skysight-inc/HackerNews huggingface dataset:
I think that's hyperbolic. It seems like a natural digression. I think you're just being negative.

Put another way, this discussion certainly has more than an infinitesimal relation to the original link.
Those few "next to noone" are just only almost everyone in general aviation in Europe.
The post you replied to questioned whether they were considered invasive everywhere and asserted that they were on a global list of the 100 worst invasive species.

All as counter to the claim that Australia was unique in considering cats a nuisance.

It seems that assertion is true:

38. Felis catus

Felis catus was domesticated in the eastern Mediterranean c. 3000 years ago. Considering the extent to which cats are valued as pets, it is not surprising that they have since been translocated by humans to almost all parts of the world.

Notable predators, cats threaten native birdlife and other fauna, especially on islands where native species have evolved in relative isolation from predators.

Common Names: cat, domestic cat, feral cat, Hauskatze, house cat, poti, pusiniveikau

GLOBAL INVASIVE SPECIES DATABASE

http://www.iucngisd.org/gisd/100_worst.php

Is there nowhere in Europe where cat populations are kept in check to protect birdlife and other local native species?
It's so ugly; why do people keep buying those ugly phones?
Hmm that could be a cool feature for Flighty. You just need to build a database of tail numbers and news events, which is much harder than “just”. I pay attention to tail numbers to see if I’m getting on the same plane again.
They mention that “mobile-first companies killed companies that weren’t mobile-first”, can anyone point to a good example? My memory is that “mobile first” was a big hype cycle. A few years later everyone fired their native mobile teams because they realised most businesses don’t actually need a mobile app.
I think you're correct although I'd like to point out that a lot of different animals are capable of reasoning. For example: https://www.cnet.com/tech/watch-a-wild-crow-tackle-a-complex...
A true friend is someone you could ring up in the middle of the night to help bury a body (without paying them).

Everyone else is an acquaintance of some degree. :P
Many people are bad at this too. It's an important and useful skill to learn, e.g. admitting in team meetings that you don't understand something.

I wonder -- does that kind of interaction come up in spoken conversation more than in written text? Things like blog posts and tweets are often stated very confidently. If LLMs are trained mostly from those sorts of sources, maybe that's why they end up artificially overconfident.
Calling a vague statement about trading arrangements a theorem is surely getting towards peak economics.
Ouch! Percentage of internet of things devices who don't ship libcurl is a rounding error. Percentage of internet of things devices that patch libcurl is also a rounding error.
> You need to work on your reading comprehension.

To which you state

> This was not a personal attack, it was a statement of fact.

It's a matter of opinion, not fact.
Too late to edit: *COMING chaotic, times, not comic - I'm sure they won't be comic.
And we also have this looming thing called climate emergency, which should conceivably motivate us to forge ahead with renewables and adjust our energy usage patterns to match production peaks, lest we doom humanity to extinction
Oh that's interesting, I didn't seem to find that when I was researching my project. Definitely worth a look.
Ahh, austria police. A few years ago, my neighbour had an aggressive episode and ended up telling me "I bring di um". Naiv as I was, I called the police, which promptly answered "Do kemma nix tuan".
Same here. OpenSuse was missing a driver or so (can't remember) but puppy just worked on my old, even then, computer. Haven't used anything else than Linux since.
Agreed with this sentiment. I personally find it funny that Craigslist is still very much alive and kicking, and is my go-to for apartment hunting amongst other things, despite an underwhelming mobile experience and a design that hasn't been updated in literally decades.
I came here hoping to geek out about Autobots and Decepticons.
Browsing the lib quickly, it seems like scenarios where you want to connect a server written in Node to clients that talks WebRTC.

For a low-latency gameserver where clients talk via PeerConnection, clients could talk to the server with the same code if it's authorative.

Recording/transcoding a multiuser video-chat session.

Possibly also Ice (helping clients connect to each other if they are behind firewalls)
> If they weren't, Delta would say so, since it makes them look better. That they won't say means the parts were used in service.

I tend to take that sort of cynical view too, though there is a more generous explanation that could be¹ possible: they haven't absolutely finished checking yet, and don't want to say something that they later need to correct. That could look worse than being vague to start with.

--

[1] caveat: I know little of their parts tracking systems, I don't know how likely it is that a more definitive answer cannot be given that quickly.
Safety vs. Performance. A case study of C, C++ and Rust sort implementations
Now we just need to develop a technology that trains racist human beings to be sufficiently woke and less racist. Then they will stop polluting the training data of LLMs so much.
You’ve had to watch out for “bad” programmers since the beginning of programming. Having been an external CS examiner for almost a decade now, I’m not too worried about LLMs in teaching because I’m not convinced they can do worse than what we’ve been doing this far. I do think it’s a little frightening that a lot of freshly educated Computer Scientists will have to “unlearn” a good amount of what they were taught to actually write good code, but on the flip side I work in a place where a big part of our BI related code is now written by people from social sciences because, well, they are easier to hire.

