skysight-inc/HackerNews huggingface dataset:
They may eat the same insects but at different phases of their life cycle.

Some insects crawl before they fly. and some even fly before they crawl I imagine.
- Software costs will fall a bit

- More software will be consumed (Jevons paradox)

- Therefore more demand for skilled engineers

- And the LLMs will not be able to build things end to end

- Salaries at the top end will rise, since an AI augmented senior engineer can deliver more value

Far future: no more software engineers, but also no more human work of any kind. Post scarcity society.
Based on what I knew from about five years ago, "it's complicated."

At least at the time, brands could buy a slot. I wrote for a company a couple of times. I think the pieces were very lightly edited.

There were/are also "contributors" who were mostly individuals who didn't have gross obvious conflicts of interest in the topics they wrote about. I think they either wrote for free or were paid some nominal sum. Again, I think there was light editing.

The latter is also what you saw with the CNET Blog Network which I did write for over a number of years at a time when everyone was branding and blogging including journalists and analysts. (I declined to accept money for various reasons. Other people were paid a modest amount.)

The problem with these things is that there are always going to be conflicts of interest and biases to various degrees. Some organizations try very hard to weed out direct examples of the former at least outside of explicit op-ed pages. But it's hard to manage. To give a current example, maybe you're bullish on generative AI because you work or consult for a company doing it no matter what reservations you have. Or maybe you work for the company because you're bullish on it. Or back in the day Microsoft's a client of your's because you really like what they're doing and they engaged you and passed on the Unix expert who didn't think much of what Microsoft was doing.

CNET got increasingly uncomfortable with the whole model and dropped it.
"gentrimmigrants", may I borrow that?
This sounds abnormal, are you using io_uring_enter in a way that asks it not to return without any cqes?

I don't have much of a feel for this because I am on the "never calling io_uring_enter" plan but I expect I would have found it alarming if it took 1ms while I was using it
Handstands wont win you any marriage material partners, though maybe it can win you 1 or 2 numbers in a mall in Vegas. Preferences are diverse, but the same biological needs drive humanity since hundreds of thousands of years ago. Beauty and ambition have both evolved as a result of procreation.
We are going to have a Dell PowerEdge review tomorrow. We call that a server or more than one servers not server units so that would feel strange to me.
The Rules of the Games in Tudor England
Sort of. I’m not the guy you asked, but in our work we’ve had trouble making good use of GPT for most things. On one hand it’s been a powerful tool for non-developers, and it’s helped a lot of our more technically inclined employees to automate part of their workflows (and maintain the automation on their own) in a way that no “no-code” solution has ever done before. For developers, however, it’s been giving so many terrible results that it’s not really been too different than simply using a regular search engine. Sometimes it’s much faster, but other times the lack of “metadata” and “other opinions” like you may find on a site like StackOverflow through time stamps and comments have made it significantly slower.

Anyway, getting back to the sort of part of my answer to you. We’ve had an issue where junior engineers trust GPT a little too much. This is more a psychological I suppose, but where they might not take what they find by “google programming” for granted, they are much more likely to believe that what GPT is telling them is correct. Which can be an issue when what GPT is telling then isn’t correct. Where our more senior engineers will laugh at it, and correct it’s mistakes, our juniors will trust it.

I’ll give you one example, we had a new programmer pull some information from a web-service and have GPT help them handle the json. GPT told the developer to disable our rules linter and handle the json dynamically, doing something like items.items[0].haps, and other such things. Which works, until it doesn’t. You can scoff at us for using a lot of Typescript on the backend, and we certainly shouldn’t have allowed this to ever get build in our automation, but that would still create something that might cause some really funny errors down the line. I know, because part of why I’m there is because the organisation used to do these things all the time, and it’s lead to a lot of “funny” things they needs to be cleaned up.

