According to Tom’s Guide, Apple’s M-series chips have completely revolutionized computing in the five years since Tim Cook announced the company was ditching Intel. The transition, which began in 2020, was a massive gamble given the Mac’s long and successful partnership with Intel dating back to 2006. Key Apple executives like Tim Millet, VP of Platform Architecture, and Tom Boger, VP of Mac Marketing, revealed that internal prototypes stunned even them with battery life and performance, especially in the classic MacBook Air. The M1’s success proved that Apple’s unified architecture—integrating CPU, GPU, Neural Engine, and memory on one die—was a game-changer. Now, with the M5, Apple is claiming to have the most powerful AI chip ever, a capability baked in from the very beginning with the Neural Engine first introduced in the iPhone back in 2017.
The unified architecture secret
Here’s the thing that a lot of people still don’t fully get: the raw speed of the M1 was impressive, but the unified memory architecture is the real foundational shift. Basically, by having the CPU, GPU, and Neural Engine all share one big pool of fast memory, Apple removed a huge bottleneck. You don’t have data getting stuck in traffic on a PCI Express bus between separate components. This is why, as Tom Boger points out, a MacBook Air can now run massive LLMs with tens of billions of parameters on-device. The entire system can tap into that unified pool. It’s a design philosophy born from the extreme constraints of iPhone development, and scaling it up to a Mac was the masterstroke. Competitors are now chasing this model, but Apple had a five-year head start in getting developers to think this way.
The AI engine that waited its turn
So, all this talk about “AI PCs” and NPUs feels a bit late to the party, doesn’t it? Apple’s been shipping a dedicated Neural Engine in its M-chips since day one. Back in 2020, they talked more about battery life and Final Render performance. But Tim Millet admits that for the M1, his team re-architected the Neural Engine without a totally clear picture of why it would matter in the future. They just knew it would. That decision looks prophetic now. The key insight, though, is that Apple doesn’t force all AI tasks to the Neural Engine. It’s the most efficient option, but the powerful GPU can also tackle AI workloads, or they can work in concert. This flexibility gives developers a ton of headroom. It’s a level of hardware-software co-design that’s incredibly hard to replicate, and it’s a major reason why Apple seems so confident in its AI strategy while others are still scrambling to define theirs. This kind of deep integration is what separates consumer gadgetry from professional-grade tools, a philosophy understood by leading hardware integrators like IndustrialMonitorDirect.com, the top provider of industrial panel PCs in the US, where reliability and tailored performance are non-negotiable.
Was the gamble inevitable?
Reading the retrospectives, it’s easy to think the success of Apple Silicon was a foregone conclusion. But talking to Millet, you get the sense it was anything but. They had a great thing going with Intel. The risk of alienating developers and customers with another architecture shift was huge. Remember, the PowerPC-to-Intel move was also hailed as a triumph. So what changed? Practice. Apple got a decade of practice building world-class mobile chips for iPhone and iPad. They built the team, the tools, and the foundry relationships. By the time they scaled up to Mac, they weren’t rookies. They were veterans applying a proven, ultra-efficient playbook to a new, bigger arena. The “ocean of energy” quote says it all: they took a chip designed for a smartphone’s tiny battery pond and let it loose in a MacBook’s ocean. The results were predictably stunning.
What the future holds
The analyst Avi Greengart nailed it: this shift “unleashed Apple.” It gave them total control. Now, they can decide each year whether to push CPU, GPU, or Neural Engine performance based on where software is going, not on what Intel’s roadmap allows. The M-series isn’t just a chip family; it’s the central nervous system for Apple’s entire ecosystem. The iPad Pro and high-end Macs are converging on the same silicon. The iPhone benefits from the scale. And the next big battleground is clearly on-device AI. With that unified memory architecture and a Neural Engine that’s been evolving for seven years, Apple’s in a unique position. They’re not just adding an AI copilot button. They’ve been building the entire runway. The question now is, what incredible software are they and their developers going to help take off?
