Machine Learning
Privacy in the Age of Generative AI
On a recent trip to my hometown in Eastern Canada, my father picked me up at the airport. One of the first things he asked me was, “Is AI going to take everyone’s jobs?”. When AI,
Weights & Biases with Chris Van Pelt
Machine learning model research requires running expensive, long-running experiments where even a slight mis-calibration can cost millions of dollars in underutilized compute resources.
Building a Privacy-Preserving LLM-Based Chatbot
As Large Language Models (LLMs) and generative AI continue to grow more sophisticated and available, many organizations are starting to build, fine-tune, and customize LLMs based on
Catching up with Technologist Charlie Gerard
Charlie Gerard is a highly accomplished software engineer and technologist. She’s worked at Stripe, Netlify, and Atlassian and authored the book, Practical Machine Learning in
Data-Centric AI with Alex Ratner
Companies have high hopes for Machine learning and AI to support real-time product offerings, prevent fraud and drive innovation. But there was a catch – training models require