A year ago, GoDaddy didn’t have a single large language model running with its backend systems. Today, the internet domain registry and web hosting firm has more than 50, some of them dedicated to client-side automation products while others are being readied for pilot projects aimed at creating internal efficiencies for employees.

The first of the company’s generative AI initiatives was to build an AI bot that could automate the creation of company design logos, websites, and email and social media campaigns for the small businesses it serves. Then, earlier this year, it launched an AI customer-facing chatbot, GoDaddy Airo. With a culture of experimentation, GoDaddy has moved to formalize the way it documents more than 1,000 AI experiments to help drive innovation. Because “innovation without some kind of hypothesis and some kind of measurement is novelty,” said GoDaddy’s CTO Charles Beadnall.

Beadnall has led the GoDaddy engineering team’s pivot to building AI solutions; he spoke to Computerworld about those efforts, and challenges. The following are excerpts from that interview:

Tell us about your AI journey and how others can learn from your experience. “We’ve been focused on AI for a number of years. We’ve used different variants of it. AI’s a big term and it’s got lots of different subcomponents: machine learning, generative AI, etc. But what we’ve been focused on over the past several years is building out a common data platform across all of our businesses, such that we have inputs coming from our different interfaces and businesses so that we can understand customer behavior better. That’s really enabled us, along with a culture of experimentation, to really leverage generative AI in a way that we can measure the benefits to our customers and to our bottom line, and do that in a way that we continue to iterate against it.

“We’re all about delivering results, ether to our business and our bottom line or to our customers, and so we want to have a measurable hypothesis or what it is that generative AI will deliver to those. That’s something we’ve been building out over the past several years with common data platforms, a culture of experimentation and now leveraging generative AI in practice.”

How important is it to have measurable deliverables with AI deployments? “Ultimately, if you don’t know what it is you’re going to expect to deliver and have some way of measuring it — it may be successful, but you won’t know that it is. It’s been really important for us to have that controlled A/B test, such that we launch a new feature and measure the results against that. So, if you don’t have some form of data you can measure, whether that’s purchase conversion or product activation or something of that nature…, you won’t really know whether they’re having the intended benefit.”

Do you have to create new data lakes or clean up your data repositories before implementing generative AI? I’ve often heard the refrain, garbage in, garbage out. “There is definitely significant implications here. It’s definitely a concern people need to be aware of. The majority of the quality assurance is being performed by the large language model vendors.

“What we’ve done is built a common gateway that talks to all the various large language models on the backend, and currently we support more than 50 different models, whether they’re for images, text or chat, or whatnot. That gateway is really responsible both for implementing the guardrails…, but also to evaluate the responses back from the LLMs to determining if we’re seeing some kind of pattern that we need to be aware of showing it’s not working as intended.

“Obviously, this space is accelerating superfast. A year ago, we had zero LLMs and today we have 50 LLMs. That gives you some indication of just how fast this is moving. Different models will have different attributes and that’s something we’ll have to continue to monitor. But by having that mechanism we can monitor with and control what we send and what we receive, we believe we can better manage that.”

Why do you have 50 LLMs? “This space is moving at a rapid pace with different LLMs leapfrogging each other in cost, accuracy, reliability and security. The large majority of these are in use in sandbox and test environments with only a very small number currently run in production behind Airo. Some of these will be dropped and never make it to production and others will be deprecated as newer models prove more accurate or more cost effective.”

Can you tell me about this gateway. How does it work and did you build it, or did you get it through a vendor? “It’s something we built and it’s going on a year now. We built it to manage the uncertainty of the technology.

“It started out with our initial push into the space as a way to coordinate among the different LLMs. If you think about it logically, a year ago there was one vendor [OpenAI] but it was clear this was going to be a very exciting space. There were going to be a lot of companies that wanted to get into this space, and so we don’t know who’s going to win. And, I think it’s probably a more nuanced discussion of who’s going to win for what. It may be that one model is better for images and another is better for chat. Still another model is better for text. This is going to evolve in such as way that vendors are going to leapfrog each other. So the gateway is a way for us to be somewhat agnostic to the underlying model that we’re using and adapt quickly in changes to cost and changes in accuracy on that path.”

