Apple Broke Its Own Rules for 2 New Macs—and AI Buyers Are Snapping Them Up

Apple has predictable habits for releasing new hardware, so it was a surprise when the tech giant revealed new Macs with updated, more powerful chips last week. The refreshed hardware arrived before Apple’s traditional iPhone event, which this year occurs on Wednesday, September 9. So why did Apple release these machines, the Mac Mini and Mac Studio, when it did? Thanks to a new report, we think we understand: Apple’s updated desktop Macs were announced early because they’re selling like hotcakes and Apple wants to sell more of them to eager buyers. These machines are desirable because they’re ideal for acting as hosts for local AI models. According to news site The Information, the sudden AI-driven popularity of the machines caught the Cupertino, California-based company by surprise. Apple even apparently lacked the necessary enterprise-centric support teams. Why would anyone want to run an AI locally, though, when enterprise-ready AI systems are everywhere at the moment? Everyone from Google to Microsoft is offering powerful AI services from their giant cloud server farms, with plenty of business-centric tools. And platforms like Amazon Web Services offer powerful developer-friendly AI environments from their data centers. The keywords are “cloud” and “data centers.” These third-party AI offerings require gigantic computer facilities, which is why they’re offered by deep-pocketed tech giants like OpenAI on a remote-access basis. But if you run your own, less powerful AI models on your own hardware, then you remain in control of the entire operation. This means you can train the models with data that no one else can access. It means only you and your staff see the outputs when you query an AI. It means that if your developers improve the AI algorithms in clever ways, then only you benefit. All of this is useful for intellectual property protection and even, for some companies, for preserving audit trails for sensitive data handling. Finally, hosting an AI model on your own hardware means you retain control of the cost. Spiraling, expensive AI bills for remote-access services have surprised many companies in recent months, landing some users in the headlines because they owe so much. Thus Apple’s reasonably priced Macs are suddenly hugely popular. The newly updated machines are even faster than earlier versions for AI purposes, too: Apple highlights that the new Studio can carry out “Up to 9.8x faster” LLM AI prompts, and the new Mini has similar improvements over previous editions, thanks to the new M6 and M5 Pro processors inside. MacRumors pointed out that when Apple announced the new Macs, it even highlighted that they can be clustered together to create a powerful compute facility (think almost-a-supercomputer on your desktop) for exactly this purpose. The Mac Mini’s prices start at just $900, leaping up if you select more powerful chips or more memory. The more powerful Mac Studio starts at $2,500, and higher-end configurations can reach many thousands of dollars. But these remain one-off purchases, compared with paying an open-ended bill for AI-as-a-service from the likes of OpenAI. There’s a lesson here for many smaller-business owners. AI is the buzziest tech right now, and it comes with the promise of boosting efficiency and maybe helping to cut costs, too. But typically, because AI is delivered by cloud-based companies like OpenAI or Google, each system brings its own risks in terms of potential expenses as well as data leaks. Surveys show a staggeringly high number of workers merrily type sensitive company data into these chatbots, unaware of the risk they pose. So running your own AI models on machines like Apple’s new ones could be a good solution. And even if you’re not in the market for building your own safer, Apple-powered local AI server, other options exist. Some AI models are freely downloadable and can run on relatively modest hardware. This may be an even simpler and cheaper option, depending on your company’s AI needs. The news should also serve as a reminder to savvy CEOs that deploying AI is not a one-and-done maneuver. The tech is advancing fast, so continuously evaluating which AI best serves your needs at what price could save you money in the long run. BY KIT EATON @KITEATON