On April 4, 1975, Bill Gates and Paul Allen founded Microsoft, a software company destined to become a tech behemoth (and key Apple frenemy).
Perhaps the most interesting thing about Microsoft and Apple is just how similar the companies were in several ways. Gates and Steve Jobs, the CEOs who came to represent the two companies, were both born in 1955. Both later dropped out of college.
Gates and Allen created Microsoft when they saw a gap in the market following the launch of the Altair 8800 kit computer. In Silicon Valley, the Altair inspired the creation of the Homebrew Computer Club, where Jobs and Steve Wozniak first showed off the Apple-1 computer.
Much more was said of Jobs' departure signaling the end of Apple than of Gates' departure signaling the end of Microsoft. And much more was celebrated of Apple 50 than Microsoft 50. Why is that?
In the case of both Microsoft and Apple, we have seen successful transitions from founders to successor managers that not only preserved but broadly expanded the companies. Cook, Ballmer and Nadella outdid their predecessors as measured by every metric of financial performance. They both reached the pinnacle of business success as measured by market capitalization.
It's romantic to think that business are embodiment of people but in reality they are the seemingly sterile combination of resources, processes and priorities. These are heavily influenced by the people who assemble or define them but ultimately the processes must outlast biology or we are doomed to have to re-invent everything.
Put another way, if a founder builds something that does not outlast him then what has he really accomplished?
Ben Thompson of the Stratechery interviews Horace on the Stratechery Plus Podcast to discuss Horace's journey to become an influential tech analyst: early career in research, business school under Clayton Christensen, and his time at Nokia during the rise of the iPhone.
The conversation further explores Disruption Theory in the context of both smartphones and AI, why Christensen misjudged Apple, and whether AI could challenge today’s tech giants. It also marks the launch of Dediu’s new paid service Asymco One and reflects his continued conviction in Apple Inc. at its 50-year milestone.
A new analysis of computers used in the enterprise finds that Macs and iPhones last much longer and have far fewer problems.
Macs in enterprise settings typically last for five years, besting the three-year lifespan for Windows PCs, according to a company that makes software to help businesses manage their computers.
But the really shocking revelation from the report is that more than half of Windows PCs used in big business get replaced within a year.
While factors like software compatibility, IT familiarity and customization options also play a role, upfront hardware cost remains the biggest driver for most organizations.
By comparison, Macs are often seen as premium products, which can make them harder to justify at scale (although the recently released $599 MacBook Neo is changing that equation).
Companies making these sorts of computer buying decisions should pay attention to a new report from Omnissa.
“Compared to Windows, 6.5x more Macs are seen in service into year 6, and 3.3x more Macs are seen in service into year 3+,” noted Omnissa’s report.
“Only 17% of macOS devices were replaced within one year, compared to 54% of Windows devices, reducing disruption tied to frequent hardware replacement,” said the analysis.
Macs are far less likely to crash. The benefits of using Apple computers don’t stop at longevity, though. Employees using Macs also run into far fewer bugs.
“The telemetry reveals that Windows devices exhibit 3.1x more total forced shutdowns (including system crashes and unexpected restarts) than macOS devices,” said Omnissa. “Windows devices experience 2.2x more app crashes and a staggering 7.5x more app hangs (unresponsive software states) than Macs.”
“A forced shutdown is much more than an IT support ticket — it’s a disruption to an employee’s work that translates directly into lost work hours,” said Omnissa.
Apple’s lifespan advantage extends to iPhones as well. When compared to Android handsets, “the data suggests that iOS devices display longer service life, with twice as many devices in service into year 6,” said Omnissa.
“iOS is updated 8.1 times faster than Android,” said Omnissa. “macOS is updated 1.5 times faster than Windows.”
The long-term cost benefits of using macOS or iOS in the enterprise are starting to overcome companies’ habit of making buying decisions based on short-term savings.
Explore how Apple’s C1X modem performs in the real world, with Ookla Speedtest data from Q4 2025 showing the iPhone Air matching Qualcomm’s X80 download speeds while setting new latency benchmarks.
iPhone Air marginalizes competing slim form-factors. The iPhone Air has largely eclipsed the Samsung Galaxy S25 Edge globally, out-sampling it 3-to-1 in the U.S. based on Speedtest data, while the Edge remains statistically negligible in terms of adoption across European markets. South Korea remains the primary competitive exception, driven by strong home-market bias.
In 2024, the iPhone 16 Plus was the clear laggard of the range, capturing a mere 2.9% of the launch mix. By sunsetting the iPhone Plus and replacing it with the design-centric iPhone Air, Apple more than doubled the share of this roster slot to 6.8%. This suggests that “Slim” as a category successfully resonates with a segment of the market that “Large” simply did not.
