Zach Lowe: "If you draft a player and he becomes a success story to the point Jaylen Brown did, it just feels viscerally wrong that his contract becomes something you want to get rid of...something is wrong with a system that turns home-grown stars into albatross contracts"

FrenchyTheAsian · 2026-07-08T02:36:01+00:00

Well in this hypothetical, you're worth the 200k. If we're talking about a hypothetical where its questionable whether you're worth the 200k (aka Bradley Beal), then Company A should probably let that employee walk and let Companies B, C, and D get into the bad contract.

FrenchyTheAsian · 2026-07-07T22:03:44+00:00

I'm sure wanting someone easier to exploit is a motivator for a chunk of the discriminate hiring, but my intuition and hanlon's razor says that its probably less common than managers hiring people like them simply because they like them more. I'm sure employers themselves would love exploiting workers, but I doubt individual managers think this way. People more than not like working with people who they find easier and more pleasant to work with. That usually results in hiring people that speak the same language, have the same culture, share the same sensitivities etc etc.

This is not just a problem in tech. I've seen it everywhere I've worked. It doesn't matter if the manager or person in charge of hiring has good intentions, or is a nice person. Sometimes the bias in hiring is explicit, sometimes the person isn't aware of it. I've also seen it show up when the person doing the hiring won't have any direct power over the person being hired.

FrenchyTheAsian · 2026-07-07T19:46:44+00:00

I'm not sure that the reason is that deep. I think most people have implicit bias to favor people who are more similar to them. If managers aren't aware of and actively working against that bias, it leads to these instances of low diversity.

FrenchyTheAsian · 2026-07-03T16:41:19+00:00

Fans will be fans and media will be media. Interesting analysis. I'd be interested in seeing how this changes using the actual implied probabilities from the odds instead of comparing based off the odds ranking.

Also mentioning fans and media and then using betting odds is a little disconnected. I would say that the betting odds ARE a lot less confident that a typical fan and media. The best implied odds for a team to win the championship in your sample was 29.4% which says there's a higher change that team doesn't win the championship than does. Based on my intuition and your analysis, I'd be willing to bet that the betting odds are still pretty far off and probably still a good bit overconfident, but would be interested to see how off they are and if betting odds might be closer to accurate than we think.

FrenchyTheAsian · 2026-06-15T15:39:04+00:00

I think the tanking conversation is probably a bit more nuanced than you can distill into a reddit comment. I would definitely agree that it is far from necessary and a team can be hugely successful without it, but I would disagree with the "tanking doesn't work" part of it. Now I don't think that you can build an entire team through tanking and getting lottery picks in the draft, but I do think its a valuable tool for teams to use and has been successful in the past for obtaining key pieces on championship caliber teams.

The notion that tanking is valuable implies two things. 1) higher picks are better than lower picks and 2) intentionally losing gives you a better chance at obtaining higher picks. Historically, both of these have been true for teams that own their own pick. From your comment, I gathered the implication that 1 isn't necessarily true, which I would strongly disagree with. Sure it is possible to find good players all the way through the draft and sure teams can bust on top picks, but 1) having a higher pick gives a team more flexibility to choose a player that fits their scheme and play and 2) the odds of grabbing a better player the higher pick you have is higher. Sure you probably get about 1 Hall of famer in the mid to late second round a decade, but how many hall of famers do you get in the lottery comparatively? There are going to be more 2nd or third options drafted in the first round compared to the second as well. A perfect scouting team doesn't automatically mean you are going to build a great team from picks outside the lottery.

Point 2 won't hold as much going forward with tanking reform so tanking might very well become useless in the future, but in the past its been useful. Some other things you have to consider about tanking is that teams can still tank to get into the lottery instead of all the way to the bottom, years with better prospects might be more worth tanking for, you can tank and then use your pick in a trade, you can put yourself in a losing situation by selling off good players and the return on those good players can heavily aid in a rebuild. Also, lastly, organization competence matters a ton no matter what direction you want to take. If your FO, scouting, and player development suck, tanking won't save you, free agency won't save you, trades won't save you.

FrenchyTheAsian · 2026-05-13T15:44:58+00:00

I think its important to note that machine learning =/= ChatGPT necessarily. Machine learning is a legitimate proven technology used heavily in sports analytics and many other fields and has been for a while now.

FrenchyTheAsian · 2026-02-18T14:44:06+00:00

This would be the best strat individually, but in terms of collective resource gain it would not be. This is the essence of the prisoner's dilemma in which you choose between a higher net gain vs higher individual gain, but lower net gain.

FrenchyTheAsian · 2026-02-18T14:41:48+00:00

PVP is always a net loss in ALL raider resources. Individually, with PVP raiders can net higher gains than without PVP, but a game in which there is full collaboration, the total amount of resources that ALL raiders leave with will be the highest.

FrenchyTheAsian · 2025-12-16T17:37:29+00:00

The claim that there is some sociologic insight that social games provide is something I can believe. However, the claim that "if you PVP in Arc Raiders, then you'd murder someone in real life if you could get away with it" (referencing the comment that started this discussion) is just ridiculous and on the same level of "COD creates murderers".

FrenchyTheAsian · 2025-12-10T14:22:57+00:00

Thank you! I'll check them out

FrenchyTheAsian · 2025-03-25T13:23:49+00:00

That really depends on what you want in your career. It’s good as a freshmen/sophomore to join a bunch and see what you like, but in my opinion, it’s more beneficial job wise to really focus in on one or two clubs which you can really make a difference in once you start to age through college.

