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Jan. 31, 2025 - Health Ranger - Mike Adams

22:25

AI will push the COST of COGNITION to ZERO, and the world will never be the same

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	Welcome to the Health Ranger Report with Mike Adams, the Health Ranger.
	Almost no one in society today seems to understand what's going to happen when the price of cognition goes to essentially zero.
	And when I say the price of cognition or the cost of cognition, if you think about it, until AI came along, and now we have these very powerful reasoning models, which are free open source models like DeepSeq.
	Before that day, cognition was purely a human endeavor.
	I mean, yes, you had computers with spreadsheet software, etc., but they didn't really solve problems.
	They just ran, they're just sort of elaborate calculators.
	You still had to have a human being putting the right formulas in the right cells and thinking through the problem, okay?
	And to have a human being that is capable of thinking through those problems, It takes at least 20 years of time, maybe more, depending on the level of education required to solve problems.
	A PhD in mathematics typically takes maybe more than 20 years to grow up and for that person to develop their brain and then to be educated and to develop a skill set, etc.
	Same thing for a physicist or a chemist.
	It takes more than 20 years.
	Typically, for a human being to develop the cognitive skills to be good at solving problems, and then, even at that point, it takes their time and effort in order to apply their cognition.
	And that time and effort has a dollar cost value to it, because that person has to live, has to pay rent, has to eat food, pay electricity, etc.
	So there's been this...
	Really relatively high costs associated with cognition and problem solving.
	And that's why engineers or coders or some finance math people have been paid a lot of money to do what they do.
	Up until now.
	Up until now.
	So what is about to change, the process has already begun, is that the cost of cognition is going to zero.
	Near zero.
	It's so low that you won't even meter it.
	And on top of that, cognition will be decentralized.
	It will become widespread.
	So, for example, instead of the high-level physicists and mathematicians being found only in universities and maybe some government research departments and certain corporations and things like that, instead, that skill set will become So that a farmer can
	have on his desk a microchip, a little computer with reasoning models loaded into it that can do high-level physics, that can do high-level math, that can calculate seed, Load requirements and crop yields based on soil conditions and weather conditions.
	It can even probably simulate weather and all kinds of incredible things.
	That's just one example, obviously.
	Every person or nearly every person will be able to put a PhD-level mathematics problem solver on their desk or a chemistry solver.
	I mean, every laboratory.
	I can think about this in our lab.
	I can't even tell you how many times we would have a question like, what are the best solvents for this molecule?
	What's the, you know, is it a polar molecule?
	What's the solubility?
	And how many moles of this and that?
	And how much of this do we need?
	And that, you know, for ionization of the chromatography, it's just on and on.
	I can just ask a model to do it now.
	A reasoning model that's trained in chemistry, which they are.
	Now, So that's one thing to realize, okay?
	So the cost of cognition is going to zero.
	There's another important reason why that's the case.
	It's not just that AI can do now what humans would take a good part of a lifetime to learn how to do.
	It's that you can't replicate a human PhD math professor.
	You can't just clone that person and have a carbon copy and then suddenly have two.
	PhD math professors, right?
	It doesn't work that way.
	But you can do that with AI. You copy the file.
	For example, the DeepSeq reasoning model has a file.
	It's a GGUF file that's, well, in one distillation, it's like 20 gigabytes.
	That's what I'm running on my desktop.
	It's a 20 gigabyte file.
	I can just copy that to another computer, get a graphics card for that computer, load it up.
	Now I've got two math professors, you know?
	And obviously, I can just keep doing that.
	I can scale it.
	I can have a thousand math professors, and maybe they're all working on a really hard math problem, or they're working on different components of a math problem, or they're working on chemistry and advanced materials problems, or medical problems, or whatever, finance, you name it.
	I can replicate, and I can have a thousand experts at pretty low cost.
	Compare that to hiring a thousand PhDs and all the human resources and all the sick days and all the benefits and all the pensions and all the complaints and all the, you know, just the human problems that nobody wants to deal with, frankly.
	If you're just trying to engineer something or build something or even coders, you know, today's reasoning models can write code really, really well.
