Microsoft broke European Union competition law by bundling Teams with other Office 365 applications, the European Commission said in a preliminary finding published Tuesday. If Microsoft fails to defend itself, the company could face billions of dollars in fines and other penalties.

The EU’s antitrust regulator said it had sent Microsoft a statement of objections outlining its finding that the company had given its Teams communications service an unfair advantage by bundling it with subscriptions to Office 365 and Microsoft 365, the suite of software-as-a-service applications that also includes Word, Excel, and PowerPoint.

Teams enables workforce collaboration via video and chat and surged in popularity during the Covid-19 pandemic, reaching over 300 million global users in 2023.

“The Commission preliminarily finds that Microsoft is dominant worldwidein the market for SaaS productivity applications for professional use,” it said in a news release posted Tuesday.

The company’s practice since at least April 2019 to tie Teams to its core SaaS productivity apps has restricted market competition for similar products as well as defended Microsoft’s own “market position in productivity software as well as its suites-centric model from competing suppliers of individual software,” the Commission concluded.

“In particular, the Commission is concerned that Microsoft may have granted Teams a distribution advantage by not giving customers the choice whether or not to acquire access to Teams when they subscribe to their SaaS productivity applications,” the Commission’s said.

Interoperability limits between competing offerings and Microsoft’s apps also bolstered Microsoft’s advantage and prevented its rivals from competing, and in turn innovating, to the detriment of customers in the European Economic Area, the Commission said, referring to the 27 EU countries plus Iceland, Norway and Liechtenstein.

Investigation a year in the making

The decision follows a nearly year-long investigation that started last July and was sparked by a July 2020 competition complaint against the software giant by then enterprise messaging application Slack, which has since been bought by Salesforce.

Microsoft first unbundled Teams from its Office suites in the European Economic Area and Switzerland in August 2023 to try to appease EU officials during the investigation, then extended that move worldwide in April.

Neither effort apparently did anything to dissuade the Commission from considering Microsoft in violation of competition rules, a decision that was foreshadowed when the Competition said in May that it planned to include Teams in its inivestigation of Microsoft for anticompetitive practices despite the company’s concessions.

For its part, Microsoft plans to continue to address remaining concerns the Commission has over Teams as it awaits further decisions by the Commission, such as what, if any, financial consequences the company will face.

“Having unbundled Teams and taken initial interoperability steps, we appreciate the additional clarity provided today and will work to find solutions to address the Commission’s remaining concerns,” Brad Smith, Microsoft vice chair and president, said in a statement emailed to Computerworld.

The road ahead

Microsoft now gets a chance to present its defense. However, if it’s unable to sway the Commission from its preliminary decision, it could be forced to pay a fine of up to 10% of its annual worldwide revenue under EU law, and the Commission may also impose remedies to end the infringement.

“This EU chargesheet proves what was feared: Microsoft didn’t do enough to provide a level playing field to the Team’s competitors,” noted Pareekh Jain, CEO of EIIRTrend & Pareekh Consulting.

It now has its work cut out for it to unbundle Teams and create interoperability for competitors’ software to avoid penalties and damages, Jain noted.

It’s about a decade since EU regulators last levelled anti-trust charges against Microsoft: Its failure to offer Windows 7 users a choice of browser drew a €561 million (then about $731 million) fine.

To date, Microsoft has racked up around €2.2 billion ($2.4 billion) in fines for tying or bundling products together in a way that was deemed anti-competitive by EU regulators.

The rush to build global cloud infrastructure to support artificial intelligence (AI) has turned Nvidia into a top three tech stock and will likely nurture innovation in processor design and energy creation — but Apple may need to serve itself.

Apple needs to bring more for less

The IEA says global electricity demand to drive data centers will more than double by 2026. That’s even as consumption of AI services such as OpenAI spikes when devices (including new iPhones) gain easy access to them.

To satisfy demand, tech firms must tweak more computational performance and additional energy efficiency from the chips they put inside both servers and edge devices. But this push for efficiency and low power reflects what Apple has been trying to do with its own silicon development for years. Apple Silicon chips were way ahead of the wider industry on both metrics (at least for consumer devices) long before generative AI (genAI) climbed through the Overton Window. 

While attention on server processors rests with Nvidia, the M4 processor inside the iPad Pro could be seen as harbinger of what is to come. At 38 trillion operations per second, we know it has the fastest Neural Engine you can get. Ever modest, Apple has described the M4 iPad as the best AI PC money can buy, and those same processors are also coming to servers.

