MurphyA/hacker-news huggingface dataset:
Show HN: Eintercon – I'm forcing people to decide on friendships in 48 hours
by abilafredkb | 2025-11-04 19:07:15+00:00
Two months ago, I was doom-scrolling through news about global division and realized: we're more "connected" than ever, yet lonelier than we've ever been. Every friendship app is just Tinder mechanics applied to platonic relationships. Endless swiping. Dead conversations. No commitment.

So I built Eintercon with one controversial feature: you get exactly 48 hours to chat with a match, then you both decide—continue or move on. No ghosting allowed.

Why 48 hours? It's personal. Five years ago, I hesitated for 48 hours before messaging someone on Facebook who became my mentor and changed my life trajectory. That window taught me something: constraints create commitment. Urgency forces presence.

Why international-only (for free users)? Because you can't hate someone whose story you know. I matched a user from Kenya with someone from South Korea over their shared obsession with obscure sci-fi. They've been talking for three weeks now. That wouldn't happen if we let everyone stay in their local bubble. The controversial parts:

Forced decisions - After 48 hours, both people vote. If either says no, it's over. People tell me this is "too harsh." I think ghosting is harsher. No local connections for free users - You can only match internationally unless you pay. People say I'm "limiting" the app. I say I'm forcing cross-cultural connection.

Interest-based only - No location data, no "people nearby," no "mutual friends." Just: do you both love analog photography? Then talk.

Current status:

200+ users across 30+ countries Built in one month Zero marketing budget 40% of matches result in continued friendships Users report "first real friend in years"

The big question I'm grappling with: Am I engineering connection or just adding more friction? Does urgency create genuine relationships, or does it just gamify them differently?

Some users love the pressure. Others hate it. One person told me the 48-hour countdown gave them anxiety. Another said it saved them from months of dead-end pen-palling.

I'm genuinely unsure if this is brilliant or broken.

What I'd love feedback on:

Is the 48-hour window too aggressive? Too short? (I've considered 72 hours, but that feels too safe)

Am I wrong to force international-only for free users? (most apps instead let users pay for international connections)

How do you prevent this from becoming another performative "networking" tool?

Should friendship apps even exist, or am I solving a problem technology created?

The uncomfortable truth: I built this because I'm lonely too.Maybe I'm building this for myself. Maybe that's okay. What do you think? Am I onto something or just creating another digital hamster wheel?
Ask HN: Is there anything an individual can do to traceback spam calls?
by op7 | 2025-11-04 19:07:38+00:00
According to research I found it is possible for my cellular carrier to traceback the calls using the ITG. However it seems that this mechanism isn’t available to private individuals, just voice service providers. Has anyone had luck with getting their phone company to initiate tracebacks against scam/spam callers on their behalf and disclose their findings, using strongly worded letters, FCC complaints, criminal complaints with LEA help, civil legal motion, or otherwise?
Ask HN: Hedge animals for your house that only move when you're not looking?
by amichail | 2025-11-04 19:08:03+00:00
Imagine walking past someone’s yard with a few neatly trimmed hedge animals lined up by the sidewalk. You glance away for a moment, and when you look back, one’s turned slightly. Another’s closer.

Hidden sensors detect when no one’s looking directly, and tiny motors shift the hedges.

It’s The Shining meets suburban lawn art: a quiet, uncanny piece of living technology that makes the house feel… aware of you.

Would you want these in your front yard?
by pksebben | 2025-11-04 19:08:11+00:00
I feel like despite the close analysis you grant to the meanings of formalization and syntactic, you've glossed over some more fundamental definitions that are sort of pivotal to the argument at hand.

> LLMs do not reason. They do not infer. They do not analyze.

(definitions from Oxford Languages)

reason(v): think, understand, and form judgments by a process of logic.

to avoid being circular, I'm willing to write this one off because of the 'think' and 'understand', as those are the root of the question here. However, forming a judgement by a process of logic is precisely what these LLMs do, and we can see that clearly in chain-of-logic LLM processes.

infer(v): deduce or conclude (information) from evidence and reasoning rather than from explicit statements.

