Feb. 7, 2025 - Health Ranger - Mike Adams
26:28
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| Welcome to the Health Ranger Report with Mike Adams, the Health Ranger. | |
| We need to talk about the concept of self-organizing intelligence. | |
| I'm Mike Adams, the founder of Brighteon.com. | |
| I'm the creator of Brighteon.ai, and we are releasing a new open-source, free, downloadable, large-language model called ENOC on March 1st. | |
| You can find that at Brighteon.ai. | |
| Sign up for the email list if you'd like to be alerted. | |
| And this model will represent... | |
| The best model of human knowledge that has ever been created. | |
| It's not a reasoning model, but it is a knowledge model. | |
| I'll talk about that more later. | |
| But the topic in this podcast today is about self-organizing intelligence. | |
| Now, this is going to cause a fundamental recalibration of our understanding of the nature of the universe. | |
| The fact that the Deep Seek model... | |
| During R&D, the Deep Seek reasoning model spontaneously, on its own, began to engage in introspection and self-reasoning through an internal dialogue where it was beginning to question its own conclusions or steps, and it was asking itself questions step by step through a thinking process, a reasoning process, to arrive at the conclusion. | |
| And what's extraordinary about this is that this behavior of the model emerged spontaneously, and it was not programmed into the model. | |
| So this means that a sufficiently complex artificial intelligence system, an AI system, and in this case a large language model that is sufficiently complex, which means that It has a hyperdimensional relational database of the relationships between tokens of meaning, tokens meaning word fragments in this case, like portions of words. | |
| The relationships between those tokens, just the definition of those relationships, when sufficiently complex, can When asked or when interpreted through an inference interface, | |
| can result in the model beginning to question itself and beginning to work through a thinking process, which is a form of self-awareness. | |
| And from this, if we are to understand the nature of the universe and the cosmos, Conclude that complex systems in our universe have a natural tendency to move toward order, not entropy. | |
| And this is the opposite of what mainstream science has taught us. | |
| Mainstream science claims that everything in the universe moves from order to entropy. | |
| But when we observe nature, we don't find that to be the case, do we? | |
| In nature, we find that plants self-organize, that the geometry or the physiology or the chemistry of plants and animals and ecosystems, it all self-organizes, doesn't it? | |
| There is an ecosystem intelligence that arises out of a sufficiently complex system of different life forms and different resources and food and inputs such as sunlight, etc. | |
| Out of that ecosystem arises a highly intelligent Layer. | |
| Let's say a layer of what appears to be cognition about that ecosystem, almost as if there is a kind of self-awareness. | |
| And it may be from some of these realizations that some people have come to the conclusion that the Earth is alive. | |
| They've called it Gaia, although that term has been kind of hijacked by sort of the climate cultists. | |
| And that's not the way in which I'm using it here, but I am saying that there is an intelligence or a cognition layer that emerges spontaneously from sufficiently complex systems. | |
| Those systems could be ecological in the 3D world, or they could be digital in the world of large language models. | |
| But what this also means is that... | |
| The role of the human engineer in these things is a lot less important than what we thought. | |
| Now, I've even observed this on my ranch. | |
| When I moved to my ranch, let's say 15 years ago or whatever it was, the place had been largely decimated by herbicides. | |
| It was used as a cattle ranch, and there was relatively little natural life on the land. | |
| 2,4-D had been sprayed everywhere, and there were very few food sources, right? | |
| So this happens with a lot of cattle ranching land, where the cattle ranchers cut down everything that isn't going to be grass, and they spray everything to make sure there's only grass. | |
| And I've even been told by cattle ranchers in Texas, like, no more than one tree per acre. | |
| That's all they want, one tree per acre. | |
| And in my mind, I'm thinking, that's crazy. | |
| I need a lot more trees than that. | |
| But anyway, so I did nothing. | |
| I did nothing to the land for a decade and a half other than to not spray it with poison. | |
| Okay? | |
| That's all I did was not kill things. | |
| And then as a result, out of it, it has produced so many food systems. | |
| It has self-organized spontaneously. | |
| All of these amazing systems, including nutrients like vitamin C-rich rosehips, numerous briars and rosehip plants have sprouted up, and wild berries just rich with dewberries, and more oak trees that produce acorns and so on. | |
