MurphyA/hacker-news huggingface dataset:
by adit_a | 2025-06-23 18:14:54+00:00
Thanks! To clarify, we launched our document processing APIs a while ago. This launch is specifically for a new platform we're building around our API based on all of the things our customers previously had to build internally to support their use of Reducto (eval tools, monitoring etc).

Generally speaking, my view on the space is that this was crowded well before LLMs. We've met a lot of the folks that worked on things like drivers for printers to print PDFs in the 1990s, IDP players from the last few decades, and more recent cloud offerings.

The context today is clearly very different than it was in the IDP era though (human process with semi-structured content -> LLMs are going to reason over most human data), and so is the solution space (VLMs are an incredible new tool to help address the problem).

Given that I don't think it's surprising that companies inside and outside of YC have pivoted into offering document processing APIs over the past year. Generally speaking we don't see differentiation in the sense of just feature set since that'll converge over time, and instead primarily focus on accuracy, reliability, and scalability, all 3 of which have a very substantive impact from last mile improvements. I think the best testament I have to that is that the customers we've onboarded are very technical, and as a result are very thorough when choosing the right solution for them. That includes a company wide roll out at one of the 4 biggest tech companies, one of the 3 biggest trading firms, and a big set of AI product teams like Harvey, Rogo, ScaleAI etc.

At the end of the day I don't see VLM improvements as antagonistic to what we're doing. We already use them a lot for things like an agentic OCR (correcting mistakes from our traditional CV pipeline). On some level our customers aren't just choosing us for PDF->markdown, they're onboarding with us because they want to spend more of their time on the things that are downstream from having accurate data, and I expect that there'll be room for us to make that even more true as models improve.
by delecti | 2025-06-23 18:14:55+00:00
Bluesky does most of this. One big miss is the lack of private accounts though.

And the "block" in "blockchain" is a different sense of the word from how you block users on social media, so I don't think it bears any resemblance to blockchain. It sounds more like email (or another similarly federated network) with a whitelist.
by dmbche | 2025-06-23 18:15:25+00:00
Where is the 1-3% coming from?

Again, is the IAEA a US gov. org responding to DNI? Or is ot an international org unrelated to US nat defense?

So why are we talking about them? Do you think DNI is an organ of IAEA?

And if you want to talk about them, can you see what they thought of Iran producing 60% enriched voluntarily (and disclosed to the IAEA)?

Your second paragraph seems to misunderatand both the situation, the process behind uranium enrichement and the IAEA report.

Actually - you seem to cherry pick bits of the report to support your dubious claims - don't you think they would have raised a flag if rhey yought Iran was making nukes, instead of the bits you fished out?

Edit0: this whole thing is you arguing that the US has been "aware that iran was making nukes" before the bombings but you fail to show any evidence of that. You show the IAEA report on Iranian urianium production, which DOES NOT talk about nukes, especially not in the extracts you've put here.

What are we doin' here?

Edit1: it just dawned on me - I don't think you know what en env. sample is. It's not some soil or "environnement" that they analysed - they swabbed surfaces around the plants (probably close to the centrifuges) and on one swab yhey detected up to 87%.

Env. samples are more likely to be contaminated than product (obviously) and the small amounts are prone to error compared to sampling product. It is more likely to get a false positive on an env. sample.

Edit2: Man I loooove reading IAEA's statement on the situation - they unequivocally say that nuclear sites should NEVER be attacked. Isn't that neat?
by kbyatnal | 2025-06-23 18:15:58+00:00
Founder of Extend (https://www.extend.ai/) here, it's a great question and thanks for the tag. There definitely are a lot of document processing companies, but it's a large market and more competition is always better for users.

In this case, the Reducto team seems to have cloned us down to the small details [1][2], which is a bit disappointing to see. But imitation is the best form of flattery I suppose! We thought deeply about how to build an ergonomic configuration experience for recursive type definitions (which is deceptively complex), and concluded that a recursive spreadsheet-like experience would be the best form factor (which we shipped over a year ago).

> "How do you see the space evolving as LLMs commoditize PDF extraction?"

