danbrooks

I agree that we should cut greenhouse gas emissions - but this certainly feels alarmist.

What an amazing ending! :)

Link isn't working for me. Stuck on a captcha.

A big thank you for putting levels.fyi together. It's a big reason that I'm working in tech today.

I had a very similar experience with Amazon and Facebook interviews.

Clearly great news for Facebook employees. For reference, the previous policy was that only level 5+ could request to work remotely.

Agreed, the ProPublica article is quite precise and consistent.

It's also important for slay the spire fanatics to understand the underlying game mechanics.

- The first three fights of act 1 come from an "easier" fight pool. There's a similar mechanic for acts 2 and 3.

- The odds of finding a potion in a hallway fight start at 40%. If you get a potion, the odds go down -10%. Otherwise they go up 10%. After each boss fight, the odds reset to 40%.

- The odds of getting a rare card from a combat card reward start at -2% (per card) and increase 1% every time a common card is offered.

- You are not offered upgraded cards in act 1. At high ascension, this increases to 12.5% in act 2 and 25% in act 3.

Insight is good for PhDs.

Job candidates could die to biters during an interview! This needs to be tried once (and posted to youtube)! Preferably on max difficulty.

I would guess that it's a reaction to job title hype.

There's a huge variety in DS responsibility and background between companies.

I'm starting at Facebook in two weeks.

I was looking forward to the branded swag too...

It's standard practice to check in with stakeholders before submitting a paper.

The important issue in the paper seems to be that the paper villainized large language models, which Google has a vested interest in.

The paper was likely publishable with a bit more context in the introduction.

I've been in similar situations and they were handled offline.

The explosiveness of this situation seems to have been prepared the history of Timnit's relationship with Google.

This incident was just the spark.

Admission is fairly selective and focuses on interest, ability, and accomplishment in math and science.

There certainly are significant differences between individuals, but nearly everyone is smart and scientifically motivated.

Exams are generally take home.

Students are expected to follow the exam instructions on the honor system.

It's a refreshing change of pace to take exams when and where it's convenient.

That sounds a lot like working at a startup!

I work in the AV space. There's a lot of ambiguity in labeling.

How should a crowd of people be annotated? A line of parked cars? A photograph of a car?

Examine the training set!

Karpathy is building the NN backend in PyTorch, for which C++ is the most popular deployment language.

This reads like a list of complaints about Django. There's much, much more to python than Django!

Yes, Schwab does allow fractional shares.

"I have no desire to become a professor/researcher. After I acquire my PhD, I surmise that I would go to industry."

Go for industry!

I am doing OK, thank you for asking. I recently graduated from a PhD program and am learning more about ML applications in industry.

Nice work! One comment - the plots show the fraction (not percentage) of postings for interns and remote workers.

A strong letter of recommendation with a few publications is definitely strongest.

Black is my favorite auto formatter. I use it for python scripts and blackcellmagic for jupyter notebooks.

My sense is that Riot executive are supportive of making a change. Legal, on the other hand, might not want to restart arbitrations and rewrite contracts.

You will get there. Keep interviewing and learn what companies look for in a candidate. It's a bit of a numbers game to land a full time job and it can take some perseverance.

It's nice to see a civil protest. Both sides seemed interested in compromise and moving the company forward.

PhD in Applied Physics, 2018

Working on data science/ML now.

Started undergrad in 2008 and had to decide between CS and engineering physics. Went with the latter because the school had a particularly strong program.

Applied for PhD programs and national lab positions in 2012. The PhD route seemed more interesting, so I went with that. Ended up spending 6 years on materials simulation.

My peer group ended up going to academia, software engineering, and data science. Technology companies seemed exciting so I interviewed for software engineering and data science roles. Ended up with a company that predicts accident risk from driving data.

I think that physicists are particularly well suited to the machine learning space. I was trained to work systematically work through problems with no analytic solution through clever approximations. This tenacity can help with tackling problems in the machine learning space.

Best part of my day!