MurphyA/hacker-news huggingface dataset:
by speak_plainly | 2026-01-30 15:34:10+00:00
To use an analogy with some metaphors: The sensor is like a sealed room with a screen window that only lets in oxygen. To get a reading, every molecule that enters is smashed to create a tiny spark of electricity. However, because the oxygen is destroyed to create that spark, it creates a suction effect, causing more oxygen to rush into the room to fill the void. This creates a major flaw: if gunk builds up on the screen, it slows down the flow of incoming oxygen. The sensor, which only counts sparks per second, is tricked into thinking the oxygen level outside is low, when really the window is just dirty.

By adding a third electrode to replace the oxygen every time one is smashed, you maintain a perfect balance and eliminate that suction. Because the room stays full, the sensor no longer relies on the speed of the oxygen rushing in; it simply measures the steady state of the oxygen already there. Even if gunk gets on the window, the sensor won't be starved of a reading. It might take a few extra seconds for the levels to settle, but the final number will be 100% accurate because the sensor is no longer emptying its own room to get a count.
by enlyth | 2026-01-30 15:34:31+00:00
A software engineer with an LLM is still infinitely more powerful than a commoner with an LLM. The engineer can debug, guide, change approaches, and give very specific instructions if they know what needs to be done.

The commoner can only hammer the prompt repeatedly with "this doesn't work can you fix it".

So yes, our jobs are changing rapidly, but this doesn't strike me as being obsolete any time soon.
by thelastgallon | 2026-01-30 15:34:37+00:00
People buy new cars (~10m/year in US) and when they are at that decision point, follow this algorithm.

1) Is there any way you can walk instead?

2) Can you bike?

3) Can you use an e-bike?

4) Can you use public transportation?

5) Can you move to a place where 1-4 are doable?

6) If none of the 4 above work, are you a 2 car family (most are), then one of the cars can be EV. While you have a gas car for longer trips, most likely a minivan.

7) Can you buy a used EV? (which is already manufactured!)

8) Can you buy a used plug-in hybrid? A plug-in hybrid can be 99% electric miles, most trips are short.

9) Can you buy a new EV?

10) Can you buy a new plug-in hybrid?

11) Can you buy a used gas car? A 2023 manufactured used gas car is identical to 2024, the delta of new features is negligible (maybe new colors?).
by verdverm | 2026-01-30 15:34:37+00:00
1. There is nothing novel in my text formats, I'm just deciding what content and what files

2. I've actually done these things, seen the difference, and share it with others

Yes there are a lot of unknowns and a lot of people speaking from ignorance, but it is a mistake, perhaps even bigotry by definition, to make such blanket statements and judgemental about people
by crazygringo | 2026-01-30 15:34:59+00:00
> Everything I've said is backed up by sources.

I've already pointed out a bunch of claims you made that are directly contradicted by sources.

> They updated it prior to publication in July 2023.

That Lowry Institute link is unclear. It says it "revised down", but the first link says the original report was leaked, and many other sources say it was leaked as well. I can't find anything saying it was ever officially released. If it was officially published as you claim, then please link to it.

> and an entire new census in 2024, all of which are nowhere near the 17 million estimate.

Right, the whole point is that the census methodology is potentially massively undercounting the rural population, for the entirely plausible reasons given. Flawed results that are more recent aren't less flawed just because they're more recent.

> How is every other independent estimate disagreeing with the 17 million figure not a clear contradiction of the article's implicit claim that the 17 million estimate is more accurate?

Because they're all implicitly based on the official census numbers and they can't even read the report, since it was buried. If they can't even read it because the report was suppressed, then they're going to have a hard time incorporating its estimates, aren't they?

> I'm going to go with all of them over a random article which makes incredible claims with no evidence.

The article is repeating the same claims based on this academic study/report that have been reported extensively elsewhere. You can trust whichever you want, but the claim that PNG is faking their population data seems entirely plausible from current reporting. The author isn't making it up out of thin air. It's been extensively reported. It's in Wikipedia. They don't seem to be "incredible claims", just repeating mostly well-known information.
by derbOac | 2026-01-30 15:35:01+00:00
It's not a Motte and Bailey fallacy at all; it's a statement of a belief about what should be expected if something is to be allowed as a matter of public health and safety implications.

