I surprised myself this morning when I came across an interesting Apple-commissioned report — Rethinking critical AI infrastructure — I’d not seen before. It looks at the shifting expectations for AI infrastructure and recognizes that enterprise users want (and need) secure, on-device AI solutions for critical parts of their business.

That’s why tens of thousands of companies are already investing in Macs, because they recognize that Macs do indeed do AI. The study, published earlier this year and put together by Omdia, reflects insights gathered across 1,500 conversations with enterprise tech leaders and practitioners, noting that for many in business the current cloud-based approach to AI fails to deliver on three key metrics:

• Costs: Current pricing models seem unsustainable. Particularly when it comes to agentic AI, costs climb fast and business users need to get those costs under control. 
• Security: Even the most secure cloud services include some degree of data risk. When it comes to using AI for regulated data in industries such as healthcare, business users need much more security than the cloud inherently provides. After all, data that is not transmitted will not leak in transmission.
• >Capacity>: Workload requirements change and capacity needs to scale. That can boost the cost of accessing additional cloud capacity, or impose limitations in the event it can’t be found. It’s also true that while frontier models can provide all the bells and whistles of AI for advanced tasks, the vast majority of the AI work does not require anything near as much power. As Omdia explains: “57% of enterprise models are under 10 billion parameters, well within the capabilities of modern devices like MacBook Air or the entry-level MacBook Pro.”

What they think

As you might expect, the researchers believe on-premises AI set-ups respond to all three needs; not only that, but once you’ve coughed up cash for the necessary computational infrastructure, you don’t have to pay much more. “On-device infrastructure has near-zero marginal cost after initial investment, enabling unlimited experimentation without budget constraints,” the report said. 

Basically, once you’ve invested in on-premises capacity, you can divert mundane AI tasks to those machines for processing — limiting costs, boosting security and releasing capacity, turning to cloud-based models only when higher end AI solutions are required. While that’s good news for Apple, that’s bad news for many AI companies’ revenue models. (Perhaps they should have recognized that even the most advanced LLM’s will run on a standard iPhone eventually.)

The other advantage is that if AI is not used as widely as expected across a company, the same hardware can be used for other company tasks.

What’s actually happening

Enterprises already using AI are learning these lessons, which is why we see more of them buying Macs for these tasks. They do so because Apple’s computers deliver the computational power and performance to run AI effectively, from chip design to power consumption to the OS itself. Apple has intentionally built its platforms to be the best in class for running AI on device, and the Unified Memory architecture Apple has created in Apple Silicon scales really well, meaning you can run ever larger LLMs on Macs. 

It’s not just Macs, either. An iPad can run up to 14 billion parameter models quite happily; a Mac Studio reaches 480 billion; and a cluster of four Mac Studios will take you all the way to 1.6 trillion parameters using off-the-shelf cables.

To put that into context, Omdia found that 57% of the AI models typically used by the enterprise come in at under 10 billion parameters, which implies that enterprises could run a huge chunk of their AI tasks on an iPad, an iPhone, and certainly on a Mac. The ability of Apple’s ecosystem to scale is precisely why most AI developers at frontier model companies already use Macs. “Organizations that build AI solutions in-house adopt Mac for AI workloads at nearly double the rate of organizations buying commercial solutions,” the report explained.

The takeaway

Apple is emerging as an important component of an overall ecosystem for applied AI in the enterprise — or anywhere else — challenging frontier models with a scalable, controllable, economical, and secure approach to deployed AI that delivers most of the bang expected for the enterprise buck. 

While Apple paid for the report, that doesn’t necessarily invalidate its conclusions, which are not myopic around the Apple platform. Apple does not replace everything else, it just becomes one of the pillars to build success with AI. Companies can use other AI services and solutions, but they’ll want Macs along for at least some of the ride. And as the models themselves evolve and become slimmer and more refined, the platforms that run them best will deliver the advantage business users need.

Now, we need Apple to develop tools for the management, deployment, and governance of these solutions.

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Nvidia has released a free tool that will enable users to build an AI inferencing cluster from disparate PCs on the same network, accessible from a single interface.

Released as a beta, Nvidia Personal AI router (PAIR) connects devices running Windows, macOS or Linux to process AI inferencing workloads privately.

While the system is aimed primarily at home users, it could find favour with enterprises looking to put idle desktop compute capacity to use.

PAIR works with DGX Spark desktop supercomputers, PCs containing RTX GPUs, and some MacOS devices. The systems in the cluster run tasks in parallel, but PAIR does not turn them into a virtual GPU, Nvidia said.

The beta version of Nvidia PAIR is available for download now.

This article first appeared on Network World.

The memory crisis is getting worse for Apple, which is struggling to get enough memory chips together for its upcoming iPhone 18 Pro series smartphones. That’s according to tech journalist Tim Culpan.

As he details it, Apple and its assembly partners are still attempting to secure sufficient quantities of memory, and though they’re confident they can meet initial demand once the devices are introduced, they apparently remain concerned that wait times could rapidly extend as retail inventory evaporates.

