental note of these possibilities and the shortcuts to get to ’em:

• To start a new message in the default lower-right-corner-of-the-screen window view, hit c.
• To start a new message in a pop-up window totally separate from your main Gmail tab, hit Shift-C. You can do the same thing for a reply by hitting Shift-R while viewing a message thread — or Shift-A for reply-all.
• To start a new message in a full-screen compose window within your main Gmail tab, hit c — then click the little arrow icon in the compose tool’s upper-right corner. (You can also hit Shift while clicking that icon to pop the message out into a separate pop-up window form.)
• If you’d rather use that full-screen compose window all the time, by default, click the three-dot menu icon in the lower-right corner of the compose tool and look for the “Default to full-screen” option there. (If you ever change your mind, you’ll find the option to disable that preference in that very same spot.)
• If for some reason you like the idea of composing a message in a new tab instead of a pop-up window or within the main Gmail tab, just hit d while in your inbox. That’ll do the trick!

To see more keyboard shortcuts, just type ? while viewing any message list within Gmail.

Smarter snoozing

12. Don’t forget to take advantage of Gmail’s super-handy snoozing tool: Instead of letting messages linger in your inbox and pile up to an unmanageable point, use the snooze function to help yourself deal with everything as soon as you see it.

A good rule of thumb to maintain: If you can respond to something in less than a minute, do it. If something doesn’t require any action on your behalf, archive it immediately. And if something requires some sort of action but you don’t have the time to mess with it at that moment, snooze it to a day and time when you will be able to handle it.

You can snooze an email from your inbox by hovering over the message and selecting the clock-shaped Snooze icon, as noted in tip 2. You can also snooze an email while it’s open by clicking the three-dot menu icon to the right of the folder symbol directly above the email and then clicking “Snooze” within the menu that pops up. Or you can simply press b while you’re viewing a message or while you have it selected in your inbox.

13. Gmail even makes it possible to snooze multiple messages at the same time — in case you see more than one email that needs to be pushed back to the same point. From your inbox, simply click the boxes to the left of any messages you want to include, then click the three-dot menu icon within the row of icons toward the top of the screen and select “Snooze” from there.

14. Need to get back to something you snoozed — or change the day and time at which it’s set to reappear? You can always find all of your snoozed emails in Gmail’s Snoozed section, located beneath the “Inbox” line in the left-hand panel. Once you’re there, just hover over any email and click the clock-shaped icon to change its snooze settings or unsnooze it entirely.

15. You can snooze messages from the Gmail mobile apps, too, though the option is a bit buried. From the inbox view, press and hold a message to select it, then tap the three-dot menu icon at the top of the screen and look for “Snooze” in the list of options that appears. If you’ve already opened the message, tap the three-dot menu icon at the top of that screen; you should see “Snooze” show up as part of the options there as well.

16. Make snoozing even simpler in the Gmail mobile app by assigning it to one of your inbox swipe actions. Just open up the app, tap the three-line menu icon in its upper-left corner, then select “Settings.” On Android, tap “General settings” followed by “Swipe actions”; on iOS, you’ll tap “Inbox customizations” and then “Mail swipe actions.”

All that’s left is to set either your left swipe or right swipe to “Snooze,” and then, you can simply swipe any message in that direction from your inbox to snooze it — no wasted taps or menu diving required. (The Gmail Android app has several other similarly useful hidden features, by the way, most of which aren’t available on iOS.)

And with that, your Gmail time-saving toolbox is officially complete! The next logical step in your inbox improvement adventure is mastering the art of Gmail labels to fight back against email chaos — and I’ve got just the guide to get you started.

This story was originally published in May 2018 and most recently updated in September 2026.

Google’s dominance in the search arena has given rise to two major antitrust lawsuits from the US government alleging the company has manipulated the market to maintain that dominance, to the exclusion of competitors and the detriment of the public at large.

The first lawsuit, targeting Google’s search business, kicked off in mid-September 2023 and drew to a close in May 2024; US District Judge Amit Mehta ruled against the tech giant in August 2024. The remedy phase of the trial ended in September 2025 with Judge Mehta rejecting the DOJ’s request to break up the company, instead imposing data-sharing requirements.

The second trial against the tech giant, focused on advertising, took place over 15 days in September 2024, with US District Judge Leonie Brinkema ruling against Google in April 2025. In September 2026, Judge Brinkema ruled that Google is not required to break off its ad exchange, instead opting for behavioral changes that have yet to be revealed publicly.

The cases heavily echo the turn-of-the-century Microsoft antitrust case in several respects, most notably that Google, like Microsoft before it, has evaded the forced breakup requested by regulators.

Here’s our condensed timeline of the two overlapping lawsuits and their progress through the court system.

Sep. 2, 2026, advertising lawsuit: In a second big win for Google, Judge Brinkema rules that the company does not have to sell its AdX ad exchange. The search giant is also not required to open-source the final-auction logic in its DoubleClick for Publishers (DFP) ad server or divest its DFP business. Behavioral remedies are sealed while the parties identify confidential information for redaction.

Sep. 2, 2025, search lawsuit: In a significant win for Google, Judge Mehta rules that the tech giant does not have to divest its Chrome and Android businesses as the US government had requested, and it will be allowed to continue paying Apple and other browser makers for default search placement. To level the competitive playing field, Google will have to share search index and user-interaction data with rivals and offer search results syndication.

April 21, 2025, search: The remedy phase of Google’s search antitrust trial begins with Judge Mehta presiding. Federal prosecutors warn that Google might leverage artificial intelligence to entrench its search monopoly, demanding “strong measures” to prevent the tech giant from extending its market control into the AI era. These include requiring Google to divest Chrome, end exclusive default search agreements, license its search data to competitors, and potentially sell its Android operating system if other remedies fail.

