We get it. Men are overly emotional. Just look at Alex Jones and Donald Trump. Ok, don’t. But the point stands. Your reaction to a perceived threat of the Penis Legislation Act being overturned is overwrought and hysterical.
Still. Why do men have to be so loud and disruptive? The Penis Legislation Act is established and totally safe from being overturned, even though so many powerful women keep promising to get rid of it and seem to have no compunction about taking away men’s rights over their own penises.
Just consider how the latest SCOTUS nominee was chosen. A small group of women who are famously hostile to the Penis Legislation Act carefully selected the best possible candidates. One of the women, who is especially committed to overturning the Penis Legislation Act, was an advisor to the President on this weighty decision. And now the nominee, an affable soccer mom, has refused to commit to upholding the Penis Legislation Act and secret emails reveal that she doesn’t believe The Penis Legislation Act is even settled law. Does that sound like The Penis Legislation Act is in peril? Calm down, gentlemen! Smile!
While you’re smiling (you look so pretty when you smile!) why not consider, for a moment, that men might not actually know what’s best for their penises? What with their hormonal emotions and everything, might it be possible that we women should make the relevant decisions about men’s health, particularly those that are penile-related? When you really think about our track record of valuing male life, the answer is clear. You can totally trust us to decide for you.
And while you stay silent as I explain some things (you look so pretty when you don’t talk!), we should remember that the role of government is not to control our bodies, and that rule only applies to one gender so it’s cool.
Would it make you feel better to know that the women politicians who constantly promise to overturn the Penis Legislation Act have ignored their own principles when it suits them and lied about it? No?
Plenty of people understand that too many men lost their lives before The Penis Legislation Act, and they’re laboring tirelessly to protect their own penises just in case it’s overturned. The fact that they even have to do this in 2018 shouldn’t make you angry at all.
So buck up, lads! Trust women. Trust your government which was not elected by a majority of people but which should be entitled to control your penises. Trust our president who has bragged about grabbing penises. America will be great again once you lose control over your penises. And stop getting so hysterical about it. You don’t look pretty when you’re hysterical.
I took a week off from work to join a deep dive study group on machine learning.
It was an incredible experience and I want to tell you about what I learned.
I learned with very smart and interesting people, and I encourage you to check out their work. You can see a list of everyone at the bottom of this article.
This is a birds-eye-view article, so hopefully it will be decipherable by laypersons, while still remaining valuable to anyone who doesn’t know what this field is about.
How should we delve into this incredibly complex topic? How about using the journalistic method of asking the classic five “W” questions: who, what, when, where, and why.
That seems like a successfully pointless structure, so let’s dive in.
What is machine learning
Machine learning is a broad term referring to training a computer using one data set to make predictions about a different dataset, without further human input.
For example, say you had a breakdown of sales for the past decade from a particular Orange Julius. Using machine learning, you might be able to have the machine predict when the most popular sales days will be for the mango pineapple smoothie in the upcoming year.
Why do I say might? In short, because it all comes down to the quality, and quantity, of your data.
In the above example, maybe the weather, or the stock market, or the cycle of the moon influence whether people want a mango pineapple smoothie or a raspberry one.
You need to have as much relevant data as you can to make the system work. If there’s a correlation between people wanting strawberry banana smoothies and the groundhog mating season, and you don’t have that data, guess what? You can’t make that connection.
However, if there is a connection between two data points—aka, groundhog mating and strawberry banana smoothies—you, the human, need to tell the machine about it to make the system go.
At the end of the day, computers are dumb. They literally don’t know their ass from their elbow. Contrary to every movie featuring robots, computers are self aware much the same way a brick is.
A computer is so dumb, it can’t figure out the relationship between data in both directions. This means that if you think there’s a relationship between Guatemalan migratory bird patterns and an uptick in blueberry smoothie sales, and you’re wrong, the computer won’t know! If you plug in that relationship, the machine will happily spit out a number. Never mind that it’s meaningless, the computer did its job.
So it’s our job, as the humans, to really make sure our thought quality is good before ascribing meaning to things. That’s probably a good call in general.
Oddly enough, in all these Orange Julius examples, nobody wants orange.
Why is machine learning
Machine learning exists for the same reason we do anything: first, curiosity, then art, and then finally money. Currently, all three reasons exist in perfect harmony tension.
Some of these applications use algorithms like neural networks, deep learning, and others that we didn’t get into in this article. While the specifics (read: math) differ greatly, the basic principles still apply.
When is machine learning
Now, and into the foreseeable future.
