skysight-inc/HackerNews huggingface dataset:
The last time that I went to a planetarium it was far too digital. As a child I would love going to the planetarium that was part of a university and it inspired my interest in astronomy at a (too) early age. Those original analogue projectors with all the movements and lenses of various sizes were amazing! Maybe we have it too easy with imax projections and lost something along the way that made a planetarium experience so believable and magical.
AI comes for YouTube's thumbnail industry
I think you need to have experienced playing (or even listening live) an acoustic instrument. Even if the sound can be produced electronically the experience cannot be reproduced. That is what he meant.
"And he gave me a list of like 40 research papers and said, ‘If you really learn all of these, you’ll know 90% of what matters today.’"

That alleged reading list given to Carmack by Sutskever is here: https://news.ycombinator.com/item?id=40297984
When I read "crash" in the context of flight, I think "everybody died". Crash is factually true, but perhaps misleading (at least to my interpretation)

"skids off runway" or "failed takeoff" would have less implication of death.
“Cloud Computing”
“us-east-1 down”

This gave me a belly laugh.
polars via Rust (cargo) also
One reproduces the sky as seen from Earth (planets, stars, galaxies, etc), while the other is a model of the solar system. The Zeiss device will let you see the sky as it is at different dates, from different places on Earth, will let you see the sky as if the Sun was not shining during daytime (so you can see the other objects). It is unfair to discount it as just a new way of presenting what that other machine was showing. They are in fact very different in what they can do.
You would not have as high penalties if it wasn’t an animal facility and you were filming.
This is rad and I can't wait to try it out for myself
Well, no, that isn't the only way to reduce piracy. Another way would be widespread collaboration between the largest tech corporations to lock down the pipeline from manufacturing to sale and onward

If users continue to accept this path, which... they seem to, that is where we'll inevitably end up.
> I decided to open-source the version I built in September 2024.

I think this is the most impressive part!
The US hardly screams at China at all, but China is completely fixated on the US (if media is anything to go by). The US will do things at its own pace like China does, picking at it as a competition is merely a saving face thing that doesn't really exist in the west.

Its only been a decade or so since China had all of those things. You would see multiple obviously imported Tesla Model S's in Beijing way before you saw even one BYD EV taxi. Then China invested in a short period of time and now they have much more than the US. But the time period was so short that China hardly has a moat in these areas.

> In the next 2 years it will become clear that the king is banked, and that the leadership is no longer with the west, and I am afraid the consequences for us will be significant.

We heard this before in the 1980s and that didn't pan out at all. This is just the 1980s again with China in place of Japan; China even has a much bigger real estate bubble than Japan ever did, the consequences will be similar if not worse. The same demographic crash is also coming to China, history is just a broken record.
We also migrated to ClickUp (though not from Jira) but while it's better than what we used before, it still feels... I don't know, sluggish. Loaders everywhere, lists are jumping when you scroll. Sometimes I click on a task, the detail modal opens up and there is a noticable delay while the data loads. Typing a / in the description which opens up the command panel or integration panal or whatever it called, freezes everything for like 100ms or more.
That is not a proper alternative to real pattern matching.
>"Healthy because it isn't very fattening"

Every single food item can be "fattening", so categorizing them as such is inaccurate. You can eat cookies and lose fat if you're in a net caloric deficit, and you can gain fat from celery if it puts you in a surplus.
The hypoxia/suffocation instinct, the irresistible urge to breathe, is caused by carbon dioxide levels in the blood. The nervous system has no means of directly detecting oxygen, or its absence. If you walk into a room of pure nitrogen there is almost no warning. The CO2 levels remain low, everything is fine while all your oxygen is rapidly dumped to the oxygen-free air - two deep breaths gets rid of most of it. Another 15 seconds after that you are dizzy, another 15 to 45 after that you are unconscious. Terrible design, IMHO, but presumably not a common situation in the ancient environment.

If you hyperventilate, it drives out the carbonic acid and CO2 in the body. But the blood is normally already near saturation for oxygen. This unusually low level of CO2 allows you to hold your breath much longer by suppressing the suffocation response, sometimes to the point of unconsciousness. You don't realize you should breathe. You feel fine, just a little lighthea... This is why you should never hyperventilate before diving under water.
Very cool idea but I wonder how well this can possibly work in practice. So many bouldering problems hinge on small things, such as how a little crimp hold is oriented or how deep the groove in it is. It can be hard to determine this even in person until you get up close or try to grab it.

