MurphyA/hacker-news huggingface dataset:
by rkomorn | 2025-11-04 07:20:21+00:00
I don't think it's just "most Americans don't know."

When I installed AC in my former Bay Area home, I would have needed multiple mini split units to cover 1200sq ft, with questions about how many you could have on at once to still get the right performance. I went with a single central air unit instead.

It also (at the time at least) didn't come with a centralized thermostat, which meant managing each room individually (that would've been fine with me, personally, but it's a drawback for lots of people).

On top of that, many (if not most) mini split units are also somewhat aesthetically displeasing.

In my new home (on a different continent), I have mini splits. I'm somewhat satisfied with them, at best. I'd still prefer central air but it's not a thing for residential homes here.
by ktpsns | 2025-11-04 07:20:53+00:00
An audacity fork. Reason for forking described at https://tenacityaudio.org/docs/_content/Introduction_and_Mot... . Their own summary:

> at the primary reasons were attempts at adding telemetry and a new desktop privacy policy [by the new audacity maintainers]

Previously discussed at https://news.ycombinator.com/item?id=34835200
by madaxe_again | 2025-11-04 07:21:02+00:00
The vast majority of human “thinking” is autocompletion.

Any thinking that happens with words is fundamentally no different to what LLMs do, and everything you say applies to human lexical reasoning.

One plus one equals two. Do you have a concept of one-ness, or two-ness, beyond symbolic assignment? Does a cashier possess number theory? Or are these just syntactical stochastic rules?

I think the problem here is the definition of “thinking”.

You can point to non-verbal models, like vision models - but again, these aren’t hugely different from how we parse non-lexical information.
by hulitu | 2025-11-04 07:21:07+00:00
> However every once in a while the stars align and the new species fits into a slot the home team didn't "realize" existed, or they hammer a weakness that the rest of the ecosystem had just been coevolving around for a long time, and you get the invasive species.

"One thing that may help resolve this in your head is that" the echosystem might be destroyed, so an invasive species just takes the place of other species. Like, you know, we kill all the volves and then we are invaded by deers.
by Kichererbsen | 2025-11-04 07:22:10+00:00
Sure. But neither do you. So are you really thinking or are you just autocompleting?

When was the last time you sat down and solved an original problem for which you had no prior context to "complete" an approximated solution with? When has that ever happened in human history? All the great invention-moment stories that come to mind seem to have exactly that going on in the background: Prior context being auto-completed in an Eureka! moment.
by heyitssim | 2025-11-04 07:22:26+00:00
Building a location-based game that captures Taiwan's absurd convenience store density[1]

The premise: stand at any 7-11/FamilyMart/etc, take a photo showing you can see the next store, walk to it, repeat. Chain as many stores together as you can. It sounds silly but Taiwan really is this convenient - you often can see 2-3 stores from one spot. Here[2] one route where you can actually link 7 convenience stores in a row!

This is actually the first game built on our upcoming platform for creating branded games. Figured the best way to test the concept was to make something fun first!

[1] https://craftmygame.com/game/convenience-store-marathon

[2] https://craftmygame.com/game/convenience-store-marathon/rout...
by gf000 | 2025-11-04 07:22:30+00:00
Game of life, PowerPoint, and a bunch of non-PL stuff are all Turing-complete. I don't mix up terms, I did use a slightly sloppy terminology but it is the correct concept - and my point is that we don't know of a computational model that can't be expressed by a Turing-machine, humans are a physical "machine", ergo we must also fall into that category.

Give my comment another read, but it was quite understandable from context. (Also, you may want to give a read to the Turing paper because being executable by a person as well was an important concept within)
by teiferer | 2025-11-04 07:23:21+00:00
> Regardless of which specific companies survive, this infrastructure being built now will create the foundation for our AI future - from inference capacity to the power generation needed to support it.

Does that comparison with the fiber infra from the dotcom era really hold up? Even when those companies went broke, the fiber was still perfectly fine a decade later. In contrast, all those datacenters will be useless when the technology has advanced by just a few years.