That’s how you end up with pipelines that can’t handle 1000 PDF documents, because they are simply designed not to scale beyond one or two documents. Because that’s what you get when you google program, or alternatively, when you use ChatGPT, and it’s fine… at least until it isn’t, but it’s not like you can’t already make a lucrative career “fixing” things once they stop being “good enough”. So I’m not sure things will really change.

If anything I think LLMs will be decent in the hands of both juniors and senior developers, it’s the mediocre developers who are in danger. At least with google programming they could easily tell if an SO answer or an article was from 20 years ago, that info isn’t readily available with LLMs. I fully expect to be paid well to clean up a lot of ChatGPT messes until the end of my career.
A Solution to Data Privacy
Have you ever noticed how big tech take your data, The big reason is that they all are connected to each other. Take Google for example the data from youtube is used in google's search engine recomendations and also v-s-a, but there might be a solution with this startup safbro.com..
Data can be copied. Giving your data away doesn't make it less valuable to you.

(There might be other concern, eg around privacy, about giving your data away. But worrying about value isn't really one of them as an individual.)
Visualizing a summer of extremes in 7 charts
Thank you for sharing this! Planning to embark on a similar adventure and having some fears, this is reassuring.
Unlicensed is the same as fully copyrighted. There is a presumotion of ownership. Licenses in this case serve to clarify allowable uses. Without a license, nothing is allowable as you maintain the right to do anything within a copyright holder's legal right.

https://www.synopsys.com/blogs/software-security/unlicensed-...
Something like Uber could have been built on top of SMS, though. It didn't necessarily need Smartphones.

(Perhaps SMS plus some feature-phone-level of GPS integration.)
Have you tried a NVRAM reset? A PRAM reset?

https://support.apple.com/en-gu/102603
I see from your other comments you still don't fully understand that these algorithms are automatically generated based on their training data. That's what we mean by "machine learning". It figures out the algorithm by itself through an iterative "learning" process that builds a predictive model. Training/Learning are perfectly reasonable terms in this context.

They learn patterns in data automatically. These are not explicitly programmed by humans.
Stray dogs are a much bigger problem on Indian streets. In 2020 ~6.8 million Indians were bitten by stray dogs and thousands of them die of rabies every year.
I think the point of the parent was that you can build expertise in all of those in a relatively short time frame (esp. when more developers will start building up experience), compared to acquiring a large customer base or a large dataset.
But you too make exceptions, right here.

All I'm pointing out, is that people who oppose strong static typing on the base of "but we don't want it everywhere" are drawing the wrong conclusions, because, indeed, we don't want it everywhere. We (I) do, however, need and want it in far more places than it's used today.
Yes, investors are just people. Some of them smart, some of them less so.
> Or, that txt message Abraham Lincoln sent about trust on the internet.

Abraham Lincon is still alive ?
The editor did nothing more than notepad does today and the IDE at least back when I was using it was basically just a compiler, debugger with basic inspection window and stepping and a make system. It wasn't doing realtime formatting of your code, inspection for errors, referencing to other parts of code, autocompletion, syntax highlighting, etc.
Interesting idea.

Humans have as input the real world. For example the wonder they experience when they perceive something preternaturally beautiful. Then they try to express this experience in language.

That's what LLM are missing. They have -- in a way -- only second-hand experiences.

I was a bookworm as a child. But then when I grew up I had the chance to experience myself some of the things I read about. Then I felt like I did a giant step of understanding the world.

LLM never experience themselves what they have in their data.
Imaginary isn’t on the list?
How on earth do you prove that it’s to the same specs without paperwork underpinning that?

What do you think “fake” means in this context? That the part is really a Loony Toons sketch of the real thing, stickytaped to the surrounding engine? No, it means it’s essentially an outwardly identical part without the appropriate QA/QC processes undertaken to certify it as genuine and to spec.

This may for example include destructive and nondestructive testing of parts, or it might include tracking the manufacturing process parameters to ensure correct outputs. For example, a cast component has sufficiently low levels of porosity, inclusions, etc. that might in time lead to premature failure. Or it might mean that there wasn’t sufficient record of the brew of the metal going into the casting or the casting process itself to confirm the part has the requisite material properties. In all but the most dire circumstances, it’s nearly impossible to verify whether any of that was done correctly just by looking at the part; for all intents and purposes, it’ll look identical to a real part.

