MurphyA/hacker-news huggingface dataset:
by dvrp | 2025-12-22 22:06:37+00:00
We're now fact-checking the video to verify how real it is. All we know is that it's part of the Volume 8 of the dataset from the DOJ and what we know for sure is that it was uploaded to justice.gov

EDIT: We think this might be a fake video. There's mentions of a fake video from Google Drive (now deleted) in a PDF hosted at DOJ site: https://www.justice.gov/epstein/files/DataSet%208/EFTA000299...
by mothballed | 2025-12-22 22:07:00+00:00
Gary Indiana had a massive infrastructure for cooling and water diversion for their mega steel industry. Electricity already in place, again for steel industry, and anything it would sink would be a drop in the bucket of the Chicago metropolitan area (so Illinois would eat much of the externalities of whatever hypothetical minor price increase of electricity) grid that it's connected to and likely far less than they were using for their steel jobs.

Probably best to just let it stay an industrial wasteland shithole rather than put datacenters there.
by tylervigen | 2025-12-22 22:07:26+00:00
This reminds me of my grandparents’ old, huge rear projection TV (RPTV). It was 4ft wide, 4ft tall (with the base), 2ft thick, and weighed 200lbs. This was the intermediary between CRTs and flat screens for me.

They had it installed in their basement. However, later they remodeled the basement stairway to add a turn. With the new layout, it would be impossible to bring back up the TV the way it was brought down. There was no other way to access the basement (it only had storm cellar windows), so they left it there when they moved.

I think about the new owners sometimes and wonder what they ended up doing. Perhaps they disassembled it, or maybe it’s still down there collecting dust.
by coryrc | 2025-12-22 22:07:32+00:00
As usual, explain how you're going to power heat pumps in the Northern half of the country during a 3 week bomb cyclone. There are answers and they cost money.

The only answer we're using is to build 1:1 natural gas capability for solar, which is roughly double the cost. That's a solution, but it needs to be accounted for when comparing options.
by vablings | 2025-12-22 22:07:54+00:00
> The per-unit cost of nuclear power plants is extremely high, making it hard to get economies of scale in building more of them.

I disagree. building big infrastructure projects always scales well. As stated by the project managers at Hinkley Point C (the most expensive nuclear reactor ever) they estimate that build times and cost will be significantly reduced for the second reactor due to the knowledge and expertise baked into the workforce. Frances nuclear revolution during the 1972 oil crisis also shows the same thing with construction cost getting lower the more reactors built.

There are other reactor designs that do not use uranium that have been tested and hypothesized.
by sebow | 2025-12-22 22:08:01+00:00
Thank you for the detailed insight. You've touched on an aspect that outsiders (like me) cannot truly grasp but can only guess about: motivation. And it's definitely true, motivation in the private sector is somewhat harder (you've explained it best), or at least motivation compared to the majority of the private companies; but, like you've mentioned, it doesn't seem like it's a problem with the system itself but with the kind of environments that grow in companies. Corporate culture is, more often than not, very toxic, especially when big money is involved (and/or big ideas; the subject of research could be even more important than money in science).

Or maybe it is a problem with the structure that fosters an environment. What comes to my mind is the exceptional case of OpenAI, which started as a nonprofit. Sure, it "ended badly" because of the known drama, but my guess is that besides the money that was poured into it, it thrived because researchers had kind of an "emotional safety net," meaning that they wouldn't be pressured for results as much. Probably the reason some startups perform much better too.

I think career continuity matters, and you don't necessarily get that in the private sector for sure. This discontinuity then leads to practical work discontinuity, which means less work done (which is amplified by the non-decentralized nature of working in private compared to shared science in public, as you've explained).

