This New Idea Could Explain Complexity
Vložit
- čas přidán 17. 06. 2024
- Check out courses about science, computer science, or math on Brilliant! First 30 days are free and 20% off the annual premium subscription when you use our link ➜ brilliant.org/sabine.
The universe creates complexity out of simplicity, but despite many attempts at understanding how, scientists still have not figured it out. We do know that complexity relies on the emergence of new features and laws, but then again we don't understand emergence either. The first step must be to clearly define what we are talking about and to measure it. A group of scientists now put forward a way to do exactly this. Let’s have a look.
Paper here: arxiv.org/abs/2402.09090
Correction to what I say at 04:07 "You will still get the correct prediction". I meant to convey that the prediction doesn't get worse if you average "lumped" classes rather than the full set. Either way, it will be a probabilistic prediction so it's correct only in a statistical sense either way.
🤓 Check out my new quiz app ➜ quizwithit.com/
💌 Support me on Donorbox ➜ donorbox.org/swtg
📝 Transcripts and written news on Substack ➜ sciencewtg.substack.com/
👉 Transcript with links to references on Patreon ➜ / sabine
📩 Free weekly science newsletter ➜ sabinehossenfelder.com/newsle...
👂 Audio only podcast ➜ open.spotify.com/show/0MkNfXl...
🔗 Join this channel to get access to perks ➜
/ @sabinehossenfelder
🖼️ On instagram ➜ / sciencewtg
#science #sciencenews #math #complexity #maths - Věda a technologie
"Usually these people are computer scientists." Shots fired.
As a software engineer, I laughed out loud
@@corbono As a software engineer, I laugh at your laughing out loud.
@@anthonylosego As someone who took an introductory webdev course, I lol'd at your lol'ing bc their lol.
@@anthonylosego as a software engineer i ask: could you explain? Didn't get the joke (well her's, not yours)
Most software engineers know diddly squat about anything except their own interminable code that defies comprehension to normal Man. I can't speak for how Women see things.
what a great explanation of such a fascinating subject. Our cat is called Kant, now he gets a new name, we call him Emergence. He is lumped with dogs
Are you relating to his behavioral aspect?
@@Dr.M.VincentCurley you Kant do that.
I was told that a good cat name should have a hissing sound (like psps) because that is grabbing their attention, or something like that. "Emergence" would better, if this is true. (But maybe your cat is different and likes these names, who knows?)
If your intuition is to name your cat Kant, then it's too late!! You've already done it!!
@carl: hope you‘re not living in an english spoken region. If you call your cat like that, the neighbours could be irritated 😄
EDIT: I can’t get rid of that picture in my head now and keep giggling 😄
This reminds of software architecture. The underlying purpose of code encapsulation is causal closure to reduce complexity. Similarly the lumpability of data reduces the test complexity to manageable levels
My thoughts exactly, it sounds like it's describing layers of an architecture that are cleanly separated by an abstraction.
Emergence, then, is a "decoupling" of two distinct "scales"?
This is what engineers do as well I think. An example I can think of is using transistors to create logic gates to create structures like adders/multipliers (for an alu) and control units to build a CPU, or transistors going to things like the different stages of an op-amp to piece together the op-amp itself so it can be used to build things like voltage comparators or a difference amplifier or whatever other configuration you want. And these things can be used to create larger circuits.
Yes... layers of abstraction work effectively in the human realm because the natural world already does something similar.
Not the same kind of "complexity", Complexity is an essential aspect of the objects so described. Removing any complexity removes the nature of the object or the entire object itself.
Cat Memes just emerge from the OSI model.
3:46 I get the idea, but I hate this example, because I have yet to see a traffic flow prediction that was actually correct. They always predict far more traffic than in reality.
In my experience, there are two reasons for this:
First, traffic engineers almost exclusively plan for moving as many cars as possible, rather than as many people as possible, so they overplan for cars to the detriment to every other form of transportation.
Second, traffic engineers are paid to build roads. They are not paid to _not_ build roads. So every projection always results in (surprise!) proof that they need to build more roads.
Incidentally this highlights an interesting difference between "traffic engineers" and "transportation engineers" and I talked about that with Build the Lanes on an episode of the Urbanist Agenda podcast.
Such a great (albeit non sequitur) comment to see on a Sabine vid!
One of my biggest pet peeves when driving is that roads are built exclusively for people who already know where they are going. Which makes driving in the city a miserable experience. Need to park somewhere? better hope you're lucky enough to be on the right side of the road and can spot the almost indistinguishable parking turning before you pass it. If not, add another 15 to 45 minutes to your trip so you can try again.
Not just bikes!!!!
If they always predict more traffic than there really is, why is traffic always congested? Shouldn't it be the other way around?
I don’t undestand the details, but a clear understanding emerges.
LUMPABILITY = integration or summation of states, dimensions -- a syntropic process!
Complexity is dual to simplicity.
Micro is dual to macro.
Increasing the number of dimensions or states is an entropic process -- differentiation or reductionism.
Decreasing the number of states or dimensions is a syntropic process -- integration or holism, LUMPABILITY.
Increasing (divergence, entropy) is dual decreasing (syntropy, convergence).
Syntropy (prediction) is dual to increasing entropy -- the 4th law of thermodynamics!
Teleological physics (syntropy) is dual to non teleological physics (entropy) -- physics is dual.
Integration is dual to differentiation.
Reductionism is dual to holism.
Homology (syntropy) is dual to co-homology (entropy).
"Always two there are" -- Yoda.
@@hyperduality2838 if two depend entirely on one another and cannot have an existence in isolation without the counterpart, could they not be described as two parts of one? There is no male without female or female without male. How do two things give rise to each other when they both are dependent on the other which they give rise to in order to exist in the first place
@@hyperduality2838I am surprised nobody mentions about statistical mechanics. Lumpability seems to be just dimensionality reduction for space and ensemble averaging for time. Some degrees of freedom/dimensions matter a lot less at larger length scales (thus can be marginalised out), and microscopic observables can be average in time (assuming that the ensemble is not perturbed too frequently).
@@__-op4qm Lumpability is just a clumsy way of saying syntropy (convergence).
Your mind associates or integrates information -- integrated information theory.
Syntactic information is dual to semantic information -- information is dual.
Syntax (objective, absolute) is dual to semantics (subjective, relative) -- languages or communication.
If mathematics is a language then it is dual.
Syntropy (prediction) is dual to increasing entropy -- the 4th law of thermodynamics!
Teleological physics (syntropy) is dual to non teleological physics (entropy) -- physics is dual.
Categories (form, syntax) are dual to sets (substance, semantics) -- Category theory.
"Only the Sith think in terms of absolutes!" -- Obi Wan Kenobi.
"Always two there are" -- Yoda.
All messages in a communication system are predicted into existence according to Shannon's information theorem -- a syntropic process, teleological.
Making predictions to track targets, goals and objectives is a syntropic process, teleological.
In homology you start with hypervolumes and reduce the number of dimensions:-
Hypervolumes become volumes become planes or surfaces become lines become points or zero dimensions and this is clearly a dimension reduction process -- syntropic.
Points are dual to lines -- the principle of duality in geometry.
In co-homology you do the opposite or opposame:-
Points becomes lines become planes become volumes become hypervolumes -- increasing dimensions or states is an entropic process.
Convergence (syntropy, homology) is dual to divergence (entropy, co-homology or dual homology).
Sine is dual to cosine or dual sine -- the word co means mutual and implies duality.
Vectors (contravariant) are dual to co-vectors (covariant) -- dual bases.
Riemann geometry or curvature is dual -- upper indices are dual to lower indices (tensors).
Gravitation is equivalent or dual (isomorphic) to acceleration -- Einstein's happiest thought, the principle of equivalence (duality).
