> But there was another aspect too and that was Linda Hamilton. This was one of the first mainstream big-budget movies that changed the way women were portrayed in film. Lots of people had posters of her wearing the sunglasses, carrying weapons, etc. It was actually a really big deal.
Yes, a strong female character in big budget movies wasn't a common theme. Aliens 2 also had a strong female protagonist played by Sigourney Weaver. The movie was also directed by James Cameron.
Terminator 2 was a huge cultural phenomenon. I remember going to the movie theater with my Dad to see it. I think it was the first R rated movie I saw in the theater, so it was something that we bonded over. Many of my friends had a similar experience.
This is very common behavior. This is where a good manager can really help. They can recognize this is happening and then provide context.
One approach to deal with ambiguity is to write a short design doc, which writes down what you are trying to do, and all of the assumptions that you are making. If you don't understand the domain, some of your assumptions will probably be wrong. The stakeholder should be able to see that and provide guidance.
There were some interesting algorithms that came out of the contest. There was a matrix factorization algorithm that worked pretty well. Another "guy in a garage" tried to incorporate the anchoring effect into their models.
I don't think Netflix used any of the algorithms. I suspect they have more data on the user and movies than was presented in the contest.
I agree, if all of the content is garbage, then you don't need a model, you could simply pick something at random.
I think the AI winter was over by 2007. There was a lot of hype about machine learning and big data. The Netflix Prize for building a Recommender model launched in 2006. There was research on neural networks and deep belief networks, but they weren't as popular as they are today.
>For example, Sales teams are often compensated on revenue generated (outcome), but what if you did a good job (process) but didn’t hit your numbers because the market was just really bad in your vertical? A good leader will recognize this and still compensate you (i.e. hold you accountable) appropriately rather than punishing you for the outcome.
A good leader might try to keep you on the team, if they like you and you miss your numbers for a couple of quarters. From what I've seen, Sales is pretty brutal. It's quite common for Sales folks to lose their jobs, even if there are circumstances outside of their control. If they do keep you on and you don't meet your OTE, you will get paid less. In many ways their job is harder and has more risk than software engineers trying to deliver a software project on time. Which also very hard to do!
When you have a large PR like this, here's how I like to get it reviewed.
1. Give reviewers sometime to become familiar with the PR. They might not understand all parts of it, but they should have at least a cursory understanding of the PR.
2. Have a meeting where the PR is explained in front of the group of reviewers. The reviewers will understand the PR better and they can ask questions in realtime.
3. Let folks review the PR after the meeting in case they spot anything else, or think of additional questions.
Most of the time PR review is done asynchronously, but doing most of the review in the meeting can also be a decent team building exercise.
Yes, a strong female character in big budget movies wasn't a common theme. Aliens 2 also had a strong female protagonist played by Sigourney Weaver. The movie was also directed by James Cameron.
Terminator 2 was a huge cultural phenomenon. I remember going to the movie theater with my Dad to see it. I think it was the first R rated movie I saw in the theater, so it was something that we bonded over. Many of my friends had a similar experience.