skysight-inc/HackerNews huggingface dataset:
> You can only make tradeoffs. In this case, Java's sacrificing time.

When you have billions of LOC, and take backward compatibility seriously, then that's a very valid approach. Furthermore, we've seen the Java team pick up cadence recently since switching to twice a year releases.

> They've historically shown poor taste in the features they've chosen,

Quite disagree. Which features are you talking about? They've shown very good taste in how records and pattern matching have been implemented for example. An also not jumping on the async bandwagon and opting for virtual threads instead.

> Already? Ten years later! Time matters.

Java had other approaches for dealing with heavyily asynchronous code, but it wasn't as ergonomic. And honestly speaking, the JVM already gives you access to native threads (something that neither golang (only "goroutines") nor python (GIL) for example offer), that unless you're doing heavy IO bound work, it's a non-issue to begin with.

> Go was built with its concurrency solution in mind

That is the claim, but in practice it is quite error prone. I was following golang from pre-release, and I voiced concerns about not having a way to declare immutable values (or at least something similar to C++'s const), but they didn't seem to care. Of course it came to bite them back[1]. Passing channels everywhere is tedious and verbose, and doesn't make it clear what the code is doing at first glance. Futures/Tasks are an easier abstraction to deal with, but of course golang didn't have generics until recently, and they still don't offer a future package.

> I've been hearing this for a while, has it been a decade yet?

You can follow the valhalla project to see what they're up to. It's sufficient to say that the pace picked up significantly on these large projects since switching to a twice a year cadence.

> You can't be serious. Complaining about another language's null problems from the perspective of Java?

Having worked on large golang codebases, I've seen first hand the issues that zero types cause in practice. At least a nullable in Java would throw an NPE instead of silently passing through the system and ending up with completely arbitrary behavior that is challenging to track down. Not to mention that you can use annotations to denote @NotNull in Java, something that golang doesn't have.

> It's a wash most of the time AFAIK. Unless we do the classic Java benchmark trick of ignoring memory usage.

Memory usage should improve with value types, but it also seems that people don't configure their JVMs properly (things like Xmx). In any case, they've also modified G1GC (and probably one or two more) to more aggressively release unused memory back to the OS).

[1] https://www.uber.com/blog/data-race-patterns-in-go/
This is just growing pains for a new industry. OpenAI shot up to 100M users almost overnight. Hosting AI models at that scale has never been done before, and surely was costing them a fortune. It's not surprising to me they are futzing around with things and causing some regressions.

Yes self-hosting is one option, and probably a good one for many companies. But I also suspect OpenAI and AI APIs by others will get much more stable and reliable in the coming months and years as the industry matures and best practices are adopted.

I would guess AI API reliability and maturity will asymptotically approach that of other cloud services, like S3, as more and more things depend on them.
> Unless Apple fucks up majorly I don’t see that changing.

I agree 100%. I just said the same is true for postman that it is hard for some other company to replace it.
Large alumni donations can and often do increase the cost of education of all the other students. They frequently lead to large capital investments that then have uncovered operational costs. I used to work for one of the wealthiest universities with 100s of millions in capital improvements annually that couldn't provide functional HVAC and a fresh coat of paint to the buildings it had.
The problem with merit is that it's impossible to determine because the circumstances of people around the world are so vastly different. If you have, say, 1500 spots for a new class, it's going to be impossible to select the best 1500 students. Some elite universities you may even have more than 1500 valedictorians. So what to do? I say you just set a qualifying point to be considered and publicize it (as standardized as you can get, i.e SAT score or similar) and then put every qualifier in a hat and select at random until you fill your spots. Nothing else should matter.

Of course this assumes that merit is actually the only thing universities care about, and I'd say that it's not.
> Alternatively, if you don't care about cell outputs then Jupytext[5] to sync .ipynb JSON to markdown

Notice that using markdown is a possibility for jupytext, but not the only one. More interestingly, you can also store your notebooks as plain python files, whose comments are interpreted as the markdown cells of the notebook.

This is very useful, and not only for version control: if your notebooks are python files they can be executed easily in CI or by third parties just by launching the interpreter. No need even of the jupyterlab dependency.

With some care, you can craft a single python file "foo.py" that can be used at the same time as

1. an executable command-line program (that happens to be written in python)

2. an importable python module

3. a jupyter notebook (to open it you need the jupytext extension of jupyter)

4. the documentation with auto-generated figures, convertible to html or to pdf using "jupyter nbconvert --execute"

5. a regular .ipynb if for some reason you want to distribute the outputs in a re-executable format

For small simple projects, to showcase, describe and illustrate an independent algorithm, we have found this structure invaluable.
I wish zig could be enabled for godot.
Do legacy admissions not pay for themselves?
> How is forcing a friend or family member to surrender their own PII have anything to do about "weed[ing] out the bad apples"?