Apple’s newest hardware cycle centered on a key question: could Apple’s first high-performance modem, the C1X, improve upon the original C1? Furthermore, could it match the industry-standard Qualcomm X80, without the thermal headroom of a “Pro” chassis. Despite its slim form-factor, the iPhone Air does include a vapor chamber to aid cooling, while its titanium frame also aids heat dispersion. Qualcomm remains a formidable incumbent with its X85 modem, which alongside MediaTek’s M90, will feature in newer Android flagship devices this year. Based on comparisons with the X80, our data suggests that Apple’s silicon has reached a critical maturity point, shifting the conversation from a performance gap to a strategic “equalizer” in real-world performance.
Apple TV completes 19 years since its launch, as reports suggest a new model may arrive soon. Apple introduced the original Apple TV in January 2007, and released it in March the same year. The device marked Apple’s early step into home entertainment.
NB: The product was always misunderstood. Judged as a product, Apple TV was always without traction. Never seen as a hit, often ignored. The problem has always been with the assumption that Apple was a "product company" or a "design/marketing company" or the "Mac | iPod | iPhone company". The hint is in the observation of the name Apple TV being both a product and a service. From a hardware point of view, the Apple TV is almost a Mac Mini, but with an A-series chipset and a funny input device. It was also priced so low that it probably had minimal margins. But that was never the point. Apple TV hardware ended up being the "brains" of the TV itself and the "set-top box" and the gateway to all content on the screen. Quite an achievement for a flop.
Data-center AI model on MacBook: Why it matters for Apple
The implications for Apple’s competitive position in AI are significant. The dominant narrative that Apple is behind — that Siri is a joke compared to ChatGPT, that Apple Intelligence is underwhelming, that the company missed the generative AI wave — could be misleading. Woods’s experiment suggests Apple may have quietly built the right hardware all along.
Apple silicon’s unified memory architecture lets CPU and GPU share the same high-bandwidth memory pool. And that looks like precisely the design needed for the flash-streaming technique Apple’s own researchers described. No other mainstream laptop platform has this. So MacBook Pro isn’t just a laptop that can run AI on the side. It may be the most capable personal AI computer on the market.
While competitors race to build billion-dollar data centers, the most powerful AI model you can run might soon be the one already sitting in your bag. Apple’s chip lead, combined with techniques like these, could make local AI on Mac — private, fast and free from cloud subscriptions — a genuine reality far sooner than anyone expected.
As Willison noted, the quality tradeoffs are still being evaluated. But we can’t overstate the breakthrough in simply getting it running. The AI race might not be won in a data center after all.
(via Cult of Mac - Your source for the latest Apple news, rumors, analysis, reviews, how-tos and deals.)
In a bold departure from its Big Tech peers, Apple sidestepped the $650 billion AI infrastructure spending frenzy. While Amazon, Google, Microsoft, and Meta funneled cash into data centers, bleeding cash flow and adding debt, Apple maintained a consistent $14 billion capital budget. This strategic choice reflects Apple’s belief that AI models are rapidly commoditizing, as evidenced by DeepSeek’s $6 million model rivaling $100 million counterparts. Instead of building proprietary models, Apple licensed Google’s Gemini, reserving the option to switch vendors as superior models emerge.
Apple’s genius lies in leveraging its ecosystem—2 billion devices transforming into a distributed AI powerhouse. Apple silicon on device enables local AI processing, bypassing the need for colossal server farms. This approach not only conserves capital but also amplifies customer loyalty, as Apple uniquely protects privacy. Ultimately, Apple bets on owning the customer experience, positioning itself to thrive regardless of infrastructure ownership. →
Apple's recent product launches, including the 17e and MacBook Neo, have sparked speculation about a strategic shift towards low-end markets. However, this view overlooks Apple's fundamental approach to market segmentation, which eschews simplistic price categorizations. Instead, Apple focuses on the "job-to-be-done," understanding that consumer purchases are driven by desired outcomes rather than affordability alone. This perspective reveals that performance and quality are crucial, transcending income levels. For instance, affluent individuals may opt for simpler devices, while budget-conscious consumers might invest in high-performance tools to meet specific needs, like content creation.