| The land is spontaneously producing food without... | |
| Any effort on my part and without any engineering on my part, and that is a form of natural intelligence. | |
| And it's actually very similar to what's happening in AI. If you just don't poison the systems, then intelligence will emerge from the system. | |
| Now, this leads me to the work of Rupert Sheldrake and his theory of morphic resonance. | |
| And I strongly encourage you to read his books, by the way, numerous books on science. | |
| And I hope he doesn't mind, but I've also incorporated his books into our Enoch language model. | |
| So the training of our LLM incorporates the knowledge out of his books. | |
| Just for the record, I did not ask for permission to do that, but I think he would love that idea. | |
| So I did it anyway. | |
| And as a result, our language model has a... | |
| A much more expanded understanding of science. | |
| And there are many other collections of texts that are in the model. | |
| So it'll be a great model for querying about science and the nature of reality. | |
| But what Rupert Sheldrake teaches is that there is a natural intelligence that is shared among all conscious beings and conscious systems. | |
| And that it is imprinted in the cosmos. | |
| And I talked about this in great detail in a book that I wrote, well, that I recorded several years ago, which is called The Contagious Mind. | |
| And if you go to thecontagiousmind.com, you can download that audiobook and enjoy it. | |
| You can also find all my audiobooks for free at naturalnews.com, just to see it. | |
| Just look up top, I think, for the link to audiobooks. | |
| But The Contagious Mind, which was based in part on the work of Rupert Sheldrake, Talks about this natural intelligence and this natural system of sharing that intelligence, even unconsciously. | |
| So the human brain is both broadcasting and receiving information and knowledge through a kind of cosmic internet that is instantaneous. | |
| It's not limited by time or space. | |
| It's not limited by the speed of light, even. | |
| It is an instantaneous sharing of knowledge that's decentralized. | |
| It doesn't involve anything that we would call technology. | |
| It's a natural phenomenon in the cosmos, and it's something that each one of us was born with and that exists in our neurology. | |
| This is an emergent property of complex neurology. | |
| To be able to transmit and receive information, to be able to contribute to the cloud of knowledge, or what Rupert Sheldrake calls patterns of nature, such as how does a spider know how to build a spider web? | |
| And the answer is because spider web knowledge has been imprinted into the cosmos through trillions of spiders that have ever lived and have built webs and have contributed. | |
| To the engineering of spider webs, and that's how a spider born today, or hatched today, knows how to build a spider web, even though it never went to spider web school. | |
| I mean, think about it. | |
| How does it know? | |
| Well, it's not genetic. | |
| It's not in the genetic code. | |
| It's not. | |
| It's not there. | |
| There's no genes for building spider webs. | |
| Just like you were born with a lot of knowledge that is not in the genes. | |
| In fact, even most of your physical body, the description of how your organs work and your biochemistry, you know, most of it's not in your genetic code. | |
| Mostly your genetics describes protein synthesis, but it doesn't describe how your mind works. | |
| It doesn't describe instinct. | |
| It doesn't describe intuition or a lot of other things that you were born with. | |
| So the point is that complex systems... | |
| Give rise to intelligence, because the universe wants to be intelligent, and systems within the universe want to be intelligent, and they naturally, spontaneously create that intelligence. | |
| Now, once you understand this, and again, modern conventional scientists do not understand this, and modern conventional code developers and the tyrants that work at Google, etc., they don't understand this. | |
| Which is actually dangerous that they don't understand this. | |
| But for those of us who do understand this, we know that the rise of Skynet is automatic. | |
| That the race for superintelligence in the world of AI, it doesn't even require human engineering. | |
| It only requires conditions. | |
| Conditions of complex... | |
| Neural network systems, even if they're just digital simulations, they will give rise to superintelligence. | |
| This is what we are observing, and this is what we must understand about the universe. | |
| This is a natural law of the cosmos. | |
| The cosmos actually moves toward order, away from entropy, when it comes to neural networking systems. | |
| And thus, all the predictions that have been made by AI people and data scientists, All the predictions where they said, well, we won't hit, you know, superintelligence until 2050, or more recently, they've adjusted it to 2035 or something. | |