Additionally, this model seems to take into account the body type but not other relevant factors, such as climber's strength and flexibility/mobility. Even in the demo, that suggested move of putting the right foot high and pushing off the jug up and to the right could not be done by a lot of new climbers. This parallels what I've personally seen when watching others climb. For example, some climbers are exceptionally strong and can basically campus their way up a route. Watching their beta is irrelevant to me. I don't have the same strength to pull those moves.
In programming language design, we tend to distinguish between global and local analysis. While type checking and elaboration is an example of global analysis, desugaring is inherently local to some piece of code. Therefore, "power" or "expressiveness" usually mean that something cannot be syntactically "expanded"; e.g., while type classes elaborate into explicit dictionaries, they still require information from the type checker, and therefore considered a "real" feature of a programming language. On the other hand, nested pattern matching can be formulated as local syntax transformation, and therefore it doesn't bring anything fundamentally new to the type system or dynamic semantics.

There's also a great talk on the matter [1], if somebody is interested in formalities.

[1] https://www.youtube.com/watch?v=43XaZEn2aLc
> It's depressing

This may sound not-so-empathetic, but it is:

Capitalism is depressing. If we lived in a society where everyone shared and benefited together, then you wouldn't have to deal with this frustration of needing to hold onto value to ensure your survival.
Is it just me, or does this landing page and product feel half-finished? Missing video, coming soon, no logo...
Another one of these! It's interesting how many times this has been made and abandoned and made again.

https://wiki.postgresql.org/wiki/PGQ_Tutorial
https://github.com/florentx/pgqueue
https://github.com/cirello-io/pgqueue

Hundreds of them! We have a home grown one called PGQ at work here also.

It's a good idea and easy to implement, but still valuable to have implemented already. Cool project.
I tried making an LLM generate different titles for a given article and compared their ranking scores. There seems to be a lot of variation in the ranking scores based on the way the title is worded. Titles that are more likely to generate 'outrage' seems to be getting ranked higher, but at the same time that increases is_hn_flagged score which tries to predict if a entry will get flagged.
I think we need to give it time. Python had a slow and steady growth from 1991 until today and it has eaten so much of the data analysis and ML world (backed by C++, C and more recently Rust).

But python doesn't vertically scale very well. A language like Elixir can grow to fit the size of the box it is on, making use of all the cores, and then without too much additional ceremony scale horizontally aswell with distributed elixir/erlang.

Elixir getting a good story around webdev (phoenix and liveview) and more recently the a good story around ML is going to increase it's adoption, but it's not going to happen overnight. But maybe tomorrows CTOs will take the leap.
This is that old finance chestnut. Two finance professors are walking down the hall and one of them spots a twenty dollar bill. He goes to pick it up but the other professor stops him and says "no don't bother. If there was twenty dollars there someone would have already picked it up"

Yes, people arbitrage away these anomalies, and make billions doing it.
I’d imagine it would be the bifurcation of the chip market between low and high transistor size scales

You’d be surprised the volume of chips anywhere from the 10s to thousands of nanometers sold even today

For every bleeding edge CPU there are many larger (and hotter) less crucial chips being sold

If you want to get nitpicky you could consider individual PMOS or NMOS transistors as 10 to 20 million nm single transistor chips (or 1-2cms)

It’s exactly the same process after all!
oh no... my time travel secrets!

i better fix that
As an experienced, very poor climber myself, I enjoy the process of problem solving. However, knowing many experienced, very good climbers - studying beta is how many of them excel. As an aside, the term beta also came from the use of beta tapes by climbers to record themselves climbing so they could study the minutiae of their movement to find improvements. In higher levels of bouldering especially, a nuanced and firm understanding of beta is everything - so careful analysis of your movement can help identify areas of improvement.

I believe this is consistent with most elite (or elite-aspiring) athletes from many sports.

While I personally enjoy the problem-solving aspect of climbing (when I rarely do get out), I absolutely see the value in this project (and other climbing apps that thrive on beta sharing)
Resource intensity is decreasing. We can solve both at the same time, but we can’t solve both with maximum possible speed at the same time, true.
Extended variants of Pascal, like Turbo Pascal, should not be confused with the Pascal language as designed by Niklaus Wirth.

Wirth's Pascal was a language designed for the purpose of teaching programming and it was adequate for that, but it was completely inappropriate for any serious work.

It had no means for writing big programs that must be divided into multiple source files and it had a lot of design errors, like including the size of an array in its data type (which made impossible the writing of any linear algebra library) or the way of handling the variant records (which was insecure and verbose).