How did you approach training your workforce on AI, and perhaps more importantly, how did you get them to engage with the technology? “I think that’s been surprisingly easy. We had a business unit that came up with our first use case for it, which is helping customers build content for their site and find the right domain name to put on that site. That’s something that a lot of customers get stuck on initially, because it takes a lot of mental cycles to figure out what domain name you’re going to pick, what content you’re going to put on your site — and if you want to start selling product, you have to create descriptions of those items. So, it’s a customer need that we wanted to address.

“Clearly identifying how AI will help us along a path, that business unit really made it a top priority and surged resources against it to come up with some of our first tests within this space. That really did help the team rally behind it to have that clear, compelling use case. We’re running these tests and getting data back and not every experiment was successful. We’re learning things along the way.

“In some ways, experiments that aren’t successful are some of the most interesting ones, because you learn what doesn’t work and that forces you to ask follow-up questions about what will work and to look at things differently. As teams saw the results of these experiments and saw the impact on customers, it’s really engaged them to spend more time with the technology and focus on customer outcomes.”

Is AI ready for creating real-world products you can sell to clients? Or is it more of an assistant, such as suggesting textual content, checking code for errors, or creating video? “We think it’s definitely ready for prime time. Now, it really depends on what the use case is. This is where I think being able to test in a way you can determine [whether it’s] ready for prime time in this particular usage scenario. But it’s definitely adding value to customer interactions, because it’s a set of steps they don’t need to take, but a majority of our customers are leveraging. There are lots of different use cases. Use cases that require deep expertise, it will continue to get better. If the customer wants assistance in completing something more routine…, that’s certainly a prime candidate for leveraging AI.”

What is GoDaddy Airo? What does it do? “It’s basically the AI enablement of our products and services. It’s our underlying AI technology built on top of our data platform, built on top of our experimentation platform and gateway we’re leveraging against our LLMs. Over time, it may turn into additional new products, but right now we’re focused on it making the products we already sell today that much better. It will evolve over time as we experiment our way into it.”

Do your clients use Airo, or do you use it and offer your clients the AI output you receive? “Basically, as soon as you buy a domain name and website, we’ll jump you directly into that experience. We’ll help you build out a site and if you upload inventory items to it, Airo will fill automatically fill that [textual] description for you. If we can get them from having an idea to having a live business online, that’s our major objective. That’s where we’ll be rewarded by our customers. That’s our focus. We do have a metric we track for improving the customer’s value and achievement. It’s still early innings there, but we are improving our customers’ ability to get their businesses up and running.”

How accurate is Airo? “It think it’s reasonably accurate. We run experiments where we have a threshold of accuracy, which is relatively high. We wouldn’t be promoting something that didn’t have significant accuracy and [was] benefiting our customers. I’d say it’s been surprisingly accurate most of the time. Again, there are permutations where we continue to learn over time, but for the core experience, so far, it’s proven to be more accurate than we would have expected.”

Where did you obtain your LLMs that power the generative AI? “The actual LLMs we’re using…are ChatGPT, Anthropic, Gemini, AWS’s Titan. So, we are leveraging a number of different models on the backend to do the genAI itself. But all the integrations into our flows and products is the work we do.”

What are some of the barriers you’ve encountered to implementing AI within your organization, and how did you address them? “We moved quickly but also thoughtfully in terms of understanding the security and privacy ramifications. That’s the area I’d say we spent a reasonable amount of time thinking through. I think the biggest barriers is having the creativity in deciding where these LLMs can be applied and how do you design the experiments to address those needs? Basically, building out the capabilities. That’s where we spend our time today with a common platform approach, which can then account for the security.

“It’s easy to spend enormous amounts of money without much benefit. So it has to be about those factors as well as the customer’s needs. Balancing those factors has been a major focus of ours.”

What’s next? “The big opportunity for us is leveraging AI in more places across the company — internally as well as to make our employee experiences more effective and efficient. There’s a lot of territory for us to cover. We’re under way in all the different avenues now. We’ve got a lot of activity going on to finalize how we augment these LLMs with our own data for more internal use cases. We’re in the thick of it right now. We’re identifying which pilot projects to launch internally.”