Apple’s manufacturing process compounds the problem. The A20 processor is packaged with memory using a new TSMC process, meaning processors are reportedly piling up while manufacturers wait for memory chips. You should read Culpan’s report to get the full picture.

What’s the frequency?

You don’t need to read between the lines to see the challenge. Despite demand for TSMC’s new processors, Apple seems to have been able to secure the supply it needs. But when it comes to churning out the final packaged chips memory, supply constraints have created significant obstacles to producing in quantity.

This is bad for Apple, particularly as the challenge doesn’t appear to be confined to iPhones; customers are experiencing delays getting new Macs. “Many new orders are now not arriving until September,” Bloomberg’s Mark Gurman wrote earlier this week. 

It isn’t just Apple that will be impacted by the AI-driven memory drought. The scale of Apple’s orders is among the greatest in the industry, and if its product plans are feeling the pain, every other manufacturer will be feeling it as well.

Conscious uncoupling

This is certainly in tune with expectations voiced at the beginning of the year when Ranjit Atwal, senior director analyst at Gartner, warned: “This is the steepest contraction in device shipments witnessed in over a decade. Higher prices will narrow the range of devices available, prompting buyers to hold on to devices for longer, fundamentally altering upgrade cycles.”

Gartner in February predicted a 10.4% decline in global PC shipments and an 8.4% drop in smartphone shipments as a result. The analyst also predicted a 130% surge in combined memory and SSD storage prices by the end of this year, with steep product price increases to follow. Recent data from IDC, Gartner, Counterpoint, and Omdia confirm PC market declines, but only at around 4% (the estimates vary).

Today’s report from Culpan suggests we’ve not yet experienced the full extent of this decline — hinting that while the initial fall reflected price, the next impact will be defined by lack of supply. While this hurts big brands like Apple, smaller entities could be left high and dry. 

When the chips are down

It is interesting to reprise Atwal’s warning in February that, “the sub-$500 entry-level PC segment will disappear by 2028,” as this seems to be what’s happening. That’s something long-time Mac users like me find particularly ironic, given it was only this year Apple briefly offered up its superbly priced $499 MacBook Neo. The industry direction we’re seeing now suggests we’ll never see that again, though the success of that device gave Apple a phenomenal 28.7% increase in sales in its just-revealed June quarter.

Despite memory supply challenges, Apple seems to be faring fairly well, with market share increasing across its business. Counterpoint data reveals that Apple has achieved an astonishing 65% share of the premium smartphone market. In part, that’s because as an existing premium brand, Apple was able to better absorb rising memory costs through higher margins and reduced promotions. Realistically, this means we can expect an overall increase in iPhone prices when the new range is announced up to $300 more, Jeff Pu, of GF Securities, recently claimed. 

Building the moat

Once again, what’s sustainable but difficult for larger brands such as Apple is existential disaster for smaller players — and it’s only now a matter of time before we see some real blood. That’s particularly true in smart home and device markets, where manufacturers lack the margins to sustain higher memory prices while delivering products customers can afford. A recent Global Electronics Association report tells us 62% of electronics manufacturers are already experiencing constrained availability or extended lead times. It also tells us 82% expect rising prices, including 33% who cite a “significant increase.”

This is already being felt by consumer and business users, as networking equipment is experiencing significant shipping delays. So, while we may find ourselves waiting a month or more for an iPhone, the wait for new routers, external storage devices, and home automation systems could be even longer once available inventories disappear. 

This doesn’t appear to be a short-term challenge; a recent Digitimes report warns that vendors have already sold their entire allocation of memory capacity for 2027.

Don’t even get me started on the likely impact on the military and defense markets as high-performance memory, storage, and processor supplies become constrained. Just like declining river levels in Europe, lack of memory threatens severe disruption. With so much turbulence impacting the tech economy, all we need now is for one or more of theinvestor-supported AI companies that have helped create the memory shortages to default on loan payments.

Got to keep the customer satisfied

Eager to protect sales, Apple recently introduced the Apple Upgrade leasing service in the US. This should enable consumers to purchase new devices at prices more sustainable to them over time. Apple isn’t alone in taking such action, which will inevitably extend beyond America.

“OEMs are expanding financing, trade-in and buyback programs to improve affordability,” said Counterpoint’s Harshit Rastogi. “Samsung has also expanded its Galaxy Forever program to several markets to make flagship devices more accessible.” 

Such schemes are all well and good, of course. Consumers will embrace them in hopes of a better tomorrow. But the tech industry is not immune to the wider constellation of existential challenges impacting economic environments.

In the end, if Apple, the industry’s biggest buyer of advanced components, is struggling to secure memory, the rest of the electronics sector is likely to face even greater challenges. For consumers, the initial impacts will be longer waits and higher prices. But the longer term consequences could be slower innovation and increased consolidation across the industry.

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It’s difficult to ignore the fact that Apple seems to have turned its MacBook Neo into a weapon to promote platform growth, with enough performance under the hood to make competitors seem inferior.

And even as the PC industry moves to try to compete with Apple’s last huge Mac success, the company is already planning a powerful follow-up.

