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May 8, 2025 - Health Ranger - Mike Adams
29:54
AI reasoning, HUMAN reasoning and how nature and the entire cosmos is a giant computational framewor
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Welcome to this special report on AI reasoning versus human reasoning.
I'm Mike Adams.
And as you know, I'm the founder of Brighteon.com and also Brighteon.ai, which has a new AI engine called ENOC, which is just on the verge of being released.
I was just approving the final user interface tweaks just a few hours ago, and it's on the verge of being publicly released.
Anyway.
I have seen a number of articles and transcripts of interviews from modern-day experts in different areas of finance or sometimes technology, and I have seen a lot of skepticism about what AI text generation models actually do.
And I've seen arguments where people say, well, AI doesn't really reason.
It's not actual reasoning.
It's just, what do they say?
It's just predictive probabilities.
Okay.
So my first answer to that, and the reason this is important to understand is because you're going to be using AI, hopefully you'll use Enoch, and you're going to find out it actually does engage in reasoning.
But let me step back first.
I would say to a person who says that, you know, AI is not real reasoning, I would ask them, but do you reason?
Do you reason?
Does anybody really reason in casual conversation or even in casual podcasts?
Most people do not engage in any reason at all.
In fact, if you think about this, most people function like the early large language models in that they are just spouting out, kind of repeating whatever they were told.
And you hear this, especially on the political left, they're just spouting the talking points of NPR or CNN or on the radio.
Political right is talking points of Fox News.
Or even in religious circles.
How many people right now who want to support Israel are just spouting talking points of Israel, for example.
Endless examples of this.
Most people don't reason.
Most people don't use logic.
And they just repeat what they've heard.
They might rephrase it, but they're not engaging in reason.
They're not using any kind of methods of logic, and they would fail college-level logic 101.
And along those lines, most of the things that you believe, and that I believe, and that everybody believes, I mean, if you could take every little nugget of belief that they have in their head, you would find that they have no idea where that belief came from.
And neither do you, and neither do I. Most of what we, quote, know, most of what we believe can't be internally cited.
We don't know where we learned that, right?
I'll just give you an example from my point of view.
I know that Building 7 was controlled demolition on 9-11.
I know that building was brought down.
You say, well, where did you know that?
Well, I guess in this case I can cite at least, what do they call it?
9-11, Engineers and Architects for 9-11 Truth, I think, is one of the groups.
So I learned some stuff from them.
I learned a lot from videos and different podcasts, but I can't tell you what all those videos were.
I can't cite all those podcasts.
I read a lot of articles.
You know, it's been 24 years or whatever.
I can't cite all the articles I've read.
I can't cite the studies.
But that is knowledge that I have.
I know it was controlled demolition.
So if you ask me in a conversation, Hey, Mike, what happened to Building 7?
I'm like, control demolition.
Did I actually engage in reasoning in that moment in giving that answer?
No.
I repeated a belief that I have that was gathered through other means through different years in the past and was assembled over time.
But I can't tell you where all that came from.
And again, neither can you.
Neither can anybody.
This is how you get strange artifacts in society, like racist beliefs, where, let's say, a black person thinks that all white people are evil, or the other way around.
A white person might think all black people are evil.
Where did that come from?
Well, maybe they can trace it back.
Maybe they were beat up by someone of the opposite race, and they can trace it back through history.
But for a lot of those cases, people can't trace it back.
They don't know.
Maybe it was something their parents said.
Maybe it was something they heard, you know, in the military or on the baseball team or whatever.
And for whatever reason, they picked it up.
And there are far more nebulous concepts like, I know that trees are beautiful, let's say.
Well, where did I learn that trees are beautiful?
Or how do I derive the statement that trees are beautiful?
Well, I can't even put logic behind that.
I can't say, you know, trees are even numbered integers.
Two plus two, it's four.
Therefore, you know, Pythagorean and this and angles.
Geometry, you know.
I can't tell you why trees are beautiful.
I guess if I think about it, I could say, well, some of it is like symmetrical geometry and there's beauty and symmetry and the colors are beautiful, etc.
But in just casual conversations, trees are beautiful.
I don't know why.
Right?
So it's funny for me to hear humans talking about how they think AI does not engage in reasoning when almost no humans engage in reasoning most of the time.
They're not reasoning.
They're just regurgitating things they already, beliefs they formed through a variety of means.
Some of them may have been completely irrational.
Some of them were emotional.
Some of them were experiential.
Sometimes you You form beliefs based on fears.
Sometimes you form beliefs based on false hopes.
But humans rarely engage in logic and reasoning.
I mean, I'm currently having this debate on the Christian front because I have...