Having worked with a ton of startups & F500s, we've seen that there's still a large gap for businesses in going from raw OCR outputs —> document pipelines deployed in prod for mission-critical use cases. LLMs and VLMs aren't magic, and anyone who goes in expecting 100% automation is in for a surprise.

The prompt engineering / schema definition is only the start. You still need to build and label datasets, orchestrate pipelines (classify -> split -> extract), detect uncertainty and correct with human-in-the-loop, fine-tune, and a lot more. You can certainly get close to full automation over time, but it takes time and effort — and that's where we come in. Our goal is to give AI teams all of that tooling on day 1, so they hit accuracy quickly and focus on the complex downstream post-processing of that data.

[1] https://dub.sh/ojv9b7p

[2] https://dub.sh/X7GFlDd
by foxyv | 2025-06-23 18:16:15+00:00
> Would EVA spacesuits be able to radiate that much away if it was really that hot but for the atmosphere absorbing some?

Yes! The tiny number of particles are moving really fast, but there are very few of them. We are talking about vacuum that is less than 10^-17 torr. A thermos is about 10^-4 torr. The LHC only gets down to 10^-10 torr. At those pressures you can lower the temperature of a kilometer cube by 10 thousand kelvin by raising the temperature of a cubic centimeter of water by 1 kelvin. There is very little thermal mass in such a vacuum which is why temperature can swing to such wild levels.

This is also why spacecraft have to reject heat purely using radiation. Typically you heat up a panel with a lot of surface area using a heat pump and dump the energy into space as infrared. Some cooling paints on roofing do this at night which is kind of neat.
by rsc | 2025-06-23 18:16:20+00:00
This is a strange and dangerous thing to try to do from assembly. In particular, all these details about write barriers being hand-coded in the assembly are subject to change from release to release.

Better to structure your code so that you do the pointer manipulation (and allocation) in Go code instead, and leave assembly only for what is absolutely necessary for performance (usually things like bulk operations, special instructions, and so on).
by ceejayoz | 2025-06-23 18:17:19+00:00
We had cameras and other devices installed under the old nuclear deal.

https://www.nbcnews.com/politics/national-security/iran-remo...

> It appeared Iran intended to remove the bulk of the cameras and other monitoring gear installed as part of the 2015 nuclear agreement between Tehran and world powers, according to Grossi. Without cameras in place, Iran could divert centrifuges used for uranium enrichment to other unknown locations, he said.
by incognito124 | 2025-06-23 18:17:32+00:00
uv is almost perfect. my only pet peeve is updating dependencies. sometimes I just want to go "uv, bump all my dependencies to the as latest version as possible while respecting their constraints". I still haven't found an elegant way to do this, but I have written a script that parses pyproject.toml, removes the deps, and invokes `uv add --upgrade` with them.

other than that, it's invaluable to me, with the best features being uvx and PEP 723
by RankingMember | 2025-06-23 18:17:48+00:00
It's very possible that Iran moved the important stuff off-site before the attacks.

https://www.npr.org/2025/06/22/nx-s1-5441734/satellites-show...

> "The program has been seriously set back, but there's a lot of odds and ends," Albright says. Ultimately he thinks the only way to truly end Iran's nuclear program is through additional nuclear inspections by international monitors and cooperation from the Iranian regime, probably through some kind of diplomatic agreement.

Weird, kinda like what we had with the Iran Nuclear Deal that our president pulled us out of.
by zozbot234 | 2025-06-23 18:18:04+00:00
The basic point is to have something akin to lambda-calculus that can equally account for both strict and lazy evaluation strategies, in a way that doesn't unduly sacrifice expressiveness for one or the other. (Compare the ML family of languages and Haskell, where strict and lazy evaluation respectively are idiomatic. You can express lazy evaluation in a ML and strict evaluation in Haskell, but only in clunky ways that don't align with the overall logic of the language. CBPV and other comparable formalisms aim to resolve this.)
by ants_everywhere | 2025-06-23 18:18:04+00:00
Editing a remote file is very common. Wanting to download and run a remote server every time you edit a remote file is far less common.

E.g. editing a config on an embedded device such as a router, editing a file inside a docker container, editing a file on a headless server, etc etc.

