MurphyA/hacker-news huggingface dataset:
by intended | 2025-09-06 13:50:31+00:00
> a generated factual error cannot be grounded in factually correct training data.

This is only true given a corpus of data large enough, and enough memory to capture as many unique dimensions as required no?

> However, a non-hallucinating model could be easily created, using a question-answer database and a calculator, which answers a fixed set of questions such as “What is the chemical symbol for gold?” and well-formed mathematical calculations such as “3 + 8”, and otherwise outputs IDK.

This is… saying that if you constrain the prompts and the training data, you will always get a response which is either from the training data, or IDK.

Which seems to be a strong claim, at least in my ignorant eyes.?

This veers into spherical cow territory, since you wouldn’t have the typical language skills we associate with an LLM, because you would have to constrain the domain, so that it’s unable to generate anything else. However many domains are not consistent and at their boundaries, would generate special cases. So in this case, being able to say IDK, would only be possible for a class of questions the model is able to gauge as outside its distribution.

Edit: I guess that is what they are working to show? That with any given model, it will hallucinate, and these are the bounds?
by jraph | 2025-09-06 13:51:15+00:00
> we all believed GitHub would eventually turn into a open platform made by and for FOSS

I really don't remember it like this at all. I do remember looking for actually open source forges and choosing Gitorious, which was then bought and shutdown by GitLab (and projects were offered to be seamlessly migrated, which worked well, and somehow we ended up being hosted on an open core platform, but that's another story).

GitHub always looked like the closed platform the whole open source world somehow elected to trust for their code hosting despite being proprietary, and then there was this FOMO where if you weren't on GitHub, your open source software would not find contributors, which still seems to be going strong btw.

I understand their was hope that GitHub would be open sourced, but I don't think there was any reason to believe it would happen.
by chubot | 2025-09-06 13:51:35+00:00
They probably get orders from all the way up the food chain to keep the show going.

Honestly I think the same thing happened with self-driving cars ~10 years ago.

Larry Page and Google's "submarine" marketing convinced investors and CEOs of automakers and tech companies [1] that they were going to become obsolete, and that Google would be taking all that profit.

In 2016, GM acquired Cruise for $1 billion or so. It seems like the whole thing was cancelled in 2023, written off, and the CEO was let go

How much profit is Waymo making now? I'm pretty sure it's $0. And they've probably gone through hundreds of billions in funding

How's Tesla Autopilot doing? Larry also "negatively inspired" Elon to start OpenAI with other people

I think if investors/CEOs/automakers had known how it was going to turn out, and how much money they were going to lose 10 years later, they might not have jumped on the FOMO train

But it turns out that AI is a plausible "magic box" that you extrapolate all sorts of economic consequences from

(on the other hand, hype cycles aren't necessarily bad; they're probably necessary to get things done. But I also think this one is masking the fact that software is getting worse and more user hostile at the same time. Probably one of the best ways to increase AI adoption is to make the underlying software more user hostile.)

[1] I think even Apple did some kind of self-driving car thing at one point.
by rthnbgrredf | 2025-09-06 13:51:53+00:00
I think it is all well and good, but the most affordable option is probably still to buy a used MacBook with 16/32 or 64 GB (depending on the budget) unified memory and install Asahi Linux for tinkering.

Graphics cards with decent amount of memory are still massively overpriced (even used), big, noisy and draw a lot of energy.
by NegativeK | 2025-09-06 13:51:55+00:00
I have a 300 mile range EV, and some of my friends also downplay charging on road trips. It seems to be a common narrative. I find it patently false. When I drove long distances in an gas car, I didn't take breaks to stretch my legs. I want to get to my destination earlier and have the driving be done.

I find EV charging on road trips to be annoying, and I can't wait until technology improves to the point where I don't have to worry about missing a charging station and being hosed and I don't have to worry about adding an hour to an hour and a half onto a road trip.

I think that gas vehicles are irresponsible for most uses and the charging at home makes having an EV great, but gas vehicles are better at road trips if only for the fact that those of us who don't want to take longer don't have to.
by hedora | 2025-09-06 13:52:23+00:00
Debian has been like this in practice for at least 25 years (when I first switched to it).

