skysight-inc/HackerNews huggingface dataset:
hm. i think it is "just porn" with just a few performers making money otherwise too. the novelty of the content makes up for the competition from free sites
But after that I'll put in creative weird things as they come to my mind. But the author is kind of attempting to be an arbiter of 'what is art' which I find ultimately absurd.
> Like, I get it, they’re going for the whales who’ll waste loads of cash on “games” that just swallow coins

It's the "pachinkization" of videogames, which is ironic considering how pachinko machines try so hard to look like videogames.
>Could it be that you hesitate to "write" because you've accurately "read" the room?

And because you don't try (or try less often), you don't have as much experience with it.
Increasing ecommerce revenue for tech savvy wine merchants
I understand your way of thinking, but we ended up having a flow for a government site where users had 2-3 steps what normally could be done in 1. Also many were not tech savvy and confused. So we ended up adding JS to automate the click.
This article? Didn't read anything like that although I just skimmed it. Be that as it may, people often associate onlyfans with sex work.
Jacob Preston (ex-Apple Firmware Engineer), Ashley Gjøvik (Apple Senior Engineering Program Manager) and Zoë Schiffer (Verge senior reporter) in the linked Twitter thread all seem to be claiming that Apple tells employees to merge their accounts. Encouraging use of a work iPhone as a personal device to "dogfood" is also mentioned.

It's a big company though, so possible that policy varies.
Taking Git out of the workflow is scary. That makes any alternative to it exciting. Nice work!
> (...) as if you were ethically responsible for the model only.

The model is the result and the outcome of the whole process. The model is supposed to be a reliable representation of reality that has acceptable accuracy within predetermined operational limits.

If someone tries to generate models that interpolate and/or extrapolate data and the data it uses to seed the model is garbage then the model is garbage, and the person responsible for putting it together is the person responsible for the model failing to do its job.

There is no separation between model and the data used to generate the model. Garbage in, garbage out. If a machine learning model uses garbage data then the model is garbage, and throwing machine learning buzzwords at the problem does not justify why garbage was sent in.
But I do agree with that some of these Services should just block certain keywords... I can't say any of the keywords here but there are single words that you could put into a lot of these generators that should just automatically be like not accepted.
> I've also lived in South Korea and visit quite often (only a 2 hour flight). The arcade scene is HUGE.

I wonder what the difference is. Just a tax thing, or novelty...?
Rational emotive behavior therapy (REBT) - Using logic to unravel how your beliefs interact with your circumstances to create negative emotions and then letting go of dysfunctional beliefs to attenuate those negative emotions. Started by applying to myself and then helping teach them to others
The classic algorithm to solve the https://en.wikipedia.org/wiki/Stable_marriage_problem is a pretty straightforward and frankly introductory-level example of an algorithm which is not impartial (and not just because it ought to be called the stable heterosexual monogamous marriage problem).

The algorithm outputs a matching between two sets A and B (e.g., bachelors and bachelorettes) where each member of set A has ranked each member of set B in preference order and vice versa. The output is called stable because there's no situation where any pair would prefer to be with each other than their current partners, e.g., there's never a case where Alice prefers Bob to her current partner and Bob prefers Alice to his current partner and are tempted to run away with each other.

But a curious property of this algorithm is that the matching is always best for one group and always worst for the other. Of the possible answers to the problem, this algorithm an answer that is at least as good for set A as any other one, and at least as bad for set B as any other one. You can, of course, flip sets A and B when running the algorithm, and it will them be optimal for set B and pessimal for set A.

This has absolutely nothing to do with ML or data fitting or anything. It's a deterministic, classical algorithm. And yet it is clearly partial, and you must choose when using it whether to be partial to set A or set B, to the men or to the women, to med school students or to their employers, etc. It would be silly to say that the algorithm is impartial and that it's solely the operator's choice to make it impartial - this particular algorithm forces the operator to make some choice.

I think in the end you're agreeing with the author, who is saying that you must make a tradeoff of some sort, and the question is which tradeoff to choose. The author (and I) would describe that as the algorithm being partial, and the operator only being able to make some choice about what to do with that.
> It's just like Myers Briggs Personality test

Oof.
All those manufacturing woes that happened after Elon tried to automate everything in the manufacturing process https://www.cnbc.com/2018/04/13/elon-musk-admits-humans-are-...
> The decisionmaker at a company knows he needs someone. He tells his friends and business contacts. One of them knows someone — family, a roommate from college, someone they met at a conference, an ex-colleague, whatever. Introductions are made, a meeting happens, and they achieve agreement in principle on the job offer.

Must be an American thing.
Where I'm from this screams "did not practice due diligence", which is a big management ouchie.
Yet another problem with that quote is that generations are in fact different. Some of them are more violent then others. Some of them drink more then others. Some of them are more submissive then others. Sometimes, kids are raised to be assertive, other times they are raised to obey.