That points to the discipline Apple has applied to the Mac since the introduction of Apple Silicon. The company has built a clear product roadmap, strong entry-level pricing, and steady performance gains. This focus is now paying dividends, giving people the impetus to keep placing their trust in Apple and its Macs — even as the industry raises prices in the face of RAMageddon and price increases. 

The numbers don’t lie

“Apple’s recent price increase seems to be an inevitable response to these cost increases. In the second half of the year, other PC OEMs are expected to continue to raise prices, and the overall ASP increase is expected to continue,” Counterpoint said in a post Wednesday. The researcher tells us global PC shipments shrank 4% in the second quarter of 2026 as rising costs hit demand. The Mac maker, by contrast, moved in the opposite direction, generating 13% growth in the quarter — mainly on the back of the MacBook Neo introduction. 

Recent IDC data gives Apple 10.1% year-over-year growth and just under 10% (9.9% to be exact) of the worldwide PC market, even as the overall market declined 4.9%.

“With emerging supply chain and tariff challenges inflating memory prices…, Apple’s incredibly aggressive price-point for the MacBook Neo makes its release feel all the more like a gut punch to one of the PC market’s most valuable price tiers,” Futurum Research Director Olivier Blanchard said when the Neo was released. 

Neo 2.0 is already coming

In the immediate future, as competitors raise prices on the PCs that compete with Apple’s lower-cost device, Cupertino is already plotting the path toward MacBook Neo 2. Reports claim this will debut in March in new colors and use the A19 Pro chip from the iPhone 17 Pro, with performance boosted by slightly more unified memory (12GB, rather than 8GB). That’ll make it a much better Mac, likely with 10-15% performance gains and the ability to run Apple Intelligence, making it the best and most affordable AI PC in its class.

Just four months after the Neo’s rollout, Apple is already in position to leak rumors of an even more computationally capable follow-up, while competitors struggle to compete with the original on performance, build quality, and price. Still, the Neo might get more expensive, reporting warns, with the lowest-price 256GB model now gone, making the $599 Mac a mirage we can only wistfully hope to see again. 

That might matter less in context, as PC makers everywhere boost prices while RAM, chips, and storage prices head north, along with transport, logistics, and energy costs. “While [Apple] did raise prices in line with the broader market, it still remains well positioned against rivals facing the same cost pressures,” said Jean Philippe Bouchard, vice president for consumer devices at IDC. 

“As market conditions continue to worsen, the importance of supply chain management and capabilities are increasingly important,” Bouchard said. “The largest vendors, with their buying power and long-standing supplier ties, are best positioned to take share from smaller rivals.”

This was never about luck

This isn’t solely a market take about competition, it’s about planning.

Few in the industry seemed prepared for the massive memory price increases that hit this year. Apple clearly planned its low-cost Mac well before that happened, hoping to seize the PC market at the low-mid-range. This is precisely what it seems to have done, what it continues to do, and what it will continue to do.

The recent reports that it has a successor planned shows the breadth of the Mac company’s strategic vision, as Apple has quite clearly sought to fully exploit the failings of Windows and the internal contradictions of a value-conscious industry in stiff competition with itself.

With the first M-series Macs about to enter the replacement cycle, Apple has built a market it can capitalize on for at least a decade, meaning it already has a vision for PC sales that extends at least as far. That’s the kind of road map corporate purchasers want when they make platform deployment decisions, which is why Apple’s 10% share gains are the beginning of even more significant market change. 

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OpenAI is selling its first hardware — without any help from Jony Ive. It describes the Codex Micro as a “command center for agentic work” but it’s really a 13-switch wireless keyboard customized to help developers keep tabs on what their Codex agents are doing. It costs $230.

The keyboard has 13 mechanical switches (one keycap covers two of them by default), a rotary encoder, joystick, and RGB backlighting around the whole keypad and individual keys. It comes with 32 customizable icon keycaps.

OpenAI claims that the Codex Micro is a serious business tool: The command keys enable Codex users accept changes, reject outputs, push-to-talk, start new chats, and trigger custom actions. The rotary encoder can be used to dial up the “brainpower” allocated to tasks — or in more conventional terms, how many tokens to allocate to reasoning on a task. And the RGB lighting can provide feedback on how various tasks are progressing. And the RGB lighting under the “agent” keys can provide feedback on how various tasks are progressing.

The Codex Micro’s manufacturer, Work Louder, already has a similar device on the market, the Creator Micro, which offers similar functionality, but without the colorful keys. It costs $56 less than the Codex Micro, however.

The Codex Micro will fit in snugly with OpenAI’s other merchandise, where using Codex is as much about a fashion statement as a technological choice.

This article first appeared on InfoWorld.

Nvidia and Microsoft this month touted the reinvention of computers with a new class of “agentic AI PCs” that will “reinvent the way PCs work.” 

That’s how Nvidia CEO Jensen Huang described the computers at the recent Computex trade show. At the event, Nvidia introduced its first AI-focused PC chip called N1X, which has an integrated CPU and GPU and will be used in agentic AI PCs.

Nvidia’s new RTX Spark PCs are the first in a major “PC reinvention for 40 years,” Huang said, likening them to AI phones. “You could talk to it, it could look at you. You could ask it to read files… [or] go help you do research.”

