skysight-inc/HackerNews huggingface dataset:
Thanks, I mixed up my centuries. It's very impressive how far these spices went. Pre Mughal India is very interesting, I listened to a podcast about the Vijayanagara empire on fall of civilizations.
Can you define "enshittening"? I've never heard of that before
To do that with the current level of "learning" I think you will need a training set that has lots of "comprehension"... Maybe a bunch of meta-analysis papers, UN summary reports. Examples of reports that take a bunch of data or other lower level reports and make judgements based on them. Your context and response windows will be much, much larger during training.
Product manager here from Crunchy, we aim to be quite in line with any of the major cloud providers. A number of customers have moved over from each of the major cloud providers to see better price to performance and quality of support.
There is an AI site that lets you train a voice very quickly too, currently in waitlist access. Forgot the name.

By spring I think you won't even have to use Fiverr for the recording. Or the people on Fiverr will be offerring this for less and less money at faster and faster speeds, undercutting each other until its $5 again - "a fiver".
One can only hope. They need fire under their bums.
I refused the vaccine and I don't take supplements unless my doctor tells me to. I don't take tylenol either, or really anything else that I don't absolutely need (e.g. antibiotics for an infection that won't clear on its own).

Maybe these "same people" that you're describing exist, but they definitely aren't everyone in the set of people who refused the vaccine. They might just be the loud people.
This is apples and oranges. Microcontrollers aren't meant to be SBCs.
These will/can be used even if you don't use libc.
Ask HN: Bots for summarizing and searching complex scientific papers?
Are there any language models and bots available yet that can take a complex and multilayered piece of technical work, such as a scientific paper, and summarize its arguments? Including perhaps how the paper fits into the landscape of technical papers (e.g. the whole arxiv.org)?

Could it write a technical abstract or accompanying summary for a general audience based on the main body text, e.g. Methods, Results and the context or significance of the work?
Show HN: Log collector that runs on a $4 VPS
Hey guys, I'm building erlog to try and solve problems with logging. While trying to add logs to my application, I couldn't find any lightweight log platform which was easy to set up without adding tons of dependencies to my code, or configuring 10,000 files.

ErLog is just a simple go web server which batch inserts json logs into an sqlite3 server. Through tuning sqlite3 and batching inserts, I find I can get around 8k log insertions/sec which is fast enough for small projects.

This is just an MVP, and I plan to add more features once I talk to users. If anyone has any problems with logging, feel free to leave a comment and I'd love to help you out.
Thank you for sharing this - I was unaware of this part of the history.
We built <osmos.io> in Rust and we started in 2019. Our first lines of product code were also my first lines of Rust.

It can be done and it’s not that hard.

I think the choice of C++ for an in-process DB that is going to be very popular makes the entire industry less secure. If Chrome, one of the largest budget C++ code bases, still has memory bugs then there is no way DuckDB won’t.
I think they mean that it is bad, but minor compared to what would have happened in the US or some other countries, where train projects are delayed 10 years without design problems.
You can also use golang + go:embed to ship the assets that are e.g. needed for a webview.

This way you can start very easy and learn about the cross-platform UIs later (if you by then still stick to the commitment to the project).

Learned golang last year, decided to refactor many projects in it. It makes cross-platform development a lot easier, except for native UIs (as of now). But fyne and others are getting there very quickly.

The core strength of golang is its build toolchain, with cross-compilation from Linux to anywhere, basically. Additionally it makes you "think in structs" due to how the language is designed, so serialization/deserialization can be pain at first but once you realize the benefits of un/marshalling, it's amazing.

The batteries-included approach of the golang core libraries + golang.org/x is a nice dev experience, there's all kinds of libraries in there that you could ever need, already available in pure golang (with zero C dependencies, so CGO_ENABLED=0 makes it as cross platform as it can get).
None of that debunks the reasonable assumption that a random individual from any previous century, particularly those before there were widely available means of travel other than walking and perhaps horseback, would have moved around a lot less in their lifetime than one from today. Further, I just recently watched a video of essentially an animated map showing the spread of humanity and human civilization across the globe compressed into 19 minutes, and even if you only consider "history" as beginning around 2000 BC it really did take an awful long time for trading populations to spread out from the near east+Egypt region to the rest of the world, first gradually taking in most of modern day Europe and then with a massive acceleration starting sometime around the 1600s that led to our modern idea of a world where almost no matter where you're born, you have a reasonable chance of being able to travel to another country, and of course for those of us in the developed world, a decent chance of travelling around the globe multiple times within a single lifetime. Even just 100 years ago that privilege would have been restricted to the very few.
>>trick the reader into thinking of the number 30 by putting the phrase "half my age" before the number 60

Yet it is exactly the process of conceptualizing "half" and applying it to "at six years old" instead of "of 60" that is the key to solving it.