This quote is used to devalue anyone who points out some difference between now and then. But, it does not prove that such person is wrong.
One thing to note is that Chromium and other Google projects are HUGE codebases; most codebases of people thinking about multi- or monorepos, microservices or monoliths, etc only WISH they had the scale of code and developers that companies like Google have.

All I'm saying is, beware of cargo cult thinking. Do something because you need it, it's practical, it's faster, not because someone else does it. I've had a few projects that were intentionally difficult because Someone decided to make it a microservices architecture, but in a monorepo to encourage the distributed monolith idea.
You're assuming narcissism as the main cause, but it could easily be stuff like "that new weird zit that's just propped up that you can't quite self-examine without taking a picture of". Or tracking weight loss. Or anything really.

As for "leave them on the phone", again you seem to assume explicit intent, but it's more likely to be a bit like leaving your underwear on the floor for a few hours when not expecting guests because you can't be bothered to tidy up just yet.

Then one day a child in the neighbourhood goes missing, SWAT raids your house due to an anonymous tip (likely by the murderer themselves), the press spots your underwear, and next thing you know you're called "The Underwear Killer" in the press.
A social psychologist examines an individual in group dynamics and interpersonal relationships. It is still focused on the individual. Thing like personal prejudice, the sense of belonging, implicit bias, and effects of bullying are what social psychologist study.

On hacker news I expect the consequence of moving away from physical relationships to digital relationships, otaku, and parasocial relationships are pretty fascinating topics that fall under the research of social psychology.

It's different from sociology because it's focused on the individual. Sociology would instead be focused on the development of groups as a whole.

I am assuming by asocial you're referring to otaku as a concept and not someone's trauma response.
Accurate hardware/software development timelines are an unsolved problem.

To me, the question is: is the technology getting better over time? And from what I've seen I would answer that question with a resounding yes.
The Truths of Building a Must-Have SaaS
This is where you build a UX around buying some crypto-token in the check-out flow via a simple redirect to a partner, fix your credit card issue, and the partner immediately gets you a USDC transfer after charging the credit card.

Yes, there are companies out there that will do this.
It's sad that I have to ask, and I may become pretty lonely because of it, but has this study been replicated in the meantime?

...

https://en.wikipedia.org/wiki/Replication_crisis

Just asking.
Why drug names are so increasingly weird
I am really not convinced of the need of any incremental build system (like Bazel) over Nix excepted if you inherited of a giant mono-repo mess.

Decomposing your dependency tree into small derivation pose no problem with Nix. Mainly due to the fact it solves entirely the ABI problem and the diamond dependency problem.

You can also simulate incremental build in Nix-only by using multiple derivations over a single source tree and combine them together.

Using a gigantic pile of complexity like Bazel just for that seems kind of an overkill to me. No offense, I am just challenging here :)
I can’t wait for Tesla Bot to veer off the path with my shopping and fall in a river.
Are the pros ready to switch to smartphones? (survey)
As is very clearly stated in the page you linked to: "It does not include the mass that is lost when glaciers calve off icebergs and melt as they come into contact with warm seawater."

There has of course been no "recovery". You can see the Greenland Ice Sheet loss at: https://grace.jpl.nasa.gov/resources/30/greenland-ice-loss-2...

This one is a continual talking point for climate change deniers, and is corrected every time, but it still gets trotted out. I strongly advise you to actually learn something about this topic as I've seen you attempt to post on it before.
Hi, Zoekt author here.

There are a bunch of interesting replies, but they all miss the point.

The reason you can't use bytes is a combination of two things:

(1) code search supports case-insensitive matching.

(2) the search algorithm uses distance between trigram occurrences to reduce the number of matches.

With UTF-8, different case flavors of a character have different widths. For example, k (ascii k, 1 byte), K (ascii K, 1 byte) and K (unicode U+212A for Kelvin, 3 bytes). This messes up algorithm (2).

The same consideration holds if you want to support searches where "a" also matches "á" and "ã".

I did a talk on exactly this subject in 2017, which goes into more detail. The bit that explains it is here, https://youtu.be/_-KTAvgJYdI?t=602 . If you have more time, you can watch the entire thing, as it is entertaining, if I may say so :)
> Most of the best developers I know would fail a technical interview for their current job.

Yes, that's because they can't code.

(No, connecting APIs and navigating information complexity landmines isn't coding.)
How I interpreted these before seeing this comment and its children:

> OnlyFans bans porn: over 1000 comments.

> Tesla announces humanoid robot: 190 comments.