They're saying that Tesla should be held to a very high standard of transparency if they are to be trusted. I can't speak to OP, but I'd argue this should apply to any company with aspirations toward autonomous driving vehicles.

The title might be misleading if you don't read the article, but the article itself at some level is about how Tesla is not being as transparent as other companies. The "shaky evidence" is due to Tesla's own lack of transparency, which is the point of stating that the burden of proof should be on Tesla. The article is about how, even with lack of transparency, the data doesn't look good, raising the question of what else they might not be disclosing.

From the article: "Perhaps more troubling than the crash rate is Tesla’s complete lack of transparency about what happened... If Tesla wants to be taken seriously as a robotaxi operator, it needs to do two things: dramatically improve its safety record, and start being honest about what’s happening..."

I'd argue the central thesis of the article isn't one of statistical estimation; it's a statement about evidentiary burden.

You don't have to agree with the position that Tesla should be held a high transparency standard. But the article is taking the position that you should, and that if you do agree with that position, that you might say that even by Tesla's unacceptable standards they are failing. They're essentially (if implicitly) challenging Tesla to provide more data to refute the conclusions, saying "prove us wrong", knowing that if they do, then at least Tesla would be improving transparency.
Show HN: SemaMesh: eBPF-based firewall for AI Agents(blocks destructive prompts)
by vikram_yerneni | 2026-01-30 15:35:04+00:00
Hello HN,

We built an open-source, sidecarless service mesh to govern autonomous AI agents on Kubernetes.

The Problem: Standard meshes (Istio/Cilium) operate at L4/L7. They see connections, but they don't see intent. If an autonomous agent gets stuck in a loop and burns $1,000 in OpenAI tokens, or decides to run DROP TABLE to "optimize storage," a standard mesh sees a valid HTTP 200 OK.

The Solution:
SemaMesh uses eBPF (sock_ops) to transparently intercept outbound traffic from AI pods and route it through a local semantic proxy (Go) that enforces "Layer 8" policies.

Features:
. eBPF-based: No sidecar injection required.
. Semantic Blocking: Parses JSON prompts to block high-risk intent (e.g., "delete database") before it leaves the node.
. Stateful Pause: Integrates with CRIU to freeze/checkpoint a rogue agent's process state for forensics instead of just killing the pod.
. Token Quotas: Rate limit by $$ cost, not just requests per second.

Tech Stack:
. Datapath: C (eBPF)
. Proxy/Control Plane: Go
. Orchestration: Kubernetes (DaemonSet/Operator)

We just released v0.4.0 with a "Smoke Test" script that spins up a local Kind cluster and simulates a "Rogue Agent" attack so you can see the blocking logic in action.

Repo: https://github.com/semamesh/SemaMesh

Would love feedback on the eBPF interception logic or the CRIU integration approach.
by phailhaus | 2026-01-30 15:35:06+00:00
Until we have world models, that is exactly what they are. They literally only understand text, and what text is likely given previous text. They are very good at this, because we've given it a metric ton of training data. Everything is "what does a response to this look like?"

This limitation is exactly why "reasoning models" work so well: if the "thinking" step is not persisted to text, it does not exist, and the LLM cannot act on it.
by Joel_Mckay | 2026-01-30 15:35:07+00:00
Blender still needs about 130 hours of course projects to become useful, but is a lot better in >5 due to better color handling and geometry nodes.

Maya is frozen in time, and that is not necessarily a bad thing...

Great video on getting 3D render preview speeds up:

https://www.youtube.com/watch?v=a0GW8Na5CIE

Geometry nodes tutorials:

https://www.youtube.com/@TheDucky3D/videos

Blender still needs plugins to be functional for content:

https://tinynocky.gumroad.com/l/tinyeye

https://sanctus.gumroad.com/l/SLibrary

https://flipfluids.gumroad.com/l/flipfluids

https://artell.gumroad.com/l/auto-rig-pro

https://bartoszstyperek.gumroad.com/l/ahwvli

https://polyhaven.com/plugins/blender

https://extensions.blender.org/add-ons/mpfb/

Recommended training (Some artists like it, and some don't ymmv):

1. (A) Complete Blender Creator: Learn 3D Modelling for Beginners

https://www.udemy.com/course/blendertutorial/

* Basics of low-poly design in blender

2. (B+) Blender Animation & Rigging: Bring Your Creations To Life

https://www.udemy.com/course/blender-animation-rigging/

* Some more practice rigging

* Export to game engine teaser

3. (B) The Ultimate Blender 3D Sculpting Course

https://www.udemy.com/course/blender-3d-sculpting-course/

* Sculpting, Retopology, and VDM brushes

* a few outdated examples, and annoying instruction style

* basic anatomy

* covers several workflows

* Instructor is inexperienced

4. (A+) The Ultimate Blender 3D Simulations, Physics & Particles

https://www.udemy.com/course/blender-simulations-physics-par...

