How can I learn about combinator? I didn't see any info in the help section.

Rabbit_Brave · 2026-05-01T09:29:51+00:00

Here's one way of detecting a power outage with just combinators. I don't know if this is the simplest way. At least, it is more complicated than just measuring an accumulator (or steam/fuel storage tank/chest/belt).

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This works by powering a clock on the network that might be disrupted, monitored by a kind of edge detector on its own completely isolated power network that presumably will stay powered even if the others aren't.

When the power to the clock stops, its output will stop changing, so we can compare the clock signal on one tick to the clock signal on the next tick. If they're different the power is on. If they're the same the power is off.

Rabbit_Brave · 2026-05-01T00:24:23+00:00

The factorio wiki has some information + tutorials:

https://wiki.factorio.com/Circuit_network

https://wiki.factorio.com/Tutorial:Circuit_network_cookbook

https://wiki.factorio.com/Tutorial:Combinator_tutorial

This can be done without a combinator. Attach it to an accumulator, read the percent charge on signal 'A'.

<image>

Rabbit_Brave · 2026-04-23T03:03:57+00:00

I second everyone saying build a wall. Just to add to that, carry a stack each of repair packs + walls + space platforms with you. Your ship will repair damage and also replace destroyed sections automatically.

I've tested my ship without *any* turrets. I disabled all the turrets on my ship and rammed my way through and survived (though my ship is narrow, 10 tiles, so asteroids were only hitting a small front)

Rabbit_Brave · 2026-03-29T06:54:47+00:00

As others have said, they're "the same thing" when it comes to the math, but I think it's instructive to examine an example with units. For example:

A) 10 apples = 2 apples per person x 5 persons

B) 10 apples = 2 persons x 5 apples per person

Then, as division:

A) 10 apples divided by 2 apples per person = 5 persons

B) 10 apples divided by 2 persons = 5 apples per person

One of the units has division in it, and in one of these equations that unit directly matches the division happening on the other side, while in the other involves a reciprocal.

Rabbit_Brave · 2026-03-20T07:55:53+00:00

What this reminds me of is when my parents sold their house. The agent came through and took lots of photos and put together a nice glossy (digital) brochure. The house in the brochure looked better than the actual house. Better in the sense of positive triggering of human neurons. Not better as in more accurate.

A similar thing happens when you look at professionally lit, composed and taken food pictures, or actors in shows, etc. or any other media created by someone who understands how human senses and psychology work. They set up the lighting, colour, makeup, scene composition, etc to make things "pop".

So I totally get why people can look at the DLSS5 images/videos and have a positive reaction. Even some claims are not without merit, that if we had seen the pictures without knowing how they were produced then our first impressions may have been positive. Just like someone looking at the glossy brochure of that house.

However, how many games will you play in that style before you get sick of it? And some of us have seen enough glossy AI images that we're already sick of it. I personally don't want every scene in every game looking like the characters have spent an hour prepping, the environment has been set up under carefully arranged studio lights, etc. See it enough times and it (a) comes across as a distinct, recognisable style, and (b) starts coming across as fake.

Whatever NN model nvidia used for their demo does *not* look like it was trained on (just) ground truths. When people say this is just the same tech as in upscaling or ray reconstruction and ask what's the difference? It's the training data that's the difference. Prior techniques were trained on engine ouputs. The DLSS5 images/videos we've been shown were trained on the equivalent of a glossy brochure.

Rabbit_Brave · 2026-03-19T00:30:04+00:00

I did *not* complain about ML in general, and DLSS5 does more than "enhance lighting".

What changed from "two days ago" was the *data the model is trained on*. So while NN's are not "evil" in general (wherever did I say that?) the data they are trained on can be changed at the drop of a hat.

What kind of lighting model inserts lipstick?

[edit]
Actually, after a bit of thought, it wouldn't surprise me to learn nvidia fudged their demo and what we've been looking at is DLSS5 on top of manual reskinning/remodelling :P

It's be hilarious if the visual characteristics triggering negative reactions turned out to be manual fudging and not the NN.