My bottom line is that the private field could do better, and frankly it's kind of their loss. What I'm curious about is whether a "semi-private" approach is better: a non-profit or some kind of foundation. I guess in practice they're still private, but whether the money part can be "solved" through crowdfunding/some modern methods and whether they're viable long-term remains to be seen. One thing is for sure: a culture appreciative of science will definitely open more doors into novel methods of funding and organizing (maybe in the future these methods could rival the "traditional ways" of public science).
by Moosdijk | 2025-12-22 22:08:17+00:00
Interesting.
Instead of running the model once (flash) or multiple times (thinking/pro) in its entirety, this approach seems to apply the same principle within one run, looping back internally.

Instead of big models that “brute force” the right answer by knowing a lot of possible outcomes, this model seems to come to results with less knowledge but more wisdom.

Kind of like having a database of most possible frames in a video game and blending between them instead of rendering the scene.
by jandrewrogers | 2025-12-22 22:08:36+00:00
This reply doesn't address any core point.

When these wind farms were permitted many years ago, shipborne drones were not part of the threat matrix. It was considered purely hypothetical even a decade ago because it was not an imminent capability for any country even though e.g. the US DoD had studied it. In the last few years shipborne drones have emerged very quickly as a substantial practical threat, largely due to the Russia/Ukraine war. Governments around the world are struggling to adapt to this new reality because none of their naval systems are designed under this assumption.

Whether or not this is convenient for Trump doesn't take away from the reality of the security implications.
by Hansenq | 2025-12-22 22:08:59+00:00
Water allocation in the American West has been a mess ever since the beginning, when Prior Appropriation was decided as the way to claim water rights. Essentially, the first person to put a claim of water into "beneficial use" gets those rights.

This is why you see California with such a large share of the Colorado River's water rights, even though it "touches" the river the least: they were the earliest fast-growing state to "use" that water. And that's why you see so many water-hungry crops being grown in the West--the owners have the rights already, and to them, if they don't use it, they'll lose it.

So any agreement here needs to make a compromise between states, the federal government, prior settled law, and owners with effectively "free" water that don't want it taken away from them.

It's a complicated issue, but one step would be to force private owners of water rights to list their rights on an open market (right now some owners of water rights, like the Imperial Irrigation District can choose to never sell them). At least that way you can start the conversation somewhere.

(In fact, John Wesley Powell, namesake of Lake Powell, argued strongly against "prior appropriation" before the area was even settled, and instead argued against a collective approach to the limited and volatile amount of freshwater. He did not succeed.)

https://en.wikipedia.org/wiki/John_Wesley_Powell#Environment...
by seinecle | 2025-12-22 22:09:10+00:00
Well put. Certainly my case with https://nocodefunctions.com

- traffic is slightly but noticeably decreasing for the last year: https://public.nocodefunctions.com

- it pushes me to improve the design, the overall quality, explore new feature spaces: https://next.nocodefunctions.com

Also, I noticed:

- at first LLMs apply a penalty to development: it requires to explore new toolings for AI assisted coding, then select and get used to one of them, that might well end up being a transient solution. e.g. Cursor, to be replaced soon by Claude Code?

- new uncertainty about which feature to develop: if I can develop it, then anyone else surely can reverse engineer it easily and replicate it? This is quite unnerving.
by foster_nyman | 2025-12-22 22:09:24+00:00
This feels like a learning-theory restatement of the Kernighan quote: the point isn’t “never be clever”, it’s that cleverness is trainable. If you write right at your current ceiling, you reliably create a debugging task that’s a bit above it, and that mismatch becomes the stimulus (and motivation) for skill growth. I think the same lever shows up in writing: drafting is “coding”, editing is “debugging”. If I only write safe/obvious prose, revision stays in the flow zone but I plateau. If I try a structure/argument I can’t quite see the full shape of yet, the rewrite phase hurts, but it’s literally me moving through the next rung. All of which maps pretty cleanly to Vygotsky’s ZPD (the bug report / reader confusion is the scaffold), and it’s also an antidote to Dunning–Kruger: the work keeps falsifying your self-assessment. The “wow, I was wrong” moment is often just evidence your skill bar moved.

