Apple has quietly raised the desktop’s starting price to $799 after demand from developers building local AI tools cleared its shelves. Tim Cook says it could take months to catch up.

For five years, the Mac mini has been the cheapest way into Apple’s desktop ecosystem. Since the M4 refresh in late 2024, that price has been $599, an unusually aggressive figure for Cupertino, and one that turned the small aluminium box into a sleeper hit.

It became the recommended starter Mac, the home-server-of-choice for tinkerers, and, increasingly, the go-to local machine for developers running AI models on their own hardware.

As of Friday, the $599 Mac mini no longer exists.

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Apple has discontinued the 256GB configuration of the M4 Mac mini and made the 512GB model, which sells for $799, the new starting point. Bloomberg reported the change first, citing Apple’s own product pages, with confirmations following from MacRumors, 9to5Mac, Macworld, and AppleInsider. The pricing on each specification has not changed; the entry rung has simply been removed.

In effect, the Mac mini is $200 more expensive to buy in its base form than it was a day earlier.

Apple’s reasoning was made unusually explicit on this week’s Q2 earnings call. Tim Cook, the company’s chief executive, attributed shortages of both the Mac mini and the more powerful Mac Studio to demand that had outpaced internal forecasts, and tied that demand directly to AI workloads.

Both machines, he said, are “amazing platforms for AI and agentic tools, and the customer recognition of that is happening faster than what we had predicted.”

That recognition has a specific shape. The Mac mini and Mac Studio share a feature that has, in 2026, become unexpectedly valuable: large amounts of unified memory directly accessible to the GPU and Neural Engine on Apple’s M-series chips.

For developers running local large language models, agentic tools that orchestrate multi-step tasks on a single machine, or compact research setups that would otherwise require cloud GPUs, that memory architecture is a meaningful advantage. A 64GB Mac Studio costs less than the cheapest Nvidia H100, runs quietly on a desk, and does not bill by the hour.

The result has been the kind of run on inventory that hardware companies usually associate with launches, not nine-month-old products. Many higher-RAM configurations on Apple’s online store are listed as currently unavailable. The 16GB, 512GB Mac mini, the new entry-level model, is, by some retail accounts, backordered into June.

Behind the consumer-facing story is a less visible one about supply. The same advanced memory chips that ship in Mac minis and Mac Studios are also a critical input for the AI server farms being built by hyperscalers, and the imbalance between data-centre demand and global memory production has been intensifying for more than a year.

DRAM prices have risen sharply, and analysts have begun warning that consumer electronics manufacturers will increasingly find themselves second in line behind cloud providers willing to pay above market.

Cook acknowledged the constraint on the call, telling investors that supply-demand balance for both machines is “several months” away. He stopped short of predicting further price changes, but Notebookcheck and others have noted that the pattern, AI demand absorbs memory, memory becomes scarcer, consumer prices rise, is unlikely to be unique to Apple.

There is also a US manufacturing dimension to the story. The M4 Mac mini is one of the products Apple has begun assembling in part within the United States, and analysts at Technetbook and elsewhere have argued that some of the cost pressure on the entry tier reflects that shift rather than chip availability alone. Apple has not commented publicly on the relative weights of the two factors.

For most consumers, the change is a soft price rise dressed up as a product simplification. The 512GB Mac mini that used to be a $200 upgrade is now the floor. Anyone who would have bought the 256GB version, students, second-machine buyers, light office users, now pays more for storage they may not need.

For the segment Apple appears to be courting, the developer running Claude- or Llama-class models locally, the new entry tier is closer to a sensible minimum. 256GB of storage was always cramped for that workflow, and 512GB combined with 16GB of unified memory is a more honest starting point.

Either way, the broader signal is harder to miss. Apple, a company that historically holds prices steady through chip cycles, has just lifted a starting price by a third in response to AI-driven demand. The Mac mini is no longer a sleeper. It is, briefly and inconveniently, an AI workstation.