The only reasonable use case I can see for the vscode approach is if you're SSHing into your main development machine from another machine.

The remote server requirements include

> 1 GB RAM is required for remote hosts, but at least 2 GB RAM and a 2-core CPU is recommended.

That's pretty far from the SSH+vi use case that TRAMP replaces.
by kissgyorgy | 2025-06-23 18:18:17+00:00
> how soon before we start designing codebases for LLM agents to navigate more cleanly?

It's already happening. Armin Ronacher started writing more Go code instead of Python because it understand it better. My coworker changed writing a Desktop app in Rust, because it can navigate it better because of better tooling and type system.

People already thinking about how to write documentation for AI instead of other people, etc.
by mike_ivanov | 2025-06-23 18:18:36+00:00
A quick web search brought this:

* https://pmc.ncbi.nlm.nih.gov/articles/PMC3441937/

* https://oehha.ca.gov/sites/default/files/media/downloads/ris...

* https://www.medicalnewstoday.com/articles/red-dye-40-adhd
by morleytj | 2025-06-23 18:19:17+00:00
A similar situation in the US can be seen in Boston. Historically terrible nightlife and for easily explained reasons. Liquor licenses are distributed by the state at a capped amount that can potentially be increased each year, meaning the majority of new businesses wanting to have alcohol sales will need to purchase an existing liquor license from another business, often at an exorbitant price (over 500k USD on average I believe)

This makes it extremely difficult for any new businesses to start, and massively advantages large chain businesses that have the ability to make the initial investment in securing a license, versus small or quirky businesses which just have no chance getting started.
by toast0 | 2025-06-23 18:19:18+00:00
Wikipedia reports red M&Ms were eliminated in 1976, and added back in 1987. I'm sure it took several months for these changes to make it to the marketplace, but probably not years; M&Ms have a reasonable shelf life, but they do degrade, so year old stock isn't great.

My Mom was pretty salty about the red M&Ms going missing, and refused to eat blue M&Ms for quite some time.
Show HN: Nodehaus – Custom AI Models Without the Technical Overhead
by neutronsoup | 2025-06-23 18:20:02+00:00
I'm an ML engineer who's been building ML platforms and data platforms for startups and enterprises for a couple of years, with a focus on generative AI platforms lately (think big GPUs, serverless inference, vector DBs). Each company has different requirements for their platforms, but some core principles and requirements are the same for all .

This inspired me to build Nodehaus.io, a platform that helps non-technical users finetune and deploy generative AI models with a few clicks, no coding or configuration required. Think of it as an ml-platform-as-a-service.

Target: Marketing and creative agencies - agile teams that need a lot of custom/bespoke generative AI models to create outputs for their clients, and who have little to no engineering support.

We're currently running a pilot program where we're giving away free trainings & deployments in exchange for detailed feedback and reviews.

Thanks for your time!

p.s: started doing cold outreach, which feels very uncomfortable as an engineer, and had this idea for the subject line: "So easy a marketer could do it!". Too much?
by Jemaclus | 2025-06-23 18:20:21+00:00
I think there's a pretty big difference between QA (letting bugs go by) and A/B testing, and your post appears to me to be conflating the two. I would argue that you are better off spending your time QAing a feature that you have high confidence is positive ROI, than spending weeks waiting for an A/B test to reach stat sig.

I don't disagree with your statement, I just think you are addressing a different problem from A/B testing and statistical significance.
by mytailorisrich | 2025-06-23 18:20:23+00:00
> It's pretty much settled that it's far better to only make 1 device than 3, even if you were to recycle the 3 devices and not recycle the 1 device.

It's certainly neither settled not factual.

> Far better to reuse the electronics for multiple years than to get a new one each year. Same with clothing.

The point isn't whether it is 'better' or not. The point is that if you don't ultimately properly dispose of them through recycling you haven't solved anything. At best you've slowed the rate at which we're covering the planet in trash but obviously the end result will be the same: It will end up covered.

> Population is declining everywhere

Not yet and current level is unsustainable (as we're seeing) whether you do symbolic gestures like keeping your smartphone longer or not.
by Terr_ | 2025-06-23 18:21:27+00:00
> comparisons to calculators

Yeah, the current LLM dilemma isn't really analogous. Offloading a task like multiplying two numbers is (A) safely reliable and (B) isn't delegating planning or decision-making.