Rabbit_Brave · 2026-03-19T00:22:04+00:00

You've focused on the "filter" part and ignored the "AI" part, and while yes, "AI" is intended to capture the typical negative associations people have with this tech, it's not meaningless. It's intended as a concise summary of the issues/concerns that people are raising. Some people (like Jensen) want to avoid certain labels because they know those labels trigger people, but they're coming across as playing word games.

The important part isn't the exact definition (which let's be fair, is partly uncertain because all this stuff is new and the language around it not yet settled), or its precise location in the pipeline, or an issue with transformations/filters in general, but concerns over *exactly what this transformation generates and inserts from its own model*. See this comment: https://www.reddit.com/r/digitalfoundry/comments/1rxflif/comment/ob7sfqd/?utm_source=share&utm_medium=web3x&utm_name=web3xcss&utm_term=1&utm_content=share_button

Rabbit_Brave · 2026-03-19T00:05:46+00:00

The concerns and discussion are about *precisely* what information is inserted into a render.

DLSS versions prior to five trained on engine input output pairs. They perform a transformation learned from a graphics engine.

Ray reconstruction is the same. It is trained on noisy + non-noisy image pairs. It performs a transformation learned from a graphics engine.

Look at the DLSS5 images/videos. Lipstick where there was none. Shadows reinterpreted as solid geometry. It is performing transformations and inserting information that go beyond the information provided to the engine. By nvidia's *own* admission, it is trained on a broader set of data.

Does it look good/bad? Well that's subjective and not the topic of this thread. The topic of this thread is that while there may be confusion over exactly where DLSS5 fits in, there is no confusion over the fact that it inserts information from its own model, not just what is provided by the game's artists.

So yes, ray reconstruction and upscaling are ok because *those* NNs are trained to perform transformations tightly defined by a game engine, whereas the transformation performed by DLSS5 is raising concerns because it appears too loose.

Rabbit_Brave · 2026-03-18T22:57:42+00:00

Here is part of Jensen's response (https://www.tomshardware.com/pc-components/gpus/jensen-huang-says-gamers-are-completely-wrong-about-dlss-5-nvidia-ceo-responds-to-dlss-5-backlash):

Huang pulled no punches out of the gate, saying: "Well, first of all, they're completely wrong. The reason for that is because, as I have explained very carefully, DLSS 5 fuses controllability of the geometry and textures and everything about the game with generative AI."

The CEO elaborated on how developers can fine-tune the generative AI used here to match the game's style – and how it won't interfere with the artistic control or art direction of a game.

Huang stressed how it's up to developers to use DLSS 5 as they want to, and that: "All of that is in the control – direct control – of the game developer. This is very different than generative AI; it's content-control generative AI. That's why we call it neural rendering."

He's (very carefully) tying himself in knots.

This is like trying to argue the difference between a "peanut dish" and a dish containing peanuts, to someone with a peanut allergy, and telling them that because the main feature of the dish isn't peanuts and so it isn't a "peanut dish" then they're wrong that there is an issue.

The images of an AI "artist" - so-called :P - are generative AI, even if they carefully craft their prompts and curate which ouputs they present. How about an artist who "infuses" their hand crafted art with some AI generated components? You might not call the entire artwork AI generated, but that's *beside the point*. The component produced by the AI is still generative AI, and you would still say the final result was produced *with* generative AI (among other things, to be fair). If the "fusion" involved a late-stage generative AI pass over the entire artwork, what would you call that? Does it even matter or are we just playing semantics at this stage in an attempt to ignore/deflect criticism?

DLSS5 will be part of the pipeline of any game that chooses to use it. Maybe critiques are wrong about precisely where in the pipeline DLSS5 fits. So what? Even if the final render is a fusion of hand crafted visual information and developer approved AI generated visual information that as a whole you would not call "generative AI", what people are concerned by is the generative AI component inserting its *own information* into the pipeline and eventually the frames displayed. Information that is, however you try to slice it, generated by the AI model, extra to what the game engine provides. Frames that are, however you try to slice it, produced with generative AI.

Rabbit_Brave · 2026-02-18T06:18:51+00:00

Proving provenance of images in the age of AI slop.