* Shader/Texture basics

* Geometry node basics

* Boid sprites

* Hair and physics simulation

* Camera FX, and post-render filters

* Focused on Blender v4.3

* Instructions on how to export your assets to Unity 3D and Unreal game engines
by palmotea | 2026-01-30 15:35:12+00:00
> It would be faster to leave the batteries in my tools, but over 40 years of sacrificing devices to alkaline cell leakage, it's my habit not to. So far I've never had leakage problems with the eneloops, but old habits die hard.

I've gotten burned by that too, but I just try to remember to take out the batteries before I put something into storage.

BTW, I think the old-style "heavy duty" batteries and lithium AAs don't have a leakage problem. Though lithium AAs are now ridiculously expensive. I think they went from $1 a cell to $2 in cell in a Sam's Club 18-cell bulk back over a couple of years.
by fc417fc802 | 2026-01-30 15:35:23+00:00
That's a fair point, but I'll note that the one time I hit an inanimate object with my car I wasn't about to needlessly involve anyone. Fixed the damage to the vehicle myself and got on with life.

So I think it's reasonable to wonder about the accuracy of estimates for humans. We (ie society) could really use a rigorous dataset for this.
by brk | 2026-01-30 15:35:43+00:00
You definitely don't have to be god tier anything, you just need to know at least a little more than the companies you are consulting for.

This kind of work has been my primary income for the last 4 years or so. Nowhere near on the same level as Feynman, but I know enough about enough other things that I get a lot of reputational referrals.
by close04 | 2026-01-30 15:36:18+00:00
> a timeline slipping

You're generous with your words to the point they sound like apologism. Musk has been promising fully autonomous driving "within 1-3 years" since 2013. And he's been charging customers money for that promise for just as long. Timelines keep slipping for more than half of the company's existence now, that's not a slipup anymore.

Tesla has never been transparent with the data on which they base their claims of safety and performance of the system. They tout some nice looking numbers but when anyone like the NHTSA requests the real data they refuse to provide it.

When NHTSA shows you numbers, they're lying. If I tell you I have evidence Tesla is lying you'll tell me to show it or STFU. When Tesla does the same after so many people died, you go all soft and claim everyone else is lying. That's very one sided behavior, more about feelings than facts.

> But this is more your feelings than actually factual.

The article is about "NHTSA crash data, combined with Tesla’s new disclosure of robotaxi mileage". Sounds factual enough. If Tesla is sitting on a trove of data that proves otherwise but refuse to publish it that's on them. If anyone is about the feels and not the facts here, it's you.
by bluGill | 2026-01-30 15:36:36+00:00
That was 10-15 years ago, but back then Musk appeared different, and Telsa was new. Today you can buy a Tesla, they are no longer the status symbol they once were. A 15 year old Mercedes is a status symbol in the US, a 15 year old Tesla is not, Tesla didn't capture the status symbol market (which might have been a good decision - what wasn't a good decision was for the CEO to go public about political views that are lot of his potential base to not support)
by heliumtera | 2026-01-30 15:36:44+00:00
Please no. Talk is cheap.

I hate this trend of using adjectives to describe systems.

Fast
Secure
Sandboxed
Minimal
Reliable
Robust
Production grade
AI ready
Let's you _____
Enables you to _____

But somewhat I agree, code is essentially free, you can shit out infinite amounts of code. Unless it's good, then show the code instead.
If your code is shit, show the program.
If your program is shit, your code is worse, but you still pursing an interesting idea (in your eyes), show the prompt instead of the slop generated. Or even better communicate an elaborate version of the prompt.

