Weed can be addictive for people with ADHD, it's one of most common of forms of self medicarion but in the long run it probably going to make things worse.

Source: I was addicted for 3 years, at first it did wonders for my sleep issues and increased my productivity. At some point, I had to smoke daily or I would get headaches and huge cravings, my tolerance would constantly increase, and then it didn't help with my sleep issues anymore.

Now, I am only using it recreationally once every few months. It's fun but I have to be careful otherwise I know things can turn sour really fast.

While the question is hilarious, the lack of references to in depth guides is a bit alarming...

Maybe something nexus project related? Working with the largest research paper database is definitely going to provide you with a decent challenge.

Again, more complicated.

It doesn't have to be.

Are the algorithms mathematically sound, or just AI/machine learning magic fairy dust?

MAB algorithms lie in middle. They are a mathematically sound way to explore the unknown and make reasonable decisions given whatever context is available.

There have been a few hospital trials with success, but progress is slow and funding is low. There are a few really interesting papers if you are interested to read more.

Do the algorithms have implicit biases against poor people, or those with darker skin or who live in certain postcodes?

In a sense, it's not different than laws that discriminate against people of color or other marginalized communities. The fact that a bunch of super privileged lawmakers create laws that disproportionately harm us, does not mean that the concept of law is flawed.

You got to ask yourself why the algorithm was given that information in the first place, and more importantly who gave it?

What we call algorithm, is actually two things. A set of instructions (the actual algorithm) and a set of parameters. The instructions explain how to use those parameters in order to make a decision. The parameters may or may not be biased, it all depends on the process that is used to generate those parameters.

AI in particular uses a process called training, in which people make decisions, and another algorithm is used to adjust the parameters so those decisions can be genralized and repeated by the AI. When, biased people make biased decisions, they are going to train an AI to make biased decisions.

Unfortunately, that's our reality, biased people make biased decisions, as a result we have biased laws and biased algorithms.

By the way, this is what the author calls algorithm cleanse, and it's bureaucracy supercharged. Why hire someone to reject applicants of color when you can build an algorithm to do that? Making a legal case against that is much harder, and the legal system isn't ready to understand the nuisances of the case.

However, in contrast to the laws, we marginalized people can create our own "algorithms", thay are not biased to our best effort. The fediverse is living proof of this. Why fight the system when we can make our own?

I used the refund money to buy Bose qc35 earbuds

Totally agree, I had the fortune to read Domain Driven Deign by Eric Evans early in my career. While, the book may be outdated, it helped me understand that my job is to turn the unknown or ambiguous into code. I find that much more exciting than being a coder.

First of all, thanks for the interesting outlook, it gave something to think about!

In general, I don't like thinking in absolutes. It's not like everyone will read the article or everyone won't, some people will and some won't.

There it helps me to break down to more categories:

1. People that will read the article, understand it, and have critical thoughts to share.
2. People that will read the article, understand it, but won't have anything to add or critize.
3. People that will read the article, but won't understand it.
4. People that won't read the article, but would if something caught their attention (like a question on the comments).
5. People that won't read the article, but would read the comments.
6. People that won't read the article, but will comment something interesting about the title or the discussions in the comments.
7. People that won't interact with the post at all.
8. Other possible categories I haven't considered.

The telephone game is really helpful to understand how interactions between people of the categories above will go. However, keep in mind that the goal is not necessarily 100% accurate transmission of the author's message. On the contrary, it's possible people are looking for different interpretations, relevant information, criticism, and/or a laugh.

Personally, I really like it when people provide quotes they find interesting along with their own analysis. An example would be:

To allow? What? Was Australia requiring/forcing everyone to answer calls from bosses at all hours?

Australia will introduce laws giving workers the right to ignore unreasonable calls and messages from their bosses outside of work hours without penalty, with potential fines for employers that breach the rule.

So you cannot be fired anymore for not answering your boss's 2AM call. It nice to make to make progress, but the bar is so low it's a tavern in Hades...

During that time, we felt quite stuck - unable to make decisions. Our daily conversations became centred around anxious what-if calculations. At one point we had reduced our budget for catering to a total of 5 USD per person per day, for breakfast, lunch and refreshments - even in Zanzibar, this is an unfeasibly low figure. We jettisoned one item after another from our budget

We started a fundraising campaign on GoFundMe to help cover the cost of financial assistance. It was a comfort to know that members of the international Python/Django community would stand up to support us, but the pleasure and gratitude we felt about that was overlaid with a feeling of humiliation that once again, a major African open-source software event had been obliged to publicly extend a begging-bowl.

Eventually, we received the grant funding we had applied for, though even this seemed to come with a humiliation: it happened after a white European spoke up publicly on behalf of the African Python community.

last week I had misconfigured my auto-format and it was leaving commas and whitespaces. The amount of "WHAT HAVE YOU DONE???" comments I got were of the chart.

There was a linter in place, I literally could not merge unless the issues were fixed, yet people felt compelled to point them out.

I am starting it as a hobby, so I am trying to minimize cost.

I have a VM I use to host personal projects, DigitalOcean has an example docker compose yaml I tweaked a bit, and connected it to the nginx reverse proxy on the VM.

I have a proton subscription, so I am planning to use that for emails.

But, orange and 1984 seem like legit choices, thanks for sharing.

Simple, yet effective!