Brighteon Broadcast News, Jan 16, 2026 – In 30 Days, Most Human Cognition will Become OBSOLETE
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All right, welcome to Brighton Broadcast News for Friday, January 16th, 2026.
And the big news today is that in less than 30 days, most human cognition becomes obsolete.
And I've got a special report explaining exactly why.
It's a little bit technical, but it's very important to understand this.
So let's just jump into that report here.
And then I've got other reports coming up.
And I think I'll have time for an interview today about the fraud of virology.
But let's see.
I've got a report.
Yeah, why Trump needs a left-wing revolt to secure the midterm elections.
I think I will play that one today also.
So let's jump right into the main story here about human cognition.
Welcome to the special report.
I'm Mike Adams, an AI developer and known as the Health Ranger, the founder of all the Brighteon platforms and now the new Bright platforms as well, such as BrightLearn.ai, which has now become the largest book publisher in the world with over 21,000 free books published in the last 45 days, thanks to many of you.
We've had over 6,000 authors creating books and you can create your own book completely free of charge.
And the books are rather amazing.
People are blown away.
I've had comments from people saying, I think I'm living in the future.
And I've got also breaking news on our book engine.
I'll get to the AI news here in a second.
But our science paper count now in our index, and this is one of the reasons why our book engine is so incredibly good, is because it researches a massive amount of other full text books and full text science papers and full text articles and transcripts and interviews and many other things in order to gather the information to write the chapters.
And we use advanced AI model reasoning with all of our custom alterations of models in order to achieve that.
Well, I can announce today that we now have 230, well, let's call it 240,000 science papers in our index now.
240,000.
It's actually 239,828, but we'll call it 240,000.
So anytime that you create a book at brightlearn.ai, it's actually researching through these 240,000 science papers.
That is, if you selected science papers.
And these were just added.
I mean, it was 100,000 two days ago.
So I just added another 140,000 over the last two days.
And there's more coming.
It'll be a million before long.
Trust me.
I know, because I'm footing the bill for all the search indexing and storage and everything.
So it's going to be huge.
A million science papers, and there'll be hundreds of thousands of books in the engine.
Okay.
My point is, when it comes to AI technology, I know what I'm talking about.
I've built the most successful book creation engine in the world and I've studied AI engines.
I've built and released an open source AI model with all kinds of custom training using ablation techniques or sometimes called abliteration, which is hilarious.
And I've used all the main models.
I've tested them all in various ways.
And I'm here to tell you that I believe within the next 30 days or so, maybe 45 on the outside, but probably within the next 30 days, a new model is about to be released that will make most human cognition obsolete.
And I want you to be aware of this because this is going to change everything in the AI space and it's going to accelerate AI job replacement, especially in middle manager roles.
This is going to bring reasoning engines to the forefront.
Now, it will still take a while, a year to two years for most corporations to absorb this breakthrough.
But the breakthrough is significant.
And I want to explain why.
It's going to get a little bit geeky here because, of course, I had to dig deeply into a new science paper that was authored by scientists that work for or are affiliated with the DeepSeek company.
Now, DeepSeek is the AI engine organization that shocked the world one year ago, actually.
It was just about exactly one year ago with the release of DeepSeek R1, which was a reasoning model that used an internal thought process of reasoning through a problem, exploring different alternatives, fact-checking its own thoughts and conclusions, revisiting what it had previously thought, etc.
Basically, what's called a chain of thought reasoning engine or COT as it's now called.
Since then, DeepSeek has pioneered many new technologies in the last year.
Those include DeepSeek Sparse Attention or DSA as it's known, which in my view, in my experiments, it's the most impressive bit of technology that I've ever seen in LLMs.
It's really quite incredible because it allows engines, especially with a mixture of experts layer, it allows them to give you performance and cost throughput of very large language models, but with the actual cost of small language models because of the token speed and efficiency due to only sort of selective activation of relatively small parts of the language model in order to bring you your answer.
Now, I have used DeepSeek a lot.
I use DeepSeek version 3.2 for all of the document cleaning.
I started doing that since 3.2 was released in really, well, late November, early December last year.
Once I saw the capabilities of DeepSeek 3.2, I immediately switched over to it and I scaled up a massive multi-threading operation.
And my company alone was using a significant portion of the DeepSeek inference capabilities in the world at times.