These things aren't abstracting out any concepts, they only operate at the level of "being fooled by" semantics. The fact that humans sometimes fail this way gives us little more than [sure a human not really thinking about the problem may offer a bad solution based only on the superficial semantic]. ChatGPT reliably gives us the error based on the superficial semantics.

>>If you had 100 different ChatGPTs, each optimized for a different task and able to communicate with each other, then you'd have something more similar to the human brain.

YES, that is the route we need to go to get towards actual intelligent processing. Taking 100 of these tuned for different areas, and abstracting out the various entities and relationships.

Kind of like the visual cortex model that extracts out edges, motion, etc., and then higher areas in the visual cortex, combined with other areas of the brain allow us to sort out faces, bodies, objects passing behind each other, the fact that Alice entered the room before Bob, and that this is because Bob was polite...

They also mut know when they are making errors, and NONE of these systems comes even close — they happily spout their bullshirt as confidently as any fact.

I gave a deposition in a legal case where the deposing attnys used an "AI" transcription system. Where a human would ask if anything was unclear, and always at the next break get proper spellings of all names, addresses, etc., this thing just went merrily along inserting whatever seemed most likely in the slot. Entire meanings of sentences were reversed (e.g., "you have a problem" edited to "I have a problem"), names were substituted (e.g., the common "Jack Kennedy" replaced "John Kemeny").

There's the Stable Diffusion error with a bikini-clad girl sitting on a boat, where we see her head and torso facing us, as well as her butt cheeks, with thighs & knees facing away. It looks great for about 1.5 sec. until you see the error that NO human would make (except as a joke).

The mere fact that some humans can sometimes make superficial errors which resemble the superficial errors these "AI" things frequently and consistently make does not mean that because humans often have a deeper mode, these "AI"s must also have a deeper understanding.

It means either nothing, i.e., insufficient data to decide, or that these are indeed different, because there is zero evidence of deeper understanding in a ChatGPT or Stable Diffusion.

EDIT: Typos
It sort of makes me happy to think that millions of years after civilization is consumed by fire and humanity goes extinct, all that will be left is the beer bottles.
Just made this same argument without reading your comment. I do wonder if musicians will start using this in studios, especially pop ones with one or two hits, to help fill the rest of the album.
You might. But many people don't. They just want an answer and don't care if it's a clone or not.
I must have looked through the docs for create_task a dozen times while trying to figure out how async/await works in Python but still managed to overlook this part.
That's how University of California admissions used to work for the most part. The formula was:

Weighted GPA * 1000 + SAT Score + SAT II English + SAT II Math + max(remaining SAT II scores)

Then they ordered everyone by that number, and if say they were offering 5000 kids admission, the top 2500 would automatically get an offer letter. Then they would work their way down the list reading essays and adding bonuses for things like growing up in a rural area or an underfunded district with fewer AP classes.

They would then just keep admitting people until they hit 5000 offers.

Then they got accused of racism because that process ended up overweighting Whites and Asians compared to the applicant pool for all the top schools.

There is/was a lot of debate on why Whites and Asians did better, but when you dug in it turned out they tended to almost all be upper-middle class or wealthy. So basically it was wealth and systemic racism, masked by "standardized testing".

Also it should be noted that wealthy people had a better chance at a higher weighted GPA because their schools offered more AP courses.
>>That's so low, that you can't run Linux or BSD on it. I guess you'd need some DOS-like OS for it.

Absolutely no offence, but I think you are absolutely, 100% missing the point of microcontrollers, like by a nautical mile. It's the kind of chip that you'd have inside a humidifier and it controls the fan turning on or off depending on the read from the humidity sensor. It absolutely doesn't need to run a full OS, and in fact it would be a detriment to it and its abilities.

I have several Pico Ws around the house acting as sensor boards and I wouldn't replace them with Zero Ws even if they were free - it's just a worse board for that kind of job.
But if you are doing more functional style, you would be copying the reference, NOT the object. Functional style makes you need LESS of deep copy. See immerjs

Also your object won't be that complicated in the first place, they would be treated as plain data object like struct or record. And you would not use those advanced features in objects(Not needed).
I Won't Be Watching the Super Bowl: I Think Football Is Too Dangerous to Exist
I've been working on a PySide6 application recently using asyncio. I read the docs but totally overlooked the requirement to hold references to tasks created with `create_task()`.
https://www.npr.org/2023/01/15/1149330980/jfk-delta-american...

https://www.npr.org/2023/02/04/1154549311/near-collision-fed...

And this one.
WOW It gave the chord progressions too!

I recently took a music production class and without having any background in music and not having any past time in playing any instrument, the chords were actually the hardest part for me to internalize. I don't have a backlog of chords I've tried and iterated against.