In an increasingly digital economy, ransomware might seem unstoppable without security measures in place to proactively detect and prevent it—especially with the relentless cycle of new phishing scams, malware attacks, and cybersecurity threats.

By 2025, Gartner predicts that at least 75% of IT organizations will have experienced at least one ransomware attack; Cybersecurity Ventures echoes this by expecting an average of one ransomware attack on a business every 11 seconds. The dangers of the digital world are relentless; without protection, there is no such thing as secure data. The reality is that ransomware is hard to detect, have long incubation periods, and may have a costly impact on services and business for long periods.

Breaking down anti-ransomware requirements

But what makes a good solution? It should have the right defense systems on the network side, the host side, and the storage side to best optimize data resilience. Protections for these different levels have different priorities, not unlike the relationship between door access controls and coffers.

A good anti-ransomware solution needs to be multilayered, seamlessly integrated, and have clean backup data for optimal recovery. And most of all, given ransomware’s adaptable, ever-shifting nature, good protection must be tailored to the situation at hand, and be able to utilize a range of flexible portfolio solutions. 

Meet Huawei’s world-class ransomware solution

Leading the industry is Huawei’s Multilayer Ransomware Protection (MRP) Solution. It offers two lines of defense with six layers of protection and is more accurate, more comprehensive, and more lightweight than its predecessor.

The MRP Solution complies with the National Institute of Standards and Technology (NIST) cybersecurity framework for enterprise data resilience, having passed all 21 test cases including detection, blocking, protection, and recovery. In 2024, Huawei’s MRP Solution was the first protection solution of its kind certified by Tolly Group at MWC Barcelona for detecting 100% of ransomware through network-storage collaboration. 

Huawei’s MRP Solution is a six-layer systematic system comprising two layers dedicated to networking and the other four to storage: detection and analysis, secure snapshots, backup recovery, and isolation zone protection. Its backup protection uses in-depth parsing to ensure clean data for a strong recovery, with up to 172 TB/h recovery bandwidth. Industry-leading implementation of flash storage and multi-stream backup architecture means significantly faster service recovery and minimal interruptions after detecting malicious encryption. The entire solution has a plug-and-play data card for added flexibility and versatility.

Strong storage protection ensures a strong recovery

One of the key components of a well-integrated ransomware protection solution is a robust storage protection system with multiple fail safes. Where the network is the first layer of security against ransomware, storage is the last line of defense to protect data.

Here, Huawei employs a 3-2-1-1 strategy: three copies of important data, at least two types of storage media, one offsite copy, and one extra copy in the air-gapped isolation zone. The last clean data copy in isolation is used for quick recovery from attacks. Better network-storage collaboration means better proactive defense, including using honeyfiles to attract attackers, and improved recovery speed.

With the growing sophistication of ransomware, businesses can’t afford to underestimate the immediate impact it has on their services—from business outage to data loss—as well as long-term ones such as eroded customer trust and regulatory fines. They must prioritize data resilience and security in an age where data is the backbone of the economy. Huawei offers a world-class ransomware solution that paves the way in proactively defending against changing threats, deploys comprehensive storage protection strategies, and spares no effort in the war against malicious actors.

Learn more about how Huawei’s MRP Solution can work for you here.

Once the dust has settled over the next UK election, Apple might be forced to open up its business there in the same way it is being opened up in Europe — thanks to the Digital Markets, Competition and Consumers Bill.

The measure, expected to become UK law later this year, aims to police digital markets, strengthen digital consumer law, control mergers, and set new standards of antitrust. Among other things, this wide-ranging legislation aims to put limits around the big tech firms to increase competition in digital markets. 

Apple is likely to be a target

When it comes to Apple, the new law brings in a new status similar to the EU’s “Gatekeeper” role.

The Strategic Market Status (SMS) regime gives the Competition and Markets Authority’s (CMA’s) Digital Markets Unit (DMU) power to designate firms as having SMS if they have “substantial and entrenched market power” and a “position of strategic significance” in relation to digital activities linked to the UK. SMS status will likely be given to Apple along with other major tech firms, including Google, Samsung, Microsoft, who all have market power and strategic significance. 

