This is true in the entertainment industry, but it's because consumers want to buy what everyone else is buying. Not because there's a huge difference in performance. In fact, it's the opposite. There are many equally attractive/talented performers who can do the job just as well. It's very competitive, success is rare and fleeting even when it does come.
This translates into other parts of the economy. High income households experience high income volatility, consistent with the hypothesis that there is lots of competition at the highest levels of success—not very little competition.
There are edge cases where a personal reference is valuable. If you’re inexperienced, it can get you an interview. Or it can get you a job at a small company without a real HR department.
But outside of that, a hiring decision made based on a personal relationship is considered cronyism. It isn’t always illegal, but most HR departments go out of their way to prevent it.
“It’s not what you know, it’s who you know” is terrible career advice in general. It can be incredibly seductive because it promises people an advantage over competition. But it’s wrong. It’s a waste of time and in my experience, the people who follow it tend to interview poorly because they come off as arrogant and complacent.
This is untrue for the simple reason that your friends’ employers wouldn’t allow it. Hiring practices based on personal references opens the door to discrimination lawsuits, so every HR department creates objective interview processes that remove such advantages.
I wondered what is this “community-based” mental health care that the author advocates for, and how is it different from psychiatry. Are psychiatrists not part of the community? It turns out it refers to “dream-work, breathwork, herbalism, and meditation.”
The goal of the union is to improve wages, benefits and working conditions. If Apple addresses those concerns to the extent that union membership is a worse deal, then the union has won.
I think people advocating for increased funding for mental health services have started to define all social problems in terms of their impact on mental health, e.g. prejudice as a traumatic experience, the stresses of poverty, etc.
Increased funding for mental health services seems like a poor solution.
What’s being implied here is that the endowments of these elite institutions were created through historical crimes, but activists won’t make an issue of that if the universities support diverse hiring initiatives.
Designers hate Adobe. This acquisition caused a huge collective meltdown on Twitter, and people are saying Figma is dead now. Many people were hoping Figma would kill Adobe.
> I understand completely why this was kept quiet.
Are you suggesting that Apple and Facebook normally have these kinds of discussions in public? Because that is not at all the case.
Possibly there is something nefarious going on here. But the fact these talks were secret means nothing, since all talks between companies are secret by default.
It's a good start, but it's more of an illustration than a logo to be honest. It should work as a single color (white, black), at small scale and in combination with your product name.
I’m a huge supporters of unions, but Amazon has been very open about their opposition to unions. The fundamental argument for unions is that companies serve shareholders at the expense of workers. Opposing unions is some kind of shocking corporate malfeasance, it’s just the nature of capitalism.
That is a normal usage in the tech industry, but that's not how ordinary people use that word. More importantly, it's not how journalists use that word.
In ordinary language, you are making inferences about what users are interested in, then making inferences about what products are relevant to that interest. The prediction is that putting relevant products in front of users will make them buy more - but that is a trivial prediction.
ML is useful for many things. I'm asking the question of whether prediction is useful, and whether it is accurate to describe ML as making predictions.
The reason to raise those questions is that for many people, the word prediction has connotations of surveillance and control, so it is best not to use it loosely.
The meaning of the word "predict" is to indicate a future event, so it doesn't make grammatical sense to put a present tense verb after it, as you have done in "Predict what features a user is most interested in." Aside from the verb being in the present tense, being interested in something is not an event.
You can't predict a present state of affairs. If I look out the window and see that it is raining, no one would say that I've predicted the weather. If I come to that conclusion indirectly (e.g. a wet umbrella by the door), that would not be considered a prediction either because it's in the present. The accurate term for this is "inference", not "prediction".
The usage of the word predict is also incorrect from the point of view of an A/B test. If your ML model has truly predicted that your users will purchase a particular product, they will purchase it regardless of which condition they are in. But this is the null hypothesis, and the ML model is being introduced in the treatment group to disprove this.
If your ML model is able to predict what consumers are going to buy, the revenue lift would be zero.
Let's say I go to the store to buy milk. The store has a perfect ML model, so they're able to predict that I'm about to do that. I walk into the store and buy the milk as planned. So how does the ML help drive revenue? The store could make my life easier by having it ready for me at the door, but I was going to buy it anyway, so the extra work just makes the store less profitable.
Maybe they know I'm driving to a different store, so they could send me an ad telling me to come to their store instead. But I'm already on my way, so I'll probably just keep going.
Revenue comes from changing consumer behavior, not predicting it. The ideal ML model would identify people who need milk, and predict that they won't buy it.
Also in the age of social media, visual identity is less about the wordmark. For most of these companies, their word mark doesn’t even show up on their social media feeds. Most have guidelines that often include a custom typeface, specific types of photography, editorial layouts, illustrations that define the brand.