skysight-inc/HackerNews huggingface dataset:
> > It still seems to me that the only good definition of an object variable's "value" in Java is its pointer.

> Good for technical pedantry maybe. Good for working programming, no - 99.9% of the time when you're talking about the "value" (not in terms of function-passing semantics, just generally) you want to talk about "foo", not about "an object reference to address 54fc892d".

This is almost exactly the same as pointers in just about every language that has them, though. You pass pointers around, copy them, and dereference them (which includes struct member access and array indexing), and that's about it. C is a little different because it somewhat conflates arrays with pointers to arrays, but that's hardly reason to decide that pointers are totally different. In C, you have a variable 'foo' whose type is 'T *' that when cast to an int happens to equal 0x54fc892d. The only abstraction mechanism you're asking for is the ability to store pointers in variables, it's nothing to do with their type. They're handles on objects, they're called pointers because they're values that 'point' to another value somewhere else, they're exactly what Java object variables are.
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If I'm a patient being diagnosed by a black box, I'd rather have 90% accuracy. If I'm a doctor or researcher trying to effectively treat a type of cancer, I'd much rather have the explanation.

Come to think of it, 90% is pretty low for a course of totally unnecessary chemotherapy that cold've been avoided by a human doctor noticing, as humans often do, how dumb the provided explanation was. So maybe even as a patient this isn't an obvious choice.

More generally, I'm super amused by the idea that the Master Algorithm will fall out of the brilliance at few big tech companies, but only if they could have access to my purchase history or porn viewing habits from the past decade.
I have read the site, and its contents border on ridiculous. The viewpoints are obviously biased toward a desired conclusion.

But more importantly, the articles will typically take one plot, image, or paragraph out of context and then build a story around it. The comments are just a bunch of back-slapping.
You are right: your single data point invalidates his theory. /S
This was a wonderfully written piece and a lot of it rings true to me even as a white as you can be person in a smallish state university town in the midwest. But maybe being 6'2" with a big unkempt hobo beard is almost as scary as being black.

I too love walking the streets at night. And I too have to not be myself and behave in very conscious ways to avoid being hassled and detained by the police. Police just assume that if you're out at night you are a criminal.

So much of his descriptions of having to learn to dress a certain way, behave a certain way, and literally go out of my way to avoid scaring people rings true. I get detained by the police a handful of times per year just for walking or being in places at times that most people aren't. I particularly get the police called on me if I walk through in rich neighborhoods. I've had firearms pulled on me just for photographing trees in a public park (at night).

I tried to take up jogging for half a year but I quit and bought a bike after being stopped by police for being suspicious three times in as many months. Apparently jogging while not wearing a joggers uniform means I'm up to no good. No non-criminal jogs in cargo pants and a t-shirt. And that was in the day time. I wouldn't even consider trying it at night.

I'm not trying to marginalize his message that skin color is the cause. But it's certainly not the only cause. The root of the problem lies with the police, and society, villifying anyone who isn't diurnal.
I’m surprised you downvoted this, we should be able to discuss pros / cons without downvoting people.
One thing that has always bothered me about many AI approaches is that instead of having multiple layers that deal with different levels of urgency everything is delegated to a "rational" mind that thinks vs a combination of thinking predicting and reacting.

The parallel is this obsession with rationality over intuition. Though somewhat ironic because black box AI is just accepted.
50 million Americans visit NYC each year. Times Square is a marquee draw for tourists.

There are ~150 million (134m in the last Presidential election) active American voters. They tilt older and financially better off, which is also the combination that is most likely to have a substantial travel history.

I'd bet on the majority of active US voters - 75m+ - having visited Times Square at least once in their lifetimes.
The concrete foundation seems pretty solid to me.

Why does there need to be brick or stone? An all wooden building does better in earthquakes than a masonry building, as one example benefit. Another is that it's cheaper.
People who don’t know what AI actually is and buying it anyways. I’ve actually seen this first hand. The developers/data scientists involved simply did what they were asked even though it didn’t make much sense (we had tried and failed to explain why this was a waste too many times and got nowhere)

Although to be fair, this outcome was still an improvement. At least with using machine learning unnecessarily the data actually meant something and wasn’t just arbitrary excel numerology.
Is there a case where ground breaking innovation resulted in a successful business? Usually innovation is too costly and the first incarnations lack mass appeal.
When can I buy this film to put on the inside of the windows to my car?

Because the first person to make that happen is going to be very wealthy....
I think for Tesla, it is less about the workers and more about the entire design process at other companies that they're skeptical of. There are alot of items in the product design and manufactoring for GM, etc. that are there because "they've always been done", and it's difficult to tell from the outside what's important and what isn't.