Nobody is going to be interested in those machines 10 years from now, no matter if the bubble bursts or not. Data centers are like fresh produce. They are only good for a short period of time and useless soon after. They are being constantly replaced.
by klaushougesen1 | 2025-11-04 07:24:02+00:00
Location: EU

Remote: Yes

Email: klh@threads.dk

Resume: https://www.linkedin.com/in/khougesen/

Techstack: js and friends (lit.dev, webcomponents, node.js, redstack, bluestack, fullstack, allstack etc.)

Exp: 20years - 20th lvl fighter

Super experienced principal, managing, leading IC engineer - can do greenfield to large corp and handle all the nuts and bolt from hither to dither.
by jonway | 2025-11-04 07:24:07+00:00
Its really expensive, its true. Prices spiked like mad after the coronavirus shortages, AC parts were back up forever. It sucked and the costs rose tremendously and seemingly never fell. Then we tarrif the imports and change the rate constantly. Nobody can sort out their supply chains(But it is not just the tariffs).

The refrigerant is often expensive, poisonous and flamable. We don't replace the refrigerant, we reclaim it and dispose of it properly. Its not without risks. Our building codes are pretty rigid as well, its a big pain point.

New HVAC install is gonna need an electrician, the lines pass through walls allowing the possibility of condensation to produce deadly mold. Every installation needs individual consideration. If it isnt %100 perfect, the customer will be riding the installer's ass.

The US has is a Safety Above All mindset on some things. We improve safety far beyond economic rationality because we don't want to systematically kill each other in this way, however few that is.

Unrelated example: a national EMT outfit operating here made all their techs wear plate carriers and ballistic plates. There is nearly no gun violence here. All the techs stopped carrying the plates after a few months because its dumb, and wont stop a baseball bat or a knife, but this is a national outfit, surely they did a cost benefit analysis. Someone signed the check and wrote a policy to make them wear em every day. Plates expire, also.

That said, we can definitely do better, and the cost is too high. Installers are in demand, and we tariff the imports to the tune of %15-%30.
by ggm | 2025-11-04 07:24:28+00:00
You didn't remove money. You only removed the appearance of an exchange of value. The gym wanted the revenue downstream from the review. The Cafe wanted the revenue downstream from the review. All you did is remove payment from a customer, but now the value proposition shifts from a sale from party A to customer B to a service of value to party A provided by customer B, but the actual value is .. what? What evidence? What recourse? Is it worth more or less than the food or the gym session?

If all that happens is floods of insta princesses consume chai latte at the cafes expense for shit reviews, you poisoned the well.

And a real world cost in milk and spice was consumed. This is not a money free situation, you just ignored some externalities to your model.
by advikipedia | 2025-11-04 07:26:45+00:00
We recently spoke with 30+ startup founders and 40+ enterprise practitioners who are building and deploying agentic AI systems across industries like financial services, healthcare, cybersecurity, and developer tooling.

A few patterns emerged that might be relevant to anyone working on applied AI or automation:

- The main blockers aren’t technical. Most founders pointed to workflow integration, employee trust, and data privacy as the toughest challenges — not model performance.

- Incremental deployment beats ambition. Successful teams focus on narrow, verifiable use cases that deliver measurable ROI and build user trust before scaling autonomy.

- Enterprise adoption is uneven. Many companies have “some agents” in production, but most use them with strong human oversight. The fully autonomous cases remain rare.

- Pricing is unresolved. Hybrid models dominate; pure outcome-based pricing is uncommon due to attribution and monitoring challenges.

Infrastructure is mostly homegrown. Over half of surveyed startups build their own agentic stacks, citing limited flexibility in existing frameworks.

The article also includes detailed case studies, commentary on autonomy vs. accuracy trade-offs, and what’s next for ambient and proactive agents.

If you’re building in this space, the full report is free here: https://mmc.vc/research/state-of-agentic-ai-founders-edition...

Would be interested to hear how others on HN are thinking about real-world deployment challenges — especially around trust, evaluation, and scaling agentic systems.
by IanCal | 2025-11-04 07:27:00+00:00
> it's just auto-completing. It cannot reason

Auto completion just means predicting the next thing in a sequence. This does not preclude reasoning.

