skysight-inc/HackerNews huggingface dataset:
The fun thing about computers being magic is that the magicians are usually more than happy to show you their tricks :)
most people ignore wwii was decided on baku.

it was the reason for Barbarossa, the first Germany defeat, and it was the only way Germany could replenish the oil used on the Russian offensive, which forced them to squeeze the polish camps dry. they lost it one baku.

it was also where most modern billionaires made their fortune.
All mental models fail to represent the real world completely. That’s kind of a fundamental feature of them.
For those that have never heard of Accrescent: https://accrescent.app/
the very nature of our current record keeping, guarantees that a very great deal of anything bieng done now will vanish
papyrus will survive long after the inevitable neglect and bit rot destroy
our digital archives
The massive physical remains of our times ,accompanied by those most enduring of our written records, labels and logos, wont tax future investigators imaginations in figuring out what happened to us.
I personaly, have access to many bones, and have toyed with creating chimera skeletons, history is too deep, and people are too wierd to draw any conclusions, much of the time.
I wonder if I'll ever give a damn about AI LLM and the like.
Maybe that's the generational barrier.
I find that topic so uninteresting, like cars or kitchen apparatuses, or home electronics of the 70s.
I see the technology as energy burning or rather wasting and not beneficial to human evolution and survival, the contrary.

It's not because of the unknown, it will also replace me and remove the joy of building something on my own.
But I bet in 20 30 years it will be like DJing back in the 90s and DJing now.
DJing back then was manual work and art, required skill.
DJing now is mostly effortless and could even be automated, with AI too. It's more of a performance show than mixing skill and art.

Creating something new will be a matter of just defining what you'd like your result to be (as already is the case very often) and refining the steps.
Instead of writing code, you'll be writing or speaking with an AI, which will then generate code.

When I started coding at the age of 11, that was the dream.
But I still can't find the motivation to deal with AI.

I'm 49 now, soon 50.
How does the problem simplify when it's restricted to piano?
I thought the same thing. And now the "locked" enum state doesn't just mean locked, it means closed AND locked. And I don't actually like it when an enum value implies multiple things.
Cyberpunk Is Already Here. And Its Boring.
What about Intel Arrow Lake?
Thanks for the information. I’m a long time Logic Pro user and I wasn’t aware of this feature.
This query appears to work as well

https://www.imdb-sql.com/?query=SELECT+*+EXCLUDE+%28titleTyp...
There's something important about the limit between fun and not fun in learning. With time you know that many times, stuff that appeared hard and not fun were indeed so simple yet so foreign.. the pain came from trying wrong path for too long.
But capital got their assets pumped and that's what matters!

We need to stop asking 10+ workdays a week from each couple. Once we only demand 7 workdays a week, people are allowed to raise their own kids again!
Link to the video in the article is broken, the correct link is https://download.fsfe.org/videos/peertube/fYwrRaaw8qQhauiG2n...
When it comes to how "open" LLMs are, there are basically three categories:

- Open Source: The architecture of the model is available, so you can bring your own data and compute to train a similar model.

- Open Weights: The trained model itself is available for you to use. You can download it and run it on your own hardware without needing to train anything from scratch.

- Open Data: You get access to the data that was used to train the model. With this, you can completely reproduce the training process, which is super helpful if you want to fine-tune the model or see exactly how it was trained.

There are some other nuances around hyperparams, training methodology, etc. but that's basically the 3 main categories.
https://en.wikipedia.org/wiki/BT_Tower#Secrecy
The one you get when you start it for the first time
Stemroller[0] has been around for a while too, it's free and based on Meta's models:

0: https://www.stemroller.com/
In fact, if you try to close a door that is locked, you’ll put a large dent in the door jamb. So this combination is not only sensical but desirable to detect.

Perhaps a better lesson is to not be overzealous when paring down your logical model.
They called it "WordPress engine tracker" too which is either childish, stupid or malicious.

I hope mullenweg gets sued out of all his money because that's what he deserves. Fuck that guy.
I've been working with a pretty specific data model now for about 8 years. One of the booleans that has turned into a trap for us is called

isFavorite = true|false

This was originally meant to indicate an item would be pinned to the end users dashboard. Turns out that over time the business unit wanted to allow users to pin items to more then just a dashboard. If we had known better we would have used a set like

favoriteLocations = Set<Locations>

but because this data was modeled across user devices in firmware and not just a central db, we were kinda stuck with adding more booleans for more locations to pin an item.
The lengths of self delusion people will resort to rather than accept the fact they've been conned.
Leaving the distortions from inflated and unrealistic expectations (case in point: people expecting evolution of AGI somehow have not yet well defined what AGI is), I also think that in the mid-long run the current state of LLMs will bloom an entire economy for migration of legacy apps to have conversational APIs. The same investors will then have a new gold rush to chase, as it always happen.
Yeah this feels like a “one way doors” problem. Designing your data models in a way that would cause a later refactor to be painful or impossible is probably the bigger trap.
Dutch police use hologram to try to solve 2009 sex worker killing
I don't use fabric softener, but that's a solved problem. The laundry machine I have takes both laundry detergent and, if I used it, fabric softener and dispenses those by itself.

