skysight-inc/HackerNews huggingface dataset:
I feel it’s not related to data or the architecture but the process of reasoning in general. For these models, every token predicted condition or drives the output in certain direction. Semantic meaning of these tokens have a magnitude in solution space. Lets say ‘answer is 5’ is very large step and ‘and’ token is very small. If you are looking for a very specific answer, these smaller nudges of each token generation provide corrections to direction. Imagine trying to click on narrow button with high sensitivity mouse settings, obviously you need to do many smaller moves whereas with a big button maybe you can one shot it. The harder or specific a task is where a solution space is very narrow that it cant be possibly one shotted, you need to learn to take smaller steps and possibly revert if you feel overall direction is bad. This is what RL is teaching the model here, response length increases(model learns to take smaller steps, reverts etc) along with performance. You reward the model if solution is correct, model discovers being cautious and evaluating many steps is the better approach. Personally I feel this is how we reason, or reasoning is in general taking smaller steps and being able to evaluate if you are in a wrong position so you cna backtrack. Einstein didn’t one shot relativity after all and had to backtrack from who knows how many things.
Can anyone explain why everyone is so hyper focused on speed? 500 images per second, 100 minutes video in 30 minutes, thousand lines of loc per hour. Who is going to consume all that?
Caution: I'm a C programmer "by history" and therefore I see "C Interfaces" as that and don't always / immediately view them through the rust lens of ownership...

Reading the article (nice troubleshooting story!), my summary, as a C programmer, is that the "C Interface" here "takes ownership". Given C cannot express this properly, a pointer is passed - and the called function "simply" makes the assumption that from hence-on, what was given to it will remain.

As "semantics" this (the need to pass an "owned" piece of data to a function) isn't unusual irrespective of the programming language. Just in case of Rust, this is explicit in the interface (if the func takes a non-ref arg, or a shared smart ref of sorts), while in C ... this can lead to errors of the observed kind. I haven't looked whether any of the sources or docs of libmodem say "this pointer must be either global/static or malloc'ed (and the caller shall not free it)".

A rust wrapper for this could / should possibly "leak a reference" here; Something that prevents the initialisation object from being dropped. yea, accepted, needs "nasty hacks" whether static lifetime, Pin, manual drops, explicit Arc leaks, ... possible though.

It'd be nice if libmodem were stricter about such ownership, agreed, and then a rust wrapper could take advantage. Takes time to evolve; is there a bug report / enhancement request out there for this in libmodem ?
https://news.ycombinator.com/item?id=42768072 (6 days ago, 664 comments)
Brits say "kaput" in informal speech - OED says we pinched it from German. Not sure if it's common in US English.
As soon as you've got something releasable.

Though, you should break work up in a way to get to something releasable asap.

The latter is where I think it's more art than science still, or at least I can't come up with a good written process on how you do it (other than the constant "where is the value in this" and "what's the smallest thing we can build" questioning), but I can always do it!
Show HN: AI Slack bot that handles all your DevOps
It is more of a metaphorical question
Other machines.
In 2003 they didn’t have grid scale batteries.
The solution for that does not start with making Software Engineers proletarians worthy being mentioned on Karl Marx's Capital Volume 1.

I hate people that think that the solution for unequal outputs lie on making other people worst to come to their level.
What differences do you notice? The remastered has some terrible code behind its UI, you can just feel it.

Menu hangs on start for up to 10 seconds for no apparent reason, people leaving the game during the “connecting to server” stage seems to make everyone else wait indefinitely usually forcing them to quit.

On the multiplayer screen, tab between “Join” and all the other tab buttons and notice how each one moves a few pixels.