Apple is now in the server market

The company’s Private Cloud Compute (PCC) system consists of proprietary Apple servers running Apple Silicon chips to provide responses to Apple Intelligence queries.  

While these are only being situated in US data centers at this time (as that’s the only place Apple Intelligence will be made available on launch), it’s easy to expect the company will deploy these highly secure systems globally *except in the EU in the coming months. 

It must. As Apple Intelligence launches globally, Apple will find itself needing to ramp up its international server infrastructure to meet the demands for AI its billion or so customers might make. 

But one data center at a time, server by server, Apple is already in the server market. Motivated by privacy, these Apple servers also meet wider industry needs around energy consumption and performance requirements.

It makes sense for Apple to expand this provision, perhaps even to offer highly secure, low energy server services to enterprise users, but it’s more likely to drive its streaming services while lowering energy consumption.

There’s another chip coming

It is worth noting that Apple hasn’t yet hit a performance ceiling. Very likely to be tumbling off production lines right now, the next iPhone chip is expected to be a 3nm processor. This might deliver even faster Neural Engine performance than you get inside the M4, which means the next iPhone will be capable of handling even bigger calculations at higher speeds for less energy than Apple’s best available current chip delivers now. Apple also has a road map toward 2nm chips, which will maintain that pattern of performance and energy efficiency.

All of this means the company already has a road map toward processor performance that it can now apply to the server market it abandoned in 2011, when it discontinued the Xserve. 

This is true corporate social responsibility

Apple already knows it isn’t good enough to just put high-performance chips inside servers and edge devices if they consume vast quantities of energy. To mitigate this, the company has already invested hundreds of millions of dollars in reducing energy consumption across its entire ecosystem, including major investments in renewable energy supply. It will not turn back time.

With that in mind, it will want to widen its ecosystem of low power, high performance iCloud servers, and when doing so it makes sense for it adopt those servers across its other online services over time. After all, if it can build servers and services that can be delivered at lower energy requirements without compromise on performance, why wouldn’t it do so?

For Apple, adoption of these may be an easy win in terms of its environmental performance data. But at what point will these systems become a service offering in their own right? What value could they unlock for the company?

However the eventual story ends, it’s interesting that by focusing on energy efficiency and computational performance for iPhone chips (and the PA Semi purchase), Apple put itself in a good position to meet the then-unseen challenges of server-based AI — and the space between the lines suggests we’re not near the end of that particular story just yet….

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Apple’s decision not to introduce Apple intelligence, iPhone Mirroring, or SharePlay Screen Sharing in the European Union this year isn’t surprising, and reflects concerns around privacy far more than being a response to Europe’s decision to act against Apple’s App Store compliance.

The news basically is that Apple has confirmed it will not introduce the Apple Intelligence features it announced at WWDC in EU nations because it has concerns around the application of the Digital Markets Act (DMA). 

Apple Intelligence delayed, App Store gets a DMA slap

“Due to the regulatory uncertainties brought about by the Digital Markets Act, we do not believe that we will be able to roll out three of these [new] features — iPhone Mirroring, SharePlay Screen Sharing enhancements, and Apple Intelligence — to our EU users this year,” Apple told the Financial Times.

At the same time Apple made its announcement, the EU itself announced it will begin to take enforcement action against the company for breach of the DMA. Europe is concerned about elements of Apple’s offer to developers and the fees it charges the small number of developers who are the most successful on the store, arguing this stifles competition. Apple says it has made changes and is “confident” its plans align with that law.

It’s worth noting that the EU recently proposed an incredibly intrusive surveillance law that would break end-to-end encryption. While it looks like those proposals may have been shelved, Apple might have decided to stall while it waits to see what kind of shabby surveillance laws do get passed. 

Privacy or convenience? It’s up to EU

If you think about it, the beauty of Apple Intelligence is that it uses information your device has collected about you in order to function. But the risk of that information existing — even on your device — is that under the DMA, it’s not certain the EU won’t insist on that data, your data, being opened up to competitors. 

That’s a lot of information.

Apple is committed to keeping that information private and secure, but once it exists and is on the device in some form, I expect the company is concerned the DMA could force it to open up the information to third parties who want to compete with their own AI. As we’ve seen since the invention of the Internet, not every company is legitimate, ethical, or trustworthy, and even those that are might not have enough clout to invest in the world’s best security teams to maintain safety on their platforms.

