bxji's comments

There was a third ruling in November 2022 for the case, so I wouldn’t say hiQ won. Based on a quick scan, the ruling ended up being that hiQ did violate TOS but that no action ended up being taken for either side.

https://www.natlawreview.com/article/court-finds-hiq-breache...

Your description of always feeling hungry after keeping it off is rather worrying to me, since I’m getting close to my target weight after a 1 year+ journey of diet and exercise.

I do remember reading before that the fat cells that get created when you gain weight never really go away, they just “deflate”. So after you lose weight, you are more likely to gain the weight back than someone who is at the same weight now but who has never been bigger than that.

I also recall seeing a study that your body sends you extra hunger pangs to gain the weight that you lost back, because it assumes that losing weight means you’re in fight-or-flight mode, so it wants to make sure you survive. That’s why a weight loss drug where an extra 300-400 calories per day were excreted via urine did not show significant results.

I couldn’t find the exact study for the second part. So I’ll just leave a general reference from Northwestern alluding to the same results.

1. https://www.discovermagazine.com/health/your-fat-cells-never...

2. https://www.nm.org/healthbeat/healthy-tips/how-your-body-fig...

Kinesis has a 60-day money back guarantee if you buy from them, minus the cost of shipping. These are also sold on Amazon, which has a really good return policy so you can return the item with no hassle if you don’t end up liking it.

Of course, this is all presuming that

A. You have enough capital to buy the keyboard and are ok with not having $300+ for a month or two

B. you can get used to the keyboard within a 30 day period and get a feel for how you’d like to use it full time

I’m still a little confused on what dbt does after reading the article. Is it like Trino that generates materialized views as output, with built-in version control and other features?

Scale is certainly a part of it.

I work in one of the data platform teams at a social media company. Between our 3 HDFS clusters, we're storing more than an exabyte of data. At our scale, we have to tune our workloads carefully to make sure that problems of scale are not noticeable to internal customers (data scientists, analysts, etc.).

We basically have an entire org of highly paid engineers focused on making sure people can use that data efficiently. So we have a team of people working on storage, on Spark, on Presto/Trino, on data ingestion, and so on.

So my understanding is that we're investing in engineers to improve data science productivity, so that they can do analysis without having to understand the internals of all our systems, so that executives can make informed decisions backed by data to continue printing money. Or something like that...

Funny enough, the model for the cover photo was actually a professor of computer science at my university (recently retired, I believe). I'm a bit surprised that this pocket guide is well-known in the mushroom hunting community.

We hire entry level SREs (new grads) as well. The job listing might have been closed already for this year, though. I also saw a couple junior SRE listings (as in not new grad but not senior level either).

Disclaimer: work for LinkedIn

The goal of these work visas is to hire someone with specialized skills to do work when the company can't find someone with the necessary skills locally. From a quick skim through the DoJ briefing, the argument which the DoJ makes is that Facebook knows that they have more power over employees that depend on them for work visas, and games the system by creating special job listings that only the applicant seeking a visa would know about and apply for.

On an intellectual level, I guess the distinction is in how you define "highly skilled" workers. Are all software engineers considered highly skilled? Or is there a distinction between a general engineer and someone who has experience and expertise in a specific subfield such as mobile development or infrastructure?

My way of thinking about it is with the latter. I would think that the DoJ is not happy with the idea of Facebook jumping through a bunch of hoops (mentioned as making positions invisible on their career site and requiring an application via physical mail while rejecting any U.S. candidates) to guarantee a work visa for someone to do specialized work that the company supposedly couldn't find any qualified Americans for when the person they hired doesn't even know what type of work they'll be doing or what team they'll be joining until after they go through 5-10 weeks of bootcamp, and which may end up not even aligning with their specialization.

Given that new hire engineers at Facebook sign an offer letter and are officially employed while they go through bootcamp before the whole team matching process, I don't think it's possible for someone to not get matched to a team, at worst they would get assigned to a random team with headcount at some point, which would really raise the chances of that person not working in their specialty.

If this assumption is true, the DoJ would definitely not be happy that Facebook was supposedly not able to find a qualified citizen/green card holder to do this job, but the new hire on a visa may not be qualified to do it either and there were most likely citizens/green card holders applicants who actually do have experience in that area of work.

Sorry if this is a bit ramble-y, I'm fairly new to HN.

Correct me if I’m wrong, but Facebook hires people under a generic role (Software Engineer) and then has them choose the team they will join after a “bootcamp” session. So they are not preallocated to a team to fulfill a specific need, and it’s not a direct 1 requisition to 1 person type system. I believe that’s what the above poster was referring to when they mentioned Facebook hiring to be general.

> If you care more about latency than consistency you have an 'eventually consistent' system, where a write will eventually propagate, but a read might get stale data.

Not just stale data, you can also have states which never actually existed. I'll steal the example from Doug Terry's paper "Replicated Data Consistency Explained Through Baseball" because it's really good. Linked below.

Say you have a baseball game which is scored by innings. It's the middle of the 7th inning, and the true write log for the state of the game is as follows:

  Write ("home", 1)
  Write ("visitors", 1)
  Write ("home", 2)
  Write ("home", 3)
  Write ("visitors", 2)
  Write ("home", 4)
  Write ("home", 5)

If you were to read the score at this point in time, and your system is strongly consistent, the score can only be 2-5 or a refusal to serve the request. If your system is eventually consistent, the score can be any of the following: 0-0, 0-1, 0-2, 0-3, 0-4, 0-5, 1-0, 1-1, 1-2, 1-3, 1-4, 1-5, 2-0, 2-1,2-2, 2-3, 2-4, 2-5.

Source paper: https://www.microsoft.com/en-us/research/wp-content/uploads/...

So that's where Gilfoyle got the name Anton from...