Not so fast, say analysts, who argue the computers are mostly repackaged AI PCs that shouldn’t necessarily drive enterprise upgrades.

“Agentic AI PCs is a strange term that should probably be deemphasized,” said Leonard Lee, principal analyst at neXt Curve. “Depending on use case, PCs of the last two generations are ‘agentic AI’-capable.”

Skeptical of the hype, analysts said many current PCs are already capable of running agents, such as those spun up on device by OpenClaw. Those agents don’t need to communicate with AI models in the cloud.

In fact, Lee said, Apple has already shown that Windows isn’t needed to run agentic workloads, with the Mac Mini among the most talked-about device for hosting personal AI agents and OpenClaw.

Analysts said the definition of agentic AI PCs really comes down to the hardware inside, which largely defines their capabilities. Most are really just an evolution of earlier AI PCs, which arrived a few years ago amid similar hype.

AI PCs, specifically CoPilot+ PCs, were originally designed with neural processing units (NPUs) to support the requirements of Windows Recall. “Some argue agentic AI PCs need more GPU compute, but…Qualcomm and Microsoft would counter that agentic AI PCs have been around for a while,” Lee said.

To highlight the capabilities of the RTX Spark PC, a demonstration at Computex showed how an architectural design workflow could be split between the PC and the cloud. (An MCP server managed data exchange to facilitate the cloud-PC workflow.)

Adobe has reengineered Photoshop and Premiere for RTX Spark PCs, allowing the software to communicate with AI agents on PCs and tools to run twice as fast, Huang said.

And at the company’s recent Build conference, Microsoft CEO Satya Nadella demonstrated the new Surface Laptop Ultra AI PC based on the RTX Spark design. He positioned agentic AI PCs as running a new execution layer that can act across files and devices, including generating and executing code. 

While AI PCs with agents will be capable, they still lack applications, said Jim McGregor, principal analyst at Tirias Research. “However, PCs — especially the small form factor PCs and workstations — are likely to be the home AI appliance,” he said.

For enterprises, upgrading to RTX Spark PCs at this point could pose problems. That’s because Nvidia’s N1X CPU is based on the Arm processor architecture and could run into compatibility issues with x86 applications designed for Intel and AMD chips.

“Despite Arm processors being available for a while, enterprise penetration stays small, since compatibility with all apps, drivers, and corporate systems is critical and requires extensive testing…, even though Microsoft has done a reasonably good job with Windows 11 on Arm,” said Jack Gold, principal analyst at J. Gold Associates.

Because Microsoft is moving to natively incorporate AI into Windows, those PCs will land in enterprises ultimately, Gold said.

Regardless of hype, it might be a good time for enterprises chasing an agentic AI agenda to upgrade laggard Windows 10 devices, Lee said. “Considering the considerable hype about agentic AI, early adopters will need to upgrade their fleets if they pursue a broad agentic AI agenda for their organizations,” he said.

Apple execs are now acknowledging the company is going to need to raises prices to cope with higher component costs, particularly memory. Apple has been battling to avoid doing so, but warned this week that those efforts are “unsustainable.”

The price pressure is being felt across the tech industry. Omdia predicts the average selling price (ASP) of smartphones globally will increase by around 20% this year — partly because AI industry demands have pushed up RAM prices and partly because of rapid cost increases in processor production as a direct consequence of war in the Middle East. This impacts anything that uses memory or processors.

Apple must raise prices, CEO warns

“We’re doing our best to mitigate the huge increases that are being passed to us, and we’ve been trying to shield our customers from the increases, but the situation has become unsustainable,” current Apple CEO Tim Cook told the Wall Street Journal.

OK, so prices are going to go up. But how?

If Apple must raise prices, the way it does so matters. Will it increase prices across the board, or choose a subtle, strategic approach that protects margins while also maintaining rapidly accelerating market share growth?

Until now, Apple has been benefiting from the rising tide in memory prices. While competitors have been steadily increasing prices across the board, Apple introduced its first $599 laptop even as it eats into mid-range smartphone sales. 

To grow, or to grow less?

The PC industry is not growing (outside of Cupertino), and Apple and its investors already know that the inordinately high customer satisfaction ratings its platforms enjoy mean that when people switch to them they tend to stick around. That’s why it matters that Cook highlighted record switchers and first-time platform users during the company’s most recent fiscal call. Apple is growing new customers, people who are likely to sign-up for services, accessories, and future upgrades. Winning the customer is an investment in future performance.

When it comes to increasing prices, we’ve seen some gentle experimentation in the Mac mini line, where the entry-level $599 model was effectively replaced by a more expensive $799 SKU. There have been suggestions Apple could do the same with the $599 MacBook Neo, dumping the entry-level build in favor of the (better) $699 model. I’m not certain that’s the best approach. 

A matter of choice

I’d argue that the $599 price point is psychologically the best bit of marketing Apple has ever done as it draws new users to look at its platforms. I also think substantial numbers of people already shift up to the $699 version, if they can, making that entry-level price an incredibly effective marketing tool with which to woo customers. It looks like that approach is working; the MacBook Neo has led the Amazon Laptop Sales chart ever since it was introduced and is selling in huge quantities globally.