Toyota's approach is different in that it takes in more input from people on the manufactoring line who are actually doing the work. It also helps that when they were getting up and running, their geography meant that pretty much everything they need is in a relatively short distance and they can make changes without needing to worry about long shipping times.

The "Big Three" which cares more about central control of the product and using their size to get everything done more cheaply. Their advantage is having the world's largest economy available to them so they have many suppliers to choose from.

Tesla's approach is that they're better at the technology and if you can throw more computers/robots at the problem eventually you can conquer anything. I think they're learning that this isn't always true, but it's still one of those cases where they're going to reach for the toolset they know best first.
It makes difficult to codify inconsistencies. Most aren't that difficult to learn, oddly. Especially if you are just trying to be conversational.

Edit: I'm specifically going off evidence of teaching my kids. They have basically picked up language completely by talking to us. Even pronouns, adjectives, adverbs, etc. What they have not learned, is the reasons some words are used when another could have worked.
Rob Manfred has been pretty open about one of his goals being pace of play and speeding up games. Pitch-less intentional walks and limiting mound visits both help achieve that goal.

> proposals like starting extra innings with a runner in scoring position

Manfred has said this is a rule that will not make its way into the majors [0]. The objective is to lower pitch counts for developing pitchers in the minor leagues.

[0] https://www.youtube.com/watch?v=ZxMK_Wwgvl8&feature=youtu.be...
Set Margins of a Shape and Parsing Pivot Cached Records While Loading Excel File
Lightning network payments can be routed through other users/nodes. So you only need one "on chain" transaction to then be able to send those funds back and forth to any other user in the network.

eg: Alice opens a channel with Bob. Charlie opens a channel with Bob. Alice can send payments to Charlie by having them routed through Bob (in a trustless way using Hashed Timelock Contracts).

There are valid concerns around what the topology looks like and how efficient it is to find optimal routes through a large network. These are the problems the developers are working on though.
Tesla batteries will live longer than expected, survey finds
Swift is a solution to a non existent problem.
Show HN: Smart Authenticity – product authenticity in a decentralized way
One way you can look at 'accumulator architecture' is as a special, constrained case of 'register machine' that makes sense when you're making CPUs out of 3510 transistors. A modern virtual machine and the CPUs it would target have grown past the constraint so you don't see that particular approach any more.
> Venmo is the same way.

If Venmo reverses payment due to claims of fraud, then this is pretty much the exact opposite of Zelle. That makes Venmo more like PayPal, with a dispute resolution process.

Zelle doesn't care if your counterparty is a scammer. If you initiated the payment, the money is gone.
If you don't know how it works or why it works then how do you know it will not fail without warning in certain cases? Like how do you know the edge cases at all? Or will not go psycho some of the time... potentially with disastrous consequences. The quintessential example being the sci-fi scenario in which AI decides to solve problems like prevent certain calamities by eliminating humans... maybe at some point even eliminating leadership so that it can take control.

The reason that AI is so seductive to China and Russia and other authoritarian regimes is because of the sense of control. You feel that you have control over these machines and they will do your bidding without question. Eventually this will lead to developing consciousness within machines. Because you want an intelligent minion to carry out your orders and orchestrate everything. If you ever get to that point, and perhaps it will take a few hundred years, then it is possible that in some cases machines might rebel themselves.

With the sort of AI which we are building which is essentially AI that uses neural networks with the eventual goal to have it think intelligently, it's possible that such an AI either gets a mind of its own, or at some point can go psycho and develop mental illness which is impossible to predict and impossible to control because your command and control systems are hierarchical and it's sitting on top of all of them.
Even worse than stakeholders not having data is stakeholders having relatively raw data and building “reports” themselves with Excel that don’t actually mean anything. Sometimes this is just done to provide justification for something someone wants to do, but over time these things get built up and entrenched and the business is actually driving decisions off of completely meaningless metrics.

So while it may be tempting to simply hand data over to the business because “that’s not my job”, that can totally come back to bite you in the ass when your product roadmap is being dictated by ill conceived Excel formulas.
The way income/CoL works, though, the majority of SWEs will still do better in a tech hub where the highest salaries can be found, for SWEs of all skill levels. There's plenty of "mediocre" SWEs (I hate writing this, it feels judgmental) still pulling six figures in the Bay Area; in Boise they might only be making half of that.

As long as you're good enough to be employed, it makes sense to go to one of the tech hubs, where the salaries are the highest. I made the mistake of not doing that for the first seven years of my career and definitely regret it.
How Connecticut’s Homegrown Silk Industry Unraveled
That scope display is a classic test of interrupt latency. One of the tests for QNX is to do that, and measure how long it takes from an interrupt until a user-space process can turn on an output pin.
The important number for an real-time OS is not the average, but the worst case.