A Pandora’s box chock-full of trouble

I get the sense that Apple’s decision to hold back on Apple Intelligence in the EU reflects the ongoing battle between the two entities as Europe forces Apple to open up a little. Given the source of this speculation, that might be correct, but the analysis misses what’s really at stake: once you have all your personal information turned into usable data on your device, every spook, hacker, fraudster, blackmailer, censor, despot, cop, or secret service operative is going to want to take a look.

That means any weakness in protecting that information opens a Pandora’s box of misanthropy — affecting consumers, corroding trust, and enabling surveillance at a scale no one has seen ever before on our sadly ailing planet. 

Could the EU end up without Apple Intelligence? 

It feels possible EU might never get Apple Intelligence.

Apple says: “We are committed to collaborating with the European Commission (EC) in an attempt to find a solution that would enable us to deliver these features to our EU customers without compromising their safety.”

According to the Financial Times, Apple seeks “clarity” from the European Commission regarding the level of access it would need to grant to third parties over Apple Intelligence features in order to be DMA-compliant.

However, rather than providing any insight into requirements, an EU rep said companies like Apple are, “Welcome to offer their services in Europe, provided that they comply with our rules aimed at ensuring fair competition.” Which is, of course, what Apple is asking for, it just wants to know how those rules will be applied to its service before launch, rather than working with decisions made after the event.

What isn’t yet clear is the extent to which other AI providers might be affected. Is it possible the European Commission might have just created an obstacle to AI deployment?

Who has the energy for this?

And, of course, the big conversation everyone should be having concerning artificial intelligence is one Europe’s regulators don’t appear to be addressing at all — the energy consumption of AI servers. Combined, the world’s data centers now consume more power in a year than the entire Italian nation, and this is set to increase exponentially. Perhaps waiting until privacy, security, and energy challenges are solved makes sense after all?

One more thing is also certain: That with the removal of these three features the temptation to upgrade to iOS 18 among European users will be lower than ever before, given they comprise the majority of improvements to the OS.

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

Data centers are draining more electricity from global power grids than ever before because of generative artificial intelligence (genAI) and general AI processing needs. 

The compute capacity to train large language models, the platforms on which generative AI (gen) and AI run, is now roughly doubling every nine months, according to Epoch AI, an AI research institute. The International Energy Agency forecast that global data center electricity demand will more than double from 2022 to 2026, in large part because of AI and cryptocurrency.

That insatiable demand for energy has tech companies scrambling for alternative sources of energy as well as ways to reduce the energy needs of AI technologies.

One potential emerging solution to the AI-compute dilemma is quantum computing, which vastly surpasses today’s binary computing systems in processing capabilities and energy consumption. Studies have shown quantum computing can increase the performance of AI neural networks for tasks such as natural language processing and image analysis.

“Quantum computing definitely augments the power of AI. For example, AI and quantum computing used together can accelerate drug discovery and personalized pharmaceuticals by years. Quantum computing supports AI-based simulation of clinical drug trials so that the trials take one hour instead of ten years,” said Avivah Litan, a vice president analyst at Gartner.

For example, in February, Insilico Medicine and the University of Toronto announced they’d demonstrated the first instance of a generative model running on quantum hardware outperforming state-of-the-art classical models in generating viable cancer drug candidates.

What is quantum computing?

In classical computers, bits programmed as units of data have a possible value of one or zero — hence the term binary code. In quantum computers, data units are programmed with quantum bits, known as qubits, which can represent a one, a zero, or a combination of both zero and one at the same time. At a high level, that trait enables quantum computers to be faster and better at fundamental processing tasks than data processing on classical computing systems that use GPUs or CPUs.

For example, Google’s Quantum AI division built a supercomputer based on its Sycamore quantum processor. Each chip currently holds 70 qubits and can reportedly complete in seconds what would take a CPU- or GPU-based supercomputer of similar size decades to process.

“Quantum artificial intelligence with better algorithms… are faster and more accurate,” CompTIA, a global, nonprofit IT association, stated in a blog.

Commercial quantum platforms, such as Microsoft Azure Quantum, AWS Braket, Google Cirq, and others, allow cloud providers to use quantum comuting as compute service offerings.