> The average person [...] stopped doing math at the grocery store and became docile enough to allow the rise of modern consumer economics, Uber, Doordash, Klarna.

Disagree on this one: Wasteful spending by consumers (and vendors encouraging it) is a very old problem, much older than calculators or any withering of daily algebra skills. If anything, people have better/faster capabilities to see the "big picture" of how much a service is ripping them off than ever before.

I think a better explanation would be stuff like the psychological distance created when using digital payments (as opposed to cash or handwritten checks) and companies getting better tools for advertising/brain-hacking.
by forrestthewoods | 2025-06-23 18:21:49+00:00
Here’s my #1 complaint about uv: I’m new to the python ecosystem. I don’t know anything about pip or the existing tools. I would love for uv to at least have documentation and a user guide that doesn’t assume knowledge of the old bad tools that uv replaces.

Perhaps uv will continue its ascendancy and get there naturally. But I’d like to see uv be a little more aggressive with “uv native” workflows. If that makes sense.
by jsnell | 2025-06-23 18:21:54+00:00
The costs are already far, far below that level. The only reason the consumer-facing businesses are not profitable is that nobody is yet showing ads, i.e. providing service to hundreds of millions of people with no monetization at all. LLM inference is cheap, but not free. But the moment they start showing ads, even basic ad formats will easily make them profitable. Let alone more sophisticated LLM-native ad formats, or the treasure trove of targeting data that a LLM chat profile can provide.
by holysoles | 2025-06-23 18:22:02+00:00
Might be worth opening an issue, the project states it aims to aggressively cache dependencies: https://docs.astral.sh/uv/concepts/cache

Maybe that functionality isnt implemented the same way for uvx.

You could try this equivalent command that is under "uv run" to see if it behaves differently: https://docs.astral.sh/uv/concepts/tools/#relationship-to-uv...
by karlgkk | 2025-06-23 18:22:14+00:00
> memory errors with no viable exploit path

i dont appreciate putting "vulns" in scare quotes, if that was your intent

swiss cheese theory. all it takes is someone changing a component that allows that vulnerability to be chained into an exploit, which has happened many times.

these should be tracked, and in fact, it's very helpful to assign cves to them

but yeah, raw numbers is less useful. in fact, cves as a "is it secure or not" metric are pretty rough. it makes it easier to convince vendors to keep their software up to date, though...
by MetaWhirledPeas | 2025-06-23 18:22:14+00:00
> Waymo seems to be the furthest ahead in my complete outsider opinion.

There's a high floor to Waymo's costs though, and therefore a lower ceiling to their profits. Tesla's aim was always to make it (way) more scalable. If they can match Waymo's performance at Tesla's costs, Waymo goes the way of the dodo pretty quick.
by semi-extrinsic | 2025-06-23 18:22:21+00:00
At this low density, temperature is very different from what you are used to experiencing. You have to work through a heat flux balance to really get a grasp of it.

Temperature is just the heat of particles moving. In the extreme case of a handful of N2 molecules moving at 1% the speed of light, it has a temperature of something like 9 billion Kelvin. But it's not going to heat you up if it hits you.
by veganjay | 2025-06-23 18:24:43+00:00
Initially, I used `uv tool run <name>`, but later discovered `uv tool install <name>`. The `install` command downloads dependencies once and caches them for future use. It is similar to how `pipx install <name>` works.

e.g.

$ uv tool install asciinema

$ asciinema play example.cast
by techpineapple | 2025-06-23 18:24:48+00:00
Our intelligence didn't know that Iran was trying to build a Nuclear Bomb, so we had to do this attack, but now our intelligence definetly knows:

'They are claiming that they moved some material," Mullin said, referring to Israel and Iran, respectively. "Our intelligence report says they didn't," the Oklahoma Republican said in an interview on CNBC's "Squawk Box."
by iLemming | 2025-06-23 18:25:04+00:00
I don't think it's Jetbrain's fault, even though I have not used their products for almost a decade. Python ecosystem is finicky - too many options - it's hard to decide which things you want and need - black or yapf or ruff, flake8, rope, mypy, pydocstyle, pylint, jedi; there are multiple lsp server options (none of which is ideal), you get to know things like what the heck 'preload' plugin is - the docstring for lsp-pylsp-plugins-preload-enabled just says "Enable or disable the plugin", etc.