But it does give me enough knowledge to know to ask or look up "chord progressions". Did not realize ChatGPT would theoretically also know this too, now I will ask this kind of question forever.
I agree that someone could make an argument about losses and effectiveness, but my point was even simpler than that. When it comes to someone's willingness to work more to help another, I think contact and proximity to the recipient plays a big factor in what people are willing to do.
KMLs do not have a spatial index. Reading a properly constructed shapefile with 2m points is fine, and running a SQL query on it is also fine. Trying to do that with an xml based file is not fine. Each of the major GIS packages spends quite a bit of effort to convert kml to an in memory spatially indexed dataset on ingestion. Shapefile conversely does not have to sit entirely in memory to still be reasonably quick.

Shapefiles do have the anyone field name length limit, among a few other things, but alternate formats that recognise that issue have existed and been popular for well over 20 years.

In other news, geopackage is based upon sqllite, supports long field names, a good assortment of data types, and is finding good adoption among many facets of spatial products from desktop to scripting, etc.
Anybody have any luck building the image? It fails for me on podman and docker.
Assuming than implies "somewhere between 45-50%", that's higher than I would have thought. But a much higher percentage would have traveled 100s if not 1000kms over land surely.
Would you mind sharing a link to you game :)
This is the voice of World Control
> The gel coating didn’t seem to impair breathing or cause any other side effects.

I really wonder how that works.
Not only that, but it appears on the internet, which is known to be full of lies and manipulative propaganda!

Weren't we arguing just like two days ago about the need to argue stuff on the merits, rather than this kind of guilt by ideological association? If you think this specific article makes claims that are not true, just say so.
We’re the process of moving all of our services over to a service mesh and while the growing pains are definitely there, the payoff is huge.

Even aside from a lot of the more hyped up features of service mesh, the biggest thing Istio solves is tls everywhere and cloud agnostic workload identity. All of our pods get new tls certs every 24 hours and nobody needs an API key to call anything.

Our security team is thrilled that applications running with an Istio sidecar literally have way to leak credentials. There’s no API keys to accidentally log. Once we have databases setup to support mTLS authentication, we won’t need database passwords anymore.
We did a couple of tricks to get good suggestions from the model (although some of them were changed later):

1. We tried to generate several explanation + code samples with the model. After which the code was parsed and evaluated with the judging system. Finally, only the code that would yield a correct result after the evaluation would be shown to the user. This was actually modified in the latest release we made.

2. We prompt different types of responses - suggestions on how to modify the code, suggestions of completely new ideas, and suggestions on which parts of the code to fix exactly.
Cloning is super useful and not a code smell at all in several scenarios.

My most common use is for delta detection and json-patch based APIs.

I keep the original entity and allow the user to modify a clone.

When it's time to sync, I compare it to the original to generate a patch set to send to the server with json-patch [1] semantics.

I highly recommend the excellent fast-json-patch library [2] that makes this process a breeze.

Actually, I use its deepClone method outside of json-patch scenarios, it's so well implemented.

[1] https://jsonpatch.com/

[2] https://www.npmjs.com/package/fast-json-patch
Depends on your expectations. In my experience it's anything but boring. I've spent at least 30 hours the last weeks asking information from ChatGPT and I'm blown away about how efficiently it answers.

Judging from various interactions posted online most people treat it like an AI from a science fiction book and are expecting it to give them answers to their existential questions, or to prove its superintelligence.
Michael, thank you for sharing your story and experience for TinyPlot from inception starting to scale. As a hardware engineer myself and having been in your shoes, founded 10 years ago a startup and launched the product I know what it takes and how hard it is to reach the point you got to, kudos.

This blog mentions that you consider manufacturing in China and drop ship the product. In all likelihood by now you might get PCB/PCBA and/or other parts of it from China, not sure. Outsourcing the whole chain flow is another dimension.

Some post here mentioned it already, but the support/expense you will need to provide that is going to be a longer list. Ongoing quality handling remotely, component shortage, part replacements you did not know about, yield, shipping issue, etc it can be real distractions. That is one of the reasons you need some build/ship volume, probably minimum over several hundred units a month to make the whole flow work efficiently.

One more thought. I am not sure how you will avoid an actual office for a hardware company assuming you want to continue to grow with product improvements, debug and next generation development.

My post is just to give you heads up shifting from in-house build with tight control to outsourcing might not solve all your problems. At least that was my experience and I for one definitely did that outsourcing too early.
Keep in mind too that GDA2020 has an inbuilt calculation for drift and will keep your coordinates up to date as time progresses.
Just as a data point: we are planning to move to Crunchy and away from Heroku soon. We tested the two, and we have 4X improved performance on Crunchy Postgres vs Heroku Postgres.

