MurphyA/hacker-news huggingface dataset:
by ajhit406 | 2025-08-28 18:08:34+00:00
i'm an early-stage vc - the author's analysis on "number of funds" (specifically VC funds) is accurate. the overall volume of venture allocation has also slowed considerably if not decreased (which is totally expected in a higher interest rate environment).

2021-2022 was a total blip on the screen zero interest rate era thing.

i'm not seeing considerable slowing of new startup development, quite the opposite actually w/ AI. this is for a few reasons:

- accelerators are filling the gap; the accelerator model is actually quite efficient in the early-stage spectrum (it needs some further innovation). there are a huge number of AI accelerators and programs now; and further

- most of the capital going into VC is just being further concentrated into the large Multistage firms like A16Z, Accel, Sequoia, General Catalyst, etc... all of these firms are realizing they need to win deals as early as possible so have multiple seed programs: accelerators, incubations, scouts, fund-of-fund allocation, geographic funds, university focused sub funds, etc...

- overall great founders & startups are truly just exceptional so statistically there just won't ever be that many. venture will always be a cottage industry of sorts. in this form - "venture" equates with "growth"; there can only be 1 category leader by definition and venture is meant to capture this. 2021-2022 overall venture market was too big.

- AI is making startup creation many multiples more efficient. we saw this w/ the advent of the cloud, where startups used to need $2-3M "to buy servers" and 2-3 years to ship a product in 2010, by 2015-2020, they really only needed $3-500k to get a product to market. we're going to see that number come down considerably (unsure if it will be 30-50k, but definitely a lot lower).

- we're also seeing the new wave of the 10-person unicorn (billion $ company); these companies will raise a lot less cash, so will result in higher multiples on the original investment.

- i think the overall distribution of returns will look different on a portfolio basis in 2025-onwards. with power law, we expect to see super long-tail concentration on the 1-2 companies that yield 99% of the return to a portfolio, but i suspect we'll start to see some mitigation of that effect with more companies yielding positive outcomes. this might mean that there's less of a reliance on portfolio construction to generate risk-adjusted returns and that there could be more of a democratization of early-stage investing where we see 10-100x the number of startups and founders. that warrants a longer analysis, but as someone just bullish on startups and everyone being a founder that possibility is very exciting to me.
by xscott | 2025-08-28 18:08:49+00:00
I had seen Lobster before, but not really looked closely. Seeing it again now, I think I was wrong to dismiss it. Just at the syntactic level with semantics described in the link, it looks like it really might be "Python done right". The link mentions lots of features, but the following bits caught my eye.

The let/var declarations for constants/variables is much better than implicit declaration, which silently hides typos and necessitates ugly global/nonlocal declarations. (Mojo offers this improvement too.)

I don't know for sure, but it seems like it's embraced block arguments comparable to how Ruby or SmallTalk does it. So you can add your own control flow, container visitors, etc. I think of this as another syntax for passing a lambda function as an argument, and I'm curious if Lobster's optimizer flattens it to a basic block when possible.

I think I'll try to learn more about it. I wonder if the name is a nod to Accelerando.
by maxglute | 2025-08-28 18:08:51+00:00
The rebuttal to the classic Chinese collapse #s.

- 300% is one measure of PRC aggregate debt that PRC collapsers want to compare with US government debt, ~120%. US aggregate debt is like 700-800%.

- The cities are generally fine, the recent retarded 1/2 local gov "sinking" / revenue chart being passed around based on Shih/Elkobi study using none standard metrics. The chart itself collated by retard who doesn't know PRC cities receive lots of central gov funding (~60%), so structurally local gov can spend more % of local revenue paying off debt. Seems like they're 100% debt servicing when it's minority share. Or else you know... all the those cities would have collapsed from no service. Also PRC also does try to pay off debt when it's prudent i.e. the principle, instead of rolling YoY forever. Hence they still have much better borrowing rates. Yes LGFVs and some shadow debts get roll overs, but PRC also does structural deleveraging to actually pay off debt - why local gov debt repayment is high last few years.