> Rain: 1 comment, after 7 hours.
How Much Computational Power Does It Take to Match the Human Brain?
Why? I mean, what are current problems with making this work?
Hardware/mechanical part? Software? Energy source? All of those? I would assume it's software, same as with level5 self driving (?)
Rig CNC
There is still no car that closely challenges 2012 Model S. Tesla has a production problem not a demand problem.
Like.... today, or ever?

That was an awful answer.

I'm going with the lead of Reality Platform just admitted they have only ever done ~3 meetings in VR.

And OT what's with kids like this being so unprofessional on Twitter? The only imaginative thing the Facebook lead of AR can mention on Twitter is their politics, in a pretty unimaginative retweet way. No wonder software is doomed.
Create a "click here" button, hide it by adding it a class or a style with JS.
Western Union suspend its services in Afghanistan
> Any downstream library team can instantly tell if their change has broken any upstream users because a good CI system will just automatically run all tests of all relevant projects. That way a library developer can either iterate until all projects depending on it are green, or the library developer can even proactively change all dependant projects and roll all fixes out in a single atomic commit.

Any proper (recent) package manager will do the same with a good CI without having any of the mono-repo disadvantages ( duplicated libraries, diamond dependency mess ).

The only real advantage of mono repo is that editing simultaneously multiple software components with API breaking changes is made easier, much easier.
High Score Girl
I can't believe Apple blew her off like that.
Many here are in the throws of this "data mythology"...

It is trivial for algorithms to introduce novel racism: consider processing text analysing minority causes. These texts contain statistical associations between politically sensitive terms, negative terms, (and so on). However they are not racist, are not born of any racist project, and most humans reading them would be moved to more positively regard racial terms. The meaning text express consists in what they want their readers to do. It is an activity of coordination (writer/reader); and it here it has no racist aspect.

A machine if it should have learned anything at all from this text, should learn to associate minority terms with virtuous political projects; it should have acquired an understanding of the many types of associative relation: needing, wanting, opposing, supporting, trusting, advocating...

Yet a machine performing an action based on statistical associations will not learn these; and so, will act prejudicially. It will merely expect terms to co-occur, wholly unable to determine why. We expect charity workers to be greedy? No, we expect them to morally oppose greed. We expect movies to smell like candy? No, we expect them to be sold together. (And so on.)

It is somewhat alarming that statistical associations in terms in historical texts are being seen as characteristic of human communication, meaning, belief, association, ethics, action. I think it has led here to a great moral oversight: that absent the ability to understand text, machines here are introducing novel prejudice where none existed prior.
I presume robots.txt is still ignored in this case?
This also server as a pretext to deeply search someone's device. So you must expect your device getting randomly searched by law enforcement. Completely ridiculous.
The questions are fairly complex, so I could easily see that people better at reading comprehension, and people who generally read more, will answer better.

Additionally, the correct answers maybe compromised, since social psychology is one of the worst offenders in the replication crisis.
A movie served via DNS. Cool!
I scored 34, but I just used the rule of thumb - people are stupid, particularly in groups.
This study isn't about the relationship in both directions. It's only really saying that lonely people might have a implicitly better understanding on the bigger trends that will face society. A total of six studies were examined.

https://econtent.hogrefe.com/doi/full/10.1027/1864-9335/a000...
Not if gmail always follows (image) links in emails, regardless of whether the recipient address belongs to anyone.

Then it’s all noise.
Turing's paper, "The Chemical Basis of Morphogenesis": http://www.dna.caltech.edu/courses/cs191/paperscs191/turing....
There is one, see pp.c.
In this context putting money into Finance means investing it through Wall Street via a range of their products such as derivatives/options trading, currency trading, HFT what have you. You could say making money through speculative assets and you won't be far off.

In other words Finance here refers to investing money not directly in real economy, such as building factories, houses etc., but in speculative products such as I listed above. It is possible that the money so invested in Finance somehow eventually makes it to the real economy. But since late 20th century the size of Finance relative to Real Economy has exploded. Multiple trillions of dollars worth of products are traded each day in Financial markets but in real economy (i.e., people buying/selling goods/services) only a fraction of that amount changes hands. So there is a growing disconnect between Finance and Real economy; which is why Wallet Street (Finance) and Main Street (real economy) have grown so much apart.

Coming to Trump and Real Estate. For a real estate builder, their domain expertise is around forecasting future needs and invest in building houses/office spaces. They invest some of their own money, borrow some from banks, build houses, sell for profit, repay banks and pocket some of that profit. So this part is well understood.

A builder can do well only when millions of people are earning well and are able to buy/rent their buildings. Falling wages is a really bad news for real estate firms. As Graeber says in that video, you can not export real estate buildings. So for them to do well the domestic real economy must do well. The Finance sector however has no such constraints. At the shortest of notice they can seamlessly move their money across the border chasing higher returns. There are times when Finance feels the effects of worsening real economy however as we saw in 2008 when falling housing prices (which were artificially inflated to being with, thanks to speculation) lead to Wall Street crisis.