> I don't get why you would say that.

Because I see them solve real debugging problems talking through the impact of code changes or lines all the time to find non-obvious errors with ordering and timing conditions on code they’ve never seen before.
by Genego | 2025-11-04 07:27:52+00:00
SEEKING WORK | Full-stack Python/Django Developer (Creative AI Focus)

Location: Thailand (UTC+7) Remote: Only Technologies: Django, Python, HTMX, Tailwind, Postgres, Replicate API, image generation pipelines, LoRA training workflows Résumé/CV: https://edwin.genego.io/about Email: edwin@genego.io

Sr. Software Engineer building production Django apps with practical AI integration. I specialize in creative AI tooling , image generation pipelines, multi-model orchestration (Flux, SDXL), prompt engineering systems, and cost-optimized workflows. Current work: 20+ custom management commands for AI image generation, character IP systems, scene replication with layered prompt architecture. I help teams ship AI-powered creative tools without risky rewrites, handling multi-model workflows, resume-capable operations, and obsessive cost tracking. Looking for fractional or project work (2-6 week cycles) involving generative AI, creative tooling, or content pipelines.

https://edwin.genego.io/
by shishironline | 2025-11-04 07:28:03+00:00
Much-needed app, thanks for the same. For some time, I have been thinking about a similar app for the simple requirement of sounding every 25 to 30 minutes while working on a computer just to give rest to the eyes, but I was unable to find a suitable one. The "offline-first PWA with zero dependencies; no build step, no cookies, no links, no analytics, nothing other than timers" gives it a really usable coat for both desktop and mobile
by zkmon | 2025-11-04 07:28:30+00:00
The only problem is, similarity with dotcom might only go thus far. For example, dotcom bubble itself might not have a similar thing in the past at that time. This is because the overall world context is different and interaction of social, political and economic forces is different.

So, when people say something about future, they are looking into the past to draw some projections or similar trends, but they may be missing the change in the full context. The considered factors of demand and automation might be too few to understand the implications. What about political, social and economic landscape? The systems are not so much insulated to study using just a few factors.
by procaryote | 2025-11-04 07:28:41+00:00
> First, autoregressive next token prediction can be Turing complete. This alone should give you a big old pause before you say "can't do X".

Lots of things are Turing complete. We don't usually think they're smart, unless it's the first time we see a computer and have no idea how it works

An LLM is a markov chain mathematically. We can build an LLM with a context window of one token and it's basically a token frequency table. We can make the context window bigger and it becomes better at generating plausible looking text.

Is it possible that beyond becoming better at generating plausible looking text – the expected and observed outcome – it also gains some actual intelligence? It's very hard to disprove, but occam's razor might not be kind to it.
by ryao | 2025-11-04 07:30:07+00:00
If I were to ask most people I know offline, I suspect only a small number of them would know what a minisplit unit is. For most people, A/C is like plumbing. They do not think about it until it breaks. Learning that there are better options is just not something that people do.

That said, I was replying to someone from Vietnam. Assuming that things in Vietnam are similar to China and Japan, people will only heat or cool the specific rooms that they are using, rather than heating or cooling everything like how many Americans do things. Those in the US who cannot afford to heat or cool everything, who are likely very underrepresented here, would be those using window units, since they are cheap upfront. A minisplit would be cheaper over the long term, but the high upfront cost dissuades people in thing market from even looking at them.

Finally, I had Fujitsu minisplit units installed in my basement two years ago. They are far more aesthetically pleasing than window A/C units.
by oarsinsync | 2025-11-04 07:30:29+00:00
Huge respect to the author for the details that have gone into this. I'd spent a week hammering at a Claude max 20x plan to try and build schengen 90/180 rolling window + tax residency in a couple of countries tracker... and that was hard work. I can only imagine how much effort has gone into this, to get all the details right.

