Recently Dataiku hosted a Malaysian, Sydney, Manila, and Melbourne Data and Analtyics leaders lunch discussing….
In the dynamic tech landscape of APAC, AI is at the forefront, with Large Language Models (LLMs) and Generative AI leading the charge. As AI becomes more pervasive and complex, scaling it to the entire organisation becomes even more pressing. Despite its potential, a startling 77% of AI models never transition to production, underscoring the urgent need for a robust framework for AI scalability.
With the need for businesses to be flexible and responsive in the face of evolving consumer trends and economic conditions, CDOs are recognizing Machine Learning Operations (MLOps) not just as an invaluable ally, but as a strategic imperative. MLOps serves as the cornerstone for effectively managing, scaling and governing machine learning models and ensures AI projects transition from experimental to business operational.
Deep dive into:
Foundational principles of MLOps and its significance in managing advanced AI models.
The heightened challenges of scaling AI and the pivotal role of MLOps in addressing them.
Best practices for governing AI projects, with a spotlight on the unique aspects of LLMs and Generative AI.
Cultivating a data-centric culture and fostering citizen data scientists for agile, data-driven decisions.