“Think of these platforms as quantum computing marketplaces whereby the cloud service providers have partnered with multiple quantum computing vendors to provide access to their hardware, software, QSDKs [Quantum software development kits], etc.,” said Heather West, a research manager with IDC.

“Most of these cloud service providers have not, and thus do not, provide access to their own quantum systems, the exception being Google. AI is not a part or related to these offerings,” she added.

As with any technology, along with the positives there are negatives associated with quantum computing. For example, quantum computing poses a serious threat to the cybersecurity systems relied on by virtually every company, according to CompTIA. The current standard for encryption algorithms, such as RSA or SSL/TLS, relies on the complexity in factoring large numbers into primes, and that’s the type of problem quantum computers are great at solving, CompTIA said.

Startups and established companies continue to accelerate their advances in the quantum computing space. Big tech companies such as Alibaba, Amazon, IBM, Google, and Microsoft have already launched commercial quantum-computing cloud services. Two years ago, Goldman Sachs said it planned to introduce quantum algorithms to price financial instruments as soon as 2026. Honeywell anticipates that quantum will form a $1 trillion industry in the decades ahead.

Quantum computing, meet genAI

Some say quantum computing is a natural partner for genAI and can reduce its energy demands.

For example, Sumitomo Mitsui Trust Bank in Japan is using quantum computing to run genAI-powered programs for financial simulation models of future market movements. The bank partnered with Zapata AI, a genAI company that was spun out of Harvard University’s quantum computing lab in 2017.

Christopher Savoie, Zapata AI’s CEO, sees linear algebra (quantum math) as the solution to perform all kinds of AI tasks, including chatbots such as ChatGPT.

“We’re throwing an obscene the amount of GPU energy at chatbots right now. Are we getting that much business value right now from it? We’re hitting a wall: when are we going to make money with that?” said Savoie, who is a molecular biophysicist.

Savoie pointed to the study done by Insilico Medicine and the University of Toronto, which Zapata participated in.

“When we used this quantum-based model… we were able to develop cancer drugs the other models didn’t,” Savoie said. “We used quantum models to determine what drugs would block this cancer protein and then non-quantum models. The quantum models found two capable drugs that we synthesized and showed they blocked the cancer protein.

“So, it’s qualitatively better,” he continued. “It’s cheaper, faster, and better — better in that we get faster answers. That’s important in drug discovery. You’re saving a lot of money for pharmaceutial companies if you get your answer the first run around. Or you have a more accurate modeling of trading behavior for a bank.”

Zapata AI’s Orquestra platform was specifically designed to run any AI or machine learning model, including more traditional neural networks as well as the company’s proprietary tensor networks.

Tensor networks can be used to model any quantum circuit and run it on today’s classical computers, giving users an on ramp to the potential benefits of future quantum computers, according to Zapata AI. Tensor networks also come with their own advantages for AI today, including more accurate, efficient, and expressive AI models.

“Every quantum circuit can be written as a tensor product, which means we can do things on GPUs that quantum computers will eventually be faster at doing. Zapata and others have shown that quantum math is better at getting better answers in the context of generative AI,” Savoie.

Specifically, Savoie said, quantum statistics can enhance genAI models’ ability to extrapolate missing information and generate new, high-quality information from big data. Generating genuinely new and high-quality data is very important for industrial use cases, he said. 

Early days yet

IDC’s West said quantum computing fits with complex problem solving, but it’s “not a big data solution.” Quantum computing will be useful for solving specific types of problems, she said.

In quantum computing, a qubit begins in a binary state of 0 or 1, but through a process known as annealing, the qubits become entangled, allowing them to represent many possible answers, always with minimum energy. The process occurs in microseconds.

“Quantum annealers are best suited for optimization problems,” West said. “The complex algebraic/factorization problems include some QML [quantum machine learning] problems, but not all AI problems will be suitable for quantum. Research is being conducted to determine how to integrate AI into [quantum computing] and [quantum] into AI to optimize the compute resources needed to solve some of these problems.”

In large part, quantum computing is in very early stages of development, West noted. That’s because the hardware still needs considerable improvements for gate-based models that allow for the​ execution of quantum‌ algorithms. By applying various gates ​sequentially, complex computations can be carried out.

“There are not any real-world applications for this type of system,” West said. “These systems are only useful for small-scale experimentation and debugging. Quantum [computing is] currently being used for solve some scientific and business optimization problems. It is still too early for the integration of AI. Right now, it is only a hypothetical and experimental.”

