zug_zug

> that many of those with the lowest intake of treats were on a diet due to bad health

I haven't read this study, but any study that isn't complete garbage normally would examine the to groups across all variables (age, gender, weight, health, etc) and deliberately control for any systematic differences between groups.

If we had what I described then we wouldn't have fake honey on shelves.

Tests are less useful on features that may be canceled soon.

Tests are more valuable on more complex codebases.

Local tests (shifting left) is more valuable when deploying is hard/infrequent and screwing up prod has higher stakes.

These factors explain why most startups should code differently than big corps.

I think the FDA should build towards mass food analysis. To sell something en masse you should have to put down a deposit, and the FDA should do an annual analysis of your food (via mass spectometry) from samples from the food store. They should mix dozens of samples from different states to get good coverage.

Should you fail (illegal pesticides, ingredients differ than label, too much lead, whatever) then you lose your deposit, all profits made that year on that product, and go through a process of re-earning the right to sell that product.

For small local brands I'd exempt them until the economics became viable.

Curios if anybody can explain what a 2:4 sparsity pattern is. Are the 2 to be removed picked randomly?

Really? It seems obvious to me.

During the learning stage we want input from every variable so that we are sure that we don't omit a variable that turns out to be essential for the calculation. However in any calculation a human does 99.9999% of variables are irrelevant (e.g. what day of the week it is, am I sleepy, etc), so of course the brain wouldn't use resources to keep connections that aren't relevant to a given function. Imagine what a liability it would be if we have had excessive direct connections from our visual processing system to the piece of our brain that controls heartrate.

I like this idea. I think we can dismiss the most literal/extreme interpretation of this (as most commenters seem to be doing), but when I look at most of us I find we are more likely to forecast with overconfidence than underconfidence (tech X will destroy the company, or NOT using x will destroy the company).

I remember working at a place and our whole data-team (myself included) seemed like a useless waste a dozen engineers. I thought the company was adrift. A few years later it was bought for billions of dollars because the business people knew exactly how to threaten a dominant player in the market. And I realized my henny-penny attitude was complete noise, I just was out-of-the-loop about what the long-term play was.

I think a lot of this is that we each want to be the center of our own universe, we want our problems to be the THE problems, and to some degree understand that peddling our advice about tech X or Y is to some degree advancing our own influence.

> You don't PIP a lower performing staff unless they're completely useless or toxic

Maybe this is part of the problem -- that it's called one thing (a plan to improve performance) but is used as another (legalese once you've already given up hope).

But I've never quite understood why. I imagine if I was a manager people would know if they are doing 20% as much as the best team member and would either be off the team or have shaped up within 6 months. That period where you genuinely are making sure that somebody understands you think they aren't doing well and clarify expectations seems valuable and ideally would happen long before it's too late.

I'm having trouble understanding all the upvotes for a wall of buzzwords from across-fields. Would love to understand what this even is in plain english if somebody has the time.

and interestingly they say they share their data, but after looking through the data I don't see what I'm looking for, which is closest-approximate words for each celebrity.

> Lonely individuals tend to think and talk in an unusual way, study finds

That's not really what this article finds... the title is "Loneliness corresponds with neural representations and language use that deviate from shared cultural perceptions", but even that title is too general when it's only talking about a handful of pop-culture celebrities.

And also, remember when a researcher says "loneliness" they mean "self-reported loneliness," I know a lot of people with very little companionship who might insist they are a 0 out of 10 on the loneliness scale.

There's so many different ways to interpret this data:

Perhaps people who are willing to admit they are lonely (usually something that's very mildly frowned upon in my experience) are more willing to break with social norms. Or perhaps having wild takes on reality results in you becoming lonelier. Or perhaps a few outlier individuals really pushed the average. Or perhaps people who are less lonely are generally more knowledgeable/well-informed about these individuals. Etc etc.

> If you answer yes to many of those questions there's really no better alternative than k8s.

Nah, most of that list is basically free for any company that uses an amazon loadbalancer and an autoscale group. In terms of likeliness of incidents, time, and cost, those will each be an order of magnitude higher with a team of kubernetes engineers than less complex setup.

We are using EKS

> I can't see how it can take 4 months to figure it out.

Well have you ever tried moving a company with a dozen services onto kubernetes piece-by-piece, with zero downtime? How long would it take you to correctly move and test every permission, environment variable, and issue you run into?

Then if you get a single setting wrong (e.g. memory size) and don't load-test with realistic traffic, you bring down production, potentially lose customers, and have to do a public post-mortem about your mistakes? [true story for current employer]

I don't see how anybody says they'd move a large company to kubernetes in such an environment in a few months with no screwups and solid testing.

For what it's worth, I've worked at multiple places that ran shell scripts just fine for their deploys.

- One had only 2 services [php] and ran over 1 billion requests a day. Deploy was trivial, ssh some new files to the server and run a migration, 0 downtime.

- One was in an industry that didn't need "Webscale" (retirement accounts). Prod deploys were just docker commands run by jenkins. We ran two servers per service from the day I joined the day I left 4 years later (3x growth), and ultimately removed one service and one database during all that growth.

Another outstanding thing about both of these places was that we had all the testing environments you need, on-demand, in minutes.