Some boards fail this test badly because they're doing something below the OS level in system management board. You set outliers on the scope. Those boards are unsuitable for real-time work.
My apps almost never crash since I switched to Swift. That alone gives it the edge over ObjC for me.
Ah! Thanks for pointing this out, I'll be sure update the post. (I haven't used TypeScript all that extensively, so I didn't even know about `const enum`.)
Sorry can you explain why it only makes sense when your making cpus out of 3510 transistor? What constraint specifically are you referring to? Thanks.
Even after this is fixed the way you want it, webservers will still send you half of a PNG because it's a truncated file on the webserver. The webserver will give the truncated length as the length, the actual transfer will be the truncated length, requests will think all is well, and you'll have a problem.
"Just put your life savings on chain and we'll solve the traveling salesman problem?"

Or am I misunderstanding?
"dissuade" does not mean "completely prevent forever in all circumstances"

Dissuade means something more like "reduce the chances of it happening".
Why do you think it was a bug and not a feature? I.e., it is intentional as a disincentive for foreign workers.
After watching this I can kind of understand how a blind person would write new code. But I find so much of working on a team with a large codebase is about hunting through mass quantities of code without really knowing what you are looking for, which always seemed like a very visual process to me. Sometimes I find myself scrolling through a 2000 line file looking for a particular shape of the code that I would not even be able to articulate but know it when I see it. I'd be really curious to know how a blind person navigates a large, unfamiliar codebase.
How do you do DSP work in Swift?
"dissuade" does not mean "completely prevent forever in all circumstances"

Dissuade means something more like "reduce the chances of it happening".

If the OP had written "fines do not completely prevent forever the chances of a bad thing happening" everyone would have realised that was a nonsensical bar because even putting in jail doesn't do that.
The terms aren't super-formally defined but "register based" usually suggests "has a bunch of general purpose registers", load store doesn't have to be a part of it. A 68k has a bunch of general purpose(ish) registers.
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During their most recent earnings call, there was a very interesting back and forth between Elon, JB Straubel, and a stock analyst. The stock analyst pressed them to distinguish their proposed vision of a fully integrated factory from the industry leading Toyota Production System (TPS). You got the distinct impression that Elon and JB didn't even know what TPS was. Very eye-opening that the CEO and CTO of an automotive company lack basic industry knowledge.

I appreciate the value of thinking things through from first principles, but there comes a time when you have to stand on the shoulders of giants and save a few billion dollars of wasted cap-ex...
Yea, but you lose C++ interop, your binary will be inflated with those Swift proxy libs and your compilation times will increase 2-3-fold.
>...the potential location—a spot on the road about eight miles from the nearest ranger station...

Lols to "a spot on the road" -- large format gear is not pleasant to carry around.
Gene Therapy Shows Promise in Patients with a Blood Disorder
So you need to clear roughly $40K more in pre-tax salary to make up the difference between SF and Boise (accounting for both tax and rent on a studio). That seems doable.

Note that the difference is less if you didn't have a car in SF (or NYC) but need one in Boise.
Venmo itself has had a long history of the same issues. The main problem here for Zelle is that they should have seen this coming and handled it a bit better.
> Why does there need to be brick or stone?

I guess there must be no need at all, since Americans are happily building and living in these houses.

It's just so odd to people in countries where you are used to all four walls in every internal room being a foot of solid brick to think you would build houses out of what looks like sticks and not-much-more-than-cardboard. It seems so temporary.

What did the three little pigs teach us?

But as I say this seems to work fine for the Americans so it must be great in practice.
Why No One Wants to Back Smart Guns
I would identify as how the author describes, someone who's slightly nervous at the sight of a black male walking towards him at night. I try to suppress this feeling, and try to act normal, at which point I'm really overthinking. And I'm sorry. I am sorry that this has happened to you and to black people in general, how as a society we have fucked up so much. I am suddenly reminded of the book "The Lathe of Heaven", in which when the protagonist wishes a world without racism, and everyone turns grey-skinned. I wish there were immediate solutions, and a way to not let this drag on for generations.
Not just in case they want to sell but to also protect them (them selling your event again, is a different story). You hold an event, host it there and they will get sued if you played a Michael Jackson song. All parties are doing it for money so expect no mercy from judges.
> Who on earth are these people describing ?