In the case that the OP references regarding Virgin Australia [1], the parts were a low-presssure turbine blade and a high-pressure turbine nozzle seal. Both of them would fall into situations similar to the above. If cast, the turbine blade would need to prove what I outlined, amongst much more. If machined from billet, it’ll still need proof the ingot itself was manufactured correctly which mirrors a lot of the above. In the case of the seal, there’s similar processes to prove that the non-metallic material is to spec so that a Challenger-style failure doesn’t occur, except within expected operating parameters.

The link I provided regarding Virgin Australia gives much more detail about the core issue at play. This isn’t a situation where manufacturer B is stamping its parts as made by manufacturer A. It’s where manufacturer B says it can make a part compliant with the specifications, same as manufacturer A, but then does not have the required documentary evidence that it meets those specifications.

1: https://www.smh.com.au/business/companies/two-virgin-aircraf...
> Why would anyone do that unless the part was inferior?

Could be refurbished or used parts being sold with or without inspection to save cost on (re)certification.

We just don’t know at this point.
The "mini" distros were fun in the time of 128mb usb sticks, where you had to find some tiny distro to fit onto it...

But now, i can buy a 128gb usb drive for ~7eur at my local supermarket, why even bother with "mini"? Just install a full ubuntu, apt-get install everything else needed, possibly neded or just "nice to have", and you still have 115gb free for other stuff. Split the drive into two partitions and have one encrypted for private data, and you're done.
All their examples seem to have only one floor in the buildings.
Carbon or tungsten I don't know, but sand as a thermal energy storage medium can be quite economical. Energy loss scales with the surface area (^2), energy stored with volume (^3).

With grid scale, above certain dimensions, you can store energy for months while maintaining economic viability.

Even for single days or weeks it makes sense. You need hot water in your home 24/7, but sun doesn't shine every day in most regions.
This post basically argues you can be a successful feature factory if you’re driving feature prioritisation with data… but when you’re small, you can often get away with it because eg. You’re feature cloning a competitor.

It’s sad to see this seriously proposed, because it shows a deep lack of understanding.

Features are never the problem.

You can have a million features and be working on a million more and be perfectly ok, if those features do not impose constraints.

Constraints are the problem.

When you add a feature, well engineered or not, you probably add some constraints to your system.

As time passes, the effort to maintain all the existing constraints scales with the constraint count.

The difference between a feature factory and good engineering is that good engineering means when you implement a feature, you minimise the set of constraints it adds.

There is no amount of data and thoughtful prioritisation that can save you if you don’t put effort into understanding and maintaining your constraints, and if you don’t understand your constraints, you can’t thoughtfully discard some of them when you need to.

When you’re small, the set of constraints you have is small, so solving the N constraint problem is easy.

As you scale up, the problem becomes harder.

You can have a big product, but if you don’t understand the difference between features and constraints, you’re doomed to one of those “why aren’t we agile any more” conversations.

Feature factories aren’t bad because they’re fast. They aren’t bad because of a focus on shipping or iterating and pivoting… they’re bad because they slap on constraint after another onto a system until you can’t breathe without something breaking.
I feel like this is kind of missing the forest for the trees.

Making super-realistic telepresence in VR is really hard -- absolutely. And Meta is the kind of huge tech company that might have the resources to do it.

But do you need super-realistic telepresence to be a useful remote work tool? Who knows?

Slack is fairly useful for remote work (arguably) and it's mostly just text, emoji and meme images. Online text chat has been around for decades and Slack is a decent implementation of it (way easier for most people than IRC, for example). What are some more useful tools that could be made for remote work, and why isn't Meta building those?

Edit to add: if you're taking Snow Crash as your starting point for "metaverse", I think the important point is not "it's a super-realistic VR experience"; the point is that "it's a cool and useful place where people like to hang out, so a lot of life and work happens there".
Why and how do you track tobacco? Is that a typo?
That's the operating system I feel safe to have my business and private data on /s
DCF77 – A German longwave time signal
I'll probably end up like this with my Pixel 4a because every single of modern phones feels like a downgrade. Larger, heavier, no headphone jack, unnecessarily more powerful CPU to drain the battery faster, all that stuff.

I used to be excited about technology. I no longer am. I may consider upgrading to something with a 4" screen however. That would truly be an upgrade.
The parent was looking for evidence for why someone could write tests easier with dynamic languages. A long waiting time for type checking to finish came to my mind first. I think hello world is a valid example when talking about unit tests.
Content will be flooded with chatgpt waffling on too
Couldn't it be just a shell of carbon or tungsten, but the bulk of material inside be molten sand, or something else "dirt cheap"?
It happens after the first time most likely, but before this one.

It's kind of disingenuous to dismiss a free-market solution because it is on some level reactive. For all we know, in the absence of government, when planes were invented and accidents started happening, people got together and started doing this on their own.