SoundHound AI has enhanced its AI-based food ordering capabilities with the acquisition of Allset, an online ordering platform that connects restaurants and local customers.

Financial terms of the deal, announced Thursday, were undisclosed.

Allset is a food ordering platform designed for local pick-up, working with nearly 7,000 restaurant partners nationwide, including Joe & The Juice and Charleys Cheesesteaks.

Speech-to-meaning

SoundHound, a voice AI and speech recognition company, was founded in 2005 and went public in 2022. The company develops speech recognition, natural language understanding, music recognition, and search technologies.

In 2023, SoundHound generated $45.9 million in revenue, a 47% year-on-year increase. The vendor is growing but not yet profitable.

As part of Nvidia’s broader strategy of investing in AI-related tech companies, the chip maker has invested $3.7 million into SoundHound, in return for a 0.6% stake.

SoundHound’s Vehicle Intelligence product, powered by Nvidia Drive, allows drivers to ask questions related to maintenance, safety, and other vehicle-specific information using natural speech.

SoundHound markets itself as an independent voice AI platform, offering customers the ability to create their own branded voice experiences rather than relying on voice assistants from bigger vendors.

Allset

SoundHound said the deal to buy Allset will advance its plans to enable voice-enabled food and drink ordering across millions of cars, TVs, and smart devices. Its voice ordering technology works across multiple channels, including via phone, drive-thru, kiosk, and mobile app.

More than 10,000 restaurant locations use SoundHound’s platform to understand speech in a range of major languages, learn any restaurant’s menu, process orders directly to the point of sale (POS), and answer customer FAQs.

“Allset will help SoundHound bring voice AI solutions to even more restaurants looking to improve operational efficiency,” Keyvan Mohajer, CEO and co-founder of SoundHound AI, said in a statement on the deal.

For example, SoundHound has been working with White Castle, the US-based fast-food hamburger joint, to offer voice AI ordering technology at select White Castle drive-thrus for a year, with plans to roll out the technology to 100 locations by the end of 2024.

Many in the fast-food industry are looking to use AI technology to increase efficiency and reduce costs.

Using an AI system that provides a consistent, interactive ordering experience is a big ask.

Super size snags at McD’s

McDonald’s recently ended its trial of AI-powered drive-thru technology developed in partnership with IBM. McDonald’s had been testing IBM’s AI-powered voice recognition technology at around 100 US drive-thru locations for around two years.

The technology has numerous glitches, chiefly around the misinterpretation of customers’ orders to sometimes comical effect.

Hard to swallow mistakes included adding bacon to ice cream and putting excessive quantities of items on orders (e.g., hundreds of chicken nuggets on a single order). People took to social media with tales of “fighting the McDonald’s robot” and similar.

The automated order taking system — which evidently had problems picking up on accents and dialects, noise and cross-talk from neighboring drive-thru stations — will be dropped from the end of July, Restaurant Business reported.

IBM has yet to respond to a request for comment from Computerworld but reportedly said it looks forward to working with the fast food restaurant chain on a variety of projects in the future.

Bill Conner, CEO of mobile technology developer Jitterbug, told Computerworld that teething problems with new technologies are to be expected. Waiting for technologies to mature is unwise, since slow adoption of AI technology is likely to leave businesses at a competitive disadvantage, Conner argued.

“The future of application development, orchestration, and automation is based on an AI evolution, not a revolution,” Conner said. “Even the most agile organizations need a smart, measured approach to infusing AI capabilities into their business and infrastructure.”

As employee experiences become increasingly digitized, the digital employee experience (DEX) is becoming the primary interaction you and your workers have, whether in person, remote, or hybrid. That’s why the technologies that enable whatever mission you happen to be on have become so important, as the tech is by definition an essential component in any digital employee experience.

We know because they told us

We already know this because big enterprises like SAP, Salesforce, Cisco, IBM, and many others have told us that when given the choice, employees will choose an Apple product as their primary workplace device. We also know that, for example, sales of portable Macs absolutely boomed during the pandemic, when every office-based worker transitioned to become a home-based employee in a matter of weeks. 

Once the pandemic seemingly ended, those home-based workers became mobile employees, and later — sometimes reluctantly — turned into hybrid workers. 

