ML Infra Best Practices: Top Challenges today

With data science becoming as ubiquitous as it is deemed to be in all types of companies and industries: AI-first, cloud-native and traditional enterprise, the rise of an infrastructure stack dedicated to AI is inevitable. There are many places where current software engineering tooling falls short — data science development is fundamentally different from software engineering necessitating the need to rethink several layers of this stack. The broad tenets of difference include: