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Comment by lhnz | Hacker News Reader

Honestly, if you read behind the lines, it sounds like the employee was intentionally making a joke about it at his expense in front of a bunch of people, and I think a lot of CEOs would take that badly as this is effectively the same thing as calling your boss egocentric.

But, we do have a bit of code that measures metrics on his account, so can we find the bit of code that increases the engagement on his account?

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> “When you’re asked a question, you run it through your head and say ‘what is the least fireable response I can have to this right now?’” one employee explained.

Reading between the lines, Musk sounds like a giant baby.

> But, we do have a bit of code that measures metrics on his account, so can we find the bit of code that increases the engagement on his account?

There doesn't need to be. When they run AB tests, it's possible that they'd pick the winning cell if it makes the Elon metrics look better.

Even if the algorithm doesn't do anything explicit about boosting him, it can be tweaked through AB testing to favor him.

You mean A/B testing of weights/biases?

No, the "weights" of your model are trained from the input data. What is usually AB tested are hyperparameters of the model, or different "flavors" of (model+input data).

What people are implying is still unsubstantiated though. The engineers on the Twitter Space say that this is to ensure that changes they make do not bias one category over another, they don't say that it's in order that they can make discretionary updates to bias towards Elon Musk.

Maybe after every update to the model, they check these stats to ensure that they haven't biased towards Elon Musk, and if so roll the change back.

? Considering Elon as its own category is a bias.

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