Then the obscene inefficiencies overall. Sitting at the main menu not even moving my mouse gets the CPU hot enough to make the fans loud. During gameplay a 4v4 multiplayer match turns into one big lag fest about 15 minutes in.
At that scale? I think it might honestly be just bandwidth, I'd offload picture data to cloudflare R2 as there's no egress fees.
Ha! I went through half of the Turkish course but stopped around two years ago, thanks for the reminder, I resumed my progression!
I'll be looking at the new courses too :)
And thanks a lot for making all of this work available to all!!
> In my experience, a lot of the talk about AI making engineers obsolete is coming from people that have some odd, deep-seated hated towards SWEs.

I’m not convinced it’s hate, but a general misunderstanding of what a SWE does. If you haven’t spent a long time doing it, you might be under the impression it’s mostly about producing lines of code, not trying to figure out what the ticket says should to be done, what can be done and what actually needs to be done and who’s the person(s) that might have the answers. Writing code is the easy part.
i9 power efficient, OK lol. If you want power efficient, get a Kontron. Below 3W idle we can talk. My MS-01 does 16W idle.
Spurious Scholar – Because if p < 0.05, why not publish?
Nepotism. Cut-throath and a lot of time dishonest competition, life-long health issues.
People who haven't come from blue-collar families tend to see the trades through rosy glasses.
There's a reason my father worked like a horse so I could study. And while I am pretty competent with manual labor, it would have completely killed him if I followed his foot-steps.
LLM's are transforming the business in multiple domains. As the business are realizing the true potential of LLMs, companies are leveraging multiple LLM models to carry out multiple use-cases in multiple domains
Puck is a marvel of drag and drop engineering and a wonderful open source project. Kudos to the team for this release!
As mentioned below, it seems you don't like true agility (though, the critical piece is re-evaluating often, most teams miss that).

If you want a successful example in a traditional engineering industry, you don't need to look further than SpaceX vs Boeing and their rocket development (one got a smaller budget and blew up a number of rockets and has been earning money for 4+ years, the other got twice the grant and wasn't trusted to bring astronauts back from ISS a few months ago).
One Approach to Beating Conference Stage Fright
> Chimera supports many different configurations, leaving the user free to carve up their disk as they please — but does not support having /usr on a separate partition.

On systems with both a hard drive and ssd (since on most distros /(s)bin and /lib* are sym links into /usr, most binaries are ultimately in /usr), my recent preference is to have the hard drive as / and ssd as /usr (then sym link or bind mount there as needed for things that could use the speed, like Steam). Am I the only one who thinks this way or am I way off?
Upskilling Employees to Bridge the Generative AI Skills Gap
Whenever we do recursive, or really long queries (not often), we’re dropping to basically raw SQL with sqlalchemy.text(). It’s really a lot to keep it wholly in SQLAlchemy: write a complex query in SQL, convert to SQLA, and remember how all the moving parts should be connected.

Should be much easier now with LLMs, though :)
It's just a norm and has been for centuries. For composed positions it should also generally be white to move.

You're right that this isn't necessary (particularly when the board is labeled) but by doing something weird you're just going to distract and confuse some chunk of people from the point you're trying to make - exactly as happened here.
I don't miss the trolls, but one thing I miss from slashdot is the ability to tag something Funny.
I am in a similar position to yourself but more concerned about remaining current, than looking for paid work.

Working with a colleague/friend in my last job for ten years gave me the edge to stay ahead. I have not figured out how fill that gap.
Well, still trying to get into nvrhi, I went on to ask ChatGPT to write me an example program using it.

To make it short, it got better when I made a project, uploaded the headers and docs of it as project files and moved my chat into that project as well.

That said, AI can help you but needs a lot support from you to do things somewhat right.
Most of what generative models produce is shit so they have to produce a lot in hopes _some_ of it is OK-ish.

It's also about responsiveness. LLMs produce junior-level quality of code at a rate of hundreds of lines per minute. I need it to produce enough to spot where it's completely wrong as quickly as possible to I can change the prompt.

It's like a edit-compile-run cycle which you also need to be fast or you lose attention.