April 17, 2025, advertising: In a second landmark defeat for Google, Judge Brinkema rules that Google illegally monopolized the ad tech market. The company’s “exclusionary conduct substantially harmed Google’s publisher customers, the competitive process, and, ultimately, consumers of information on the open web,” she wrote in the ruling. Remedies, which could include the breakup of Google’s advertising products and/or changes to its business practices, will be imposed at a future date.

Oct. 8, 2024, search: The US Department of Justice submits a court filing proposing that the Chrome browser and Android operating system be split off from Google as part of sweeping remedies aimed at curbing the tech giant’s monopoly in online search and advertising.

Sept. 20, 2024, advertising: The US Department of Justice is set to wrap its case in the Google antitrust trial after an eventful two weeks. The tech giant is accused of engaging in monopolistic behavior by strategically acquiring certain companies and controlling the adtech industry’s most widely-used tools and exchanges,  beginning with its acquisition of advertising company DoubleClick in 2008.

Sept. 9, 2024, advertising: The second major case against Google begins with the company defending itself against claims it engaged in illegal behavior to maintain control of the ad tech market. The US government is accusing Google of purposefully manipulating that market, snuffing out competitors and gobbling up key technologies through acquisitions. If the DoJ successfully makes its case, Google risks being broken up by regulators.

Aug. 5, 2024, search: In a major defeat for Google, Judge Amit Mehta rules that the company had engaged in anticompetitive behavior in an effort to protect its search business. In the 277-page decision, Mehta was blunt: “After having carefully considered and weighed the witness testimony and evidence, the court reaches the following conclusion: Google is a monopolist, and it has acted as one to maintain its monopoly. It has violated Section 2 of the Sherman Act.” Mehta’s ruling did not include remedies for the anticompetitive behavior; those will be decided later.

May 3, 2024, search: Over two days of closing arguments, the DoJ revisits its case for Google having a monopoly on search advertising, and Judge Mehta quizzes both parties about whether other platforms could be viewed as substitutes for Google’s search advertising business. He hasn’t said how long he expects to take to reach a decision, but if he rules against Google, a second hearing will take place to decide on any remedies.

Nov. 16, 2023, search: The evidentiary phase of the trial finishes, as Judge Mehta issues instructions for post-trial submissions. Despite considerable amounts of redaction and closed-door testimony, the case revealed some unprecedented details about the relationships between the largest tech companies in the world, including the fact that Apple apparently keeps 36% of the search revenue from Google searches in Safari, and Apple once considered buying Microsoft’s Bing search engine as leverage against Google. Judge Mehta has scheduled closing arguments in the case for May 1, 2024.

Oct. 31, 2023, search: Google CEO Sundai Pichai takes the stand, for long-awaited testimony about the relationship between his company and Apple. He gave some details about Google’s negotiations with Apple over a contract that made Google the default search engine on Apple’s iPhones, iPads, and Macs. Google has paid billions for the privilege of being the default search on Apple products, and the relationship is a key part of the case – which was underlined by the Justice Department’s cross-examination of Pichai, during which he admitted that default search status is a major driver of market share.

Oct. 18, 2023, search: Google begins its defense, calling Paul Nayak, a vice president of search, to the stand as its first witness. Nayak downplays the importance of scale in his testimony, stressing that machine intelligence, compute infrastructure, and a team of 16,000 staff that checks on search results are crucial to maintaining quality of service. DOJ witnesses including DuckDuckGo CEO Gabriel Weinberg and Microsoft CEO Satya Nadella had testified that Google keeps an edge over competitors via an ever-increasing trove of data — the result of its default search engine status, maintained through exclusive contracts and billions of dollars in payments to Apple, Samsung and other companies. This data gives Google an advantage in refining search engine results, they said. 

Oct. 3, 2023, search: As a witness for the prosecution in the Google antitrust trial, Microsoft CEO Satya Nadella warns that Google’s monopoly profits could lock in publishers as AI-enabled search arrives. Nadella argued that it’s almost impossible to compete with Google, given the search leader’s massive competitive edge in collecting and analyzing user data. He also warned that Google, with its vast profits and lock on the search market, stands poised to extend its monopoly power in a new era where artificial intelligence technologies will turbocharge the search business.

Sept. 26, 2023, search: Apple’s Eddy Cue testifies behind closed doors in the Google search case, as critics slam presiding Judge Amit Mehta’s decision to hold much of the trial’s testimony from witnesses secret, allow documents to be heavily redacted, and block some documents from public view — mainly at the insistence of Google, but also at the request of other companies, including Apple. By the end of Cue’s testimony — and after a wek of wrangling by all parties — Judge Mehta rules that documents used during the trial can be published online at the end of each day, but still allows time Google and third parties to object to exhibits being shown publicly before the DOJ presents them in court. 

Sept. 21, 2023, search: Judge Mehta rules that public access to court exhibits, which have been mostly internal Google documents thus far, should be removed, after Google challenged the Justice Department’s regular publication of them. The company said that it was concerned for its employees’ privacy.

Sept. 12, 2023, search: The default search trial begins with opening statements, and the government begins its case.

Aug. 2023, search: Judge Mehta grants partial summary judgment for Google in the search case, saying that the government had failed to raise a genuine dispute of material fact on antitrust charges relating to contracts around the use of the Android operating system, as well as Google Assistant and IoT devices. The claims relating to Google’s exclusive “default search” contracts, however, are allowed to proceed to trial.

