In the rapidly evolving AI technology space, the ability for government, defense and intelligence missions to use AI and analyze data efficiently at its source is becoming increasingly crucial. Oracle has introduced solutions that bring the power of OCI’s AI infrastructure capabilities to on-prem, remote, and edge locations, enabling advanced AI workloads and inferencing.
With Oracle Cloud@Customer Compute, Private Cloud Appliance, along with the Roving Edge Device, organizations can now harness the power of AI in isolated and disconnected environments, opening a world of possibilities.
Remote or Isolated AI Cloud Computing
Oracle’s Cloud@Customer, PCA and Roving Edge offerings are specifically designed for customers who require cloud services to be hosted within their own data centers, or remote locations, either for sovereignty, mission or latency reasons. The solutions allow for semi-disconnected wide area communications and in many cases totally disconnected support, which meets the needs of many military and humanitarian missions.
Now with the addition of GPU-accelerated instances, Oracle brings high computing power to these environments. The Cloud@Customer Compute and PCA now support NVIDIA L40s GPUs, providing a high-performance environment for AI and machine learning workloads.
Up to 48 L40S NVIDIA GPUs, 6,624 OCPUs with 80.4 TB of memory, and a mix of up to 3.65 PB of high-capacity storage and 1.2 PB of high-performance storage.
The Roving Edge Device, a small single ruggedized cloud node has also been enhanced for AI missions with the inclusion of 3 NVIDIA L4 GPUs in a small portable form factor.
Isolated AI Workloads
By leveraging these distributed and edge Oracle Cloud offerings, organizations can perform complex AI inferencing tasks at remote or isolated locations.
- In a defense industrial base manufacturing setting, sensors equipped for computer vision can inspect products for defects in real-time, enabling quality control without the need for extensive data transmission to a central cloud.
- Digital twin models can be used to find anomalies in complex machines.
- Organizations can run large language model (LLM) fine-tuning without the need to move that compute intensive task back to a larger cloud region.
- During natural disaster responses when traditional connectivity is compromised, these AI instances can continue to process and analyze data, perform computations from local sensors.
- In transportation and maintenance, AI inferencing can help optimize routes, predict equipment failures, and enhance safety.
- Border security can benefit from real-time sensor for AI threat detection.
- Military operations can utilize edge devices for tactical AI processing, enabling secure and efficient decision-making on the battlefield.
This technology is set to revolutionize the government, defense and intelligence mission, improving efficiency, and response times. As AI continues to advance, the ability to process data at the edge will become increasingly vital.
To learn more, visit, please see our recent announcement, Oracle Delivers AI to Increase Efficiency, Agility, and Success