Space is dual to time -- Einstein.
@@__-op4qm "The brain is a prediction machine" -- Karl Friston, neuroscientist.
Your brain integrates information to make predictions -- a syntropic process, teleological.
Certainty (predictability, syntropy) is dual to uncertainty (unpredictability, entropy) -- the Heisenberg certainty/uncertainty principle.
Hence there is a 4th law of thermodynamics.
Synergy is dual to energy -- energy is dual.
Synchronic points/lines are dual to enchronic points/lines.
Highly lumpable is such a good insult
to your mom?
There are much worst than a mere insult:
"Mrs, your test results show your breast is highly lumpable"
It's not, it applies only to a group of things.
@@Caellyan Yeah, it says that they are easily added to a big group: don't think for themselves or such.
@@Windows__2000 Lumpenproletariat?
4:00 - having conducted a few traffic studies in the US... "You still get the correct prediction" is giving us a LOT of credit we probably don't deserve.
But then, the fact that your individual odds of getting stuck at any traffic light (not involving a train, anyway) for more than 120 seconds are basically zero means that statistics kinda work. Which is reassuring.
And yes, rather than use actual stats terminology, traffic engineers and city planners call "the value that tells you how meaningful your grouping selections have been" "Lumpability". The reason for this is that they often have to explain the results of their research to town councils and city board selectpersons who barely understand the concept of "road".
Lumpability sounds a lot like computational reducibility.
LUMPABILITY = integration or summation of states, dimensions -- a syntropic process!
Complexity is dual to simplicity.
Micro is dual to macro.
Increasing the number of dimensions or states is an entropic process -- differentiation or reductionism.
Decreasing the number of states or dimensions is a syntropic process -- integration or holism, LUMPABILITY.
Increasing (divergence, entropy) is dual decreasing (syntropy, convergence).
Syntropy (prediction) is dual to increasing entropy -- the 4th law of thermodynamics!
Teleological physics (syntropy) is dual to non teleological physics (entropy) -- physics is dual.
Integration is dual to differentiation.
Reductionism is dual to holism.
Homology (syntropy) is dual to co-homology (entropy).
"Always two there are" -- Yoda.
I gave this some thought when I was sequencing DNA in 1994 using the God awful method "dideoxy chain termination sequencing" method. Very painful, but the point is. Identical twins are the same (ignoring the complexity) and yet you find a large number of emergent properties between them that are unexplainably different. While there are aspects we can certainly lump together, there are strange permutations that are unexpected.
That's very interesting, hadn't thought about this. Thanks for sharing!
We are all the same (ignoring the complexity)!
I was still using sanger sequencing in 2017 :(
@dr: nature vs nurture is a long standing topic. Monozygotic twins are the ideal study objects for such research.
@@dtrcs9518 Was your face as sunburned as mine?
Lumpability? I would have gone with "Glomular."
I would have gone with ‘morsular’
Corpuscular
tubular idea
Lumpability. Useful for making complicated things simpler. Secret superpower for mathematicians, you could say! (My AI say's)
That'll mix with the term 'Glomarular'. Glomarular Filtrate is basically urine. So, then it'll become 'piss parameter'.
Great review of a seminal article. It applies directly to my current research. I will look into how it might be used "by the numbers." That is to say, using the exact ideas and doing rigorous application to the concepts in my work. TY Sabine.
Great topic! Thanks for making me aware of this paper. This is something I have worked on and I'll take a close look at this paper.
Nice shot at Wolfram.. Oh. Just all computer scientists in general? Well, we are kinda lumpable. Lumpen? Lumpy?
wolfram is a physicist by training, but oddly the paper doesnt mention his work once, which is weird.
@@leecarraher yeah my first thought on seeing this video was to start looking for his name or the name of one of his student co-authors...
@@leecarraher Well, Wolfram was not very good at mentioning anybody else in his book A New Kind Of Science
Yes, lumpy would be the closest to reality.
@@emilgustavsson7310 Also my nickname from when I used to work out with weights.
Wolfram's A New Kind of Science uses some of these ideas as a fundamental property, particularly that complexity arises out of simple rules, as with Cellular Automata. What's fascinating is that from simple rules, you can derive BOTH the math of Relativity and Quantum Mechanics, and why they are the way they are is completely explained and understandable. Again, from very simple rules. Simple rules can even produce what seems to be "randomness" -- unpredictability is what's called computational irreducibility. It's impossible to predict the output in the future without running the rules in sequence. It's still early, and we don't have experiments to make predictions and provide evidence that it's "what's really going on" yet, but it's fascinating stuff.
Yes, well said & accurate! That Simple-rule generated "randomness" was used as the cryptographic basis for a generation of NATO radio communication, starting in the late 1980s. Darpa has been ALL OVER this research.
Wolfram is definitely not the first person to look at the problem in depth. I was reading entire books dedicated to the subject in the 90s and Ilya Prigogine did a lot of the original ground work in the area back in the 1960s. I applaud Wolfram's efforts in the area but I don't feel that his research has created much in the way of actual insights beyond simple categorization. If this new paper holds up, it will be one of the first major advances in the subject I've seen in a long time.
Hi, if I understand Wolfram also use Cellular Automata ....to try explain the Universe using simple rules....
@@danheidel True, "complexity science" was not invented by Wolfram, but he has made important contributions.
@@danheidel FYI, wolfram's CA work was in the 1980s. He knew about Prigogine's work, of course, and built on it.
FYI, Wolfram's work had HUGE effects but he is forbidden to mention it for National Security reasons. He's party to NDA from Darpa. The juicy good stuff we aren't allowed to know about. I know, though ...
I have had a hypothesis that gravity is emergent. Rather than a fundamental force with an associated particle, it's a perceived force much like a centrifugal force. However, being a lowly youtube, layman commenter, I don't have the resources to test such a hypothesis. Also, I could be way off in my understanding of particle physics as well...
You emerged only 3 hours ago
Advanced Boob Bot (ABB)
Likely you don’t remember where you saw the idea. With a Google search you could see that it’s a common hypothesis. Parallel, thinking possibly.
Classical theory GR versus quantum mechanics' empirical falsification. Three powerhouse German groups: equipment, chemistry, and guts to look. Sabine, native German bright light, could intervene. One group is *Professorin._ headed. Freude, schöner Götterfunken Tochter aus Elysium.* I'm running HyperChem Professional in a water-cooled Intel Core 17 with an Nvidia GeForce RTX 3070 8 GB triple fan graphics brick. Give me a fulcrum and I'll move the world.
there have been a big current of scientists who think the same you do, i think this class of hypothesis is called "entropic gravity"
In addition to Wolfram's work, the Santa Fe Institute has done great work in Complexity and Emergence. My favorite novel about Emergence is "Lila" by William Pirsig, the same guy/genius who wrote "Zen and the Art of Motorcycle Maintenance".
Interesting! thanks a lot
I'm still undecided on whether to buy "A New Kind of Science" - it's over a decade old now. Maybe I should just buy a more recent book by SW.
In Lila, though, we were told that a Creator God was necessitated by the second law of thermodynamics. His utter misunderstanding of science disgusted me mightily.
@@michaelstreeter3125 It is worth it if you can find a deal on a second hand copy. It exhaustively and methodically goes through every rule (within the constraints of his rule set). I found it interesting to see the visualizations of each rule in a way that is super easy to grok. It also offers a peak into chaos theory because it is so methodical.
@@evelynsinclair4937 Huh, I must have read the other "Lila" by Pirsig. I have no idea how you came up with your conclusion. "Lila" is more focused on metaphysics than science, and outlines a concrete instantiation of emergence . A number of people I know hated the book. I think it is brilliant.