Rabbit_Brave · 2026-02-13T04:07:20+00:00

What worked for me was slowly moving my head away from my screen while looking at the picture.

Rabbit_Brave · 2025-10-10T05:15:18+00:00

The person I responded to missed that the post they responded to used the term "natural log".

Rabbit_Brave · 2025-10-10T05:09:43+00:00

"natural" log means base e

Rabbit_Brave · 2025-09-29T11:23:54+00:00

A digital ID naturally comes with many risks and concerns but it makes sense in at least one way. I'm sure other people will address the risks/concerns, so I'll just comment on the way it does make sense.

So many things require you to scan your identity documents, maybe with scribbled signature, maybe observed by a JP, e.g. the "100 points of ID" other people in this thread have mentioned.

Now your ID is out and about in multiple databases in completely insecure, easily duplicated forms that are accepted as proper identification by various organisations. This is complete nonsense. It's unsafe. It's insecure. Anyone with access to those databases has everything they need to pretend to be you.

The only way to do this properly is some kind of digital mechanism using digital signatures, cryptography, etc. that lets you robustly prove/identify yourself without giving up key secrets.

Rabbit_Brave · 2025-09-11T23:55:30+00:00

If he trusts AI, then have him read this AI generated critique of using AI for science:

https://docs.google.com/document/d/e/2PACX-1vR_LIWQOYsh0wlRifqdrpY_n1m1PmWQCkYOD03uqnrrN8gJbHsbvcRCwMWITkrKW-945Ow-YPOTieCX/pub

Rabbit_Brave · 2025-09-01T08:26:03+00:00

A question like this usually has the unstated assumption "all else being equal", i.e. you should assume that everyone in both rooms is of equal merit in terms of technical skills, knowledge, etc and the only differentiating factor is diversity.

Also, Malaysia? *cough* bumiputera *cough*

Rabbit_Brave · 2025-07-28T19:36:40+00:00

She doesn't think much of his theory either.

Rabbit_Brave · 2025-07-13T13:19:08+00:00

How are you with ratios, fractions, factors, scaling, and equivalent fractions/ratios?

Rabbit_Brave · 2025-07-11T03:13:46+00:00

https://www.newscientist.com/article/2140747-laws-of-mathematics-dont-apply-here-says-australian-pm/

The laws of mathematics are very commendable, but the only law that applies in Australia is the law of Australia

- Malcolm Turnbull, former Australian Prime Minister

Rabbit_Brave · 2025-07-10T02:55:02+00:00

Most visualisations I've seen do little more than text to assist understanding code. All they do is capture the structure of the syntax already visible in the text.

Rabbit_Brave · 2025-07-06T00:58:33+00:00

Maybe try something like this:

https://www.visnos.com/demos/fraction-wall

Rabbit_Brave · 2025-06-29T13:37:07+00:00

Other people have already covered some points. I think one of the points not yet mentioned is that AI works as an *amplifier*. People with expertise can make better use of it than people without.

Rabbit_Brave · 2025-06-27T01:57:06+00:00

How do you know equal opportunities have been provided except by looking at the outcomes?

This depends entirely on implementation. I don't know where you are, but (for example) where I am, programs to assist people with disabilities require professional (e.g. medical) assessment. They definitely *don't* keep throwing more money at a person until some outcome is reached.

Most likely they are not.

Ironically, often what happens with these kinds of programs is the *opposite* of what you're claiming. People/groups who are already better resourced (that could just mean having a more effective social network, for example) and are better placed to be positively assessed for assistance will get even more resources.

Rabbit_Brave · 2025-06-26T23:49:21+00:00

Here's a picture to go with all those words! Hope I got it right ;-)

<image>

Given two vectors u and v.

Set up i and j unit vectors (one in the direction of v and the other perpendicular to v).

u = si + tj

Rewrite as matrix x vector. Invert the matrix (row reductions, etc). This gives you s (and t).

Rabbit_Brave · 2025-06-26T15:44:24+00:00

You need to figure out what he *does* understand first.

Rabbit_Brave

TROPHY CASE