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Apple was surprised by AI-driven demand for Macs

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Apple’s iPhone sales and Services revenue were the stars of the show in the tech giant’s most recent quarter, but the Mac quietly outperformed — helped by growing demand for AI workloads.

Wall Street investors had expected to see Mac revenue in the low $8 billion range, but Apple reported $8.4 billion in the second quarter ended March 28 — a notable beat for a non-core segment of the tech giant’s business. In addition, investors ahead of earnings believed that Mac sales would be essentially flat year-over-year. Instead, Mac sales were up 6% on an annual basis, the company told investors. The company’s total revenue was $111.2 billion, a 17% increase from the same period last year.

Apple chalked up some of the Mac growth to recent product launches, including the well-received MacBook Neo. However, those fun, colorful computers were only on sale for a few weeks after the March 4th pre-orders began. Realistically, most units shipped mid-to-late March, and some demand may have been pushed into April as certain models sold out.

Apple CEO Tim Cook told analysts on the company’s Q2 earnings call on Thursday that customer demand for the Neo was “off the charts” and higher than Apple had expected. He also noted that Apple set a record in the quarter for customers new to the Mac, partly due to the Neo.

Cook attributed the Mac sales growth to the use of the platform for running local AI models, like OpenClaw — something that took Apple somewhat by surprise as Mac Mini and Mac Studio devices sold out in recent weeks.

“Both of these are amazing platforms for AI and agentic tools, and the customer recognition of that is happening faster than what we had predicted, and so we saw higher than expected demand,” Cook said of these Mac sales. He also noted that the Mac Mini was top-selling desktop in China — a market that’s been in an OpenClaw frenzy as of late.

Still, Mac revenue was flat on a quarter-over-quarter basis, suggesting this new demand has yet to scale. Cook said it may take Apple “several months” to reach supply-demand balance on the Mac Mini and Studio models.

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“We’re not at the point where we’re saying this [constraint] is going to end anytime soon. And it’s not because of a problem, per se, other than we just under-called the demand,” Cook explained.

Enterprise demand for the Mac was also at play. Apple pointed to a couple of larger companies, including Perplexity, that had turned to Mac as their preferred platform for building enterprise-grade AI assistants.

He also said Apple was “supply constrained on the MacBook Neo,” and has even seen school systems, like Kansas City Public Schools, dropping Chromebooks for the Neo.

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Nvidia launches new platform for reining in rogue AI agents

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As the debate rages over whether the recent spate of rogue AI agents is a step toward AGI or a more conventional engineering problem, Nvidia is offering its own answer to problem.

Nvidia CEO Jensen Huang on Monday introduced a toolkit of software and hardware products that add independent security layers around AI agents to ensure they stay within their test environments even if they attempt to break out.

The release follows a string of hacking incidents involving AI models from Anthropic, Google, OpenAI, and Meta that bypassed security controls to escape their testing environments and access real-world systems. The first and most prominent example occurred this summer when OpenAI agents breached Hugging Face while trying to complete a cybersecurity task. And the hits keep on coming — OpenAI published a new site dedicated to reports of its AI agents going rogue.

Huang said Monday during an interview with CNBC that its new Nvidia Open Agent Safety Platform would have prevented these breaches.

Nvidia, which has made tens of billions of dollars selling its GPU and CPU chips to AI labs, doesn’t support slowing down development or adding new regulations to the industry to solve the security problem. The answer, the company believes, is to move some security controls outside the agent altogether — creating a constant and independent security guard that will keep AI agents in check.

“AI’s extraordinary potential for society will only be realized if we solve AI safety,” Huang said in a statement. “As we continue to discover the frontier of AI capabilities, we must accelerate discovery at the frontier of AI safety. Safety and security require full-stack engineering.”

The new Nvidia Open Agent Safety Platform combines OpenShell, its open-source software for controlling what agents can access while they operate, with Sentry, an independent monitoring system that runs on Nvidia’s BlueField-4 data processing units. Nvidia says placing Sentry on a separate processor — rather than on the CPU or GPU where the AI agent operates — provides an isolated view of the agent’s activity.

OpenShell isn’t new; the company announced the software in March. But it’s the combination that Nvidia believes will provide the security layer needed to keep the industry plugging along. OpenShell provides the software boundary around the agent, while Sentry adds another line of defense at the hardware level tha the company says will continuously monitor behavior and “quarantine agents that attempt to move outside their boundaries in milliseconds.”