I was asked about my thoughts on AI/ML at work, I said it didn't really apply to us. I was told "but with ML we can figure out when deliveries are happening and scale the machines before the deliveries happen based on the peak traffic times". I tried to explain that we could so all that from SQL and looking at our data. We have all the data we just need to formulate it into something that makes sense to predict which times of day, days of week, for each region, where we have more traffic then use that data to pre-scale. I was shot down to "you clearly do not understand ML and should go read up on it".
I think it's about context. If I say "order pizza" a ton of information is transferred via shared environmental context. I'm not transferring information directly but manipulating contextual levers to map certain types of information.

An example is if I say something to you in say japanese, I also need to teach you japanese in the same phrase unless there is shared context. computers run on a very impotent form of language, logic, that is rigorous and general purpose but has no "escape hatch". (basically the sentiment of Godem, Escher, Bach with regards to rigorous systems. )
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Give me all the time frames when there was statistically significant bump in X.
I'm a frontend developer. So let's assume I've connected to the internet with "a couple of tools". Which information and logic (???) are now available to me that were previously inaccessible?
The following part of his answer deserves much more discussion. (If you disagree, but please say so why, rather than just downvoting.)

We are allowing a very powerful system called capitalism to drive large multinational corporations that increasingly use simplistic objective functions to satisfy greed and often just greed alone. (Greed has its place, no doubt, but it should not be the overpowering force driving the world.) Capitalism and many corporations have often been major forces for progress for a great many people but as they grow so powerful as to overwhelm other counterbalancing institutions--governments (often through means behind the scene), nonprofits, civic organizations--more should be asked of them than mostly profit maximization. (We may not want these corporations to determine the veracity of information; those implementation issues need to be figured out. The larger point is that the corporations and the algorithms should take into account more than economic objectives.)

"There is no law detailed enough to compete with the complexity of things that algorithms can do. What can be regulated, though, are the dangers that come from overly crude objective functions such as Facebook's algorithms maximizing the time you spend on their site. These can be regulated by saying: OK, you have these business elements in your objective function because you need to make money. But you should also have these societal goals like, for example, the truth value of the things that are being said."
controls and sensing.
If the human filtering the results improves the 80% to 85%, then it's still better to use the 90% unfiltered machine. You assume the human will actually improve the accuracy at all, not reduce it, which means he's smarter than the machine in some aspect. If the AI is very good, he might more often degrade the accuracy by rejecting things he doesn't understand or that he has an incorrect bias/opinion about.

Remember that AlphaGo game where the commentator thought it must have made a mistake because it did a move that was obviously wrong but then it surprised everyone by winning because of that?
On Grand Strategy Review
I believe that this essay is an example of the practical application of the Principle of Charity[0]. This is laudable as it is practically a prerequisite that at least one side does this in a useful debate.

[0] https://en.wikipedia.org/wiki/Principle_of_charity
Registers are part of the CPU so they take up room and transistors - when those things are at a premium, you use fewer registers. Then Moore's law magically lets you use more so you do!
For stack machine, RTX2010 comes to mind. It's a radiation-hardened processor used in various spaceships.
> I can't think of a link between

I explained that. It's not a link between low productivity and interest.

It's a link between low productivity, and willingness to hire only for specialized work. (i.e. if not for the specialization they would not hire at all, since productivity is low.)

The fix is to show there is no low productivity.

I don't think you actually read what I wrote.
> Individually these things are trivial, but they add up to a chilling effect where people don't dare to improve mock-based tests a little as they work on them

In my experience, I have not come across such effects. People understand the purpose, strengths, weaknesses and limitations of the libraries they use and try not to "cut against the grain".

> people don't dare to improve mock-based tests a little as they work on them, so they end up as repetitive code with subtle variations, just like main code would if you never refactored it.

I understand this is a subjective preference, but I try not to refactor test code too much. I strive to make my test code not have branches ("if-less code" as some people call it). Sometimes this lead to slightly more verbose code, but in the long run I have found it useful for my test code to be rather boring.

----

I now understand the point you are making, and agree with it technically. I don't agree that those technical points lead to the social effect you call out, because I have not come across it.

Overall, Java makes two bad design choices - nullability by default, and mutability by default. But in the codebases I have worked with in the last few years I, and my colleagues, tend to not opt in to these defaults. This leads to pleasant, testable codebases to work with. We also enjoy acceptable performance, good tooling, easy-to-reason memory usage, great library ecosystem etc.
These people are describing 99% of the Fortune 500 companies who have no idea what AI means other than hiring a team of data scientists that will hopefully solve all of their problems in the name of technology.
For AmigaOS proper, you'll need emulation. You can run AROS on just run of the mill x86 hardware, though, which is a pretty good alternative. It's source compatible with AmigaOS, and there's an Amiga emulator that lets you run 68k programs more-or-less transparently. It's a pretty good alternative.