Caveat: in collaborative/prod contexts you sometimes trade cleverness for maintainability, but if you always do that, you skip the lever.
by tdfirth | 2025-12-22 22:09:29+00:00
If you do backend web development in 99% of software companies then being very good at whatever your RDBMS is is a superpower.

It's definitely worth learning SQL very well, but you also need to learn the data structures your RDBMS uses, how queries translate into operations on that data, and what those operations look like in a query plan.

You can go surprisingly far with just that knowledge.

A great resource is https://use-the-index-luke.com/
by roadside_picnic | 2025-12-22 22:10:02+00:00
What "actual reasoning" are you referring to? I believe you're making my point for me.

Speculative decoding requires the implementer to understand:

- How the initial prompt is processed by the LLM

- How to retrieve all the probabilities of previously observed tokens in the prompt (this also help people understand things like the probability of the entire prompt itself, the entropy of the prompt etc).

- Details of how the logits generate the distribution of next tokens

- Precise details of the sampling process + the rejection sampling logic for comparing the two models

- How each step of the LLM is run under-the-hood as the response is processed.

Hardly just plumbing, especially since, to my knowledge, there are not a lot of hand-holding tutorials on this topic. You need to really internalize what's going on and how this is going to lead to a 2-5x speed up in inference.

Building all of this yourself gives you a lot of visibility into how the model behaves and how "reasoning" emerges from the sampling process.

edit: Anyone who can perform speculative decoding work also has the ability to inspect the reasoning steps of an LLM and do experiments such as rewinding the thought process of the LLM and substituting a reasoning step to see how it impacts the results. If you're just prompt hacking you're not going to be able to perform these types of experiments to understand exactly how the model is reasoning and what's important to it.
by rayiner | 2025-12-22 22:10:02+00:00
If you look at the Github, there's a design proposal (under docs/design) for that.

It looks like the idea at the present time is to have four modes: value types, affine types, linear types, and rc types. Instead, of borrowing, you have an inout parameter passing convention, like Swift. Struct fields cannot be inout, so you can't store borrowed references on the heap.

I'm very interested in seeing how this works in practice--especially given who is developing Rue. It seems like Rust spends a lot of work enabling the borrow checker to be quite general for C/C++-like usage. E.g. you can store a borrowed reference to a struct on the stack into the heap if you use lifetime annotations to make clear the heap object does not outlive the stack frame. On the other hand it seems like a lot of the pain points with Rust in practice are not the lifetime annotations, but borrowing different parts of the same object, or multiple borrows in functions further down the call stack, etc.
by hombre_fatal | 2025-12-22 22:11:17+00:00
AI tools are shifting the story of indie app creation from needing the skill + time + interest to just needing the time + interest (spending the necessary time workshopping the process with AI).

So the simpler your app is, the less of the moat it has going forward.

Example: It was only a few years ago that I wanted a basic iOS app to remind me to do 100 pushups, 100 situps, etc. every day. I paid $5 for quite a crappy app that got the job done (it was comically slow somehow). I found the developer's twitter and he was one of those "I make money creating and selling 1000 apps" people.

Now making that kind of app is trivial with Claude Code without even launching Xcode. I've build at least five apps so far just for personal use.

So, on the other hand, another definition of "indie software" is on the cusp of explosion.
by bb88 | 2025-12-22 22:11:43+00:00
If you look at water usage in Nevada, 75% of it goes to agriculture [1]. Agriculture provides a lot of jobs and food. Unfortunately the resources are no longer there. You can eliminate landscaping (yards, golf courses, las vegas fountains, etc), but it still won't make a dent in the water use.

It's not just Nevada, but Nevada is the poster child here for everything that's gone wrong with water use.

So something's gotta give. And it turns out that farming in deserts may not have been the best use of the land (or water).

[1] https://extension.unr.edu/publication.aspx?PubID=4764
by theshrike79 | 2025-12-22 22:12:24+00:00
During 2025 I've almost exhausted my personal TODO-list of small applications and created a few extra ones.

This would've never happened without a Claude Pro (+ChatGPT) subscription.