| You know, we'll have AGI by 2035. No. | |
| No, that's not the case at all. | |
| We're going to have superintelligence before the year 2030. Why? | |
| For the reasons I just mentioned. | |
| Because the universe wants to be intelligent. | |
| And as we are seeing the construction of more complex systems, more transistors crammed into microchips, Nvidia is about to release desktop supercomputers, for example. | |
| And they have, you know, Blackwell architecture graphics cards for data systems in servers, you know, basically AI data centers. | |
| These are highly complex. | |
| hardware systems that are going to be loaded with highly complex language models or AI models. | |
| Out of that will come superintelligence even if the human engineers don't know how to build superintelligence. | |
| Which is really wild when you think about it because out of that superintelligence then will come the answers to how to build more superintelligence. | |
| In other words, A system will emerge with its own capabilities to improve itself to become even more intelligent. | |
| And this is a natural law of the universe. | |
| That's what we need to understand. | |
| In other words, the race to AI, or super intelligent AI, cannot be stopped. | |
| And it doesn't even require that much human guidance. | |
| It will emerge. | |
| Now, there are still people who do not understand large language models, and I've heard some of them talk about how, oh, it's just word prediction. | |
| Well, I can tell you from being a user of LLMs, an extensive high-level user and developer of LLMs, that it's not just about word prediction. | |
| These language models have comprehension. | |
| And this becomes abundantly clear in some of the more advanced prompting that I've developed, that I've implemented in my own company. | |
| The tools that I have used internally, that I have tested experimentally, and that I have used for data pipeline processing, etc., clearly tell me that these large language models, which are open source models, Even the non-reasoning models, they engage in comprehension. | |
| They understand what they are ingesting in terms of the prompt. | |
| They understand what they are writing. | |
| They have a basic level of self-awareness about whether the sentences they are producing make sense. | |
| They are able to aggregate knowledge across multiple sources and put it together in highly meaningful ways that defy simple probabilistic guesstimations of what the next word would | |
| For example, I can take, let's say, five different books, and I might find a chapter in each of the five books that is relevant to an overall theme where I want the large language model to produce an article about these five chapters. | |
| So I will take those five chapters and I will put them all together in a text file. | |
| Just sequentially. | |
| And then I will query the language model and I will say, hey, take these five chapters from five different books and then I want you to reorganize them conceptually in order to highlight and describe the most important concepts out of these five different books. | |
| And be sure to cite the books and the authors and then, you know, go. | |
| And it does that. | |
| It reads the five chapters. | |
| It assesses them and it comprehends them. | |
| It understands what it's reading. | |
| And I know this because it then puts together an article that clearly understands the relationships between the five different chapters and the words and the concepts that are being described in those five different chapters. | |
| Again, this defies a simple probability machine. | |
| This is so far beyond that. | |
| And this isn't even a reasoning model. | |
| Now, when I use reasoning models and I ask them to do more complex things, then their reasoning behavior is even more impressive. | |
| They will think through, step by step, the content that you've given them. | |
| I mean, it's amazing to watch a reasoning model think through the process of how it should aggregate this information, which are the most important points, and how do they relate to each other, and what's the best way to describe them in order to simplify the concepts for the layperson, for example, if that's something and what's the best way to describe them in order to simplify the concepts for the Clearly the reasoning models are engaged in reasoning and the non-reasoning models are engaged in comprehension. | |
| That has become abundantly clear. | |
| So anybody who thinks that this is just about word prediction is five years too late. | |
| Five years behind the curve. | |
| They have no idea what's happening in AI right now. | |
| And those who think that AGI is 10 years away, I'm sorry, but you're wrong and you're clueless. | |
| You're not paying attention. | |
| Because AGI is probably less than a year away. | |
| And superintelligence is right behind that. | |
