Apple’s outgoing CEO, Tim Cook, bade an emotional farewell to analysts and shareholders on Thursday as the company announced a record June quarter. His successor, John Ternus, takes over at the beginning of September with the company seemingly in solid shape.

The results were impressive, though some worrying challenges were confirmed. Apple managed to set a new June quarter record, but acknowledged slowing services growth and an unexpected mishap in forecasting future demand. Mac sales jumped an absolutely astonishing 28.7%, as the MacBook Neo grabbed consumer imagination, and overall the company saw growth everywhere except the iPad.

Apple’s fiscal Q3 2026 results saw the company generate $109.4 billion in revenue, up 16% year-over-year for a net quarterly profit of $29.8 billion. Gross margin for the quarter was 50.1%, compared to 46.5% in the year-ago quarter (though two points of this was attributed to tariff returns). 

More specifically:

• iPhone sales were up 21.7%, an unusually high number for what is traditionally a slower quarter.
• Wearables increased 6.5%.
• Services revenue increased 12%.
• And the iPad declined 5.9%.

The Mac is out the bottle

Apple’s huge Mac quarter is a bellwether moment for the company. The platform is benefiting from both the iPhone halo and the MacBook Neo/MacBook Pro blessing. Apple confirmed MacBook Neo is drawing interest from education and enterprise clients, with Apple CFO Kevan Parekh noting that roughly half of the large US education Mac purchases during the quarter displaced Windows and Chromebook devices. 

Big business wins included a massive 20,000-unit iPhone deployment at Morgan Stanley as the company shifted from employee-owned to corporate-owned/managed devices. The only problem is that demand for both Macs and iPhones is greater than Apple originally anticipated; as a result, some systems could be in short supply moving forward.

Memory, components, and demand

Cook described the current memory pricing environment as a “100-year flood” that forced Apple to raise prices on iPads and Macs. Parekh explained that memory cost changes explain more than 100% of the sequential gross margin decline, with adjusted gross margin falling from 49.3% in March to 48.1% in June (excluding tariff refunds). They’re projected to decline further. 

Cook noted the DRAM market has only three primary suppliers, and Apple is evaluating options for additional supply flexibility.

The company also has a fresh problem on its hands, in that its iPhones and Macs are selling in much bigger quantities than Apple expected. And while the company managed to meet demand in the quarter, it might be constrained in the next. “It’s not a regular supply issue. It’s a demand forecast issue, to be candid,” Cook explained. “The iPhone and the Mac are both doing remarkably better than we thought they would do.… We continue to expect high levels of demand. However, with less flexibility in supply chain, we expect the impact from the supply constraints to increase significantly sequentially.

“We’re seeing some very significant constraints currently with limited flexibility in the supply chain to remedy it.”

Services grew, right?

Apple’s services revenue also grew, but not as much as many analysts had anticipated. Apple passed $30 billion for the first time in a June quarter, buoyed by all-time records in cloud and payment services, while the company’s paid subscription base surpassed 1.5 billion. 

At the same time, Apple confirmed headwinds to services income, principally around currency exchange impacts and volatile economies, softness in mobile gaming, and – confirming the punitive impact of regulation on this part of the Apple business model – App Store business model changes.

What no one yet can know is the extent to which Apple’s recently announced Klarna product leasing deal will contribute both to services income and to accelerated replacement cycles. With 1.5 billion people in its addressable market, it’s very possible that a substantial number of customers will decide to pay for their Apple products on a monthly basis. The result would be a stable, predictable income stream for the company.

What about AI?

Apple’s introduction of Siri AI is delayed in the EU and China due to regulatory hurdles, though the situation in China could soon change following recent reports of an AI support deal with Alibaba and Baidu. 

Goldman Sachs analyst Michael Ng asked about Siri AI plans and experience. Cook said the company remains “off the charts excited” about Siri AI, and the company continues to receive positive feedback, though he added some warnings about cost. 

Cook explained that to handle users who might want to use Siri AI extensively, the company plans an upgrade option through iCloud+, though it is too early to define the specifics. (Incoming CEO John Ternus said Apple is focused on its own approach to artificial intelligence, but continues to see “enormous opportunity” in the sector.)