Historically, Apple has aimed to deliver superior experiences to a broad audience, refusing to compromise on quality with budget-friendly products like Chromebooks. While cost can limit access, as seen with the Vision Pro, Apple prioritizes profitability as a validation of its value proposition. The MacBook Neo exemplifies this ethos, leveraging efficient mobile chipsets to redefine laptop capabilities at a competitive price point. This innovation blurs the lines between mobile and traditional computing, underscoring Apple's commitment to crafting products tailored to diverse tasks. Ultimately, Apple's strategic depth, powered by Silicon advancements, positions it to serve an expansive global market by addressing a wide array of functional needs. →
Nota Bene
Rosenblatt Lifts Price Target on Apple by $1, Maintains Netural Rating → On March 5, Rosenblatt's Barton Crockett slightly raised Apple's price target to $268 while maintaining a Neutral stance, optimistic about Apple's budget product launches and steady high-end performance, despite trading at a modest premium compared to peers, as analysts foresee robust revenue growth for FY2026. →
How many employees does Apple have? What do they do? → Apple, despite its marketing reputation, is fundamentally an engineering powerhouse with nearly half its workforce dedicated to engineering roles, driving its substantial revenue growth and global employment expansion. →
First footage of X-Plane 12 on Vision Pro → X-Plane 12 on Apple Vision Pro leverages ARKit to seamlessly integrate physical controls into a mixed reality flight simulation streamed from a Mac, showcasing advanced professional-grade AR capabilities. →
iPhone production in India increases by 53% in 2025 → Apple's strategic shift to ramp up iPhone production in India by 53% last year, aiming not just to sidestep tariffs but to cultivate a vast new customer base, underscores a long-term vision mirroring its successful penetration of the Chinese market. →
The 3rd? most valuable company on Earth watched as its rivals lit $650 billion on fire and did nothing. The biggest cash bonfire in history, by far, eagerly fed by all the usual suspects but one.
It's either the dumbest or the most brilliant move in corporate history.
Apple used to be the biggest capex spender, mainly because it paid for most of the property plant and equipment in the factories that made its phones and computers. The so-called tooling or equipment spending plus its leased store renovations and some data centers were costs no other tech giants had and so Apple was an outlier. It was, as I wrote at the time, equivalent to buying a few aircraft carriers every year.
But that all changed with AI. Amazon is spending $200 billion this year on AI data centers. Google, $185 billion. Microsoft, $114 billion. Meta, $135 billion. Combined: $650 billion. [Not including OpenAI, Anthropic and SpaceX/XAI.] That is like buying the US Navy every year. And yet Apple's capital budget is still a modest $14 billion, oscillating with new hardware tooling cycles.
Apple is refusing to transfer its cash flow to Nvidia. Curiously, it believes that its cash flow belongs to its shareholders, not to Nvidia's.
The hyperscalers are now spending 94% of their operating cash flows on AI infrastructure. Amazon is projected to go negative free cash flow this year with as much as $28 billion in the red. Alphabet's free cash flow is expected to collapse 90% from $73 billion to $8 billion. These companies used to be the greatest cash machines ever built. Now they're borrowing money to keep the data center lights on.
The Big Five raised $121 billion in bonds in 2025 alone. Morgan Stanley projects $1.5 trillion in tech debt over the coming years. For the first time in history, hyperscalers hold more debt than cash. Perhaps this is why their P/E ratios slumped from mid thirties to mid twenties.
And what are they getting for that $650 billion? AI services generate roughly $35 billion in total revenue or 5% of what's being spent on infrastructure. There are dreams of more of course, but the business models of AI have yet to resonate, especially for consumers.
Now here is where Apple's bet becomes genius. AI models are commoditizing faster than anyone predicted. Software and hardware both have tendencies to commodify. Protections exist but they have to do with integration and distribution. DeepSeek built a model for $6 million that matches systems costing $100 million. Open source models now power 80% of startups seeking VC funding. The moat these companies are spending hundreds of billions to build is evaporating.
Apple understood this before anyone else. It didn't build its own AI model, it licensed Google's Gemini for about $1 billion a year. Why spend $100 billion building a factory when outsourcing costs a billion? And if a better model appears next year, Apple just switches vendors.
But Apple is not sitting still. It just dropped the M5 chip with a 16 core Neural Engine and Neural Accelerators built into every GPU core. It runs 70 billion parameter AI models locally, eventually even on your phone. The M5 delivers 4x the AI performance of the M4 and Apple doesn't need $200 billion in data centers.
Because Apple turned 2 billion devices into the data center. Every iPhone, Mac, iPad gets distributed AI at a scale no server farm can match. While its rivals burn cash, Apple is doing the opposite. $90.7 billion in stock buybacks last fiscal year. Its competitors? Combined buybacks collapsed 74% from their peak.
Apple didn't miss the AI revolution. It just bet that the winners won't be the ones who build the infrastructure. They'll be the ones who own the customer and no one else on Earth owns the best customers.