Well, interviewing family and friends can definitely help weed out people with problematic far-right attitudes, a history of domestic violence or other issues.
I think you are underestimating the extent to which standardized tests can be (and have been) biased.

https://www.nea.org/advocating-for-change/new-from-nea/racis...
A menagerie of animal-part patchwork humans sounds like a great time!
Legacy admissions can be gamed too with modest donations just enough to make the system gameable. With large donors it’s a different story though, those do help the universities and the number of students who enter this way is a pretty low ratio.
Does Apple do general-purpose web APIs? The only one I can think of is WeatherKit.

Seems like any AI stuff will be designed to add value to its hardware exclusively, probably in conjunction with its on-device Neural Engine (tm).
But this isn't their main product. As it should be ideally.
this decision is not motivated by merit, it's entirely motivated by race.

and they have no intentions of using a merit based approach for applicants because that would result in an even more white and asian dominant student pool.

without the legacy pool they now have more wiggle room to juice their "merit-based" approach so that they can admit more blacks without getting busted for illegal affirmative action.
This, and Roboto Mono, are my two desert island monospace typefaces. Are you allowed to have two desert island mono typefaces? I don't think I could could choose between them.
Since we are sharing resources Fluent Python is my favorite reference on Python. It covers so many advanced features like concurrency, functools etc. It’s not the kind of book you read cover to cover it’s one that you go to as you need it, when I was working on python stuff I would read it once a month.

My favorite introductory book (not an introduction to programming but an introduction to the language) is “Introducing Python by Lubanovic” because it’s one of the only beginner books that actually covers the python module system with enough depth and the second half of the book gives a quick overview of a lot of different python libraries.
At a large government agency, partnered with one of the top AI companies in the world. We've been deploying models and transformers and recently a LLM ensemble in prod for 3-4 years now. Many lessons learnt that open source hadn't really provided utility for.

The biggest backend things: models can run on CPU architecture, you still need highly performant CPU, but in cloud there is a way to significantly discount that by relying on spot instances (this doesn't mean GPU isnt viable, we just found a real cost lever here that CPU has supported... but things may change and we know how to test that). Further, distributed and parallel (network) processing are important, especially in retrieval-augmented architectures... thus we've booted python long ago, and the lower level apis aren't simply serializing standard json-- think protobuffer land (tensorflow serving offers inspiration). BTW we never needed any "vector DB" ... the integration of real data is complex, embeddings get created through platforms like Airflow, metadata in a document store, and made available for fast retrieval on low-gravity disk (e.g. built on top of something like rocks db... then something like ANN is easy on tools like FAISS).

The biggest UX thing: integration into real-life workflows has to be worked on in a design-centered way, very carefully. Responsible AI means not blindly throwing these type of things into critical workflows. This guides what I assume to be a bit of a complicated frontend effort for most (was for us esp as we integrate into real existing applications... we started prototyping with a chrome extension).

EDIT: btw oss has definitely made some of these things easier (esp for greenfield & simple product architecture), but I'm skeptical of the new popular kids on the block that are vc-funded & building abstractions you'll likely need to break through across software, data, and inference serving for anything in scaled+integrated commercial enterprise.

EDIT2: Monitoring, metrics, and analytics architecture were big efforts as well. Ask yourself how do you measure "value added by AI"
I've been meaning to write up a blog post. I've had a lot of success with:

- Using LLMs to summarize, create structure, etc., rather than relying on them to generate responses

- Having my apps rely on receiving LLM output in an exact format (e.g. an OpenAI function call) and raising an error otherwise

- Never showing generated outputs directly to a user or saving them directly to the database (avoids a lot of potential for unexpected behavior)

This kind of stuff is less flashy than chatbots for everything, but IMO has a lot more potential to actually impact how software works at scale in the next ~year or two.
Yes, that's how anti-competitive practices look like.
Not sure how to phrase this. It's illegal in the US government, but it still exists all over unofficially and it's openly acknowledged standard practice in many NGOs.

It's very difficult to get a job at NASA. I forget the exact number, but something like 75% of people who "work for NASA" are contractors and only a small minority are actual government employees. In order to get a full-time job, it helps to have previous experience usually in the form of a graduate fellowship. In order to get a fellowship, it helps to have undergrad summer experience. In order to get undergraduate experience, it's very helpful to have high school summer program experience. In order to get high school experience, you'll need to live in the area and probably have some connections which means parents or family who work at the NASA facility in question.

