Leo Meyerovich on how and why the best companies are adopting Graph Visual Analytics, Graph AI, and Graph Neural Networks.
NLP and Language Models in Healthcare and the Life Sciences
Dia Trambitas-Miron and David Talby on what makes NLP in Health/Pharma/Biotech challenging and unique.
Delivering Continuous Intelligence at Scale
Simon Crosby on distributed actors and data infrastructure that enable companies to analyze, learn and predict on the fly.
Imperceptible NLP Attacks
Nicholas Boucher on adversarial examples that can be used to attack text-based models, and the state of homomorphic encryption for…
Evolving Data Science Training Programs
Anjali Samani on the evolution of the data scientist role, the rise of ML engineers and MLOps, and how to…
Building Machine Learning Infrastructure at Netflix and beyond
Savin Goyal on Metaflow and the state of ML infrastructure.
Democratizing NLP
Moshe Wasserblat on transfer learning, active learning, and other tools to help non-experts customize and fine-tune NLP models.
Machine Learning at Discord
Gaurav Chakravorty on building industrial grade machine learning systems for search, recommenders, and personalization systems.
Applications of Knowledge Graphs
Mike Tung on lessons learned from building, maintaining, and using a knowledge graph with over a trillion connected facts.
Key AI and Data Trends for 2022
What lies ahead in data platforms, machine learning, MLOps, and DataOps