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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I’ve been using and writing about Microsoft Copilot since it was publicly released in 2023. I’ve reviewed it, written articles about using it more effectively, explained how to curb hallucinations in it and other similar tools, and detailed how to use it in concert with Microsoft 365. It’s also been my go-to generative AI (genAI) tool for personal projects and advice.

But the time has come for me to leave it behind for my personal use. It’s become abundantly clear that for those tasks, Google Gemini is better. Here’s why.

Copilot is inept at solving a tech problem

Like many people who know something about technology, I’m the IT staff for friends and family. I’ve often used Copilot to help solve issues I can’t fix myself. Sometimes Copilot helps. And other times…, well, the last time I turned to it for troubleshooting advice is when I realized it was time to abandon Copilot.

My wife had bought a new iPhone, and I noticed she was receiving texts sent to her email address but hadn’t received any sent to her phone number. I asked Copilot for help.

I won’t go into the details of the wild goose chase Copilot sent me on — I’ll just offer a few lowlights. It first told me, with absolute authority, that there are “only two real explanations” for the problem and asked me to look at several settings to confirm which explanation would fix the issue.

It turned out that neither of the “two real explanations” were the cause. Undeterred, Copilot assured me, again with complete confidence, that it was going to send me “straight to the switch” that would immediately solve the problem.

I tried it. The switch didn’t work. Neither did the “final fix” it promised me. Nor did any of the other many “solutions” if offered after that so-called final fix. For more than an hour, it flailed with utter confidence and utter futility trying to diagnose and fix the problem. 

And then came the final indignity: After doing some digging, I realized Copilot was trying to solve the problem based on an old version of iOS, not the current one on my wife’s phone. When I confronted Copilot about that, it briefly apologized and promised it knew the solution: I had to call the cellphone carrier.

That was it for me. I’d had enough. I turned to Gemini for help. 

Thirty seconds later, Gemini diagnosed the problem and recommended a simple fix, which didn’t require a call to my phone carrier. It worked like a charm. Gemini had solved a tech problem in 30 seconds that Copilot couldn’t resolve after an hour. 

Copilot whiffs on personal research 

I often used Copilot for personal research projects. A recent one involved Parisian neighborhoods in the 1870s. I was looking for information about the area around the Saint-Lazare train station. When I asked Copilot, it told me the area was dangerous and poverty-ridden back then, with poor housing whose exteriors were heavily stained by coal smoke from arriving and departing trains.

That didn’t sit right with me. I recalled a well-known painting Paris Street; Rainy Day by the Impressionist painter Gustave Caillebotte, which depicted the neighborhood in the 1870s as wealthy and fashionable, filled with elegant Hausmann-style apartment buildings. I asked both Gemini and Claude about the neighborhood in the 1870s. They both told me it was expensive, fashionable and sought after by the well-off. I confirmed that with my own follow-up research.

Once again, Copilot had whiffed.

Copilot gives bad scheduling advice

I swim for exercise three or four times a week at my health club’s indoor pool. The club closed the pool for several months, so I decided to swim at the pool of an elementary school a short walk from my house. I hadn’t exercised there before and wanted to find the times on Monday through Friday when the pool would be least crowded. I asked Copilot for help.

As always, Copilot spoke with a solid air of authority. And once again, it was wrong. It told me that the least crowded time for public swimming on weekdays was between 11:30 a.m. and 12:30 p.m. or between 12:00 p.m. and 1:00 p.m.

On one count it was right: the pool would certainly not be crowded with public swimmers at those times. Because the pool doesn’t open to the public until 3 p.m. 

I turned to Gemini, which told me that 3 p.m., when the pool opened, would be the least-crowded time. Claude was no help. It demurred and said it didn’t know the answer – a rare, refreshing admittance of ignorance from a chatbot.

Gemini was on target again — 3 p.m. did indeed turn out to be the least-crowded time to swim. I often get a lane to myself, and at worst have to split a lane with one other swimmer. I asked several lifeguards if 3 p.m. was the least-crowded time on weekdays; they all confirmed it was.

Bye-bye, Copilot

For all those reasons, when it comes to personal research and advice, I’ve abandoned Copilot. I typically use Gemini now, although on occasion, I ask for a second opinion from Claude.

For my Computerworld work, I’ll keep using Copilot, and continue to write reviews of it, offer advice on how to use it and keep you informed about the latest news about it.

But other than that, for my personal use, Copilot is dead to me.