Who is machine learning
In short: not many people. It’s a specialty inside (at least one other) specialty. Practitioners need an understanding of programming, statistics, calculus, plus the vagaries of whatever aspect of life they are trying to make predictions on. That’s on top of machine learning specifics.
That’s one of the reasons I wanted to study it. The more people know about machine learning the more we as a society will be able to deal with its consequences.
At least that’s the prediction; I haven’t proved that in a model yet 🤓.
With whom I learned
I’d like to give a big shout out to the super smart and interesting folks I worked with over the week. Here they are, along with links to what they’re up to. I highly encourage you to check them out.
I started buying records a few months ago, and I’ve already compiled a large
body of imagined insults to my person about why I’d do such a dumb, dusty thing.
In the time honored tradition of humoring your own neuroses, I’m going to
respond to these accusations.
But first, an opinion:
Why you should buy records, too
You shouldn’t. Or you should. Do what you want. Pluralistic societies for the
Okay, on to why I started buying records.
Many would see this as a drawback, but for me, as I get older and the world gets
faster and my attention becomes more precious, I find it rather meditative to
attend to something as fragile as a record.
It becomes it’s own kind of ritual.
Leafing through the record spines, hearing the paper swoosh as you pull it
off the shelf, carefully extracting the record, delicately placing it on the
spindle, cleaning and wiping for dust as necessary.
It’s like worshiping at an altar, except instead of having to confess your sins
you get to dance.
You own them
Music streaming services have taken over the world, and their great, don’t get
me wrong. However, about a year ago I had this moment where I realized I hadn’t
bought any music in a long time.
It made me feel strange; I care about music a lot, and only using a
streaming service felt like a gear head only leasing a car.
I wanted something in my hands.
This one is more aspirational. I don’t know if I can tell the difference, sound
wise, between a lossless digital file and a vinyl recording, but I hope to when
I get good enough speakers to really make that apparent.
In the meantime, my records still sound great on my almost two decades old Sony
5 CD changer, tape, radio and speaker combo.
Big cover art
Trivial? Maybe, but some albums have amazing artwork, and I want to hold it and
gaze into it like the coffee-table-book-sized masterpiece it is.
I like having music in the format it was indented for. For records that were
recorded in analog, that’s vinyl.
If that sounds suspiciously like a lot of hand waving and magical thinking,
yeah, you’re probably right. Yet I think good art always has elements of magical
disbelief, so why not stretch that metaphor from the art to the medium?
I hear it’s the message.
They smell nice, too. What does an mp3 smell like?
This is an anti-reason.
It’s like trading cards for hipsters.
You can still listen to digital music
This is the best part: even though I own a record player and several records, and
listen to them frequently, I have not been outlawed from listening to music on
my phone (at least not yet).
In a best of both worlds move I’m pretty proud of, I started ripping my records
to high quality FLAC files so I could listen to them on the go, or just
categorize them obsessively, or whatever, don’t judge.
That way, the files are legally mine, they are DRM free, and I can play them
anywhere without an internet connection (I’m looking at you, The Subway) without
having to pay for Spotify.
If you’ve made it this far, congratulations, you win nothing.
The Situation You have a list of items that you need to render with comma separation, and an “and” at the end.
Cookies, rice, and farts.
The Problem This display is traditionally done in business logic, creating more complexity than this simple output warrants.
The Solution We can use pure CSS, using well supported pseudo-classes and pseudo-content. Behold!
HTML <ul class="list"> <li class="item">Cookies</li> <li class="item">rice</li> <li class="item">farts</li> </ul> CSS /* Boilerplate to inline the list.
More than being lampooned as a press secretary who makes up facts, it was Spicer’s portrayal by a woman that was most problematic in the president’s eyes, according to sources close to him. And the unflattering send-up by a female comedian was not considered helpful for Spicer’s longevity in the grueling, high-profile job, where he has struggled to strike the right balance between representing an administration that considers the media the “opposition party,” and developing a functional relationship with the press.
“Trump doesn’t like his people to look weak,” added a top Trump donor.
Trump’s uncharacteristic Twitter silence over the weekend about the “Saturday Night Live” sketch was seen internally as a sign of how uncomfortable it made the White House feel. Sources said the caricature of Spicer by McCarthy struck a nerve and was upsetting to the press secretary and to his allies, who immediately saw how damaging it could be in Trumpworld.
Since SNL has so much power, how about portraying Bannon as a puppetmaster controlling everything Trump says. Or portray Trump as a dog who Bannon pets on the head when he says something properly racist. Even better, Trump can be played by a woman, evidently the most outrageous insult ever imagined.