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Jan. 29, 2025 - Health Ranger - Mike Adams

26:01

Soon AI will REPLACE judges, lawmakers and middle managers...

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	Welcome to the Health Ranger Report with Mike Adams, the Health Ranger!
	It was only a couple of months ago that I heard people saying the AI bubble has burst and there are no real-world applications for AI. I mean, financial analysts were saying that, and I was laughing so hard.
	Like, gosh, they're incredibly stupid.
	They don't see the real-world use cases.
	For AI, because I'm using it every day.
	My company's using it every day.
	And that's even before the reasoning models started to really emerge, like the DeepSeq R1 model that is making waves around the world, which I was talking about right after it came out, because I said, this is going to change the world, you know?
	And Zach Voorhees, who I interviewed about this, he said the same thing.
	I mean, he said it first, actually.
	He's like, this is a game changer.
	And then I was checking it out, and I'm like, yep, this is going to change the world.
	Just a matter of time before the world figures it out.
	And so those Wall Street analysts who were saying there are no applications for AI, they look like morons now.
	And they are.
	Human intelligence is not evenly distributed across the population.
	Let's just put it that way.
	And so now that the reasoning models have come out, It hasn't just sent shockwaves through the tech industry in terms of investments and the drastically reduced price of AI compute, which has dropped by 97% now in terms of DeepSeek providing reasoning for a fraction of the price of open AI. But it also shows that this technology can leap forward much more quickly than people anticipate.
	That leap forward can actually be anticipated, but only by people who are typically called crazy by the masses.
	What I mean is the masses can't anticipate the parabolic rise in AI capabilities, but certain mavericks can anticipate that.
	It's just that those mavericks are often deemed bonkers.
	By the masses because their view of what's going to happen diverges so strongly from what the masses think.
	Turns out the masses are totally wrong, in this case, about AI. And it's the mavericks who have been proven right again and again.
	And what I'm here to tell you, as a kind of maverick forward thinker myself, is that we are still Under-anticipating or underestimating the rapid nature of the advancement towards artificial general intelligence.
	I believe that AGI will be here before the end of the year 2030. And probably much sooner.
	In fact, the DeepSeq R1 reasoning model shows us Some really important features on the pathway toward AGI. It shows us that models can be trained at very low cost.
	Models can distill themselves from very high parameter count down to smaller parameter counts to run on smaller devices using a lot less compute and a lot less space.
	On top of that, the DeepSeq R1 model has an internal dialogue, internal thinking.
	And it shows you what that is, but it's thinking step by step through a problem, and it's also questioning itself.
	So it may arrive at an interim conclusion, and then it will check itself and say, well, wait a second, but I also know that, you know, x equals this or whatever, and so that might contradict what I just said.
	So let me check that, and let's see what the final conclusion may be, etc.
	It's going through an internal thinking process which is rather indicative of the way general intelligence works in human beings.
	When you try to solve a problem, you might think about a number of different ways to solve it, like a plumbing problem even, or maybe you have to remove a door from the doorframe and you're thinking, well, how am I going to remove this door?
	And so in your mind, you start thinking about ways, I could rip it off and then, no, that's not good.
	Right?
	And you go through the process.
	I could find the hinges and see if there are screws in the hinges.
	Yes, that makes more sense, right?
	And so this is the way humans think, too.
	And the other thing that DeepSeek proved is that you don't need a warehouse full of computers in order to have really good reasoning models.
	You can run it on a gaming graphics card on your desktop computer.
	And that's what I'm doing right now.
	I suppose millions of people all over the world are doing that.
	Right now, they're running what just five years ago would have required a room full of, you know, supercomputer servers.
	Now you can run it on your desk using a card that costs less than a thousand dollars.
	So you see how fast that just happened?
	And still the world hasn't really fully absorbed this.
	Trust me.
	There's a lot more coming.
	Now, if this leap forward just came out of the blue from essentially an unknown company, a small company, I ask you this question.
	What else might be coming that we don't know about, that we can't anticipate some other breakthroughs that are readily achievable or right around the corner that we will see soon that will also...
	Send shockwaves through the industry because I can see a day in the not-too-distant future.
	In fact, I could see in one year or less the DeepSeat company itself rolling out something that is considered AGI by many people.
	Something that runs on just modest desktop hardware like that new NVIDIA supercomputer called Digits, which is a very capable computer, but it's only a $3,000 system.
	And it's small.
	It fits on your desk.
	I mean, it's very small.
	It's smaller than a notebook computer.
	If that can run a DeepSeq model that is an AGI model, then it changes everything.
	And I think that that could happen within a year.
	You know, not even considering 2030. I'm talking about within a year.
	And two months ago, nobody would have thought that's possible.
	A lot of people are realizing, oh yeah, that's very possible, if not likely.
	You see how fast things change.
	The other important concept here to understand is that the reasoning models can build themselves and make themselves better.
