Companies must innovate and one of their objectives is to enhance competitiveness and efficiency by utilizing AI. In today’s world, it is vital to provide storage models for hybrid cloud environments and intelligent data management solutions for Artificial Intelligence.
To offer better digital experiences, customers must adapt to the current pace of innovation and utilize high-capacity data processing and intelligent storage that can grow in size and time.
“Large Language Models (LLMs) could be an example of generative AI solutions, which are highly efficient natural language processing models for tasks related to language, from text generation to language comprehension and translation.”
Elena Viniegra. Cloud Director EEMI región, NetApp
The demand for more product innovation, productivity, and AI application development that offers better experiences to consumers is driving business creativity. For this, it is crucial to have AI with a robust infrastructure capable of storing data, both locally and in the cloud, at the edge, in hybrid or multicloud environments. Customers are looking for technological partners that guarantee unique and unified data governance and management, as well as intelligent storage solutions that allow seamless and guaranteed data movement across all customer environments because of the risk of losing information or encountering security breaches when switching data.
Today, generative AI already allows users to make requests using natural language, and AI interprets and generates information, whether it can be text, articles, code, music, video, voice, visual effects, 3D designs, engineering analysis… an endless array of possibilities that utilize machine learning models (ML).
Large Language Models (LLMs) could be an example of generative AI solutions, which are highly efficient natural language processing models for tasks related to language, from text generation to language comprehension and translation. The process of reading and processing data countless times, from where it is stored to memory, is necessary for these models to foster and promote intelligence. In the coming years, the need to manage massive volumes of data will continue to grow, and that is where the technology of a good technology partner becomes crucial. It is important that they provide solutions with high storage capacity and AI management to facilitate deep learning from data, as well as the ability to transport data smoothly and efficiently between different storage environments, even in real-time.
The technology from leading storage vendors makes it easier for AI to access a large amount of diverse data, which is allocated in various repository locations, using high-performance workloads.
Thanks to this technology, customers will be able to generate immense data repositories, both in all-flash or public cloud environments, as well as hybrid or edge locations. We are talking about enabling simultaneous access to multiple AI models, even in production environments, which can represent a substantial change for the business model of many companies. Research analyst firms like McKinsey state that “The impact of generative AI on productivity could mean trillions of dollars for the global economy.”
Therefore, customers embracing AI developments for their business must have storage technology that not only guarantees workload execution in secure and high-performance infrastructures, but also offers scalable and diverse environments, allowing customers to work with any public cloud provider, access any data repository wherever it is, and manage these hybrid and multicloud environments in a simple, easy, and secure manner. This flexibility and scalability make NetApp’s offering the best choice for Artificial Intelligence developments.