Who doesn't want a t-shirt with "Highly Lumpable" emblazoned on it? 😆
With an Ompa-Lumpas:
"Ompa-lumpa-dee-di-do. Lumpability is what we do. "
with the L crossed and an H scribbled in?
"Highly lumpable man" made my day, I feel, channel is gold.
Big thanks to you!
Thankfully, my girlfriend thinks I'm pretty lumpable. 😎
@@michaelblacktreemore like h… nvm.
"Emergence of activists groups" also killed me :D. This time, Sabine outperformed herself :D.
LUMPABILITY = integration or summation of states, dimensions -- a syntropic process!
Complexity is dual to simplicity.
Micro is dual to macro.
Increasing the number of dimensions or states is an entropic process -- differentiation or reductionism.
Decreasing the number of states or dimensions is a syntropic process -- integration or holism, LUMPABILITY.
Increasing (divergence, entropy) is dual decreasing (syntropy, convergence).
Syntropy (prediction) is dual to increasing entropy -- the 4th law of thermodynamics!
Teleological physics (syntropy) is dual to non teleological physics (entropy) -- physics is dual.
Integration is dual to differentiation.
Reductionism is dual to holism.
Homology (syntropy) is dual to co-homology (entropy).
"Always two there are" -- Yoda.
Wonderful! I need more :) This emergence is a reason that some scientists don't support superdeterminism, claiming that sum is different than its parts (recently Kurzgesagt made a video about it). It is also a heart of entropy and I have a hunch that going deeper into this phenomena would give us answers to many scientific questions. and many philosophical ones. Thanks for the video, Sabine :)
Hi Sabine. Thanks again for another great video. Was wondering if you do podcasts?
So much to learn, so little time. Thank you for lumping together such high density information.
LUMPABILITY = integration or summation of states, dimensions -- a syntropic process!
Complexity is dual to simplicity.
Micro is dual to macro.
Increasing the number of dimensions or states is an entropic process -- differentiation or reductionism.
Decreasing the number of states or dimensions is a syntropic process -- integration or holism, LUMPABILITY.
Increasing (divergence, entropy) is dual decreasing (syntropy, convergence).
Syntropy (prediction) is dual to increasing entropy -- the 4th law of thermodynamics!
Teleological physics (syntropy) is dual to non teleological physics (entropy) -- physics is dual.
Integration is dual to differentiation.
Reductionism is dual to holism.
Homology (syntropy) is dual to co-homology (entropy).
"Always two there are" -- Yoda.
Thank you Sabine. This is one of the more interesting and timely podcasts to my particular situation - helping build alternative / supplemental schools for young children in Japan.
In the broadest sense, education as a process of social maturation is an emergent process, though typical institutionalization of that process tends to restrict human potential. My research area as a college instructor was in tapping into the students' intrinsic motivation as a social primate by replacing end of semesters tests and papers with what I termed an "Event-Driven Curriculum" ... student presentations in front of a real audience as a fractal of what we professors do in academic conferences.
By chance (synchronicity?), only a few days ago, I came across a link in substack's "Naked Emperor" to an on-line article in Quanta Magazine named "The New Math of How Large-Scale Order Emerges" ... a great supplement to this video. Thank you again Sabine!
Thank you, Sabine. You give ideas to think and develop. Love your work. Your knowledge, way to explain complex things easy and your music. Thank you 🙏🏻
Separation of Scales ... Sabine is such an illuminating teacher ... this idea was seldom discussed or even mentioned in my classes ...
She explains that term very detailed and accurate in her book "Lost in Math" from 2018.
So happy to see that! I’ve been fascinated by threshold effect as general principle forever but never found literature on it… so it’s emergence! Good to know
And emergent properties
It's crazy that this paper doesn't mention Stephen Wolfram anywhere...
You beat me to it.
They even use Mathematica for the graphics. They are certainly familiar with Stephen Wolfram :/
Ya, but Wolfram rarely mentions the concepts he's drawing from either. Maybe it's a tit-for-tat happening now?
Thanks so much for creating and sharing this informative video. Great job. Keep it up.
Instant subscription. Who ever has the ability to speak so eloquently and easy to understand at the very same time and giving out deeper Understanding of the Universe is a Master in Teaching. very inspiring
LUMPABILITY = integration or summation of states, dimensions -- a syntropic process!
Complexity is dual to simplicity.
Micro is dual to macro.
Increasing the number of dimensions or states is an entropic process -- differentiation or reductionism.
Decreasing the number of states or dimensions is a syntropic process -- integration or holism, LUMPABILITY.
Increasing (divergence, entropy) is dual decreasing (syntropy, convergence).
Syntropy (prediction) is dual to increasing entropy -- the 4th law of thermodynamics!
Teleological physics (syntropy) is dual to non teleological physics (entropy) -- physics is dual.
Integration is dual to differentiation.
Reductionism is dual to holism.
Homology (syntropy) is dual to co-homology (entropy).
"Always two there are" -- Yoda.
Did mathematicians really create a formal description to "decide on cohort before running experiments"?
Ya our ontology is starting to run together as the fields over specialize and don’t talk to each other.
Did mathematicians ever make experiments? 😉
Ask The Romans.
@@arcobrunner1979 I would say proving something is an experiment but it can only have definite outcomes yes or no. There is no significance testing required. Other experimental methods EMERGE from mathematical concepts, tho, lol. So, I guess it's good, that you don't need a significance associated to if the sqrt(2) is irrational are not.
@@MsSonali1980 Math has its axions, which can’t be proven. And everything else is derived from them. Math is the language of science, needed to analyse and interpret data from experiments. But math itself makes no experiment.
Super interesting, thank you for showing this topic. I once, long ago, made computer programs for business applications. The most valuable lesson I learned there is, that the program should have the same structure as the problem you are tackling. This way, the program would be more robust, less prone to mysterious errors, which proved to be true. This gave quite some “freedom”, not sure how to put it, and maintaining the program was rather easy as long as you kept a keen eye on the also changing structure of the problem. Somehow your video rings a bell, I’ll have a look at it a few times.
freedom = maintainability?
low technical debt?
This makes perfect sense as what you are stating in basis is that the “problem” is understood. At this point there is no longer a problem as such, but rather a known characteristic that may be worked with and offset for. This is what your program is doing - providing a naturally fitting response 🕹️
Great vid. Looking forward to more on this topic.
Based on some of the comments I have read, and speaking as a computer scientist (well, PhD student, take it as you will):
1) please don't conflate software engineering with computer science, these are two totally different things entirely - even if, and especially if, you are yourself a software engineer
2) Computer science is essentially the study of computation, which I believe can be very accurately described as the study of the macroscopic emergent properties of mathematics
3) Hence if anything, I would argue this paper actually serves as evidence that computation (if we assume it functions as the study of emergence) is a fundamental property of the universe
4) I don't think Sabine was being at all sarcastic when she described some computer scientists as seeing their field as more fundamental than particle physics - I personally interpreted this response to be that she found this notion to simply be an interesting concept. (Perhaps her further input would clarify this?)
I'm happy someone besides myself posted a comment about this, indeed, software engineering is not computer science. It's unfortunate the word "computer" is part of the description because it creates the false impression that electronic computers - as we know them, including the programming tools that help make them perform useful tasks - is what the science specifically studies.
LUMPABILITY = integration or summation of states, dimensions -- a syntropic process!
Complexity is dual to simplicity.
Micro is dual to macro.
Increasing the number of dimensions or states is an entropic process -- differentiation or reductionism.
Decreasing the number of states or dimensions is a syntropic process -- integration or holism, LUMPABILITY.
Increasing (divergence, entropy) is dual decreasing (syntropy, convergence).