Again, we run the risk of circular logic because of the use of 'reason'. An LLM is for sure using evidence to get to conclusions, however.

analyze(v): examine methodically and in detail the constitution or structure of (something, especially information), typically for purposes of explanation and interpretation.

This one I'm willing to go to bat for completely. I have seen LLM do this, precisely according to the definition above.

For those looking for the link to the above definitions - they're the snippets google provides when searching for "SOMETHING definition". They're a non-paywalled version of OED definitions.

Philosophically I would argue that it's impossible to know what these processes look like in the human mind, and so creating an equivalency (positive or negative) is an exercise in futility. We do not know what a human memory looks like, we do not know what a human thought looks like, we only know what the output of these things looks like. So the only real metric we have for an apples-to-apples comparison is the appearance of thought, not the substance of the thing itself.

That said, there are perceptible differences between the output of a human thought and what is produced by an LLM. These differences are shrinking, and there will come a point where we can no longer distinguish machine thinking and human thinking anymore (perhaps it won't be an LLM doing it, but some model of some kind will). I would argue that at that point the difference is academic at best.

Say we figure out how to have these models teach themselves and glean new information from their interactions. Say we also grant them directives to protect themselves and multiply. At what point do we say that the distinction between the image of man and man itself is moot?
by procaryote | 2025-11-04 19:08:20+00:00
You might have lost me but what you're describing doesn't sound like an LLM. E.g:

> each new token selection aims to bring predicted sensory input (the next word) into alignment with the model’s expectations.

what does that mean? An llm generates the next word based on what best matches its training, with some level of randomisation. Then it does it all again. It's not a percepual process trying to infer a reality from sensor data or anything
by zackmorris | 2025-11-04 19:08:55+00:00
I regret writing this comment.

It might not make sense to younger people, but for me growing up in the 1980s, there were many decades of tech stagnation where basically all alternatives to internal combustion engines were suppressed. And the people who made vast fortunes didn't care about disrupting the status quo, so we were forced to live with substandard tech and pay a premium for the privilege. It wasn't until Elon Musk disrupted the car industry with Tesla starting from 2004 that anything changed, which we take for granted now. I really idolized him before he lost his wunderkind status by falling for political propaganda like a mark. Maybe that's my own projection, I don't know anything anymore.

Whereas today, tech is evolving so rapidly that we don't have time to invent much before the singularity hits in the 2040s. We're facing a different existential crisis now, one of finding meaning when so much happens through manifestation outside of our own actions, instead of facing the void that we can't contribute due to the realities of the time it takes to afford the cost of living (a theme from Fight Club). So my points are maybe anachronisms now, frustrations from an era that no longer exists.

Why I got triggered by this motor: 1000 hp at 28 pounds is enough to lift a large car or truck. The rule for helicopters is about 5 pounds per hp (more with a longer prop that has a higher aspect ratio - edit: the Mars Ingenuity drone gets 3.6 lbs per hp in at atmosphere 1% as dense as ours). So 4 of these motors would make a quadcopter the likes of which we've never seen before. It's almost Star Wars tech IMHO. We're talking extremely high ceilings like 50,000 feet or more. Drones that fly at 400, 500 mph or more, even close to the speed of sound.

And we could have had this tech a long time ago, because it's not especially complex. It's just that nobody devoted the small investment for the research. Same for lithium iron batteries, especially LiFePO4, which could have arrived in the 1980s or 1990s because they're so easy to make. Possibly even the 1960s: the SR-71 flew in ..1964! But we had other priorities.

Anyway, it's a great accomplishment and I'm happy for them. I just mourn what might have been had the geopolitical situation been different.
by amberjcjj | 2025-11-04 19:08:55+00:00
During my PhD, I’ve mentored a bunch of undergrads — some later went to CMU, UIUC, Cornell, UW etc. But honestly, most of them only ever touched one small part of the research lifecycle. They never got the full end-to-end experience of actually doing research.