Actuators, competently designed, won't break when torque gets too high:

1) The control system can handle this, trivially.

2) The mechanical linkage can be designed to limit torque. At some point, it should slip.

3) Forces out-of-axis should not be transferred to the actuator

The kleptocracy is more a function of rent-seeking city living. Even a little ways out, into the suburbs, things are very different. Rural, and space is virtually free.
And then some time later someone adds a nullable boolean to a column in your database and that null (3rd) value ends up representing different things.
> But in the last 30 years this didn’t go mainstream.

It's started to in the last few years (last decade?). First OO languages started getting type-safe enums, which still suck but at least aren't as bad as C-style enums, then most recent languages got either actual sum types or something more or equivalent (type-safe unions, sealed classes / interfaces).
They are all bialgebras.
I've absolutely had a real life door in the locked-open state, that is done to prevent it from closing. As some doors always need a key to open from the outside, this is useful. And as they can be further locked to need a key even from inside, that's not making "closed-locked" redundant instead.

For the general case, I think this may have been the inspiration for swift having enums with associated values, which in the author's toy example would have been

enum DoorState {
case open
case closed(Bool)
}
Why luxury cheese is being targeted by black market criminals
Right, one might say that ADTs are a generalizaiton of the Enum concept.
I'm all for minimizing violence and harm, but violence is a necessary part of life.

I just watched a surgeon slice open a woman and save her life and the baby. Blood was everywhere, it was pretty violent. Nothing wrong with it.

Violence != Malice

Mergiraf looks pretty awesome though.
Which has its own unexpected bug in that the extended deadbolt can damage the wood frame and/or trim. Or perhaps the sensor you use to determine the door's state (open or closed) is positioned on the hinge side in such a way that it's triggered when the door is kept open with the deadlock extended. It's close enough to closed that the sensor gets triggered, and you--I can't help myself--open the door to the possibility that your system falsely represents the door as being both closed and locked.

This stuff can be hard, and sometimes, you just have to refactor later on instead of trying to nail down every possibility for the model, despite trying to figure out likely issues in the near-term. In which case, the goal is to keep in mind that data models will eventually change over time, and consider how that knowledge might change what you're writing now to make that process less painful.
Speaking of fallacies, dismissing an argument because you found a single fallacy within it without addressing the main substance of the argument is known as the fallacy fallacy.

There is a lot chew on in that comment and that article beyond "a bit of a quack"
> Languages in the ML family solved this decades ago. But in the last 30 years this didn’t go mainstream.

Rust is mainstream.
Audio Source Separation I think is the general term used in research. It is often applied to musical audio though, where you want to do stem separation - that's source separation where you want to isolate audio stems, a term referring to audio from related groups of signals, e.g. drums (which can contain multiple individual signals, like one for each drum/cymbal).
Because Java mindshare is going down fast while Rust is going up faster?
What tool do you use for the source separation? Everything I've used so far is great for learning or transcribing to MIDI but the separated tracks always have a strange phasing sound to them. Are you doing something to clean that up before mixing back in or are the results already good enough?
I'd use a set (or map, or "tags") for the complex example. Basically, you're saying that booleans are hard to enumerate and combine. How you combine states is pretty arbitrary and dependent. For the company partner/AI/features case, just create a set/map called "features" and put a price on each of them. Create a method to check for common combinations, like being a basic customer.
Wow, I didn't see that. Great to see this level of interest early on!
Exactly! Beat me to it.

This is a constant source of bugs in software: developer making a "reasonable" judgement that gets crushed by reality.

The core idea is true, though. Enumeration types, set operations and pattern matching are must-have features in any PL.
I remember this being posted. It's a bit surreal to read now.
It wouldn't cost 1M. The BOM[1] of Stanford's Mobile Aloha[2] (very similar to physical intelligence's robot) is around $30,000.

[1]https://docs.google.com/document/d/1_3yhWjodSNNYlpxkRCPIlvIA...

[2]https://mobile-aloha.github.io/

$7000 for the wheels/navigation module
$3500 x2 for the control arms
$6000 x2 for the controlled arms

I don't think you need a $7000 navigation module and the arms are also probably overkill. To which extent do we need closed-loop Dynamixel servos when the policy diffusion algo already relies on computer vision driven closed-loop control ?
As a university lecturer, I have interviewed many people… academics and admins. I have taught in many S E Asian universities and multi-lingualism is the norm, with English assumed to be the ‘Lingua franca’. Almost everyone I interview claims to have ‘excellent’ skills in written and spoken English. Almost none of them could produce so much as a single paragraph of English that did not burn my eyes.

