skysight-inc/HackerNews huggingface dataset:
Under Cook, Apple products have become bland and overpriced in most categories (the M_ processors are a huge exception), but it's also wildly successful. The stock price is 7x what it was when Cook took over. He's one of the most successful CEOs of all time.

Unfortunately the only conclusion we can draw is that consumers don't care about:

- software quality

- bugs

- voice assistants

...and do care about:

- hardware quality

- integrated ecosystems

- cameras

- battery life
A Calendar of Wisdom by Leo Tolstoy

It’s a collection of quotes from various influential people along with Tolstoy’s own thoughts. The book is arranged in a daily reading sort of format but I found reading it normally fascinating.
I have no reason to doubt you, but that does not mirror my experience. I generally don’t have to think at all about iOS. It just silently does everything I need, including backups with no fuss. The only time I have to think is every three years when I upgrade, but that has always gone seamlessly.

Siri being bad is probably more to do with data collection / privacy. I’ve not looked into it, but that’s my assumption.
> Is it suddenly different when a computer does it?

The answer is yes.

Everyone here knows where this is heading, and yet people will sit here and defend these companies as if they're on some righteous path. Humans are already becoming disposable statistics and the engines of compute, all for free and all for the benefit of corporations who didn't pay for any of it and don't even contribute back taxes.
I don’t get it, I am not in the US. OP is an intern and what percentage will OP get a formal software engineering job after internship? It’s confusing
Is this confirmed? I even saw some speculations that it runs on Bluray.
If writing a few paragraphs around something someone else said is copyrightable to you then isn’t GPT writing a few paragraphs around your work copyrightable to OpenAI too…
The trend with Google and other search engines over the past ten years has been for them to incorporate more and more content on their own pages. It's hard to remember that not so long ago Google search results pages were just lists of web pages bereft of any other content.

Today, if you Google for a song lyric, that lyric appears in Google. You get a tiny grey source link to Musixmatch or whatever but why would anyone bother to go there if you have the complete lyric right there on the page you are looking at?

More and more content real estate has appeared on search engines' pages. Answer boxes answering questions, again with a source link few people will use, and of course the large Knowledge Graph panel filled with Wikipedia content (written by volunteers and monetised by the world's richest tech companies).

The result is that it's tech companies and their platforms that make most of the money off content (YouTube is another example). They are the oil companies of today, and like the latter use all sorts of lobbying to make sure things are organised to their advantage.

For all the ingenuity and usability they offer, they behave at least in part like parasites. They should be forced to spread the wealth round a bit more.
There are no "sidecar servers" or monkey patching or "potentially spooky action at a distance" involved in what I described.
Yes, this is VERY close to the APL way: +/ages>17

OP here; maybe I'll add a comment to the article to make the comparison between NumPy and APL for this expression.
Thanks!
> We can already get losses down to a couple percent per thousand kilometers.

Yes, and if we could squeeze down these couple percent to a <1%, the same farm would be even better.
You argument holds true if you want massive distribution. I believe 100% green ammnoia is first step and for that I just need green H2. No need to redesign anything.
Interesting that they use the word "post-medieval" instead of "modern"... And they mention 17th century, well after the middle ages ended.

In fact, such superstitious practices were almost non-existent during middle ages: they're one of the natural consequences of de-christianization, which happened at a faster pace after the middle ages.

I know I need to assume good intentions, but "post-medieval" seems just misplaced and an attempt to associate these practices to the middle ages. I thought we were finally past the times in which we demonized the middle ages. At least in Italy, several historians are finally talking about how great and important that time was.

Look for "Alessandro Barbero" on YouTube for more.
The problem is though how do you evaluate for real work without a portfolio of experience? Real work projects take weeks - perhaps months - to design, build, review and release. How do you test for that, really?

I agree leetcode style interviews are artificial, but I think they persist because few people have identified and popularised effective alternatives. At least with leetcode you've shown people in front of you have been prepared to go learn arcane stuff and apply it. It's not good, but it's better than nothing.

I was once asked to do the Gilded Rose kata[1] for one ~200 headcount Series D "startup", and it not only resembled real work - it's a refactoring problem - but it also showed their engineering culture. When I joined, I found smart people who weren't leetcode robots, but thoughtful engineers trying to solve tricky engineering problems. I "stole" Gilded Rose to use in other companies when interviewing until I joined my current employer (a FAANG, heavily prescribed process), with great success. I would like to see more katas that are as good at testing real world skills.

Also, something I've only ever been interviewed for twice in 25+ years, which I think is underplayed: pair programming and handling code review feedback. Do this more, please. If you hire people not knowing how they're going to respond to a principal engineer telling them "we need you to think about 4 other things that weren't in the original scope given to you by the PM, can you please go deal with them", why are you surprised when toys are subsequently thrown out of metaphorical prams?

[1] https://github.com/emilybache/GildedRose-Refactoring-Kata
Does anyone have the history for why number of pins was such an important consideration (not just for Zilog, Intel too)? Was it really that much more expensive to make a 64 pin package than a 40 pin one?
Even if you aren't, it is still going to be roughly driven by how many hours of recruiter/ interviewer time you want to allocate per hire.
Article OP here!
Thanks everyone for reading and for your feedback.

If you have suggestions for improvements for the article, let me know here!
Thanks again.
Experiences with these things vary a lot, depending on your location, the construction of your home, and (I assume) the cost of the receiver.

I had a ~$15 radio-synchronised clock when I was quite a long way from the transmitter, in a solid brick building. It would get a signal in some locations and orientations in the building.

I don't have firm information on how good the signal reception was, as of course it would keep ticking even if it didn't have a signal.
It was recovered and it was such a pain that they deprecated tape storage entirely.
I'd add ours too, although we're trying to be an end-to-end one-stop platform.

https://github.com/agenta-ai/agenta
Interesting that there are more Chinese universities in the list than US/UK universities, I wonder if there is some article or analysis written somewhere about the ranking of this list.
What are you using for the GUI parts?
I personally prefer Leo’s work “War - What Is It Good For?”
The sea of fertility tetraology by Mishima. The Sailor who went to sea is one of his shorter works if you're looking to give him a read with less commitment.
Reminds me of how homebrew on MacOS used to work, it softlinked into the /usr/local prefix.

Nowadays homebrew on arm processors puts everything into /opt/homebrew instead by default...
> Hmm, need to put the assignment before.

No, that would not have the intended behaviour: your `print(a)` is reading a fresh local variable, defined by the `:=` expression (which shadows that from the outer scope), so it will output '2'. The intended behaviour is to print '1' and reassign the outer name; but we can't do that (that's why I chose it as an example!)

> Can't access nonlocals unless you only read the the var and don't write to it. That's the way functions in python work as well.

Yes, that is precisely what I meant when I said it "suffers the same broken/ambiguous scoping as assignment statements".

Python took a haphazard, WorseIsBetter approach to assignment/declaration/scoping. The resulting behaviour is complex, confusing and involves spooky action-at-a-distance (e.g. the meaning of my `print(a)` expression was altered by the presence of an ':=' expression which hadn't been reached yet!). Since this doesn't really affect simple "top to bottom" scripts, it only became an issue once large applications and frameworks started emerging; by that time it was too late to fix, since there was too much Python code in the wild to justify such a large breaking change :(
> which hilariously does not apply to vim, which by default drops swapfiles in pwd anyway.

That's configurable! Check out :h directory , or just add *.sw? as a filter in .gitignore.

Configurable is best. XDG peeps get what they want, the rest of us get what we want.
The Crypto Hell on the Other Side of a Spam Text
can confirm, it's as simple PG says "just build something people want"

it will open many doors :)
A fantasy novel with Tolkien's characters' names is an evident copyright violation regardless of how it was generated. That's not what's happening here.
Which raises the question of why do the other kind of interview at all. I mean the leetcode nonsense whose end state is often a theatrical performance: “I’m pretending to invent this clever algorithm on the fly although I’ve practiced it for weeks”.

Is there any evidence that candidates who do well on design interviews but fumble on leetcode would be any worse at the actual job?
Yes, and if we reproduce something significant that way we have (depending on licences etc.) committed copyright infringement. The definition of significant is a very grey hairy one though – there are many obvious examples where you would say it is definitely copying from memory (so plagiarism rather than research or accidental similarity) or copying directly, and many examples where we'd all agree that the result is so likely to be independently produced that it isn't an issue, but even more examples where there is room for interpretation and disagreement.

This isn't as well-defined for humans as you might think, so can't be well-defined for LLM techniques by comparing them to human agents.

My argument against the current hoovering up of data under various licences for AI training, which they claim can#'t reproduce anything verbatim, is CoPilot. If there is no risk, then why did they only use public repositories and none of their own private ones? Surely they think their code contains good training material, unless they think their own code is gobbledygook. Or back in terms of licences: if it can't breach the GPL family, then it can't breach their own commercial licensing arrangements.

Would OpenAI have a problem with humans for using some of their code/documents/other in this way?
Good to hear that the pipelines can be reused. For home appliances we really should move away from using natural gas and not try to substitute it with hydrogen instead, heat pumps and district heating are better solutions.
Some of the highest salaries I know are in core ML at big tech or some of the foundational labs like Allen AI. While whiteboard coding interviews are often part of the process, it is generally pretty basic LC.