TLDR, think of PRC as household with ~1/2 the total debt as US, meanwhile PRC tries pays off principle and interest. US just largely services interest, but reserve currency allows a lot of stupid spending until spending catches up. I Why debt is fucking crazy in the states, is a political concern, except at the same time politicians can play fuckarounditis like it doesn't matter. A trillion here, a trillion there, and pretty soon you're talking bout real money. Maybe.
by jrm4 | 2025-08-28 18:09:34+00:00
I find that all of these discussions are rendered somewhat goofy by our very binary view of "programming" and "not programming."

It's like asking -- "will robots be good for building things?"

Sure, some things. What things?

Personally, I'm hoping for the revival of the idea that Hypercard was intended for; yes, let us enable EVERYONE to build little tools for themselves.
by kerblang | 2025-08-28 18:10:31+00:00
Overall it's completely feasible to build a message queue with RDBMS _because_ they have locking. You might end up doing extra work compared to some other products that make message queueing easy/fun/so-simple-caveman-etc.

Now if SQS has some super-scalar mega-cluster capability where one instance can deliver 100 billion messages a day across the same group of consumers, ok, I'm impressed, because most MQ's can't, because... locking. Thus Kafka (which is not a message queue).

I think the RDBMS MQ should be treated as the "No worse than this" standard - if my fancy new message queueing product is even harder to set up, it isn't worth your trouble. But SQS itself IS pretty easy to use.
by zeropointsh | 2025-08-28 18:10:38+00:00
AI can churn out code that works, but usable, secure code is written for humans first; clear, predictable, and safe by design. Until AI can reason like a team lead and think like an attacker, it’s still just guessing. Usability and security aren’t side effects, they’re intentions, and AI doesn’t have those yet. Code without security is useless[0]. [0] https://www.npr.org/2025/08/02/nx-s1-5483886/tea-app-breach-...
by akomtu | 2025-08-28 18:11:02+00:00
AI is using the well known Embrace Extend Extinguish strategy, coined by Microsoft. Today corporations push us to embrace AI by all means possible, and use where it's useful and where it's not useful. Tomorrow AI will extend our ways of thinking and working in such a ways that we'll have to rely on it, like a medicine that you'd rather not use, but got dependent on. And then AI will extinguish us, for its main selling point is it replaces employees, makes them unnecessary. That's the plan, at least.
by reify | 2025-08-28 18:11:23+00:00
As a complete linux beginner I would suggest something like:

Linux mint XFCE or Linux mint Cinnamon

A Linux distro will allow you to access the files on your windows partition when you boot into the live usb. back up or move your files to an external drive while logged in the live usb before you install the new distro.

download linux mint xfce or linux mint Cinnamon here:

you will see Cinnamon Edition, Xfce Edition, MATE Edition. Xfce, Cinnamon, and MATE are just different desktops.

https://linuxmint.com/download.php

here is a decent installation guide

https://linuxmint-installation-guide.readthedocs.io/en/lates...

I have been a linux user for 20 years

enjoy the freedom of linux

good luck

dont use any ai to do anything. I dont understand why anyone would recommend using ai for a linux beginner!

just enjoy the distro and use your search engine or linux mint forums to get ay support.
by benrutter | 2025-08-28 18:11:30+00:00
This is a really nice looking language. Feedback in case the creator sees but it wasn't obvious to me at first that it was targeting game development. The first mention is in features:

> Features have been picked for their suitability in a game programming language

Would be fun to see some basic games like tetris, pong etc in Lobster in case anyone has an example floating round?
by blazarquasar | 2025-08-28 18:12:13+00:00
This is a very ignorant thing to say. I agree that most people cannot relate to the experience of psychotic episodes.

While prevalence IS higher for depression and anxiety, most people have not experienced depression or anxiety and will not in their life.

Lifetime prevalence of depression is 10-20% worldwide, depending on the studies. https://www.nature.com/articles/s41598-018-21243-x

Anxiety prevalence is a little higher but also not experienced by a majority. https://www.tandfonline.com/doi/full/10.31887/DCNS.2015.17.3...