Francisco Jeronimo, IDC vice president for data and analytics, sees this, writing: “It will be interesting to see whether Apple raises prices across its entire portfolio or plays strategically by subsidizing its more affordable products to gain market share and grow its installed base.”

If Apple raises prices at the price sensitive, entry-level end of its market, it runs the risk of slowing its own resurgence. Given that a 10% price hike here is only worth around $60, the revenue generated might not justify blunting Apple’s offer to new users.

Pricing and strategy

But Apple isn’t defined by its entry-level markets. Its biggest earning opportunities continue to be generated by the aspirational middle class, who, while feeling the pinch of declining living standards in many markets, can still handle the price of a top-of-the-range iPhone Pro. A 10% price increase at that end of the market will generate a much more significant chunk of revenue – and since rival vendors are raising their prices at this end of the market, Apple can follow suit while still seeming affordable. It’s an approach that maintains growth while optimizing margins.

Apple generates roughly half its revenue from iPhone sales, with the Pro and Pro Max devices accounting for a significant chunk of that money. Consumers looking to buy one of Apple’s high-end devices are likely to be less price-sensitive than those making purchases at the low- and mid-points of the company’s market range. 

With that in mind, it makes more sense for the company to raise prices at the top, while working to maintain the cost of entry at the lower end. It could, of course, raise prices universally, but doing so makes less sense.

What next?

Whatever strategy Apple adopts, company leadership is clear that component pricing is hitting hard. “We definitely need memory pricing and supply to return to reasonable levels for consumer products. That’s the bottom line,” Cook said.

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Apple Silicon Macs fail at less than half the rate of Intel Macs, dramatically reducing the platform’s already industry-leading total cost of ownership (TCO), according to data revealed by London, UK-based Apple reseller Hoxton Macs.

While it’s true the data is based on a relatively small sample group, it does seem to reflect what the industry in general sees.

Apple’s chip design transforms Mac reliability

The success of Apple Silicon hardware is attributed to its simpler design, which integrates multiple components into a single chip, reducing the number of potential failure points. Additionally, Apple Silicon Macs run cooler, leading to less wear and tear on components such as batteries and USB-C ports, the report says. Across the wider laptop market, most studies show hardware faults affect one in five non-Apple machines over their first three years in use.

This builds on Apple’s enduring record for making good hardware as independent reliability surveys consistently rank the company as the most reliable laptop brand. To some extent, the data reflects the anecdotal experience most Mac users have — their computers seem to last much longer than other systems do, which helps them retain value on the second-user market.

Apple already had a good story to tell in terms of tech support before it introduced Apple Silicon machines. More than a decade ago, Fletcher Previn, then vice president of Workplace-as-a-Service at IBM, told the Jamf Nation User Conference that just 5% of IBM’s Mac-using employees needed to call the help desk; in contrast, an astonishing 40% of PC-using staff had to do so. That difference is significant because it translates into serious differences in cost; each tech support call made by those working on your ailing PC fleet has a price.

That TCO difference prompted Previn to say, “I can confidently say every Mac that we buy is making and saving IBM money.” Years later, as CIO at Cisco, he said the company’s tens of thousands of Mac users experienced five times fewer cyberthreats and nine times fewer virus issues than PCs, and that Cisco needed 33% fewer engineers to manage the Macs.

Those impressive real-world data points reflected Macs in the pre-Apple Silicon world. Those Intel Macs already worked better for longer and required less tech support. This month’s Hoxton Macs data, while based on a much smaller sample group, suggests that this particular advantage has grown even greater now. And it’s not just down to the silicon.

Fewer parts, less heat, fewer failures

Apple has designed its processors to deliver excellent performance per watt. Because these are SoCs (System on Chips) the power requirement to drive all the system components is that much lower, and it means whole categories of component failure are removed. The design also means they use less energy and generate less heat to run, dramatically reducing thermal wear and tear. 

“Fewer parts, less heat, simpler construction: the result is a machine with markedly fewer ways to break,” Hoxton Mac said in an extensive article explaining its data.

>Failure rates are consequential to everyone. Even a small failure rate means some people will end up with Macs that have hardware issues, which is always a problem for those affected. But the low fail rate should be reassuring to the millions of people switching to Apple’s  href="https://www.computerworld.com/article/4180406/after-a-quick-1-1m-sales-macbook-neo-set-to-reshape-the-pc-industry.html">even cooler-running MacBook Neos>. 

Those users might now justifiably look forward to lower running costs from their new computers, combined with good resale rates once they’re ready to upgrade. It doesn’t hurt Apple’s platform loyalty either — making it even more likely those millions of users will stay with the Mac rather than going back to where they were before.

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Google has released new tools that allow developers to run agentic AI workflows locally using Gemma 4 12B, a 12-billion-parameter model from Google DeepMind.

In a blog post, the company said the model, combined with the Google AI Edge stack, can be used to build and test applications on everyday machines. The model-runtime combination supports capabilities such as autonomous data processing, visual insight generation, webpage creation, and tool use.