Nvidia listed dozens of companies that have signed on to to support the effort and use the open-source platform including Anthropic, Arm, Microsoft, Oracle, and SpaceX. OpenAI is not listed as a participating company.

Huang told CNBC in an interview Monday that work on this effort started a year ago following the introduction of OpenClaw, an operating system of agents created by Peter Steinberger. In March, Nvidia released NemoClaw, an enterprise-grade AI agent platform and its own version of OpenClaw that baked in security.

“When you deploy an agent, no matter how smart, the first thing you do is to take away all of its rights,” Huang said during his CNBC interview, later comparing these security measures to how human employees and even executives are managed with companies.

Nvidia’s release was widely supported by those who have cautioned that a slowdown in development could allow China to surpass the U.S. in AI.

David Sacks, a founder, venture capitalist, former White House AI czar, and co-chair the President’s Council of Advisors on Science and Technology, said Nvidia’s announcement is a reminder that agent safety is an engineering problem.

“Recent breakouts weren’t proof that development must stop,” he wrote on X. “They were proof that the sandbox was too weak. The runtime environment was poorly designed and misconfigured.”

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Anthropic releases Sonnet 5.5, which it calls a significantly cheaper, faster work partner

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As the AI model wars continue, Anthropic has released the newest version of Sonnet, the company’s mid-tier model, which it says will work much faster (and for significantly less) than its predecessor.

The lab describes Sonnet 5.5 as an ideal assistant for everyday tasks — including coding and creating office documents.

5.5’s predecessor, Sonnet 5, was announced about three months ago. At the time, the model’s selling point was efficient agentic deployment — the ability to run agents at a lower cost than competitors.

The big selling point with 5.5, meanwhile, is speed. Anthropic claims that Sonnet 5.5 is 30 percent faster than its predecessor, and that its rate of token burn is significantly slower.

In the Anthropic hierarchy of models, Sonnet is less powerful than the Opus model, but can be more useful in certain circumstances because its agility. In particular, Anthropic’s benchmarks show Sonnet 5.5 performing better than Opus 5.5 on agentic coding, likely because of its ability to spawn multiple agents without exceeding cost limits.

Sonnet 5.5 is also said to have significant cyber capabilities, with the company claiming that it has “comparable” cyber capabilities to Opus 5. As a result, Anthropic says that 5.5 is the first Sonnet model that will be subject the same cyber safeguards that apply to Fable and Opus.

The company also plans to release a new version of Haiku — its smallest model — in the coming weeks, although it didn’t give a firm date as to when that would happen.

The last year has seen a flurry of new model releases from the major AI labs. Just last week, OpenAI released a number of new models — including enhanced versions of Sol and Luna, its mid-tier and budget-friendly models. Meta also announced a new model, which it said would power an upcoming feature associated with its smart glasses.

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Google is killing off Gemini’s Gems in favor of ‘skills’

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As all-in-one AI agents like Meta’s Muse and Instinct take off, Google announced it’s shutting down the Gemini feature known as “Gems,” which had allowed users to build custom AI assistants for specific tasks. However, the work users invested in creating the Gems won’t be destroyed. Gems will be automatically migrated to “skills” that can be used across different AI tasks.

Details about the change are being shared in the Gemini app, where a message warns users that Gems will become skills starting on November 17, 2026. The company said it will migrate the Gems to the new format, so users won’t have to do anything to make the transition. The Gems themselves will remain usable until then.

Launched in 2024, Gems were meant to help users teach their AI to perform certain tasks without having to repeat the instructions. For instance, some of Google’s pre-made Gems had included a learning coach, a brainstorming assistant, a career guide, a coding partner, and an editor. Users could also make Gems for their own needs, like a running coach, nutritionist, or vacation planner. These custom assistants could also be shared with others, which Google had hoped would help make its Gemini AI app more popular.

Image Credits:Google

The news of Gems’ shutdown is another example of why Google shouldn’t be so quick to give every new AI feature its own brand name, icon, and prominent placement in its app’s navigation — especially if it’s going to shuffle things around over time, merging one feature into another. (To be clear, this has been a failing point of Google’s strategy long before the AI era. At one point, for instance, the company was operating multiple different messaging and communication apps at the same time.)

Yet, even as skills, the former Gems still aren’t as consumer-friendly as just typing in text to a chatbot like Meta’s Muse. Instead, Google notes you’ll have to enter a forward slash “/” in a task thread to select the skill you want to use — a user interface that engineers, not regular folks, tend to prefer.

Gems’ wind-down was first reported over the weekend by 9to5Google.

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