As AI infrastructure evolves rapidly, enterprises increasingly rely on AI Centers of Excellence to scale operations while maintaining governance and compliance. These dedicated hubs empower organizations to streamline AI model training and data management, enabling compliance across global operations.
For example, Johnson & Johnson Innovative Medicine, in collaboration with NetApp Inc., is successfully using its AI Center of Excellence to balance scalability, security and innovation in healthcare, setting a strong precedent for using AI to enhance global operations.
“It is when we are working on the data management as a whole, data governance is an essential piece of it,” said Monica Jain (pictured, second from left), director of R&D data science at Johnson & Johnson Innovative Medicine. “We have a separate committee like ethics and compliance to take care of the data as well. I think it’s a very important piece here to take care what we are doing with our data.”
Jain, Hoseb Dermanilian (left), senior director and global head of Al go to market and sales at NetApp, and Krish Vitaldevara (second from right), senior vice president of product platforms at NetApp, spoke with theCUBE Research’s Rob Strechay (right) at NetApp Insight, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how the collaboration between Johnson & Johnson Innovative Medicine and NetApp has enabled scalable, secure AI infrastructure through AI Centers of Excellence, driving innovation in healthcare by optimizing data management and model training across global operations. (* Disclosure below.)
Scaling innovation with data management and AI Centers of Excellence
As AI adoption grows, effective data management practices are crucial to driving innovation, according to Jain. Data infrastructure plays a critical role at J&J in ensuring that AI projects are both scalable and compliant across different regions.
Johnson & Johnson’s Monica Jain and NetApp’s Hoseb Dermanilian and Krish Vitaldevara talk with theCUBE about how the collaboration between the two companies has enabled scalable, secure AI infrastructure.
“What we are focusing on with the ‘tsunami of the data’ is to follow our [Findable, Accessible, Interoperable and Reusable] principle to make our data infrastructure very robust,” Jain said. “Before rushing into the gen AI or AI as a whole, we are focusing on our data management to be perfect. It cannot be perfect, for sure, but we are trying to do that.”
Companies such as Johnson & Johnson have been using AI Centers of Excellence for years to handle workloads such as model training, according to Dermanilian. These initiatives enable internal users, including developers and data scientists, to build different types of environments for AI workloads.
“We have some customers who have built AI Centers of Excellence like Johnson & Johnson, who are enabling their internal users … to do different types of workloads, and we’ve been doing this for six years,” Dermanilian said. “Our long-standing relationship with Johnson & Johnson goes more than two [or] three years.”
Effective AI integration requires both a robust infrastructure and governance, according to Vitaldevara. Organizations that are successfully developing AI are the ones that are better prepared to handle the massive influx of data.
“This is where ONTAP … and being able to bring the data management technologies that we built over the last two decades together becomes incredibly important in how you cut through this complexity,” Vitaldevara said. “Because it’s a pretty complex picture out there.”
J&J’s approach to data management emphasizes the strategic use of both large and small language models, according to Jain. These models are tailored to solve complex healthcare challenges.
“All those [large language models] actually are breaking down into small language models, which are combining and solving the problem,” Jain said. “One LLM cannot solve the complexity we have, especially in the [research and development] space. So, we are breaking them into pieces to solve small problems, combining them together, and then we are solving the problem.”
By using AI to unlock the full potential of their enterprise data, organizations can bring about significant advancements that improve both business outcomes and human health, according to Vitaldevara. AI has become a game-changer for organizations prepared to handle its complexities.
“This is about unleashing the power of their enterprise data using AI,” Vitaldevara said. “When you talk about J&J and other customers in the healthcare industry, they are rapidly changing the pace at which the drugs come out. This kind of innovation is game-changing. It changes everything we do as humans, and some of the innovation is mind-boggling for us that we see every day.”
Here’s the complete video interview, part of SiliconANGLE’s and theCUBE Research’s coverage of NetApp Insight:
(* Disclosure: TheCUBE is a paid media partner for NetApp Insight. Neither NetApp Inc., the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)