The place I'm at now is trying to do kubernetes and is failing miserably (ongoing nightmare 4 months in and probably at least 8 to go, when it was allegedly supposed to only take 3 total). It has one shared test environment that it takes 3-hours to see your changes in.

I don't fault kubernetes directly, I fault the overall complexity. But at the end of the day kubernetes feels like complexity trying to abstract over complexity, and often I find that's less successful that removing complexity in the first place.

The interesting thing in my mind is how dysfunctional I've found reporting chains' behavior (to the company). I've found the same thing others here have found -- certain cultural backgrounds or a large preponderance of H1Bs create a culture where upward feedback is silenced.

And in the end usually the company loses out - directors forge ahead with ill-informed projects (rewrite entire system X), don't measure/cherry-pick/game-metrics, and create a major threat to anybody on the team who surfaces any contraindicating metrics (e.g. "Our pipeline still takes Y hours and nobody is happy about it, including us").

Well there are two appropriate action--

Jail time to the CEO of that compary for fraud (because it wasn't FDIC insured) or full reimbursement of all creditors.

I'm okay with either, but if neither of those happens then it's a failing system.

I came here to write the same thing. Getting an estimate accurate for at least 5 digits on all netflix video watches worldwide can all be done with intelligent sampling (like hyperloglog) and likely one macbook air as the backend. And aside from the compute save the complexity and implementation time would be much lower too.

It always felt like such a contradiction that police could lie to you but had to read you your miranda rights.

Apparently police are allowed some threshold of deception (e.g. can outright lie but can't pretend to be your lawyer) but since 99% of people don't know this it really undermines the purpose.

Like if the police can lie, but tell you that you get an attorney, how is a client supposed to know that your lawyer can't lie to you too?

I never understood articles trying to put objective criteria on a system that’s as much a function of supply and demand as any inherent ability. Most companies have set percentages for titles and promotions, regardless of actual abilities.

That's a good point. I imagine this advice would be actively bad advice for building more complicated things (e.g. an IDE, perhaps a game, a turbotax alternative).

Part of the skill of engineering is knowing when you need to do upfront engineering and when you can just throw some code at the wall.

Eh, the more I think about it though the more I can think of times that "Going by my gut" when my brain and gut disagreed where my gut was wrong.

Like suppose you're talking to somebody over text and your gut says they're being an asshole, but your brain is rereading what they say and can't find anything specific to call out.

Which is correct?

Well, I've found that the gut is systematically unreliable in a number of situations... Are you in a bad mood for example? They say never go food shopping when you're hungry.

Not to say mind > gut, because that's just as stupid as saying gut > mind. The point is that there are dozens of variables (variables like mood) we need to learn in such evaluations, and generalizations can rarely be useful.

As somebody under that umbrella myself

> soy turning me trans or social media turning me trans I agree is absolutely mind-numbingly naive.

However, I feel like there's only so many options for where sexuality and gender-identity can come from -- and if we know there's no god doing it, and we know it's not entirely learned (because of case studies of surgeons who assigned a gender to babies with ambiguous genitals), the remainder must be from the environment... and it just so happens that almost all of the body's signaling around gender, puberty, and development is chemicals in one form or another.

I believe .codeowners does that

Obviously this is baseless speculation, but I sure do wonder if various psychological conditions that are so diverse and hard to pin down (i.e. 3 out of these 9 symptoms around attention, social behavior, or impulse control) are ultimately just going to be proven to be purely biological. And since genetics can only explain less than half of it, it sure seems that something messing with chemical signaling would be a reasonable explanation for the rest.

How much would I need to reimburse you for giving you Down syndrome, for example

I heard it’s even worse than this: I heard any app can access a list of wireless access point unique IDs your phone is near and that there is a database of enough of these to lookup your location regardless of settings.

Would love to hear confirmation from an iOS developer

Moreover, even if it was say 15% better than git (and I doubt it is), the overhead of moving a whole industry across VCs is billions of dollars of loss.

Every single engineer has to start over in their mastery experience by learning all the new quirks and issues, and all the tools, libraries, pipelines need to be rewritten.

IMO better to support the dominant tooling than invest in fracturing one of the few areas where engineers can agree on something for once (to everyone's benefit).

I guess then my thought is that whether it's one disorder or 4 or any number perhaps is best understood as a statistical question.

For example, if a parent exhibit autism symptom X (e.g. trouble understanding emotions), are there kids more likely to inherit symptom X, or ANY autism symptom.

If X is uniquely heritable, then perhaps it's best as multiple disorders. But if X leads equally likely to X, Y, or Z then it's better understood as one disorder.

I feel like that's saying weather forecasting is voodoo bullshit because it's all quantum mechanics deep down

Maybe you put a 500% tariff (at least, since plastic is such a cheap product) on the most dangerous plastics (the ones that are known to disrupt hormones).

Also a domestic plastic tax - by making plastic less cheap (perhaps have it go up 10% every year in perpetuity) eventually there will be incentives to find natural alternatives (paper, bamboo, woods, etc).

It makes no sense to me to claim the most productive country in all of history, with our AI and everything, couldn't replace plastic. It's the same thing people said about oil 50 years ago.