That "temporary" fix from Q1?
That pipeline nobody understands?
That executive dashboard with 17 definitions of "revenue"?
In kitchens, we call this "skating through service."
In tech, you call it Tuesday.
Check out the latest Line Cook Logic article. Links in comments below.
That "temporary" fix from Q1?
That pipeline nobody understands?
That executive dashboard with 17 definitions of "revenue"?
In kitchens, we call this "skating through service."
In tech, you call it Tuesday.
Check out the latest Line Cook Logic article. Links in comments below.
Absolutely loving #Pluribus on @AppleTV. Feels like Kim Wexler (the badass attorney that she is) saving humanity from an Invasion of the Body Snatchers-type threat. (Though, so far, this foe appears to be much more pleasant.) Really hoping a Slippin Jimmy character enters soon.
@JVMonte2 I love the nod to the older musicians on in this thread, but Beck and Kevin Parker (Tame Impala) absolutely need to be towards the top of the list. (Perhaps right underneath Prince.)
@SixersAdam Shamelessly replayed this missed dunk approx. 10 times in a row now. VJ brings some much, much needed lifeblood to this team. For the first time in a long time, watching the Sixers makes you feel alive!
Elon Musk came up with a pretty incredible idea during the Q3 Earnings Call, that no one is really talking about.
His words: “Actually, one of the things I thought, if we've got all these cars that maybe are bored, while they're sort of, if they are bored, we could actually have a giant distributed inference fleet and say, if they're not actively driving, let's just have a giant distributed inference fleet.
At some point, if you've got tens of millions of cars in the fleet, or maybe at some point 100 million cars in the fleet, and let's say they had at that point, I don't know, a kilowatt of inference capability, of high-performance inference capability, that's 100 gigawatts of inference distributed with power and cooling taken, with cooling and power conversion taken care of. That seems like a pretty significant asset.”
So basically, each car has ~1 kilowatt of high-performance AI inference capability, Tesla wouldn’t need to build giant data centers — the fleet is the data center.
Tesla could turn their entire fleet into a giant distributed inference network, spread across the world, powered by the batteries and AI in the car already.
Mind blown.
My career path from chef de partie to Co-Founder & CTO isn't typical, but maybe that's exactly why these insights matter. We're all navigating uncertainty and pressure. The kitchen has taught me a lot about both.
Presented at IBM Manhattan last week, blocks from Craft where I worked as chef de partie. Finally launching Line Cook Logic—exploring patterns between kitchens and tech.
First article: "From Mise en Place to Microservices: What Enterprise AI Can Learn from Professional Kitchens"
You can read this article at the following locations:
🔗 Medium: https://t.co/a8k1KMETJu
🔗 Substack: https://t.co/QZbMM9I5UP
🔗 Beehiiv: https://t.co/IFj5UgVism