TL;DR: improved training-inference trade-off of drifting models Faster training & comparable FID, costing increased memory usage First author Ali Falahati, co-supervised w/ @elliot-creager.bsky.social & Shubhankar Mohapatra Paper: arxiv.org/abs/2605.12183 Code: github.com/Mort…
Who's Who of AI
Gautam Kamath
Assistant Prof of CS at the University of Waterloo, Faculty and Canada CIFAR AI Chair at the Vector Institute. Joining NYU Courant in September 2026. Co-EiC of TMLR. My group is The Salon. Privacy, robustness, machine learning.
http://www.gautamkamath.com
What they're sharing
arxiv.org
victorzhong.com
View on Bluesky →
kamathematics.wordpress.com
Articles & links
Gautam Kamath reposted
I helping recalibrate Waterloo’s software engineering program (and to some degree CS) for the age of AI. I wrote an essay on the challenges I’m seeing. www.victorzhong.com/writing/the-...
kamathematics.wordpress.com/2026/05/27/m...
kamathematics.wordpress.com
Their own posts
Recent commentary
In the last 48h: - Jr researcher asked me wheter to use AI in making talks - Saw two talks, with AI {slop, enhanced} slides Collected my thoughts and wrote a post. Tl;dr: don't steal your own thinking, don't remove *you* from your talks. Also, give a &#@% about your talks.
if you get caught submitting AI slop to arxiv, the punishment should be generational aura loss
I think frontier AI labs should hire people who either: - at least pretend to care about the people affected by their products - can make good jokes? I talk to brilliant young people every day, terrified about the future. This callousness from those inside is sad.
It's so cringe when real people I otherwise know and respect post obvious AI slop on social media, particularly when they're (supposedly) expressing their feelings. Authenticity is so rare and valuable these days, and it's sad to see people just cede it from the get-go