For example, I would have 1,500 DeepSeek APIs running simultaneously, cleaning or normalizing books or normalizing science papers.
So it's bizarre to use so much inference of a language model that it starts giving you 429 errors, which means you're using too much and you need to back off and start having delays between your API requests.
So I built in the 429 error handling into my code, and sometimes it has to slow down.
But I don't think anybody else is using DeepSeek as much as I am, other than maybe the DeepSeek company itself.
Anyway, that's only part of the story.
The other thing I realized in using DeepSeek is that I got the best results if I separated the cognition of the engine from the actual memory or facts or factoids of what it was dealing with.
So, for example, I would instruct the engine specifically to never use internal knowledge in any of your composition of, for example, summaries of science papers or summaries of books or keyword extraction or rewriting paragraphs for clarity, things like that.
I would always instruct the engine, do not use internal knowledge.
Instead, you're going to use this external knowledge that I provide through, of course, our massive library of the world's knowledge.
And I found that this approach worked extremely well.
And it gave me just really impressive output, which is what you see now at brightanswers.ai as well as brightlearn.ai.
Both of those use various renditions of DeepSeek in part of the research and composition and fact-checking or chain of thought processes in order to create content.
Of course, it's combined with our engine, our knowledge, our processes, our special in-house, you could say, secret sauce.
But DeepSeek plays a role in all of that.
And by separating cognition from knowledge, I was able to get really extraordinary results.
So imagine my surprise when I stumbled across this new paper that was just released a few days ago from the DeepSeek scientists.
And it's called Conditional Memory via Scalable Lookup, a New Axis of Sparsity for Large Language Models.
Now, what this means is that in effect, they have now, and this is what's coming out in DeepSeek version 4.
I'm certain of it.
This is what's coming out.
They have separated the reasoning and cognition from the knowledge of the internal LLM.
Or the way this is described in the science paper is that they use conditional memory as a complementary sparsity axis instantiated via Ngram, a module that modernizes classic N-gram embeddings for 0-1 lookups.
So what that means, so an N-gram is a, I mean, from biology, it's a neurological event that gives rise to a nugget of memory or a nugget of knowledge.
And in AI technology, the N-gram, as it's spelled, E-N-G-R-A-M, in this paper, which of course refers to N dashgram, what this means is that they have also, they have isolated the knowledge of the model, such as knowing the authors of books or knowing the names of people or knowing the cities of a country or knowing things, whatever they are.
They've isolated that into a separate sort of, let's call it a room, a separate storage area inside the model.
And they found that it works best to make that about something like 20 to 25% of the model.
And then the other 75 to 80% of the model is brains.
It's brains that can do amazing thinking.
So it's, you know, reasoning and rationality, brains, chain of thought, reasoning, also with sparse attention technology so that it only activates the parts of the brains that need to be used in order to achieve certain tasks.
And that's very similar to the way human brains work.
So you don't activate your entire brain for every task.
There might be one task you're doing, which is trying to work out a math problem.
So you're activating, you know, the math part of your brain.
Or another day, I don't know, it's Easter and you're decorating Easter eggs.
And so you're activating the art portion of your brain, the creative part, right?
So you're having fun.
Or, you know, there may be another thing, you're writing a paper, and so you're activating the linguistic creativity parts of your brain.
Those are all different logical parts of your brain, even if they overlap the physical structures.
But they're different logical parts of your brain.
So you use sparse attention.
All of us do.
That's how humans get things done.
That's how you drive a car.
That's how you figure out how to walk down a flight of stairs without falling on your face and face planting on the sidewalk.
You use sparse attention all the time.
We all do.
And what they figured out at DeepSeek is then how to use sparse attention, which is selective activation of the neurons required to carry out reasoning tasks and cognitive tasks.
And then they've separated that entirely from the knowledge portion.
So, you know, the sort of database of facts.
Okay.
And what this allows the DeepSeek engine to do is to plow through reasoning with much more efficiency with far fewer tokens, which is a, this is a transformer topology change affecting multiple layers of how, let's say,
how cognition bubbles up through the layers of an LLM in order to produce intelligence, actual intelligence.
And then that intelligence can retrieve knowledge and facts and things and then incorporate that into its thinking in order to produce the best answer or the best response to your prompt, whatever you're asking for, whether it's do this math or figure out this calculation or write this paragraph.