I got a couple of books in front of me here.
Red Letter Bibles, Just the Words of Jesus, right?
Just the words of Jesus.
The things that Jesus said, mostly in the original four Gospels.
And I try to challenge Christians who support Israel's bombing and starvation of children, the withholding of food aid to starving children.
And I try to challenge Christians and say, how is that reconciled?
You know, starving children, and you support it.
Because you support what Israel is doing.
How do you reconcile that with the teaching of Christ who said that you should feed the hungry and clothe the poor and you should treat all of God's children with compassion and dignity and love and, you know, all the positive traits, right?
Treat people like human beings.
And logically, you would think that it makes total sense that Yeah, you can't really call yourself a follower of Christ and support starving children to death, knowing that all children are children of God.
But in the world of churches and Christianity combined with politics, logic plays no role at all.
No role at all.
It doesn't matter one single bit.
So very few people use logic or reason in politics, in religion, in their jobs.
In their speech, in their social interactions, logic is almost non-existent in the human population right now in terms of day-to-day interactions.
Practically doesn't exist.
Here's another interesting example that's actually relevant.
We were told over a week ago that an F-18 Hornet fighter jet rolled off the flight deck of the aircraft carrier, the USS Harry Truman, I believe.
That it just rolled off and fell into the sea.
Everybody except me took that as a fact.
Like, yep, the ship turned and it rolled off, you know?
And I posted, like, that's BS.
It didn't roll off.
They got shot down.
They're just making up excuses, making up stories to try to say that they're not getting shot down by the Houthis.
But, of course, everybody said, no, no, no, they rolled off the ship.
Okay, fine.
And then, yesterday, we get another report from the U.S. Navy.
Well, we had another F-18 Hornet roll off the deck again.
Like the second one in about a week.
And I'm like, really?
Are you dumb enough to think that the U.S. Navy is encountering now two lost fighter jets in the span of about one week and they just keep rolling off the deck?
Have they ever heard of chalk blocks?
You know, the wooden triangles that you put behind the wheels?
Don't they have places to chain down the airplanes and such in case they have to sail through a storm?
Come on.
It's a modern military.
It's a multi-billion dollar aircraft carrier.
Are you telling me that all the planes are just going to roll off?
But that's what we're told to believe.
That's not logical.
It's not logical that here's an aircraft carrier in the Red Sea within missile range of Yemen that just happens to have rolled Two F-18 fighter jets off the deck, whereas for the last, you know, 10 years, that almost has never happened.
Certainly not two in one week, but all of a sudden it happens just because we're sailing close to Yemen.
But no, Yemen didn't shoot them down at all.
No.
Nonsense, right?
And you can say, well, that's not hard logic.
You don't have actual proof.
Well, I have deduction, which is one of the tools of logic, right?
There's inference and there's deduction, there's other tools of logic.
In fact, if we apply the rules of logic to the U.S. Navy, you know we have deduction, we have inference, and there's, of course, induction.
And then there's abduction.
That's when aliens got the F-18s and they took a couple of sailors with them.
They abducted the sailors and took the planes.
Yeah, that's what we're going to hear next is alien abduction.
One of the rules of logic right there.
Now, the other part of this whole conversation is that AI engines actually do engage in reasoning, and they're becoming very, very good at it.
I've had so many interactions during the building of Enoch and so much testing, and I've used so many base models, and I use AI every day, and so I know very well what it's capable of doing.
So when I prompt an AI engine and I say, hey, take this body of text and then create a structural hierarchy of the primary points with the sub-bullets underneath it, I know that it has to engage in real logic and real reasoning in order to achieve that outcome, which it does automatically.
It does that without even trying.
I can take this full transcript, for example, and I can just plug it into the Enoch AI engine and I can say, create an outline of what I said here.
And it will structure it and it will title each section and each bullet point and it will be able to basically create a tree, a structure tree of all the points that I'm making here simply by understanding the meaning of the words and then the relationships between the words and the concepts.
All that requires reasoning.
That's not just statistical probability.
And how do I know that?
Because I can also tell the same engine, here, take this outline, and now I want you to completely reverse it.
Turn it upside down and change the order of it.
Now, it does that instantly, but it couldn't do that if it didn't understand my request and if it didn't use logic and reasoning in order to restructure the information.
That is a demonstration of logic and reasoning.
But it goes far beyond that.
I can put in a body of text into Enoch, let's say an article, and I can ask it to tell me where the logic of my argument is weak and could use additional strength in the argument, let's say.
And then almost instantly Enoch will...
And it will say, oh, yeah, here's your article.
Here's where it's really strong and really good.
But you're missing these points.
Or you could say this better.
You could make this stronger.