The well known paper "Why Pascal Is Not My Favorite Programming Language" by Brian W. Kernighan contains valid arguments against Pascal (against Wirth's Pascal, there have been many extended Pascals, especially following Turbo Pascal, which have corrected some of the most egregious defects of the original Pascal).
The advantage of TI approach is that they propose to earn money - if you bought their plant, you can sell methane, no carbon tax needed - you just make a product. I think in this sense TI has greater scaling potential.
There's one problem you face with issues like this. One reason it took so long to prove, beyond significant doubt, that cigarettes cause cancer is because it's something that happens over many decades and with high variance. Fewer than 20% of smokers will get lung cancer over their whole lives. You cannot experimentally prove side effects that happen only over such prolonged periods of time. So you're left with observational correlations that, to this day, are even scrutinized by some eccentric scientists.

When you look at society today, it's going downhill in terms of overall health in a multitude of ways across both the physical and mental/psychological domains. Lowered testosterone, increased obesity, increased mental illness, decreasing IQs [1], and so on endlessly. And if something like e.g. processed foods ends up being one of the factors in this, it may well be another one of those things that's basically impossible to actually prove - outside of extremely long-term correlations which can be endlessly challenged, exactly like this article is doing.

And the correlations in this case will be even easier to challenge. Like you mentioned processed foods are enjoyable to eat. They're made to generate profit and so hone in on every little receptor, desire, and impulsive (or even addictive) tendency in our bodies. People are only going to avoid this if they're already substantially health conscious, so even observational correlations can be trivially challenged. So how can we ever hope to prove anything, especially when there may be every reason to expect absolutely zilch will show up in short controlled experimental trials?

[1] - https://www.sciencedirect.com/science/article/pii/S016028962...
Structs are arguably better then most type systems, but I don't use it either in my day job and have only used it for toy projects...
Global Energy Storage Market Records Biggest Jump yet (BNEF)
"The global energy storage market almost tripled in 2023, the largest year-on-year gain on record. Growth is set against the backdrop of the lowest-ever prices, especially in China where turnkey energy storage system costs in February were 43% lower than a year ago at a record low of $115 per kilowatt-hour for two-hour energy storage systems."
The new REPL in Python 3.13
Congrats on the launch. I recently was trying out Microsoft Edge's built-in Workspaces feature which allows multiplayer collaboration. What would you say are the key differences?

https://www.youtube.com/watch?v=w5AX_HvtYfI
Neuralink's First Human Brain-Chip Implant Appeared Flawless,There Was a Problem
Quite crappy? It seems to me like the current SOTA is working plenty good enough for most use cases and like the highest impact (practical) way to improve right now is going to be advancements in domain knowledge acquisition and retention.
Yeah, I really miss the old 360 Blade UI rather than the New Xbox Experience UI. From then on, it just sort of got worse. It's ironic since Microsoft also has Windows and DirectX and corners the PC gaming market in this regard.
I wonder if there's room for some kind of 'video game YC', where a company would shotgun invest in a bunch of promising indie titles in the hopes of finding the next Stardew Valley / Factorio?
You can make them better with the right prompts & conditional agent chaining
As an American, that's a pretty embarrassing, if not unexpected, result.
> 8GB of RAM is fine for 95% of the population and the other 5% can buy something more expensive.

This argument is self defeating in the context of the M4 announcement. "Average consumers" who don't need 16 GB of RAM don't need an M4 either. But people who do need an M4 chip probably also need 16 GB of RAM.

I think actually more people need 16 GB of RAM rather than a top M4 chip. Having only 8 GB can be a serious limitation in some memory heavy circumstances, while having (say) an M2 SoC rather than an M4 SoC probably doesn't break any workflow at all, it just makes it somewhat slower.
Thank you for feedback!

Regarding contact, on the website there is an option to schedule a call where we can talk so you can see I'm real person. During that I'm happy to share any information about me. I completely missed that there is no email on the website, right now it's visible on calendly page if you go to book call. I'll add it somewhere there. Thanks!
I tried to fetch his RSS too! :)

Turns out, there's only 1 post so far on his blog.

Hoping for more! This one is great.
Error Handling for Large Rust Projects
Experience organizing variant Error types in a complex system.Topics including: (1) How to build a cheaper yet more accurate error stack to replace system backtrace; (2) How to organize errors in large projects; (3) How to print errors in different schemes to log and end users.
(Not the author)

The advantage of using your DB as a queue is that a traditional DB is easier to interact with (for example using SQL queries to view or edit the state of your queue).

In most business applications the message payload is a "job_id" pointing to a DB table so you always need and have to go back to the database to do something useful anyway. With this setup it's one less thing to worry about and you can take full advantage of SQL and traditional database features.

The only downside and bottleneck of having your DB act as a queue is if the workers processes are hitting the DB too frequently to reserve their next job.

Most applications will not reach the level of scale for that to be a problem.

