MurphyA/hacker-news huggingface dataset:
by chelm | 2025-05-31 10:02:46+00:00
Adding 4 hypotheses to the dicussion.

B2B opportunities are inherently easier to identify during early-stage evaluations due to clearer revenue models and problem-solution alignment.

YC’s network amplifies B2B growth by directly connecting startups to other batch companies as potential early adopters or customers. I found it interesting that https://www.ycombinator.com/companies/legora (former Leya) is using Reducto. If I get page 9 in the pitch deck correct: https://www.pitchdeckinspo.com/deck/Reducto_02c1f2af-3fa2-4a...

Early-stage B2B startups require less capital and shorter timelines to demonstrate product-market fit compared to B2C.

YC’s founder archetype—technical, execution-driven, and efficiency-focused - naturally gravitates toward building scalable B2B solutions.

Thanks for pointing out Reducto! I added it to my market overview: https://idp-software.com/vendors/reducto-ai/

TLDR

The IDP market remains a massive and growing space. There will be a new segment of the market for simple cases that do not need domain expertise, validation, and integration. Generic Document AI tools, so-called AI wrapper, provide easy wins for basic input extraction / categorization and splitting tasks.

Operational complexity, on-premises, integrating directly with enterprise infrastructure and domain-specific validation across fields mean different workflows require specialized handling. I think this is why Hyland, Abbyy and others can compete with the market, event the tech stack lagging.
by john_the_writer | 2025-05-31 10:02:58+00:00
I was the same. Notes all through year 1 and 2 of university.. Less in year 3, I paid attention, and took part in class. I also recorded the lecture. My grades shot up. In year 4, I took minimal notes, and had my best year.

It's like the paper straw, or learning style stuff. Bad science lead to bad policy.
by efitz | 2025-05-31 10:03:03+00:00
Why a lookup table? Why not just have the client remember the last backoff, and multiply it by a constant and apply a ceiling?

def getNewBackoff( oldBackoff: int): int {

newBackoff = oldBackoff * BACKOFF_CONSTANT

if (newBackoff > BACKOFF_CEILING) { newBackoff = BACKOFF_CEILING }

return newBackoff }

if you bit align the ceiling value you can replace the conditional with a bitwise and mask. If you use 2 as your exponent you can replace the multiplication with a bit shift left.

It’s also a good idea to introduce jitter, e.g. don’t set the new backoff to the old backoff * a constant, but add a random value such that the old value gets randomized around the desired new value- this helps prevent pile-ons when a bunch of clients noticed about the same time that the server became unresponsive; if they all have the same backoff algorithm then they’re all going to hit the server again at about the same time. It’s good to spread that out to try to avoid server overloading during restarts/cold starts/whatever.

The best results I ever got were when I used server side hinting to avoid pile-ons when the retries from the client were all clustered around the same time.

When my server got in an overloaded state, the auth path for clients short circuited and delivered an overloaded message with a randomized suggested retry value. The server can’t make the clients honor it (we could in my case because we wrote the clients) but if the clients do honor it you can spread out reconnects over a period instead of make them all point-in-time and dampen or prevent oscillating overloads.
by 7952 | 2025-05-31 10:03:13+00:00
I agree, although it seems like a failure of imagination that this is so difficult. The staff will have a good understanding of what usually happens and what needs to happen. What they are lacking is some really basic things that are the natural monopoly of "the system".

Perhaps we need fallback systems that can rebuild some of that utility from scratch...

* A communication channel of last resort that can be bootstrapped. Like an emergency RCS messaging number that everyone is given or even a print/mailing service.

* A way to authenticate people getting in touch using photo ID, archived employee data or some kind of web of trust.

* A way to send messages to everyone using a he RCS system.

* A way to commission printing, delivery and collection of printed forms.

* A bot that can guide people to enter data into a particular schema.

* An append only data store that records messages. A filtering and export layer on top of that.

* A way to give people access to an office suite outside of the normal MS/Google subscription.

* A reliable third party wifi/cell service that is detached from your infrastructure.