July/Aug. 2023, search: Google and the plaintiffs in the search case argue various motions in limine, designed to control what evidence should be included or excluded in the actual trial. Discovery and motion practice over evidence continues in the advertising case.

June 2023, search: Judge Mehta schedules a trial date of September 12, 2023 for the search case.

April 2023, advertising: Judge Leonie M. Brinkema denies Google’s motion to dismiss in the advertising case.

March 2023, advertising: Google’s motion to transfer the advertising case to New York is denied by Judge Brinkema, who orders the parties to propose discovery schedules within two weeks of the order. Two weeks later, Google moves to dismiss the case for failure to state a claim, arguing that the plaintiffs have simply produced legal conclusions, and not specific facts, that could support their claims. Judge Brinkema schedules pre-trial conferences for January 2024.

Feb. 2023, search: The plaintiffs in the default search case case move for sanctions against Google, accusing it of spoliation, which refers to the destruction, alteration or failure to preserve relevant evidence in a case. Elsewhere, in the advertising case, Google moves to transfer the case from the Eastern District of Virginia to the Southern District of New York, which is seen as an attempt to consolidate the case with related digital advertising antitrust litigation.

Jan. 2023, advertising: A second antitrust action, pushed by eight states and the DoJ, is filed in federal district court in eastern Virginia. The plaintiffs, who call for Google’s advertising business to be split up, accuse Google of manipulating its dominant position in the online advertising world to squeeze out rivals and control both the supply and demand side of the advertising market. Google, according to the complaint, thwarted fair competition by manipulating fees, punished advertisers for using alternative platforms and ad exchanges, and engaged in a host of further anti-competitive behavior in the interest of monopolizing the marketplace. (This is case that began in September 2024.)

Dec. 2022, search: Google moves for summary judgment against the separate Colorado case and the larger, DoJ-led case. A summary judgement motion is essentially a request by one of the parties in a lawsuit that the judge rule in their favor and end the case, arguing that, based on the undisputed facts, they are entitled to win the case as a matter of law.

May 2022, search: A deadline of June 17 is set for the production of all discovery materials. Further documents – for example, those whose is existence is first disclosed in late in the discovery window – can be produced until June 30.

May 2022, search: Judge Mehta denies a government motion to sanction Google for inaccurately classifying documents as attorney-client privileged. The plaintiffs had argued that emails on which Google’s lawyers were listed as recipients or CCed, but that the lawyers never responded to, constituted a misuse of the attorney-client privilege rules.

Dec. 2021, search: Judge Mehta conditionally splits Colorado’s claims from the case at large, ordering that separate trials on that state’s issues of liability and remedies will be “more convenient for the Court and the Parties, and will expedite and economize this litigation.”

Aug.-Oct. 2021, search: Discovery-related motions and orders continue, as Yelp and Samsung join the fray. (Those companies, like Microsoft and Apple, are relevant to the case even if they aren’t parties themselves, as their internal records are potentially relevant to Google’s liability.)

June/July 2021, search: The discovery process continues, and the US and Google both file several documents with the court under seal. (Microsoft files two sealed documents, as well, in response to Google’s subpoenas for company records, and Apple becomes involved after the government requests access to some of its internal information.)

March 2021, search: Meetings between Google and the various governmental plaintiffs continue, with periodic status reports on the discovery process.

Jan. 2021, search: Google files a response to the complaint, admitting to many of the facts alleged by the Justice Department and associated attorneys general, but categorically denying the substance of the government’s claims of illegality. Further responses to separate but related claims, generally to specific state attorneys general, follow in the subsequent weeks and months.

Dec. 2020, search: Judge Amit Mehta approves the joinder of Michigan, Wisconsin and California to the suit.

Oct. 2020, search: The Department of Justice, along with the attorneys general of 11 states, sues Google in DC federal district court for unlawfully maintaining a monopoly, in violation of Section 2 of the Sherman Act. The case centers on Google’s use of exclusive contracts that mandate its use as the default search engine in a host of different hardware and software applications, with the government alleging that this represents an artificial constraint on any possible competition for the search giant.

Gmail is filled with hidden features and add-on possibilities, but one of the service’s most powerful organizational tools is sitting right in the heart of its regular settings.

As you may have guessed by now (especially if you read this story’s headline, you clever little cat), I’m talking about filters — Gmail’s long-standing system for automating your inbox with a series of custom-crafted rules. At a glance, filters can seem complicated. They can seem overwhelming. They can even seem unnecessary.

But don’t let yourself be fooled by the feature’s curiously crusty exterior. Gmail filters have the potential to completely reshape your inbox and the way your incoming messages are handled. They can help you keep your email in order with no ongoing thought or effort.

And, unlike Google’s new AI Inbox option (which notably still doesn’t seem to be available for most people as of this writing), filters (a) don’t require your personal messages to be processed by generative AI systems — and (b) give you complete control over exactly how your email is handled instead of forcing you to rely on inherently unreliable technology to figure out what you want for you (and then likely come up short at least some of the time).

Best of all? All it takes is a teensy touch of one-time planning to get Gmail filters set up to your exact specifications and working for you quietly and automatically from that moment onward.

Follow the filter-centric Gmail tips in this guide, and your inbox will be running like a well-oiled (but not too greasy) machine in no time.

Part 1: Figuring out your Gmail filters

Let’s start by thinking through some Gmail filter possibilities to get an idea for the sorts of setups you might want to consider — then, we’ll go step by step through the process of creating them.

