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Cake day: Mar 29, 2021

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Other developed countries handle this fine. If someone is shit, you put them on a performance improvement plan, a formal step that shows the company is trying everything they can to up your performance and that also provides notice to the employee that they aren’t doing good enough. After a series of meetings over a period of time if the employee isn’t improving and the company can show they tried to bring them up to scratch then the employee can be let go. If you need to drop staff due to being overstaffed there are processes for this as well.

This is far different than the current US situation, where you can lose your job today because your boss doesn’t like your shoes.


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Law enforcement is run on government contracts. If the government bans facial recognition technology in law enforcement then their conftracts won’t allow it and therefore the law enforcement agencies aren’t able to use it.

This isn’t a blanket ban on the technology, just a ban on law enforcement using it.


Primer is one of those movies that you want to watch again straight after finishing it. Not just because it’s good, but because you need another watch to understand what is was you just watched.


Khan Academy has something similar in their iPad app.


If Amazon is paying them to defend the company then aren’t they technically real employees?


Live in New Zealand. Locked down hard and early, followed by a new lockdown in our biggest city every few months when a case sneaks through the quarantine at border, but largely things have been normal here the last 9 months.

Our vaccination programme has only really just started as we had no reason to rush approval of the vaccine. Currently doing high risk, the general population vaccination doesn’t start for another couple of months.



Your link takes me to a blog post about chakras that doesn’t mention Matrix at all…


Many, many apps and websites use Google analytics. So it’s certainly possible that Google knows you listened to the podcast. But the problem with “big data” is that they don’t need to know specifically that you did, they can infer from large amounts of data that you likely listened to it.


The most likely answer is the simplest: many people listened to the podcast (especially people like you, as per Google’s profile of them and you), and a portion of them searched for the channel - YouTube uses this information to deduce that you also may be interested.


Any suggestions for who to follow?