* A pool of admin people who can run OCR, do data entry.

Basically you onboard people onto an emergency system. And have some basic resources that let people communicate and start spreadsheets.
by hshdhdhj4444 | 2025-05-31 10:03:14+00:00
Even if we ignore the fact that the rest of the world could have easily rustled up the money, surely you have the basic intelligence to understand why that would be extremely difficult within a couple of months?

It would be one thing if DOGE had said that a year from now US funding would dry up and for recipients to find alternatives.

Instead DOGE, almost certainly illegally, cut funding that had already been allocated by Congress overnight.
by bonki | 2025-05-31 10:03:18+00:00
I have only skimmed the text but regarding GUIs specifically the list in the end is spot on.

With that being said, I firmly believe that all software (given that one is not already deeply familiar with the domain) is/can/should be written three times to end up with a good product:

1. Minimal prototype. You throw something together fast to see it can be done, taking shortcuts and leaving out features which you know you will want later(tm).

2. First naive real implementation. You build upon the prototype, oftentimes thinking that there is actually not that much missing to turn it into something useful. You make bad design decisions and cut corners because you haven't had a chance to fully grasp all the underlying intricacies of the domain and the more time you spend on it the more frustrating it becomes because you start seeing all the wrong turns you took.

3. Once you arrive at a point where you know exactly what you want, you throw it all away and rewrite the whole thing in an elegant way, also focusing on performance.

(1) and (3) are usually fun wereas (2) fast becomes a dread. The main problem is that in a work context you almost never are allowed to transition from (2) to (3) because for an outsider (2) seems good enough and nobody wants to pay for (3).
by theawakened | 2025-05-31 10:04:07+00:00
I've said this before and I'll say it again: The idea that 'AI' will EVER take over any programmers job is ridiculous. These idiots think they are going to create AGI, it's never going to happen, not with this race of people. There is far too much ignorance in humanity. AI will never be able to be any better than it's source, humanity. It's a soon-to-be realization for these billionaire talking heads. Nothing can rise higher than it's source. Even if they cover every square foot of land with data centers, it'll never work like they expect it to. The AI bubble will burst so hard the entire world will quake. I give it 5 years max.
by hn_throwaway_99 | 2025-05-31 10:04:32+00:00
I am curious about how this compares to past years.

I was pretty shocked that of 275 companies in the Winter 2023 batch, only 12 have received Series A deals. Granted, I know a huge part of that is that the VC environment has just collapsed due to the end of the ZIRP era, but those numbers at least sound pretty brutal to me.
by whitehexagon | 2025-05-31 10:05:11+00:00
I found this one so far:

https://github.com/emard/ulx3s_c64

Exciting to have an alternative to de10-nano, especially seeing the price doubled? since I got mine.

Amazing project anyway, and brings back dreams of building some arcade cabinates. Icepi Zero looks perfect for the job! I hope they arrive in the EU one day.
by rsqnow | 2025-05-31 10:08:37+00:00
As a percentage of GNI, many nations give more development aid than the US. Norway gives 5x more, Germany 3x, France 2x, UK 2x.

The US is on par with Slovenia, Poland, Lithuania, and Spain.

You can see for yourself here: https://www.oecd.org/en/topics/official-development-assistan...
by raphinou | 2025-05-31 10:09:02+00:00
In case you're interested when you set up proper distribution, I'm working on an open source solution aiming to improve security of downloads from the internet. Our first step is maintaining a mirror of checksums published in GitHub releases at https://github.com/asfaload/checksums/. If you publish a checksums file in your releases it can automatically be mirrored. The checksums mirror is not our end game, but it already protects against changes of released files from the time the mirror was taken. For anyone interested: https://asfaload.com/asfald/
by SirHumphrey | 2025-05-31 10:09:56+00:00
I think AlphaFold is where current AI terminology starts breaking down. Because in some real sense, AlphaFold is primarily a statistical model - yes, it's interesting that they developed it using ML techniques, but from the use standpoint it's little different than perturbation based black boxes that were used before that for 20 years.