Syntropy (prediction) is dual to increasing entropy -- the 4th law of thermodynamics!
Teleological physics (syntropy) is dual to non teleological physics (entropy) -- physics is dual.
Integration is dual to differentiation.
Reductionism is dual to holism.
Homology (syntropy) is dual to co-homology (entropy).
"Always two there are" -- Yoda.
@@hyperduality2838 haha I love this
I would define computer science a little differently: it's the study of the behavior of Turing machines (or any other equivalent model). It just so happens, as long as the Church-Turing thesis is true, that the space of all computations (i.e. all Turing machines) is so rich that it includes everything imaginable, from simple mathematical models to our brains to the whole universe that we live in. It even encompasses all of mathematics in some sense, since formal proof systems can be seen as nondeterministic computations that generate the set of all of that system's theorems. Whether or not that means it's more fundamental, I don't know, it really depends on your definition of "fundamental," but we can certainly make an argument that all of the theorems of physics and chemistry could rightly be considered theorems of computer science at the same time.
@@hyperduality2838 What if there's partial duality or triality, etc?
Stephen Wolfram wrote about this 20 years ago in his book " A New Kind of Science ."
Isaac Asimov wrote about this 73 years ago in his book “Foundation.”
@@ek3279
I don't see how those are related.
@@ek3279 Not really.
Would say, depends on what "this" is.
@@Kokuswolf
Yes, the problem is plenty have wrote about "this" way before 20 years ago.
Who cares about Wolfram then?
And if we still care that Wolfram had something to add, why not care about what this work adds too?
Love all the jokes and subtle references you put in your videos recently ^^. Very entertaining
The topics you're discussing are as interesting as ever, however I miss those longer in-depth videos.
As a Computer Scientist, we refer to "lumpability" as "encapsulation". This is typically used withing Object-Oriented Programming. "Encapsulation" means all the behavior of a class of objects can be described by code that defines that class (of objects) and reads from and alters its objects' data, and the data private to each object can be effectively hidden from the outside world (code that is not part of that class of objects). Good code is typically code in which each system is encapsulated from the others.
In the natural world, emergent behavior is fascinating and chaotic. In Computer Science, good code reduces emergent behavior as much as possible, building complex systems as a collection of simple systems, as emergent behavior leads to bugs (unintended outcomes).
And yes, Computer Science may rest at the foundation of physics. Wolfram is key here, although I suspect hypergraphs are not the only system that could emerge into quantum and relativistic structures.
interesting..
Perfect supplement to this topic! Tyvm
I am not sure that you are correct. Certainly taxi drivers and commuters are different classes and can be encapsulated as Driver but there is no sense of the combination of virtual functions,from different classes, creating a new Base Class function.
Emergence is Atheist bs to explain "fine tuning" by natural processes only.
All systems are Functions ... with purpose, reason, processes, rules, properties & design ( information).
Universal Functions ... is the hypothesis .. for Sir Issac Newton's Watchmaker Analogy over 300 years ago and all Machine Analogies ( Observation ) used by Christians (Natural Intelligence) to explain creation of the Universe & Life (Natural Functions) by God ( Unnatural Intelligence).
The Scientific Method ( a Function) created by Man (Function) to explain natural phenomena (Functions) of the Universe ( Isolated Thermodynamic Function) based on fixed Laws of Nature (Functions) is simply:
1. Observation
2. Hypothesis
3. Test & Predict ( needs the fixed laws)
4. Conclude
5. Refine (if valid).
The hypothesis of Evolution of the Species by Natural Selection in the 1850's ... fails he scientific Method ... especially when if was known Natural Selection only causes variation & adaptation within a species. There is zero evidence in the fossil record of gradual "evolution" from a simple organism to the complex species today ... but only variation & adaptation within a species. And yet somehow ... Darwin's Evolution ... was accepted as a fact of Science .. and from that point only all of the Sciences would be based on a NATURAL origin of the Universe & Life billions or millions of years ago. Definitely not a 6 day Creation less than 6000 years ago.
Universal Functions .... explains ..... space, time, Laws of Nature, matter & energy ... are Natural Functions with information like purpose, reason, rules, & design .... that can only come from the Mind of ... a multidimensional, timeless, infinite, nonphysical UNNATURAL intelligence with a mind & freewill. And with Man being the only known NATURAL intelligence with an intellect in a Universe where everything including Man's body ... has clear purpose, reason, rules & design, fully explains why Mankind has and will always ... believe in "the gods" & spirits.
Science through the Universal Functions ... proves ... there is a Natural & Unnatural reality .. and by default the Mind of an Intelligence must be UNNATURAL ( spirit). Therefore the Mind of Man (Natural intelligence) has to be Natural (body) & unnatural (soul) which identifies God of the Bible, Israel & Jerusalem ... as the Unnatural Intelligence ... who made the Universe & life ... less than 6000 years ago.
Science (Function) today was developed by Christians from the 1500's, not the Ancient pagan Greeks and Christians are still the majority (just) of Nobel Prize winners. Again, Man( primitive or civilized) has an INTELLECT to always make deductions from observations .. but also has freewill .... to follow & obey God (Torah) or Man (will, nature, ways, beliefs, ideologies).
There has not been any major leap in scientific knowledge .... because the Sciences today are dominated by Atheists who have always rejected the Machine Analogies used by Christians ....and only seek a NATURAL explanation of natural phenomena .. making up story after story with the title of "theory" to prove their belief that the Universe is 13.8 billion years old .. and nature & natural processes can make, operate & improve Functions and laws/rules.
Emergence is Humanist Liberal bs. And it is Liberal Humanists who are currently running & ruining ... the free civilized "Christian-based" world.
Hm, so you mean LLMs or neutral networks in general are not "good code" because they can produce "hallucinations" which I'd consider unintended "*emergent" behavior?
Didn’t wolfram already solve this?
Solve? Dunno...but the emergence found in the cellular automata concept is 100% Wolfram. Kind of astonished that his name wasn't mentioned...it's like talking about general and special relativity and not mentioning "that guy again ".
@@KravMagoo Emergence from cellular automata as a concept has been there since Conway's game of life.
@@KravMagoo100 % Wolfram ? That’s ridiculous.
Sure. Just ask him, he'll tell you.
You can’t “solve” something which isn’t a clear question. And Wolfram goes into a much deeper concept in his book: “A New Kind of Science”. There he talks about mostly how complex behavior can arise from extremely simple rules, counterintuitively. And also about how most non-obvious patterened or nested systems are “computationally irreducible”, which essentially means that there are no shortcuts regarding calculating the system’s state other than simply performing the computation which it’s defined by. This has very far reaching implications in physics and other fields. But all that is not completely relevant to this video’s topic, where that is more about system’s tendency to form patterns/emergent phenomena as we go up scales, for which we use different models than the underlying, fundamental dynamics (e.g. Navier-Stokes equations for macroscopic fluid behavior vs particle physics to express the dynamics of each fundamental particle that each atom that each molecule of that fluid is made of)
I have studied the Physical and Natural Sciences for over 60 years & can't remember ever having enjoyed presentations more. Your brief offerings are more like being immersed in a thought provoking song than a dry didactic lecture. Nicely done as always Bee.
Speaking as a research mathematician (PhD 1979), this is the clearest, and most correct and complete explanation of emergence not requiring advanced mathematics I have ever encountered. (Of course, we expect that from Sabina.) I was also a computer science professor, and I find it interesting that systems analysts working on very large computer programs have to "offload" some of the "bug detection" onto the end users, because they are emergent.
I dont understand why emergence is made up to be so mysterious and unknown. I dont imagine that things on a large scale dont just follow the rules of what is happening on the small scale inside. Am i wrong in thinking that new and advanced behaviour on a large scale isnt in fact new, but just complex application of the basic rules on the smallest scale?