The builds weren’t reproducible back then, but never mattered in practice for me personally. Now, the vast majority of the packages have reproducible builds, which is good enough for me. (Though these days I’m using devuan because I’ve never seen a stable systemd desktop/laptop that uses .debs)
by eldaisfish | 2025-09-06 13:52:32+00:00
i'm always surprised how people here downvote correct information. This is 100% correct because heat in electrical wiring is a function of power (current) and time. The vast majority of electrical devices in a typical home use under 80% of their rated power. The few that do use their full power, like a resistive heater, often do not run continuously.

In contrast, it is completely normal to charge an EV at a socket's maximum power for over ten hours straight. This time component is why charging EVs from a regular AC outlet can be a fire risk.
by techpineapple | 2025-09-06 13:52:55+00:00
A, singular? Which specific point of view is it weaponized for that it’s trying to hide?

Maybe you’re not skeptical enough.

Me a Wikipedia editor?! blushes no? These days I just let ChatGPT tell me what to think, it’s more objective and rational since it’s just the thoughts of a computer and not messy human emotions.
by ModernMech | 2025-09-06 13:54:47+00:00
> Vision systems were improving a lot back then so the idea you could have a FSD on vision alone was plausible.

This was only plausible to people who had no experience in robotics, autonomy, and vision systems.

Everyone knew LIDAR was the enabling technology thanks to the 2007 DARPA Urban challenge.

But the ignoramus Elon Musk decided he knew better and spent the last decade+ trashing the robotics industry. He set us back as far as safety protocols in research and development, caused the first death due to robotic cars, deployed them on public roads without the consent of the public by hoisting around his massive wealth, lied consistently for a DECADE about the capabilities of these machines, defrauded customers and shareholders while becoming richer and richer, all to finally admit defeat while he still maintains the growth story of for Tesla's future remains in robotics. The nerve of this fucking guy.
by akerl_ | 2025-09-06 13:54:53+00:00
That generally suggests they’re not pointing at the resolver you have set to handle that domain. Otherwise your apple devices can’t tell a valid TLD from an invalid one: they just launch the DNS lookup and let the server tell them.

The exception to this is .local, which you shouldn’t use for internal systems because it will confuse the heck out of them in weird ways, because .local is by RFC not meant to be used in that way.
by ben_w | 2025-09-06 13:55:31+00:00
Just remember to account for blue-shifted CMB.

I'm not sure if the CMB itself will decay fast enough with the expansion of the universe to avoid 1g eventually getting you hull eroded by positron-electron pair production from photons blueshifted above 1022 keV, but that's in the set of things you need to think about.
by bookofjoe | 2025-09-06 13:55:37+00:00
Apple car project

https://en.wikipedia.org/wiki/Apple_car_project

>From 2014 until 2024, Apple undertook a research and development effort to develop an electric and self-driving car,[1] codenamed "Project Titan".[2][3] Apple never openly discussed any of its automotive research,[4] but around 5,000 employees were reported to be working on the project as of 2018.[5] In May 2018, Apple reportedly partnered with Volkswagen to produce an autonomous employee shuttle van based on the T6 Transporter commercial vehicle platform.[6] In August 2018, the BBC reported that Apple had 66 road-registered driverless cars, with 111 drivers registered to operate those cars.[7] In 2020, it was believed that Apple was still working on self-driving related hardware, software and service as a potential product, instead of actual Apple-branded cars.[8] In December 2020, Reuters reported that Apple was planning on a possible launch date of 2024,[9] but analyst Ming-Chi Kuo claimed it would not be launched before 2025 and might not be launched until 2028 or later.[10]

In February 2024, Apple executives canceled their plans to release the autonomous electric vehicle, instead shifting resources on the project to the company's generative artificial intelligence efforts.[11][12] The project had reportedly cost the company over $1 billion per year, with other parts of Apple collaborating and costing hundreds of millions of dollars in additional spend. Additionally, over 600 employees were laid off due to the cancellation of the project.[13]
by DennisP | 2025-09-06 13:55:55+00:00
You might not have the classical guardrails, but you are providing the neural net with a lot more information. Even humans are starting to find it useful to get inputs from other sensor types in their cars.