Yes, it's an example of ML used in science (other examples include NN based force fields for molecule dynamics simulations and meteorological models) - but a biologist or meteorologist usually cares little how the software package they are using works (excluding the knowledge of different limitation of numerical vs statistical models).

The whole thing "but look AI in science" seem to me like Motte-and-bailey argument to imply the use of AGI-like MLLM agents that perform independent research - currently a much less successful approach.
by tim333 | 2025-05-31 10:09:56+00:00
I think something Keynes got wrong there and much AI job discussion ignores is people like working, subject to the job being fun. Look at the richest people with no need to work - Musk, Buffett etc. Still working away, often well past retirement age with no need for the money. Keynes himself, wealth and probably with tenure working away on his theories. In the UK you can quite easily do nothing by going on disability allowance and doing nothing and many do but they are not happy.

There can be a certain snobbishness with academics where they are like of course I enjoy working away on my theories of employment but the unwashed masses do crap jobs where they'd rather sit on their arses watching reality TV. But it isn't really like that. Usually.
by ben_w | 2025-05-31 10:10:53+00:00
Although I broadly agree, I wouldn't go quite as far as where you say:

> All the "no true Scotsman" stuff about what it's doing behind the scenes is irrelevant, because we have no idea what human brains are doing behind the scenes either.

Computers and transistors have a massive speed advantage over biological brains and synapses — literally, not metaphorically, the same ratio as the speed difference between how far you walk in a day and continental drift, with your brain being continental draft — which means they have the possibility of reading the entire Internet in a few weeks to months to learn what they know, and not the few tens to hundreds of millenia it would take a human.

Unfortunately, the method by which they acquire information and knowledge, is sufficiently inefficient that they actually need to read the entire Internet to reach the skill level of someone who has only just graduated.

This means I'm quite happy to *simultaneously* call them extremely useful, even "artificial general intelligence", and yet also agree with anyone who calls them "very very stupid".

If we actually knew how our brains did this inteligence thing, we could probably make AI genuinely smart as well as absurdly fast.
by genewitch | 2025-05-31 10:11:39+00:00
Approximately 1 second was how long AI could hold it together. If you had a lot of free time you could extend that out a bit, but it'll mess something up. So generally people who make them will run it slow-motion. This is the first clip I've seen with it at full speed.

The quick cuts thing is a huge turnoff so if they have a 15 second clip later on, I missed it.

When I say "1second" I mean that's what I was doing with automatic1111 a couple years ago. And every video I've seen is the same 30-60 generated frames...
by d4mi3n | 2025-05-31 10:11:56+00:00
While you’re not wrong in what differentiates those with wealth to those without, I think ignores a lot of nuance.

Does one have savings? Can they afford to spend time with their children outside of working day to day? Do they have the ability to take reasonable risks without chancing financial ruin in pursuit of better opportunities?

These are things we typically attribute to someone in the middle class. I worry that boiling down these discussions to “you work and they don’t” misses a lot of opportunity for tangible improvement to quality of life for large number of people.
by meander_water | 2025-05-31 10:12:04+00:00
I've recently started wondering what the long term impacts of AI slop is going to be. Will people get so sick of the sub-par quality that there will be a widespread backlash, and a renewed focus on handmade or artisinal products made by hand? Or will we go the other way where everyone will accept the status-quo and everything will just get shittier, and we will just have multiple cycles of AI slop trained on AI slop?
by rlpb | 2025-05-31 10:12:06+00:00
> The optimisations in -O3 aren't supposed to give incorrect results.

I didn't mean to imply that they result in incorrect results.

> they make a more aggressive space/speed tradeoff...

Right...so "better" becomes subjective, depends on the use case, so it doesn't make sense to choose -O3 blindly unless you understand the trade-offs and want that side of them for the particular builds you're doing. Things that everyone wants would be in -O2. That's all I'm saying.
by pydry | 2025-05-31 10:12:23+00:00
Trump didnt kick off the layoffs.