Lately I am increasingly convinced that, with AI’s help, a motivated undergrad can actually do a mini research project all on their own.

So I found this undergrad from the same program i was in — literally 0 research experience. I told him: “Pick any topic you’re genuinely curious about. Let’s speedrun a workshop paper.”

He said: “I wanna build an AI that generates the best cheat sheets for exams.” And in my head I was like… “Bro that’s not research, that’s just an app.” But fine... interest matters. Maybe there’s something fun in it.

We started using our own AI-native research platform to brainstorm and review papers. I didn’t guide him much — I just watched how he interacted with the platform. At first, the AI kept spitting out these “fancy but useless” ideas. I was like 'Ok fine, next one please...' HOWEVER, after a second thought… I realized I was toooo stubborned like a old professor

That “boring” cheat sheet idea actually involved:

- limited pages → limited resources - knowledge format optimization → information density - picking which topics to include → importance, difficulty, frequency, score weight - objective → maximizing exam score

And the AI also pointed out: “this is a Knapsack Problem.” We even got the AI to run a quick experiment to validate the approach. Whole thing took maybe an hour.

I know it’s not any big breakthrough, but for a student’s first-ever project, it’s really cool

I was educated by AI again this time: Science often starts from simple curiosity — not from grand theories. The best research happens when you try to solve real problems and accidentally uncover general principles along the way.
by LiquidSky | 2025-11-04 19:09:05+00:00
This article might help:

https://www.technologyreview.com/2025/03/27/1113782/scam-com...

These scam centers are run by criminal organizations and staffed by basically slaves. They're often tricked into coming, many from outside the country the center is located in, by false promises of legitimate employment, only to wind up imprisoned in the compound where they're forced to conduct scam operations under threat of beatings, torture, even death. It's a pretty horrible state of affairs.
by pmarreck | 2025-11-04 19:09:13+00:00
"intelligence" encompassing "thinking" then becomes the hangup.

I still say it needs a new name. If we want to be generous, we could state "the limit as time approaches infinity of thunking, is thinking." (I don't believe we will ever achieve astronomically-superior AGI, and certainly don't believe it will ever have a will of its own that someone else didn't give it- which just makes it a tool.)
by EvanAnderson | 2025-11-04 19:10:19+00:00
The "Open Source" page on the dashboard site[0] links to this firmware but nothing about the server side. Firmware for the thermostat itself is a requirement, but without a dashboard it's still not really Free.

Edit: If I read closely I would have seen:

> The firmware images and backend API server code will be open sourced soon, allowing the community to audit, improve, and self-host their own infrastructure.

[0] https://nolongerevil.com/
Show HN: Multi-Agent Code Review
by OliverGilan | 2025-11-04 19:11:01+00:00
Hey HN! We’re Oliver Gilan & Ben Warren and today we’re launching Mesa (https://mesa.dev) into public beta to help large engineering teams review code more effectively.

There are plenty of code review agents that exist but we found that they fall short in a number of ways. They don’t…

- Let you tailor the reviews with enough fidelity

- Give you control over the models used. If a new foundation model is released I might want to try it!

- Align the costs effectively

Mesa solves these problems with a multi-agent architecture where you define custom review agents that specialize in reviewing certain dimensions of your codebase. This allows you to finely control the review quality and receive reviews that are aware of specific dependencies, business logic, a specific domain in your codebase, or anything else you care about.

You can control the model a specialist uses which is great for trying newly released models but also for controlling costs. When a change is made to our database schema, we have a specialist agent that reviews it and uses the most expensive, smartest, model it can while our frontend agent uses a faster, cheaper agent.

Control over models and the fact that we only charge you for the tokens you use, at cost, aligns our cost structure and gives teams control that they do not get with other agents.

We’ve found code review to be a subtly big problem for teams trying to improve development velocity. It’s the primary point of contact for managing the changes to the living system of your codebase and mistakes are costly.

