Notch worked at King before, so MC is directly related to one of the companies on the list.

Excel functions are translated. This leads to being pretty much locked out of any support beyond documentation if your system language isn’t English.

The note reads:

IF YOU HAVE FOUND THIS NOTE YOU MUST BE ENGAGED IN DEMOLISHING ONE OF THE FALSE COLUMNS THAT HAVE BEEN PLACED IN THE FOYER OF THE SAINSBURY WING OF THE NATIONAL GALLERY. I BELIEVE THAT THE FALSE COLUMNS ARE A MISTAKE OF THE ARCHITECT AND THAT WE WOULD LIVE TO REGRET OUR ACCEPTING THIS DETAIL OF HIS DESIGN.

LET IT BE KNOWN THAT ONE OF THE DONORS OF THIS BUILDING IS ABSOLUTELY DELIGHTED THAT YOUR GENERATION HAS DECIDED TO DISPENSE WITH THE UNNECESSARY COLUMNS.

Pork?! These are all beef, baby.

There are various methods, but from a practical standpoint it is gone regardless.

They are trans.

They have two avenues to make money:

1. Sell commercial services such as customer support bots. They get customers thanks to the massive buzz their free services generated.
2. Milking investors, the real way to make money.

Generative AI doesn’t get any training in use. The explosion in public AI offerings falls into three categories:

1. Saves the company labor by replacing support staff
2. Used to entice users by offering features competitors lack (or as catch-up after competitors have added it for this reason)
3. Because AI is the current hot thing that gets investors excited

To make a good model you need two things:

1. Clean data that is tagged in a way that allows you to grade model performance
2. Lots of it

User data might meet need 2, but it fails at need 1. Running random data through neural networks to make it more exploitable (more accurate interest extraction, etc) makes sense, but training on that data doesn’t.

This is clearly demonstrated by Google’s search AI, which learned lots of useful info from Reddit but also learned absurd lies with the same weight. Not just overtuned-for-confidence lies, straight up glue-the-cheese-on lies.

The lack of pressure leads to absurd file sizes for silly things.

A few weeks ago, I needed a vector company logo, so I asked our graphics team for one. The file they sent me was 6MB. While working with it, I noticed it was actually quite clean, so I exported it as an SVG and it came out to 2KB. 1/3000th the size for the exact same graphic.

I opened their file up in a text editor and found font configs for specific printer models (in a graphic with only filled curves), conditional logic, multiple thumbnails, and other junk.

Cucumbers have much better shelf-life when shrink-wrapped. It ends up a debate of which is worse between food waste and plastic waste.