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Secure AI data pipelines for generative AI in the public cloud

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Mackinnon Giddings
Mackinnon Giddings

Generative AI has revolutionized how organizations innovate, enhance productivity, and prototype AI applications. As a marketer, it has given me the freedom to think creatively instead of getting bogged down with mundane tasks. To truly harness the potential of generative AI, feeding foundational language and learning models (LLMs) with massive amounts of high-quality data is essential. Although foundational LLMs are readily available, the key to gaining a competitive edge lies in augmenting them with proprietary data. But how can organizations easily tap into and move data between on-premises and cloud environments without compromising security and data management? In this blog, we’ll explore how NetApp® cloud data solutions solve these challenges, empowering organizations to securely integrate their data for cloud-based generative AI workloads.

Ensuring data quality with Google Cloud NetApp Volumes and Vertex AI

Data quality is the secret sauce for successful AI projects. With Google Cloud’s Vertex AI platform and the fully-managed Google Cloud NetApp Volumes storage service, organizations can effortlessly bring the power of generative AI to their enterprise data - no coding wizardry required! Unleash the full potential of your proprietary data, including images, videos, audio, and text, securely stored within NetApp volumes.

With the power of Vertex AI and Google Cloud NetApp Volumes, you can generate meaningful and relevant answers that augment foundational LLMs. This combination enhances the value of data, providing customers with more insightful results while simplifying data management pipelines, particularly in hybrid setups.

With data from on-premises or cloud storage made visible to generative AI platforms on demand, you can obtain better, relevant results without compromising security or data privacy. It's time to gain new insights, drive creativity, and solve business problems while keeping your proprietary data sources under lock and key.

Streamlining workflows with Amazon FSx for NetApp ONTAP and Sagemaker

Access to more data means better decisions, but protocol differences between on-premises and cloud data often slow down data science teams. Enter NetApp’s collaboration with AWS through Amazon FSx for NetApp ONTAP. This integration smooths data pipelines between the premises and the cloud, eliminating the need to switch between file and object protocols. Collaborate effortlessly with Sagemaker notebooks, where building, training, and deploying machine learning models becomes a breeze. Embrace real-time data processing with Apache Kafka, and let Spark unleash the power of analytics on your on-premises data. Connect with rich API libraries for interactive dashboards and watch your productivity soar. NetApp’s solution maintains data safety and security, while empowering technology teams to create data-centric businesses without breaking a sweat. This results in simplified data management pipelines, particularly in hybrid setups, allowing you to focus on extracting insights from your data.

NetApp’s commitment to internal AI use cases

NetApp practices what it preaches. Our in-house team of AI enthusiasts isn’t just providing solutions; they’re leading the charge. With a passion for integrating AI/ML into NetApp‘s products and services, they’re unlocking the hidden potential of your data estate. Armed with state-of-the-art AI techniques, they’re revolutionizing cyber resilience, data management, and generative AI. From a documentation query system that speaks your language to code conversion tools that breathe new life into legacy code, NetApp is pushing the boundaries of AI. Do you need troubleshooting wizardry with intelligent recommendations? We’ve got you covered. Our commitment to innovation empowers you to squeeze every ounce of value from your data. So, buckle up and join the AI revolution with NetApp as your trusted guide.

NetApp’s cloud data solutions offer a secure and streamlined approach to integrating generative AI workloads. Seamlessly connect on-premises data to cloud-based AI/ML services, augmenting foundational models with your proprietary data and gaining a competitive edge. NetApp’s collaboration with Google Cloud and AWS enables data science teams to ensure data quality, simplify workflows, and unlock the full potential of generative AI. Our commitment to internal AI use cases solidifies our position as a trusted partner in driving successful data-centric businesses.

Are you ready to dive into the world of secure and transformative AI-driven solutions? To learn more about NetApp’s AI solutions, visit the NetApp AI webpage.

Mackinnon Giddings

Mackinnon joined NetApp and the Solutions Marketing team in 2020. In her time, she has focused on Enterprise Applications and Virtualization, but uncovered a passion in Artificial Intelligence and Analytics. In her current role as a Marketing Specialist, Mackinnon strives to push messaging and solutions that focus on the intersection of authentic human experience and innovative technology. With a background that spans industries like Software Development, Fashion, and small business operations, Mackinnon approaches AI topics with a fresh, outsider perspective. Mackinnon holds a Masters of Business Administration from the Leeds School of Business at the University of Colorado, Boulder. She continues to live in Colorado with an often sleeping greyhound and a growing collection of empty Margaux bottles.

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