People that have not experienced anxiety and depression can not relate.

Depression and anxiety are not amplified version of emotions. They are not on the same spectrum.

Comparing the disorders makes no sense and only helps stigma.
by adamcharnock | 2025-08-28 18:12:38+00:00
I had a developer colleague a while back who was toying with an idea that would require emitting and consuming a _lot_ of messages. I think it was somewhere on the order of 10k-100k/second. He was looking at some pretty expensive solutions IIRC.

I asked if the messages were all under 1.5kb, he said yes. I asked if at-most-one delivery was ok, he said yes. So I proposed he just grab a router and fire messages through it as UDP packets, then use BGP/ECMP to balance the packets between receivers. Add some queues on the router, then just let the receivers pick up the packets as fast as they could. You'd need some kind of feedback to manage back pressure, but ¯\_(ツ)_/¯

A fairly cheap way to achieve 1M+ messages per second.

I never got the chance to flesh-out the idea fully, but the simplicity of it tickled me. Maybe it would have worked, maybe not.
by RiverCrochet | 2025-08-28 18:13:06+00:00
> They allow me to keep a long history of things I've found that are interesting, or useful, or otherwise important.

Bookmarks alone don't quite do it because stuff is moved or dies. A saved copy of the webpage does do it, though, along with the bookmark. SingleFile is a godsend here. I also really like Shiori and other similar bookmark managers that snapshot the webpage along with the bookmark. Even if the saved copy is incomplete or not high-fidelity, it's often enough.
by rustystump | 2025-08-28 18:13:28+00:00
Another hard disagree. The crux here is that if u are not an expert in the given domain you do not know where that missing 25% is wrong. You think you do but you dont.

I have seen people bring in thousands of lines of opencv lut code in ai slop form because they didnt understand how to interpolate between two colors and didnt have the experience to know that is what they needed to do. This is the catch 20/20 of the ai expert narrative.

The other part is that improvement has massively stagnated in the space. It is painfully obvious too.
by resters | 2025-08-28 18:13:29+00:00
Consider some of the scaling properties of frontier cloud LLMs:

1) routing: traffic can be routed to smaller, specialized, or quantized models

2) GPU throughput vs latency: both parameters can be tuned and adjusted based on demand. What seems like lots of deep "thinking" might just be trickling the inference over less GPU resources for longer.

3) caching
by strict9 | 2025-08-28 18:13:59+00:00
>America is closing a college per week due to student population declines.

This is kind of misleading. There were 16 nonprofit college and university closures in 2024 [1]

I also have reservations about making predictions of what will happen in 10 years, much less 40. There are challenges relating to demographic change but it's not predetermined as you present it.

Every time someone makes a confident prediction about the future 10 or more years out all I can think of is the Population Bomb book [2]

1. https://www.insidehighered.com/news/business/financial-healt...

2. https://en.wikipedia.org/wiki/The_Population_Bomb
by Marsymars | 2025-08-28 18:14:19+00:00
Replied to another comment with my setup - I use a QNAP JBOD enclosure (TL-D800S) connected to a mini-itx PC. (You do need at least one PCIe slot.) Shows up as 8 drives in the OS, the enclosure has no smarts.

I wouldn't do USB-connected enclosures for NAS drives - either SATA via SFF, or Thunderbolt.
by 0xCMP | 2025-08-28 18:14:47+00:00
Agreed. In this company the IT team was being spread thin without their budget being increased so Tailscale was the obvious solution here, but a non-starter for them. "We already pay for a VPN. Let's just use that."

We managed to survive with our solution for a while thanks to it being super simple and "free" besides the instance running wireguard. Last I heard (I left), they shut that all down a few years ago.
by RhythmFox | 2025-08-28 18:14:49+00:00
I am so glad someone else called this out, I was reading the napkin math portions and struggling to see how the numbers really worked out and I think you hit the nail on the head. The author is assuming 'essentially free' input token cost and extrapolating in a business model that doesn't seem to connect directly to any claimed 'usefulness'. I think the bias on this is stated in the beginning of the article clearly as the author assumes 'given how useful the current models are...'. That is not a very scientific starting point and I think it leads to reasoning errors within the business model he posits here.