In my experience, national labs were similar but to a much lesser extreme, often just because they're remote and sometimes antiquated and children of lab employees often can't wait to get away.

When I worked at at the UN, (NGO, not formal government) coworkers were genuinely confused about how I got a job there with no family connections in higher places. I had the same conversation with several bewildered coworkers who plainly told me about their parent or uncle who got them their job. I was told that nepotism is much, much more common and openly acknowledged in Europe than in the US.
They don't have to. They just need enough time and believe for the investors to dump it on retail (IPO) or get bought-out by another company.
Sports programs at the top ~20 universities pay for themselves (and that too just the top sports). The rest are a money sink.
I'd love to see that level of transparency. It don't think it would change as much as you'd hope though. Even when we're aware of the manipulation and the vulnerabilities in our brains we're still susceptible to them (some more than others). It's just how we're wired.
Apple probably has half a dozen layers of moats one of which is their M line of processors.
There's a product called DisplayLink that's used with certain USB monitors and USB docks. It compresses the video displayed on the screen in a userland daemon.

It requires Synaptic's software and it does work as a solution for devices that don't have enough I/O capacity to support multiple DisplayPort screens.
Why not publicly distribute the design? Because skimmer-makers might adapt? It seems trivial to acquire one (getting a job at Target or spoofing a corp email account isn't a high barrier).
Auto Gen-AI App Generator with the Power of Llama 2
With just a prompt, you can create interactive Streamlit apps via LangChain's transformative capabilities & Llama 2
The time for media PCs may be over, they may not. I have a Plex server and the NUC is a great form factor for that.

But, even leaving aside media PCs, the form factor is great. They're powerful enough for me to use happily as a desktop, and I love having a tiny PC that doesn't take up acres of desktop.
> The concern about legacy admissions is more that the legacies may be disproportionately white

Disproportionally rich is my problem with legacy admissions.
I love this, my friend hates comic sans so I’m definitely using this for April fools
> I typically only eat chicken but I just don’t see an issue with if the chickens are humanely treated and killed.

If that's your only concern, and not environmental destruction, then that's fine - if you're ensuring that the chickens you eat are humanely treated and humanely killed. The best way to do that is to buy from local farms you can visit - otherwise it's just aspirational and in effect identical to someone who doesn't care at all.

> The way I see it is we’ve bred these animals as livestock and we’re responsible for them as livestock and that’s okay.

But we can stop mass producing them. There don't need to be 30 billion of them. Scale is what makes factory farming such a catastrophe (environmentally, ethically, and for our own health).
I hypothesis that this position will be largely debunked as we learn more about how computer algorithms can manipulate people. Hopefully advances in scientific research will allow us to better model and categorize unethical systems.

"could the devs really be held responsible for anything" - Yes.

"It's a free market" - algorithms which can hijack the mind are a form of coercion. A free market is roughly defined as voluntary exchange without coercion. That's why we ban children from gambling.

"playing by the playbook" - society gets to define ethical constraints in which companies must comply. We learn this in business ethics. eg: Labor rights, safety, health, etc.
Correct, and I did say so. While "your spouse will lose his or her job if you do X, Y, or Z" is not technically a legal requirement, for most people it's a distinction without a difference.
The concept at the center of this discussion, but which is not being discussed is called “bailment.” While every bankruptcy system has rules for unwinding those bailments entered into before filing, they vary from jurisdiction to jurisdiction and much of what we think would be workable or fair just doesn’t work that way.
Deterministic universe. We're all just slaves to cause and effect.
Why tie it to legacy though?

The university could just offer a secondary admissions pool with a higher tuiting cost.
My personal goal is to get as close to Norvig as possible for general Python code: https://github.com/norvig/pytudes/blob/main/ipynb/Advent%20o...

(short but exact comments, inline testing, good function and variable naming, overall good use but not overuse of the standard library, functions very rarely more than a dozen lines, generally understandable code)
I think the fidelity of unspoken information is so much higher in person. Over zoom and most certainly via text-based comms like slack, it's hard to tell if you are being understood, and if you are understanding.