The release includes Google AI Edge Gallery for macOS, where developers can use Gemma 4 12B to generate and run scripts for tasks such as data analysis. Google also said its Eloquent voice dictation and editing app now runs fully on-device on macOS, with support for local transcription and voice-driven text editing.

Google has also expanded LiteRT-LM, its lightweight command-line tool for running language models locally, with a new serve command. The company said this allows the CLI to act as a local LLM server and lets developers connect Gemma 4 12B to standard tools, SDKs, and frameworks through a local endpoint.

“Your data stays on your device while maintaining reliable responsiveness, utility, and cost efficiency,” the company said in the blog post.

The announcement comes as enterprises are looking beyond large, general-purpose models for some AI workloads. Gartner predicted that by 2027, organizations will use small, task-specific AI models at least three times more than general-purpose large language models, citing demand for more contextualized and cost-effective AI systems.

Challenges to overcome

But running agents on employee devices brings a number of problems. Companies must work within the limits of endpoint hardware, which can restrict the size of models that run effectively and the number of model instances that can operate at one time.

“While the AI can now fit on a laptop, enterprise IT infrastructure is largely unprepared to manage it,” said Rishi Padhi, principal analyst at Gartner. “Even highly optimized models like the Gemma 4 12B require around 16GB of unified memory or VRAM to run alongside standard applications. Many standard-issue enterprise laptops lack the memory bandwidth and NPUs/GPUs required for fluid, multi-turn agentic execution.”

Anand Joshi, AI analyst at TechInsights, said local deployment also changes the nature of the workloads. On a PC, search may mean finding information across internal folders and files. In a data center, the same function could involve searching the internet or querying a large database such as SQL.

“The framework for local deployment of agentic AI is different from that of a data center,” Joshi said. “The models are smaller; you can run only one instance of a large model at a time. You are limited by memory, CPU, and so on.”

Security and governance are also likely to become bigger concerns as AI agents move closer to enterprise endpoints. Agentic AI is designed to take actions, creating new security risks when local models are given access to employee files or allowed to interact directly with applications and scripts.

“Sandboxing these agents without breaking their utility is still a major operational challenge,” Padhi added. “And all this while enterprises need to audit AI usage for compliance and security. When inference happens entirely offline, capturing logs, tracking model drift, and ensuring employees are using the approved, compliant ways for a model becomes incredibly difficult.”

The cost tradeoff

Running AI agents locally could reduce some cloud inference costs, but the savings may be offset in the near term by higher spending on endpoint hardware and management.

“First and foremost, it is an OpEx-to-CapEx shift, as it shifts that financial burden by forcing accelerated hardware refresh cycles for premium PCs or edge devices,” Padhi said. “It would require buying expensive, high-memory laptops for employees at a time when memflation in the hardware industry is already driving up end-user average selling prices for laptops.”

Many enterprises refreshed PCs in 2025 to support Windows 11, but at that point, most AI inference still ran in the cloud, and the case for on-device AI remained unclear, Padhi said.

Enterprises may therefore move cautiously, buying AI-capable PCs only where local inference has a clear business case.

Over time, however, on-device AI could make enterprise AI spending more predictable by reducing exposure to variable cloud inference bills. The tradeoff is that companies may face a higher baseline cost for equipping and managing employees’ devices.

Complementing cloud AI

For enterprises, local AI is unlikely to replace cloud-based AI outright. Analysts said local AI is more likely to be used for workloads that benefit from endpoint processing, especially when applications must operate offline or when privacy and response times are critical.

“For local agentic AI to proliferate, the use cases on edge will have to complement data center/cloud use cases,” Joshi said. “I don’t expect local agentic AI to replace cloud AI, but it has potential to take a slice away from the cloud, and models like Gemma are significant steps towards enabling that.”

The market, Joshi added, is still determining where local AI fits best. “I estimate that use cases that require privacy or have strict latency needs will move to local node first, with further migration of others in the next 2-3 years,” he said.

Padhi said model placement will depend on the privacy requirements of a workload, the computing power it needs, and where the relevant data resides. Tasks such as code generation or analysis of local files could increasingly run on employee devices, while enterprise-wide RAG systems and more complex AI workflows are likely to remain cloud-based.

The article originally appeared on InfoWorld.

Apple’s MacBook Neo appears to be a triumph of strategic disruption that has already cast shock waves across the industry — and that energy is still playing out.

Approximately 55,000 MacBook Neo computers have been sold every day since it was introduced in March, according to IDC data (as first noted by TechCrunch). In fact, it looks as if Apple sold 1.1 million of these Macs in the first 20 days of sale, the analysts said.

There’s no real reason to imagine that level of demand has declined very much.

MacBook Neo: Millions sold

After all, not only do these Macs continue to dominate Amazon’s US laptop charts, but supply chain rumors claim Apple has doubled its manufacturing orders. “MacBook Neo shipments have come in better than expected, with the 2026 shipment forecast raised from 5 million to 10 million units,” Apple analyst Ming-Chi Kuo said recently. 

IDC’s March data may not capture the larger extent of the demand, as IDC analyst Navkendar Singh pointed out that MacBook Neo shipments “began to spike from early April”, which suggests demand has accelerated since then.

