Artificial intelligence (AI) and data storage is a big topic these days. The Next Platform brought this interesting topic to our attention in their article, “The Challenge Machine Learning Brings to Storage.”
Data storage is an equally vital component of today’s machine learning technology, but it’s rarely the star. However, today’s analytics-based AI wouldn’t exist without it. As enterprises increasingly prioritize machine data analytics and management, they need to ensure IT infrastructure can support such initiatives in order to produce a return on investment.
Developers, not the traditional IT professionals, are driving the creation and adoption of next-generation architectures that aim to leverage public clouds while supporting AI, machine learning, machine data analytics and more.
When problems arise, IT has an opportunity to produce innovative solutions rather than throw up roadblocks. Getting involved, and driving discussion about alternatives, is the best way to remain relevant.
Deploying a new AI project brings plenty of challenges. Don’t let storage be one of them.
Melody K. Smith
Sponsored by Access Innovations, the world leader in thesaurus, ontology, and taxonomy creation and metadata application.