Beyond just the technical understanding, then there is emotional understanding. I find that it's much easier to encounter apathy and malice over digital comms. In person, you have limited access to someone else's attention. On slack, you can be pestered by dozens of "very important" walls of text every day.
Yes, but 11.7 has been the "stable" release: https://github.com/pytorch/pytorch/blob/main/RELEASE.md#rele...
You opt into gambling, you don't opt into having your water polluted

Teenagers shouldn't be gambling, their parents should be responsible for that, but some don't want to rear their children.
I don't like ligatures at all it only confusing
This is the way many public universities without legacy admissions actually function as well. They have a high published tuition, but if you are a half decent student, there are many discounts and scholarships that can reduce it significantly. Only less qualified students pay full price.
Thing is, in a legal state there is no leverage for a bad actor, unless the US federal government changes its policy - but that's very unlikely under a Democrat government given they're pro federal legalization, and even under a hardliner like Trump the Republicans didn't dare touch the issue because it would counteract their entire "states rights" agenda and piss off a sizable amount of their own voters.
Merit isn't enough.

I went to a po-dunk school in rural Missouri. I would never be able to I compete with kids from a rich Chicago/NY school. In the same way a black kid from a poor inner city wouldn't be able to.

This is part of the problem. The world isn't egalitarian. The poor will continue to get poorer, the rich will get richer.

Solution? Lottery? Don't have a great one.
As citizens expect the state to uphold the old world despite physics saying nay, tax levls inside and outside of the empire should increase until they don't. Once that happens, the "stabilizing" influence sphere shrinks rapidly. I'm honestly not very eager to see that world..
The same way we can revoke NetBet's gambling license, right?

The government could easily require a gambling license (or a "random gaming" or a "f2p game" license or whatever form it takes) to be able to distribute a certain type of game which would be legally defined. Then, they could impose requirements like age checking for such games, and companies who failed to respect the requirements would lose the right to distribute these games in that country. International treaties could be used to extend this ban across a wider economic area.

Note that there already exist laws that define precisely what types of games require a gambling license, extending that to a new type of game has to be done carefully, but is definitely achievable. As just a low-effort pass at it, we could require a license for any game that includes a way for the player to pay to have some advantage in-game, where this advantage is obtained via random chance after the payment is made. An advantage could be defined as any change to the player that statistically increases the player's chances of reaching a win state.
>Is it really a big deal?

Probably not in general. At least outside of a relatively small number of schools. IMO, what you're seeing is a bunch of schools that really don't take legacies much into account (if at all) all coming out of the woodwork to put themselves on the side of the angels without having to actually change any of their policies.
Ask HN: Should I learn to code and what would this journey look like?
I've got a background in marketing and know some very small amount of code but not enough to build small product ideas. I've got a few startup ideas but don't have the ability to execute on them or budget to hire some great dev agency. Should I learn to code? How long realistically before I could build a great side project?
"Geoengineering" is what that's called. You can put chemicals in the atmosphere to make it hold less heat, or in the water to encourage algae to use more CO2, or put a sunshade in orbit, etc. I think that is discussed less than it should be. I think people avoid the topic because it is of course hugely risky. I would bet that will change because the risk of continuing fossil fuel use is so high and so uncontrollable.
Keep distractions out of YouTube search results
TIL:

> add before:2025 to the end of the search term

It prevents the 'For you' and 'People also watched' sections appearing in results!

The 'shorts' section still appears, but can reliably be removed with a content blocker.

Source: https://www.reddit.com/r/youtube/comments/13wx9tw/comment/jmn0z7g/?utm_source=reddit&utm_medium=web2x&context=3
Gotta be honest, I have no clue what I’m doing. We just pushed to prod and finding stuff out while we go. Logging all conversations and because we have no idea what we are doing, just trying different stuff.

For context, I build in some api calls and LLM is asking for the required data. My proof of concept was enough to make the client say, ship it! And we’re rolling with it since
I also prefer Comic Mono.
That's soft bigotry of low expecations. All you have to do is look at data that includes Asian Americans, which is always conveniently omitted from these racist narratives. Even non-Americans routinely do better on American standardized tests.
Apple TV, google play, Amazon, and all the other video stores are no harder to use than Spotify.

You don’t use them because it costs 6 bucks a pop.

That’s a price motive not a service issue.
I don't know if I agree with the premise:

> People are terrified of parsers and parsing

But this implementation of a reduced feature set version of .ini file parsing does not convince me that I should write my own parser instead of using one that implements a more full feature set

> No newlines in keys, values, or section names. Empty values are not allowed. Comments only on their own lines (minus whitespace). Whitespace-insensitive (whitespace at the start of line, end of line, around the “=”, is all ignored). No need for a terminating newline either.

I think it's reasonable that people want to use a parser that has better error handling and gives an idea of where the ini file may have parsing problems than just a barebones implementation such as this provides.

I also think that using a library for parsing instead of writing your own parser does not imply that you are scared of parsing.