I gave a short informal talk at the Spring 2022 Machine Learning Artificial Intelligence and Data Science (MLADS) conference. The MLADS conference is an internal event at the large tech company I work for, and so the conference wasn’t open to the public. The bottom line is that I learned a lot and enjoyed the event.

The event ran May 31 through June 3, 2022 in Redmond, Washington.

Actually, I didn’t really give a talk in the traditional sense. I was part of a five-person group at a session called “Ask a Data Scientist”. Each of us introduced ourselves (about five minutes each) and then fielded a question or two from the audience. Then each speaker went to a table and hosted a question-and-answer session for an hour.

Here is the table where my work pal Ricky L (an expert in reinforcement learning) and I (circled in red) hosted a question-and-answer session. I blotted out the faces of my colleagues because some people don’t want their images on the Internet. The attendees are eating some super-fancy cupcakes that were provided by Alexandra S, the session organizer and host.

I really enjoyed talking to my colleagues. There was a lot of good discussion about many different topics, both technical (for example, about self-supervised neural networks) and non-technical (for example, about career paths).

The Data Science panel was in-person and was the first in-person event my company has hosted in over two years because of the covid pandemic. Like most people, I’ve been doing all my meetings online (mostly Microsoft Teams, some Zoom) and have gotten used to the online form of collaboration and communication. But some things are just much better in person. During the MLADS conference, I could take advantage of people’s body language and eye contact and other cues that don’t appear in an online environment.

Anyway, I guess the mini-moral to the story is that before covid started in March 2020, there was an established balance between the pros and cons of in-person vs. remote events. Post-covid (whenever that will be), there will be a period of flux as a new balance is established.

“The Great Wave off Kanagawa” (circa 1830) is a famous print by a Japanese artist named Hokusai. The image pops up in many data science contexts such a style transfer.