Just look around and you’ll almost certainly find a device nearby that uses a processor based on the same design: smartphones, smart speakers, TV remote controls, coffee machines, car components, industrial automation.
Behind this unassuming community lies Arm : the company rarely appears in consumer advertising, yet its developments determine how billions of gadgets work and how much energy they consume.
The reason Arm is once again in the spotlight more than usual is that the market is clearly preparing for another change.
Qualcomm is pushing ARM processors into Windows laptops, Apple has been raising expectations for speed and battery life with its M-series chips for several years now, and at the same time, sectors are growing where power consumption is becoming almost more important than raw performance : robotics, self-driving cars, and artificial intelligence. Where once the battle was focused on maximum gigahertz and core counts, the decisive question is now increasingly how much processing power can be achieved per watt.
To understand why Arm is having such a significant impact on the industry, it helps to remember what a processor actually does.
It’s essentially a vast system of electronic switches operating in binary logic . Their physical core is made up of transistors : if there’s a signal, we get a “1”; if there’s no signal, we get a “0.” Billions of these switches work together to execute instructions , move data, make simple decisions, and synchronize the entire device. The processor is constantly exchanging data with memory: long-term data resides in storage, working data resides in RAM, and external devices, from sensors to touchscreens, provide input signals that are converted into program actions.
In this context, a key feature of Arm seems surprising: the company doesn’t manufacture chips. Unlike Intel, Arm creates the architectural “manual,” a description of how the processor should be designed and how the software should communicate with it. These designs are shared with partners, and physical production is handled by contract foundries like TSMC . In other words, Arm doesn’t sell silicon, but the intelligence embedded in the design .
This “manual” consists of two levels , often confused with each other. The first level is the microarchitecture : the specific structure of the processor core, the way it executes instructions, the cache, the pipeline, branch prediction, and other details that affect speed and power consumption. This includes, for example, the Cortex core family.
The second layer is the ISA , or instruction set architecture, which is the set of commands the processor understands and the rules by which software interacts with the hardware. It’s important to note that the ISA acts as a stable “contract” between chip designers and software developers, ensuring compatibility across a broad ecosystem.
Then licensing comes into play. Arm doesn’t just distribute “instructions,” it sells the right to use them in its products. A partner can take an existing Arm core and integrate it into their own chip , or they can create their own core while maintaining compatibility with the Arm ISA .
Qualcomm’s Snapdragon is an example: it maintains compatibility with ARM, but architectural decisions and the balance between performance and power efficiency are determined by the developer. It’s this flexibility that has allowed ARM to become a universal foundation for a wide variety of devices.
Modern chips are almost always SoCs (system-on-a-chips) , integrating CPU cores, graphics, communications modules, AI accelerators, and numerous controllers . This approach enables faster data exchange within the chip and helps save power. This is crucial for smartphones: the device must be powerful, yet cool and have all-day battery life . This is why Arm has become such a major player in the mobile industry.
Even the history of Arm and its arrival at this point is tied to constraints. The company was born out of the Cambridge engineering culture and the projects of Acorn Computers, where the challenge was daunting: building a processor that met stringent thermal and power consumption limits.
This pressure pushed for simplicity and efficiency, not brute force. One of its first notable applications was the Apple Newton , a pocket-sized device that wasn’t a commercial success in itself, but helped build Arm’s technical reputation . To survive and grow, Arm eventually relied on licensing, a move that became the basis for its future expansion.
A major turning point occurred with the advent of the smartphone era in the late 2000s.
Unlike the PC world, which was dominated for decades by older x86 architectures, smartphones were developed around new operating systems like Android and iOS , designed from the ground up with efficiency in mind.
Arm was the natural candidate to power these devices. As phones grew in power and complexity, Arm refined its design to handle advanced interfaces, multitasking, and complex applications . At the same time, a huge army of developers grew up writing and optimizing software for ARM. Over time, this software ecosystem became one of Arm’s key competitive advantages.
Now they’re trying to transfer this experience to the PC world. Technically, ARM processors are already mature at the laptop level, but the most pressing obstacle here isn’t hardware, but compatibility . Moving to a different architecture usually means adapting operating systems and applications, and sometimes even rewriting them. Apple, when it abandoned Intel, eased this transition with an instruction translation program that allows older applications to run on the new ARM chips , albeit with some performance compromises. Similar processes are just beginning in Windows: Qualcomm is releasing ARM-based laptop chips, and Microsoft is expanding support for ARM devices, and this looks like a serious attempt to give Intel and AMD’s long-standing x86 dominance its first truly mainstream alternative in the laptop segment.
At the same time, Arm is increasingly moving into robotics . A modern robot must process real-time data streams from cameras and sensors, understand its 3D environment, and make decisions based on complex input signals. At the same time, it must simultaneously perform the classic tasks of controlling actuators and sensors and perform AI inference , that is, recognition and decision-making based on pre-existing models. Previously, robots were slow and rigid, suited to repetitive tasks in predictable environments. Increased computing power has enabled more realistic scenarios, from agile humanoid movements to delicate object manipulation , and Arm processors are increasingly at the heart of such systems.
Automotive electronics impose equally stringent requirements. Electric vehicles must constantly monitor battery status, charge, and energy consumption , while driver assistance and autonomous driving systems must constantly process data from cameras and sensors. Added to this are large displays, multimedia content, and the vehicle’s “brain” that connects everything. Arm’s approach, focused on high performance and low power consumption, is well-suited to these challenges, making ARM processing a key component of modern automotive architecture.
Another issue that makes the topic even more pressing is the energy costs of AI. Large data centers consume enormous amounts of electricity to train and run models , which becomes a scalability issue and even an environmental concern . Arm sees this as an opportunity to extend its ” low-power computing ” philosophy to AI workloads, enabling more efficient operation both in the cloud and on devices. The idea is to shift more AI processing to local computing, in smartphones, cars, and appliances, reducing reliance on energy-intensive centralized processing.
As a result, Arm appears to be a company that, almost unnoticed by the general public, is shaping the future of computing through standards , interoperability, and an engineering-first approach to efficiency .
If the industry is truly entering an era of ubiquitous robots, more autonomous machines, and embedded AI, then the winners will not only be those who can compute faster, but also those who can compute without wasting watts and generating heat .
And it is at this juncture that Arm’s influence becomes particularly evident.
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