In that sense, the importance of Apple’s products has already been proven. These devices, whether Mac, iPhone, or iPad, have already been used on a global scale to maintain businesses remotely in real time — as will visionOS devices in their time. 

That success continues to translate into increasingly large deployments across industries you might not have considered to be natural Apple users before, from retail to engineering and beyond. 

Empowering good business with DEX

Of course, business leaders recognize the changing workplace, with 24% of leaders already seeking to unlock improved DEX and productivity. The analysts at Gartner say digital workers who are happy with the tools and applications provided for work are 1.6 times more likely to stay.

While not everyone is an Apple user, sundry TCO studies suggest that businesses that do adopt those products realize significant benefits in terms of support costs, device longevity, employee retention, and productivity.

But at its core, Apple’s key offer to business is the same one it offers to consumer users: a user interface that, for the most part, gets out of the way to enable the user to get what they want to get done as effectively as they can.

That’s the whole point of smart DEX strategy — to equip and empower employees so they can stay focused on their task and not get bogged down by tech.

This secret sauce is compelling to any busy person, and the savor gains gusto on strength of Apple’s full platform — by which I mean that on mobile, tablet, or computer you get a similar DEX.

This familiarity is critical, as it makes it easier to complete tasks on whatever device makes the most contextual sense for a person at any point in time. In essence, the provision of consumer-simple technologies capable of delivering enterprise-class results to employees who can work from anywhere empowers immense business flexibility. 

Infrastructural change

The other post-pandemic benefit supporting the trend comes through the rapid evolution of device management of Apple devices since the pandemic first hit.

Sure, there was already a healthy industry of device management vendors (including Apple itself), but the company took note of enterprise pain points and introduced tools to address them. Think zero touch, declarative device management, improvements to activation lock, and even the recent introduction of a dedicated (and provisionable) password app based on the company’s existing iCloud Keychain. 

The result? 

At the front end of business, DEX improves through employee-driven adoption of Apple’s products.

But the company has also been speaking with both Windows- and Apple-familiar IT admins to figure out how to enable good experiences for them. It’s now truly possible to ship hardware to new hires, who can safely and effectively start their managed employee experience with a single login to their new device — and for IT to manage the entire transition through a single pane of glass.

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

One small but key new feature for iCloud in macOS Sequoia should make developers and engineers a little happier, as it will be possible to sign into iCloud and other Apple ID (soon Apple Account) services from virtual machines.

This hasn’t been possible before, which has impeded developers and users hoping to test iCloud features in apps, including trialing iCloud sync on their software. It has also been an obstacle for any Mac user who just wanted easy access to iCloud data form within a virtual machine. 

Who is this feature for?

For most developers, the big advantage will be in software testing. Many developers need to test software in multiple Mac configurations, but not all of them have the fleets of Macs required. Given that so many app developers now make use of iCloud features or make use to some degree of iCloud sync (think calendars, for example), the inability to easily make such tests may impact customer experiences.

Developers who like to keep a firewall between clients and their projects by hosting these in different virtual machines should also benefit from this support, as it means their iCloud data and services remain consistently available independently of their workflow.

So, what is the deal? 

Apple says that so long as both the host machine and VM are running macOS 15 Sequoia or later, it will be possible to use iCloud and other Apple ID-related services with the hardware. It’s not a complete panacea, unfortunately. That’s because the need to run macOS 15 or later means developers wanting to trial older operating systems will still have problems. All the same, it means that over time, it will become possible to test the performance of older macOS versions as new iterations ship.

There are a few technical considerations, as explained in an Apple tech note:

• If someone moves a VM to a different Mac host and restarts it, the Virtualization framework automatically creates a new identity for the VM using the information from the Secure Enclave of the new Mac host. The person using the VM will need to reauthenticate to allow iCloud to work.
• The Mac will also detect attempts to start multiple copies of the same VM simultaneously on the same Mac host. 

Enterprise-ready Macs

This is just one of a slew of WWDC-announced improvements coming to Macs and other Apple devices this fall. These include improvements in device management, passkeys, software updates, and Safari management.

Admins can also install executables, scripts, and configuration files remotely via MDM, which should make it a little easier for organizations to deploy and manage services across their fleets. Apple Account (formerly Apple ID) management has also been improved to encourage organizations to use Managed Apple Accounts..

