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biddlesby

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This strikes me as a bit pessimistic. I think you are mostly against _bad_ standards than standards per se.

If the consortium does its job well it will produce a good standard that all the major libraries like: from a UX as well as a performance viewpoint.

If it produces a bad standard, all that will happen is that nobody will sign up. No libraries are going to be _forced_ to do anything.

Totally agree. Having to think about how I need to organise my thoughts as the same time as coming up with the thoughts themselves always seems like a burden!

Just because there's no objectively correct measure, I wouldn't say that means it isn't wrong. There's nothing objective in ethics.

In your example of people not caring about their health: the environmental impact of diet is in a different ethical class for me. If you choose to ignore your own health that's your deal, but if you make choices that negatively impact the lives of millions I think the ethics are different.

I wouldn't agree with that. People may have made their choice based on incorrect research or incorrect assumptions: there is value in discussing the latest research.

It's like saying discussions about whether cigarettes are good or bad for you are pointless, the important thing is that people are able to buy them if they want.

I can sympathise with you on that. The whole of pure mathematics seems to be about making definitions and seeing what weird places and surprising connections you get. This isn't as exciting as seeing how mathematics can describe and predict phenomena in the real world.

This is a great point. You might take a different approach depending on when you expect your reader to already be proficient in the language or the framework, compared to whether a non-developer might be reading the code.

One argument against these kind of comments is that they aren't the right place to teach somebody a programming language. However I can definitely see cases where they are justified.

To be fair, "the centre of the distribution catching up" is exactly the fear that the article is criticising. The fear isn't that one company is going to make some huge leap in AI - it's more about what happens if that leap gets adopted en-masse by the whole economy.

I think the OP's comment is very relevant.

Ever since my undergraduate I've wanted to understand what representation theory is and the rough outline of how Andrew Wile's proof was constructed.

This article gave me both in a very understandable and engaging way. Thank you to the author!!!

I see this argument a lot: in the "good old days" there was Unix and apt and it was brilliant, now we have hundreds of toolsets and libraries that are flaky and need updating every year.

I think what these arguments miss is the upside of today. The "good old days" of brilliant developer experience was only brilliant for a small number of people. You had to learn right way of thinking, invest the right amount of time to learn good principles, how Linux was architectured, how not to re-invent the wheel, and so on.

This was a huge barrier to many people getting started with coding and the economics demanded getting more new developers ramped up faster. This pressure caused people to try to quickly develop little "get started quick" ecosystems.

Now we are in a situation where from a pure software engineering perspective we do have a complicated stack of teetering and shifting frameworks, I agree. But on the other hand this has come with enabling an awful lot more people to quickly get started toying with apps and coding.

What I'm trying to say is, these days its quicker to go from Level Zero to Level One, even if that means you've shot yourself in the foot going from Level One to Level Two.

Totally agree with you.

Given the title I expected to find an interesting article on what can go wrong if we overly rely on quantitative methods in the humanities. But this article doesn't distinguish between badly-applied quantitative methods and where the limits of those methods are even if they are executed well.

For example:

We look at instances where the effect exists and posit a cause—and forget all the times the exact same cause led to no visible effect, or to an effect that was altogether different

This just sounds to me like bad quantitative modelling.

There is a huge argument to be made for qualitative research, and there is much-needed criticism of the idea that "hard" methods are more valuable than "soft" methods. I think this article manages neither.

I'm not convinced by your argument that since nothing evil has happened in the last 20 years, we are safe in the future.

It's about power dynamics. If you get a consolidation of power, that's going to be open to abuse. Maybe not now, maybe in the future, who knows. Democratic systems have checks and balances in the public domain. Google doesn't have this.

I'm not so sure. I think the task is to find a treatment and a point in time where the treatment was considered alternative medicine, was then proven to work, and thereafter was considered medicine.

The conclusion then is that there are things we consider medicine today that used to be alternative medicine.

I would say it was a mistake to introduce the concept of adding fractions from two different "wholes". Instead, teach that in order to add fractions, you first have to get everything into the same "whole".

Like, you can add Jack / 3 to Ben / 3 because they were at the same table. But adding the boys from one table to another is quite a different thing.

Instead, you should teach that you should first make the fractions with both tables as the whole. Only then are you allowed to add. This could come as a later concept

I would love to do this, but I live in a country where cash isn't a thing. It's explicitly not accepted in most places.

How can I spend the same effect if I only have a debit card? I am wondering if two accounts or a currency card is a good idea. But it's just not the same as having a physical pile of cash that you can judge how fast it's going down and how much is left