And as I'm not American, none of them are aimed to be subscription based SaaS offerings, they're just simple CLI applications for my personal use. If someone else enjoys them, good for them. =)
by yencabulator | 2025-12-22 22:12:27+00:00
If you have an extra 20 GB of RAM and a recent-enough CPU (no GPU needed), you can run qwen3:30b-a3b locally well enough to analyze documents and have it report back quickly enough to be completely realistic for analytical use. I find the output of Qwen3's 30B model for that sort of task is plenty good enough.
by mythoughtsexact | 2025-12-22 22:12:38+00:00
You're awesome, thank you.

I stopped following this guy back in 2015 when he straight up forked all of my ansible roles and then published everything to Ansible Galaxy before mine were even complete, tested and ready to be published, and only for me to find that the same day they were all forked by him a new Github organization with the name of the org I had used in my roles had been registered and then squatted, it completely turned me off to his methods.
by fasterik | 2025-12-22 22:12:40+00:00
I didn't disagree that there is price parity for the levelized cost. There is still not price parity for levelized full system cost. If we used wind and solar for 95-100% of generation, the price would be much higher.

My point is not that we can or should replace wind and solar with nuclear. It's that it is far cheaper to use a combination of nuclear, wind, and solar than it is to use 100% wind and solar.
by sh3rl0ck | 2025-12-22 22:12:58+00:00
I agree.

There's such an opportunity for people to actually explore ideas whose prototyping cost would have been too high with both time/money to not be worth it earlier.

And even outside that perspective, there's a lot of broken corpo software now. The indie hackers are fighting back. See Helium by imputnet, for example. Ghostty by the revered Mitchell Hashimoto is another example of something I daily and is relatively indie.

Corpo-slop seems to be enshittifying at an exponential rate due to decision paralysis and general management talent decay.
by saxenaabhi | 2025-12-22 22:13:27+00:00
We have a POS system where entire blogic is postgres functions.

There are many others as well. Sure Rails/Laravel/Django people use the ORM supplied by their framework, but many of us feel it's un-necessary and limiting.

Limiting because for example many of them don't support cte queries(rails only added it a couple of years ago). Plus it get weird when sometimes you have to use sql.raw because your ORM can't express what you want.

Also transactions are way faster when done in a SQL function than in code. I have also seen people do silly things like call startTransaction in code and the do a network request resulting in table lock for the duration of that call.

Some people complain that writing postgres functions make testing harder, but with pglite it's a non issue.

As an aside I have seen people in finance/healthcare rely on authorization provided by their db, and just give access to only particular tables/functions to a sql role owned by a specific team.
by mothballed | 2025-12-22 22:14:07+00:00
The Desert Land Act under which a lot of desert land was claimed (and, the only remaining way I know of state land can still privately be claimed) only gave it to you if you established irrigation and agriculture.

The government basically asked for it, and then made it the only way to get much of the land. And now of course, many heads in government now complaining about the evil private land owner who did the thing the government asked for and precondition.
by rx_tx | 2025-12-22 22:14:39+00:00
If you ever are in Paris, I can't recommend the Musee des Arts et Metiers enough.
I believe they have the several reference platinum kilograms that are now out of spec. [1]
they also have the original actual Foucault pendulum that was used to demonstrate Earth's rotation. (and a replica doing a live demo, of course)

They have so many incredible artifacts (for weights and measures but also so much more: engineering, physics, civil engineering, machining,...)

[1]: https://collections.arts-et-metiers.net?id=13404-0001-
by observationist | 2025-12-22 22:14:43+00:00
Fair - it's gotten significantly better over the last 4 months or so, and hallucinations aren't nearly as bad as they once were. When I was using Heavy, it was excellent at ensuring grounding and factual statements, but it's not worth $100 more than ChatGPT Pro in capabilities or utility. In general, it's about the same as ChatGPT Pro - once every so often I'll have to call out the model making something up, but for the most part they're good at using search tools and ensuring claims get grounding and confirmation.