What the analysts said

Discussing the results, Morgan Stanley analyst Erik Woodring pointed to decelerating services growth and memory costs nibbling at the edge of Apple’s margins. “Apple’s leverage over the supply chain appears to be in question,” he said, adding it’s not clear whether AI is serving as a measurable tailwind to products or services, with its future monetization impact still uncertain.

Bank of America analyst Wamsi Mohan noted that continued demand means supply constraints are the biggest inhibitor for the stock, since demand will be shunted into subsequent quarters. Wells Fargo also pointed to the longer range picture that despite supply challenges in the current quarter, Apple still has plenty of momentum going into Q1 2027.

Finally, Jeff Pu, of GF Securities, speculated that demand might also be impacted by an estimated $300 increase in the cost of the upcoming 18 Pro series of devices, though this may be partially mitigated by Apple’s new leasing deal.

Cook’s watch is almost over

This was Cook’s 19th and final earnings call as CEO, with his successor joining the call for the first time. Cook closed the meeting with this message: “As you know, this will be my final earnings call, and John will lead these calls going forward. The transition is going seamlessly, and I am beyond excited for John to step into his new role and lead Apple into its next era.”

Apple stock was down around 9% at mid-day Friday as investors consider the quarter’s record results.

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All of the major AI providers want you to use, and ideally stay within, their super apps, and now Microsoft is looking to capture that attention, too.

During an earnings call this week, CEO Satya Nadella confirmed that the tech giant is building a Copilot ‘super app’ that will be rolled out this quarter. The new platform will bring together various Copilot tools, including chat, Cowork, long-running Autopilot agents, and the always-on Microsoft Scout, powered by OpenClaw.

Microsoft said the super app will be wired into many of its other governance platforms, including Agent 365, IT Ops, SecOps, FinOps, and business processes. And, it said, CRM and ERP systems will “serve as skills and plug-ins that go into core work.”

“You’re able to take that enterprise-wide workflow and wire it into the super app,” Nadella said, describing it as “the coming together of a new way to work.”

With this move, Microsoft will compete with OpenAI’s ChatGPT Work, Claude Cowork, and a growing number of others trying to capture as much of a user’s workflow as possible. It could prove a strong contender, as everyday Copilot “usage intensity” is at the same level as that of Outlook or Teams, Nadella said, and paid seats now surpass 30 million.

Every model should be ‘swappable’

Even as it builds a super app to bridge workflows, Microsoft is acknowledging enterprise demand for model choice. Customers are making it clear that they don’t want to be locked into one model; they want the ability to move between open, closed, and frontier options based on the best tool for the job.

This trend is reflected in Redmond’s own usage statistics: Since the beginning of the year, it has tracked a 5x increase in the number of customers building with models from multiple providers featured on its platform.

The company claims it has the broadest model catalog in the cloud, offering more than 11,000 models from OpenAI, Anthropic, Mistral, its own MAI family, and others.

“We are building a new model system, where the harness, context, memory, and action space are separate from any one model family, thereby moving the frontier on the cost-to-outcome curve,” Nadella said. “That’s really the enterprise design architecture that we are going to evangelize.”

He described enterprises as “learning machines” that need their own internal learning machines, and said that they will be evaluating how providers are helping them reach their business goals and support knowledge creation.

“The models are an input, not some extraction of the knowledge of the enterprise,” Nadella said. “This is not going to be about, ‘come in and take all my knowledge and benefit yourself, [and] I am not getting anything out of it.’”

The key is in balancing the advantages of frontier models with lower-cost options, open weights with closed weights, and having the ability to train internal models based on outputs, traces, and context. “You should and you can use frontier models,” Nadella said. “There’s no reason not to.”

However, he said, any given model at any given time should be swappable to democratize design.

For instance, data from cybersecurity evaluation framework CyberGym showed that Microsoft’s new MAI-Cyber-1-Flash coding agent achieved Claude Mythos-level performance at 50% of the cost. This is because 90% of tasks were completed by Cyber-1-Flash and 10% by frontier models from OpenAI, Anthropic, and others. 

This ability to use the right model for the right task in what is essentially a pipeline job is a “super important characteristic,” Nadella said. Microsoft Copilot, Security Copilot, and GitHub Copilot are all built to support movement between different models based on the task.

This strategy is also reflected in the company’s new Project Perception cybersecurity offering. The platform features three specialized types of agent (red, blue, and green), and the underlying harness decides which AI model is best suited for a given task. Guided by specialized playbooks, red team agents discover vulnerabilities, blue team agents triage, and green team agents propose remediation plans.

