Harnessing AI: A NetApp perspective

We take pride in our heritage at NetApp. Our heritage is rooted in developing innovative solutions that address the challenges of storing, managing, and protecting data in a complex IT environment. From pioneering the NetApp^® WAFL^® file system to providing a first-party cloud-native storage service with NetApp Cloud Volumes and NetApp Astra™ Trident—one of the first open-source storage orchestrators for containers and Kubernetes distributions—our heritage is built on innovation. We’re leaders in providing cutting-edge solutions that empower companies to transform their businesses. 

Although generative AI is the new kid on the block, businesses have been using predictive AI for years to improve financial forecasting, detect financial fraud by identifying anomalies, and find the most successful treatments for high-risk patients in healthcare. We know because we’ve been helping customers achieve these AI-driven outcomes. However, generative AI goes beyond mere pattern recognition, employing advanced modeling techniques to produce fresh, original content. 

Regardless of whether you believe generative AI is overhyped or underhyped, it has the potential to reshape industries, revolutionize how businesses operate, and enhance our lives. With the right tools, individuals can unleash their creativity. Marketing professionals can use generative AI to create high-quality video content from simple text; AI-powered music enables artists to craft full audio tracks from prompts like genre, lyrics, or inspirational artists. The applications of AI are vast, diverse, and still growing. 

All these applications are made possible by one thing: data. Current innovations are rapidly improving these foundation models by using customers’ private data to provide better context or to fine-tune an existing model and make better decisions. But when adopting AI, organizations can struggle to effectively manage and extract value from their ever-growing volumes of data that is scattered and unstructured. At NetApp, we tackle this challenge head-on with an intelligent data infrastructure.  

The NetApp intelligent data infrastructure gives you the ability to access any data from any location, maintaining data security, protection, and governance. Our adaptive operations aim to maximize the performance and efficiency of both infrastructure and applications, while focusing on cost-effectiveness and sustainability. Together, these capabilities can enhance the productivity of AI workers and help you achieve more successful outcomes for your business. 

In the recent Scaling AI Initiatives Responsibly survey, commissioned by NetApp, IDC identified these top reasons for AI initiatives failing: 

1. Inability to access data 
2. Insufficient data to train models 
3. Privacy, compliance, and data governance concerns or requirements 
4. Data engineering complexity 
5. Untrustworthy or poor-quality data sources 

AI transformation is often hindered by the inability to access scattered data in siloed storage infrastructure—so it’s harder for AI engineers to train and develop models. NetApp helps companies by supporting the movement, transformation, and preparation of data across hybrid cloud environments using block, file, and object storage solutions. This seamless integration means that data sources for machine learning and AI are readily available, regardless of their location. 

We understand that AI isn’t just about algorithms and models; it’s about trust, transparency, and ethical use of data. We’re committed to helping you build responsible AI systems that prioritize accountability and privacy. With our data governance and compliance capabilities, your AI initiatives can adhere to regulatory requirements and ethical standards, building stakeholder trust and confidence. NetApp’s classification service automatically tags data to support streamlined data cleansing for both the ingest and inferencing phases of the data pipeline, so the right data is used for queries, and sensitive data is not exposed to the model out of policy. 

Furthermore, NetApp offers revolutionary cyber-resilience capabilities, including AI/ML embedded in storage to combat ransomware. With Our systems, you can detect and mitigate sophisticated cyberthreats with increased accuracy and performance. 

Our Python library of tools makes it easy for developers, data scientists, and data engineers to manage data. For example, teams can create an auditable NetApp Snapshot copy of a development workspace for traceability and error detection, or an instant clone of a vector index store to make relevant data instantly available for different queries, without affecting production. 

However, our dedication to AI extends beyond technology. We believe in the power of partnership to drive innovation and accelerate AI adoption across industries. We collaborate closely with industry leaders like NVIDIA and Google to co-create AI solutions that tackle real-world challenges and deliver tangible business value. For instance, with our GenAI toolkit for retrieval-augmented generation (RAG) operations, you can implement RAG operations by connecting proprietary data stored on NetApp volumes with Google’s Vertex AI for faster access to unique insights. 

The potential of AI is limitless, and at NetApp, we’re excited to be at the forefront of this transformative journey. By combining our intelligent data management expertise with the power of AI, we empower organizations to unlock new possibilities, drive growth, and shape a better, more intelligent future for all. 

To explore further, visit our NetApp AI Solutions page. 

Read more about NetApp AI thought leadership perspectives. 

Watch our webinar where we talked through the survey results of IDC's AI maturity model white paper.