AI at the edge comes with a host of challenges: limited processing resources, small storage capacities, insufficient memory, security concerns, electrical power requirements, limited physical space on edge devices, and excessive costs. That being said, there is an enormous need for AI at the edge - for devices to learn fast and make decisions in real time. Issues such as latency and distance are current drawbacks that hold edge-to-cloud AI back from reaching its full potential. In some cases, cloud data centers can be as far as hundreds or even thousands of kilometers away from edge devices. Reducing the distance and therefore the latency, by bringing AI into the edge device itself, can open up a world of new possibilities. And, compared to edge-to-cloud AI, AI-enabled edge devices don't need to rely on a stable internet connection, nor do they have as much vulnerability to cyber-security issues, because they don't send data offsite.

Edge AI box computers equipped with compact and high-capacity storage is one of the key factors to make AI come true at the edge. By offloading computation and storage from the cloud to the edge itself, edge computing is enhancing the power and capabilities of the IoT. To help make this a reality, SP Industrial has launched the new MEA3FEV0 SSD Series. This industrial-grade PCIe Gen 3x4 SSD series features support for NVMe 1.3 and BiCS5 112-layer 3D TLC NAND Flash technology. It ticks many boxes that are common problems for edge AI computing: large storage capacities up to 2 TB, small M.2 2242 form factor for minimal space usage, lower power consumption compared to BiCS4, and affordable cost with a DRAM-less design.

As industries compete to capitalize on the abundance of data generated by intelligent, connected devices, implementation of an intelligent data strategy has become even more critical. Edge computing has played an instrumental role to address this demand, but the edge itself has continued to evolve with the ever-growing need for even more demanding, real-time computing. Rugged edge computing enables applications that require real-time, low latency data processing and storage to function reliably in volatile environments that are not friendly to regular systems.

Trends and technologies such as Industry 4.0, AIoT, and 5G are driving the need for improved intelligence at the rugged edge. Businesses and organizations want more computing power at the edge because of the benefits it provides to their operations. NVM Express (NVMe) is an essential enabling technology for rugged edge computing, reducing latency and accelerating data processing to the point where connected devices can operate anywhere to perform machine learning, artificial intelligence, and inference computing. Real-time data access and analytics are turning rugged edge computing into a competitive necessity across all sectors and industries.