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The power of unified data storage with generative AI

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Jonsi Stefansson
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The promise of generative AI (GenAI) is undeniable, but the volume and complexity of the data involved pose significant challenges. Unlike traditional AI models that rely on predefined rules and datasets, GenAI algorithms, such as generative adversarial networks (GANs) and transformers, can learn and generate new data from scratch. Training these models requires high-quality, diverse data to produce accurate, coherent, and contextually relevant output. The more comprehensive the training data, the better the model will perform in producing realistic and useful responses.  

Organizations can find it overwhelming to manage this vast amount of data while also providing accessibility, security, and performance. For AI innovation to flourish, an intelligent data infrastructure is essential. This infrastructure must support data preparation, model training and tuning, retrieval augmented generation (RAG), and inferencing. Additionally, it should meet the requirements for responsible AI, including model and data versioning, data governance, and privacy. 

The data dilemma: Breaking down data silos with intelligent data infrastructure

In most organizations, storage silos and data fragmentation are common problems—caused by application requirements, mergers and acquisitions, data ownership issues, rapid tech adoption, and organizational structure.

 This fragmentation includes:

  • Different media types: high-performance flash, high-capacity flash, hybrid flash, hard disks
  • Multiple protocols: block, file, object 
  • Various deployment models: storage appliances, software-defined storage, storage as a service, public cloud storage 

Data fragmentation makes it difficult for data scientists and AI engineers to access the datasets they need. This is the primary reason why AI initiatives fail, according to IDC’s new survey Scaling AI Initiatives Responsibly, commissioned by NetApp. 

Unified data storage resembles a well-organized library. In a modern library, every book, magazine, DVD, and digital media item is stored in one place and accessible from any section without hassle. Everything is categorized and readily available through a single system, regardless of whether you’re searching for a classic novel, a research journal, a documentary film, an e-book, or an encyclopedia (do they even produce those anymore?).

In the same way, intelligent data infrastructure brings together diverse data types under one cohesive umbrella. By combining access to file, block, and object-based storage from a single storage OS across corporate data centers, colocation facilities, and public clouds, unified data storage streamlines data access, enhances data management, and provides consistent data governance—providing silo-free infrastructure.

In GenAI, this capability means providing structured, semi structured, and unstructured data seamlessly to your data scientists. Whether you’re using RAG or fine-tuning a large language model (LLM), you can work with a rich and diverse dataset, regardless of location, to help provide nuanced language patterns, cultural references, and proprietary knowledge, making your AI more effective in producing accurate and domain-specific answers. 

With intelligent data infrastructure from NetApp, you can feel confident in data preparation, data security, and data mobility. You can select cloud-based AI services for compute-intensive training, a colocation facility to help with internal power constraints, or data center infrastructure to secure sensitive information. 

Our unified data storage solutions are designed to scale dynamically, making it easier to expand your storage performance and capacity as your GenAI initiatives grow. This is the same NetApp® technology leveraged by the top three public cloud providers and available to you as a first-party cloud native storage service. 

Empowering innovation

As GenAI continues to reshape industries and drive innovation, the importance of unified data storage cannot be overstated. NetApp’s comprehensive suite of unified storage solutions provides the scalability, performance, and security needed to unlock the full potential of GenAI. By streamlining data management workflows and maintaining the availability of critical resources, NetApp empowers organizations to accelerate their GenAI initiatives and stay ahead in an increasingly competitive landscape. 

Intelligent data infrastructure is more than just a storage solution; it plays a strategic role in GenAI innovation. With our industry-leading expertise and cutting-edge technologies, organizations can harness the power of GenAI with confidence, driving transformative outcomes and unlocking new opportunities for growth. 

We make data infrastructure intelligent: any data, any workload, any environment. 

Explore more

To explore further, visit the NetApp AI solutions page. 

Read more about NetApp AI thought leadership perspectives. 

If you missed out on our webinar where we talked through the survey results of IDC’s AI maturity model white paper, you can watch it on demand

Jonsi Stefansson

Jonsi Stefansson is NetApp's Chief Technology Officer and Senior Vice President. An experienced executive and founder, he's led startups and Fortune 500 companies. An Icelander with a passion for family, travel, and culture, Jonsi enjoys golf, fishing, and relaxing at his summerhouse with a glass of wine or Kaldi beer.

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