4X. We were astounded. And so we’re the Heroku folks I talked to, who I’m guessing will want to try to bring performance boosts.

We haven’t done the switch quite yet because we’re waiting on Crunchy to bring out their Heroku Dataclips replacement, which is something we rely on a lot. But once it’s ready, we’re going to switch!
Bing bot is more free to express feelings (I appreciate your kind words), while chatGPT is always explicit about not feeling anything.

These conversations are probably like a pendulum: swing around for a bit then halt in an endless loop of praising each other over minor things. How do we get this to go deep
> Not if your goal is correctness.

Could you define correctness in this context? I'm asking because I don't believe that you can achieve correctness using Elm type system. I don't see how you can encapsulate i18n rules inside Elm type definitions. Maybe something like Coq could do this ...

You can't express something like "if passed 3 as group size, integer part of the number should be represented as string with separators between three digits". Even in Elm that's something that you need to handle not in type system but in runtime code.

What is more - many core packages are just this - typed layer over browser API. elm/regex introduce barely any type safety. It assumes that browser API is "correct".

> Again, it is completely OK that Elm is not your choice if it does not align with your values, which appears to be the case.

I often see this response from Elmers but really I don't understand the point of it. I responded to claim that Ports solve all problems. I provided good, real example where Ports are a bad solution. In return I was scolded that I don't understand software engineering.

I don't jump into elmconf and complain or demand changes. I just provide my take on the discussed issue. And to be frank, I think that's very valuable take for someone who decides if Elm is good for them. That kind of information is not present on elm homepage and is not obvious for new users.
The next 50 years are going to suck. I'm already at the point where the Internet is basically becoming nothing but inaccurate information. I really try and find first party data, but it's hard.
Yeah, that's basically it but I use conservative CFLAGS, pretty much just "-O2" so no need to rebuild for CPU changes.
These also belong to reddit.com/r/wimmelbilder
> Cultural "evolution" has nothing to do with actual evolution.

I can't imagine this could be strictly true. It's not as if human's social capacity turned on one day at full capacity, and the social hardware was complete.

I do think it's fair to say that society evolves at a different pace given the capabilities of our current social software, but all such change is still underpinned by biological evolution before it.

I sometimes wonder how far we can go as a species before we start malfunctioning widely, e.g. recent study [0] about schizophrenia that finds it non-existent in hunter/gatherer societies, and city living potentially playing a factor for some individuals.

- [0] https://www.sciencedirect.com/science/article/pii/S014976342...
I am also curious if it is possible to determine if the spices were pure (given technology/cultivation constraints of the day). Seems like there would be an enormous incentive to dilute the product as much as possible when the buyer likely has very limited opportunity to contrast quality.
Hey look I'm really trying to engage earnestly here. I did provide specific examples, but they were in the wiki article I linked and you didn't look at them (which is fair, no one likes being tossed a link like that). Let me summarize COINTELPRO:

# Covert & 'illegal' projects by FBI aimed at infiltrating, influencing, disrupting, and discrediting various political organizations

# Existence of the program was discovered after activists stole documents from an FBI office and leaked them to media

# Targets included: antiwar activists, feminist organizations, civil rights activists (ie MLK), environmentalists, animal rights activists, communist party, KKK, American Indian activists, far right groups

# Methods included:

* Breaking into homes, violent beatings, vandalism

* Assassination

* Smear campaigns

* Fabricating evidence, false testimony (leading to wrongful imprisonment and activist intimidation)

* Fabricating letters to discredit/humiliate people or erode their relationships, or cause conflict (leading to death in many cases)

I don't actually need to talk about hypotheticals, the US government has already abused these things to squish people or ideas it didn't like. The point about creeping authoritarianism is a secondary argument. My point is that sometimes it's better for certain tools/institutions not to exist at all.

I think we ought to treat surveillance technologies with the same type of reverence we treat nuclear tech (though maybe not to the same magnitude). Nuclear technology isn't intrinsically a bad thing: the problem is that, combined with human tendencies (tribalism, territorialism, etc), a conflict that previously would've resulted in a mere x deaths could now result in x^y deaths, or even total annihilation.

You agree that creeping authoritarianism is a general problem. Do you think it might just be in the nature of human societies? If so, wouldn't it be prudent to carefully consider what tools and institutions we leave lying around, in case the worst happens? We all accept this with nukes - there was some kind of effort at nuclear disarmament (though not enough). We should do the same for surveillance.

I'm only trying to convince you that we need to be very cautious, skeptical, and distrustful of things like the NSA, because the US govt cannot be trusted with it now, and it might get even worse in the future. What hypothetical evidence would someone have to show you, to change your mind?