It was the war with Russia that drove the fed to raise interest rates in 2022 - a measure that was intended to curb inflation triggered by spikes in the prices of economic inputs (gas, oil, fertilizer, etc.).

The tech layoffs started later that year.

Widespread job cuts are an intended effect of raising interest rates - more unemployed = less spending = keeps a lid on inflation.

AI is just cashing in on the trend.
by PhilipRoman | 2025-05-31 10:12:30+00:00
Safety can mean many things. I'm fairly sure JVM will keep the C-level memory safety guarantee after an OOM, but you can still end up with Java objects in inconsistent states that will start throwing exceptions when you poke them.

The reason why these exceptions are so "unsafe" is that they can occur at any moment. Maybe you were in the middle of modifying some data structure which will enter an infinite loop the next time you touch it. It's a bit like signals in C where you have to be extremely careful about the APIs you use, except worse because exceptions unwind the stack. At least in C you can still safely call kernel syscalls regardless of userspace state.
by tacker2000 | 2025-05-31 10:14:16+00:00
Its basically a symptom of them being huge corporations with people in-fighting for top jobs. It seems one route is to create a new mesagging app, the one that “changes everything now”.

These apps are pretty low hanging fruit and not as involved as one like google maps or ms excel, which cannot be easily replaced.

So person X releases the new app, gets promoted, leaves it behind and of course the “next guy” also wants to leave a mark and therefore creates his own.

Its basically a similar reason why a new JS framework gets released every month.
by bjackman | 2025-05-31 10:14:49+00:00
When you escape a container generally you can do whatever the kernel can do. There is no further security boundary.

If you escape into a VMM you can do whatever the VMM can do. You can build a system where it can not do very much more than the VM guest itself. By the time the guest boots the process containing the vCPU threads has already lost all its interesting privileges and has no credentials of value.

Similar with device passthrough. It's not very interesting if the device you're passing through ultimately has unchecked access to PCIe but if you have a proper ioMMU set up it should be possible to have a system where pwning the device firmware is just a small step rather than an immediate escalation to root-equivalent. (I should say, I don't know if this system actually exists today, I just know it's possible).

With a VMM escape your next step is usually to exploit the kernel. But if you sandbox the VMM properly there is very limited kernel attack surface available to it.

So yeah you're right it's similar to the microkernel discussion. You could develop these properties for a shared-kernel container runtime... By making it a microkernel.

It's just that isn't a path with any next steps in the real world. The road from Docker to a secure VM platform is rich with reasonable incremental steps forward (virtualization is an essential step but it's still just one of many). The road from Docker to a microkernel is... Rewrite your entire platform and every workload!
by kalaksi | 2025-05-31 10:15:28+00:00
The point is that trade-offs are a fact of life. Some problems get solved, other problems appear. I'm not saying the new problems shouldn't be addressed, I'm just talking in general and I believe there are many kinds of solutions that can mitigate many kinds of problems. Just like in traditional banking. I just think it's pointless to try to invent and flesh them out here.

You could still decide what kind of use suits you the best. Regular people wouldn't (and shouldn't) need to know all the technicalities. A trusted party, maybe a bank, could provide their own integrated solution with whatever features they want to offer.
by threeseed | 2025-05-31 10:15:32+00:00
> YC doesn't push founders to start a specific type of business

Of course it does.

Founders look at YC batches, see that it is 99% AI companies and are then forced to also go in that direction if they want the benefits of the accelerated YC path.

And YC deliberately chooses founders with AI companies because they have an investment thesis that is different from "request for startups". Garry Tan has been a massive e/acc fanboy since the beginning and genuinely believes that AI in every use case will advance humanity. And the partners all align with this.