And the amazing thing about this transformer topology structure is that it maintains strong persistence and integrity of its ideas through a much longer context window.
Whereas DeepSeek version 3.2 has a context window of about, well, roughly, I think it's 128K.
Although I think there are different variations of that model that are a little bit longer.
Nevertheless, I think there was a special version that had maybe 192K, but nobody really uses that.
Nevertheless, Speciale was just, it was an experiment that DeepSeek offered for a short period of time.
They had an API to it, and then they pulled it off.
Well, I think they pulled it off because it was such a breakthrough that they incorporated that into what's about to become DeepSeek 4.0, which is rumored to have a context window of up to 1 million tokens.
Now, that's not confirmed, just to be clear.
It's a rumor, but even if it were half of that, such as half a million tokens, that would still be significantly more than what is available today.
And what does that mean?
Well, it means that, for example, if I wanted to have DeepSeek do something like write a, let's say write an article or write a chapter or write an executive summary report, what I could do is, you know how I have this library of now 240,000 science papers, right?
Well, at the moment, I can only select a small number of those papers to put into the context to teach the engine, like, here's the science surrounding this question, and I want you to consider all this science in answering the question.
But that's limited to 128K tokens.
And one token is about three quarters of a word, by the way, an English word.
So, you know, it's only like less than 100,000 words.
And you might think, well, that still sounds like a lot, but not if you start throwing in 50 science papers.
You see what I mean?
So I have to limit the amount of knowledge that's pushed into the context of the engine, which limits its ability to reason through, you know, additional relevant information because it won't fit in the context window.
But once DeepSeek version 4 is released, that will allow me to bring in maybe hundreds of science papers into the context window and to instruct the engine, hey, analyze this entire body, this massive corpus of science surrounding this particular question.
Maybe you asked a question about, I don't know, cold fusion or whatever, time travel.
And, you know, and it pulls up time travel journal from the year 2055, obviously, because it's a time travel journal.
And then it can bring in all the time travel papers and it can actually reason through all of that context without losing cognitive coherence.
So in a practical sense, this has enormous implications.
For example, in the area of law, once you have DeepSeek version 4, which is supposed to be coming out again in about a month, you would be able to ask it a law question and feed it a massive library of relevant law books or documents or case history, just a massive amount and say, here, crunch this.
And now, of course, there's a cost associated with all those input tokens, but it's not very much.
It's a very reasonable cost, considering the amount of cognitive work that it's doing.
In any case, the engine would then go through all of that and it would formulate its answer.
And it would be able to, if instructed properly, to carry out a chain of thought reasoning, chain of verification, fact-checking its own thinking before it outputs, things like this.
And what that means is that now the AI model is highly intelligent.
It's carrying out cognitive work with incredible efficiency and a massive memory, a large memory, and it's highly efficient because it's not wasting internal tokens on its own internal knowledge.
It doesn't need to.
That's been separated.
That's been set in a different room.
And what that means for you and I and the world is that the inference costs of this engine are going to be very, very low, especially given the amount of cognition that it's going to perform.
And what that means, and this is my guess, I think that DeepSeek version 4 is going to represent about a 10x improvement in the cost per cognitive function over previous engines, including DeepSeek 3.2.
And when I say cost per cognitive function, if you were to be able to meter cognition, cognitive output, if you could put a meter on it, the cost of cognitive output right now has a certain associated dollar cost, you could say, that cost is about to be slashed by a factor of 10.
That's my guess.
I mean, that might be off.
Maybe it's a factor of 5 or a factor of 20.
I don't know.
But I think it'll be a factor of 10.
And that means that you're going to see deployments of DeepSeek version 4 in specific applications that engage in things like recursive reasoning, which forces the engine to revisit its own answers by feeding answers back into itself and essentially burning tokens and time for enhanced cognition.
In other words, it's kind of like saying to it, hey, work hard on this problem.
Keep working.
Check your work over and over and over again.
Refine your work.
Do it 10 times until you get the absolute best answer.
And it's going to say, okay, I'll burn the tokens.
I'll spend the time.
So instead of just a great answer in, let's say, 60 seconds, it might give you a world-class answer in 10 minutes at the cost of more and more tokens.
But the point is, and again, I'm sorry if this is sounding too technical, but the point of all of this is that with the proper application of this technology, it's clear in my mind that most human cognition that happens at a desk or a work environment, most of it will be obsolete when DeepSeek version 4 comes out.