While this could be seen as a badge of honor, it also means the companies will have to follow a code of conduct created by the DMU. “The scope of permitted conduct requirements is incredibly broad, giving the DMU very wide discretion to decide what obligations should be imposed on each firm,” writes Linklaters.

They may also be given more stringent merger reporting requirements and could be subject to what are called Pro-Competitive Interventions (PCI’s). 

Forced to open up?

Apple could find itself hit with one or more of these PCIs that might bring the UK more in line with the EU in terms of opening up its platforms and services. This outcome is made more probable because the CMA has been investigating Apple for some time, arguing that, “Apple’s restrictions in particular are holding back potentially disruptive innovation that could transform the way that consumers access and experience content online.”

As previously reported, the three main strands of that investigation relate to:

• How control of the browser market affects developers.
• The insistence that browser developers use WebKit.
• Apple’s refusal to permit cloud gaming services/portals on the App store.

This case has been in and out of courts for a couple of years, but the CMA’s dogged pursuit of this action shows how seriously it intends on taking action.

Now armed with the new legislation, the CMA has more tools at its disposal with which to force Apple and other big tech firms to loosen their perceived grip on digital markets, including things like unbundling WebKit from browsers or opening up for sideloading on devices.

Protecting the core business

Apple’s actions in Europe since similar legislation came into effect shows the company is willing to make changes while working to preserve its business and protect consumer privacy and security. Ultimately, its core mission seems to be that of continuing to offer goods and services via an App Store designed to maintain the user experience and consumer trust that digital storefront has already created.

There is still a compelling argument to say that many consumers actually want a curated, safe, purchasing experience, rather than being exposed to a more complex web of competing stores, with varying commitments to the consumer experience.

However, the international regulatory consensus at this point — including the crazed US antitrust case — seems to be that Apple and other big tech firms must be forced to loosen their grip, the hope being that other competitors can grow in the space they leave behind.

There is some risk to the regulatory approach: In June 2023, Apple said the iOS app economy supports over 4.8 million jobs across the US and Europe. This might turn out to mean something should regulatory zeal dent Apple’s business in those places. 

For additional insight into the provisions of the new UK law, you can take a look at the Bill in full here, or explore legal firm Linklater’s commentary on the significance of the Bill here.

Please follow me on Mastodon, or join me in the AppleHolic’s bar & grill and Apple Discussions groups on MeWe.

Nothing lives forever, and researchers have confirmed that web pages are no exception. They pop into existence at one moment in time and have a habit of disappearing with an abrupt “404 not found” at an unknown point in the future.

The rate at which this happens has a name: “digital decay”, or “link rot”. According to an analysis by the Pew Research Center, When Online Content Disappears, we can even put some numbers on the phenomenon.

Looking at a random sample of web pages that existed in 2013, the researchers found that by 2023, 38% had disappeared. If it doesn’t sound surprising that nearly four in ten web pages from 2013 would have disappeared a decade later, they did the same analysis for pages that appeared in 2023 itself, finding that a surprising 8% disappeared by the year end.

But what matters is not simply how many web pages have disappeared but where they disappeared from. On that score, 23% of news pages and 21% of pages on US government sites contained at least one broken link.

The most interesting barometer of all for link rot is Wikipedia, a site which depends heavily on referenced links to external information sources.

Despite the importance of references, the researchers found that at least one link was broken on 54% of a sample 50,000 English language Wikipedia entries. From the total of one million references on those pages, 11% of the links were no longer accessible.

Disappearing tweets

And it’s not just links. Looking at that other cultural reference point, “tweets” on the X (formerly Twitter) platform, a similar pattern was evident. From a representative sample of 5 million tweets posted between 8 March and 27 April 2023, the team found that by 15 June 18% had disappeared. And that figure could get a lot higher if the company ever stops redirecting URLs from its historic twitter.com domain name.

Some languages were more affected by disappearing tweets than others, with the rate for English language tweets being 20% and for those in Arabic and Turkish an extraordinary 42% and 49%, respectively.

Pew is not the first to look into the issue. In 2021, an analysis by the Harvard Law School of 2,283,445 links inside New York Times articles found that of the 72% that were deep links (i.e., pointing to a specific article rather than a homepage), 25% were inaccessible.