Coatue, one of the biggest names in venture capital and hedge funds, has a new plan to generate bigger returns on AI beyond its sizable stakes in Anthropic, OpenAI, xAI, and data center companies like Singapore’s DayOne and CoreWeave.

It has launched a venture called Next Frontier to buy up land near large power sources with the goal of turning those parcels into data centers, the Wall Street Journal reports. Sources tell the WSJ that Next Frontier has already signed a joint venture with Fluidstack, a cloud infrastructure startup that penned a $50 billion deal to build data centers for Anthropic. (Coatue did not respond to a request for comment.)

Although the U.S. already has 3,000 data centers, more than 1,500 new ones are in various stages of being built, according to Pew Research, most of them in rural areas. The frenzy is enticing land speculation and data center financing projects from lots of players, ranging from Blackstone to Kevin O’Leary from “Shark Tank.”

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Meta has acquired humanoid robotics startup Assured Robot Intelligence (ARI) for an undisclosed sum, the social media giant said.

“We acquired Assured Robot Intelligence, a company at the frontier of robotic intelligence designed to enable robots to understand, predict, and adapt to human behaviors in complex and dynamic environments,” a Meta spokesperson told TechCrunch in an emailed statement.

ARI’s team, including its co-founders, will join Meta’s AI unit, the Superintelligence Labs research division. ARI had raised an undisclosed seed round from AI seed firm AIX Ventures.

The startup was building foundation models for humanoid robots to perform all types of physical labor such as household chores. Co-founder Xiaolong Wang was previously a researcher at Nvidia, and an associate professor at UC San Diego, with a list of prestigious awards to his name. Co-founder Lerrel Pinto, who previously taught at NYU and co-founded the kid-size humanoid startup Fauna Robotics before Amazon snapped it up last month, has also won a string of prestigious awards.

ARI will help Meta with its humanoid ambitions. “This team, led by Lerrel Pinto and Xiaolong Wang, will bring a deep expertise in how we can design our models and frontier capabilities for robot control and self-learning to whole-body humanoid control.”

Meta researchers have been working on humanoid robotics tech for years. A leaked memo from a year ago discussed Meta’s ambitions to build such a robot, including AI models and hardware, aimed at consumers.

Even if Meta never releases a consumer humanoid product, many AI experts these days believe that the path to artificial general intelligence (AGI) — the theoretical point at which AI reaches or surpasses human-level intelligence across all domains — will require training AI models in the physical world, where robots learn through direct interaction rather than data alone.

The ARI and Fauna deals reflect a broader industry sprint — one where forecasts vary wildly, from Goldman Sachs’ projection of $38 billion by 2035 to Morgan Stanley’s estimate of $5 trillion by 2050 — a spread that reflects both the enormous potential and the uncertainty around tech that’s still finding its footing.

Apple’s earnings call revealed a few things that make it easy to see what products we can and can’t expect between now and September. The “not coming” list is much longer than the “is probably coming” one.

The Mac is supply-constrained, the iPad isn’t being updated, and iPhones don’t release again until the fall. So, there’s not much left that could arrive in the intervening months.

The Mac mini, Mac Studio, and iMac are all awaiting their M5 upgrades, but Apple’s supply chain is already backed up quite a bit. You can’t purchase an M4 Mac mini if you wanted to.

Memory prices and scarce parts could mean a longer-than-usual wait for new Macs. It’s pretty safe to say based on Tim Cook’s remarks during earnings that there won’t be any through the summer.

The iPad is a gimme because Apple said one isn’t coming without directly saying so. During the earnings call, Apple made it clear that it would be a tough compare since the iPad with A16 was released a year ago.

So if you’re holding your breath for that new budget iPad with A19 and Apple Intelligence, you’ll be waiting a little while longer.

We’ve already got iPhone 17e, so there won’t be any new iPhones until September. Also, Apple Watch won’t get touched until then either.

iPhone, Apple Watch, and AirPods are done with updates for now

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AirPods and AirPods Pro tend to be announced alongside iPhone too. AirPods Pro were just upgraded in September 2025, but if AirPods 5 are ready, those likely won’t be announced until the iPhone event.