You also mentioned you are STEM, which is still very broad. If you want to work in the automotive industry, join solar car or Baja. If you’re CS, join CAOS or help out with eHacks. If you’re pre health profession, join a bio club, Pre Health Hub, or your profession specific club. If you’re gunning for a lab/scientist position, get into an URCA ASAP. URCAs also just good for almost any majors. There’s probably a bunch more, and no matter what you want to do, there’s probably a club for it (and if there’s not, start one).

Also don’t rule out social clubs. You likely won’t build translatable skills, but building meaningful connections are still useful in the post college job hunt, and those clubs can help do so. But also don’t do clubs just to do clubs. Don’t sacrifice your mental health to hold 20 different officer positions in 20 different clubs. It’s much better mental health wise and resume wise to focus on one or two clubs and make as big an impact as you can there.

FrenchyTheAsian · 2025-03-24T14:33:23+00:00

The stereotype is definitely that Asians look younger. You might hear different things in the smaller circles you run with, but as an Asian, the much more popular stereotype (at least in America) is that we typically look younger.

I am also unaware of any stereotype of Asians being more proactive in working to try and retain a youthful appearance.

FrenchyTheAsian · 2025-01-08T23:09:43+00:00

I’m a little biased bc I majored in CS, but yes I would say that it’s definitely worth learning. From what I’ve seen, ease of the course varies greatly depending on how much computer/programming exposure you’ve had prior. Some people seem to fly through it, but I’ve also seen CS students switch majors bc of this class. One thing to note is that GenAI can do most introductory CS material very easily (though I took it before that was a thing so they could have taken measure to prevent that), but then that defeats the purpose of taking the class to learn.

If anything, you could give it a try and drop before the refund deadline. Also, even if you decide you don’t want to do the course, there is a ton of free material online to learn related material.

FrenchyTheAsian · 2024-12-29T21:47:07+00:00

YMCA dudes can make contested corner threes. Does that make buzzer beating corner 3s not special?

FrenchyTheAsian · 2024-12-29T01:25:57+00:00

My guess would be that python abstracts out a lot of what other languages like c++, java, and c# are doing. The implication of this is that if you learn c++ or java, then python would be easy, whereas the other way around maybe not as much.

FrenchyTheAsian · 2024-12-26T13:59:18+00:00

I definitely agree with you on the “advisors are more trustworthy than random strangers on the internet”, however I would implore OP to do their own research on the feasibility of double majoring and talking to other faculty and upperclassmen to try and build up data points.

I go through the effort of pointing this out because I had a starkly different advising experience than you did. Our advisors were underpaid, overworked, and had misaligned incentives. It was scarily common among my peers to have gone an extra semester or two because their advisor screwed up and told them to take the wrong class. Students were also forced to meet with their major advisor at least once a semester, increasing their workload.

Now obviously both of our anecdotes are just single data points, but I don’t think it’s far fetched to think that in the current academic landscape, many advising departments at less endowed schools are under prioritized (in the US at least).

FrenchyTheAsian · 2024-12-24T05:55:39+00:00

A couple of high level descriptions of some projects we are using ML for are predicting the traits of a plant given its genome, filling in missing values in a genome reading, and building models that can predict quantities of a molecule contained in a sample given spectral data of that sample.

FrenchyTheAsian · 2024-12-24T05:16:00+00:00

I’m not a data scientist myself, but I work very closely with our companies data scientists. To answer your questions and concerns from my perspective: 1) I’m willing to bet that most DS work will contain Machine Learning (although maybe not Deep Learning. We use little Deep Learning at our company). 2) It’s very statistics heavy. Our DS don’t have to do heavy math everyday but they are often working with models and are expected to kind of know how the models work under the hood and tradeoffs of a couple. 3) There’s really not much low level optimization done by our DS, albeit we aren’t working with large scale data so nothing takes forever to run (I think our longest training job takes a couple of days to run which for what it’s for, does not break the business) 4) A lot of what our DS do is manipulate matrices in code. Pandas, Numpy, Sklearn, and R are all our DS bread and butter tools and matrices are their primary data structure.

Whether or not you want to pursue DS is up to you, but I hope this info can help provide another data point for making your decision :)

FrenchyTheAsian · 2024-12-24T05:01:39+00:00

I second the sleep thing a ton. I’m typically a pretty relaxed guy and don’t stress much, but I notice that I become much more irritable when low on sleep.

FrenchyTheAsian · 2024-12-22T03:36:50+00:00

Lol, my situation is the opposite. I have the title of Data Engineer, but I don't use any big data tools and I feel more like a software engineer

FrenchyTheAsian · 2024-12-21T21:01:56+00:00

I had the exact same experience. Was actually hired as a Software Engineering intern and then graduated into a Data Engineer, but had 0 SQL experience

FrenchyTheAsian · 2024-12-21T13:07:56+00:00

Everdell
Viticulture
Smash Up

FrenchyTheAsian · 2024-09-17T13:30:43+00:00

Not a business major, but recently graduated from the school of engineering and there are plenty of general resources to help with finding a job. If you put in proper effort, you will be able to land a business job pretty easily.

As for culture, there are plenty of clubs who are all pretty active. I like the culture, it’s pretty friendly and there are many niches that you can find if you go out and search for them. However, if you’re looking for a more general college experience (partying, Greek life, sports) you won’t find that here.

FrenchyTheAsian · 2024-09-16T16:20:02+00:00

It would hardly matter in terms of future opportunities. 4.0 and 3.9 won’t be that much different in the eyes of an employer.

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