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The electronics industry tirelessly pushes the envelope of technological innovation, but the rise of artificial intelligence (AI) and machine learning (ML) represents a watershed moment for business transformation. AI may very well make former impressive benchmarks in transformation, such as the rise of the cellular phone and the smartphone revolution, pale in comparison.
The impact forecasts and expectations are bullish. AI is expected to contribute more than $4 trillion to the global economy annually, spawn new business models, and accelerate productivity and efficiency gains that will transform business and society.
But why is this happening now, at this point in history? Here are five foundational technology pillars that have emerged in recent years, and how they serve as jet fuel for AI systems and applications innovations.
Processor technology
In earlier waves of innovation, the processor architecture was fixed. At the time, this one-size-fits-all approach worked to create scale around hardware technology and supporting software so that it could appeal to a mass audience of consumers.
But this eventually fell short when mobile phones came onto the scene. Hardware for mobile phones needed to take into consideration the power constraints of battery-operated devices and their small physical size, two things that the major processor computing architecture at the time could not deliver.
In 1990, Arm (NASDAQ: ARM), then a startup based in Cambridge, UK, filled the void with high-performance, power-efficient, and small form-factor processor technology for battery-run products. These products ultimately sparked the mobile revolution. The processor architecture was so robust that AI functions could be built into the devices themselves – voice, touch, and facial recognition. The technology has expanded over the decades to touch virtually all vertical market segments. Along the way, the company has made the security of silicon and systems its top priority, whether it’s designing trust into its IP or helping found industry groups such as PSA Certified to create frameworks for best security practices.
Digital nervous system
Years passed, and the value of Arm’s power-efficient, small form-factor processor architecture caught the attention of innovators building the Internet of Things (IoT), a vast network of connected devices capturing new forms of data to transform businesses.
Today, the combination of AI and Arm’s power-efficient compute platform in connected IoT devices creates new possibilities for IoT at scale while shaping future super platforms. AI on the edge will be the catalyst for unleashing this potential, driving a remarkable future we can’t even imagine.
Turning AI on the edge’s power into action is analogous to our senses and muscles. The nervous system regulates critical functions, and similarly, IoT requires its own autonomous system, especially during cloud AI downtime. Much like our survival depends on the autonomous nervous system, IoT’s success will hinge on its ability to function independently when required.
Democratization of development
As AI models and applications get more sophisticated, developers need to be able to customize their hardware with different types of CPUs, GPUs, neural processor units (NPUs), or vision processors for their specific software workloads. It’s as far from one-size-fits-all processor approaches as the mobile phone is from the abacus. Arm enables this by providing a compute platform based on a broad array of processor IPs, subsystems, and software while encouraging innovation and collaboration, which ultimately lowers barriers to entry to chip design.
Delivering the right compute, from cloud to edge
Enormous cloud data centers process most of the world’s big AI workloads today because they can do so more efficiently at scale. But as data centers expand, and as AI workloads take up a notoriously large percentage of their computing cycles, concerns about energy consumption have increased. This is compounded by the increased use of large language models like ChatGPT, which have huge computing requirements. Arm technology addresses this: NVIDIA’s Grace Hopper chip has 72 Arm Neoverse CPUs which perform AI training workloads two to four times faster than Intel-based devices with better performance-per-watt.
Whether it’s NVIDIA or Amazon AWS Graviton, Arm’s power-efficient processor architecture is being increasingly embraced as a way to manage specific AI workloads while lowering energy costs significantly. Arm technology is also designed to follow and support AI workloads as they increasingly get distributed outside the cloud to edge devices.
Arm technology also underpins AI-powered autonomous and software-defined vehicle designs, where the demands for the required compute performance within the power, cost, and thermal constraints of vehicles are intense.
Global innovation ecosystem
While software and hardware used to be developed in silos, that approach is no longer possible given how closely aligned hardware needs to be to deliver the required software functionality. A global innovation ecosystem has emerged over the years, as 15 million developers have embraced the Arm architecture for its technical capabilities and the flexibility it brings to design.
This ecosystem serves to help startups and existing companies punch above their weight by giving them access to technologies, resources, and technical know-how that otherwise would take years to build in-house. Arm supplies all the software tools and libraries, IP subsystems, development kits, security frameworks, test and certification environments, and standards required to speed developers to market faster.
A future built on Arm
The increasingly tight coupling of software and hardware, combined with the transformative power of AI and ML, is driving innovation to previously unimagined heights. As the most pervasive CPU architecture ever, Arm is at the forefront of the AI/ML revolution, powering billions of devices from smartphones to cloud servers.
From CPU-only workloads to combined CPU/GPU or NPU setups, the Arm platform delivers the performance and efficiency to handle the most demanding AI algorithms. We’re constantly innovating to optimize for future AI and ML needs, working with industry leaders to deploy Arm tech for cutting-edge applications like autonomous driving, generative AI, and more. As we start to architect a new digital nervous system to drive humans forward, we look to the future of computing – a future built on Arm.
Learn how Arm is powering the future of computing.
This post was created by NASDAQ: ARM with Insider Studios.