Complex behaviour is just so complex that we create simpler abstractions. These simple abstractions are usefull, we can just look at the large scale thing and not have worry about every single particle that it is made up of. Why do we make these abstractions so mystical when they arent laws of nature, just approximations of complex structures that do follow the laws of nature?
I feel like there is something im missing here...
It has nothing to do with being mysterious and everything to do with emergence being codified and predictable. The goal is to use emergence as a mathematical/physical tool and not just as an intuition.
@@jmbreche I think I agree. But people quite often use the term 'emergent' much like they use the term 'god'. No further explanation required. Are the different levels of scale connected? Of course yes.
because you "loose" some information during separation of scales. Imagine that in the context of quantum size objects there is determinism, than at the size of "our" scale it is perceived as random or chaotic. In our scale we have laws of mechanics, thermodynamics but it is possible, that on the bigger scale, our own world could be perceived as quantum. Some of the information is lost between scales and it has physical effects (for example thermodynamic). It is possible that in other scales information has a mass or information is equivalent of matter or that there is a process a information-energy conversion. That's why emergence is a good name for this "information phase shift".
I agree that consciously or not, scientists seem to smear out the whole topic. It is not difficult to present it clearly. There are two basic possibilities:
1/ In reality, there's only a single fundamental layer. The universe doesn't 'know' or 'care' whether the fundamental 'pixels' are lumped into cells or planets. Exactly like cellular automata don't care about the macro shapes of the pixel lumps - they simply transform from frame to frame, pixel by pixel. In this case, scales are only hierarchical levels of abstraction in _human thinking_. They are not something 'real' out there.
2/ A given scale is truly _irreducible_ to the smallest scale (or any other scale, or combination thereof). There are different laws that modulate the whole at different scales (this direction is investigated for example by Michael Levin). This would mean that, for example, in Conway's game of life, there would be certain gliders that can _never_ be simulated using only the pixel rules. In the same sense, this would mean that the purely physical laws of attraction and repulsion of particles would never be able to produce the behavior of a biological cell. This has the interesting consequence that our cognitive flow may also be irreducible to other scales. This doesn't mean that our thinking process is independent of other scales but only that there are certain aspects of our intuitive steering through the cognitive landscape that cannot be explained as merely the output of other levels.
Rationality does not come from irrationality, the burden of proof is on those who say it does. Emergence is a deus ex to do away with the need for God. A blind faith in magic aka that probability can produce rational outcomes.
To everybody interested in this topic I highly recommend the two books "Gödel, Escher, Bach" by Douglas Hofstadter and "From Bacteria to Bach and Back" by Daniel Dennett!
Also: 'The Collapse of Chaos' by Ian Stewart & Jack Cohen. (And their 'Figments of Reality') 👁️🗨️
just watch planet of the humans instead
Agree, and would add Sabine´s book "Existential Physics"
neither of those authors or books really ctach the nature of complexity. Though a good starting point
Also, Deacon's "Incomplete Nature."
You're great. I loved that topic. awesome job as always!
Really enjoyed this one
Thanks for all your work
New???!!! That’s Stephen Wolfram “New Kind of Science” book that was published 20 years ago!! 😢😢😢
The way that I’ve seen emergence framed as “separation of scales” seems problematic to me. Ultimately, more simplifying models can be used effectively at larger scales because with increasing scale, less resolution tends to be necessary for usably high accuracy of analysis. But that doesn’t mean the scale “below” disappears, only that our resolution of imaging lacks perfect precision but remains workable.
But in some cases a low resolution of imaging remains workable in others not. I guess what they are trying to do is use this fact for a definition of emergence. Of course now you need to define what 'workable' means.
No one is saying the scale below disappears. But in some cases, it becomes irrelevant. All this will make more sense if you study complexity science.
You can think of the emergence between scales as the result of two statistical effects. Combinatorial effects create new behaviors at large scales while the law of large numbers flattens out the details of the level below. Both of these effects are only on average if they exist in a given setting
@@DeLambada As in, some system phenomena can be considered more “emergent” than others based on how effectively those systems can be described without any reference to lower, underlying scales of objects? So, “emergence” is more of an adjective than a noun? Which ultimately depends a lot on the system and the complexity of the constructs used for modeling. But, like, all of this boils down to the choices we use in describing systems and what level of precision / accuracy we want, which feels subjective in a way that it feels like we’re missing something on how these ideas properly connect to objective knowledge and science.
Well, to be fair, in most applications you don't need to take electron spin or ionization to make a program work, or as Sabine pointed out, in order to model orbital mechanics for time scales longer than human civilization.
Even a thing like tic tac toe works with only marks on some surface. It's whole and complete without taking any scale into account, just certain rules and bounds with very precise limits. Despite this it's still the product of the extremely complex quantum to meter scale object that is a human with a mind.
This is brilliantly explained! Thank you for this. It gave me a new perspective on the science of emergence.
I would love to hear you about what Ilya Prigogine called "dissipative structures", also treated in Bobby Azarian's "The Romance of Reality"
Sounds like this paper has connections to the ideas in Wolfram's book "The Second Law."
indeed, but what happened to rule 30? Not detected by the new algorithm?
The Second Law was explained in a perfect way by Arieh Ben Naim in his book series about Entropy ( 1) Information Theory, 2) A Farewell to Entropy, 3) Entropy Demystified, 4) Information, Entropy, Life and the Universe)
Thank you for this
Thanks from the entire team!
Great show. This is a sweet spot for you.
Stephen Wolfram talks about rule 30 a lot. He is lately proposing a new kind of mathematics and theory of everything based on this notion of computational equivalence and computational irreducibility and notions of discrete space, brancheal space and rulial space and multiway graphs.
Sara Imari Walker and Lee Cronin have a new theory about complexity called Assembly Theory which also sounds similar to the above.
The notion of entropy is also similar in the sense that the fraction of micro-states (from the phase space) that map to what we would course grain and identify as the same macro-state. For example a water in a glass could be said to be at 50 degrees Celsius temperature, yet there may be many different arrangements of water molecules, zipping around at different speed that result in the same temperature.
An every day´s pleasure, to follow Sabine´s thoughts. Astonishing how much content she compresses in five minutes. This one I have to watch more than one time. 😊 (This is a bit like "Mehr als nur Atome")
Why do you have a problem saying the name Stephen Wolfram?
Very interesting! The first time I encountered this discussion of different levels, or scales, and their relation to the concept of Emergence was in Karl Poppers (with John C. Eccles) "The Self and Its Brain" from 1977.
Hi Sabine, this is my research area.
Emergentism is pretty well disavowed outside of biology. It likely has more to do with how we draw the parameters of a larger-scale system, such as what are screened off.
I think you explained this all very well. Thank you for the video. I would love to see more. If I could recommend some topics: causal closure, scientific reduction (especially radical reduction), and the ontology of levels.
The beautiful, shimmering patterns in flocks of flying starlings are a glaring way to get the concept of emergence across. The patterns are the result of a few simple rules each bird follows in regards to other starlings flying close to it. A single starling by itself would give no indication whatsoever of the patterns that flocks exhibit -- the patterns are emergent. Here's a National Geographic video of them in action:
czcams.com/video/V4f_1_r80RY/video.html
Absolutely!
Great example!
Stephen Wolfram's Rule 30 got slipped in there.
Fascinating, as usual Sabine !
Very good video, but it should have included at least one mention of the condensed-matter-physics(CMP) field, which is basically synonymous to emergent phenomena in physics. The concept that the macroscopic properties of a system do not depend on its microscopic details is the widely used concept of universalities in CMP, for example in phase transitions, localization phenomena etc..
