mateo411

I suppose that Anthropic or any of the other companies that develop foundational AI models do this. This would be a vertical integration strategy. However, they would spend less time developing the best foundational models, so they might not want to keep a more focused product vision, and keep their capital focused on build better models and improving Claude.

Yes, they will be able to do this, but it's a lot of work, and Lovable has a pretty good head start.

> 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.

This is called contextual advertising. It's becoming more popular as cookies are becoming less effective.

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.

Interesting. Thanks for telling me that.

Well, AI is changing so fast nobody can really tell you what it is.

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.

Yes, the Singularity came from Kurzweil.

I bet somebody could make a movie about this.

>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!

I agree.

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.

I think Denver home prices have decreased by 4% since the peak in 2022.

I don't think anybody is going to be permanently underwater. Home prices changing should be a second order effect of building more apartments.

I bet your friend is good at Scrabble.

That makes a lot of sense. Jalopy is a term for a car that isn't in very good shape. I suspect that's why they chose the name Jalopnik.

Sure, I think it is an odd line. In this case car ownership is a proxy for geography. You could probably find some other interesting proxy variables for geography, that could be used to write 500 word articles. A proxy variable that is in interesting from a monetary perspective could be something that you could use for contextual advertising. I saw four our five car ads when I skimmed the article.

The Emancipation Proclamation freed very few slaves. The order did not apply to areas of the Union which still had slaves, nor did it apply to areas of the Confederacy occupied by the Union. Although, it did apply to unoccupied areas of the Confederacy. The government of the Confederacy was unlikely to follow an order issued by the Union during the Civil War.

It may have encouraged some slaves in the Confederacy to flee, if they found out about it.

It's true that there is tax money that is spent on infrastructure to support cars, but taxes are also collected from the use of cars through gas taxes and annual registration fees. If you include those taxes and fees it's not obvious how much other taxes are used to subsidize cars.

It will be different in each state, since each state imposes different levels of gas taxes and has different registration fees.

One of the functions Product Management is to be an intermediary between the business/sales and Engineering. Sometimes you might have issues working with Product Management, but you don't want to interact and build features for a bunch of stressed sales folks, so they can make their quota.

It would be very hard for a company to build a sustainable business that way.

I agree. Unless you are programming Java.

"Java is a blue collar language." - James Gosling

The app gives pretty good discounts. It's pretty easy to save about 20% using the app for an order. I think the rewards is also about 10-15%. If you are going to go to a Quick Stop Restaurant, it's generally a good idea to use the app.

Thanks for the additional context. This is very interesting.

The paper came out in 1972 which is the same year that C was invented. I don't think the paper mentioned what programming language was used, but since it has function calls with parameters, it's a higher level language than assembly.

> Maybe a PhD gets a boost in pay starting out

My sense is you might get paid when you start what an undergraduate makes after one year and a pay raise.

Your career will probably develop faster than the person who started working after undergrad. Your ceiling is likely hire.

I don't have a PhD, but this is what I've observed.

I suppose it could be like Cicero.

I was thinking more like the Les Grossman character from Tropic Thunder. The character was played by Tom Cruise.

This is true too.

However, many times Engineering teams are asked to build something that is speculative. Leadership and the Product team thinks they are building something that could make money in the future and justify the investment.

Other times folks are building something which is directly attributable to existing customers revenue. It may be that it won't bring in any additional revenue, but it will reduce OPEX and improve the margins of the business.

It's a good idea to understand which type of project they are working on from the business perspective.

I guess that means the fastest way to become better than a 1x engineer is to declare that you are 1x engineer. Makes sense to me!

I think ARR/LOC would be a better metric.

It would be life changing, but it would still be hard to retire on 300K in the US.

> I am quite... what's the English word for someone who gets way too excited from the thrill of gambling and forgoes the caution?

I think degen is the common term that used here. It's short for degenerate.