“You create your own agentic system that’s continuously operating to create the cyber defense you need,” Nadella explained. “Especially in cyber[security], it becomes critical to have that multi-model approach.”

Nadella also pointed to the recent Hugging Face incident, in which an OpenAI model went rogue, broke out of its sandbox, and launched an attack against the popular open-source platform, noting that enterprises will likely need to use multiple models to offset and remediate the various challenges of each, and should not be “subject to the refusals of one model.”

“We talk about the frontier as if it’s one thing,” Nadella said. “The frontier is about every firm having a frontier, the choice, the cost control, and the capability that they need in order to be able to control their destiny.”

Increased push to usage-based pricing, closing demand gaps

As Microsoft emphasizes its model-agnostic architecture, it is also shifting from per-seat to per-seat-plus-consumption pricing; the company recently added usage-based billing to Cowork and Agent 365, and plans to continue that trend across its products.

While these moves have resulted in sticker shock and ‘tokenmaxxing’ at many companies, Nadella framed it as a revenue driver. “We are advancing the frontier on the cost-to-outcome curve, ensuring every customer can turn tokens into business results.”

Meanwhile, Microsoft said it will continue to close data demand-capacity gaps.

The company added 88 data centers in FY 2026, including 31 across five continents this past quarter. It contended that it is bringing capacity online “faster than ever,” reducing dock-to-live times for new GPUs in its largest regions by nearly 50% over the fiscal year.

However, CFO Amy Hood acknowledged during the earnings call, “the situation is obviously that demand exceeds available supply in a relatively extreme moment.”

Reflecting this, revenue for Azure and other cloud services grew by 43% in Microsoft’s fiscal year ended June 30, and the company expects similar revenue growth (45%) in fiscal year ‘27.

Hood said that Microsoft remains “focused on delivering efficiencies,” including in its CPU and GPU fleets, and engineers are also working on process improvements. The company added another gigawatt of capacity this quarter and is on track to roughly double its overall capacity in two years.

“We are also getting more from the infrastructure we already have by optimizing across silicon, systems, and software,” Hood said.

This article originally appeared on CIO.com.

Apple may be moving faster than expected in its modem development work, and Qualcomm’s latest comments suggest that shift is already reshaping the iPhone supply chain. 

Qualcomm overnight said supply constraints are shrinking some of its Apple business faster than anticipated. “It’s availability of supply,” CEO Cristiano Amon told Reuters.

While he wasn’t specific, that likely reflects the broader industry shortage in memory, storage, and everything else and means the company’s share of components used for the next iPhone launch will fall “well below” its anticipated estimates. Amon says this is part of a transition in which future Qualcomm income will be generated by AI datacenter demand.

The company also intends to boost modem prices on Sept. 1 (And remember, the patent licensing agreement between Apple and Qualcomm expires in March 2027.)

Given Apple is selling plenty of smartphones (even as the broader industry shrinks), supply constraints won’t necessarily be because of demand for the devices; this could reflect Apple’s plan to divide the iPhone release schedule across several months, as well as its future modem development efforts. 

Reports for months have indicated Apple plans to introduce new iPhones twice a year, with the Pro range updated each fall and entry-level devices scheduled for spring. It’s a move that’s likely to help build more consistent quarterly earnings by spreading demand across different parts of the year and could reduce short-term demand for components.

Things look a little different this year, of course; the expected introduction of the new iPhone Ultra means Apple will be making three new iPhone models, not the customary four – though there is also speculation the Ultra may not ship in quantity until later on this year. 

How much does Apple need Qualcomm? Not much

There’s also Apple’s own modem development plans to consider. We know Apple’s relationship with Qualcomm isn’t easy. The two firms were engaged in costly litigation before they found a way to bury the hatchet and work together on 5G iPhones while Apple developed its C-series modems.

Those C-series modems are already used in Apple devices. The iPhone 16e, 17e and iPhone Air carry Apple’s C1/C1X modem, with the C2 variant expected in the 18 Pro series this year. 

Apple’s new modem is expected to deliver better battery efficiency, improved cellular network privacy, and AI-supported network efficiency. So, your device should last longer, be less visible to your carrier, and better able to get a connection — even when connectivity is constrained. 