Prior to starting writing my first book, I had already accumulated some experience in academic writing. I thought it would be a doddle. I can honestly say that it was one of the most demanding experiences of my life.

The worst thing is the degree to which I was blind to my own shortcomings… just like all those people I interviewed.

Moral of the story… "writing is easy; you just stare at a blank sheet of paper until drops of blood form on your forehead" (Gene Fowler).
The fact that this comment was very gray should tell us all about HN main demographic i.e. privileged SV engineers who never had to negotiate once in their lives, and could land a job the next day if they were let go.
Essentially, the leading way to do automatic music transcription is to train a neural network on supervised data, i.e., paired audio-MIDI data. In the case of piano recordings, there is a very good dataset for this task which was released by Google in 2018:

https://magenta.tensorflow.org/datasets/maestro

Most current research involves refining deep learning based approaches to this task. When I worked on this problem earlier this year, I was interested in adding robustness to these models by training a sort of musical awareness into them. You can see a good example of it in this tweet:

https://x.com/loubbrad/status/1794747652191777049
If you're looking for the most valuable forgery/con in history, a good candidate is the Donation of Constantine[1], a forged document which claimed to transfer sovereignty over western europe to the pope.

[1] https://en.wikipedia.org/wiki/Donation_of_Constantine
I think this highlights the main issue with replacing Excel, which is that most people have an undocumented, informal workflow with their tools in Excel that would be difficult to replicate fully in other software.

Relevant XKCD: https://xkcd.com/1172/

As someone that has had other software tools replaced with alternatives (think Slack replaced with Teams), the new solution almost always speeds up and fixes a lot of problems. It also invariably screws up at least one thing that I need the tool to do as a part of my job.

I love my IT colleagues, but (and I mean no offense to them or other IT folks) they don't
understand that the way we use our internal tools is super flexible and doesn't adhere to an end to end process. It's how we ended up with an entire software platform that takes more manual steps, breaks in a way that we can't fix, and still requires the use of Excel to get the output into the formats that our stakeholders need. It also can't adapt quickly when we need to change things in our process.

It is a technically impressive tool that does the things they designed it to do super well. But we're like a month away from needing an Excel tool (or another piece of software) that can reliably do all the things we didn't realize relied on the "hot spacebar" from the XKCD.
1. Put it online now so ChatGPT indexes it. Can be forever prompted.

2. Put it in a Ethereum transaction.

More seriously, I have no idea.
I would expect my web application framework to handle all of these tasks, except perhaps header filtering. If it didn’t I’d rather fix that problem in the web application itself instead of adding a complicating layer of infrastructure that I now need to include in integration tests and release process.

I see some merit to moving the size limits etc out of the application to reduce CPU waste there on overly large requests, but either way I’m still burning some CPUs on it.

Is the use-case for this mostly about sticking some validation in front of a system who’s code you can’t or don’t want to modify for some reason, like in front of Wordpress?
Debcow Optimizing Debian Packages for Copy-on-Write File-Systems
Yeah, my thought while reading this was that this is why I am so often disappointed by books.
I understand that it could have been easier from the start by using a set. But at the time, it wasn't a requirement. Why would you use a set for a single entry?

Furthermore, you didn't need to keep using booleans. You could run a script that reads the boolean and update the new field in the row, and transition your code to use that.
I would argue when the prefrontal lobe has matured, which is about 25 for males. These platforms are highly manipulative and causing immeasurable damage to our social fabric. A dopamine slot machine in your pocket powered by AI, ready to grab your attention anyway it can, by outraging, triggering or seducing you. I personally would ascribe these platforms as evil.
No need. Obtainium already supports downloading from third-party F-Droid, so users can add Grayjay this way:
1. Enter the URL "https://app.futo.org/fdroid/repo/"
2. In "Override Source", select "F-Droid Third-Party Repo"
3. For "App ID or Name", enter "grayjay"
4. Press "Add"
5. Done

Reference images:
- Add app: https://ibb.co/dL1Hqw6
- Result: https://ibb.co/whmL3PY
> spaced repetition, once you see some concepts often enough

I think there's a quote on this but I can't remember by whom, but I think it's something like "Familiarity doesn't lead to repetion, repetition leads to familiarity."

Even if not a quote, I think the idea (with spaced repetion adding the concept of time) of repeated exposure to a subject as the thing that drives understanding, and not understanding just being a thing that itself allows people to do the subject a lot, is an important one to keep in mind for learning any new topic, particularly ones that are perhaps further away from your current knowledge base, and so feel inherently trickier.