	In other words, the DeepSeq R1 model can help rebuild the DeepSeq R1 model, or call it R2, R2-D2. We're actually going to have an R2. Star Wars has come to life.
	Now, if we can only find C-3PO, the gay robot from a woke corporation, yeah.
	But, no.
	Getting serious again.
	The DeepSeek reasoning model can build itself better.
	And this loop, this feedback loop...
	This results in a rapid explosion of advancements in AI, way beyond the ability of humans to anticipate the advancements.
	And this is how we could achieve AGI by Christmas, you know?
	Because, well, OpenAI is doing the same thing, or trying to, but of course they're being utterly destroyed by DeepSeek, deservedly so.
	But when you've got models that can build better models themselves that don't need human engineers and human intervention, then you're on a rapidly exploding pathway to AI reasoning model innovation.
	And that's the stepping stone to AGI, which is the stepping stone to superintelligence.
	So the world is going to change so dramatically over the next year.
	It will be shocking to most people what will happen.
	Let me give you some examples of this.
	I believe I'm the first person to have publicly called for AI as an option to replace a human judge in the court system.
	So if you've been charged with a crime and you don't like the human judge because the human judge is crazy biased, which many of them are, especially on the left, the Democrat judges are crazy biased against conservatives or Trump supporters or white people or men or whatever.
	And you've seen that.
	That's played out.
	You've seen the lawfare against conservatives and against Trump himself.
	And these judges are just wild, ravenous, lawless lunatics, right?
	In those cases, you would greatly prefer an AI judge because an AI judge would judge the case on its merits and would follow the rule of law very closely and would not have this crazy human bias.
	I believe that very quickly we're going to see more and more people joining what I have said, which is to say, we should have AI judges.
	And I don't mean to immediately replace all human judges.
	What I mean is to give the person facing the judge, give them the option of saying, no, I'd rather have AI than a human judge.
	You're going to see that.
	You'll see experiments with that, and those experiments, I believe, will be very successful.
	And then that will be rolled out more and more.
	And actually, most people are going to love it because they're going to get a fair trial.
	Now, you might say, those of you listening, because I know you're very informed and very intelligent, you might say, well, wait a second.
	AI judges don't have human values.
	And I would say, in response to that, nor do most left-wing judges.
	Okay?
	Democrats don't have human values.
	So if your argument is that we shouldn't replace Democrats, even in Congress, we shouldn't replace them with AI systems because the AI systems don't have human values, I would say, well, you know, your argument fails because Democrats don't have human values either.
	They are anti-human.
	For example, you can teach an AI system that life has value from the moment of conception.
	You can't teach a Democrat.
	That life has value.
	Democrats don't believe that life has value, especially unborn human lives.
	And they certainly don't believe that life has value from the moment of conception.
	But you can train an AI model to believe that and it will follow that faithfully and all of its reasoning and logic will follow from that key statement.
	So, in other words, an AI judge or an AI legislator could actually be more effective at protecting human life than A left-wing human judge or a human senator.
	And you're going to see more and more calls to replace senators with AI. You're going to see calls to replace, you know, legislators in the House.
	Or you're going to see calls to replace mayors or governors.
	And I'm going to support those calls.
	Because you take a typical mayor, like especially a left-wing Democrat mayor, Who is a lunatic, doesn't know how to do anything except pander to the LGBT crowd.
	They're not effective as a mayor.
	I mean, look at what just happened in California.
	Look at LA. Look at the fires.
	Look at the total failure of a response.
	You can't tell me that AI couldn't do a better job there.
	You put the deep seek reasoning model in charge of the fire response, and you're going to get the fires put out.
	But you have libtard humans in charge, and then you have, you know, half a trillion dollars in damage from the fires because the humans are stupid libtards who can't get anything done in the real world.
	All they do is brag about how many lesbians they have in charge in the fire department, but they don't know how to actually get water to the fire hydrants, you know, for God's sake.
	So there's no question that we have reached the point where AI is better Then many humans, not all humans, but many humans, especially corrupt or stupid or woke humans who are irrational and delusional and living in fantasy land worlds anyway.
	Obviously, AI can reason much better than those people can.
	But those people represent about half the country.
	So, you know, there's a lot of low-hanging fruit in terms of replacing incompetent humans with very capable AI systems.
	And I fully support that.
	Now, you're also going to see a lot of AI middle managers soon because of the reasoning models.
	So the way this works is, right now, AI agents can replace sort of the lower-level workers in a company.
	So an AI agent can replace a press release writer, you know, a journalist.
	An AI agent can replace a graphic designer, a logo designer.
	In many cases, a webpage coder.
	You know, things like that.
	AI agents can do that today.
	But because of the reasoning models, soon you're going to see higher-level, more capable AI agents replacing middle managers that make decisions, that balance resources, that check in with other agents to ask, have you finished your project yet?
	Are you aware of the deadline of the project?
	Or that...
	The middle managers will take the project that's been completed and they will test it.
	They will do quality control.