It's unclear whether the author wrote all of this themselves, or if they outsourced a bunch of it to Claude. My experience with Claude was that it was terrible at writing code to do the math, even when I explained what the calculation needed to be, what the input was, and what the expected result was. It ultimately took starting a whole new project just to do the rolling window calculation, and then have that fed back in.

My biggest question for the author, if they happen to see this, is: how much manual testing validation did you do of the outputs the app produces? IE: Did you do the inputs + transformations = output calculations yourself as well, counting days on calendars, etc, to validate that the app is actually accurate? (That was the only way I developed any faith in solution I made for myself, which is way less impressive than your app). Regardless of whether you wrote the code yourself or not, a thorough test harness feels vitally important for an app like this.
by rhubarbtree | 2025-11-04 07:31:14+00:00
In our company, you would immediately reject the PR based on size. There are a bunch of other quick bounce items it could also fail on, eg documentation.

The PR would then be split into small ones up to 400 lines long.

In truth, such a big PR is an indicator that either (a) the original code is a complete mess and needs reengineering or more likely (b) the PR is vibe coded and is making lots of very poor engineering decisions and goes in the bin.

We don’t use AI agents for coding. They’re not ready. Autocomplete is fine. Agents don’t reason like engineers, they make crap PRs.
by FOHO | 2025-11-04 07:31:18+00:00
If you're a foreigner renting a home in Korea, there's a high chance you’ll need to hand over a deposit of ₩10–₩100+ million (approx. $7,500–$75,000 USD). This is standard under Korea’s jeonse (lump-sum lease) and wolse (monthly rent + deposit) systems. But if the landlord defaults, disappears, or refuses repayment at the end of the lease, tenants can lose everything.

Korean citizens have some legal protections and access to public deposit guarantees (e.g., via HUG). Foreign residents usually don’t. Language barriers, administrative hurdles, and residency status often block access—leaving even long-term expats exposed to real financial risk.

After seeing too many renters burned, we built deposit insurance specifically for foreigners in Korea. It covers unpaid housing deposits in cases of landlord fraud, bankruptcy, or non-compliance. Applications are available in English, with support for Korean property verification (등록부등본), landlord confirmation, and claims.

We're not solving everything, but it's a start. Feedback from other global housing markets is welcome.

Launch page → foreignerhome.com/en/insurance/deposit
by exe34 | 2025-11-04 07:32:14+00:00
you line up 10-20 PRs and merge them in a temporary integration branch that gets tested/demoed. The PRs still have to be reviewed/accepted and merged into main separately. You can say 'the purpose of this pr is to do x for blah, see top level ticket'. often there will be more than one ticket based on how self-contained the PRs are.
by ako | 2025-11-04 07:32:25+00:00
An LLM by itself is not thinking, just remembering and autocompleting. But if you add a feedback loop where it can use tools, investigate external files or processes, and then autocomplete on the results, you get to see something that is (close to) thinking. I've seen claude code debug things by adding print statements in the source and reasoning on the output, and then determining next steps. This feedback loop is what sets AI tools apart, they can all use the same LLM, but the quality of the feedback loop makes the difference.
by KoolKat23 | 2025-11-04 07:32:33+00:00
Well it depends. It doesn't have arms and legs so can't physically experiment in the real world, a human is currently a proxy for that, we can do it's bidding and feedback results though, so it's not really an issue.

Most of the time that data is already available to it and they merely need to a prove a thereom using existing historic data points and math.

For instance the Black-Scholes-Merton equation which won the Nobel economics prize was derived using preexisting mathematical concepts and mathematical principles. The application and validation relied on existing data.
by brabel | 2025-11-04 07:32:45+00:00
This argument comes up often but can be easily dismissed. Make up a language and explain it to the LLM like you would to a person. Tell it to only use that language now to communicate. Even earlier AI was really good at this. You will probably move the goal posts and say that this is just pattern recognition, but it still fits nicely within your request for something that no one ever came up with.
by roflcopter69 | 2025-11-04 07:33:42+00:00
I know, it's the title of their own post, but making it sound like pixi is only for robotics is underselling pixi quite heavily.