As a website that’s been in existence since 1996, The New York Times is a good measure of long-term link rot. Not surprisingly, the further back in time you went, the more rot was evident, with 72% of links dating to 1998 and 42% from 2008 no longer accessible.

This study also looked at content drift, that is the extent to which a page is accessible but has changed over time, sometimes dramatically, from its original form. On that score, 13% of a sample 4,500 pages published in the New York Times had drifted significantly since they’d first been published.

Where is IT going wrong?

Does any of this matter? One could argue that web pages disappearing or changing is inevitable even if not many people notice or care.

While the Pew researchers offer no judgement, the authors of the Harvard Law School study point out the problems link rot leaves in its wake:

“The fragility of the web poses an issue for any area of work or interest that is reliant on written records. […] More fundamentally, it leaves articles from decades past as shells of their former selves, cut off from their original sourcing and context.”

According to Mark Stockley, an experienced content management systems (CMS) and web admin who now works as a cybersecurity evangelist for security company Malwarebytes, while some link loss was inevitable, the scale of the issue suggested deeper administrative failures.

“People seem to be more ambivalent about losing pages than they used to be. When I first started working on the web, losing a page, or at least a URL, was anathema. If you didn’t need a page any more you at least replaced it with a redirect to a suitable alternative, to ensure there were no dead ends,” said Stockley.

“What’s baffling is when CMSs don’t pick up the slack. While some CMSs will catch mistakes and backfill URL changes with redirects automatically, there are others that, inexplicably, don’t. It’s an obvious and easy way to prevent a particular kind of link rot, and it’s baffling that it exists in 2024,” he said.

Alternatively, if the CMS doesn’t include a link checking facility, admins can also deploy link checking tools that will crawl a site to find broken links.

For CMS admins, spotting and correcting broken links should be a defined process not an afterthought.

Anyone who wants more detail on the methodology behind When Online Content Disappears can follow this link (PDF).

As Apple device use spirals across the enterprise, Apple admins have grown accustomed to maintaining tolerance when it comes to iCloud. But there are some controls they can apply to manage what employees can do with the online service.

Managed or personal Apple ID?

There is a difference between what restrictions can be applied on personal iCloud accounts and Managed Apple IDs. IT has far more control over the latter, but can apply some restrictions to personal devices as well, so long as they are managed by an MDM (Mobile Device Management) system of some kind.

If they are not protected by MDM, then no restrictions can be applied at all.

The big difference is that on personal devices assigned to an enterprise MDM account, IT can use a set of MDM restrictions to reduce access to some iCloud services. Managed Apple IDs have far more power, and can be used alongside personal Apple IDs on employee-owned devices, thanks to Apple’s User Enrollment tools. 

How to control iCloud access with managed devices

Managed Apple IDs cannot access certain iCloud services.  Apple says this is due to “organizational focus and to protect user privacy.” The following services are not available, though in some cases the app might be visible:

• Find My.
• Health.
• Home.
• Journal.
• Wallet (though employee badges in Wallet do function).
• iCloud Mail, iCloud+ and iCloud Family Sharing.

You can also customize access to some other apps using Apple School or Business Manager, Apple Business Essentials, and/or your MDM tools. If your fleet runs the latest operating systems, you might also be able to add further refinements to help lock iCloud access down — for example, whether users can collaborate on Keynote files from within Business Manager. Most MDM services offer similar tools.

The idea is that by preventing people from using these services from within their work-related Managed Apple ID, the natural security of the devices is enhanced. It also means you can deploy your own digital employee experiences on the devices, including use of company email.

Of course, employees with devices that support both personal and managed Apple IDs also have access to all their own personal iCloud services, but not from within your deployed mobile work environment.

What about Personal Apple IDs?

Sensibly, Apple does not let IT restrict use of iCloud on personal devices; someone can access their own iCloud account from any Apple device. 

What Apple does allow is some control of iCloud access from devices enrolled in a company’s MDM system. Using Apple’s provided MDM restriction keys, companies that don’t use Managed Apple IDs can block access to specific iCloud services from a given device. This is a little like using a hammer to crack an egg, but you can block access to the following iCloud services: Address Book, Bookmarks, Calendar, Drive, Keychain, Mail, Notes, Reminders, Photo Library, and Private Relay.