	And then they will find errors and they will send it back to the originating agent to say, hey, you need to fix these errors.
	And all of this will be done by AI. So the middle managers will not be human in a lot of companies very quickly.
	And you'll have maybe just a few high-level executive humans at the very top.
	That are essentially telling the AI middle managers what to do.
	Like, oh, come up with a new sale for Valentine's Day or whatever.
	Or change up the product logos because they suck.
	Or, you know, go out and survey 10,000 people and ask them which logo they like the best and then get me back the answers and we'll use that information.
	Go!
	And the AI agent will just come up with that and do it and actually put it out on social media and create a poll and create the images and get back the information and then report back to the human manager to say, okay, here's what we found.
	Here's what people like.
	So you're going to see this being rolled out.
	We are implementing AI agents for quality control of supply chain documentation.
	So I'll tell you more about this as we implement it, but the short version is that, you know, we get a lot of certificates from raw materials providers, you know.
	Organic food providers, freeze-dried coffee, whatever the case may be.
	And they provide certificates.
	And often those are PDFs.
	And we have to check off a lot of checkboxes for adherence or compliance of those certificates.
	And then we also have our own internal procedure for laboratory testing, obviously heavy metals testing and glyphosate testing, etc.
	So we have a lot of steps that we have to go through.
	But one of the things, the very first step that we follow is to look at the incoming certificates or documentation from the vendors and to read that.
	We've been reading that with our human eyeballs.
	Those days are over.
	We are implementing a process where AI reads those documents and then AI actually understands them and then AI checks off the check boxes of the things that the document says and then helps us with that process to know what else we need to do next or what's lacking so that we can go back to the vendor and ask for more documentation.
	And guess what?
	The AI system Writes that email and tells the vendor, hey, we're missing this and this and this.
	So that's, even in our own company, that's not going to be done by humans.
	And by the way, the people that work for us love this idea.
	Because who isn't sick and tired of writing emails to vendors?
	Like, you're missing something.
	Why should you spend your day doing that?
	That's a waste of time.
	So the people that work for us love AI augmentation.
	Makes their job easier.
	Reduces stress levels and it makes their job less tedious and actually more intelligent.
	Instead of doing all the tedious stuff, you spend your focus on higher level planning and prompting, you know, decision making, which is actually a lot more rewarding for humans to do.
	You know, it's more fun.
	It's more meaningful to be a decision maker than just, you know, an email grunt, right?
	And we've already incorporated AI. Into our natural news story augmentation, research, summarizing process, script writing for videos that report on books or report on interviews.
	All of that is AI augmented, and it has been, you know, for a month or two or whatever it's been.
	And you can see the results.
	We have better content, we have more content, more meaningful content, more engaging content.
	And yeah, it's still all humans in charge of all of this.
	It's just that those people are way more effective now.
	And so, you know, we're considered an early adopter of AI technology, if not a pioneer, because we're building our own AI models.
	But I want to encourage you, if you're listening to this, think about ways that AI can enhance your company, your nonprofit, your job, whatever you do.
	It's going to involve AI, probably.
	Even if you're working or own a construction company, there are still things that you can automate in terms of email communication with clients, automated billing for clients, semi-automated ordering of supplies that you need, tracking your inventory of supplies, and maybe you have a plumbing company.
	Well, how do you know if you have all the parts that you need for plumbing?
	Do you have an inventory tracking system?
	If not, AI is really good at that.
	So think about all the ways that AI may help support your company.
	And also, everybody needs to write letters from time to time.
	And if you have an e-commerce website, then you need to write product descriptions.
	Well, AI is really good at doing that.
	In our model, Enoch will just excel at that.
	And Enoch is coming out March 1st, free of charge, on brightown.ai.
	And you'll be able to use it and download it for free.
	And, you know, forever.
	It's non-commercial.
	There are no advertisements.
	There's no monitoring or surveillance.
	You can use it free forever, and it's awesome.
	So sign up at brighttown.ai, get ready to download it, and download the software for inference called LMStudio.
	That's lmstudio.ai.
	And start playing around with language models and...
	And download the DeepSeek R1 reasoning model and learn about AI reasoning.
	And you'll find out there are all kinds of applications in your own business, your own nonprofit, your own whatever you do, your own hobbies.
	You know, even if you make crafts and sell them at the farmer's market, there's a way that you can help automate what you do, like maybe your listings on Etsy.
	So get ready for big changes and stay informed.
	Check it all out.
	I'm Mike Adams, the Health Ranger, the founder of Brighteon, the builder of brighteon.ai, the publisher of naturalnews.com, and so much more.
	So you can follow me at brighteon.social.
	My username is HealthRanger.
	You can follow me on Telegram at RealHealthRanger.
	You can follow me on X at HealthRanger.
	And you can follow me on brightown.io also, which is our decentralized peer-to-peer social media network.
	Also, my username there is HealthRanger.
	Thank you for listening.
	God bless you all, and take care.
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