MacBook Neo demand exceeded expectations across multiple nations, including in India, where the company shifted 18,000 of them in the opening weeks.

Doing the business

Apple has also instructed processor maker TSMC to manufacture additional A18 processors specifically for its affordable laptop, while earlier speculation has claimed the company has been using ongoing memory price increases as a strategic competitive tool.  (The Neo starts at $599, with a pricier model set at $699.)

By expanding the potential customer base for Macs with a lower cost Neo, Apple is aiming a claim at the biggest-selling part of the PC market. And it is doing so even as rapidly increasing component prices force others to choose between higher product prices and profitability, or much-reduced margins in to compete at the same price. levels

That’s a losing battle; competitors for the most part can’t hope to match Apple’s bargaining position when it comes to the cost of components like memory because they don’t have the same scale. That means that even when component costs increase for everybody, Apple pays less, because it orders more. 

That scale means that for many component suppliers, it’s Apple’s business that keeps the meat on the table while other customers merely contribute the gravy. So, suppliers are happy to make deals with Apple to secure that main course — to continue the analogy — but are less likely to match those deals for dessert. As such, Apple is expected to be the only laptop vendor to see growth this year.

Apple’s great game

IDC’s figures confirm Apple’s strategy is working, with strong demand for the Neo, and, indeed, all Apple’s new laptops. At the same time, the researcher predicts overall global PC shipments will decline 11.3% this year, with a painful 20% sales drop envisioned for Q4. 

“We’re not seeing any relief to the memory shortage situation before the end of 2027, which means prices will continue to rise and PC manufacturers will struggle to maintain full product portfolios for the foreseeable future,” Jean Philippe Bouchard, vice president of devices and consumers at IDC said in a statement.

“The introduction of the MacBook Neo is putting real pressure on the entire PC ecosystem,” added Jitesh Ubrani, research manager for IDC’s Consumer Devices Trackers. 

Competitors are already responding with new devices equipped with ARM-based processors and aggressive promotional pricing. But none truly match what Apple has with MacBook Neo, and all must reach profitable scale to compete long-term. 

None have yet done so.

The strategy makes sense

“The MacBook Neo launch stands out as one of Apple’s most strategically important recent Mac releases,” Counterpoint analyst David Naranjo said. 

Apple is directly targeting customers that previously saw its products as too expensive. That allows it is also to aggressively build business in parts of the market such as education that tend to be more resilient to economic headwinds. MacBook Neo is also enjoying strong demand across the enterprise.

Both these parts of the market give Apple’s competitors their lunch. “The competitive pressure from the Neo is providing a partial offset to broader price increases, keeping some low-cost notebook options alive,” Ubrani said. “But the overall trajectory for average selling prices (ASPs) is firmly upward. IDC forecasts ASP growth of 17% in 2026, and even as memory capacity expands over the next two years, pricing is unlikely to return to 2025 levels.” 

Apple’s control over its processors, along with its strategic approach to component purchasing, means it should be able to maintain its existing Mac price points for a while. “Apple’s vertical integration (own silicon, own OS) gives it more levers than competitors reliant on third-party chips and Microsoft licensing,” Hexnode CEO Apu Pavithran told me recently.

So, while PC makers either exit the market or raise prices in pursuit of profits, MacBook Neo will continue racing off the shelves, particularly to large enterprise and education customers. 

The endgame? 

The Neo is more than a lower-cost Apple notebook. It’s a hugely disruptive product that is already driving noteworthy change across the PC industry; it’s forcing competitors to make difficult choices between cost and price — even as they grapple with the existential challenges of memory shortages, component price hikes, and raw materials costs. 

That’s not bad for a product that costs your local school just $499.

Just a reminder: the original $399 iPod cost only slightly less when it was first introduced, before subsequently disrupting the music industry.

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Apple surprised everyone with the power and performance of the M1 MacBook Air when it launched the laptop in late 2020. And more than five years later, those Macs show no sign of slowing down, handling everything users care to throw at them.

The Mac still boots almost instantly, races through daily tasks, offers battery life that puts even some newer Windows laptops to shame and, perhaps most importantly, still gives millions of users no compelling reason to upgrade. 

Why the MacBook Air is still going strong

The M1 wasn’t merely better than the Intel Macs it replaced. It delivered a dramatic step forward. Silent, fast, and with remarkable energy efficiency, these laptops have proved themselves to be more reliable and longer-lasting than almost any other notebook.

Apple has continued to deliver impressive improvements ever since the M1 Macs first appeared. The recently introduced M5 MacBook Air delivers double the multi-core and 50% better single-core performance than M1; that means it provides similar performance to the MacBook Pro of around three years ago. 

Apple Silicon has improved every single year and is now extremely powerful — so much so that Apple is about to sell 10 million units of the A-series MacBook Neo, a $599 machine with an iPhone-derived chip that delivers more performance than many mainstream users need.

Meanwhile, even when using a nearly-six-year-old MacBook Air, you still experience a fast browser, responsive Office apps, great battery life and powerful photo editing capabilities. 