I agree that Tesla may have made the right hardware decision when they started with this. It was probably a bad idea to lock themselves into that path by over-promising.
by mehdibl | 2025-09-06 13:55:56+00:00
The most important you need always to do:

1. Plan, review the plan.

2. Review the code during changes before even it finish and fix ASAP you see drift.

3. Then again review

4. Add tests & use all quality tools don't rely 100% on LLM.

5. Don't trust LLM reviews for own produced code as it's very biased.

This is basic steps that you do as you like.

Avoid FULL AUTOMATED AGENT pipeline where you review the code only at the end unless it's very small task.
by troupo | 2025-09-06 13:56:55+00:00
> Uber drivers should pay taxes and Uber itself pays taxes - or at least should.

Yup. The drivers should have to pay everything because despite working for Uber they are "free contractors"

> And the drivers have the free will to choose to drive for Uber

Ah yes, I forgot that's exactly how price dumping works: there are multiple companies to chose from and all of them offer competitive wages.

I mean, it's not ancient history. For half of Uber's existence the ongoing story was: drivers have to drive almost 24 hours a day to make living wage with Uber randomly stealing their wages.

This only somewhat changed once governments stepped in and forced Uber to change some of its practices.
by jrockway | 2025-09-06 13:56:57+00:00
I'm most surprised that they have this whole system for how drive-thru interactions should go. Positive tone. Saying "you rule" like their exceedingly-irritating television commercials. Like... what if you don't? "If you don't follow the four Sales Best Practices, you're gonna be flippin' burgers for a living. Oh. Well. Oh." They're getting paid $6 an hour. The microphone/speaker system can't reproduce audio to an extent where a customer could ever be sure if you said "you rule" or that your tone is positive. They are thrilled if at least a few items they ordered are in the bag they collect. Why write software to micromanage minimum wage employees?
by JKFSOM | 2025-09-06 13:57:33+00:00
The BBC News robots.txt file includes an interesting selection of disallowed pages:

- "Jailed refugee wins right to stay" (http://news.bbc.co.uk/1/hi/england/1678616.stm) - "Teacher's HIV sack claim rejected" (http://news.bbc.co.uk/1/hi/england/beds/bucks/herts/3663494....) - "Should the UK vote on the EU constitution?" subpage (http://news.bbc.co.uk/1/shared/spl/hi/pop_ups/05/uk_should_t...) - Retail students cash in their talent (http://news.bbc.co.uk/1/hi/education/3826037.stm)
by jsnell | 2025-09-06 13:57:48+00:00
> Protobuf's original sin was failing to distinguish zero/false from undefined/unset/nil.

It's only proto3 that doesn't distinguish between zero and unset by default. Both the earlier and later versions support it.

Proto3 was a giant pile of poop in most respects, including removing support for field presence. They eventually put it back in as a per-field opt-in property, but by then the damage was done.

A huge unforced mistake, but I don't think a change made after the library had existed for 15 years and reverted qualifies as an "original sin".
by marginalia_nu | 2025-09-06 13:58:01+00:00
KPIs are likely the missing part of the puzzle. CEO wants AI engagement to go up, organization makes AI engagement go up.

If users don't want to engage with new AI features, the new AI features become unavoidable so that engagement goes up despite user preferences.

KPIs are a fantastic way for an organization to lose any touch with reality and can drive some truly bizarre decision-making.
by chimeracoder | 2025-09-06 13:59:18+00:00
> Considering that sunscreen in general is pretty garbage at blocking UVA, it isn't nearly as effective as traditional methods like a hat and a shirt.

While the US has no regulations around UVA protection, that's not true worldwide.

Europe and Australia both regulate the use of the term "broad spectrum". In Europe, that means the UVA protection needs to be at least 1/3 of the UVB protection to be able to use the term. I believe Australia is even stricter - all sunscreen is expected to have a baseline level of UVA protection.

Japan has PA ratings that go all the way up to PA++++ to specify the exact level of UVA protection.