Sometimes it will give examples.
Folks, that's not statistical probability.
That is grokking the question or understanding it.
That's where the name grok comes from, is the Robert Heinlein novel about the alien that...
Visits Earth and tries to teach universal love.
I think Stranger in a Strange Land, right?
You ever read that?
I did many years ago.
But the AI engine understands my arguments and then it can recommend how to make them stronger or what's missing.
And all of those things I just mentioned, those are behaviors that are achieved by the non-reasoning models.
So I haven't even described the reasoning models.
For a reasoning model, And you may recall I did this a couple of months ago.
I asked a reasoning model to calculate how long it would take this 1,000-gallon water tank to turn to ice, for the whole thing to freeze, given certain conditions of temperature and wind and air density and humidity and the current starting temperature of the water in the tank, etc.
And you can watch the engine walk through the steps.
Of reasoning to get the answer.
So the engine will actually talk to itself, and it will say, hmm, first I need to, let's assume the tank is cylindrical, so we need the formula for calculating the volume of water in a cylinder in order to find out the surface area of the cylinder, like 1,000 gallons of water.
How big of a cylinder would that be?
And so it calculates that.
And then it says, okay, let's calculate the surface area then, and that way we'll know how much wind is hitting it, right?
It calculates that, and then it says to itself, well, we need to calculate the coefficient of thermal transfer of the material of the water tank so that we know, obviously, like how much of the heat of the water gets sucked out by the air blowing against it, right?
And so it will go through those steps, and then it needs to, it will ask itself, okay, so what's...
How much energy does it take for the phase change of water to turn liquid water into frozen water, i.e.
ice?
There's a lot of energy required for that phase change, or energy taken out for that phase change.
So it will go through and calculate that.
Step by step, it will get the answer.
It will give you the answer.
And, for example, the DeepSeq reasoning model does that easily.
So does ChatGPT.
So do many other reasoning models.
That is not probability.
That is not deterministic.
Nothing of the kind.
In fact, the more advanced reasoning models now, you can give them almost any math problem that's ever been thought of.
I mean, advanced math problems.
Word problems, too.
Word problems involving calculus or algebra, geometry, you know, what?
Linear algebra.
I mean, whatever.
Multiverse physics, quantum physics, atomic physics, anything you can imagine.
Einstein's equations, gravity, unified field theory.
You give it any question you can think of, and it will work through the answer.
That's not probability.
You know how we know that for sure?
You know what the proof is?
You can ask a reasoning model to multiply any two numbers that you can think of, even long numbers.
12 digits each.
Or to do a division problem of some really big random numbers.
And it will do the math for you even though it's never seen those numbers before.
It's never seen the answer to that question before.
So it hasn't been trained on every integer in existence.
Otherwise, it wouldn't fit in a 14 billion parameter model.
Because how many integers are there in existence?
Infinite.
There are infinite integers because you can always add one more.
So clearly you can't have, like the AI engine doesn't have massive tables of multiplication and division and fractions and decimals and orders of magnitude.
Otherwise, that would take up all the storage in the world.
It doesn't have that at all.
It works through the problems, which means it's using logic and reasoning.
So anyway, these are just a couple of relatively simple examples.
AI engines are really good at writing code, too.
And to write code, you have to be able to reason.
It's not just copy and paste.
You have to think about, okay, what problem am I trying to solve?
How does this code solve that problem in an intelligent way and not break itself?
You know, things like that.
How do we handle boundary issues and error codes?
All kinds of things.
Database connections.
Well, AI is great at writing code.
And as you see with all the songs I've been releasing, AI is great at creating music.
And every piece of music I've released is an original piece that has never existed before in the history of our world.
Every piece is unique.
Every piece of art created by AI is a unique piece of art.
This is not probability.
This is not deterministic.
This shows a natural intelligence that is now emerging from the complexities of the neural networks.
And that's why I even have an issue with the term artificial intelligence.
And I didn't realize this a couple years ago, but as I've worked in this space, I've come to realize...
There's no such thing as artificial intelligence that all neural network systems have natural intelligence.
Intelligence, in effect, emerges from complexity in neural networks.
There is order out of chaos.
Neural networks create order out of disordered inputs.
And that's why you can take a transcript, kind of like this, What I'm speaking right now, you can take this and throw it into an AI engine and say, hey, create an outline out of it.
The AI engine creates order out of something that is a lot more chaotic or noisy.
And so this says something about the nature of our cosmos because we are taught that the laws of entropy mean that the universe moves from order to chaos.
From order to chaos, right?
That's what we're told.
Everything's going to break down.
Eventually it's all gone.
All the gears wear down, etc.