Anyway, this isn’t necessarily a criticism of GPT, because it still does other things well, but it is a risk you need to consider, because I do think someone is going to be able to justify those answers you talk about, and if it’s not GPT then it’ll have to be the developer who uses GPT. In many cases it won’t be an issue, because we live in a world that’s sort of used to IT not working all the time, but you probably wouldn’t want your medical software to be written in this manner.
During the FTX fallout, I saw many articles share here -- some from major and others from mid-sized media websites. Across the board, they were mostly worse that any reporting from Financial Times (ft.com) and their blog FT AlphaVille (ftalphaville.ft.com). FTA "guerilla analysis" is so good that it breaks major scandals 2-5 times per year. (See Wirecard in Germany.) So, no, not all big media websites. Plus, The Guardian (UK) does some excellent reporting in the United States on touchy subjects that domestic media does want to touch. (NZZ Neue Zürcher Zeitung is legendary in German language media for the same type of coverage in Germany and Austria.)
Compose Multiplatform: Shared UIs for Android, iOS, Desktop, and Web
That's interesting. I had a similar experience, where I was proficient with computers and programming before entering university, chose to get an EE degree instead of CS, and then immediately went into software engineering where I've never used my degree. I've long since forgotten pretty much everything EE-related that I learned in school, so my degree is also pretty worthless at this point.

But I never got advice encouraging me to get an EE degree as a way to get a "leg up" on SWEs. Most of the advice I got was that I was making a mistake, and should get a CS degree instead if I was interested in programming. I went ahead with the EE degree anyway, but it's never seemed to hurt me in the eyes of potential employers, at least not that I've noticed.

Can you say a little more about how employers held your education against you? I've also been asked questions about why I chose various aspects of my education and job history, but never assumed it was hurting me as long as I gave a reasonable response.
Curious, why is that a "no-no" for you?
Yup Big tech, which is really big advertising if you take Google+Meta online ad market share, get their main revenue from Likes/clicks/links/views counting + personal data. As info exploded you needed this crap to work out what to show ppl.

And ppl have learnt how to accumulate status/power/cash by gaming those numbers.

Chat-GPT et al dont rely on any of these number. So all the infrastructure of the Advertising-Industrial Attention capture complex can be thrown in the sea. Which should have been done long ago but we got free email, video, chat, games, movies etc so we gave away attention for free.

Behind the morons talking abt "god like" ai and similar ridiculous bullshit are mainly ppl worried about how they are going to capture the chimp troupes attention(and through it cash/status/power), if the tools they have relied on arent going to work anymore.

Eventually AI startups will end up where Google and Facebook ended up cause how else to fund their server farms? Subscriptions are never enough. Just ask Newspapers or Netflix.
Is it? It might have even more computing power, but are cards now able to share VRAM now? My hands-on experience of all this is from a few years ago and I think it was not possible back then.
Reading comprehension failure on your part, or we're in violent agreement which you somehow chose to voice as disagreement.
Do you have any solutions to the (admittedly theoretical ) existential problems that will likely arise ?

I see the problem more like, a fail is an all or nothing fail, that’s it, everyone dies, maybe including the ASI (goes rogue and destroys itself and us), then what? Good outcome for anyone if we don’t understand what we’re doing?

I’m not saying you’re entirely wrong, or we need to stop, but I mean, we do share a planet with other species and children who probably have good lives ahead of them. So why rush into potential disaster, what is the actual hurry?

I know that many Silicon Valley elders are getting older and facing the inevitable, they see ASI as a way out of their own mortality. They’ve believed this for many years if you look at old footage, so giving up that dream is probably very hard to do at this point. But I do see it as a large reason for the push. Time is running out for the mega wealthy. I honestly empathise with them too, but I don’t think it’s fare to say everyone wants to deal with the risk.

I empathize with everyone damn it.