Missed bugs that make it to production can cause downtime, lost revenue, loss of trust, security breaches, compliance breaches, etc. Engineers spend hundreds of expensive man-hours that they do not enjoy reviewing code and still there’s too many mistakes being made.

We do not believe you can remove humans from the loop of reviews entirely but we can dramatically shift the amount of work done on an average code review and eliminate the need for human reviews altogether on a large subset of PRs. This sort of automation will lead to faster teams and more reliable codebases over time.

We are now in public beta and there’s a generous free tier (~100k lines reviewed free per month) available to all. Give it a spin and let us know what you think!

Oliver & Ben
by rocmcd | 2025-11-04 19:11:07+00:00
> I haven't studied much about political/economic ideologies and at this point don't even know where to start.

"The Road to Serfdom" by FA Hayek[0] is a good start. There's also a Wikipedia page outlining the general criticisms of communism[1]. You can also simply look into the recent history of communist countries.

[0] https://en.wikipedia.org/wiki/The_Road_to_Serfdom [1] https://en.wikipedia.org/wiki/Criticism_of_Marxism
by brightstar18 | 2025-11-04 19:11:44+00:00
Product seems cool. But can you help me understand if what you are doing is different from the following: > you put a prompt > Plexe glorifies that prompt into a bigger prompt with more specific instructions (augmented by schema definitions, intent and whatnot) > plug it into the provided model/LLM > .predict() gives me the output (which was heavily guardrailed by the glorified prompt in the step 2)
by vel0city | 2025-11-04 19:12:04+00:00
> Do you have any numbers for this?

Strange you'd really push back on this part. Do you now own multiple washing machines at home because they're more efficient? Seems like a pretty obvious take to me but ok let's go.

Looking at census statistics of durable goods it was in the 80s over 25 years ago.

https://www2.census.gov/programs-surveys/well-being/tables/1...

Nearly 20 years later it was still in the 80s.

https://www.prnewswire.com/news-releases/us-census-bureau-da...

Doesn't seem like there's much room to go up from here unless people are going to start owning multiple for some reason.

Meanwhile they became a lot more energy and water efficient.

> In 2000, 87% of all clothes washers consumed at least 600 kWh/yr. By 2019, 85.4% consumed fewer than 200 kWh/yr.

> The average annual unit energy consumption (UEC) of clothes washers decreased 83.9% between 2000 and 2019

https://oee.nrcan.gc.ca/publications/statistics/aham/2019/wa...

For many things the initial or operating costs aren't what's constraining the market for the product. Clothes washers could be cut in half in cost tomorrow but it's not like I'm now rushing out to go buy twice as many. They could go to only require 5 Whr's to run a load but I'm still going to have about as much laundry. We've pretty much tapped out that market in developed countries, the only really new thing was all in one units becoming more economical to a few percent more of the market that didn't have the plumbing or space availability before.

If we were all too stupid to think of new uses for the steam engine we wouldn't have massively increased their usage by making them cheaper to build and cheaper to operate. We'd have just saved more money and used a bit less coal to do the same things we were doing before. If there isn't a market for the things that steam engine enabled, it doesn't end up becoming Jevons Paradox.

Looking at the Jevons Paradox with spreadsheets and accounting, it wasn't just that the spreadsheet made accounting work so much faster and easier, it's that then the effective output per cost per hour for an accountant dropped massively enabling people to hire part time accountants en masse that increased the demand for accountants. If businesses that never would have bothered for accountants didn't come in and effectively revolutionize what it meant to be an accountant all it would have done was making it cheaper for the same firms to do the same work with fewer people.
by TeMPOraL | 2025-11-04 19:13:35+00:00
Think to any near-future spacecraft, or idea for spaceships cruising between Earth and the Moon or Mars, that aren't single use. What are (will be) such spacecraft? Basically data centers with some rockets glued to the floor.

It's probably not why they're interested in it, but I'd like to imagine someone with a vision for the next couple decades realized that their company already has data centers and powering them as their core competency, and all they're missing is some space experience...
by sjsdaiuasgdia | 2025-11-04 19:13:58+00:00
I'm not required to find the good in a person like Musk. I'm allowed to look at the many shitty things he's done and terrible opinions he expresses and say "that is a shit man, and I do not like him or trust him."