The downside is that by blocking access to these services you effectively limit what your staff can do with a device that is for all intents and purposes their own device, using their own Apple ID. Many workers would likely feel this to be an unwanted intrusion into their personal devices and see such moves as displaying a lack of trust. (IT admins could, of course, argue that they feel forced to deploy such restrictions to prevent exfiltration of valuable corporate or personal data.)

Which approach is best?

For me, if you do need to restrict access to iCloud services across your teams, it feels more appropriate to impose those restrictions via a Managed Apple ID. Doing so provides the maximum benefit — you can control and restrict device use that relates to your business, its services, and data, while also permitting personal use of that device.

The beauty of this approach is that work and personal data on a device is cryptographically separated and stored on different partitions, keeping work data secure and personal data private. While there is no such thing as a guarantee when it comes to device or data security, the combination delivers the best employee experience while enabling close control of any potential data/passcode exfiltration. Apple has also tied this experience up with Focus mode, making it as simple as a tap to switch between the work experience and personal use of the device.

Please follow me on Mastodon, or join me in the AppleHolic’s bar & grill and Apple Discussions groups on MeWe.

Zoom is adding “post-quantum” end-to-end encryption to its video and voice meeting software. The aim is to protect communication data sent between its apps once quantum computers are sufficiently power to compromise existing encryption methods. 

Right now, it’s difficult for current or “classical” computers to break the modern encryption algorithms that protect internet communications — that means anything from text messages to online banking or shopping. But security experts are concerned cybercriminals can collect encrypted data now and decrypt it once quantum computers become sufficiently capable, a strategy referred to as “harvest now, decrypt later.”

To secure communications on its meetings apps in the long term, Zoom on Tuesday said it will enhance existing EE2E capabilities available in its Zoom Workplace apps with “post-quantum cryptography.” It’s the first unified communication software vendor to do so, Zoom claimed in a blog post.

For Zoom, this means the use of Kyber 768, a key encapsulation mechanism (KEM) algorithm that’s being standardized by the National Institute of Standards and Technology (NIST). NIST has been working to identify a set of “post-quantum” algorithms that can withstand attacks from future quantum computers. 

Although quantum computers are adept at solving complex mathematical equations, meaning they could decrypt classical algorithms, existing systems are small scale and plagued with high error rates, said Heather West, research manager for quantum computing at IDC’s Infrastructure Systems, Platforms, and Technology Group.

As a result, modern classical algorithms are not yet at risk; that could change as quantum computing advances, enabling systems that can run Shor’s algorithm —a quantum algorithm that, according to one definition, is able to “efficiently factorize large composite numbers” and therefore reduce the time taken to break classical encryption.

“Due to this advantage, there is concern that some entities — specifically state-sponsored actors — are breaching and stealing data with a long-shelf life value now (think financial, government, DOD, etc.) with the intent of using future quantum systems to decrypt it and use it later,” said West.

Several initiatives are now under way to identify and develop post-quantum cryptographic algorithms organizations can deploy to become quantum-resilient. For example, NIST launched a global initiative in 2016 and is expected to release its final recommendations later this year. In 2022, US President Joseph R. Biden Jr. issued two security memorandums (NSM-8 and NSM10) to provide government agencies with the guidance and timeframes to begin implementing post-quantum cryptography.  

As for Zoom’s post-quantum EE2E feature, West said the amount of information transferred via text messages and in virtual meetings “is a rather unexplored territory for post-quantum cryptography [PQC],” but is an important area of focus. “Compromised information using these technologies could lead to national security breaches, the accidental exposure of company trade secrets, and more,” she said. “Zoom has taken this opportunity to identify a current area of data security weakness and develop an industry disruptive PQC solution.”

Even so, West points to “severe limitations” in Zoom’s approach. For example, to be secure, all meeting participants are required to use the Zoom desktop or mobile app version 6.0.10 or higher. “So there is no guarantee that everyone will be using the most up-to-date version…,” she said.