Trying to bootstrap a Python setup "that just works™" is also a common struggle e.g. in Emacs world. Python tools are just a bunch of contraptions built with fiddlesticks and bullcrap. Anyone who tells you differently either already have learned how to navigate that confusing world and totally forgot "the beginner's journey"; or too new and have not tussled with its tooling just yet; or simply don't know any better.
by o11c | 2025-06-23 18:25:22+00:00
IMO, the real problem with trying to enforce capability-based systems on desktop/server environments is the correct API isn't implemented. `capabilities(7)` is only a tiny subset of `credentials(7)`, `PR_SET_NO_NEW_PRIVS` is an abomination, `SCM_RIGHTS` has warts, and `close_range` is fundamentally braindead.

We need at least the following sets: effective, permitted, bounding (per escalation method?), and the ability to make a copy of all of the preceding to automatically apply to a child (or to ourselves if we request an atomic change). Linux's `inheritable` set is just confusing, and confusion means people will use it wrong. At least we aren't Windows.
by b0a04gl | 2025-06-23 18:25:48+00:00
terminal scrollback is the only UI we don't treat as queryable state. op's setup shows how much context we're missing away a lot of rg output, file paths, stack traces, build logs they're all already right there in cluttered state.

if shells exposed a scrollback api with line refs and structural tagging, we could annotate paths, link to buffers, diff last two runs, all without re executing anything. that would cut through half the indirection in current workflows. tmux's regex jump is a hack but it hints at a deeper model. scrollback should be its own memory layer
Ask HN: How does AI overcome the "essential complexity" as in No Silver Bullet?
by hintymad | 2025-06-23 18:25:52+00:00
In No Silver Bullet, Fred Brooks argues that the hard part of software engineering lies in essential complexity - understanding, specifying, and modeling the problem space - while accidental complexity like tool limitations is secondary. His point was that no tool or methodology would "magically" eliminate the difficulty of software development because the core challenge is conceptual, not syntactic.

Fast forward to today: there's a lot of talk about AI agents replacing engineers by writing entire codebases from natural language prompts. But that seems to assume the specification problem is somehow solved or simplified. In reality, turning vague ideas into detailed, robust systems still feels like the core job of engineers.

If someone provides detailed specs and iteratively works with an AI to build software, aren’t they just using AI to eliminate accidental complexity—like how we moved from assembly to high-level languages? That doesn’t replace engineers; it boosts our productivity. If anything, it should increase opportunities by lowering the cost of iteration and scaling our impact.

So how do we reconcile this? If an agent writes a product from a prompt, that only works because someone else has already fully specified the system—implicitly or explicitly. And if we’re just using AI to replicate existing products, then we’re not solving technical problems anymore; we’re just competing on distribution or cost. That’s not an engineering disruption—it’s a business one.

What am I missing here?
by Jemaclus | 2025-06-23 18:25:53+00:00
Absolutely. If you're the business owner, selling fewer widgets is Very Bad!

But in my post, I specifically called out a line in OP's article that I disagreed with: (paraphrasing) "Your startup deserves the same rigor as medical testing."

To clarify -- and support your point --, we're shipping software, not irreversible medical procedures. If you get it wrong, you sell fewer widgets /temporarily/ and you revert back to a known better solution. With medicine, there aren't necessarily take-backsies -- but there absolutely are in software. Reverting deploys is something all of us do quite regularly!

Is it A/B testing? Maybe, maybe not. I'm not a data scientist. But I think saying that your startup deserves the same rigor as a medical test is misleading at best and harmful at worst.

I just think companies should be more okay with educated risks, rather than waiting days, weeks, months for statistical significance on a feature that has little chance of actually having a negative impact. As you said elsewhere in the thread, for startups, stasis is death.

(BTW, I've read a lot of your other comments in the thread. I think we're pretty well aligned!)