To the Moon and back

At the high end of Apple’s range, you’ll find Macs so accomplished they can handle almost every imaginable professional task. It means that right now, today, Apple’s product range extends from good enough to simply amazing. 

Despite heavy marketing hype from competitors who boast of their own ARM-based competitors in similar price brackets, those PCs remain compromised in comparison, if only by their use of Windows, build quality, and overall higher running costs.

Think about it: All things being equal, if you gave a typical office worker an M1 MacBook Air and an M5 MacBook Air and asked them which models they were using, how long would it take them to figure it out? 

Sure, a highly experienced Mac user would likely know. But for a lot of people, the difference would be hard to spot because what they do on their computers just isn’t particularly demanding. 

Making people happy is good for business

Surely that’s bad for Apple’s business, right? I think not. It means Apple has created a huge population of happy Mac users who are still having a good time with the Mac they acquired in 2020. Those people tell other people about their experience, which helps evangelize the platform and can’t have hurt MacBook Neo sales this year. 

They also become more interested in other Apple products, which they can afford to invest in instead of investing in the standard PC “upgrade’”cycle. After all, if you have a platform that doesn’t need an upgrade every three years, you can spend your money on something else instead. For consumers, that might be AirPods and Apple services, while for enterprise professionals that investment might become an iPad or iPhone Pro. 

Apple doesn’t mind. It still makes bank.

The company generally finds that giving people what they want is good for business. It boosts customer satisfaction scores, reduces maintenance costs, and builds repeat customers.

That long replacement cycle delivers a second benefit, too. Apple talks extensively about sustainability. With the M-series Macs, it has achieved it. 

Sustainable technology

People use these laptops longer and get more value later when they sell them on. And when they eventually get returned for recycling, Apple can tear the machines down for parts as it works toward establishing circular manufacturing within the next four years.

The M1 MacBook Air might eventually be remembered not just as the first Apple Silicon Mac, but as representing the moment when ordinary people didn’t have to worry about performance anymore. That’s why the product refuses to die — not because it’s immortal, but because for millions of users it still does everything they need. And all the M- and A-series Macs that follow it do exactly the same thing.

One more thing, however: Intel Macs will no longer be supported by macOS 27 when it ships this year. Apple typically ends support for products around 6-7 years after it removes them from sale, so when will it end support for the M1? Potentially, not too soon.

Apple only stopped selling the M1 MacBook Air in 2024, which suggests support could continue until 2030 or 2031. So, if you bought an M1 MacBook Air in 2020, you’ve actually invested in something designed to work for you for a decade. Which PCs can truly deliver that?

No wonder the M1 MacBook Air refuses to die.

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Intel is invading the physical AI space with a reentry into the robotics market it quit many years ago amid financial struggles.

The robotics strategy is part of the company’s larger plan to establish AI on the “edge,” in which devices have the computing capability to run AI locally. Many devices lack AI capabilities and have to offload processing to the cloud.

The chipmaker said its Intel Series 3 processors are now in 130 edge AI and robotics designs. It also had a design win with SensoryAI, which provides technology for robots that include Ella, a robotic barista made by Crown Digital.

The company’s Core Ultra Series 3 processors are derivatives of chip designs intended for laptops. But Intel has achieved a level of power efficiency for long battery life that allows those chips to be adapted for handheld devices and laptops.

Intel also said it can build advanced robotics chips thanks to its latest manufacturing technologies.

For example, many robotic functions, such as computer vision and real-time controls, can be integrated into a single chip. Previously, functions like graphics and movement and control were distributed among different cores in a chip.

SensoryAI, for example, has a chip architecture that provides the robotic barista — which is more like a robotic arm — with AI capabilities, Intel said.

The main “Avatar” agent handles customers as the main “Ella” agent reasons and executes the task. If Ella encounters errors, it passes on the issue to a Guardian agent, which helps with the recovery. Some issues could include making sense of an order, or cups that might be stuck. 

The three agents are embedded in a single piece of Core Ultra Series 3 silicon.

Intel is displaying some of those robots at the Computex trade show in Taiwan. The company shared a video of a humanoid-style robot from the floor in a X.com post  

This is not Intel’s first attempt at the robotics market. Intel sold robotics chips and kits when it was a dominant chip player in the field, but curtailed efforts in 2021 after Pat Gelsinger took over as CEO and restructured the company to focus on manufacturing.

Robotics is now back on the menu under new Intel CEO Lip-Bu Tan, who replaced Gelsinger last year. He has restructured to company to focus on high-growth areas that can generate high returns.

A Morgan Stanley study last year indicated the robotics market could be worth $5 trillion by 2050 — and more than 1 billion humanoid robots could be in operation. 

Robots are seen to improve human productivity and manufacturing output. For example, they could help factories that are facing labor shortages or be used to complete tasks that are dangerous. 

However, challenges remain. There isn’t yet enough real-world data to train robots to do targeted work. And the AI models — generally called world models — they will need are still under development. 

Training robots to do a specific job requires a sequence of events to happen in succession without any errors. Companies are still training robots to spot and understand errors, analyze possible resolutions, and take the right corrective action.