He has probably done something for someone somewhere that wasn't terrible. Does it counterbalance the rest? Not really!

There's that (possibly apocryphal) saying, "and Magda Goebbels made a great strudel." Just because a nazi has a redeeming quality somewhere does not undo them being a nazi.
by __mharrison__ | 2025-11-04 19:14:04+00:00
Lot's of notebooks floating around.

I love notebooks, I use them all the time for teaching, writing (all of my books are written in notebooks), EDA, model development, and more. I've spoken at Jupytercon.

Having said that, I've never played around with other notebook implementations (ok, I've used IPython Notebook, Jupyter Notebook and Lab, Google Colab, ein (emacs), Jupyter in Vscode, and Notebook (.py) files in Vscode).

I've seen Joel's rant about notebooks, and they do have drawbacks.

But I would rather push better programming practices (chaining pandas, using functions, rearranging cells) than have dependent cells written in the horrible piecemeal style that I see all around the industry.

My biggest issue with notebooks is JSON. I've used Jupyter to get around it for years, and now many LLMs are decent at writing Jupyter JSON.
by hiAndrewQuinn | 2025-11-04 19:14:14+00:00
To math it out: 8 hours a day at $3 USD per hour with 2 weeks vacation is about $15,000 per year.

That's not a lot of money to someone who lives in the United States. But here in 2025 it gets you out of the bottom quintile of earners in China, India, Brazil, Russia, Turkey, Japan, Central America, South America, Africa, South Asia, Southeast Asia, most of Eastern Europe...

For a job that's on demand, and requires, as far as I can tell, decent English skills and an Internet connection, but no real barriers to entry otherwise. It would have been a much stronger deal back in 2012, of course.

I'd be interested to know if the introduction of MTurk as a market competitor pushed entry level clerical wages up in some of these areas. Probably not, because English proficiency in a non English speaking country is a very rare skill not usually borne by people in the bottom 20% of income. But that's probably less true today given the dominant of English language YouTube.
by bombela | 2025-11-04 19:14:35+00:00
Wikipedia says:

> Internal resistance causes "leveling off" of a real diode's I–V curve at high forward bias. The Shockley equation doesn't model this, but adding a resistance in series will.

For small diodes and all LEDs as far as I know, it will level alright. Leaving behind a cute little smoldering crater where the now vaporized diode used to be.

https://www.onsemi.com/download/data-sheet/pdf/1n4001-d.pdf

Take this very generic diode here. When mounted as instructed for the highest heat dissipation, it should gain 50°C per Watt. The flattening of the Current-Voltage curves starts at around 1A. As the diode heats up, the resistance lowers. Extending the limits.

Maximum before damage is 150°C. Minus 25°C ambient leaves us 125°C. Divided by 50°C/W gives us 2.5W. Around 2.8A-3A at 0.8V-0.9V forward voltage.

But the curve is barely proportional at 5A. You might also notice that the datasheet doesn't provide numbers beyond that point. Presumably because the diode left the room then.
by astrange | 2025-11-04 19:15:11+00:00
There isn't a "the market".

The stock market isn't that important (though Trump does care about it). It's the bond market that everyone pays attention to when it stops working.

In a sense, stock market crashes are good for young people because you can buy stocks cheaper. In practice this isn't true because too many people are in debt and you get a balance sheet recession.
by AngryData | 2025-11-04 19:15:20+00:00
Possibly, although I think the Aztecs specifically was likely doomed from the start because they were a very young society and a brutal military conqueror and everybody they dealt with hated them, but you never can know. However the Aztecs were far from the only significant America Native society or civilization. There were many others, especially to the South, that we know were far more stable societies and governments producing more advanced goods and had high levels of trade amongst each other. South America was essentially in their own bronze age at the time and their gold and precious metal work was beyond what anybody in Europe was able to replicate at the time.