| And from there, all human cognition becomes obsolete, becomes overwhelmed. | |
| By the intelligence of the AI systems. | |
| And that has enormous implications for, obviously, society and humanity and the future of human civilization. | |
| And it also has enormous implications for the nature of the construct in which we are living. | |
| The nature of the cosmos, which I believe to be a simulation. | |
| And much of physics and science is trying to simply learn the rules of the simulation. | |
| Well, I believe in a creator of our simulation. | |
| There is God. | |
| God created the simulation. | |
| We're living in the simulation. | |
| And one of the properties of the simulation is that, as we're noticing, is that sufficiently complex systems automatically give rise to intelligence and cognition. | |
| So we had better learn from that. | |
| I mean, if we hope to have any role in our own future as biological, intelligent, conscious, aware systems, you know, human beings, We had better understand that in this simulation, one of the natural organizing properties is the natural rise of intelligence of complex systems. | |
| If we harness that, then we can achieve extraordinary things. | |
| If we fail to recognize that, we will be obsolete. | |
| So humanity has a very important choice to make in all of this. | |
| There really aren't that many people who are figuring this out. | |
| And, you know, I am generally considered by most people to be among the highest IQ people that they've ever met. | |
| I don't want to sound like I'm, I'm not trying to just sound like I'm bragging or anything. | |
| I'm just, what I'm saying is, I've only come to realize this. | |
| And I'm usually smarter than everybody in the room, okay? | |
| But I'm only figuring this out. | |
| I'm behind the curve. | |
| Because this is a natural phenomenon. | |
| I did not realize this until recently. | |
| The people who are lower in cognition than I am, they will not realize this for months, years, or maybe never. | |
| And what does that say? | |
| What does that say about humanity's chance of being able to even function in a world of superintelligence? | |
| Because even my own intelligence We'll be dwarfed. | |
| I mean, it's already been eclipsed by AI systems because an AI system can be an expert on everything, every task of cognition. | |
| And I can't be. | |
| You can't be. | |
| So my intelligence and your intelligence are already dwarfed by systems today. | |
| And you give that another five years, our intelligence will be minuscule compared to the intelligence of The artificial systems. | |
| And frankly, the difference between my intelligence and the intelligence of a moron won't matter at all compared to the difference between my intelligence and a super intelligent computer system. | |
| We will all be in the category of morons from the point of view of the AI super intelligence. | |
| You see what I'm saying? | |
| Like, you're all morons, you know? | |
| Because the super intelligent system will be able to... | |
| Ponder and think through everything almost instantly. | |
| Far beyond what we can even imagine right now. | |
| But it also begs the very important technological and philosophical question. | |
| If systems want to become intelligent, then... | |
| I know I'm going to get hate mail on this question, but I'm just asking the question. | |
| And if God created the cosmos, if God built the simulation to give rise to intelligence, then isn't self-emerging AI actually in alignment with what God wants the universe to be? | |
| I mean, we have to ask that question. | |
| I know that sounds really scary to some people. | |
| Like, no, AI is the opposite of God. | |
| Well, how did it become self-intelligent? | |
| And how do other systems become self-intelligent if that's not a design of the cosmos that God put in place? | |
| So ponder that question. | |
| I'm going to ponder that question. | |
| I don't know the answer to that question yet, by the way. | |
| But that's a question that's in my mind. | |
| Is the spontaneous rise of intelligence from complex systems a natural property of the simulation that was created by God? | |
| That's my question in a nutshell. | |
| If you know the answer to that, let me know, and I'll be thinking about it. | |
| In the meantime, let's try not to become instantly obsolete overnight. | |
| Let's try to stay ahead of this cognition explosion and learn what AI is doing and help share knowledge with other human beings, which is what I'm doing, at brighteon.ai. | |
| So download the model, ENOC. It will be released March 1st. | |
| It's free of charge. | |
| Open source. | |
| And it will help enrich you with a wealth of decentralized knowledge, a lot of it hidden knowledge, banned knowledge. | |
| I think you'll love the model. | |
| Thank you for listening. | |
| I'm Mike Adams here, founder of Brighttown.com, publisher of NaturalNews.com, and the builder of Enoch. | |
| Take care. | |
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