I usually don't trust Wikipedia now a days but it does have good content in this case[1].

[1] https://en.wikipedia.org/wiki/Financialization
That's still stupid - surely the solution is to moderate better, not to literally kill the company.
This is Finland. That declaration is basically what they are checking but you are not trusted to declare it yourself.

I don't know how important the permanent thing is or if it is tbh. Here it is not possible to claim salary-linked unemployment benefits (which on paper are actually quite generous) unless you have worked for some period of time (6 months or so in some larger period) even if you are as Finnish as can be.

The thing is, there are many 'soft' things that rely on that registration going through, eg. bank account[1], even a local-priced transport pass.

[1]A Finnish bank account here is more than a place to stash money, it's proof of your ID online to any of the nice e-government services.
Having had no psychology course, books, or other education, I get a 35/40 (97.3%).

Most of these sundry facts I suspect I learned by osmosis after spending too much time on the internet — but I would never have called myself a natural psychologist, so I don't know how much predictive power this study really has =)
Also, there's a difference. You upload stuff to someone's server' if they don't vet it, they become accomplices. Apple intrudes on what you do on your phone, this, among other things, tells that you paid mad bucks for this phone and you don't even own it, you rent it from your phonelord Apple. Also, in their eyes you're suspect and likely a filthy pedo.
To be fair, Google, Facebook, et al chose to have monorepos when they were startups, so it's not necessarily cargo culting to look at what they did. I'd argue part of the success was cultural - with everything in one repo there isn't generally specific folders which are restricted in these large codebases, and that helps with a bunch of things.
Very difficult for a person that only ever copy-pasted existing code into an IDE and fixed the squiggly lines by trial and error.

(And remember that "senior" only references to years of experience; if you have 10 years of copy-paste experience, then congratulations, you're now a "senior".)
You are right that there are no algorithms which capture semantics, and therefore none which can be constructed not to introduce bias.

In that sense it is a "data solution", but it is not a data problem.

> de-biasing the data

The issue isnt statistical bias. The issue is semantic: occurrence doesnt capture meaning. Negative terms and racial terms can co-occur more frequently in some text (eg., a biography of MLK) without the remedy being to "rebalance them with positive terms".
I see, I was thinking about instances where it crashes into pillars which would be pretty obvious case for disgareement between vision and LIDAR. It would alert the driver to take control instead to crashing into it. Tesla autopilot has some scary corner cases where LIDAR can be a backup system for human intervention. But, for FSD level 5 - it's a different story.
Show HN: Deploy Empathy A practical guide to interviewing customers
Maybe GP means that satisfying emotional needs could be the rational choice.
Shouldn’t Stripe be big enough at this point to have some leverage as a customer?
> The models are neutral.

Models are not neutral. All models encode inbuilt priors reflecting some inherent bias. In fact, absent that bias a model would have little to no generalizability beyond its training set!
China Passes One of the World’s Strictest Data-Privacy Laws
I think there's a reasonable insight in the article, though, that there are two different kinds of potential data set bias.

One potential bias is, say, that a data set of loans shows that in a certain city, people born in one neighborhood are more likely to pay back large loans without defaulting than people born in another neighborhood. An algorithm could, based on this data, conclude that it should not issue large loans to anyone from the second neighborhood, because it lacks data that those people are usually but not always poorer, and thereby encode bias based on place of birth.

But the paper is talking about a different kind of bias, say, that a data set of loans has thousands of data points of people born in the first neighborhood and tens of data points of people born in the second neighborhood. Even if you were to control for economic status (or perhaps explicitly control for things like ethnicity), an algorithm that performs well on the data set as a whole might perform poorly on the particular subset of people born in the second neighborhood, simply because it has less data. The algorithm might have an acceptable (to its human supervisors) false-positive rate rejecting loans to people born in the first neighborhood, but the exact same model might have a much higher false-positive rate to people born in the second neighborhood.

That's different, and that effect could apply even if people in the second neighborhood were just as good as paying back loans, because you have fewer items in your sample and so there's more noise. That's what the section "Measuring complex trade-offs" is about.
I honestly don't mind going without C const (compared to C++ where it is more useful).
Yeah, yeah, but aside from all that, what has Musk done for us?
Syncthing is also pretty nice
Sad story but a good side effect of that is you can now buy one of these arcade machine for a good price.

I bought a vewlix diamond a few months ago for $2k. Something I never thought possible a few years ago.

Game center are closing but if you are motivated, and not afraid to spend countless hours of research, cleaning, figuring out manual guide in japanese,… now is a good time to own one of those aracde machine before they completely disappear!

Check out https://www.arcade-projects.com/