Three Edge AI Architectures That Demand Smarter Memory—and Why?

AI is one of the biggest growth drivers in the semiconductor industry today—but so far, only a few companies currently benefit from this trend, such as hyperscalers and large data centers. However, more and more are entering the second wave of artificial intelligence, a movement called “AI Everywhere,” where intelligence is shifting to the edge: into the hands of robots, medical devices, industrial controllers, and more. In this new reality, real-time inference, local decision-making, and data privacy aren’t optional, they’re essential.

The good news? This edge-centric AI trend doesn’t rely on high-bandwidth, high-cost memory. Instead, it can thrive using today’s available memory technologies, particularly emerging options like MRAM and FeRAM, which have long been waiting for the right moment to break through. “AI Everywhere” might be that moment.

Here are three examples of edge AI architectures where MRAM and FeRAM are enabling smarter, more resilient memory at the edge.

In the early stages of AI adoption, most processing occurred in cloud-based data centers. Data was collected by endpoint devices, transmitted to the cloud for processing, and the results were sent back. But for many industries, that’s no longer fast or reliable enough.

While much attention is paid to edge processors, such as MCUs and NPUs, memory plays an equally important role. In edge environments, every millisecond and every milliwatt counts. Memory determines how quickly a device wakes from sleep, how long it can operate on limited power, and how often it can be updated without failure.

The key architectural constraints include:

• Limited space and thermal budgets: Edge systems must fit in compact designs without excessive heat output.
• Fast wake-up times: Devices should power on and start inference in under a second.
• Endurance: Frequent data logging and model updates require high write cycles.
• Security and resilience: Data must be preserved during outages and protected from EMI and radiation.

Modern edge SoCs often combine MCUs, NPUs, and a complex memory hierarchy, including volatile SRAM, and non-volatile Flash or EEPROM. However, legacy memory technologies are beginning to show their age in edge applications.

Traditional memories come with inherent limitations. In contrast, MRAM (Magnetoresistive RAM) and FeRAM (Ferroelectric RAM) offer the best of both worlds: non-volatility with high-speed access. They also provide significantly higher endurance and lower power consumption.