Wedbush analyst Dan Ives believes the launch lineup could help drive the next upgrade cycle for Apple, with the firm maintaining a $350 price target, implying roughly 33% upside from current levels.
According to Ives, the chips deliver over four times the peak GPU compute for AI compared with M4, alongside roughly 35% stronger graphics performance.
Apple paired the silicon with a refreshed Mac lineup, including new MacBook Air and MacBook Pro models, alongside a surprise entry: the MacBook Neo.
Ives believes the lineup could broaden the Mac base further, noting nearly half of Mac buyers remain new to the platform, leaving room for incremental growth.
Apple also introduced the iPhone 17e, powered by the A19 chip, designed to run generative AI models more efficiently.
For Ives, the takeaway is simple: Apple's expanding lineup of AI-enabled devices could set the stage for the next major hardware cycle — and potentially push the stock toward its $350 target.
Are Apple and Google competitors or are they partners?
Prior to the launch of the Android operating system, Apple and Google collaborated on many projects. Google Search was predominant on Apple products including the (at the time) new iPhone. The iPhone also launched with support for Gmail and had native Google Maps and even YouTube. Google was a cornerstone supplier for the new smartphone.
After the launch of Android only a year later, the relationship changed. The two companies came to be viewed as mortal enemies. The perception that Android was disruptive to Apple—insofar as it undercut the pricing power of the new touch-based user experience—was universal. The "zero price" of Android and its licensing by all other phone makers suggested a competitive collapse was imminent for the fledgling iPhone. Android phones were far cheaper and "good enough." If not immediately, then with the resources of all phone makers and Google itself, Android would surely soon overtake the iPhone in performance along all dimensions. It took a great deal of courage to argue otherwise.
But, over time, the notion that the iPhone would continue to exist became more widely held. Holding on to a "premium" positioning, iPhone seemed to be have pulled a rabbit out of a hat, perhaps because of Steve Jobs' reality distortion field or because of magical marketing. Nonetheless, doubts over long-term growth persisted.
Having survived Android, Apple was still seen as vulnerable to a multitude of Google initiatives including Chrome and Chromebooks, a range of Google Pixel phones (enabled by the acquisition of Motorola and HTC.) The entry of Google wearables (enabled by the acquisition of Fitbit), Glasses, the Play Store, YouTube content, Google productivity apps, Google cloud, Google TV, Nest, Google Assistant and numerous other services were all cited as nails in the iPhone coffin. This is all before the age of Crypto a new generation of AIs came into fashion.
Throughout this period the iPhone continued to increase its audience, growing its base of users not only from smartphone non-users but also from so-called "switchers", that is, those who moved from Android to iOS. Apple has benefitted from this net positive switching for at least five years now as most of its addressable market has already adopted the smartphone. There are about 1.2 billion iPhone users and it's far more likely that a new iPhone user today arrives from the 3.5 billion Android users than from the 3.2 billion people who don't yet have any smartphone. That is because those who don't yet have a smartphone today are also likely to not yet have access to electricity, cellular networks or money.
Indeed, it is Android that seems to be in a precarious position. The ecosystem is bleeding not just high-end users but also from fragmentation. Chinese OEMs in particular deliver their own experiences and code bases, eschewing Google services altogether. Large OEMs such as Samsung are seeking to differentiate with their own experiences and ecosystems and accessories and chafe against Google's hardware offerings. Upgrade rates to new Android versions are poor. Support of hardware beyond a few years is lacking. But, most fundamentally, Google has not developed a business model that directly fuels development of Android.
Put simply, Android is not a profitable product. It's not designed to create revenues. It's designed to reduce costs.
To understand this, we have to understand Google's business. It's not very complicated. Google's revenues in the last quarter are segmented as follows:
The colors above indicate the major categories. Blues are Advertising, yellow is "Other" and red is Google Cloud. Other Bets, consisting of research projects, is a 0.4% rounding error. Apart from Search which is about 60%, each major category is about 10%. Advertising as a business model is about 78%.
To Alphabet's credit, Advertising as a business model has been reduced from 94% a few years ago. Much of that credit goes to Cloud which is a B2B business and has completely different resources, processes and priorities than Search. The "one trick pony" label is less applicable to Google today.
Search however, and the ancillary properties, are still, by far, the largest sources of revenues and profit. Note that Android itself is missing from this mix apart from Play Store which is a direct Android extension. Play does contribute somewhat as part of "Other" but the OS itself is an enabler across all these categories.