Sure we could argue "something something greedy profits", but even then, we have to assume action on the part of consumers, companies, intermediaries, etc. It's a valid business model to provide a "certification" service, and there are many examples out there of just such a thing if you squint.

Further, we really can't discount the "laziness" and "apathy" that is caused by over-reliance on government and what it purports to do.
Other People’s Money TM!
If anything, the past years has demonstrated that crashes are now caused by "certified software upgrade" (I’m refering to the 737-MAX fiasco)
>> GPT-4 took months to train on a supercomputer and it generated a neural network of hundreds of gigabytes. What exactly was that supercomputer doing for several months and what exactly would the neural network represent if not a world model?

I believe GPT-4 was trained on a server farm, not a single computer. In any case what it was doing all that time was going over and over the text in its gigantic training corpus, which was of petabyte size, and optimising the objective P(tₖ|tₖ₋ₙ , ..., tₖ₋₁) i.e. the probability of token k given a "sliding window" of the n preceding (or surrounding) tokens.

There is nothing in this objective that needs a world model, and it is really not obvious why optimising this objective should lead to development of a world model, rather than, or in addition to, a model of the training corpus.

It is easy to see how this stuff works. You can train your own language model easily, although of course it would have to be a smaller language model. For example, you can train a Hidden Markov Model on the text of freely available literary works on project Guttenberg, or on wikipedia pages, and without too much compute (an ordinary laptop will do).

In fact, I recommend that as an exercise and as an experiment to gain a better understanding in how language modelling works, for those who are curious about questions regarding their ability to model something beyond text.

A good textbook to begin with statistical language modelling is "Foundations of Statistical Natural Language Processing" by Manning and Schűtze:

https://nlp.stanford.edu/fsnlp/

Or, just as good, "Speech and Language Processing" by Jurafsky and Martin:

https://web.stanford.edu/~jurafsky/slp3/

Or, if you don't have the time for an entire textbook, "Statistical Language Learning" by Eugene Charniak is an excellent, concise introduction to the subject:

https://archive.org/details/statisticallangu0000char
Data can be copied. Giving your data away doesn't make it less valuable to you.

Data is a moat. If you share it you're giving your advantage away.
Lol who cares whatever fiction people imagined to be "real" ai ? Logic general intelligence doesn't work. This does. Get over it.
While the Navy's time keeping mission is fascinating on its own (and itself was(is) a prerequisite for navigational abilities) the understated 'read-between-the-lines' reason the Navy looks "outward" is because that's how it points the nukes.
Yes, civilization would have largely survived a partial and temporary collapse of the US healthcare system that was a potential outcome from covid.

There were multiple countries where the medical system came close to collapse. India in 2021 is a case study of a medical system pushed beyond its limits (https://www.nytimes.com/2021/06/28/world/asia/india-coronavi...) and civilization largely continued.

But there is a lot of latitude between normal and survived.

Let’s assume that US policymakers considered taking no-action and let the ICUs collapse. Could policymakers in that scenario reasonably expect that teachers would continue to teach? Would the school system function if 20% of school teachers decided to not risk death and opted out?

That answer was easy to get and the answer was that schools would be shutting down.

How many essential workers would opt-out? How many need to drop-out to care for children? How many because they are sick? For how long? How does that impact fuel and food distribution?

Can we expect crowds would gather at hospitals? How many in that case become violent? How do we control crowds? Do we call in the national guard?

I’m not sure I can see any scenario that a policymaker could consider where reducing spread wasn’t the only viable option.
That doesn't necessarily follow. Film data can be copied, but production companies don't give them away.
Charter and Comcast Officially Roll Out Xumo Streaming Box
Not a stupid question at all. If you're building anything in the realm of real-time gaming or high-frequency streaming, WebRTC is your go-to. It operates on UDP, which means minimal latency and rapid data transfer, keeping user experiences smooth. Plus, it comes with built-in NAT traversal and encryption, saving you from some standard dev headaches.

While originating in the browser as a P2P tech, using a Node WebRTC library can gain you server-side control for even better performance. At the really sophisticated end that can be intelligent routing and on-the-fly quality adjustments, so you're not just faster but smarter in delivering content.

I think WebRTC is essential for any real-time project, and coupling it with Node.js takes your tech stack from good to very good. We use it in BrowserBox to stream the viewport of a remote browser: https://github.com/BrowserBox/BrowserBox
The post didn't question that, it raised the question if they should not be considered invasive everywhere/or at least it can be read like that.

In Western Europe, not really to that end other than quite localised.

But even then the discussion has to be what is a native species (with birds that can get quite odd with species disappearing and reappearing hundreds of years later, for example). There is just no real nature left, i.e., more about deciding when to make a cut.
Sure it does. A secret stops becoming a secret once you give it away to enough people. I feel like you're trying to justify piracy but picked the wrong argument.