I was tempted to say it's another _step_ in the edit-compile-run but often the code is so bad I don't even bother compiling.
This roughly mirrors my experience so far. Mind you I'm an extremely qualified engineer who has worked at FAANG.

Except I'd add that as one gets experience working with the AI I can only assume they'd get much better at making it go smoothly. For example, I wouldn't manually rewrite localhost, I'd tell the AI "Why is localhost everywhere? Will this worker if I deploy to a droplet?" and it will fix it for you.

Also I just paste error-messages directly into the AI and it usually knows how to fix them.

Sometimes it's net positive, sometimes it's net-negative due to creating a mess that's really hard to get out of or debug. But I imagine it's only a matter of time until the scopes in which it's cost-effective go up.

I don't like that AI is a threat of huge monopolistic and job-reducing potential, but I don't think downplaying it is a long-term strategy to combat that.
Nah. The Guardian is not the same anymore, they are getting soft.
I vote for Butlerian Jihad instead.
Humans can also be disappointing and interesting. I like to do Lichess puzzles not logged in, which mostly gives puzzles with a Lichess puzzle ratings in the 1400-1600 range with some going down to around 1200 or up to the 1700s. Presumably that is the range the average Lichess player is in.

For those who have not used Lichess, the puzzles it gives (unless you ask for a specific type) do not tell you what the goal is (mate, win material, get a winning endgame, save a bad position, etc) or how many moves it will take.

Here are some puzzles it has recently given me and their current ratings. These all have something in common.

1492 https://lichess.org/training/KsrR0
1506 https://lichess.org/training/RwLfy
1545 https://lichess.org/training/TzZdx
1557 https://lichess.org/training/IJfT7
1564 https://lichess.org/training/oOMz4
1604 https://lichess.org/training/uRRck
1661 https://lichess.org/training/jBrLX
1719 https://lichess.org/training/cpKAM

What they have in common is that they are all mate in one. I have seen composed mate in ones that puzzled even high rated players, but they involved something unusual like the mating move was an en passant capture.

None of the above puzzles are tricks like that.

So how are enough people failing them for their ratings to be that high?
How do we know that they didn't see it? Their work is much more secret now. Isn't it possible that o1 and o3 rely on something similar maybe with some additions. Same for the gemini thinking models.

My point it that OpenAI and google might have been working with very similar approaches for months.
Someone might think so, but ultimately, nobody is (too important).
it would be faster for me to just write it directly in my normal IDE

Then you are a much better developer than me (which you may very well be). I'd like to think I'm pretty good, and I've many times spent hours trying to think through complex SQL queries or getting all the details right in some tricky equation or algorithm. Writing the same code with an AI often takes 2-20 minutes.

If it's faster for me, it might not be faster for everybody, but it is probably faster for many people.
While I do agree with you, if it took tens of millions of dollars in initial capital to get there, which hasn’t been returned, it’s quite a different thing to the standard small businesses model.
I experimented with Cursor over christmas, with writing a simple-ish Swift/SwiftUI app on iOS as the challenge. I can code fairly well in Python, moderately in JS, and almost not at all in Swift. I was using Cursor on a Mac, in parallel to XCode.

Basically, it worked, but not without issues:

- The biggest issue was debugging: because the bugs appeared in XCode, not Cursor, it either meant laboriously describing/transcribing errors into Cursor, or manually fixing them.

- The 'parallel' work between Cursor and XCode was clunky, especially when Cursor created new files. It took a while to figure out a halfway-decent workflow.

- At one point something screwed up somewhere deep in the confusing depths of XCode, and the app refused to compile altogehter. Neither Cursor nor I could figure it out, but a new project with the files transferred over worked just fine.

But... after a few short hours' chatting, learning, and fixing, I had a functional app. It wasn't free of frustrations, and it's pretty far from the level where a non-coder could do the same, but it impressed me that it's already at the level where it's a decent multiplier of someone's abilities.
I think it depends a bit on what markets we're talking about. Multi-material capability is mostly something I see hobbyists use. I rarely see it in an industrial setting.