I just don’t want to witness the “he chose poorly” scene at the end of Indiana Jones happening for real on a global scale.
Yes, computers can handle base 20. The IBM 1401 business computer (1959) could optionally support pounds/shillings/pence in hardware, where there were 20 shillings in a pound and 12 pence in a shilling. (Britain switched to decimal currency in 1971 for reasons that should be clear.) It could add, subtract, multiply, divide, and format pounds/shillings/pence as well as its normal base-10 arithmetic. So it was doing base-12 and base-20 arithmetic.

I should point out that this was implemented in hardware with transistors (lots of germanium transistors), not microcode or software. In other words, the three fundamental hardware datatypes of the IBM 1401 were arbitrary-length decimal numbers, arbitrary-length strings, and pounds/shillings/pence. Of course there were two conflicting standards on how to represent pounds/shillings/pence, so there was a knob on the computer's front panel to select the standard.

(This isn't directly related to the Inuit base-20, but I'm sure IBM would have supported Inuit base-20 if customers would pay for it.)
I don’t know enough to say for sure in this case, but if there’s one issue I have with Go performance, it’s the excessive syscall overhead for standard networking stuff. If you do high bandwidth or high concurrency you often waste a large fraction in syscalls, which can be reduced greatly in theory.

For instance, socket deadlines have iirc 2 syscalls per timeout extension, which is sold as best practice for network timeouts.
Sometimes 2-3 tries but that is also from pacing. I usually have my laptop out to reference quickly but no prompter. People can tell when I read from one, so I have just had to get comfortable without reading.
This is true, but Elon Musk is, let's say, a producer of content that drives engagement on the platform that is Twitter. I'd say he gets enough tax breaks and such to qualify for a state shill label. That's not even considering his many years' long business affiliation with the Saudis, even before he decided to piss away 44 billion dollars to buy one of the world's largest megaphones.
> Here's the thing, current computational power isn't enough to achieve the scale of model that would be required for "god like" AI.

I don't see how that is the case at all. The human brain only needs about 100 watts. A GPT-3 instance only needs a few GPUs and maybe 1000 watts. GPT-4 is presumably in the same ballpark, let's say 10000 watts to be generous (even though it's probably closer to 1000 too), but still small enough to fit inside a full height rack.

Many datacenters are megawatt-level. Seeing how GPT-4 is already human-level at many tasks and watt-to-subjective-capability increases seem to grow linearly at worst, an AI could be ran in a single data center and perform 100x GPT-4 abilities. I'm not sure what 10x, much less 100x GPT-4 abilities would be, but that sure sounds like godlike or near-god to me.
It's absurd that some rich guy is micromanaging such cases and deciding the outcomes willy-nilly.
Pondering as well... Machine learning should have some applications
This is because Italy has lots of small towns/villages.
Large cities (e.g. Milan) are an entirely different story.

Also, if you live outside of large cities... you can't do much without a car, which implies another set of problems.
Wikipedia doesn't show ads now? So what is that giant popup that occupies half my screen asking for money every time I visit it? That's an ad -- and one more obnoxious than most.
See https://rationalwiki.org/wiki/AI-box_experiment
Looks similar to Bazel’s Starlark language[1].

[1]: https://bazel.build/rules/language
These missiles are in outer space, at the altitude of the ISS or higher.

https://en.wikipedia.org/wiki/List_of_North_Korean_missile_t... (*old* ICBM tests, not today's one)

- There's no extant technology to shoot them down;

- They're not in Japanese airspace or territory (does not extend to orbital altitude);

- If they were to crash in Japan by mistake, there's no benefit in shooting at them, because they'd be untargeted debris with no warheads. An anti-missile missile is just additional debris with extra steps.
>novel, general logical problems.

What might be a couple examples of that?
> it's still on the level of CS undergrad.

I have 21 years of professional experience as a software engineer with a bachelor in CS before that and have never heard of "Manhattan distance metric", "A* implementation", "D*-lite" or "Theta*" until now. I'm sure if I'd read the explanation of those things I'd eventually figure it out (and I'm sure an LLM would make more sense if fed descriptions instead of gobbledygook.
This is silly. Assembly is an abstraction too. Do you think the CPU actually runs the code you give it? Of course not. There's microcode, register aliasing, speculative execution, etc.