Next year’s 18-series devices will certainly stick with Apple’s modems, meaning Qualcomm’s remaining Apple business should be wrapped up in the release this fall. As Apple’s modem appears in more devices, you’ll probably only see Qualcomm modems used to provide mmWave support, which realistically has very little traction or carrier support outside America.

Waiting to replace mmWave

That view is supported by reports based on information recently stolen from Apple’s India-based iPhone partner, Tata. It claimed Apple will use the C2 in internationally sold iPhones Pro and Max, while keeping to Qualcomm in US devices.

If Apple takes the same approach with next year’s iPhone releases, it would mean only US iPhones — and probably not all of them — have mmWave. As a result, Qualcomm’s modems will only be available in a very small subset of iPhones sold. That would almost certainly account for the modem maker’s reduced Apple optimism. (Apple is also part of the 6G standard development group, which implies it hopes to find some way to replace mmWave.)

It also indicates Apple is less likely to renew its current patent licensing deal, though it could still require some licenses since Qualcomm’s SEPs include some 5G-essential technologies. The other takeaway here: Apple has a high degree of confidence in its forthcoming C2 modem, which makes sense given how well-received its C1 modem has been. 

A clean sweep

One more thought. It is interesting the extent to which Tim Cook’s Apple seems to be finalizing much of its business before the transition to new CEO John Ternus on Sept. 1. (It is also notable that Qualcomm also intends to raise its prices on the same date.)

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This fall, with watchOS 27, Apple Watch will finally get access to Siri AI with a software update that turns your wrist into the most widely-used wearable AI platform on Earth.

That’s not hyperbole. Siri AI on Apple Watch is arguably the most important feature to this year’s watchOS update. Though it didn’t get much attention at WWDC, the update also offers a preview into how Apple will wrap AI into its future smart glasses.

What to expect

One important caveat is to observe that Siri AI on Apple Watch still requires your Apple Intelligence-enabled iPhone to do the heavy lifting. The interaction is easy: tap the Digital Crown and Apple’s new glowing icon appears on screen (you’ll also find this in the App viewer). The experience looks identical across every Apple device — iPhone, iPad, Mac, Apple Watch, and Vision Pro — making the assistant feel like one consistent product rather than a different experience per device.

The Siri app lets you access all your past Siri conversations (unless you turn that feature off) and pick up an old conversation right where you left off. Conversation history syncs privately through iCloud, so you can start an exchange on your iPhone and continue it later from your wrist. You can also pin a conversation you expect to revisit.

You can also use Siri on the Apple Watch to ask questions, launch apps, or even get more complex responses, such as step counts on a specific day. It can also answer difficult and specific queries with detailed answers and can summon real-time information from the web.

Personal context is the real story

That’s key, of course, as it means the smartwatch on your wrist can help you access specific details from all your contextual information; it can get details from messages, emails, and notes, for instance. Or you might use it to find a number and call it, access your door code, or look up customer information for business — all without touching your phone.

One of Apple’s own examples demonstrates this well: Saying, “Show me photos from when I went to Spain,” results in precisely that. You can also ask follow-up questions and keep the conversational going naturally, rather than being confined to single, isolated commands.

Beyond personal data, the watch can also act in apps — get directions home, send an email, play a playlist, or even more specifically, “Play the song that Brandon sent me.”

Context runs deep. A new Call Context tool can proactively surface relevant information from across your apps when phoning a business or help locate a confirmation code from Mail while calling an airline. This arguably challenges a real pain point when speaking with providers and is a good illustration of Apple’s broader AI strategy: to use on-device intelligence to remove everyday friction without asking you to track down the information yourself.

Where we are, where it’s going

It’s frustrating that you still can’t use the Watch to remotely run applications on your Mac, iPhone, or iPad. What you can do is trigger Shortcuts that run on your iPhone: enable this first on your phone by selecting the Shortcut you want and switching on “Show on Apple Watch.” Once that’s done, you can run the Shortcut from your wrist, even by voice.

That’s useful now, but as more complex apps add Shortcuts support and App Intents become more widely adopted by developers, it should be easy to trigger genuinely complex, multi-stage tasks on your iPhone from your wrist.

It’s worth noting: early hands-on testing of the watchOS 27 beta has found Siri AI genuinely impressive on personal-context queries, but still buggy in places. This is very much a first-generation feature — promising, but not yet fully reliable.