In addition, using Zoom’s post-quantum encryption means participants loseaccess to some key features, such as cloud recording. “For PQC to be effective, not only must it be secure against potential quantum cyber security breaches, but it should also allow for the same performance and utility of the applications and infrastructure than if it weren’t being used. This doesn’t seem to be the case with Zoom’s implementation,” West  said. 

In general, West said all businesses should be considering how to keep encrypted data safe in future.

“Organizations should be taking this risk seriously,” she said. “There seems to be a misconception that if an organization is not investing in quantum computing there isn’t a need to invest in post-quantum cryptography.” 

Cyberattacks using quantum algorithms have the potential to affect all businesses and organizations, she said. Some understand the importance of post-quantum cryptography and are waiting for final standards from NIST to be released, but updating to post-quantum cryptography can be a “laborious process,” so organizations should get started now by inventorying and identifying at-risk data and infrastructure. 

“Partnering with a PQC vendor or consultant can help guide the transition. PQC vendors and consultants can also help to determine what solution is most suitable for the organization,” said West.

With AI tools and Qualcomm Snapdragon X Elite chips inside its new Surface Pro laptops (called Copilot+ PCs), Microsoft is making no secret that it wants to compete head-on with the world’s most popular laptop, Apple’s MacBook Air. 

It look like the PC wars have begun again

Despite this declaration of war, it feels like Microsoft owes a lot to Apple. For example, it’s all-new Recall feature reminds me of something Apple already had in its systems called Time Machine. Like Recall, Time Machine saves versions of everything on your device in an encrypted form and lets you “recall” them later on. The feature has always been tied to the user ID and heavily secured. 

We’ll soon find out if Recall is as well protected.

But it’s not the only nod to Apple’s work Microsoft has made in its latest fan-fueled attack on the Mac: even the processors are based on the Arm chips Apple has used for years now in iPhones, iPads, and Macs. And, just like Apple’s Rosetta on M-series chips, Microsoft has an on-board emulator to run older apps that aren’t yet optimized for Windows on Arm. Microsoft claims 87% of the apps people use most will already be ARM-optimized. Helpfully, Apple’s adoption of Arm in Apple Silicon means most of the world’s biggest developers have already ported applications to Arm.

“We have completely reimagined the entirety of the PC — from silicon to the operating system, the application layer to the cloud — with AI at the center,” wrote Microsoft’s Chief Marketing Officer Yusuf Mehdi. (Arguably, that’s something Apple also already did.) 

Comparisons, comparisons, comparisons

Microsoft shared a range of test results it claims show not only that the new devices compete with Apple’s, but in some cases exceed what the Mac can do. However, as we see each time a tech product gets released, some of the claims seem a little uncertain.

Take performance, for example: Microsoft claims its product can run 58% faster than the MacBook Air M3. The company even ran a side-by-side photo editing test between the two computers to prove its advantage.

It’s worth noting, however, that the Surface device contains a fan, which the MacBook Air does not, which means Microsoft’s system can run at a higher temperature.

Once the inevitable comparative reviews appear, it will be interesting to learn how long you can run such intensive tasks on a Surface in terms of energy consumption and battery life, and how this compares to the same tasks on a Mac. Microsoft says that when it comes to simulated web browsing, you’ll get over an hour more battery life on its device than Apple’s. However, Ars Technica calls Microsoft’s battery life claims “muddy”, saying they need further independent verification.

To some degree, the comparisons might become moot, given Apple is already striding toward equipping Macs with M4 chips; they’re already available in what I see as Apple’s more direct Surface competitor, the iPad Pro. 

Making Windows…

Microsoft doesn’t see it that way. It believes its Surface Pro devices should be seen as MacBook Air competitors, is buoyed by no-doubt excellent test results, and hopes that by pimping out its systems with AI it has a compelling market proposition with which to tempt enterprise users to stay inside the Windows flock.

(Though even that bid for regained relevance still needs to get past the data sovereignty/privacy problems that beset all the big genAI solutions at the moment. Enterprise users will need to be certain of the cloud-based components of these systems before using them to handle regulated data, I expect.)

All the same, on paper and in keynote at least, Microsoft is making what seems to be one of its sassiest bids yet, once again raising the temperature as the industry prepares for what’s shaping up to be among Apple’s most existentially important WWDC events ever.

There’s a lot to get through.

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