Emerging tools allow real-time, highly visual collaboration on data science projects — even in ways that allow those who code and those who don't to work together. Tim Kraska fills us in on how ML models enable this.

Tim:
• Is Associate Professor in the revered CSAIL lab at the Massachusetts Institute of Technology.
• Co-founded Einblick, a visual data computing platform that has received $6m in seed funding.
• Was previous a professor at Brown University, a visiting researcher at Google, and a postdoctoral researcher at Berkeley.
• Holds a PhD in computer science from ETH Zürich in Switzerland.

Today’s episode gets into technical aspects here and there, but will largely appeal to anyone who’s interested in hearing about the visual, collaborative future of machine learning.

In this episode, Tim details:
• How a tool like Einblick can simultaneously support folks who code as well as folks who’d like to leverage data and ML without code.
• How this dual no-code/Python code environment supports visual, real-time, click-and-point collaboration on data science projects.
• The clever database and ML tricks under the hood of Einblick that enable the tool to run effectively in real time.
• How to make data models more widely available in organizations.
• How university environments like MIT’s CSAIL support long-term innovations that can be spun out to make game-changing impacts.

The SuperDataScience show's available on all major podcasting platforms, YouTube, and at SuperDataScience.com.