Weird, that page is likely for legacy customers as snowflake owns them and they’re now known by another name.
The logo itself they’re using is an old logo, predating 2022 when they moved to the “friendly hippo” away from “murder hippo”
Their sponsors list is pretty out of date, I clocked crunchydata on there which is now snowflake, and that’s an old logo
This is actually a pickup truck I believe, the bed is full.
The rear defrost is right behind the driver, it’s got like 10 feet of snow to get through.
Wait are you really advocating for the notion that driving with snow on your vehicle is safe and others ought to watch out?
In a handful of the states where snow is common it is illegal to drive with snow on your car, because of how dangerous it is.
Did you also struggle with the concept of how wearing a mask helped protect others, which in turn protected you.
Lmao check lemvotes on this chud
Only if that large truck has an unsecured load, which is illegal.
Schmidt is a well known bad take kinda guy.
One of my favorite hot takes is how “poor people should spend their money smarter, be more responsible so they aren’t poor anymore”
Yeah, it’s wildly dangerous to drive with ice and snow on the top of your car as it becomes projectiles and hampers other drivers visibility.
Flux the repo
Thank you for leaking from about your hole
What if I told you I sudo as root
With constrained data sets it’s actually really useful.
Parsing text and logs and correlating events, super useful.
When you dump all human “intelligence” into it you discover how dumb we are collectively.
Common misconception, it was dude looks like a Minotaur but they couldn’t come up with enough rhyming words
The LLM basically just did the work once for the sample data set, so all the computation happened up front.
If that was the only data set we’d ever need, and the data set didn’t change realtime based on sensors then … hell yeah that gross switch woulda worked 😂
It ran super fast but only over that one constrained input, it didn’t allow for new use cases.
It’s not a bug per se, and we’re gonna see a lot of this moving forward.
Did a code review, hefty code review, and as I got to the end of it where “the magic happened” I discovered that the logic was actually a case statement for every permutation.
Because they’d asked the AI to write logic to go through each type, the AI wrote a case statement for EACH TYPE.
… it was so fucking fast though. So wrong but so so fast compared to the actual running code.
💰💸💵💶💷💴
^ this is how
Their move to attempt to monetize our on-prem runners might be the kick needed to move to Gitlab 🤞
neat.