I defer to Wolfram on anything in this domain…
I'm sure one of the pictures was Rule 30 ie a non-repeating aka random emergence out of a few simple rules.
I'm a little surprised that an even simpler system was not postulated than 25 physical units (itself almost certainly a limitation of current knowledge) and starting with a more logic/rule based starting position.
@@commentarytalk1446 Yes, that was Rule 30.
I have had a hypothesis that gravity is emergent. Rather than a fundamental force with an associated particle, it's a perceived force much like a centrifugal force. However, being a lowly youtube, layman commenter, I don't have the resources to test such a hypothesis. Also, I could be way off in my understanding of particle physics as well...🤷♀
Lmao
@@rayparent1 I would appreciate being corrected, as I said, I am a layman. More productive than just laughing.
@@thisisbriannaandrea Nothing to laugh about, some others had similar thoughts too. But of course there´s a lot of research on quantum gravity.
@@thisisbriannaandrea most people that talk like you in my experience think they know better. I laugh because you talk about testing without being intimately aware of the mathematical structure of our theories. Which sparks my crackpot detector.
Maybe ive spent to much time talking to flat earthers and you were genuine. If so this is an open area of research
@rayparent1 I agree! I don't know better which is why I stated it as hypothesis given my limited understanding of particle physics. I don't claim it to be definitive. And unlike flerfers, I am open to new information, evidence and experimentation. And will revise or toss out my hypothesis based on new information.
4:33 I have a soft spot for cellular automata. I used to play around with a Lego Mindstorms EV3 set (a robotics kit), mostly writing small games and gadgets to use on the base unit, turning it into a crappy Game Boy. Tetris, Snake, Mineseweeper, etc. I also put together a cellular automaton program just like in the video. I even made a barebones version of Conway's Game of Life for it, but ran into massive performance issues. Depending on the board size chosen, each frame would take several seconds to render 😅. Good times!
This is so enlightening!
Will this 'complexity model' would work equally well if there are no "building blocks"? In other words, would the model be the same if the elementary particles themselves are made of smaller (and smaller) particles?
(BTW, Thank you Sabine for your videos. I wrote you an Email, from Tomer Zimmerman, I hope it was delivered)
Computer Science here. Just as we're now trying to understand why and how - specifically - LLMs encode what looks like some form of experience, we're trying to understand emergence. And we see that they are too deeply tied together to separate, and this goes beyond inter-mixing of any two resolutions/scales.
My take is you needed the fundamental rules (whatever they turn out to be) to make matter/energy, and you needed matter/energy to make life, so there's more rules for that (fundamental and emergent) which are tied to the fundamentals at the very bottom.
From life we get experience, the point of which is to expand. I would not be surprised to find that is yet another jump-off of some kind.
If you expand, do you become lumpable?
The only “experience” is the dataset, and the only understanding are the connections from the dataset. So models succeed to the extent that they contain the dataset accurately, and that cannot be abstracted. It’s not that mythical
@@Real-HumanBeingmore or less abstract or mythical than "the only understanding are .."? It's IS not are; the subject is understanding, singular, not connections - plural.
The fascinating thing about dogs IS .. that they are so good at understanding how to manipulate humans, not ARE ..
Abstract, mythical? No. Grammatical? Yes.
Simple, long understood? Yes.
Fashionable incorrect? Yep!
Lawyers, journalists & other professional wordsmiths doing it? Yep.
Why? Because fashionably incorrect is a socially constrained or motivated emergent property of simple rules incorrectly scaled!
Easier to be fashionable incorrect than unpopularity correct right?
Try ..
..unseasonable weather =
unseasonal
.. rightfully so = rightly so
.. living life to the fullest = full, fuller, fullest (really?).
So, fashionably incorrect is an emergent category created by misapplication of simple rules.
Does nature do this too, or just too clever conscious beings?
Presumably misread & uncorrected DNA, or mutations, creating novel variants is analogous, and grammatical errors are subjected to social correction?
Thus, I am but an agent of social natural selection, So please don't shoot the messenger!
@@chrisfreebairn870 shut up
I’m not big on these more recent videos not ending with a strong conclusion and transitioning directly into a sponsor segment. We need the takeaway message to be stated in a way that we recognize it as the takeaway message, not as a transitional sentence into a sponsor message.
1) pay for content if you don’t want advertising - of course not! I’d also want knowledge & understanding to be free. Unfortunately our societies don’t value that. They value endless consumption & greed for some & grueling drudgery of work - if lucky, for the rest of us.
2) the conclusion was clearly stated twice in the beginning. Make the effort to rewind if you’ve already forgotten it.
Huh, cyber sec researcher here, and this is of great interest for what I get up to.
With the tcp/ip stack we’ve taken this idea of separation of ideas as an explicit rule of network architecture, ie you don’t need the hardware layer to understand the application layer, or vise versa
It’s interesting since we haven’t updated it in a while too, with emergent cloud computing and edge functions, it would be an interesting branch of research to design emergent computing concepts beyond our current explicit stack
This is rooted in Wolfram's cellular automata work. For anyone interested, he published the book, "A New Kind of Science" with a follow-up in 2023, 20 years after the first book was published. It's an excellent book; my degree is in computer science and I've been fascinated by cellular automata since I first discovered them in the early 80's so stumbling across Wolfram's book made my day.
Does he explain how cellular mechanisms can form when there is no evolutionary pressure to create building blocks of said mechanism that does not yet exist because evolution has no foresight?
Be nice, Sabine! It's not"lumpable", traffic flow just has big bones, okay???
I would go further to say that LLM processing power allow s for reduction in lumpability. And every decrease in lumpability corresponds with an increase in predictive power. Delumping means moving from word lumps to granular 1 dimensional scales. Then those scales can be combined in increasingly complex ways to allow for multidimensional analyses that increase predictive power AND computational efficiency. Multidimensional gradient scales > lumpability.
Keep in mind computer programming also happens in lumps. Most notably the binary lump. 0 or 1 instead of 0 through 1. True or false instead of 0 through 1 true and 0 through 1 false.
Ya gots to get your own show -- you just lumped too much in two paragraphs, and my head feels bumped.
@@pnf197 😅👍
@@Thomas-yl8lb LLMs say: " 'Fart' goes well with 'brain' "
Are you having it?
I agree, and very good insight here.
@@pnf197 Doing a show is a lot of effort. I can respect the heck out of Sabine for doing it for us, but I couldn’t do it myself. 🤣
What a wonderful video - many thanks Sabine.
So pleased to hear a scientist talk about ideas like Emergence and Lumpability - these are concepts that Engineers have had to manage for decades (although we might refer to it as propensity for coupling) . Both Engineers and Scientists rely heavily on the scientific method, but the way they approach complexity is a key defining difference: Scientists are inherently reductionist - as they seek to remove complexity in the pursuit of causality. Engineers seek value and approach complexity from the vie of behaviours to manage at each strata of organisation. Both need to understand Emergence as a superimposed phenomena in its own right.
Great video Sabine! Thanks. I learnt that I'm highly lumpable.
While a programmer definitely doesn't NEED to know how a computer works, it definitely helps knowing that when one wants to optimize their program, if they are using a low-level language.
A programmer needs to know a few things about computer architecture, if he bothers about the performance of his or her programms
Indeed, and I would apply it a bit to high level languages as well. Understanding some core CPU concepts is helpful when trying to explain (for example) a stack overflow and how to avoid them, and why threading has the limitations it does.
True, but I think what Sabine meant was you don't need to know at the gate or silicon level, just the functional logic level to effectively write programs.
Do you need to know how the transistors work though, or the quantum properties of the electrons?
@@tomschmidt381 arguably, this can be useful information for general IT. Knowing how the gates work can explain why SSD has a generally fewer read/write cycles. But I guess that this is stretching it....