Watch the developers

Developers are already beginning to experiment with the potential for wearable AI. One of the best current examples is Granola, which just launched a Watch app built specifically to take notes during in-person meetings away from a laptop. The idea is that you tap your wrist, the screen turns green and makes a sound to alert your companion(s) that it is recording and then you carry on as normal. Once the meeting stops, switch the app off and you’ll get polished notes with meeting summaries and action items provided to you.

The only reservation I have with Granola is the lack of documentation on privacy and data retention on the developer site. Tools like these will almost certainly become more private, more secure, and more prevalent once Apple’s on-device dictation APIs extend fully to watchOS.

That last thing is perhaps the most important as wearable AI emerges: the decisions Apple makes around watchOS and SiriAI will be foundational to its future wearable AI glasses products.

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Artificial intelligence is becoming a force multiplier for Apple security research. Apple’s latest 26.5.2 software update includes patches for a record number of bugs — many of them identified by security researchers using AI-assisted tools.

A record haul of fixes

The numbers tell the story. Apple fixed 87 security vulnerabilities in iOS and iPadOS 26.6, along with an additional 155 patches for Macs. Roughly 100 flaws have been patched in each of Apple’s other operating systems: watchOS, tvOS, and visionOS. Taken together, these represent record numbers for an Apple security update. 

This is only the beginning. The scale of the release echoes the impact AI coding agents are already having on security research and may well reflect Apple’s Project Glasswing research with Anthropic and others to use AI to identify software vulnerabilities. 

Apple’s use of AI for security research is visible in the official release note. Read through it and you’ll see multiple credits to Claude, Codex, and AI adjacent tools, labs, and researchers. These tools identified flaws across Apple’s systems, including in WebKit, WebDAV, and WebKit Storage.

For good and ill

It’s a neat illustration of the sea change under way as AI adoption accelerates. This release highlights how security researchers are leaning into AI tools to check platform security just as heavily as attackers are. One fix in today’s release is credited to researchers from Calif.io, who some may recall used Anthropic’s Mythos Preview model to create a working macOS kernel memory corruption exploit in just a few days.

The release is proof positive that while AI can be used to identify vulnerabilities to undermine protection, it can also be used to identify opportunities to further secure the platforms. It is also true that as AI use across the security industry grows, the number of flaws identified will also accelerate; it’s doubtful we’ll ever reach a point at which there are no flaws at all. Apple is likely to beef up its own internal observability tools following the acquisition of SigLens, which might help it identify even more bugs using AI.

Don’t delay, install today

None of these matters much, though, if the security patches never get installed — and the delay between security patch release and installation represents a huge opportunity for attackers. Recent analysis from Fleet Device Management found that 79% of organizations take more than a day to deploy critical security patches, even as attackers increasingly exploit vulnerabilities within hours of disclosure. The same report also showed something else to worry about: AI tools are spreading fast across the enterprise, often without the version control or auditability that would let anyone track how they’re actually being used.

Despite their number, the tally of fixes Apple has published isn’t the end of the story. In this case, while Apple has published its latest fixes, how many of those vulnerabilities have already been abused in the weeks between discovery and security patch release? More to the point, how swiftly will Apple’s installed base update devices now, and how many attackers will use that delay to dive in and do the damage?

It’s a security arms race

Adam Boynton, senior security strategy manager at Jamf noted that one vulnerability, CVE-2026-43810, can be exploited by a remote user to corrupt kernel memory. “The WebKit fixes are easy to read as a phishing story, when they are actually something slightly different,” he said.

“The raw material for targeted spyware is browser engine memory corruption, and those chains are expensive enough that they get pointed at specific people like senior executives, journalists, anyone whose access justifies the cost. That’s the honest reason to update promptly rather than eventually. 

“In other words, this update matters less for its raw numbers than for what those numbers represent: an arms race between defenders and attackers who are both, increasingly, running the same kind of tools,” Boynton said.

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The 19^th-century French novelist Honore de Balzac is believed to have said that behind every great fortune lies a great crime.

That’s even more true today than it was 200 years ago — just look at how Big AI, including Anthropic, OpenAI, Google, and others have built their trillion-dollar fortunes. 

They all use vast amounts of copyrighted material to train their large language models (LLMs) without paying the copyright holders. In other words, they steal it. They don’t call it stealing, though. They call it “fair use,” which in this case amounts to the same thing.