Even assembly itself has symbols and labels, which are themselves abstractions.
What algorithms and data-structures do you commonly use when shutting down useful services?
Very interesting, Vlang sounds like a cool project and kind of a dreamy language if it can become more stable.

However, it doesn't speak for the most popular languages but maybe rather to the most active ones? I really doubt that Vlang (as an example) is more popular than Python, PHP etc..
Yep, and even if it's (nearly) free (not the US) the opportunity costs of not working for a few years can be harsh. It depends, and I'm still not sure if I regret it, I keep telling myself that I learned enough interesting and useful things so that I recognize problems and can look up the solutions I once knew. In my case CS, and finished in 2010.
Library of Congress' National Recording Registry Inducts Super Mario Theme Song
A beginner's guide to code editors
Bullshit. You're just making things up. The actions you describe are generally not illegal. This is settled law at least since New York Times Co. v. United States.
Same problem

For some reason this seems to be trained deep into the GPT model. Even when you tell it in the prompt it doesn't exist sometimes it will contradict itself. That's why it can be an interesting test case
Then you realize that your CPU has hardware bugs, and you go design and manufacture your own CPU :).
Someone I know did that too. Published a blog post then started adding “author” to their credentials. Spoke at a local 10 person meetup about some node.js framework at the time and promptly added “speaker” to the list.
How would you know when the very existence of these new silos is hidden from you?

This is like saying "our model recognizes 99% of the AI generated images", but it leave out that you don't know the actual amount since when your model does not recognize that an image in the wild was generated by AI you dont know that it was generated by an AI.
I'm Haxorus. Thanks, Haxorus News.
Tutorial: Developing a RESTful API with Go and Gin
if you feel the need to carry firearms to a programming convention, then yeah I’m okay excluding them.

Many events, including the NRAs own events, prohibit the carrying of firearms in part or in full. This is normal.
Yes. Also on MacOS.

I am a fan of container tabs which allow me to use a website with multiple identities such as the AWS console and to constrain the tentacles of Facebook.
[+] for Brio, though it’s so expensive that i often joke I have half of my savings in these brio train sets.
Comprehensive Guide to Testing in Go
I would love chat with all of the following, maybe let them chat to each other: an gmail me from Google, a Hacker News comment me, a Reddit comment me, an iMessage chats me from Apple, a telegram me, and a WhatsApp/Facebook post me from meta.

I feel as though Google gmail me would be very efficient and wooden, and the iMessage me would be most authentic because that's the one I chat to my family and partner on. WhatsApp/Facebook has exclusively jokes I've made on social media and chats with my best friend, so they would be not-a-serious-person at all.

I think I've stumbled upon a plot for something here, I'd love to see this as a thing.
> Twitter only responds to requests for comment with a poop emoji now and hasn't officially commented on the controversy

He changed the corporate sign in SF to Titter as well. Sad.
My advice came from academic EEs. In my youthful ignorance, I failed to consider the potential for biased advice. From people with no industrial experience.

As for employers, some interviewers grilled me about my education. Others I deduced by de-emphasizing my education in my resume.
> Do you have any solutions to the (admittedly theoretical ) existential problems that will likely arise ?

I guess we can develop super AI then ask it to solve it. :P
Nope. Please explain which "law" you think they have broken? Let's have a specific citation of the US criminal code and relevant case law please.
It's astronomy.
Semaphore basically means "traffic light" in many languages.
I hear you. Here is a quick tip. For the next year try contributing to open source projects that you like and that have companies behind them.

After a while, either they will make you offers to work for them on the spot, or they will at least "fast-track" you through the interview process.