>One can no longer know whether such a repository was “vibe”

This is absurd. Simply false, people can spot INSTANTLY when the code is good, see:
https://news.ycombinator.com/item?id=46753708
by vel0city | 2026-01-30 15:36:47+00:00
But that's the thing, in many ways it is a pretty low number. Its less than the number of miles a single average US commuter will have driven in their working years. So in some ways its like trying to draw lifetime crash statistics but only looking at a single person in your study.

Its also kind of telling that despite supposedly having this tech ready to go for years they've only bothered rolling out a few cars which are still supervised. If this tech was really ready for prime time wouldn't they have driven more than 500,000mi in six months? If they were really confident in the safety of their systems, wouldn't they have expanded this greatly?

I mean, FFS, they don't even trust their own cars to be unsupervised in the Las Vegas Loop. An enclosed, well-lit, single-lane, private access loop and they can't even automate that reliably enough.

Waymo is already doing over 250,000 weekly trips.[0] The trips average ~4mi each. With those numbers, Waymo is doing 1 million miles a week. Every week, Waymo is doing twice as many miles unsupervised than Tesla's robotaxi has done supervised in six months.

[0] https://waymo.com/sustainability/
by paxprose | 2026-01-30 15:36:50+00:00
Seriously what is up with all the Electrical n apologists?
Dude's a nazi. Weaseled his way into everything digitally related to the American government and should be treated like foreign intelligence agent. He has oversold and under-delivered everything he has bought from other people to claim for himself.
Weird he's got so many dickriders on HN.
by verdverm | 2026-01-30 15:37:06+00:00
I am not aiming for something as e2e as you, because it has unsolved problems and I want to build an app with private data features today

For what I'm doing, everything should carry over because the permission system doesn't care what data it is gating

The hard problem I'm working on now is content moving or gardening in the face of at-uri. Users want to be able to drag-n-drop things, i.e. move a doc from one folder to another to share with a lawyer (Google docs inspired)

Have you seen peergos? It's spiritually closer to what you are after, iiuyc
by Waterluvian | 2026-01-30 15:37:56+00:00
I think it's a bit like the Dunning-Kruger effect. You need to know what you're even asking for and how to ask for it. And you need to know how to evaluate if you've got it.

This actually reminds me so strongly of the Pakleds from Star Trek TNG. They knew they wanted to be strong and fast, but the best they could do is say, "make us strong." They had no ability to evaluate that their AI (sorry, Geordi) was giving them something that looked strong, but simply wasn't.
by hedora | 2026-01-30 15:37:59+00:00
The article lists the crashes right at the top. One of 9 involved hitting a fixed object. The rest involved collisions with people, cars, animals, or injuries.

So, let's exclude hitting fixed objects as you suggest (though the incident we'd be excluding might have been anything from a totaled car and huge fire to zero damage), and also assume that humans fail to report injury / serious property damage accidents more often than not (as the article assumes).

That gets the crash rate down from an unbiased 9x to a lowball 2.66x higher than human drivers. That's with human monitors supervising the cars.

2.66x is still so poor they should be pulled of the streets IMO.
by adastra22 | 2026-01-30 15:38:10+00:00
No there is a logical errror in there. You are implicitly asserting that the trained thing is an imitation, whereas it is only the output that is being imitated.

A flip way of saying it is that we are evolving a process that exhibits the signs of what we call thinking. Why should we not say it is actually thinking?

How certain are you that in your brain there isn’t a process very similar?
by quadrifoliate | 2026-01-30 15:38:19+00:00
I think you are hyper-focusing on the headline, which is just a joke. The underlying article does not indicate to me that the author is ignorant of code, and if you care to look, they seem to have a substantial body of public open source contributions that proves this quite conclusively.

The underlying point is just that while it was very cognitively expensive to back up a good design with good code back in 2000, it's much cheaper now. And therefore, making sure the design is good is the more important part. That's it really.
by Wowfunhappy | 2026-01-30 15:38:37+00:00
I agree, it must not be literally infinite, I shouldn’t have said that. But it may be effectively infinite. My strong suspicion is that most of us are nowhere close to whatever the limit is.

Think about how we talk about exercise. Yes, there probably is a theoretical limit to how fast any human could run, and maybe Olympic athletes are close to that, but most of us aren’t. Also, if you want your arms to get stronger, it isn’t bad to also exercise your legs; your leg muscles don’t somehow pull strength away from your arm muscles.
by dguest | 2026-01-30 15:38:38+00:00
I think what you are talking about is called "tragedy of the anticommons" [1].