1/3 the level of protection might sound like a significant difference, but it's not, especially since UVA is far less damaging than UVB is.
by ryanchants | 2025-09-06 14:00:16+00:00
I'm currently working through Mathematics for Machine Learning and Data Science Specialization from Deeplearning.AI. It's been the best into to Linear Algebra I've found. It's worth the $50 a month just for the quizzes, labs, etc. I'm simultaneously working through the book Math and Architectures of Deep Learning, which is helping re-inforce and flesh out the ideas from the course.

[0] https://www.coursera.org/specializations/mathematics-for-mac... [1] https://www.manning.com/books/math-and-architectures-of-deep...
by chamomeal | 2025-09-06 14:00:25+00:00
Critical piece of tech infrastructure. Which is absolutely is.

When GitHub goes down, the company I work at is pretty much kneecapped for the duration of the outage. If you’re in the middle of a PR, waiting for GitHub actions, doing work in a codespace, or just need to pull/fetch/push changes before you can work, you’re just stuck!
by tombert | 2025-09-06 14:01:01+00:00
I am a big functional programming geek. I am one of the few people on the planet who can honestly say I have been paid to write F#, Haskell, Clojure, and Erlang. I have spoken at FP conferences like six or seven times, and I have shit on Java for most of my career.

And yet, my latest talk at Lambda Days basically boiled down to “Java 21 and later don’t actually suck anymore”, and I genuinely do mean that.

Java 21 is actually fun to write, even for a grumpy FP advocate like me. Virtual threads make concurrency a lot simpler, and now that there’s proper records and ADTs (in the form of sealed interfaces), along with pattern matching, the language is actually pleasant to use. I haven’t dived into 25 yet, but I suspect I will like it as much or more than 21.

The biggest issue, though, is that Java programmers won’t use the new features. It was like pulling teeth at my last job to get people to use stuff from Java 8 (e.g. the `var` keyword), and none of my coworkers even knew how to use NIO or BlockingQueues which I think predate agriculture. I mean, hell, I had explain what “fairness” was to engineers when using a ReentrantLock because someone “corrected” my code with `synchronized`.

I don’t think Java makes people into bad programmers, but I do think it selection-biases for intellectually unambitious engineers. They learn exactly enough Java in college to pass their courses, and then get a job at a BigCo that doesn’t strictly require ever learning anything more than what they were taught in their “intro to data structures” course.

I have met some extremely intelligent Java engineers who do have intellectual curiosity, so I am not saying it affects everyone, but I do think that they are the minority. Java 25 might add every feature to make my wildest dream come true but it won’t matter if I am not allowed to use it.
by ModernMech | 2025-09-06 14:01:41+00:00
Researchers had this knowledge in 2007, when the only cars to finish the DARPA Urban challenge were equipped with Velodyne 3D LIDAR. Elon Musk sent us back a decade by using his platform to ignorantly convince everyone it was possible with just camera alone.

For anyone who understands sensor fusion and the Kalman filter, read this and ask yourself if you trust Elon Musk to direct the sensor strategy on your autonomous vehicle: https://www.threads.com/@mdsnprks/post/DN_FhFikyUE

For anyone wondering, to a sensors engineer the above tweet is like sayin 1 + 1 = 0 -- the truth (and science) is the exact opposite of what he's saying.
by hyperpape | 2025-09-06 14:02:24+00:00
From Dan Luu (https://danluu.com/wat/):

> When I joined this company, my team didn't use version control for months and it was a real fight to get everyone to use version control. Although I won that fight, I lost the fight to get people to run a build, let alone run tests, before checking in, so the build is broken multiple times per day. When I mentioned that I thought this was a problem for our productivity, I was told that it's fine because it affects everyone equally. Since the only thing that mattered was my stack ranked productivity, so I shouldn't care that it impacts the entire team, the fact that it's normal for everyone means that there's no cause for concern.

Do not underestimate the ability of developers to ignore good ideas. I am not going to argue that AI is as good as version control. Version control is a more important idea than AI. I sometimes want to argue it's the most important idea in software engineering.

All I'm saying is that you can't assume that good ideas will (quickly) win. Your argument that AI isn't valuable is invalid, whether or not your conclusion is true.

