As warfare becomes increasingly digital, the Department of Defense (DoD) is doubling down on efforts to effectively scale and operate artificial intelligence (AI). To enable a wide range of business cases and mission success with AI, it is imperative that the right data, technology, infrastructure, and expertise are available. However, for data scientists especially, the amount of data generated by smart edge devices is challenging. Not to mention a massive number of ingestion points that can overwhelm compute, storage, and networks at the edge.
That’s why NetApp, leader of cloud and AI solutions, is committed to empowering data scientists so they can deliver the results they need quickly without fail. Additionally, NetApp’s AI solutions drive intelligence at the edge by allowing edge-level analytics to process and selectively pass on data during ingest, ensuring operational decisions are made during time of need. This helps create different tiers of data service and speeds up data movement so that data scientists can focus on important analytical tasks while equipping warfighters and civilian personnel with the insights they need.
Ensuring Trustworthy Data Through Data Modelling Management and Integrity
For DoD missions that require rapid decision-making, it’s vital that the ultimate decision makers can trust the data that feeds their AI models. This can be especially challenging when the apps and IoT devices (i.e. sensors) that feed these AI models are under constant attack. With this certainty, the DoD will need to prioritize industry partnerships that lead to enhanced security and data authenticity with a better understanding of all data sources.
More specifically, this means the DoD will need to ensure validated technologies are leveraged to encrypt data at rest and while in transport. Building an AI infrastructure in a highly regulated environment like that of the DoD is especially challenging. However, NetApp is able to deploy machine learning and deep learning frameworks to compute and protect models with vast amounts of data as well as build a trustworthy data pipeline spanning the entire ecosystem that allows data to seamlessly move from edge to core to cloud ensuring the correct data is available for all AI modeling.
Simplifying Deployment Through AI Platform as a Service
The benefit of cloud computing environments is it’s relatively easy for data science and AI projects to begin rapidly. The downside? Challenges that arise when data scientists and leaders fail to properly plan for the scale of the end-state data pipeline. This can lead to skyrocketing costs due to improper cloud sizing or data sprawl.
That’s why NetApp focuses on providing customers with access to infrastructure that makes the most sense for each requirement. Ideally, customers should start with what is needed and then leverage the flexibility and modularity of the solution, allowing them to scale data repositories in the cloud or on premises as the requirement dictates.
For the data science teams, this results in simple deployment and more time to focus on mission-important tasks without having to worry about maintaining the infrastructure. For the DoD overall, it means delivering performance, security, and scale while reaping the full benefits of AI without risking projects by overrunning costs.
Enabling Optimal AI Environment Configuration Through a Data Science Toolkit
Building a robust data platform requires embracing the need for openness, speed, and scale. Not only is data being created at an exponential rate, but there are also many data types, formats, and tools needed to manipulate and normalize this data.
NetApp provides the broadest support for different datasets in a single storage platform. This allows data scientists to bring different capabilities they require while avoiding the problem of siloed infrastructures to support different use cases.
Additionally, NetApp’s unique Data Science Toolkit makes it easy for data scientists and engineers to perform necessary housekeeping tasks, simplify data management, streamline AI workflows, and enable traceability. With this capability, data scientists can eliminate manual tasks and rapidly provision new data volumes almost instantaneously.
Assembling the Right Team and the Right Tools at the Right Time
Nothing is more critical than teams working together to stay in front of evolving adversaries, especially when deploying an AI platform. As the cyberthreat landscape continues to evolve, so must the DoD’s ability to collect, secure, and analyze data.
Additionally, there will be much needed expertise at the data science, infrastructure, and operational levels, all of which appreciate each other’s roles on the team while working to support each other’s results. This will enable the DoD to be proactive with the adversary instead of reactive.
Integrating It All
Iron Bow continues to empower organizations like the DoD to leverage AI-informed decision-making from the edge to cloud by integrating environments with the industry’s leading and trusted software tools and platforms in a simple and adaptable fashion. Ultimately, data scientists within the DoD can look forward to leveraging data they can trust, simplified deployment and configuration, and being able to work together with the right tools at exactly the right time-ensuring decision makers have the right data in time of need to make mission-critical assessments.
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