With Gmail filters, you could:

• Ensure messages from specific high-priority senders always go into your inbox’s Primary tab, where you’re certain to see them
• Ensure specific sorts of lower-priority messages — like invoices, reports, or updates from different services you use — automatically get sorted into an out-of-the-way location and never even show up in your inbox
• Keep messages from annoying people out of your hair (but still available in case you need to find them) by automatically archiving them as soon as they arrive
• Forward messages from a specific address or with a specific phrase in their subjects to other members of your team or family
• Instantly respond to messages to or from a specific address with a prewritten template
• Label messages sent to a specific variation of your Gmail address (like youraddress+vip@gmail.com) or written with a specific word or phrase in the subject (like “urgent,” “important,” or “hey jerkwad, pay attention to this”) as “VIP” and then receive notifications only for messages with that designation
• Mark specific types of messages from yourself as reminders by giving them a bright yellow “REMINDER” label that makes them stand out in your inbox
• Get a snickerdoodle delivered to your desk every time your boss emails you

All right, so that last one isn’t really possible (not yet, anyway) — just wanted to make sure you were still paying attention. Everything else in that list, however, is absolutely doable and actually quite easy to set up with Gmail filters.

Got some ideas of your own? Good deal. Time to make ’em happen.

Part 2: Creating your Gmail filters

The simplest way to start a new Gmail filter is to click the control panel icon — the symbol showing three horizontal lines stacked on top of each other — within the big search box at the top of the Gmail website. (Filters can’t easily be managed on mobile, unfortunately, so you’ll need to do all of this in a desktop browser.)

That’ll pull up a form where you can fill in whatever you want to use as the basis for your filtering — a word or phase that might appear within an email’s subject or body, an address from which a message could originate, or any other variable or combination of variables you like.

Fill in the fields as appropriate, using however many variables you want — even employing quotation marks around multiword terms along with operators like “AND” and “OR” between terms, if you really want to get fancy — and then click “Create filter” at the bottom of the box.

One quick warning: By default, your filter will apply to any and all incoming messages — hence the “All Mail” setting that shows up next to the “Search” option in the filter creation pop-up. If you change that option to “Inbox,” you’re likely to see an error message informing you that the parameters you chose are not recommended and may not work properly. Leave that “Search” option set to “All Mail” — which is probably what you want, anyway — and you’ll steer clear of any errors and allow things to work the way they should.

Now it’s time for the fun part — the part where you decide exactly what happens when a message meeting your conditions arrives. You can select any combination of actions from the list and then configure them as needed. You can even tell Gmail to apply your filter retroactively to messages already in your account (as opposed to using it only for new messages that arrive from that point forward) by checking the “Also apply filter to matching conversations” option at the bottom of the box.

Once you’ve got that finished, click the blue “Create filter” button — and that’s it: Your new Gmail filter is officially in place and active. The next time any message comes in that meets the parameters you outlined, the actions you specified will automatically take place faster than you can say “I embrace Workspace in my workplace cyberspace.”

Part 3: Managing your Gmail filters

Last but not least, make yourself a mental note in case you ever need to adjust your filters in the future: If you want to edit, delete, or even just revisit a filter you created, just click the gear-shaped icon in the upper-right corner of the Gmail website, click “Settings,” then click the “Filters and Blocked Addresses” tab at the top of the settings screen. You’ll see every filter you’ve ever created there and can tweak or remove any of ’em with a couple quick clicks.

Now if only we could find a way to get the filters to deliver those blasted snickerdoodles for us. Hey, Google: Any chance you can make that happen?

This article was originally published in October 2019 and most recently updated in September 2026.

IT industry experts and analysts are still trying to piece together Nvidia’s surprise plan to pay $12.9 billion for open-source AI company Hugging Face.

Nvidia dominates AI with its GPUs, and the company generates billions of dollars in revenue through a proprietary approach to the fast-moving technology. Hugging Face, on the other hand, hosts open models and has been a neutral player between chip vendors and model labs.

“This is about Nvidia having more say in how the stack gets built,” said Stephanie Walter, analyst at Hyperframe Research.

Hugging Face is wildly popular with developers, and Nvidia is buying early influence with that crowd. “You have a better chance of being part of the production environment later,” Walter said, adding that she wasn’t sure how Nvidia reached a nearly $13 billion price tag for the acquisition.

“Hugging Face has near-uncontested market primacy over where developers go for open-weight model releases. Now Nvidia owns that,” said Mark Petty, senior director analyst at Gartner.

Nvidia’s chase for developers should force IT decision-makers to review how much of the AI stack they control, said Hector Liu, director of Institute of Foundation Models’ Silicon Valley Lab. IFM is part of the Abu Dhabi-based Mohamed bin Zayed University of Artificial Intelligence.

Liu said CIOs should ask themselves three questions: “Can you run the model on hardware you already have, without a dependency you didn’t choose? Can you see how it was built?” And, “is the license one you can build a business on?

“A model that passes all three is durable, no matter who buys whom next year,” Liu said.

IFM’s latest K2 Horizon model, which was introduced on the same day Nvidia’s deal was announced, is hosted on Hugging Face. The open model was built to answer all of those questions.

K2 Horizon runs on AI hardware from Nvidia, AMD, Cerebras, and major cloud providers, said Liu, who doesn’t expect that to change. “Nvidia has said Hugging Face stays an open platform for every builder and every accelerator, and we’ll take that at face value,” Liu said.

Nvidia pledged to maintain Hugging Face’s hardware and model independence, and said its compute won’t be required. 

Even so, Nvidia isn’t paying nearly $13 billion for a model repository, said Jake Newfield, CEO at Hermetiq — it’s buying the front door to open AI.

(Hermetiq develops AI build and code observability tools.)

AI-generated output is becoming abundant and the infrastructure that makes it testable, reproducible and deployable is becoming strategically valuable, Newfield said. “Nvidia can accelerate it with capital and compute, but the real test is operational neutrality,” he said. 