The crux of the evaluation often revolves around have you built something amazing before? For most new grad folks it is the work done as part of their PhD thesis, but for non PhDs it often boils to amazing past work. And it’s a similar process for more experience folks except the reliance on LC fades even more.

If this works well for cutting edge ML why shouldn't it work for everything else?
It is way easier for me to read than what you proposed in Typescript, more characters to write? sure but how many times do I have to write a piece of code and how many times do I have to read it?

I guess ultimately it depends on which language you are more familiar with...
Ask HN: Why are you publishing new projects on GitHub instead of Gitlab?
Remember when everyone switched to GitLab when Microsoft bought GitHub? I haven't seen one big startup/FOSS using Gitlab.com (let's exclude self-hosted like freedesktop). Looks like even the monthly outages are not reason enough for people to switch.
Just to be clear, we are talking about Ubiquiti. I am not fancy enough to own it's hardware but I like the android and iPhone app for Wi-Fi man which is an easy to use Internet speed testing thing for Android and iPhone.

https://en.wikipedia.org/wiki/Ubiquiti
It started being so inconsistent and randomly delayed that I just realized I'm still planning ahead and don't really need prime.

Also, if it needs bundling bs I don't want to seem attractive, then I feel I'm forced to pay for stuff I don't care about.
There is complexity in making the change and diverging on different platforms. ~/.myapprc was there first and it was XDG that came along and wanted everything to change.
> Do we want a future where Europe pushes through mandatory low quality carbon offsets on airfares, further restricting the privilege of high speed travel to the richest of the rich? Or do we want a future where cheap carbon-neutral aviation fuel expands access to globe-spanning travel opportunities for hundreds of millions of people while also enabling a renaissance of supersonic transport?

That’s a false dichotomy. I don’t want any of these, I want airplane quota per capita and stopping travel growth to preserve earth and its biodiversity. Fuck growth. There’s enough planes in the sky.
I build https://amazing-gains.app where you can manage your workouts and some nutritional metrics. One focus is on data protection, so you should be able to easily download your data whenever you feel like it. It is also supposed to work offline (PWA) as I personally have very poor connectivity in my basement gym :)

Currently it is completely free but I would need to assign certain permissions to new user accounts so they can create exercises and workouts. I would do that for everyone who signs up today.
same as title :) please star and contribute!
I don't have one yet, but will ping you here when I do.
Lance Hedrick in his latest video (review of Decent XL) mentions that he got the Gaggiuino parts, but haven't got around to building it. I look forward to that video, whenever it comes out.
LeetCode has no correlation with great software development. Great development is more about paying attention to the end users, having an eye for usability and design and great communication & the ability to execute. The current LeetCode churning explains why Google hasn't produced anything worth using since Brin & Page checked out and why so much of software today is absolute garbage - but it is what it is I suppose. I suppose its better to screen for IQ and desparation than you know...people who love developing great software. Let them keep doing what they're doing while treating their own people like disposable garbage during hard times (like Google & Meta just did) and we'll see what they'll churn out over the next decade or so (I'm not expecting anything from either of these companies).
It depends if the hierarchy is open or closed.

If the hierarchy is open, the behavior is defined in each subtypes and it's easy to add a new subtypes but you can not add a new operation (a new method). That's the OOP way.

If the hierarchy is closed, the behavior is defined in each function, it's easy to add a new operation (new function) but you can not add a new subtype. That's the ADT way.

This is known as the https://en.wikipedia.org/wiki/Expression_problem
Doctors couldn't get pricing even if they wanted to.
I don't know if the reservoir is big enough but some pumps for tubeless tires do come with an integral tank for an initial rush of air to pop the bead in place.
The XDG spec gives YOU as the user CONTROL to get it like how you want it to be. That is why you can set the $XDG* variables, so that the software listens to your wishes.
Without XDG adherence, software packages just piss all over the place, wherever they like to.

There are programs that even manage to create multiple dirs, like .something1/ and .something2/. Some other programs are even worse and put files just into $HOME. Good luck with backups.
Why are you making a strawman?
That's what orthogonal means. They're separate things, and they don't interefere with each other.
Could technology, defined as the elaborate (=intelligent) and large scale manipulation of non-biological environments be incompatible with the long term survival of biological life (i.e. it is an unstable evolutionary process)?

Its a difficult argument, as all of life manipulates its abiotic surroundings one way or another. Yet the antropocene is clearly at least one qualitative step up. We only have this one data point (our own) so make of that whatever you will. But it doesn't take an ultra-pessimist or doomist psychology to see that on the basis of our behavior the odds that technologically enhanced life self-destructs in short timescales are, indeed, non-zero.