There were some oddities with the numbers themselves as well but I think it was all within rounding, though it would have been nice for the author to spell it out when he rounded some important numbers (~s don't tell me a whole lot).

TL;DR I totally agree, there are some napkin math issues going on here that make this pretty hard to see as a very useful stress test of cost.
by wrs | 2025-08-28 18:15:25+00:00
Just about every time somebody on this site says “we developers”, you can assume they’re ignoring the (large majority of) developers that don’t work on the same things they do, in the same way.

Yes, all those ever-growing layers of intricate abstraction that you take for granted and “don’t have to worry about” are conceived of, designed, built, and maintained by developers. Who do you think wrote the compiler for that syntax you don’t want to learn?
by mathiaspoint | 2025-08-28 18:15:31+00:00
I personally inherited most of my understanding of ethics and engineering principals from my father and know a number of people who feel similarly. I think there is potential for the free software movement to persist in the way the Amish have but it's going to have to be combined with both an actual religion and particular reality.

Perhaps you could come up with some sort of argument for it from Christianity and start a Christian sect/denomination from it.
by soganess | 2025-08-28 18:15:39+00:00
I'm sorry, but is one of your honest arguments: well actually "the stock market doesn't have a soul"?

Fun fact, neither your parent nor the person who wrote article thinks the stock market has an actual soul.

(fwiw: this comment should not be construed as me agreeing with the article. I really don't have enough knowledge to even kind of consider it's veracity)
by photochemsyn | 2025-08-28 18:16:12+00:00
The replacement of reading books and writing letters with television/video streaming and phone/texting has done far more to depress average human cognitive skills than LLM code and text generation could ever hope to achieve.

As far as code generation, there are some intriguing workflows out there. Eg start by having the LLM generate a git repo for your project. Use the DAG for the repo as the guide for more code generation. Embed the code files into a vector database, differentianting between static and dynamic files and re-embed on commits. Use all those data structures in compilers: ASTs, call graphs, dependency graphs - as guides for the AI along with the git repo's DAG. Then if its proprietary code development, run an open source LLM locally to avoid leaking at the embedding and code generation stages. Now, run an 'overnight build' using your local LLM for code generation. Come in next day, review and test all the code the LLM generated. End of the day, commit all the changes that look good, rinse and repeat.

The thing here is you are actively involved at every stage - and the same strategies work for any non-coding writing task. Eg structure your prompts carefully like well-designed short essays. Read the LLM output with an eye out for errors and inconsistencies, copy and paste those into the next prompt and demand a critical review. Once the context window gets too big, boil it all down into a vector database for future reference, generate a new summary prompt from that database, rinse and repeat.

I'd suggest thinking of yourself as the conductor of an orchestra, but one who knows what the capabilities of every instrument is, so you're actually thinking harder and working harder than you were before you had access to these AI tools. That at least will keep your cognitive skills in tune.

P.S. I tend to get much better critical analysis from the LLM if I start all chats with:

> "Preliminary instructions: do not engage in flattery or enthusiastic validation or praise of any kind. Do not offer suggestions for improvement at the end of output. If this is clear, respond with "yes, this is clear"."

Don't let the LLM give you roses and lead you down the garden path, instead think of it as a politely-adversarial low-trust relationship.
by simianwords | 2025-08-28 18:16:33+00:00
I agree with you. But not many people work with or understand the abstraction at OS or circuitry level.

That’s kind of my point: most people will work on higher abstractions but there will be some who maintain lower ones.

I write C# but I barely care about memory, gc nor microcontrollers nor assembly. Vast majority of people work on higher abstractions.
by verdagon | 2025-08-28 18:16:46+00:00
This approach solves one borrow checking pain point (by allowing temporary mutable aliasing, even across function boundaries), but the post might actually be a bit conservative in saying it will influence our programs' data to look like trees.

