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buddhiajuke

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But Python is strongly typed. If you say x=2, type(x) will say “int”.

It does suffer from an excessive overloading of operators (“a” times 6 shouldn’t work). But that’s neither here nor there.

If Python wasn’t strongly typed, it wouldn’t be conceptually possible to move it towards explicit typing as the current push is.

Now, it’s not statically typed. You don’t get to assign values and interpretations to memory addresses. This is what “performant” people usually defend. But _that_ has nothing to do with typing assuming semantic roles in codebases.

This is the case in my marriage, but not in my parents’. They are musicians, artists, perform together and/or take active stakes in each other’s careers. They weren’t sexual as I was growing up (I’m not giving intimate details here) but they had this whole other source of cohesion. A much greater one indeed — I have fond sexual memories but my parents have dozens of live albums at cool venues.

Then, maybe all of this anomie is a disease of affluence. The other thing that united my parents was that, well, they had to fight for survival and for the means if giving us kids a decent childhood experience. Maybe that alone works like continuous shared trauma, us-two-against-the-world.

I’m paid to manage a penguin farm.

Weak penguins need additional feeding. Thin penguins are just thin.

But there’s no objective criteria to tell weak from thin. And I have a budget.

Now, my penguins happen to have owners. But they don’t pay for their penguin, they pay into the penguin system.

I have pretty sharp productivity/energy/focus fluctuations and often achieve more by waiting for the “inspiration” (so to speak) to come and do tasks quickly than by slogging through low times. But they’re pretty sharp: sometimes something might take me two hours at low tide and ten minutes at high tide.

Then there’s the issue of what to do at low tide.

I’ve tried countless times to adhere to Pomodoro or Jocko Willink-type mindsets that willpower is fickle while discipline equals freedom. But the results don’t seem to be there.

You’re not wrong.

OTOH the other day I heard someone in the Netflix doc about Alberto Nisman’s murder that described a terrorist network as a “matrix”.

I grumped as card-carrying pedants are duty-bound to, but then realized that if there’s a 1:1 correspondence between graphs and (adjacency, incidence) matrices, then there’s very little loss of meaning in referring to graphs as “matrices”. Maybe in some communication contexts it’s even clearer.

The examples I have seen tease but are not fully clear on how far GPT-3 can go on tasks that are not in principle text generation tasks.

For example I’ve seen the translation to HTML code demo. Of course, LSTMs already generate quasi compilable code. But the promise seems far better here. Countless “AI” tasks can be conceptualized as entering prompts and receiving code — playing chess, finding logical implications (maybe from tabular data like in Formal Concept Analysis), detecting outliers in columnar/matrix data. How much does GPT do? How much turf beyond chatbots and automatic journalism does it cover?

I’m using lattice (line) diagrams to understand intersection concepts like this. They’re easy to generate from cross tables using FCA tools such as the “concepts” Python available in pip.

There’s an episode of “Star Trek: the Next Generation” where Scotty, the engineer from the original Shatner Star Trek tells the next-century engineer LaForge that this is how it’s done. You never tell the captain all that you have so you keep something to squeeze at the fatal moment.