Leo Meyerovich on how and why the best companies are adopting Graph Visual Analytics, Graph AI, and Graph Neural Networks.

Dia Trambitas-Miron and David Talby on what makes NLP in Health/Pharma/Biotech challenging and unique.

Simon Crosby on distributed actors and data infrastructure that enable companies to analyze, learn and predict on the fly.

Nicholas Boucher on adversarial examples that can be used to attack text-based models, and the state of homomorphic encryption for…

Anjali Samani on the evolution of the data scientist role, the rise of ML engineers and MLOps, and how to…

Savin Goyal on Metaflow and the state of ML infrastructure.

Moshe Wasserblat on transfer learning, active learning, and other tools to help non-experts customize and fine-tune NLP models.

Gaurav Chakravorty on building industrial grade machine learning systems for search, recommenders, and personalization systems.

Mike Tung on lessons learned from building, maintaining, and using a knowledge graph with over a trillion connected facts.

What lies ahead in data platforms, machine learning, MLOps, and DataOps