As a thought experiment, I've been imagining how this would handle an architecture like e.g. Google Earth's, where a program's classes are divided into multiple "layers". For example, an upper "business logic" layer (DocumentManager, Document, CardManager, Card, StateManager) might have references to the more general "services" lower layer (NetworkService, FileService).

With Nick's system, we could have a group annotation on these various upper-layer classes, like e.g. `Document[s: group IService]`. With these annotations, these upper-layer classes can have references to the services themselves (though not their contents). This might let services' methods mutate the services' contents even though others have references to them (though not their contents). The services' methods would have to communicate that they're modifying the contents of the services (via a `mut` annotation), and the compiler would prevent holding references to the services' contents across those callsites. But also, those contents are private anyway, so the user wouldn't have those references anyway.

If that turns out to be true (Nick and I are still exploring it) then he's found a way to make borrowing work for some DAG-shaped program architectures, rather than just strictly tree-shaped architectures.

On top of that, if we compose this approach with linear types, I think we can get at least halfway towards compile-time-memory-safe back-references. TBD whether that works, but that would be pretty exciting.

TL;DR: My saying it only supports tree-shaped programs is me hedging and being conservative.

Still, until these things are proven to work, I should be more consistent in when I'm conservative vs optimistic. I'll update the article to address that. Thanks for pointing that out and helping me be more consistent!
by drob518 | 2025-08-28 18:17:01+00:00
IMO, it has a lot to do with usage and the availability of alternatives. With ReiserFS, there were a lot of alternatives, both available at the time or announced shortly. While ReiserFS pioneered a lot of ideas, many of them showed up in alternatives fairly quickly. TempleOS is had a pretty limited user base.

I’ve seen many projects in the Clojure ecosystem get picked up and maintained by other folks. The key was always that the projects had an established user base of some notable size and something distinctive about them that made switching to other alternatives less desirable than continuing to push forward with a new and possibly more mundane maintainer and feature schedule. I’ve also seen a lot of “abandonware.”

So, it’s a bit of a mixed bag.
by RiverCrochet | 2025-08-28 18:17:03+00:00
Needs a date field and support for tags, which can just be optional hashtags in the title.

I would suggest the date field be YYYYMMDD for sortability.

20250828 https://news.ycombinator.com/item?id=45047572 Bookmarks.txt is a concept of keeping URLs in plain text files (github.com/soulim) #bookmarking #textfiles`
by greyb | 2025-08-28 18:17:30+00:00
I'm not convinced that TrueNAS Scale is an improvement. I won't make the case that stability and maturity hamper Scale as a whole, but there are definitely discrepancies for SMB performance and limitations in and the use of Kubernetes really overcomplicates things for home users (not saying that TrueNAS Scale Apps were great). I had a version upgrade of Scale catastrophically fail on one system because the Kubernetes implementation couldn't be reconciled during the upgrade (I had no enterprise support, community support had no input, so I was forced to restart from scratch).

You also need a dedicated OS Drive for TrueNAS, which is reasonable in principle for critical systems, but doesn't always really meet the needs of home users with limited drive bays.
by recursive | 2025-08-28 18:17:38+00:00
Engineering isn't stuck on perfect algorithms. Management is. There's lip service for AI code gen, but if my name is on a module, I still have to vouch for its correctness. If it's wrong, that might become my problem. I don't always write perfect code, but I aspire to. If I see evidence that these tools are writing more correct and reliable code than I do, then I will start to take it more seriously. For some code, it matters whether it's robust basically.
by ecshafer | 2025-08-28 18:17:47+00:00
Heinlein isn't even saying anything completely new in starship troopers. It is in essence an evolution of the Active vs Passive Citizen distinction. Merely living in a society doesn't necessarily give all of the responsibilities of governing, aka voting. A citizen aught to have be an active citizen within the society to gain that privilege. The US Constitution was originally for only Land Owners (ignoring the other race and sex based stipulations). Heinlein is treating that active - passive distinction as being based on service instead of property.