P.S. Dan Luu wrote that in 2015, and it may have been a company that he already left. Version control has mostly won. Still, post 2020, I talked to a friend, whose organization did use git, but their deployed software still didn't correspond to any version checked into git, because they were manually rebuilding components and copying them to production servers piecemeal.
by ModernMech | 2025-09-06 14:04:41+00:00
Because LIDAR can detect the object at the beginning of the perception pipeline, whereas camera can only detect the object after an expensive and time consuming ML inference process. By the time the camera even knows there's an object (if it does at all) the LIDAR would have had the car hitting its brakes. When you're traveling 60 MPH, milliseconds matter.
by stinkbeetle | 2025-09-06 14:04:54+00:00
Of the wire format you mean? I compress it and still need to care about the space efficiency of the wire format beyond that. Compression ratio does improve a lot when not doing our own, end result is significantly larger. Also it becomes also significantly slower because more data to process which is possibly the bigger problem.

It's probably not like most web application, it's hardware data loggers that produce about hundreds of millions to billions of events per second (each with minimum about 4 bytes of wire format and maximum roughly 500 bytes).
by b112 | 2025-09-06 14:06:06+00:00
A straw man? An actual argument?

I responded to this parent comment:

"LLMs have shown the general public how AI can be plain wrong and shouldn't be trusted for everything."

You take issue with my response of:

"loads of DEVs on here will claim LLMs are infallible"

You're not really making sense. I'm not straw-manning anything, as I'm directly discussing the statement made. What exactly are you presuming I'm throwing a straw man over?

It's entirely valid to say "there are loads of supposed experts that don't see this point, and you're expecting the general public to?". That's clearly my statement.

You may disagree, but that doesn't make it a strawman. Nor does it make it a poorly phrased argument on my part.

Do pay better attention please. And your entire last sentence is way over the line. We're not on reddit.
by itfourall | 2025-09-06 14:06:10+00:00
Hi HN community,

I’m excited to share my latest project: a free, AI-powered photo colorizer that transforms black-and-white images into vivid, full-color versions instantly. Built with advanced models like DDColor (and optionally GFPGAN for restoration), it’s designed to bring old family photos, historical images, or creative projects to life with natural, vibrant colors.

Why I built it: I noticed that many existing tools either produce lackluster colors or are locked behind paywalls. My goal was to create something accessible, fast, and open for anyone to use, whether you’re restoring a 100-year-old family portrait or experimenting with creative edits. The global demand for photo colorization is huge—millions of people are digitizing memories or enhancing visuals for professional use.

Features:

Free and Online: Upload your black-and-white photo and get a colorized version in seconds, no signup needed.

AI-Powered: Leverages state-of-the-art models (like DDColor) for photorealistic results.

GPU-Accelerated: Uses CUDA for fast processing (seconds per image on modern GPUs).

Optional Restoration: Combine with GFPGAN to sharpen and enhance details after colorization.

Open-Source Friendly: Built on open-source frameworks, with plans to release parts of the code soon.

How it works: Upload your image, and the AI analyzes textures, patterns, and context to predict natural colors. You can tweak settings like saturation for bolder results. The backend runs on Debian 12 with PyTorch and CUDA, ensuring scalability. I’m also experimenting with a MySQL database (via PyMySQL) to store user uploads for future features like batch processing.

Try it out: [Insert your website URL here, e.g., myphotocolorizer.com]

Example: Upload a 1920s photo, get a vibrant, modern-looking version.

Perfect for genealogists, photographers, or anyone curious about history.

What’s next: I’m working on mobile support, batch processing, and integrating more artistic colorization models (e.g., DDColor’s artistic variant). Feedback is welcome—let me know what features you’d love to see or if you run into issues!

Would love to hear your thoughts, HN! Have you used colorization tools before? What makes a great one for you?
by nilamo | 2025-09-06 14:06:20+00:00
Sure you could. Each local area (such as a planet) is a single timezone, and everyone there experiences time at the same rate. Someone leaving that timezone would experience time dilation... But in game it would just appear as a communications lag, just as it is for people on different planets. Then, once you've arrived at your destination, there's no longer any lag with your new timezone, and your lag with the original time zone is now fully synched with everyone else on your new planet.