	And instead of hiring coders at $150 an hour now, you can maybe hire one coder who is augmented by AI, and that person is multiplied through the AI tools, and that person can accomplish as much as five coders or even ten coders.
	So that kind of thing is underway right now.
	So think about it this way.
	Any kind of cognitive problem that needs to be solved in the world, whether it's an engineering problem, what are the loads on this bridge, you know, or it's a physics problem or an astronomy problem or a medicine problem, whatever, finance problem, they will all soon be solved almost instantly because cognition will be commoditized and widely available and extremely inexpensive.
	You'll be able to ask...
	Common machines, even at some point on your phone, your phone will be able to run, you know, weather simulations like a supercomputer from 10 years ago on your phone.
	Your phone will be able to generate movies, generate songs on the fly, generate any kind of content, generate articles, you name it.
	They will all be able to do that on edge computing devices.
	For almost nothing.
	For the cost of, you know, a little bit of electricity.
	That's it.
	So ask yourself, how does that change the world?
	How does that change economies?
	How does that change R&D departments?
	I'll tell you.
	One obvious way, and there are many of these, but one thing it does is it puts the development of advanced materials And advanced chemistry into the hands of, let's say, non-wealthy nations or smaller nations.
	So right now, developing weapons and aerospace technology and the advanced materials for stealth bombers, etc., that requires large nations.
	Really, there are only a few nations in the world that can do that.
	You know, Russia, U.S., right?
	China.
	Maybe the U.K., but not so much recently.
	Probably India is moving that direction, Iran moving that direction, etc.
	But it's a very small list of countries that could do that until now.
	Now you're going to have this capability in the hands of many, many different nations, even many different small or smallish corporations.
	So let's say you're a small business in America and you want to design a new drone.
	Like a fixed-wing drone or something.
	Well, it used to be you'd have to hire engineering firms to go through all the aerodynamic design principles and stability tests.
	You'd have to have all kinds of, you know, computer code simulations, and then you'd have to have a 3D designer that'd have to use AutoCAD or whatever.
	Now, or let's say really soon here, this year, you'll be able to simply prompt an AI program to do all that for you.
	So, in summary of where we are so far in this, we realize that as the cost of cognition goes to essentially zero, then obviously those people who specialize in cognition, you know, engineers, mathematicians, physicists, chemists, etc., well, you know, they're going to be replaced, many of them.
	Or you could say the value of what they offer the world is no longer as valuable.
	20 plus years becoming a high-level physicist.
	And everything that you can do in physics can be done by a computer for, you know, one ten thousandth of your cost, let's say, or a millionth, something like that.
	However, what's interesting about this, and this is kind of the silver lining of this, and this is how...
	Human beings remain relevant in a world with a lot of AI compute potential.
	Somebody still has to describe the problem.
	In other words, as it's called, prompt engineering.
	Somebody has to prompt the AI in the proper way so that the AI can solve the problem.
	And also, this is where it really matters, is we always need creative, innovative humans to imagine new things.
	That might be achieved through cognition.
	So whereas before, a lot of, let's say, physicists were sitting there working out the problems, often with the help of software and computers, but not AI before, now they can offload more to AI and they can focus on the things that they want to do.
	Like, hey, could we have, I don't know, high-powered laser weapons on Humvees or something for the military?
	I don't know.
	Maybe there's a way to do that.
	Could we increase battery energy storage density by a factor of a thousand?
	Well, that's going to involve probably some pretty crazy chemistry or physics or both.
	Material science, you know?
	Now they can work on those problems and offload the thinking to the machine while they, the inventor, they focus on strategies for solving the problem.
	Strategies for describing the problem or even Telling the AI system some of the possible pathways of how to potentially approach the problem.
	So on one hand, you could say, well, AI is going to make a lot of this thinking capability of high-level people obsolete.
	But on the other hand, it frees up those people to do higher-level strategic thinking, you know, planning, innovation.
	Laying out goals for the AI, etc.
	And that's the pathway to remaining relevant in the age of AI. AI cannot replace the human mind.
	It can't replace innovation or creativity.
	It can crunch numbers.
	It can do a lot.
	It can solve problems now.
	It can read word problems and solve them.