And if you fully comfortable with the subject, you're probably not learning anything at that point ;)
i've got it all in Beanie Babies™. Thinking of diversifying into MtG.
There is something to be said about exactly what the practice is/how the practice is structured. Both the learning and practice phases should rely less on rote memorization and more on dissecting and understanding principles. For instance, physics without basic calculus means being handed a set of opaque equations, which encourages blind application and needless confusion where that doesn't work. At least in the US, I find this lacking.
Show HN: AI tool that analyzes support conversations to identify revenue leaks
Hi!

I built Owlify AI, a tool that analyzes support conversations to identify revenue leaks (like preventable refunds and missed upsells).

Would love to get your feedback - does this sound like something that could be valuable for companies?

Best,
L
There's a timescale problem that you may be overlooking.

One part of NATO is a quid pro quo: It's in the interest of the nuclear powers, most of all the US, that other countries don't build their own nuclear weapons. You might say that US offers an alliance (including nuclear weapons) in exchange for Norway, Finland, Poland, Austria, Italy etc. spending their budgets on non-nuclear weapons. All of those have advanced economies and generally sufficient resources that they could build nuclear weapons, but doing it is a decade-long project.

Imagine yourself as the government of Poland. Make a choice about the 2026 defense budget. Start a nuclear bomb project that you think will take ten years, or trust that if Russia invades in 2035 the US will stand by its promises? What do you choose if you feel a tinge of doubt in the trustworthiness of half of the recent US presidents, or in the statements of many leading US politicians? That Vance person may be president in 2035, is he reliable? He spoke the words "drop support for NATO if", he suggested forcing your neighbour to cede territory, will he sacrifice American lives if Russia invades Poland?
Though Python compiles to bytecode (pyc) and recently added optional typing.

On the other side, Rust can be compiles to WASM, which can be considered a form of bytecode.

If you look at Clojure (app lang w/o types, very dynamic) or Elm (strongly typed app lang that transpiles to a scripting lang), you'll find the situation today is even more whimsical than Ousterhout could have predicted.
Yes, because they are focused on the relevant parts for solving a specific problem.

So one could say that the article's fundamental flaw is not explaining what is the purpose of the model, therefore we cannot assess if it is capturing the relevant aspects to solve the problem.
Groceries are a highly competitive market so a large fraction of cost savings end up being returned to the customer in lower prices.

From my perspective self checkout is a latency optimization. The person in front of you in line may have 3 items and still take an unreasonably long time finishing the transaction, but replace one line with 4 machines and the line keeps moving.

Sure I’ll take a full cart to an actual cashier, but by removing people with only a few items from those lines they become more predictable.
Folding clothes is a special task. Other prototypical tasks that are used in robot benchmark:

- changing a bike chain

- closing a jacket's zipper
IANAEconomist, but I've long arrived at the same conjecture; I usually phrase it as "the market always adjusts to keep average discretionary income at 0".

So, if you give everyone in a given population (I'd go for the country instead of the world to see the effect much faster) a million dollars a month, the average discretionary income would, obviously, rise by one million dollars. That would cause prices to raise, but also all kinds of new products and services to become available. Some of those would evolve from luxuries to necessities over time - like e.g. having a car, or a mobile phone. Housing would likely eat a chunk of the surplus.

In the end, it would all stabilize, at exactly the "life is more expensive by a million dollars, on average" point. We'd still have socioeconomic classes - poor with < 0 surplus, rich with > 0 surplus, and the middle with ~0 surplus. Some people would've moved to different places on the ladder, but the ladder would still be there, simply because of variability in individual incomes.

I guess put another way, you could say, the market is a DC filter - as wealth distribution in a population changes, the market always adjusts to cancel out the constant component ("DC offset").
> Python is fast

Compared to compiled languages and JIT languages CPython is not fast, and removing the GIL does not improve the single thread performance of the language, right now it causes a 1-2% performance regression of single thread. Something like request validation seems like it wouldn’t benefit from more threads much; or if you need N threads to validate a request in 1ms in Python, it’s likely you could validate the same request in 1 thread in 1ms with another language.
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I'm a senior software engineer working in the payments team on building highly secure, performant, and compliant payment applications and actively engaging with Banks and government entities. The daily work involves building critical performant applications while taking a highly secure approach from code to the infrastructure. I also have solid open-source experience and have made significant contributions to Redis. In my free time, I am a technical advisor and engineer for Redis's parent company. In the past, I have also worked on Android reverse engineering to build plugins for multiple health service providers.
I came to same conclusion but my thoughts were 'boy idk what I'm doing here'
Star Wars: Rogue Squadron was also a technical marvel at the time.
99% of people are either better off using a language with a garbage collector or need to avoid heap allocations altogether.
Making Sense of Lambda Calculus 0: Abstration, Reduction, Substitution?
ADTs are the space generated recursively by sums and products. Enums are a single flat sum type.