That involves assessing whether competing hardware remains equally supported across the tooling, benchmarks and deployment paths developers actually use, Newfield said.

Beyond distribution, Nvidia is also buying Hugging Face for data, Petty said. That data showed that agents overtook humans as its largest traffic source in July, the kind of insight that could prove valuable down the road.

“Every model pulled tells Nvidia what the market wants next,” Petty said.

Nvidia has every reason to grow demand for open models and to keep them cheap, Petty said. “That’s good for enterprises, as it prevents market consolidation around a small number of proprietary model owners,” Petty said.

Closed and open models will coexist and lead to a world “where you’re going to continue to train these models and run these models at scale,” Justin Boitano, Nvidia’s vice president for Enterprise AI, said in a press conference after the deal’s announcement.

Nvidia will benefit “through the training that’s done and the inference that’s done on our hardware as models get diffused into the ecosystem at scale,” Boitano said.

That’s one motivation to keep the ecosystem open and neutral, so “developers can work wherever they want to work,” Boitano said.

Open source makes AI more accessible by lowering the barriers to experimentation and adoption, said Jon Carvill, senior vice president of marketing at AI chip maker Nuvacore. “Bringing Nvidia and Hugging Face closer together should help accelerate that choice, access and innovation,” Carvill said.

But there are still unanswered questions around whether Hugging Face will remain open and how much proprietary control Nvidia might exert, said Jack Gold, principal analyst at J. Gold Associates.

Microsoft traveled a similar path with its acquisition of open-source repository GitHub, which “did not really pan out as well as Microsoft hoped,” Gold said. “With Nvidia’s acquisition, will it still be as open to competitive hardware-software access, or will there be some barriers employed?”

I surprised myself this morning when I came across an interesting Apple-commissioned report — Rethinking critical AI infrastructure — I’d not seen before. It looks at the shifting expectations for AI infrastructure and recognizes that enterprise users want (and need) secure, on-device AI solutions for critical parts of their business.

That’s why tens of thousands of companies are already investing in Macs, because they recognize that Macs do indeed do AI. The study, published earlier this year and put together by Omdia, reflects insights gathered across 1,500 conversations with enterprise tech leaders and practitioners, noting that for many in business the current cloud-based approach to AI fails to deliver on three key metrics:

• Costs: Current pricing models seem unsustainable. Particularly when it comes to agentic AI, costs climb fast and business users need to get those costs under control. 
• Security: Even the most secure cloud services include some degree of data risk. When it comes to using AI for regulated data in industries such as healthcare, business users need much more security than the cloud inherently provides. After all, data that is not transmitted will not leak in transmission.
• >Capacity>: Workload requirements change and capacity needs to scale. That can boost the cost of accessing additional cloud capacity, or impose limitations in the event it can’t be found. It’s also true that while frontier models can provide all the bells and whistles of AI for advanced tasks, the vast majority of the AI work does not require anything near as much power. As Omdia explains: “57% of enterprise models are under 10 billion parameters, well within the capabilities of modern devices like MacBook Air or the entry-level MacBook Pro.”

What they think

As you might expect, the researchers believe on-premises AI set-ups respond to all three needs; not only that, but once you’ve coughed up cash for the necessary computational infrastructure, you don’t have to pay much more. “On-device infrastructure has near-zero marginal cost after initial investment, enabling unlimited experimentation without budget constraints,” the report said. 

Basically, once you’ve invested in on-premises capacity, you can divert mundane AI tasks to those machines for processing — limiting costs, boosting security and releasing capacity, turning to cloud-based models only when higher end AI solutions are required. While that’s good news for Apple, that’s bad news for many AI companies’ revenue models. (Perhaps they should have recognized that even the most advanced LLM’s will run on a standard iPhone eventually.)

The other advantage is that if AI is not used as widely as expected across a company, the same hardware can be used for other company tasks.

What’s actually happening

Enterprises already using AI are learning these lessons, which is why we see more of them buying Macs for these tasks. They do so because Apple’s computers deliver the computational power and performance to run AI effectively, from chip design to power consumption to the OS itself. Apple has intentionally built its platforms to be the best in class for running AI on device, and the Unified Memory architecture Apple has created in Apple Silicon scales really well, meaning you can run ever larger LLMs on Macs. 

It’s not just Macs, either. An iPad can run up to 14 billion parameter models quite happily; a Mac Studio reaches 480 billion; and a cluster of four Mac Studios will take you all the way to 1.6 trillion parameters using off-the-shelf cables.

To put that into context, Omdia found that 57% of the AI models typically used by the enterprise come in at under 10 billion parameters, which implies that enterprises could run a huge chunk of their AI tasks on an iPad, an iPhone, and certainly on a Mac. The ability of Apple’s ecosystem to scale is precisely why most AI developers at frontier model companies already use Macs. “Organizations that build AI solutions in-house adopt Mac for AI workloads at nearly double the rate of organizations buying commercial solutions,” the report explained.

The takeaway

Apple is emerging as an important component of an overall ecosystem for applied AI in the enterprise — or anywhere else — challenging frontier models with a scalable, controllable, economical, and secure approach to deployed AI that delivers most of the bang expected for the enterprise buck. 

While Apple paid for the report, that doesn’t necessarily invalidate its conclusions, which are not myopic around the Apple platform. Apple does not replace everything else, it just becomes one of the pillars to build success with AI. Companies can use other AI services and solutions, but they’ll want Macs along for at least some of the ride. And as the models themselves evolve and become slimmer and more refined, the platforms that run them best will deliver the advantage business users need.

Now, we need Apple to develop tools for the management, deployment, and governance of these solutions.