	But somebody has to tell the system.
	What's the problem or what's the challenge?
	Now, something similar to this will happen in the world of labor, but not as dramatic because you can't really say the cost of labor will go to zero because anytime you're involved with labor, even if it's a robot doing the labor, well, there's still a cost associated with that.
	Somebody has to make the robot.
	Somebody has to maintain it.
	Anything with moving parts will eventually wear out or fail.
	So somebody has to, you know, replace the robots, replace the parts, etc.
	So robot labor will not take the price of labor to zero, but it may cut the cost of labor by maybe a factor of 10 or more, maybe a factor of 100 at some point, compared to human labor.
	Now, we have a human, I don't know, fulfillment person at an Amazon warehouse, and they're making Let's say $25 an hour or $20.
	I don't know.
	I don't know whether you get paid.
	Let's just call it $20.
	Well, a robot could probably do that pretty soon, within two years, at, let's say, $2 an hour.
	Or maybe at first it's like it starts at $20 an hour, but it's more reliable than a human.
	And then that cost will be driven down through mass production of the robots.
	So maybe it starts at $20, but then it goes down to $10, and then $5, and then $2, and maybe then eventually $1.
	At some point, robot labor is going to become very, very inexpensive.
	And that's going to put robot labor into the hands, in a decentralized fashion, into the hands of a lot of people, just like I mentioned about cognition.
	Eventually, you'll have, let's say, small farmers that will have robot laborers.
	And those robots will do things that the farmer tells it to do.
	Like, hey, go out and pick the green beans.
	Go out and pull the weeds.
	Go out and collect the goat poop because it's really great fertilizer.
	And that robot will figure out how to do that.
	Okay, I need to collect goat poop.
	What do I need?
	I need a bucket.
	I need a shovel.
	Small shovel.
	I need to know where the goats poop.
	I need to run around looking for goats, looking for goat poop, you know, whatever.
	It's going to break it down into steps and then solve the problem and then go get the goat poop.
	And then the farmer says, okay, you got all the goat poop.
	Okay, what are we going to do?
	We're going to want you to kind of shovel that into the dirt around these fruit trees.
	You know, so shovel the goat poop into the orchard.
	Okay, then the robot has to figure out how to do that.
	But the point is, even...
	Everyday people will have robot assistants doing things.
	Now, I've warned people don't buy robots with opposable thumbs.
	Not at first, anyway.
	Maybe never.
	So, maybe you don't have a robot that can hold a shovel.
	I don't know.
	But if it can hold a shovel, it can hold a knife, and that's where I get concerned.
	I don't want robots that can kill me.
	You know, especially if they're connected to the internet.
	And they're downloading updates and directives and things like that.
	You know, Skynet, iRobot.
	Oh, this is not good.
	But if it's an offline robot, like an open source OS robot, kind of like the Linux of robots, that's different.
	It'll probably be fine.
	But that's up to you to decide.
	Eventually, we'll all have robots helping us out and cognition helping us out.
	And the cognition will come first on your desk.
	You might have it right now.
	If not, you'll probably have it real soon because everybody will be using AI on their desk in no time.
	And then AI robots over the next couple of years, you're going to have robots that do yard work and do dishes and whatever.
	It'll be an interesting world, that's for sure.
	So thank you for listening.
	Stay informed.
	You can hear...
	More of my podcasts at brighteon.com.
	And I'm working on launching a revolutionary AI language model.
	I call it a knowledge model, actually.
	It's called Enoch, and it releases for free on March 1st at brighteon.ai.
	So go there, enter your email address on the top right corner there.
	We'll email you when the model's available.
	You can download it for free and use it forever.
	And it's trained on a vast amount of otherwise suppressed knowledge.
	On herbs, nutrition, gardening, permaculture, survival, off-grid, sustainable living, even economics, finance, gold, central banks, fiat currencies, you know, all kinds of interesting stuff.
	Plus, it's trained on every interview I've ever done, and every podcast I've ever done, and a lot, a lot more.
	A lot of other things.
	So, check it out, brighteon.ai.
	Until then!
	Get ready.
	The world's changing rapidly.
	Thanks for listening.
	Take care.
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