Apple Vision Pro just got the M5 chip in October 2025 after about 20 months on the market, so that won’t be touched anytime soon. And no, that product line hasn’t been abandoned even if rumors attempted to say as much.

There is one product category Apple could touch upon due to its unpredictable release cycle.

Apple Home products are always possible

The Apple TV 4K is still rocking the A15 processor that first debuted in the iPhone 13 in 2021. It is still supported by Apple’s modern operating systems, but at nearly 5 years old, it’s time for an update.

It’s time for Apple to update the HomePods

Since Apple TV 4K is the brains of an Apple Home, it might make sense to make that product capable of Apple Intelligence. I know I’d appreciate the upgrade to my new smart home.

The HomePod and HomePod mini are both rocking Apple Watch processors — the S7 and S5 respectively. The S7 debuted in Apple Watch Series 7 in 2021, while the S5 was included in the Apple Watch Series 5 in 2019.

It might not be entirely relevant, but watchOS doesn’t even support the S5 chipset anymore. While HomePods run a version of tvOS, that does indicate exactly how old these chipsets are.

It might be time for Apple to do a basic chipset upgrade of the HomePod and HomePod mini. While they likely won’t support Apple Intelligence natively, it would do them good to have modern networking standards for use in Apple Home.

Those are the only Apple Home products Apple offers today, but there are some rumored products too.

Home Hub and cameras are unlikely

Apple is expected to debut what we’ve been calling the Home Hub tablet at some point in 2026. There are also Apple security cameras in the pipeline, or at least a doorbell, but that release window isn’t known.

Apple security cameras, doorbell, and Home Hub are all waiting on AI

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WWDC 2026 is expected to be filled with announcements regarding Apple Intelligence. One of the biggest announcements will be about Siri and its new Apple Foundation Model backend.

That Siri upgrade is what the Home Hub has been waiting for. However, while Apple could show off the Home Hub during WWDC to demonstrate AI advancements, it is unlikely to put it for sale until later.

Since the Home Hub product and Apple doorbell don’t have an Apple-equivalent, the company can safely pre-announce them at any point. I believe WWDC would be the best place to demonstrate the Home Hub, but the already-packed event may not have room for it.

Likely nothing until the fall

Since Apple has a bundle of smart home products waiting in the wings, it is safe to assume there might be an Apple Home-focused event in the future. So, even if Apple TV and the HomePods are ready to go, Apple might hold off on them for now.

If you’ve been keeping count, that means we should all have little to no expectations for hardware before the iPhone event in September. While many are likely waiting for their pet product to get an update, they’ll just have to make do with WWDC instead.

The OS 27 cycle will be an important one for Apple. It will be among the first things released to the public under the new CEO John Ternus.

An odd rumor led to premature calls of Apple Vision Pro’s death, rumors of AI and Home Hubs abound, and Apple’s App Store troubles continue on the AppleInsider Podcast.

AppleInsider Managing Editor Mike Wuerthele joins host Wesley Hilliard as a guest this week to catch up on CEO transition news. It’s clear that the silly coverage surrounding the upcoming transition is already becoming exhausting.

The Apple vs Epic trial continues to be an ongoing event that seems to have no end. This time, Apple has to go to the Supreme Court and Circuit Courts at once.

Your hosts dive into the odd Apple Vision Pro rumor that said Apple had given up on the product. They discuss why this likely isn’t the case and how the Vision product line will continue forward.

There’s also a lot to discuss around incoming products like the Home Hub and security cameras. Wes asks Mike if Apple makes too many products.

The show concludes with a discussion around WWDC and Apple’s AI efforts.

BONUS: Subscribe via Patreon or Apple Podcasts to hear AppleInsider+, the extended edition. This week, Wes and Mike discuss their work at AppleInsider and some odds and ends surrounding that.

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For years, California’s streets have hosted a quiet double standard: a human driver caught making an illegal U-turn got a ticket, but a driverless car doing the same thing got away with it, with perhaps a call to the manufacturer. That changes now.

