Ash Srivastava - October 8, 2024
AI models are only as good as the data they’re trained on.
Ensuring high data quality is crucial for AI to deliver accurate predictions and insights.
Develop a data quality framework that aligns with your AI initiatives for better outcomes.
How are you ensuring data quality for your AI projects?
First shared on LinkedIn.
Dumping a database into a prompt doesn't solve search. In the AI era, data engineering is about filtering noise so the model gets the right context.
It was inspiring to share the stage with great leaders and engage with a room full of passionate professionals, students, and technology enthusiasts...
Documentation doesn't need to be a multi-month writing project. Record the work, let an LLM structure it, and review in thirty seconds.
Go deeper: AI Audit Checklist: What Auditors Will Ask For | NIST AI RMF Explained: Govern, Map, Measure, Manage
Weekly thinking on data and AI governance from Ash Srivastava.
