AI in Action: From Machine Learning Interpret...

In this episode of the Data Science Salon Podcast, we sit down with Carlos Aguilar, Head of Product at Hex and former founder of Hashboard, to discuss a topic critical for every data team: how to properly evaluate AI analytics tools.Carlos shares why traditional checklist-based e ...  Show more

Together, Leon and Oscar share how applied EDA practices remain the backbone of trustworthy analytics pipelines in both academic and industry settings. Their discussion highlights the challenges and lessons learned from building the EDA Toolkit, and why reproducible workflows are ...  Show more

The role of the data scientist is changing. Some organizations are splitting the role into more narrowly focused jobs, while others are broadening it. The latter approach, known as the Full Stack Data Scientist, is derived from the concept of a full stack software engineer, with ...  Show more

David Kanter, Executive Director at MLCommons, discusses the work they're doing with MLPerf Benchmarks, creating the world's first industry standard approach to measuring AI speed and safety. He also shares ways they're testing AI and LLMs for harm, to measure—and, o ...

What if AI could revolutionize healthcare with advanced language learning models? Sarah and Elad welcome Karan Singhal, Staff Software Engineer at Google Research, who specializes in medical AI and the development of MedPaLM2. On this episode, Karan emphasizes the importance of s ...  Show more

With AI tools constantly evolving, the potential for innovation seems limitless. But with great potential comes significant costs, and the question of efficiency and scalability becomes crucial. How can you ensure that your AI models are not only pushing boundaries but also de ...