5 things you need to know about Edge AI

In today’s tech-driven world, AI is revolutionizing industries. Whether you’re into mobile phones, PCs or cars, you need to understand the crucial role of memory and storage in AI workloads on edge devices. At Micron Technology, we know that, while compute like GPUs (including tensor cores), TPUs and NPUs are vital, AI workloads often hit a memory wall before computing resources are maxed out. Our industry-leading memory and storage solutions are designed to meet these extreme data demands at the edge, ensuring performance, efficiency and reliability.

Edge devices have been proliferating for years, quietly collecting and processing massive streams of data. Now, their inference capabilities are rapidly advancing, enabling AI workloads to run closer to where data originates. This evolution represents a massive opportunity for memory and storage makers. Gartner projects that spending on generative AI-capable edge device hardware will increase by 99.5% to $3.9 billion in 2025. Micron, a leader in DRAM and NAND technology, is a key player in the AI ecosystem and well positioned to capitalize on this opportunity.

When you consider how AI will grow on edge devices you need to know these five key things.

1. Inference at the edge is driving efficiency and accelerating AI adoption

Edge AI inference delivers tangible benefits — reduced latency, improved privacy, less reliance on a network connectivity, reduced operational costs and power efficiency. By processing data locally instead of sending it to the cloud, edge devices offer faster and more responsive AI experiences while saving significant energy by avoiding the constant transfer of massive datasets back and forth between the edge devices and data centers.

This evolution marks a major shift: edge devices once depended heavily on cloud servers for tasks like autonomous driving, introducing latency and connectivity risks. Today, advanced inference at the edge enables vehicles to process sensor data in real time, making immediate decisions without waiting for cloud responses. These improvements unlock new edge AI possibilities, leading to enhanced user experiences.  As consumers experience these benefits firsthand, AI adoption will accelerate.

2. Advanced inference at the edge will drive a distributed model for AI— but the cloud is not going away.

Edge computing is rapidly advancing, but the cloud remains a critical part of the AI ecosystem. A distributed model, combining the agility of the edge and scale of the cloud, is emerging as the best solution for AI workloads. The cloud will continue to handle large-scale data processing, model training, and centralized management while edge devices manage real-time inference and localized processing. To see how this works in practice, watch From ingest to insight: Micron’s portfolio accelerates the AI data pipeline. This short video illustrates how structuring and normalizing AI data at scale enables seamless collaboration between edge and cloud for efficient AI performance.

This collaboration is the foundation of a hybrid approach that leverages the strengths of both environments. By combining edge agility with cloud scalability, organizations gain flexibility, efficiency, and resilience. Building on this foundation, agentic AI — that is, autonomous AI systems making intelligent decisions without human intervention strengthens this edge-cloud partnership, optimizing performance, enhancing security and ensuring efficient resource allocation. In simple terms, an AI agent can reside on your device and when it comes up against a question it can’t fully answer, it will seamlessly reach out to a more complex or specialized AI model in the cloud or data center to get the answer. Then it will return a more precise response to you.

In short, edge devices will increasingly handle inference independently, relying on the cloud only for tasks that demand scale or specialized models.

3. Edge AI and cloud AI are the ultimate data challenge

Managing AI workloads in both edge and cloud environments presents unique data challenges. The sheer volume and variety of data, coupled with the need for real-time processing, require innovative solutions. Micron’s advanced memory and storage technologies are engineered to address these challenges, offering the performance, reliability and efficiency needed for complex AI data workloads.

Memory bottlenecks are a significant issue, especially during training and inference phases. High-bandwidth memory (HBM3E) helps to alleviate these bottlenecks in the cloud, while LPDDR5X offers high bandwidth and power efficiency for edge devices. These memory technologies ensure smooth and efficient AI operations, no matter where they reside.

Our customers, across all products, rely on our leadership and expertise to navigate these data challenges effectively.

4. Memory and storage are more important than ever for AI

As AI models grow in complexity, the demand for memory and storage capacity increases. Both edge devices and cloud infrastructure need to support these expanding models without compromising performance. Micron’s memory and storage solutions are designed to meet these demands, providing the necessary capacity and speed for AI.

Our products are built on industry-leading process nodes and offer superior power efficiency, the most advanced being Micron’s 1γ (1-gamma) process node, which leads against all competitors. For AI data centers, high-bandwidth memory (HBM3E and HBM4) breaks down the memory wall for AI acceleration. AI data centers need a full hierarchy of memory and storage for best performance, including high-density DDR5 modules, LPDDR5X, CXL-based expansion memory pools using Micron CZ122, local SSD data cache using Micron 9650 NVMe™ SSDs, and networked data lakes using Micron 6600 ION.

Similarly, edge devices need a balanced mix of memory and storage to keep AI workloads responsive. Low-power DRAM like LPDDR5X delivers the bandwidth for real-time processing, while fast, efficient storage handles model data and inference results. Universal Flash Storage (UFS) 4.0 provides that speed and reliability for mobile and AI PCs, and when paired with PCIe Gen5-based SSDs such as the Micron 4600 NVMe SSD, it ensures edge AI runs seamlessly—from smartphones to next-generation AI PCs.

5. You don’t have to solve all your data challenges on your own — Micron is here to help

With over 45 years of experience, Micron is the trusted partner for mobile phone makers, PC OEMs and automakers. Our expertise in memory and storage solutions is unparalleled, and we are committed to helping our customers achieve their AI goals. Our industry knowledge and innovative products make us the ideal collaborator for solving the most difficult data challenges and pursuing new opportunities to accelerate the AI revolution. Together, we can navigate the complexities of AI and drive forward intelligent technology.

As AI continues to evolve, the importance of memory and storage in edge applications and devices cannot be overstated. Companies in the mobile, PC, automotive, industrial, and robotics sectors must prioritize these components to ensure the success of their AI workloads. Micron is here to support these companies, with solutions that are fast, efficient and reliable.

Our technology doesn't just store data; it accelerates the transformation of data into actionable intelligence.