Like the idea of psycho history, you don't need to know the behavior of a single person you understand the broad circumstances and the group. You don't understand each individual particle you study the nebula and it's circumstances to understand where it's going as a whole
But that's not how societies work, as it was explained in the video. Individual humans do have influence over large scale events. At the very least they can move timelines around, delay or bring forward events. And that can have massive consequences, when the order of events matter.
This is more chaos theory, which has very different rules.
@@andrasbiro3007 did you read foundation? Second foundation? Foundation and empire?
@@ryanatkins5736
It's called science fiction. And Asimov wrote the first book 10 years before the discovery of chaotic systems.
More on this please!
(I’m not a computer scientist, but I think computation is more fundamental than particle physics)
Computer hardware is completely independent of algorithm. Implementing computers with electric circuits is common but a computer implemented with pneumatics, hydraulics, mechanical is absolutely possible. Slow, huge, expensive ... but possible.
I hope your daily release model has worked out for you Sabine. I’ve definitely grown to like it more. I feel like it’s given you more time with each topic, even just a minute or two
Sometimes we humans reach a zenith, as we ourselves are emergent 'beings' or 'beings of beings' as in the Lumpability Model. Sabine has reached a zenith and emerged as a proficient Lumper of Humor and Science. What portends now?
A lumpen proletariat ?
@@DinsDale-tx4br a lumpen elites (for symmetry)
As a “Lumpable” creature, I find comfort that scientists also struggle understanding complexity.
Husbands have been working on that problem ad infinitum and while we have workable general model to understand the female mind, we definitely don’t have the details figured out.
Women are attracted to power, they love men for their utility, they are willing to deceive in order to get what they want from you, and they judge things emotionally rather than rationally. I think that summarizes the main differences between men and women.
Stop begging for acceptance in a youtube comment section
@@neo-filthyfrank1347What are you talking about?
I made a mildly humorous joke riffing on Sabine’s mildly humorous joke. Maybe you didn’t watch the video or just missed her dry humor.
@@Nathan-vt1jz The type of joke one's inclined to tell belays the underlying psychology.
Many humans briefly enter the state of highly Humpable then after a period of entropy , emerging into a state of solid lumpability
Much of Mario Bunge's work in the second half of the last century revolves around material systems and emergent properties resulting from their rules of interaction. In general, in complex systems (if possible) it is not trivial to deduce emergent properties from component properties or interaction rules.
An example is the structures that arise in the flock flight of starlings in which each individual averages the flight orientation of its approximately 5-7 nearest neighbors. A simplification of this to be able to work statistically on a computer with flock phenomena is the Vicsek model.
This is very interesting.
I've always thought of emergence as a thermodynamic process.
Whatever structure/ process releases heat in forming is subject to being broken if the heat it releases is available in the environment.
When a structure forms that requires more heat than is usually available it remains stable and can accumulate additions based on how stable those additions are. Snowflakes for example, or spontaneous polymerisation of nitrogenous bases.
A grain of dust can act as a substrate for water vapor to initiate formation of an ice nanocrystal but it's the thermodynamic stability of the additional water molecules to the crystal that directs the structure and symmetry of the delicate snowflake that grows from it.
In abiogenesis, there seems to be a bias for there being some "best" way for self catalyzing nucleotides to form by spontaneous polymerisation, but all that appears to be necessary is an environment that favors thermodynamicly stable structures, which pretty much implies that there were multitudes of differently viable environments competing and colluding together to produce the first primordial living chemistry and the first reproductive proto-living constructs by assimilation and çonstructive interaction, eventually resulting in crude homeostatic assemblages... Living cells.
Through it all, the structures that perform the most work tend to compete most favorably and lead to the highest dissipation of potential.
The highest entropy structure/process wins.
More complex structures/processes tend to require more available potential, and tend to increase in complexity so long as there is sufficient available potential. Evolution then, is just a competition for the best heat engine.
So, they've just discovered Conway's game of Life? Bless...
Wolframs ' a new kind of science ' came out about 30 years ago and is by far the most thorough investigation into cellular automata
I bet you they are already familiar with this
@@xmathmanx Yes. Also, Wolfram was a team leader in assorted Darpa projects to generate new Quantum Computation & AI technologies. Seems like those were successful. NKS is an active thing. Perhaps someone needs to write another book on this topic.
@@energyscholar I never heard of wolframs association with DARPA and it doesn't sound likely to me
@@xmathmanx Of course you've not heard about it! It's covered by NDA! I'm sharing inside information right now.
His first Darpa project was in the late 1980s, when one of his CA rules were used as the cryptographic basis for next-generation NATO radio communication.
Later he lead a Darpa project starting in late 1990 to build a new technology to crack Public Key Cryptography. Other project scientists included Stuart Kauffman, Murray Gel-Mann, & Brosl Hasslacher. Gel-Mann had to withdraw for health reasons and was replaced by a young Aussie super-genius. This project SUCCEEDED beyond wildest expectations and was HEAVILY CLASSIFIED. It's created a new form of Quantum Neural Computing that has lead directly to the current breakthroughs in AI.
This is history-making stuff that's not documented publicly.
I could go on but will stop with those two.
I've had the privilege of interviewing quite a few people connected with these projects. Much of the work took place at the New Mexico Center for Complexity.
Lol, "Doesn't sound likely to me". Funny!
His particular special talent, beyond innate brilliance, is how he enhances the effective intelligence of those with whom he works.
Do you think the transition from one of these levels of complexity to another would involve what we would usually consider random errors? Where would these 'random' events be accommodated in this model?
Love your content, Keep keeping us updated on the latest science news, Thank you :D
I'm not sure what you mean by error, but transitioning from one level to the next can (and usually does) bring in some noise, that's remaining fluctuations from the underlying levels that isn't resolved. I mean, think of the traffic example: you'll get statistical predictions, but if you don't know exactly what each driver is doing, you will inevitably have some outlier events.
I recommend looking into new Noise based thermodynamic computation. It applies what you’re implying I believe.
That's an interesting thought considering error and noise as Sabine said. I was immediately thinking about the transition from quantum to relativistic and the collapse of the wave function where the left over uncertainty needs to be manually reset.
Left over uncertainty, noise, error... We seam to encounter this often in any conversion or transition. Analog to digital is a good example in my head. In that conversion the noise (leftover precision or error) is discarded, but in the real universe you would expect that it has to go somewhere.
Fascinating. According to Wikipedia (I know, I know…), the term “lumpability” has been around since 1976.
It originates from the area of modeling and simulation of systems, a field I briefly taught to future teachers. However, we used methods and terminology from the former Czechoslovakia, which was “a bit” different, so I never heard this term or any similar ones before.
I guess one learns something new every day…
Once again, another video that makes me think. As an older lumpable guy, I'd like to thank you for all your hard work. 👍🙂
"Lumpability" is my new favorite word.
Also, Stephen Wolfram (the Mathematica guy) got a start on the cellular automata side of this in his 2002 book, _A New Kind of Science._ it's a fascinating read, and now available for free on line as a PDF. (I spent like $60 on it some years ago, but who knew?)
Complexity science is older than that.
I have a well founded maths & physics background with specialization in IT and sincerely, I have read it (A new kind of science) and I've got nothing new, it is extremely boring and : OK, complexity could emerge from simple rules, Boltzmann knew it! He showed how Entropy could emerge from the atomistic structure level, Claude Shannon's Theory of Information was the key to understand it. So what with Wolfram? Now they have discovered a new term "lumpability" when IT has the more proper "encapsulation" to hide complexities when you don't need them
@@DanielMartinez-ss5co Boltzman operated in adiabatic systems, Wolfram put the problem in a wide context of any system.