This is all inarguable because amongst the tens of thousands of applications there are surely many amazing non-AI companies. Is this implication that they are all worse than what was selected in the batch ?
by OtherShrezzing | 2025-05-31 10:15:41+00:00
Because of a mix of comparative advantage and opportunity cost. Google as an entity absolutely dwarfs those other companies, and competes at that scale. Airbnb’s annual revenues are lower than Googles annual r&d spend. Google’s “wins” need to move the needle on a $2tn valuation, and an Airbnb size win doesn’t do that.
by 708145_ | 2025-05-31 10:15:45+00:00
Of course it possible to limit the number of virtual threads. A web server can have a limit on number of virtual threads too, and queue incoming request before dispatching to to workers (virtual threads).

As other have said, this can be achieved with a semaphore and the bulkhead pattern. You can also limit the number of number of connections.

I would expect any "production ready" web server using virtual threads having some sort of limiting. That must be the case right?
Show HN: I built an AI agent that turns ROS 2's turtlesim into a digital artist
by ponta17 | 2025-05-31 10:17:17+00:00
I'm a grad student studying robotics, with a particular interest in the intersection of LLMs and mobile robots. Recently, I discovered how easily LangChain enables the creation of AI agents, and I wanted to explore how such agents could interact with simulated environments.

So, I built TurtleSim Agent, an AI agent that turns the classic ROS 2 turtlesim turtle into a creative artist.

With this agent, you can give plain English commands like “draw a triangle” or “make a red star,” and it will reason through the instructions and control the simulated turtle accordingly. I’ve included demo videos on GitHub. Behind the scenes, it uses an LLM to interpret the text, decide what actions are needed, and then call a set of modular tools (motion, pen control, math, etc.) to complete the task.

If you're interested in LLM+robotics, ROS, or just want to see a turtle become a digital artist, I'd love for you to check it out:

GitHub: https://github.com/Yutarop/turtlesim_agent

Looking ahead, I’m also exploring frameworks like LangGraph and MCP (Modular Chain of Thought Planning) to see whether they might be better suited for more complex planning and decision-making tasks in robotics. If anyone here is familiar with these frameworks or working in this space, I’d love to connect or hear your thoughts.
by bonki | 2025-05-31 10:17:49+00:00
I like crotcheting (tried it again for the first time since childhood during Covid). My main problem is that, unless you have already mastered it and can do it in your sleep, I have to fully concentrate on it to not fuck things up, which means I can't do something else at the same time, e.g. listen to an audiobook. And because I'm so slow it takes too much time for me to not think that it's a waste of time because I could have done something more meaningful instead. Objectively, I know it is wrong to think so because the whole point of it is to get away from other stuff and let your brain rest for a while, but it just doesn't work for me and creates extra stress, sadly.
by trinix912 | 2025-05-31 10:18:04+00:00
Am I the only one who thinks these features would be a better fit for WordPad instead of Notepad? They could've made a WordPad from scratch with Markdown, RTF, DOC(X), and ODT at this point and it would've been more complete than shipping a half-baked Markdown implementation in Notepad. Plus, it wouldn't break the decades old assumptions by users that Notepad is for plain unformatted text and WordPad is for formatted/rich/"enhanced" text.
by 1659447091 | 2025-05-31 10:19:57+00:00
DuckDuckGo Ai assist is going in the right direction, imo. It will pull info from wikipedia, use math and map tools plus other web sources that has been mostly accurate for me on the search page.

The chat option uses gpt-4o with web search and was able to provide links to colonial map resources I was curious about after falling down that rabbit hole. It also gave me general (& proper) present day map links to the places I was looking for in the map sites I asked for.

It did get confused a few times when I was trying to get present day names of old places I had forgot; like Charles River in Va that it kept trying to send me to Boston or Charles City Co on the James river and told me to look for it around there...

The York river wiki page clearly says it was once Charles River. Maybe I wasn't asking the right questions. For more unique things it was pretty helpful thou and saved the endless searching w/ 100 tabs adventure
by cxr | 2025-05-31 10:20:08+00:00
At $17/hr even 10% (versus your 5) works out to $3536 at the end of the year ($17/hr × 40 hrs × 52 weeks @ 10%), which is a fair bit short of the $15,000 standard deduction; it doesn't really matter whether those donations are tax-deductible or not—you're not going to be able to deduct them.