And before people say that Prusa and Bambu printers are for the home market: sure. But I have seen consumer grade 3D printers in a lot of different industries. Prusa, Bambu lab and RatRig are the most common consumer grade printers I tend to see in industrial companies. (I don't think RatRigs are that common, but in a few companies that do mechanical design and they need larger volumes I've seen them being used)

Consumer grade FDM printers are cheap to buy, very cheap to run, reliable and produce decent quality prints. Also, they are far, far better than the FDM printers that you used to be able to get from the likes of Stratasys. For the price of one of the more upscale industrial machines you can buy a sizeable print farm of FDM printers.

When you do a lot of rough prototyping it is better to have a lot of cheap printers than just one advanced printer. Having lots of printers means more people can make more prototypes per day. And it reduces the need for buying more of the expensive printers and then have people have to wait for their turn.

This is why it would be interesting to know the sales figures for multi-material systems. I think the professional market might be less visible online, but they certainly buy a lot of printers.
Each pair of people creates a unique combination
I didn’t really have this experience.

Every time I tried it, the thinking mode would spin for years, it’d send itself in a loop, not do anything I instructed in the prompt, and then just give a weird summary at the end.

Claude models correctly parsed the prompt and asked the follow-up questions.

Edit: tried it a few more times. Without the “R1” mode enabled it genuinely just restated the problem back to me, so that’s not ideal. Enabling R1 and pointing that out has sent it into a loop again, and then produced a wildly-overcomplicated solution.
> Hence why most keywords and variable names (a hard part of computer science) are in simple English and it is considered a net positive.

As I'm not a native English speaker, I disagree. I learned programming long before I got decent in English, and even today I just consider the English keywords in programming languages to be some "abstract mathematical concept" that by mere coincidence is named after some real, existing English word. Even today, being somewhat decent in English, I stil think this way when I see program code.

I actually would insist that this is a much more useful way to think about good programming, since this way you have no difficulties to ask yourself all the time whether it would make sense to replace some "English-named" concept by something more useful, but which has no analogue in the English language (or any other natural language).
You have to add “and return initial capital” to that list. That’s usually what’s at issue here.
> It’s also really fascinating talking to people who stayed in South Vietnam after. The entire system is reset.

It took me a while to appreciate the significance of renaming Saigon to Ho Chi Minh City. I've lived in HCMC (although I'm not Vietnamese) and the renaming is actually controversial to this day, although most Vietnamese know better than to speak up about it.

Basically, imagine if Russia conquered Ukraine and then renamed Kyiv to "Vladimir Putin City".
It’s interesting. I would’ve agreed that ‘driving intent from natural language is something that LLMs have fallen far short of’ maybe a month ago.

Since then, I spent a week trying to get cursor to work, and after dealing dealing with all the bugs, and restarting the composer each time with a new prompt, was able to get what I would consider a quality output for a moderately complex app (a parimutuel betting market).

The issue isn’t that LLMs are terrible, it’s the software like cursor is buggy and poorly written.

It should know that I don’t want to use code from an old version of the library I am using because the new library I am using is already in my projects dependencies.

It should let me set up preferences for different programming languages. And preferences for all programming languages.

So when I give it a prompt, it looks at the dependencies and language rules I already have set up, adds those to the prompt and produces the quality output I’m seeing now without me having to manually specify all those things.

Short version: LLMs rule the software is just shitty.
"Cera: Invest with Stablecoins" -- with that elevator pitch, how could they possibly NOT be clowns and absolute scammers and incompetent software developers who hold their customers in contempt? And how could YC possibly be fooled by that, unless they were maliciously and unethically intending to make money by financing fraud? I hope the leopards ate their faces off and peed on their couch.