Pixi is basically uv but for the conda ecosystem in the sense that it has all the goodness (fast and reliable dependency solver, smart caching, using hardlinks for environment installs to speed things up and save space) and makes the whole environment/dependency management for conda project so much faster and more robust. For dependencies from PyPI, pixi uses the uv crate under the hood, so it doesn't waste effort on that front and works just as well.

I think many python project will be fine with just using uv but at least for my use case, pixi turned out to be just what I needed, because my software also needs to run on older macOS versions, Intel and Arm Macs, and packages like OpenCV or PyTorch are just not officially built for those anymore, but in the conda ecosystem, there are countless brave souls who build this stuff for macOS 11+ so I can just use that and it's such a relief.

Uv is getting most of the attention right now and I can totally understand why, but if python is your main thing and you want to keep up with what's the best the ecosystem can offer right now, you should at least give pixi a try and evaluate the pros and cons yourself. It's really worth it imo.
by erdlet | 2025-11-04 07:34:36+00:00
This law was introduced to help deal with what is essentially a public health issue.

Any law can be framed as oppression on the basis that it informs people they're not allowed to do something. Speed limits oppress drivers who want to drive over 70 mph, etc.

Also, it was the Supreme Court who decided on the issue of transwomen being legally interpreted as men in the Equality Act, this was independent of the Government.
by Zolomon | 2025-11-04 07:34:39+00:00
This is not true, this change is a recent phenomenon, I believe it came into effect sometime around 2021-2023 (maybe earlier even). I believe it changed when OpenAI showed the value of data.

Before, there was no problem using Instagram or Twitter while not logged in. Now there is a dark pattern that forces you to create an account, or log in.
by k310 | 2025-11-04 07:35:11+00:00
I'm retired from SV tech, and built early computers from S-100 boards and lots and lots of solder (hasn't affected my brain). Like Kevin Kelley, and Ted Nelson "Computer Lib/Dream Machines" and maybe even Jobs and Woz, always felt that computers should liberate people.

I've despised "big tech" even when it wasn't so big, as in a certain creep dumpster-diving to get the source code for BASIC.

I've written down ideas for liberating kinds of tech, but it occurred to me that they often just try to undo the damage that's been done by sociopaths leveraging technology, and some of the worst offenders with a brilliant new business model: Sell ads. Low hanging fruit at the expense of print media.

And I experienced the internet before ads.

> Advertising is a poison that demeans even love – and we're hooked on it: George Monbiot (2011) [0]

Still worth trying. The times demand it.

[0] https://www.theguardian.com/commentisfree/2011/oct/24/advert...
by oarsinsync | 2025-11-04 07:36:38+00:00
> If my boss forces me to review it, then I do so and start quietly applying for new jobs where my job isn't to spend 10x (or 100x) more time reviewing code than my coworkers did "writing" it.

Another equally correct approach (given the circumstances of the organisation) is to get a different AISlopBot to do the review for you, so that you spend as much time reviewing as the person who submitted the PR did coding.
by vasco | 2025-11-04 07:37:22+00:00
Maybe you were just never surrounded by dumb people. The amount of damage they make to their own quality of life is almost unbelievable. I sure as hell think it's the biggest lottery we play with the most impact on the course of our lives. Intelligence and wealth of parents.

What you do with that after is up to you, but those two factors will make for the easiest lives.
by watwut | 2025-11-04 07:37:57+00:00
I would start with assumption that strangling, cutting or beating someone is likely to be illegal. There are not that many countries with bdsm exception to those. And strangling is literally the most dangerous of all those. If you are strangling someome under assumptiom that of course it must be legal, you are likely breaking the law in all kinds of unaware and dangerous ways.

And yes, in domestic violence situation, strangling is pretty consistent predictor of actual murder attempt later on.
by impossiblefork | 2025-11-04 07:38:45+00:00
Things like that do exist though. There's an expensive Renault with motors like this, there's also the MW Motors Luka.

MW Motors eventually made a version where the electric motors were moved from the wheel hubs to a more conventional arrangement, so presumably they felt that it was some sort of problem, but they still make the original version and I've never been in one, so I can't be sure.