[thorum]

Some ideas are too complex to explain accurately in simple terms.

You can give someone a simple explanation of quantum chromodynamics and have them walk away feeling like they learned something, but only by glossing over or misrepresenting critical details. You’d basically just be lying to them.

[jiggawatts]

Quantum Mechanics is the example of a subject where supposed experts don’t really understand it either and hence can’t explain it adequately.

Also, it’s hilarious to get comments like this voted down by non-experts who assume this must be an outsider’s uninformed point of view.

I have a physics degree and I studied the origins and history of quantum mechanics. Its “founding fathers” all admitted that it’s a bunch of guesswork and that the models we have are arbitrary and lack something essential needed for proper understanding.

[tbrownaw]

Take for example entanglement.

The math that describes it is known precisely. Specific implications of this are known. There's no information transfer, there's no time delay, etc.

And yet lay people keep incorrectly thinking it can be used for communication. Because lay-audience descriptions by experts keep using words that imply causality and information transfer.

This is not a failure of the experts to understand what's going on. It's a failure to translate that understanding to ordinary language. Because ordinary language is not suited for it.

> Its “founding fathers” all admitted that it’s a bunch of guesswork and that the models we have are arbitrary and lack something essential needed for proper understanding.

We don't have a model of why it works / if there's a more comprehensible layer of reality below it. But it's characterized well enough that we can make practical useful things with it.

[zmgsabst]

> This is not a failure of the experts to understand what's going on.

> We don't have a model of why it works / if there's a more comprehensible layer of reality below it.

Counterpoint:

You’ve just admitted they don’t understand what’s going on — they merely have descriptive statistics. No different than a DNN that spits out incomprehensible but accurate answers.

So this is an example affirming that QM isn’t understood.

[teiferer]

QM isn't less well understood though than Newton's mechanics. Neither cover the "why". But both provide a model of the world, the model (!) is very precisely understood and it matches observations in certain parts of reality. Like all reasonable scientific theories do. They have limits, and beyond those limits they don't apply, but that doesnt mean they are not understood. It's reality that is not sufficiently well understood and by coming up with more and more refined models/theories, we keep approximating it, likely without ever having a "fully correct" theory encompassing everything without limits. (But that's ok.)

[tbrownaw]

The only descriptive / empirical parts is the particle masses.

But it sounds like your objection is that reality isn't allowed to be described by something as weird as complex values that you multiply to get probabilities, so there necessarily must be another layer down that would be more amenable to lay descriptions?

[zmgsabst]

That’s not my point, nor close to what I said.

My point is that their models are fitted tensors/probability distributions, often retuned to fit new data (eg, the epicyclic nature of collider correction terms) — the same as fitting a DNN would be.

Their inability to describe what is happening is precisely the same as in the DNN case.

[ted_dunning]

Actually it is just the opposite. QED is comprehensive and, as far as we know, accurate.

But it is impractical to use in most situations so major simplifications are required.

The correction factors that you mention are the result of undoing some of those simplifications, sometimes by including more of the basic theory and sometimes by saying something like "we know that we ignored something important here and it has to have this shape but we can only kinda sort measure how big it might be because it's too hard to actually calculate".

[Dylan16807]

If you have a very small neural network, you can fully understand and explain how it works.

As you increase the detail of a description, it reaches a point where nothing is missing.

[tbrownaw]

... So it's about not being able to observe short-lived particles directly, and having to work backwards from longer lived interaction or decay products? Or about how those intermediate particles they have to calculate through also have empirically-determined properties?

[ars]

There's nothing wrong with that: https://en.wikipedia.org/wiki/Lie-to-children

[pests]

Reminds me of the old videos on the Mill CPU architecture. There is multi hour long video about “the belt”, a primary concept in understanding the Mill architecture and instruction scheduling. It’s portrayed in the slides as an actual belt with a queue of items about to be processed, etc.

Only in the end to reveal the belt is truely conceptualized and does not formally exist. The belt is an accurate visual representation and teaching tool, but the actual mechanics emerge from data latches and the timing of releasing the data, etc.

I thought it was helpful.

[watersb]

https://youtu.be/QGw-cy0ylCc

Is this an asynchronous architecture CPU?

[Dylan16807]

It's not. I'm curious what gave you that idea, though?

The belt moves once per cycle, if that wasn't clear? He says the word "cycle" (and measures latency in cycles) a lot.

[ZoomZoomZoom]

That's how you get a whole population imagining mitochondria as puffy gelatinous beans, instead of network around other organelles.

https://www.nature.com/immersive/d41586-025-00269-y/index.ht...

[doubledamio]

To me, every profession—from software engineering to farming—has its complexities, yet most professionals can explain what they do in clear terms. When academics say they can’t offer a basic explanation, it often feels like an attempt to protect their status or avoid the effort—if not a kind of intellectual arrogance. Yes, the topics are challenging—you don’t need to throw in quantum buzzwords to convince me—but simplifying your work isn’t “dumbing it down”; it often sharpens your own understanding too.

[SubiculumCode]

I encounter this idea too much..the idea that complex topics can always be explained in a way to make everyone understand it...and that just isn't true. There is usually a point on any topic where further reduction/compression is no longer lossless. Yes, I think the analogy of image compression works pretty well. Lossless compression can only go so far. Further reduction introduces loss, but the image may still be understandable, but at a certain point, the loss from compression prevents understanding of the image, and may even mislead (Is that a bear, or uncle Robert?).

[aleph_minus_one]

If you have such an opinion, explain some advanced papers of Peter Scholze to me.

[Angostura]

'It's the study how the particles that make atoms interact... it's fiendishly complicated'