Another example of objectively obvious fraud that is on the graveyard list is "NFTScoring". Yeah, just what kind of people aspire to tell other people which NFTs to buy (professional shills and get-rich-quick ponzi pyramid scheme scammers, that's who), and what kind of people knowingly invest in them, or recommend them after performing due shilligence?
3Blue1Brown also has a good video on mathematical animations, in case it’s relevant for you: https://youtu.be/rbu7Zu5X1zI?si=KTAfolRBm1NsZOE9
I don't know how you can read about the half dozen or more documented cases of lab leaks in this thread - regardless of what you believe about covid - and call heightened restrictions for experimental work with human-infectious viruses security theatre. It's not sci-fi horror movies folks are worried about, it's people making mistakes the way all people do. The way you seem to be doing.

We take the effort to air gap infected or security critical IT systems, but can't be bothered to air gap humanity from existential threats. If protecting all of humanity from the next pandemic is too much work for virologists, maybe it's best that they consider another career?
I'm not sure how safe a hydrogen car is...any insight?
Bad take. Identifiers are just labels.
Thank you :) A real labor of love [0] for me.

[0]: https://notes.jordanscales.com/98-css-reflections
There's also a GC pause issue: reference counts are the main method, but when those don't do the job we rely on stop-the-world mark and sweep. And we do very little analysis so it's easy for namespaces and closures to form reference loops. If you're careful about how you use those, it's possible to keep the reference counts working, but debugging when this fails is probably not such a nice experience. Running GC every frame might be acceptable if the stored state has few enough objects; it can be around 1ms if there's not much to do.
Amazon offers a 32-core virtual workstation in the cloud for $4.40/hour
I think iceberg solves a lot of big data problems, for handling huge amounts of data on blob storage, including partitioning, compaction and ACID semantics.

I really like the way the catalog standard can decouple underlying storage as well.

My biggest concern is how inaccessible the implementations are, Java / spark has the only mature implementation right now,

Even DuckDB doesn’t support writing yet.

I built out a tool to stream data to iceberg which uses the python iceberg client:

https://www.linkedin.com/pulse/streaming-iceberg-using-sqlfl...
Filestack was acquired by Scaleworks: https://www.scaleworks.com/companies

It’s not really dead, but not really a “startup” in the traditional sense anymore either.
Whatever the reason (many reasonable at the time), this was after PRC did a full lock down, with outbound flights limited to repatriation, i.e. they weren't trying to spread the disease, other countries wanted their citizens back while PRC did one of the harshest locked downs in modern history. Can't blame others for thinking CCP was over reacting, but ultimately, PRC locked down during period where covid spread in PRC was minimal and signifant first incidents in many countries were from western travellers, who thought things were going to be fine.
As unfair as that is, Russians can still rely on basically volunteers who an average choose to be there, Ukrainians do not. I've heard many horror stories from there. About men who are basically hiding in cellars so that the recruteers won't pull them off the streets.

Fucked situation all around. I want to blame Russians as the only ones responsible for that, I guess. (As in they started this. Not saying Ukraine is crystal clear with many issues they have with the army, but still I can't blame them.)

I'm Pole, so it's more personal for me. Knowing if I was born a bit more to the East, I'd be awaiting my death (and in agony).
Maybe it seems a stupid question, but it's an honest one: why openbsd rather than freebsd?

I tried freebsd when Debian integrated systemd. Being neither savvy or intelligent, I had trouble with the ports system and installations were taking hours for small applications. I gave up.

I've always had a nagging desire to try again, but poor health has discouraged me from those kinds of learning curves. I recently left Debian again and use Void, with Opensuse on a separate drive for purposes of maintaining some competency and familiarity with systemd (just in case...).

Anyway, I'd appreciate your input on the various BSDs. As I understand, recent funding suggests it may be growing and will remain viable for a long time, which was, however relevant or not, a concern for me.

Edit: I might also mention that I gave serious consideration to Chimera before settling on Void, for similar reasons of learning curves. Of all distros, I had determined it would either be Void or Chimera and nothing else - or BSD.