Generative AI (genAI) training requires massive amounts of text. The better-written and more information-dense that text is, the more it helps. AI gets a lot smarter a lot faster when it’s trained on well-written books and magazine and newspaper articles than when it’s trained on social media banter (or most everything else you find on the internet).

Since the dawn of AI, companies have been hoovering up copyrighted material wherever they find it — on the open web, behind paywalls, even in manually scanned books — and then used the scanned text. And they do it all without asking authors’ or publishers’ permissions, and without paying them.

It’s the greatest intellectual property theft in history by a long shot — billions and billions of dollars worth. Books, articles, music, photographs, artwork, you name it. If a human being has created it, Big AI has likely grabbed it and ingested it without asking, then made big profits off it.

I know this from personal experience; I’ve got skin in the game. Big AI companies have used at least 30 of my books to train their models without asking.  And that’s only what I’ve confirmed. Big AI might well have stolen even more. And it also might have stolen many of the thousands of articles I’ve written through the years.

For the AI bigwigs, it’s standard operating procedure. So it was surprising to see Microsoft CEO Satya Nadella calling out Big AI for its hypocrisy in using other people’s intellectual property without paying, then crying foul when small AI companies use Big AI’s work to train their own models using a technique called distillation.

He wrote on X: “While the great innovation that comes from model providers having fair use rights to train models on public data is needed, I find it ironic that the status quo is to then turn around and impose restrictive terms on distillation, and to reserve the right to learn from customer usage and interaction data.” 

One important note here: Nadella believes Big AI should be allowed to steal copyrighted material for training purposes. He makes that clear by his mention of “fair use.” His issue is that he believes smaller AI companies should be able to use Big AI’s work to train their models — and Big AI doesn’t want to let them do it.

Alistar Barr, in Business Insider, makes a related point: “Anthropic, OpenAI, and Google are discovering what the rest of the internet has already learned through painful experience: once you put something online, people will find ways to use it in ways you don’t like and can’t stop.” 

Before we look at whether Nadella is right in calling Big AI’s actions hypocritical, let’s examine the technique at the heart of the issue: distillation.

The lowdown on distillation

Distillation refers to an AI training technique in which you take outputs from one AI model, such as the answer to a prompt, and use that output to train your own model. AI companies do that quite frequently and have been doing so for a long time.

Barr explains distillation this way: “Distillation looks an awful lot like what AI companies have been doing to the rest of the internet. Scrape web content for free and without permission. Turn it into a product you sell. Argue it’s fair use. Hope the lawyers sort out the details later.”

Elon Musk has admitted his company xAI used distillation techniques to take output from competitor OpenAI to train xAI’s Grok chatbot. He explained, “Generally AI companies distill other AI companies.”

Analysts point out the AI industry is built on distillation. Neil Shah, vice president of research at Counterpoint Research says, “The reality is none of the models is an island and the entire industry has mostly evolved based on recursive learning. The newer entrants are in many instances going through the same routes of ‘distillation’ and ‘optimization.’”

It’s only become an issue now because Chinese AI companies have been using distillation techniques to catch up to American AI companies.

OpenAI CEO Sam Altman has been pressuring the US to take legal action against the Chinese companies.  Anthropic has piled on as well, saying the fight against distillation requires a coordinated response across the AI industry, cloud providers, and policymakers.

Hypocrisy or fair use?

So are OpenAI, Anthropic and other big US AI firms hypocritical, as Nadella claims? Absolutely. They’ve built their businesses on the theft of billions of dollars of stolen intellectual property and call it fair use. Now, they’re playing the victims when competitors do the same to them. (They’re also in some cases paying up; Anthropic just last week settled a copyright suit, paying out $1.5 billion.)

It’s good to see Nadella call out their hypocrisy. But Microsoft is as guilty of intellectual theft as the others — its AI Copilot is powered by OpenAI’s and Anthropic’s chatbots. The company faces major lawsuits for intellectual property theft. Among them is one by the New York Times, New York Daily News, and Center for Investigating Reporting, another by 400 local and regional newspapers, and another by 11 authors, including Pulitzer Prize winners Kai Bird, Jia Tolentino, and Daniel Okrent.

So, don’t praise Nadella for speaking out. Criticize him (and other AI tech leaders) for stealing billions of dollars in intellectual property from countless writers and publishers and calling it fair use.