It doesn't work in all software areas (it is pretty difficult to do it if you are an embedded systems developer) but it works especially well in others (e.g. cloud)
I mean it’s what any “intelligent” species would do right ? :)
Quick thoughts:

- Identifying a specific age group or academic level, such as high school or college students. This will help you focus on the product development and marketing efforts to test on the most receptive early adopters.

- Incorporating adaptive quizzing algorithms will set it apart from existing solutions. By tailoring question difficulty based on a student's performance, you can provide a more personalized and engaging assessment experience.

- Go light on features and focus on the one thing (or a few things) that make your product stand out than existing tools. Test them with early adopters, and see what work and what doesn't. Iterate and refine. Pivot if necessary.
I've hired close to 100 developers across three companies that I started, and it has never occurred to me to compel a candidate to regurgitate memorized algorithms in an awkward, stressful moment because that doesn't test anything close to what they will actually do in a typical day.

Key point: I've never met anyone in the industry whose job it is to implement algorithms without reference materials all day long. It's more like... you might find yourself needing 1-2 clever bits a year, and the rest of the time you're tweaking model classes and hunting down UI bugs.

Algorithms are both easy to Google and these days, CoPilot will do the hard 4/5ths for you if you actually need them. It's also common that the really intense stuff is written by the PhD braintrust cofounder, not the people being hired after the fact.

What I want to know when I'm interviewing is simple: how do you approach solving problems; do you have an interesting personality that I'd like to interact with every day; are you the sort of person who has a strong instinct about what the next thing to do is, and will default to working on that thing without prompting?

Do you think learning new things is exciting? Are you able to admit you don't know something and do you feel comfortable asking for help when you're stuck?

Do you seem reliable? Are you a starter, a finisher or both?

Do you have a sense of humour? What do you do on the weekend?

Ultimately, I care what you know... but I am far more interested in your capacity to quickly master new things.
Oh, neat. TIL, TYVM!
I suck at those questions, and I hated those competitions. Yet I was the only one who would create things (hard- and software) in their spare time. I think some of these questions are insulting. Do you wanna get someone who solves actual realworld issues and interacts with real world challenges or what?

That being said I am easily the best/fastest programmer in my organization despite there being people who have 20 years more experience.
> 700km per hour in the Byzantine Empire

Interesting that Byzantine light seems to have been slower than modern light.
"complete failure of controls". Most traditional assets would call this criminal negligence, no?
Tyan (which was the ODM for the Intel boxes) and
Quanta are generally speaking in the same ballpark. Though you miss out on the extra QC that Intel or a Dell DCS would do for you if you order direct.
Kodi had 400k accounts breached
For what Apple's headset is going to cost, it better be a lot better than what's on the market now.
Actually, x86 assembly also embodies plenty of abstractions. Not sure on ARM or RISC-V, but x86 assembly instructions are not executed the way you'd think by any modern processor.

Essentially the processor reads a while bunch of instructions at once, splits each in the raw microinstructions, arranges them in a graph of dependencies, and then solves an optimization problem to find the best way to schedule nodes from that graph onto its internal execution pipelines. In real-world execution, you can't even tell what assembly instruction(s ) are the ones being executed at a partocular time - disparate parts of various instructions. Some instructions, like "mov ax, 0", don't even execute: they just serve to mark which the tens of real registers is now free to use for another symbolic register like bx.
If you also have duplo, search for duplo-brio connectors. Quadratic fun combining both toy sets!
I recommend you keep at it, I also hated interviewing and it would give me anxiety which made me draw blanks and under perform embarrassingly a couple interviews.

The trick for me was diligently applying to as many places as possible (that were at least somewhat of a fit), and eventually coming across one where the main technical part of it was "take home". Coding and discussing thought processes on the spot for an audience isn't something I'm good at it turns out, but solving a practical problem on my own time was fine.

It's ultimately a numbers game, the more places you apply to, the more likely you'll find an interview process that fits. That is the most important thing to keep in mind--shotgun blast those applications. It's hard not to take rejection personally, but don't give up and settle for a toxic job, that's even worse.