Jeremiah Lowin on designing tools to allow teams to build, run, and monitor data pipelines at scale.
Author: Ben Lorica
Practical Machine Learning and Deep learning
Sebastian Raschka on the state of tools for training, tuning, and evaluating machine learning models.
Machine Learning for Optimization
Ade Fajemisin and Donato Maragno on recent trends and challenges in applying ML to optimization problems.
Efficient Scaling of Language Models
Barret Zoph and Liam Fedus on recent trends and challenges in NLP and Large Language Models.
Data Science at Stitch Fix
Olivia Liao on blending recommendation and personalization models with human expertise.
The 2022 AI Index
Jack Clark on recent progress in deep learning, the rise of AI ethics, and what lies ahead for language models.
Why You Need A Time-Series Database
Ajay Kulkarni and Mike Freedman on the many benefits of data management solutions focused on temporal data.
Data Science at Shopify
Wendy Foster on data science use cases, Responsible AI, and emerging tools such as large language models and multimodal models.
An AI Risk Management Framework
Elham Tabassi and Andrew Burt on a new NIST framework that addresses risks in the design, development, use, and evaluation … More
An open source and end-to-end library for causal inference
Amit Sharma and Emre Kiciman on making causal inference and learning more accessible.