Another great improvement is in Activation Lock. There have been problems in which perfectly functional Macs that have been handed on for renewal or sold legitimately on second-hand markets have ceased to function because people have neglected to disable Activation Lock. Apple does have a process to help in cases of this kind, but at WWDC it introduced new support to enable IT admins to remove Activation Lock using Apple Business Manager, which should mitigate the unintentionally bricked Mac problem.

Finally, Declarative Management will replace MDM profiles for software updates, as well as for some other commands and queries. The beauty of this is that Declarative Management delivers far more transparency to admins, while also improving the experience for users — your Mac won’t suddenly enter an update cycle just as you sit down with the board to begin a critical business condition status presentation, for example.

One more thing: whispers tell me it is also going to be possible for IT to disable services such as access to OpenAI from within Apple Intelligence, so unapproved sharing of enterprise data should not happen on managed devices.

All told, WWDC has been really good for IT admins, who now enjoy access to a broad and growing range of powerful tools with which to manage their Apple fleets. This seems particularly timely as the size of those fleets continue to expand. 

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

Slack CEO Denise Dresser this week laid out what she sees as her company’s primary use for artificial intelligence (AI) in the future: making it easier for users to find key channel conversations and turn them into the basis for tasks and projects.

Dresser, a longtime Salesforce employee who took the reins of Slack six months ago, sat down with members of the media on Tuesday after her keynote address at Salesforce’s World Tour event in Boston. Much of the focus was on Slack’s integration with Salesforce’s Einstein Copilot.

(Salesforce acquired Slack in late 2020.)

What Slack will eventually be able to offer both its own and Salesforce’s users is a unified experience where AI oversees any influx of both structured and unstructured data and parses through it to offer users the most important summaries. Being able to find key moments in chats and knowing what happened in conversations is hard to navigate, Dresser said, and is at the heart of Slack’s AI integration.

“Sometimes AI can be the simplest thing that drives productivity,” she said. “So, we did Slack AI Search. With that, Slack becomes the long-term memory of your organization. …Being able to find things easily in a generative manner, where you actually get a summary of what you need to find, was a really big ‘Aha’ moment for us.”

AI’s adoption and integration into virtually every Slack function will continue to accelerate. Dresser pointed to an “evolution of skills” that has come with the adoption of the technology, including prompt engineering or the use of natural language processing to perform functions, such as the creation of software without traditional line-by-line coding.

“It took two months for ChatGPT to get to 100 million users, 15 years for the mobile phone to get to 100 million users, four years for Facebook to get to 100 million users. What I think we’re going to start to see is this [same] acceleration as people start to adopt it, and see productivity improvements,” Dresser said.

“We’re going to bring that into Canvas. It’s going to be in Workflow, it’s going to be in Huddle,” she continued. “So, you’ll see AI infused everywhere. It’s just going to be by your side in the application.”

Users, Dresser explained, won’t even know it’s AI with which they’re interacting; it will be a natural offshoot of the Slack functionality. For example, users would need to use a search window to weed through days of Slack messages they may have missed. Instead, an AI-infused Slack would quickly surface the most important message summaries.

In terms of future innovations, Dresser pointed to the recently launched Slack Lists feature, which automatically captures the most important parts of channel conversations and surfaces them to users.

Less than 34% of projects are completed on time and one budget, Dresser claimed, saying that users having to switch between tasks in applications was a significant drain on time and productivity. “We have millions of people working in Slack; why leave Slack?” she said. “We wanted to bring that capability for tasks, and lists, and projects into Slack. It starts right in a [Slack] conversation, where you’re able to start a task list from that conversation and start working on your project right there.”

The AI-infused communication and collaboration platform will eventually also suggest to its users the chat channels they should prioritize for project purposes. “That type of power in terms of capability is going to be ‘Aha’ moments for people,” Dresser said.

She noted that only about a third of employees in general use AI-powered platforms in their jobs — but those who do have seen an average 81% productivity increase by eliminating mundane tasks.

As AI continues to be integrated into Slack and Salesforce tools, one challenge will be maintaining the feel and “integrity” of what’s she called a “beloved” application.

“We’ve already integrated Slack, Sales Elevate, and Salesforce. Copilot’s integration is going to be great,” she said. “One of the things we thought deeply about was making sure the craft of Slack and the experience of Slack is maintained, even when thinking about architectural integration. Creating that experience that is very Slack-like and that’s efficient and productivity is something we’ve thought deeply about.”