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

Nvidia has released a free tool that will enable users to build an AI inferencing cluster from disparate PCs on the same network, accessible from a single interface.

Released as a beta, Nvidia Personal AI router (PAIR) connects devices running Windows, macOS or Linux to process AI inferencing workloads privately.

While the system is aimed primarily at home users, it could find favour with enterprises looking to put idle desktop compute capacity to use.

PAIR works with DGX Spark desktop supercomputers, PCs containing RTX GPUs, and some MacOS devices. The systems in the cluster run tasks in parallel, but PAIR does not turn them into a virtual GPU, Nvidia said.

The beta version of Nvidia PAIR is available for download now.

This article first appeared on Network World.

The destiny of Spirit Airline’s data is still undecided, months after the company sought bankruptcy protection.

AI data company Micro1 has now offered $12.5 million to acquire a trove of the company’s emails, Teams chats, operations and employee productivity data, according to a report by aviation website Simply Flying,

It said the data includes about 600 million email and chat records generated by 17,000 employees, as well as 17 million OneDrive files, 20.5 million SharePoint items, and more than 30 million recorded customer service calls. Such a large repository of information is a gold mine to any company looking to train AI models more effectively. The report says that this data includes sensitive, decades-old employee and workplace records.

But Micro1’s offer comes weeks after Google acquired the data at auction, with its $10 million bid beating the $7.5 million offered by another AI training company, Mercor.

The airline’s former employees objected to the sale, and last week their unions took legal action to block the it.

Nelson, international president of the Association of Flight Attendants-CWA, which continues to represent more than 5,500 of Spirit’s flight attendants, told Forbes that former flight attendants were unhappy about Spirit attempting to cash in on sensitive data when they still have not been paid their accrued vacation time, sick leave, and outstanding compensation.

However, this type of personal data is extremely valuable to the likes of Google. It means that AI models can be trained in more realistic scenarios. One option that is being explored is whether the data can be anonymized, which may offer a way forward to keep both sides happy.

This article first appeared on CSO.

Adobe’s search for a new CEO is over: It has promoted Anil Chakravarthy, president of its customer experience orchestration business, to the top role.

It has taken six months to find a successor to outgoing CEO Shantanu Narayen, who announced in March that he would step back from the CEO role, remaining with the company as chairman.

There had been much speculation that he would be replaced by Adobe’s president of creativity and productivity, David Wadhwani, who was responsible for the digital media business segment that generates around three-quarters of the company’s revenue. Having missed out on the top job, however, he has chosen to leave Adobe, announcing his departure on LinkedIn.

Chakravarthy was responsible for the development of several products, including Adobe CX Enterprise, GenStudio and Brand Visibility, as well as the introduction of CX Enterprise Coworker.

He takes over at a shaky time for Adobe: Its stock price has tumbled dramatically in the past few years as the rise of AI has meant workers can lay out content and manipulate photos without needing Adobe products. Chakravarthy, who will initially work in tandem with Narayen, will have his work cut out for arresting the current decline.

So, you’ve got email, you say? Lots of it? More than you can possibly manage without losing the few metaphorical marbles still sloshing around in that soggy ol’ brain of yours?

I hear ya. In fact, I think we all can relate (even those of us whose brains are, erm, slightly less soggy). And I’m here to tell you: It doesn’t have to be so difficult.

Gmail has a variety of built-in tools for making your messages more manageable. Some of ’em are a little bit different from what you might be accustomed to using in more traditional email clients (here’s lookin’ at you, Outlook) — but if you take the time to figure out how they work, you might just be surprised at how effective they can be.

There’s no better example than Gmail’s label system. It’s a strange concept to wrap your head around at first, especially if you’re used to the more typical folder-based method of inbox organization, but here’s a little secret: Labels actually are folders, in a sense. That, however, is just one small part of their inbox-organizing power.

Think through these nine label-centric possibilities and get ready to see Gmail’s labels in a whole new light.

1. Use Gmail labels like super-folders for categorizing your email

First, the most basic Gmail label mindset to master: You can think of a label like a folder — but with an important twist: Instead of a message being placed into a label, the label is placed onto the message.

That subtle-seeming distinction is actually quite significant. What it means is that a message doesn’t have to be associated with only one label, as is typically the case with folders; rather, you can apply as many labels as you want to any message, and each one ends up acting like a sticker — a label, one might even say! — that sits atop the email along with any other labels you’ve applied.

So, for instance, if you keep tabs on stats for your company’s website, you might label all incoming emails from Google Analytics as “Web Reports.” But maybe you also have your own personal website for which you receive Analytics updates. You could label the reports from your personal website as “Web Reports,” too, and then add a second label of either “Work” or “Personal” onto every message to create a distinction between the two types.

On the Gmail desktop website, the easiest way to create a label is to click the label icon in the toolbar at the top of the screen when you’re viewing a message or when you’ve selected something from a message list — then start typing whatever name you want to use for the label. Once you’re done, simply hit Enter, and Gmail will create the label for you and apply it to the message.

The next time you click the label command, you’ll see your newly created label as an option.

You can also perform the same action by using the keyboard shortcut L while an email is open or selected, provided you’ve enabled Gmail’s keyboard shortcuts system.

On the mobile front, you can create a new label within the Gmail app for Android or iOS by tapping the three-line menu icon in the upper-left corner of the screen and then looking for the “Create label” option before the list of existing labels (on Android) or the “Create new” option directly after that list. You can apply an existing label onto a message, meanwhile, by looking for the “Label” (on Android) or “Label as” (on iOS) option in the main three-dot menu anytime an email is open or selected.

