If you can't explain something in simple terms, you don't understand it well enough
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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.
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.
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.
> 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.
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.)
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?
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.
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".
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.
... 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?
There's nothing wrong with that: https://en.wikipedia.org/wiki/Lie-to-children
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.
https://youtu.be/QGw-cy0ylCc
Is this an asynchronous architecture CPU?
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.
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...
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.
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?).
If you have such an opinion, explain some advanced papers of Peter Scholze to me.
'It's the study how the particles that make atoms interact... it's fiendishly complicated'
I personally think of this in terms of giving directions.
It's easy to give directions to somewhere near where you currently are -- "Just head down the road, it's the second left, then 3 doors down".
When giving directions to a far-away place you either have to get less accurate "it's on the other side of the world", or they get really, really long. Unless of course they already know the layout of the land -- "You already know Amy's house, over in Algebra Land? Oh, then it's just down the road, fourth left, six doors down".
People often seem cleverer because they know the layout of some really obscure land, but often it's just because people have never been anywhere near it. I have a joke about my research where I say, "A full explanation isn't that hard to explain, it's just long. About 4 hours probably. Are you interested?" So far, I've had 3 people take me up on that, and they all seemed to have an understanding once I'd finished (or, they really really wanted to escape).
Simple terms need not be short terms.
Huh; now want to write a Supercalifragilisticexpialidocious song for my research topic.
As one must.
And that’s why Feynman was always happy to explain how magnets work!
Feynman was happy to explain why he couldn't explain how magnets work!
Not every subject has simple explanations.
A horse is just a bunch of chemicals in a skin sack. Gee, I understand it!
Hmmmm, what might Feynman say about a horse?
So, what's a horse? Well, you look at it: it’s this big animal, standing on four legs, with muscles rippling under its skin, breathing steam into the cold air. And already — that’s amazing. Because somehow, inside that animal, grass gets turned into motion. Just grass! It eats plants, and then it runs like the wind.
Now, let’s dig deeper. You see those legs? Bones and tendons and muscles working like pulleys and levers — a beautiful system of mechanical engineering, except it evolved all by itself, over millions of years. The hoof? That’s a toe — it’s walking on its fingernail, basically — modified for speed and power.
And what about the brain? That horse is aware. It makes decisions. It gets scared, or curious. It remembers. It can learn. Inside that head is a network of neurons, just like yours, firing electricity and sending chemical messages. But it doesn’t talk. So we don’t know exactly what it thinks — but we know it does think, in its own horselike way.
The skin and hair? Cells growing in patterns, each one following instructions written in a long molecule called DNA. And where’d that come from? From the horse’s parents — and theirs, all the way back to a small, many-toed creature millions of years ago.
So the horse — it’s not just a horse. It’s a machine, a chemical plant, a thinking animal, a product of evolution, and a living example of how life organizes matter into something astonishing. And what’s really amazing is, we’re just scratching the surface. There’s still so much we don’t know. And that is the fun of it!
Sounds like an LLM's impression of Feynman.
It does seem that way, doesn't it.
Feynman passed away 37 years ago, so he wasn't available for this.
How simple? Simple to who?
The quip you're referring to was meant to be inspirational. It doesn't pass even the slightest logical scrutiny when taken at its literal meaning. Please. (Apologies if this was just a reference without any further rhetorical intent though.)
It's like claiming that hashes are unique fingerprints. No, they aren't, they mathematically cannot be. Or like claiming how movie or video game trailers should be "perfectly representative" - once again, by definition, they cannot be. It's trivial to see this.