@@DanielMartinez-ss5co I spent my entire 40+ year career in I.T. and software development, so I'm qualified to say that surely your credentials prove that Wolfram is full of shit.
Right.
"Boring" is a personal assessment, not a universal one. I found the book intelligent and engaging, but my physics background is merely that of more than 30 years as a passionate layman, so what do I know?
Gee, you win.
@@jan.kowalski You should read Arieh Ben Naim books about Entropy, not Wolfram that is “Words, Words, Words”
"Software in the natural world: A computational approach to hierarchical emergence" is a research framework that aims to understand complex systems by looking at how they process information and perform tasks.
Key Points:
Hierarchical:
A hierarchy means that smaller parts are organized into larger systems.
Research:
This is a way to study and understand complex systems.
Architecture:
The architecture of a system refers to how its parts are organized and work together.
Macroscopic Process:
A macroscopic process is a higher-level process that involves multiple smaller processes working together.
This approach helps us understand complex systems by looking at how they process information and perform tasks.
Cellular automata are equivalent to a subset of Turing Machines and a brief study of Tibor Rado's article on the Busy Beaver Function will offer a clearer and more general understanding of why we can't explicitly predict the outcome of iterative computations per se. The keyword here is 'explicitly'.
Bringing these domains together was novel for me and the narrative made it quite clear. Thank you.
It looks to me these ideas are Stephen Wolfram’s ideas. He published the cellular automata long ago and most recently he and his team talk about observer theory. How this new paper is different from Wolfram’s team ideas apart from the mathematical particularities? I found observer theory the most convincing theory of everything.
I was waiting for Wolfram to be mentioned in the video 😮
Wolfram is utterly naive, regarding computation, information,, and meaning. The three central counterarguments are:
1. it is impossible to xtract meaning from something
2. the claim of fundamentally computational disregards Heisenbergs principle
3. Information is not received, but a result of perception
That theory is neither convincing nor leading anywhere. particularly it is not explaining the mechanism by which complexity arises
Yep, I posted the same thing. This is straight out of Wolfram's A New Kind of Science, except not as advanced. Still, I'm happy to see that the ideas are spreading. People should realize that ANKOS explains both Relativity and QM in terms of simple rules, and if nothing else, it's remarkable that we have ANY theory that can completely resolve those two into the same simple model, without having to invoke some sort of "AND THEN MAGIC HAPPENS", as we do with so much physics ("and then the particle splits at some random time, for magical reasons").
@@monnoo8221 Sure he is. He was also the leader of multiple highly successful Darpa projects to generate Quantum Neural Computing and AI. His books, which are HAMSTRUNG by Non Disclosure Agreements, only say a FRACTION of what he wanted to say. Dapra would not let him publish the key insights & implications for 'national security' reasons.
@@cuthbertallgood7781 Sure is. I'm shocked this knowledge has been so slow spreading.
We also have the word 'granularity' for that; but where is the hubris if you don't coin a new unsavory useless term for an exsiting notion?
I call that, "hubricity"
@@Boneless_Chuck I shall name this novel concept of writing chuckleworthy things "funistry"!
@@Boneless_Chuck well posiformed.
Some wet sand just whispered that those 2 things aren't the same.
@@TheWooTubes 😂
It has to do with time, and understanding what creates time and the geometry involved, even in the barest notion, is quite revealing. If you are really interested in this topic, you really want to look into Stephen Wolfram, who essentially spear-led this way of viewing the universe through A New Kind of Science.
In artificial neural networks, the activation dynamics of non-trainable variables is strongly coupled to the learning dynamics of trainable variables. During the activation pass, the boundary neurons (e.g., input neurons) are mapped to the bulk neurons (e.g., hidden neurons), and during the learning pass, both bulk and boundary neurons are mapped to changes in trainable variables (e.g., weights and biases). For example, in feed-forward neural networks, forward propagation is the activation pass and backward propagation is the learning pass. We show that a composition of the two maps establishes a duality map between a subspace of non-trainable boundary variables (e.g., dataset) and a tangent subspace of trainable variables (i.e., learning). In general, the dataset-learning duality is a complex non-linear map between high-dimensional spaces, but in a learning equilibrium, the problem can be linearized and reduced to many weakly coupled one-dimensional problems. We use the duality to study the emergence of criticality, or the power-law distributions of fluctuations of the trainable variables. In particular, we show that criticality can emerge in the learning system even from the dataset in a non-critical state, and that the power-law distribution can be modified by changing either the activation function or the loss function.
Terence McKenna talked a lot about the mechanisms of complexity conservation and generation (concrescence)
I AM THE HIGHEST LUMPABLE!
I’m a physicist doing a master degree in computer science exactly because of this kind of ideas. You can’t imagine how exited all this recent development is 😍😍😍
LUMPABILITY = integration or summation of states, dimensions -- a syntropic process!
Complexity is dual to simplicity.
Micro is dual to macro.
Increasing the number of dimensions or states is an entropic process -- differentiation or reductionism.
Decreasing the number of states or dimensions is a syntropic process -- integration or holism, LUMPABILITY.
Increasing (divergence, entropy) is dual decreasing (syntropy, convergence).
Syntropy (prediction) is dual to increasing entropy -- the 4th law of thermodynamics!
Teleological physics (syntropy) is dual to non teleological physics (entropy) -- physics is dual.
Integration is dual to differentiation.
Reductionism is dual to holism.
Homology (syntropy) is dual to co-homology (entropy).
"Always two there are" -- Yoda.
I hear "and they call that property 'lumpability'", and as a computer scientist, it warms my heart to see something sensibly named
I am not sure that we have a lot of evidence for emergence as a principle. I think small building blocks could cause "complexity" to emerge, but it could also be reversed from all we know.
The key question is, when you plot different resolutions like in the video, ftozen at one point in time, and then start evolving them, are all resolutions evolving simultaneously or not? If they are, it's hard to put a direction that must be implied by causality.
I don't know what you mean by a resolution evolving, sorry, can you explain?
The separate resolutions aren't different realities that are evolving in unison, it's all one reality that evolves, we just have different descriptions as a matter of convenience. I don't think there's a good case for downward causation, which seems to be what you're implying. If moving water molecules are one description, and waves are another description, I think it's clear that all that really exists is the atoms, and waves are a higher order concept that we use because motion of waves is what we perceive, but I think it's a mistake to say that because the atoms and the waves evolve simultaneously, that causation can go the other way and the waves could cause the atoms.
@@generichuman_ yep, make it flat, make it into dus, and then try explaining. usual positivist crap
@@SabineHossenfelder Yes, I might have hyper-focused on a very specific part of the video, sorry :D. I meant if we look at the representation at 1:37, which was very interesting to me, we see different resolutions of "the world", so to say. These are still representations of the same "world" and in the same space, and (I think) same time - i.e. if we somehow start evolving the "world" over time according to some laws, all of the resolutions should evolve simultaneously.
So if that is true, it seems hard to say if the direction of causality goes from deepest resolution upward, ex from particle physics to the solar system, or the other way around. It seems like it could be the other way too, for all I can tell.
Though it might be only me, I'm a data scientist, not physicist. :D
@@aleksandarjovanovic9080Surely, if you are a data scientist, the laws of physics are just data compression from data about the universe :-) I think you said "particle physics" when you really meant "particles". Physics is the study of reality, not reality itself.
Could this apply to particle accelerators as well?
This is quite fascinating. It's like trying to understand something that appears to exist for the sole reason of not being understood.
@4:52 Also the block formations of the Great Pyramid when using penetrating radar of sorts if I recall. I remember seeing that pattern on another CZcams video somewhere of the Great Pyramid. IDK.