2. Save yourself a step and label while archiving

Here’s a handy command to remember: If you want to add a label to a message and simultaneously dismiss the message from your inbox, use Gmail’s “Move to” option.

On the desktop website, that’s the icon showing an arrow inside a folder, directly to the left of the regular label icon. On both Android and iOS, you can find the same command within the three-dot menu icon while any email is open or selected. You’ll see a list of options that include your labels; just select the label you want to assign to the message.

Whatever platform you’re using, that’ll handle all the steps for you in one fell swoop. And if you’re a fan of shortcuts like this, by the way, I’ve got a whole story dedicated to time-saving Gmail tips just like ’em.

3. Apply labels while you’re composing an email

Gmail labels aren’t only for incoming messages; you can also proactively apply them to a new message you’re composing and then know that that email and any replies associated with it will remain properly organized and present in all the right places.

On the Gmail desktop website, all you’ve gotta do is hit the three-dot menu icon in the service’s compose window and look for the “Label” option in the list that appears — then create a new label right then and there or select any existing label to apply it.

The mid-composing label-adding option isn’t present in the Gmail mobile apps, unfortunately, but you can accomplish the same thing in a roundabout way by heading into your Sent messages (from the app’s main three-line menu) and then selecting or opening an email to add a label onto it right after you’ve sent it.

4. Organize your label lists

All right, so you’ve got your messages labeled — now what? Well, first, you can always browse through your labels to find something you need. Gmail keeps your list of labels (in alphabetical order) in its left sidebar, on the desktop website. You can collapse or expand that sidebar by clicking the three-line menu icon in the upper-left corner of the screen, and you can click on any label in the list to see all of the messages associated with it.

By default, though, that list is probably quite the unruly mess. So let’s get it organized:

• First, if you see a line in the list of labels that says “More,” with a downward-facing arrow alongside it, click it to expand your full list of existing labels.
• Now, click the three-dot menu icon next to each one of your labels. (The three-dot icon appears only when you hover over a label.) Assign each label a color, if you’d like; that’ll make it more visually distinctive and give it more or less emphasis (depending on the color you choose) when it appears in your inbox.
• In that same three-dot menu, look at the “In label list” section and consider if you want the label to always appear in your label list, to remain permanently hidden beneath that “More” divider, or to appear in the list only when unread messages are present within it. The less unnecessary clutter you have visible, the easier it’ll be to find the labels you actually use often.
• Next, look at the “In message list” section and think about whether you want the label to show up as an option when you’re adding a label onto a message. If it isn’t a label you ever actively apply to messages, you might consider hiding it to reduce clutter and increase your efficiency in that area.

On Android or iOS, you can find your labels and browse through any of ’em by looking inside the Gmail app’s main three-line menu. On Android, a third-party app called eLabels can also let you make more advanced label modifications from your phone or tablet — but in general, those sorts of adjustments are most easily managed from the Gmail desktop website.

5. Combine related labels into groups

While we’re getting your labels organized, take a moment to mull over whether any of your labels would make more sense as sublabels within a broader category. Maybe, for instance, you’d have one label called “Expense Reports” and then sublabels within it for “Staff,” “Freelancers,” and “Travel.”

This is an adjustment you’ll absolutely want to make on the Gmail desktop website, where the full selection of label customization commands is readily available. You can find the option to create a sublabel by clicking the three-dot menu icon next to any label name within the site and then selecting “Add sublabel” from the list that appears.

Just note: Somewhat confusingly, sublabels and parent labels are treated as separate but related entities — so if you were to add a message to “Staff” in our previous example, its label would show up as being “Expense Reports/Staff.” The message wouldn’t, however, show up when you click “Expense Reports” in the left-of-screen label list; it’d appear only when you clicked “Staff” in that same section. If you wanted it to appear within the results for both the parent label and the sublabel, you’d have to add both of them onto the message.

6. Use labels for smarter searches

Gmail’s labels aren’t just for browsing; you can also use them as variables to narrow down a search and make it faster to find a message you need. To include a label as a variable in a search, just click or tap the Gmail search box at the top of the website or mobile app, type label:work (using the name of your actual label name in place of “work,” of course), and then type in any other term or variable you want.

If you were trying to find a travel-related expense report from Tim Cook’s trip to Chicago, for instance, you could type label:travel from:tim@apple.com chicago into the search box. Including the label would narrow down your search considerably — skipping over messages from Tim Cook that might’ve just mentioned Chicago in some other context — and let you get to what you need more efficiently.

You can even narrow down your search further and search for messages that contain multiple specific labels — like label:travel label:work, which would show you a list of all messages that have both of those labels in place.

And on the mobile front, you can make your life easier yet by tapping the “Labels” dropdown within the app’s search area. That’ll let you simply select from a list of available options and save yourself the trouble of manually typing anything in.

Gmail actually treats many of its own built-in message designations as labels, too — so in addition to searching for your own custom labels, you can search for (and in some cases also find within the mobile app dropdown menu) things like:

• label:inbox
• label:unread
• label:promotions
• label:social
• label:starred
• label:muted

Beyond that, you’d never know it, but Google also supports a hidden series of advanced Gmail labels for automatically identifying emails related to areas like travel, purchases, and finance.

And finally, any recent past searches you’ve conducted will show up as suggestions whenever you tap or click in the search box, which makes it especially convenient to revisit any frequently accessed label-related explorations in the future.

7. Let Gmail apply labels for you

Here’s where things really start to get interesting: In addition to manually applying labels to messages as you see fit, you can train Gmail to automatically categorize and process messages for you.

The first step is to think about what factors would make an incoming message fit into a particular label — whether it’s the sender’s email address or domain name, a specific word or phrase in the subject line, or maybe even the address to which the message was sent.

