Every business wants to transform with AI to enhance customer experiences, improve patient outcomes and streamline supply chain — but too often, large investments in data science expertise result in innovative ML models that languish in prototypes, never to be implemented in applications.
To ensure the ROI of AI investments, enterprises need a platform that brings together tools to streamline data science workflow with leading edge infrastructure that can tackle the most complex ML models. Your enterprise needs a platform that can bring innovative concepts into production sooner, integrated within your existing IT/DevOps-grounded approach.
Attend this session to learn:
- What makes AI models unlike conventional software and how data science talent alone can’t get your valuable innovations into production
- How to solve specific workflow and platform challenges that stall deployment and cause AI models to languish in the prototype stage
- How IT leaders can scale AI success with an MLOps mindset and platform, and architectural choices that enable IT to industrialize AI
Senior Director of AI Systems, NVIDIA
Co-Founder and CTO, Iguazio