Who gets to decide if an airport or data center gets built is a complicated question. But there are other options to keeping one party in the dark via NDAs. On one extreme we have eminent domain, on the other there's just buying out the local community transparently.

[1]: https://en.wikipedia.org/wiki/Tragedy_of_the_anticommons
by duped | 2026-01-30 15:38:47+00:00
> Whereas everyone here seems to assume it's to avoid NIMBY

Literally every data center project that gets announced near me gets protested at council meetings, petitioned, and multiple series of reddit/bluesky posts about the project.

It's hard to put into words for HN how deeply locals resent tech companies and AI. You could call it NIMBY, but the hatred is deeper than that.

The sentiment is "you have enough money, go away. Your business is fundamentally bad."
by everdrive | 2026-01-30 15:38:49+00:00
This is a weird quirk that I observe in all sorts of contexts. "No one's talking about [thing that is frequently discussed]!" or, "There's never been [an actor in this identity category] in major movie role before!" (except there has plenty of times) or sometimes "You can't even say Christmas anymore!" (except they just did) The somewhat inaccurate use of hyperbolic language does not mean that there is _nothing_ to the particular statement or issue. Only that the hyperbole is just that; an exaggeration of a potentially real and valid issue. The hyperbole is not very helpful, but neither is a total refutation of the issue based on the usage of hyperbole.
by palmotea | 2026-01-30 15:39:16+00:00
> including the part where alcohol isn't considered to be a drug for some strange reason.

It's not a strange reason. IIRC, most cultures have a culturally understood and tolerated intoxicant. In our culture, that's alcohol.

Human culture is not some strange robotic thing, where the expectation is some kind hyper consistency in whatever narrow slice you look at.
by SoftTalker | 2026-01-30 15:39:20+00:00
Do you remember EVs before Tesla? They were glorified golf carts using lead-acid batteries. The performance and range were awful. The Roadster and the Model S changed all that. I'm not saying I remember this perfectly but as I recall, Tesla's original objective was to show that an EV could be a real car, look attractive (or at least normal), and to create demand for EVs that would force all manufacturers to start making them. The ultimate value in Tesla was supposed to be batteries, which all cars would eventually need.
by raincole | 2026-01-30 15:39:50+00:00
> I know a lot of counter arguments are a form of, “but AI is automating that second class of job!”

Uh, it's not the issue. The issue is that there isn't that much demand for the second class of job. At least not yet. The first class of job is what feeds billions of families.

Yeah, I'm aware of the lump of labour fallacy.
by zabzonk | 2026-01-30 15:40:08+00:00
I think I have only one device that uses AA - my central heating's radio thermostat. This thing has caused me untold hassle, which is only partially down to the batteries, but still...

Totally OT, but does anyone have a good link on how the thermostat gets paired with the boiler? I'm thinking of getting replaced and would like to talk to the gas fitter from a vaguely informed point of view.
by derbOac | 2026-01-30 15:40:40+00:00
Maybe? For years the highest selling EV was the Leaf.

I agree Tesla kind of increased the desirability of EVs at least in the US, but I'm not convinced it wouldn't have happened anyway.

It's a hard question to answer, because you're talking about a counterfactual.

I feel like there's probably some broader type of cognitive bias at play (where we assume something common wouldn't have been common otherwise, because it is common) but I don't know what the term for it might be.
by calibas | 2026-01-30 15:40:48+00:00
So use Rust instead, Godot supports bindings via FFI: https://godot-rust.github.io/

I wont claim it works flawlessly, but you don't have to use GDScript or C# to program Godot.

You can also use C++, Go, Java, Typescript, Zig, Scala, Kotlin and Swift: https://github.com/Godot-Languages-Support/godot-lang-suppor...
by sharifhsn | 2026-01-30 15:41:21+00:00
Because those criticisms misses the forest for the trees. You might as well complain about the pollution caused by the Industrial Revolution. AI doesn’t use nearly as much as water as even a small amount of beef production. And we have cheap ways of producing electricity, we just need to overhaul our infrastructure and regulations.

The more interesting questions are about psychology, productivity, intelligence, AGI risk, etc. Resource constraints can be solved, but we’re wrestling with societal constraints. Industrialization created modernism, we could see a similar movement in reaction to AI.