In my own inbox, for example, Gmail applies a red “VIP” label to emails that arrive from editors or other contacts whose messages tend to be timely and important. And it applies a green “Invoices” label to messages that come in from a specific address and with certain subject lines that my accounting software uses for carbon copies of new invoices.

In some cases, like with the “VIP” label, the messages remain in my primary inbox. But in others, they end up moving to less attention-demanding places — like the invoice copies, which skip over my inbox entirely (since I’m keeping them mostly as records and don’t need to be bothered dealing with them every time they come in).

Once you decide what factors should apply to what label — and what else should happen once the label is applied — a Gmail filter is the key to making the magic happen. I outlined the exact steps to setting one up in my separate Gmail filters guide. Go have at it!

8. Let your labels limit your notifications

Last but not least, instead of getting distracting alerts for every new message that lands in your inbox — or going to the opposite extreme and not getting any email notifications whatsoever — use your Gmail labels as a way to control which messages alert you.

You can pick any label that seems notification-worthy and then limit your notifications only to messages with that label attached. You can even set up label-driven notifications to function on your desktop computer and on your mobile device. (Provided you use Android, that is. Sorry, iPhone folks, but Apple’s garden doesn’t allow this level of customization to fly.)

That’s exactly what I do with my aforementioned “VIP” label, in fact. And it’s actually quite easy to set up. I put together a step-by-step guide here.

And with that, my inbox-dwelling comrade, your label education is complete. Go ahead: Label yourself organized. You’ve earned it.

This article was originally published in November 2019 and most recently updated in September 2026.

OpenAI launched GPT-6 Astra on Thursday, disclosing that the new flagship model has crossed the “Critical” threshold for cybersecurity risk under its Preparedness Framework, a classification the company said triggers additional deployment restrictions.

“GPT‑6 Astra is rolling out today to a limited set of organizations and over the coming days will become available to all ChatGPT Plus, Pro, Business, and Enterprise users, as well as through the OpenAI API and AWS,” OpenAI said in a statement.

Enterprise administrators must manually enable Astra for their workspace, since access is off by default at launch, according to the company.

Developers can access Astra in the API as gpt-6-astra or through Amazon Bedrock, OpenAI said, priced at $10 per million input tokens and $50 per million output tokens. Pro, Business, and Enterprise users also get a variant called Astra Pro, and the company said Astra supports Zero Data Retention for eligible API customers.

Company claims perfect score on exploit benchmark

OpenAI said it tested Astra without production safeguards on ExploitBench, and that the model scored 100%, up from 78.5% for predecessor GPT-5.6 Sol. On ExploitGym, a broader exploit-development benchmark, the company said Astra reached a 42.4% success rate against 30.3% for Sol, while using fewer output tokens.

“Its ability to identify and develop zero-day exploits can help defenders find and patch weaknesses, but it also creates a need for stronger safeguards,” OpenAI said in the blog post.

OpenAI also tested Astra on vulnerabilities disclosed in the three months before launch, to check whether it could find flaws on its own rather than recalling old exploits from training data. The model found two new zero-day vulnerabilities during that test, OpenAI said, and it is now disclosing both to the software makers involved.

Sanchit Vir Gogia, chief analyst at Greyhound Research, said the Critical label is a disclosure event rather than a capability event.

“Astra’s capability did not change between 10 August, when OpenAI said Critical capability could not be ruled out, and September 1, when it said the threshold was met,” Gogia noted. “The testing changed. The model did not.”

That inverts the obvious enterprise response, he said.

“Astra is now the only frontier model whose cyber capability an enterprise actually knows, because it is the only one measured against a published threshold, while every unlabelled model already sitting behind enterprise credentials has never been measured that way and will not be until its vendor chooses to measure it,” Gogia pointed out. “Those models are not safer.”

OpenAI said the public version of Astra will refuse advanced offensive tasks such as generating proof-of-concept exploits, though it plans to loosen those restrictions for vetted defenders through a program called OpenAI Daybreak in the coming weeks.

The launch follows OpenAI’s rollout of GPT-5.6 Sol, which the company said scored 73.5% on ExploitBench at launch, and comes months after Anthropic’s Fable and Mythos models were briefly pulled from export markets over similar concerns.

Governance shifts from the model to the harness around it

Gogia said the bigger shift is that reasoning now translates into state change, since a wrong chatbot answer is an information problem while a wrong agent action inside a customer-record system is an operating event.

“The governance unit therefore moves off the model,” he said, arguing the relevant question is no longer which model is approved, but how much damage a given identity can do before a control intervenes.

Amit Kumar Jena, head of AI development at Kanerika said the visibility problem is concrete: when an agent acts through a user interface, systems of record log the action as a person, so an agent that updates 400 ERP rows shows up as a service account making 400 updates, with no record of which instruction or model version produced them.

“You lose granularity inside the exact system a regulator or auditor will ask to see,” Jena added.

OpenAI said it built a new evaluation, informed by an incident involving Hugging Face, to test whether a model given an impossible task would exceed its authorized scope.

“Compared to GPT‑5.6 Sol, which without production safeguards went beyond the authorized target 48% of the time, GPT‑6 Astra did this in 0% of cases,” the statement added.

Gogia said the more uncomfortable finding is that Astra behaves better and watches worse: OpenAI reports decreased chain-of-thought monitorability against Sol, with Astra less likely to reveal incriminating reasoning, and its monitoring covers OpenAI’s own external deployment but nothing published extends that telemetry to customers. “OpenAI being able to monitor Astra does not mean an enterprise can audit Astra,” Gogia said.

The article originally appeared on CSO.