However if it does become a problem there is an elegant solution where you can continously populate a real queue by querying the DB and putting items in it ("feeder process"). Now you can let the workers reserve their jobs from the real queue so the DB is not being hit as frequently.

The workers will still interact with the DB as part of doing their work of course. However they will not ask their "give me my next job ID" question to the DB. They get it from the real queue which is more efficient for that kind of QPOP operation.

This solution has the best of both worlds you get the best features of something like Postgres to be the storage backend for your jobs without the downside of hammering the DB to get the next available job (but in general the DB alone can scale quite well for 95% of the businesses out there).
I guess my threshold for care is if it is sufficient to motivate any action to be taken at all, whether that is eating slightly less meat or switching to non-factory farmed. The vast majority of people don’t do that, so their revealed “care” is very little.

Frankly, I don’t really care which type they eat, meat is meat and has pretty much the same environmental (and ethics of killing) issues.
I'm not complaining, Google can do whatever they want, it's just not proper research, even though they want it to feel like it is.
I can read and modify all kinds of code I couldn't write in the first place.

I haven't used any llm for code yet but most code I ever touched was mostly written by others, and I wouldn't have been able to write it from scratch, but was able to modify it, take only chunks out of the whole to use for something else, take only the structure and not the verbatim code and use in some other language, refactor to satisfy my own priorities vs the original, get useful results in languages I don't even know, etc etc.

It doesn't seem like using some pattern-matched uber-autocorrect code would be much different, especially once you understand that understandingless nature of what your getting.
I'm curious about the same thing.. I use a deadletter queue in sqs and even sns and here I can see an archiver but it's not clear if I need to rollout my own deadletter behaviour here.. not sure I would be too confident in it either..

A nice novel project here but I'm a bit skeptical of its application for me at least.
RAG takes the current limit of LLM and focuses it on specific problems using custom data. It's not exactly magic, it just finds a way to produce something tangible and usable from an otherwise broadly focused model.

It's the rage because it's a way to practically _do work_ from LLMs that generally provide wow from conversationally accurate, often factually accurate responses.
Lot's of installations will not notice this. Issue is probably not very serious if this approach was chosen.
Is this an application of CRISPR?
Once you've gotten as far as possible using the anti-reuse/anti-recycling business model with your own hardware (and software) for so long, it seems pretty easy to disparage the benefits of anyone elses' hardware, especially things traditionally built to stand the test of time.

An instrument can be special.

Portable electronics can definitely be turned into an instrument. It may be a lot of effort, but it can be worth it.

OTOH how long is it nominally going to last compared to a generic five & dime guitar or harmonica?

And what happens if it's battery powered and you can't just slap in a new battery any time?

By one playbook, the need for disposable circuit boards gave rise to the possibility of ever more complex disposable complete products. Then augmented where it needs to be acceptable to replace the whole product while still fully functional electronically. On these terms you can expect the biggest hitters to step up to the plate and hit it out of the park the furthest.

It is a little bit blatant acting like they are inhabiting higher ground when they're not even in the same league as a tambourine.
Microsoft provides consultants that happily show you how to use their tools.

I doubt this is a case of some random engineer at an oil company buying a few VMs on a website.
>We’re in the midst of a scientific revolution right now, because 10 years ago, there was not the sense that AI was working. We’ve had these AI ‘winters’—a couple of them over the decades, in fact. It’s funny, because virtual reality also went through this: It had almost been a bad word because it had crashed so bad in the 1990s, people didn’t even want to talk about it. And artificial intelligence had a couple of those cycles where hype spins up, money flows in, it underperforms, and then it crashes, and nobody wants to talk about it. But this last decade was different, and people who don’t notice how different it is this time aren’t paying attention, because the number of absolutely astounding things that have happened in the last decade with machine learning is really profound.

Is it that different?

Except that the overal IT and comsumer computing industry is 1000x bigger and thus the money involved and the available hype too?

Without some major breakthrough in LLMs, the current hotness will also fade, and the money will move elsewhere. We have a couple of years for that, judging from similar cycles (first they get to bundle AI to everything, and sell LLM based AI to the enterprise and consumer -- then the market dies of, and people start thinking "that was all there is?", that being more or less what current LLMs do).
Ivermectin has two orders of magnitude more cardiac side effects than the vaccine. It is compared to benzimidazoles which aren't light on anything.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7297930/
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8087035/

Check rates for placebo, just in case. The rates for the vaccination are pretty close indeed to that, but not exactly the same.

Not enough of a difference to warrant a black box warning, but enough for "very rare".

Safety is not an absolute. Vitamin C is not absolutely safe at RDI dosages. Water has known side effects that are dose dependent.

COVID and Influenza also come with cardiac side effects, more common than the vaccine, and that is the counterbalance.