The California DMV has announced what it calls the most important autonomous vehicle regulations in the United States. For the first time, self-driving cars can now be formally cited for breaking traffic laws (via Futurism). 

What exactly can authorities do now?

Quite a lot, actually. Under the new rules, authorities can issue a “Notice of AV Noncompliance” directly to manufacturers whenever their autonomous vehicle (AV) commits a moving violation. All the notices add up as a formal paper trail that feeds into the DMV’s permit review process. 

Beyond traffic citations, AV companies are bound to respond to first-responder calls within 30 seconds, provide access to manual override systems, and comply with emergency geofencing directives (clearing restricted zones within two minutes of being notified).

If self-driving carmakers fail to comply, they risk suspension of permits, fleet size restrictions, speed caps, and geographic operation limits, all of which could have a negative effect on the companies’ operations and revenue. 

Does this affect self-driving trucks, too?

The same set of regulations also opens California roads to heavy-duty self-driving vehicles for the first time, with new permits now available for trucks weighing over 10,000 pounds. Aurora, which has been operating autonomous freight trucks in Texas, has welcomed the development.

What’s good is that AV companies have until summer 2026 to comply with the new communication, after which, the DMV’s enforcement kicks in. Given that the robotaxi services in America are scaling quickly, establishing a citation system tied directly to operating permits could keep things in check. 

The regulations, in totality, were partly inspired by a September 2025 incident in San Bruno, where police were powerless in front of a Waymo that had allegedly made an illegal U-turn, and by repeated cases of robotaxis clogging emergency response routes across San Francisco. 

Uber has a long-term ambition that goes well beyond shuttling passengers: the company eventually wants to outfit its human drivers’ cars with sensors to soak up real-world data for autonomous vehicle (AV) companies — and potentially other companies training AI models on physical-world scenarios.

Praveen Neppalli Naga, Uber’s chief technology officer, revealed the plan in an interview at TechCrunch’s StrictlyVC event in San Francisco on Thursday night, describing it as a natural extension of a nascent program the company announced in late January called AV Labs.

“That is the direction we want to go eventually,” Naga said of equipping human drivers’ vehicles. “But first we need to get the understanding of the sensor kits and how they all work. There are some regulations — we have to make sure every state has [clarity on] what sensors mean, and what sharing it means.”

For now, AV Labs relies on a small, dedicated fleet of sensor-equipped cars that Uber operates itself, separate from its driver network. But the ambition is clearly much larger. Uber has millions of drivers globally, and if even a fraction of those cars could be transformed into rolling data-collection platforms, the scale of what Uber could offer the AV industry would dwarf what any individual AV company could assemble on its own.

The insight driving the program, Naga said, is that the limiting factor for AV development is no longer the underlying technology. “The bottleneck is data,” he said. “[Companies like Waymo] need to go around and collect the data, collect different scenarios. You may be able to say: in San Francisco, ‘At this school intersection, I want some data at this time of day so I can train my models.’ The problem for all these companies is access to that data, because they don’t have the capital to deploy the cars and go collect all this information.”

Becoming the data layer for the entire AV ecosystem is a pretty smart play, particularly considering Uber years ago abandoned its own ambitions to build self-driving cars (a move that co-founder Travis Kalanick has publicly lamented as a big mistake). Indeed, many industry observers have wondered if, without its own self-driving cars, Uber might one day be rendered irrelevant as AVs increasingly spring up around the globe.

The company currently has partnerships with 25 AV companies — including Wayve, which operates in London — and is building what Naga described as an “AV cloud”: a library of labeled sensor data that partner companies can query and use to train their models. Partners, which Uber plans to more aggressively invest in directly, can also use the system to run their trained models in “shadow mode” against real Uber trips, simulating how an AV would have performed without actually putting one on the road.

“Our goal is not to make money out of this data,” Naga said. “We want to democratize it.”

Given the obvious commercial value of what Uber is building, that positioning may not last long. The company has already made equity investments in numerous AV players, and its ability to offer proprietary training data at scale could give it significant leverage over a sector that right now depends on Uber’s ride marketplace to reach customers.