AI Centers of Excellence: Driving Innovation
As the field of artificial intelligence (AI) evolves, companies are increasingly turning to AI Centers of Excellence. These centers play a crucial role in scaling operations while ensuring governance and compliance. They help organizations manage AI model training and data efficiently, which is vital for organizations operating on a global scale.
A great example is Johnson & Johnson Innovative Medicine. Partnering with NetApp Inc., they have successfully leveraged their AI Center of Excellence to balance scalability, security, and innovation in healthcare. This sets a strong precedent for using AI to improve global operations.
Data Management and Governance
Monica Jain, director of R&D data science at Johnson & Johnson, emphasizes the importance of data management. "Data governance is essential," she says. "We'll have a dedicated committee for ethics and compliance to ensure proper data handling." This focus on data is key to what they do with AI.
Scalable AI Infrastructure
With effective data management, AI projects at J&J become scalable and compliant across different regions. Jain, alongside Hoseb Dermanilian from NetApp, and Krish Vitaldevara, also of NetApp, have discussed how their collaboration supports scalable, secure AI infrastructure, driving innovation in healthcare.
Principles of Data Handling
Jain highlights the importance of adhering to the Findable, Accessible, Interoperable, and Reusable (FAIR) principles. This ensures that data infrastructure is robust before diving into AI technologies. "We focus on perfecting our data management," Jain says, noting that while perfection is unattainable, striving for it is crucial.
Empowering Internal Users
AI Centers of Excellence at companies like Johnson & Johnson empower internal users such as developers and data scientists. These initiatives allow teams to create various environments for AI workloads, which have been in place for years. Dermanilian notes, "Our relationship with J&J has been ongoing for over two or three years."
Challenges and Solutions
According to Vitaldevara, successful AI integration requires robust infrastructure and governance. Organizations prepared for the data influx can manage AI's complexities better. "This is where ONTAP and our data management technologies become crucial," Vitaldevara explains, highlighting the complexity of managing huge amounts of data.
Strategic Use of AI Models
J&J employs both large and small language models to tackle complex healthcare issues. Jain elaborates, "Large language models are broken down into smaller ones to solve specific problems, then combined to address larger challenges." This approach is particularly useful in the research and development space.
Unlocking Enterprise Data Potential
By employing AI effectively, organizations can unlock the potential of their enterprise data, leading to significant advancements in business and human health outcomes. Vitaldevara states, "AI is changing the pace of drug development in healthcare, proving to be a game-changer."
This strategic use of AI is transforming how organizations operate, particularly in the healthcare industry, where rapid advancements are being made. It showcases the profound impact AI can have when managed efficiently and ethically.