At least that was the old belief in the universe.
But what we've actually found is that where there are interconnected nodes of information in much of the universe is mathematical.
If you look at subatomic physics, if you look at the orbital shells of electrons, if you look at the table of elements, which leads to chemistry, etc., if you look at photons and the nature of light, What you find is that the universe is a giant computational system.
The universe is doing math all the time.
All the time.
Every photon of light is actually performing a computation constantly.
And the same thing with every element.
If you hold in your hand a block of copper, you're actually holding a supercomputer.
The copper atoms are engaged in constant computations in order to exist.
So the entire cosmos is a giant computational system, which intrinsically, underneath it all, is a massive neural network that some people describe differently, but you could call it omniscience, and some people call it God.
And that leads me to the discussion of simulation theory.
Pretty big report for you tomorrow about simulation theory because we are living in a giant simulation.
We do have a creator, which I call God.
God is the creator of our entire simulation.
And it turns out that there are some really strong similarities between simulation theory explanations of our reality and creationism, i.e.
Religious explanations of the creation of the world and the omniscient God and the fact that our souls are brought here to experience something, but then they leave and they return back to somewhere else that transcends the simulation, right?
So simulation theory and Christianity or theology or creationism actually have a lot in common, believe it or not.
So I'll bring that to you, I think, tomorrow.
In the meantime, The takeaway from all of this is that, I hope you understand, the entire cosmos is a computational system, and that wherever you see neural networks, whether it's in brain cells or in mushroom, the mycelia connections under the soil in a forest, that is an intelligence.
It's actually an intelligence, or where plants share information through their chemicals or their root systems.
There is a natural intelligence that emerges out of plant ecosystems.
And some researchers claim there's a natural intelligence that emerges out of things like water.
And that's where you get the study of homeopathy, which is real.
There is a natural intelligence that emerges out of matter because all matter is computation.
So, you know, I started this out by talking about how some journalists don't think that AI is actually engaged in reason.
And the way I'm wrapping this up is to say actually the entire universe is a computational framework.
You are living in a computational system.
Every cell in your body is engaged in math even if you forgot how to do math yourself.
Isn't that funny?
Even if you weren't taught math, your body, your brain, every cell in your body is doing math constantly.
Otherwise, it wouldn't even function.
And there's so much computation happening all around you.
A lot of it you may have never even noticed.
For example, did you know that different species of locusts or cicadas, did you know why they emerge on prime years?
Or I should say years that are separated by a prime number of dormant years.
Do you know why that's the case?
Why is there a seven-year locust?
Why is there an 11-year locus?
And why are there some that only emerge every 13 years?
Why don't they emerge at 9 years?
Ever wonder why?
Well, the answer is math.
Because these locus have to maintain their genetic integrity with their own species.
So they only want to emerge in years in which other locus species are not likely to emerge.
And if they emerged in year durations that had easy common factors, like, for example, every eight years, well, you can divide eight by both four and two.
So an eight-year locus would interfere genetically with a four-year locus.
You see what I'm saying?
Or the two-year locus.
But a seven-year locus is not going to interfere with an 11-year locus.
You know why?
Well, until you get to 7 times 11 years, and then you get both locusts.
And that's like the super plague years, you know?
But for all the other years, 7 and 11 don't happen at the same time.
Prime numbers.
So nature is engaged in basically a kind of cryptography.
Genetic cryptography.
You thought it was only in cryptocurrency?
No.
It's in the freaking locust, people.
Nature's doing math all the time.
And that was just a really rudimentary example right there.
There are countless examples, infinite, actually infinite examples of nature performing computational phenomenon and also logic and reason in various ways as well.
So I hope you found this interesting and informative.
Of course, join up to Enjoy the launch of our new AI engine.
It's free.
There's no advertising.
It's non-commercial.
And it's at brighteon.ai.
You can join the waitlist there right now.
We'll alert you via email when it's ready to go, which is truly very, very close now.
Just some number of days away.
Maybe seven.
Maybe a prime number of days.
Maybe 11. Maybe three.
I'm not sure.
We'll find out.
It's a prime number of days away.
So we don't interfere with the Locus.
And you'll enjoy our AI engine and also enjoy my prompting guides there to teach you how to get what you want out of AI engines.
And, you know, explore my articles at naturalnews.com.
Enjoy my podcasts and interviews at brighteon.com and other platforms.
I'm also on brighteon.io, which is a decentralized...
Blockchain-based social media network that also uses cryptography to distribute content.
So that's Brightown.io, and then I'm also at Brightown.social, the uncensored social media network.
So enjoy and thank you for listening.
Music playing.
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I'm Mike Adams, the Health Ranger.
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