I do expect them to pull ahead, given the resources and the allocation of developers at xAI, so maybe at some point it'll be clearly worth paying $300 a month compared to the prices of other flagships. For now, private hosts and ChatGPT Pro are the best bang for your buck.
by Tostino | 2025-12-22 22:15:04+00:00
There will be an estimated 14 million extra deaths directly attributed to this policy choice: https://www.thelancet.com/journals/lancet/article/PIIS0140-6...

91 million lives were saved over the last two decades. The vast majority of that wasn't "international development" fluff; it was basic survival. We’re talking about stopping tuberculosis, malaria, and starvation.

Framing this as getting rid of unwanted "cultural programs" is a convenient way to ignore the fact that we pulled the plug on the life support system for 30 million children.
by keyle | 2025-12-22 22:15:08+00:00
For me I care about the minutiae's of good software and AI slop produced software just has none of that. It takes experience to produce that and experience to understand how well something is crafted.

Granted it flies over the head of most people. They can't discern a well written website to a 15MB webpage with an 8K thumbnail.

Same applies to software. Margins, bevels, grouping, spacing, primary and secondary actions. Some see the difference. Some don't. You can't fake understanding of what you can't perceive exists.

You can't know what you don't know.
by gioele | 2025-12-22 22:15:36+00:00
> The whole patch quilting thing is awful. Just keep the patches as commits.

I'd say that `quilt` the utility is pretty much abandoned at this point. The name `quilt` remains in the format name, but otherwise is not relevant.

Nowadays people that maintain patches do it via `gbp-pq` (the "patch queue" subcommand of the badly named `git-buildpackage` software). `gbp-pq switch` reads the patches stored in `debian/patches/`, creates an ephemeral branch on top of the HEAD, and replays them there. Any change done to this branch (new commits, removed comments, amended commits) are transformed by `gbp-pq export` into a valid set of patches that replaces `debian/patches/`.

This mechanism introduces two extra commands (one to "enter" and one to "exit" the patch-applied view) but it allows Debian to easily maintain a mergeable Git repo with floating patches on top of the upstream sources. That's impossible to do with plain Git and needs extra tools or special workflows even outside of Debian.
by LexiMax | 2025-12-22 22:15:44+00:00
Whitespace cleanliness is only part of the problem. The much bigger issue is the fact that the ending of a block is invisible. This leads to several problems:

1. It becomes much more difficult to tell beginners where the end of a block is, because the ending of the block isn't something you can describe verbally. You have to point to it instead.

2. Students who might be prone to using the wrong number of "}" or "end" tokens to close a block will instead un-indent the wrong number of times. It doesn't prevent the kinds of mistakes that mismatched parens tend to cause.

3. When closing a block, the thing you're trying to align a prior block with might not be on screen any longer. I don't know why, but I've seen more off-by-one spacing gaffes after the close of a nested block than I ever expected to see.

That said, I don't doubt that Python arrived at the choice of whitespace blocks empirically. However, I highly suspect that the majority of the users learning how to program in the late 80's and early 90's were familiar with monospaced text, which was ever-present in most productivity applications of the day, and thus easier for them to reason about.

And to be clear, I don't really care that much about Python's whitespace blocks. I don't like them, but I'm at the age where I feel like quibbling over minor syntax gaffes is beneath me, and Python is my top "swiss army knife" language when I need a job done quickly. My only point is that I feel like whitespace blocks are a relic of the time when they were developed, and I don't think they are as beginner friendly as advertised.

EDIT: After stepping away from the post, I realized that in my perfect world, a beginner language would look a lot more like Lua than Python. Then I remembered how popular Roblox is, and how popular Garry's Mod was before that. Given the success of those platforms, there might be something to it.
by theshrike79 | 2025-12-22 22:15:48+00:00
This is just the Blockchain and Web3 (NTF) crazes all over again on the surface.

Every single grifter from those times is slapping AI on everything that moves or doesn't move.

But the difference is that the blockchain was (and still is) a solution looking for a problem. LLMs can solve actual problems today.