If "intelligent" biology is an intrinsically unstable system (can't self-regulate because primal drives for reproduction, dominance etc highjack mechanisms that are too powerful for its own good) this would make the absence of technosignals self-evident.
That's rich for "Know your place, grad students. We, like Walmart, condone taking tax payer money (also known as "welfare for the poor for the rich") as indirectly part of your compensation."

If you want to be rich, avoid being a grad student for very long or entirely unless it's pivotal to a tangible financial path where the opportunity cost is significantly worth it.
I'd argue that even though it's well defined behaviour in Python, it still appears to me as a programmer as weak typing. For example, Python lets me write:

if 23:
print('hello')

and it'll print 'hello'. But I'd prefer a strongly typed approach where this code would give an error saying, 'a bool is expected here'. Sure it's a subjective thing, and this is just my preference.
> I have similar ideas in society fwiw. I don't see a moral reason to defer to someone else

My opinions are probably a result of how and where I was raised.

That being said, I don't claim we should defer to authority for authority's sake. Authority is given by the people. In the case of the XDG Base Directories, for instance, I believe the specification is well-laid-out. It has gained enough traction and enough developers adhere to it that it has authority of its own accord: by accepting the specification, developers have voted to give XDG that authority.

That is how it works in democracies, no?
>The general way LLMs work do not preserve content in it's original form: the ideas they contain are extracted and clustered statistically - as a

Is the way LLM work relevant?
I can make a shitty script that has as input Microsoft proprietary code and as output something identical in purpose but the text is completely different, I would rename names with synonyms, swap some things around etc.

I am not against AIs, my opinion is that if your AI uses GPL code the output should be GPL, if it uses public domain images the output should be public domain images.

I mean for code if AI is actual intelligent you should be able to train an AI with C with just a few books and not with the entire GitHub open source code (and notice MS did not trained copilot on the proprietary code they have access proving they are not confident that they are in the right).
Internet, computing, etc.. As time goes on and attestation catches on general purpose computing will die for the most part.

But maybe we'll see a renaissance of sorts? When the only sites that work on Firefox are fediverse and a few hobbyist sites and people need to go out of their way to find computers that they actually control we might undo the eternal September of the web as a whole.
On the Duality of Intelligence
What does one have to do with the other though? You can use any programming language where the compiler supports WASM output, and any cross-platform graphics library that also has a (Web)GL or WebGPU backend.

(also not sure how Qt fits in here, but it also has WASM support: https://www.qt.io/qt-examples-for-webassembly, but IMHO Qt is way too bloated for this sort of thing)

In the end, WASM running in browsers can only use browser features that are also available to Javascript, e.g. for rendering that would be canvas-2d, WebGL, WebGPU or the DOM). But at least WebGL and WebGPU are close enough to similar native 3D APIs that you can share some code between native ports and WASM running in browsers - but it still makes sense to use a higher level graphics libraries which abstracts over the 3D-API differences, or alternatively use wgpu.rs or libdawn in the native versions (which are the standalone native WebGPU libraries used by Firefox and Chrome).
Worth noting that is initial capital costs of building the plant. Maintenance, fuel etc are not included, even before considering external costs such as poor health outcomes from pollution.
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Well, there is also the fact that if you train LLMs on LLM output the quality degrades very quickly. It is not a good thing to do.
Thanks for the enormous amount of interest and questions in this post. I wanted to make a follow-up comment to answer all the questions above about differentiation, where we see issues in the current solution space and clarify the problem we are trying to tackle.

Starting with the problem - the problem we are trying to tackle is to make iteration of LLMs and Agent applications as easy as possible for data teams - not for people to quickly edit and compare prompts (although that is 1 way of doing it). There are a number of solutions out there to help you test prompts etc. but many fail to fit within the data team's workflow (which consists of tooling like Pytest and CLI-first approaches) and do not make it easy to iterate and launch on things like agents.

From conducting 30+ interviews with ML Engineers and data scientists building in this space - all of them want to first build a LangChain agent/RAG pipeline and then build their own internal version of it (due to the fact that LangChain is quick to set up but lacks tooling). A lot of them are encountering issues with developing the right evaluation infrastructure (which DeepEval aims to solve through synthetic data creation and easy-to-use testing tools).

Our product roadmap is to not only build the initial unit testing for LLM but also to make it easy for other developers and other MLEs to quickly iterate off this. This means long-term, our plan is to ensure that our users and customers are able to build the best agents/LLM solutions possible.

And (to be frank) a lot of the existing solutions aren't the best looking, have limited visualisations (or are just dead)
The author of this blogpost presented it a couple of days ago on Functional Programming Sweden:

How APL made me a better Python developer by Rodrigo Girão Serrão: https://www.youtube.com/watch?v=tDy-to9fgaw