While not directly producing revenues, what Android does is perhaps even more important. It helps reduce the amount Google has to pay to access its customers. Think of Search as a system which takes queries in and puts results out. These results are what advertisers pay for and the queries are what Google pays for. The output depends on the input. That input is harvested from many users. Access to those users is not free. The cost can be paid by building access directly (Android) or by paying for access to someone else's property (Apple, Windows, or Firefox). In old-school business terminology this is called distribution.
Distribution is often ignored or considered a superfluous "middleman" to be bypassed. But distribution is foundational to any business. It is, effectively, other people, outside your company, helping you sell your product because they have access to the customers. They get paid for that access, often with a percent of sales. Stores are distribution. Wholesalers are distribution. Resellers are distribution. Without distribution scale cannot happen. Distributors help both producers and consumers by creating access.
Access is also provided by what we call infrastructure. Just like you can't travel by car from your house to your destination without roads, all access to products and services is effectively infrastructure. If you own the infrastructure then you have to pay to build it and maintain it. If you don't own it you have to pay to use it. All infrastructure has value and all infrastructure has costs.
This all makes more sense when recalling the historic birth of Android. At the time (2006 to 2008) the worry for Google was that Microsoft's mobile operating system (Windows Mobile née Windows CE) would be licensed as was Windows. That is to say that all phone OEMs would take a license for a nominal fee and build Windows Mobile phones. Microsoft would thus dominate the mobile computing market the way it dominated the PC market (with market share above 95%). Microsoft would then ensure that Bing search was the default on all devices running Windows and Windows Mobile, thus blocking access to what was expected to be the next 3 billion users while capturing all search ad dollars ad infinitum.
If Windows Mobile were to dominate, Google would be denied distribution, at any price. It would thus be relegated to, at best, 10% market share of mobile search. This would be an existential crisis.
In this setting, Apple was an ally for Google. Apple was not a search engine provider and was very welcoming of Google search on a nascent Safari browser. Whereas Explorer would block Google search, Safari would offer default placement. Not for free, but for a reasonable cost. Google was a "go-to-market" partner for Apple and it was a symbiotic relationship.
However, the expectation of Google at the time was that Apple would be no more successful with iPhone than it was with the Mac: A fringe of "creative" or "fanboy" quirky oddballs. This was not just Google's expectation. It was everyone's expectation.
Android was built to counter a Microsoft mobile OS monopoly with a "zero cost" option vs. Microsoft's end-user-license model. Microsoft made money selling software. Both system software (Windows) and application software (Office.) Google would give away system software (Android) and services (Gmail and Docs) but make money on advertising.
A genius move. Phone OEMs would much rather pay zero of the OS on their phones than for the non-zero Windows Mobile license. [On a $200 retail cost phone (and thus $90 bill of materials) a $8 OS license is a huge cost.] Google's Android did indeed block Windows Mobile from getting a foothold in the post-PC era.
But it did so by taking some short cuts. Android itself was an acquisition in 2005 (for $50 million, with a keyboard interface) and, in response to the iPhone, a new touch user interface was developed. It so happened that this interface copied as closely iOS as Windows had copied the original Mac. This perceived theft was such an affront to Steve Jobs that he declared war on Google.
It was important to ask (as few did) why did Google need to develop an OS, only to give it away. Was its business that robust if it needed to expend enormous energy and capital to build an enabler? The answer is, of course, distribution.
Google was initially not paying for distribution as most people just typed "google.com" into their browsers. As the URL field became a search field, Google could still expect PC users to make Google.com their search bookmark, one click away.
But on mobile devices, the friction of the constrained interface meant that defaults mattered. Mobile was going to require new distribution economics. Devices were going to be in the hands of many more people, who, since they did not have full-size keyboards, would type less and who would interact in new (and very succinct) ways. One click away was one click too far.
With Android (and Chrome) Google set defaults for its services across the platform. If Android was the OS then Chrome would be the default. If Chrome was the default, then Google Search would be the default. For these Android-sourced queries, Google would not pay for distribution. Or, more precisely, would only pay to build and keep Android. Thus the more Android there was, the cheaper it was to obtain search queries for Google. Google had built its own highways: it owned the infrastructure that connected users to its services. These roads were for Android users. And what about iOS users?
Over a 15 year period the smartphone went from essentially zero to 5 billion users. It became so important to those 5 billion people that they keep it with them every waking moment, use it 100 times for a total of 5 hours each day. That adds up to 182,500,000,000,000 interactions a year and, as a result, it has changed behavior, politics and humanity itself.
Throughout this period, the relationship between Google and Apple changed. From being allies, to mortal enemies to, as we shall see, partners. We have to understand this new relationship that has emerged and its consequences.
The next post will explore the relationship in detail using the lens of the deal structure that exists. A deal which is not public and largely unexamined.
