once again continuing the trend of spoiling SF startup founders ————— come get free donuts.

RT @chendotnet: if ur a startup in SF that has any cloud infra and want free donuts, dm me!.

RT @ycombinator: Datafruit (@datafruit_dev) is an AI DevOps engineer that manages infrastructure by indexing repos, docs, and runbooks, tur….

every developer has experienced this vibe on a late night.

life update !

Make a gaussian distribution.

This projects the vectors onto a space where the distances between any two vectors are "pretty close" to their distance in the original space. It works best if the d is large and k is not unreasonably small.

*more precisely, multiply it by a k × d matrix, where k is your desired output dimension, and each entry is randomly +1 or -1. also make sure to scale all the entries by 1⁄√k.

Math party trick: if you have a bunch of high dimensional points (like vector embeddings) and want to project them into a lower dimensional space while preserving similarity, you can just multiply your points by a random ±1 matrix.

RT @venkat9165: why was ubernetes scared of k… . because k 8 s.

workplace productivity is cooked

Getting rejected from @GeorgiaTech is a humbling feeling, and really, really tough . I created a resource for highschool students who just got rejected from GT to help them out a bit during this rough time :).

this is our CTO is the startup cooked?

Today I learned that “ultrathink” is a magic word which makes Claude think really hard .

How come the berkeley sidewalks randomly be getting beautiful

I’m marrying the right person

RT @TommyLovesSosa: Building the easiest data engineering tool stack for the hardest engineers out there. https:/….

RT @TommyLovesSosa: @_alisawu these "founders" when they actually meet employed people.