Now, it doesn't mean that everybody's going to lose their job instantly, and it doesn't replace human creativity.
It doesn't replace high-level decision-making for CEOs and founders or high-level managers, whatever.
But it does mean that it will be relatively simple to replace most middle manager type of jobs, including those that require a lot of reasoning and decision-making.
Analyzing information, assessing things, working with spreadsheets and input-output of numbers and facts and quantities and inventory and sales volumes and estimations, whatever, things that people do in middle manager jobs at companies, all those things will be easily replaced by DeepSeek version 4 this year.
Easily.
So, last year, customer service was easily replaced.
Most of it, not 100%, but typically 80 to 90% of customer service could be automated.
This year, the customer service automation is going to go up to something like 98%, and the automation is going to bleed into a lot more of the higher cognition middle manager type of roles.
And that's going to, of course, force all those middle manager human workers to either upgrade their skill set, augment their own cognition using AI tools, and then push themselves higher into the corporate hierarchy if that's possible, or they will be replaced by AI or a department of, let's say, 10 humans who are doing middle manager jobs.
Nine of the 10 will be replaced by DeepSeek, and one will be there to keep an eye on DeepSeek.
Let's make sure nothing goes catastrophically wrong, you know.
And that one person will typically have to be the person who knows how to use DeepSeek, who knows how to run agents, who knows how to write prompts, who knows how to interact with AI.
So if you're in a company environment right now, you want to be that one person that knows how to use AI.
Trust me.
That's for sure.
Now, there's an image that I want to show you here.
And to my editor, pull up the scaling law image from section three, evaluation.
Note there are two images side by side.
The image on the left is called allocation ratio.
And the image on the right is the number of embedding slots on a log scale.
So what I want you to understand about this chart, notice that the vertical axis says validation loss.
And It's a smiley face chart or a U-shaped chart there.
And what we're looking for here is the lower parts of the line are better because that means we have less validation loss.
This really affects the cognitive coherence of language models.
So you want really, you know, you want the bottom of the U shape, basically the gully of the U.
Now, what this is showing is the allocation ratio of cognition versus memory storage, essentially, inside the language model.
And that ratio is designated by the rho character there, which looks like a lowercase letter P, but that's actually pronounced rho.
So rho typically as a variable indicates ratios.
So the allocation ratios indicated here are the ratio of the cognitive portion of the model versus the knowledge storage portion of the model.
And what it means is that if you try to go with almost all storage, you know, knowledge storage, then you don't get good results.
You get higher validation losses.
Also, if you try to go with mostly cognition, you get validation losses.
And the proper ratio where you get the sweet spot in the bottom of the U is about 70% to 80% cognition focus.
And then, you know, 20 to 30% typically of knowledge storage.
So that ratio is proven in this plot or demonstrated in the plot.
I know it's not a perfect, if you look at the dots, it's not a perfect fit for the U, but it's close.
Now notice that it's also showing on that chart pure MOE, which is mixture of experts.
And notice that pure mixture of experts models, which is what has been the state of the art across, I mean, all the mainstream engines have used MOE still to this day, that the losses are higher.
And understand that these validation losses get compounded through the topographical layers of language models.
So as this says, the hybrid allocation surpasses pure MOE.
So this is a big deal.
Now, on the right, the right-hand side, you see this is a downward slanting two lines, and the vertical axis is again called validation loss.
And the horizontal axis is number of embedding slots on a log scale.
That's important to note.
Now, embeddings, let's simplify that.
Let's just call it facts that it's remembering, you know, stuff in its memory.
So we don't need to say embeddings, but what this is showing is that the more stuff the model knows, the lower its validation loss.
That kind of makes sense.
The more stuff you know, the better you're going to do on answering questions, right?
That makes sense.
But it's on a log scale.
So, you know, that's noteworthy.
I mean, it's 10 to the 6th at one point on the x-axis, and then it's 10 to the 7th.
So notably, these are not straight lines if you have a regular linear scale, but this is a log scale.
So isn't that interesting?
So if an LLM knows 10 times as much stuff, it's going to do slightly better on answering questions, but not 10 times better.
Anyway, that's just interesting.
But the bottom line is that what DeepSeek has been able to innovate here is a way to isolate knowledge from reasoning and to mix in like a secret pancake recipe just the right amount of cognition, which is 70 to 80%, and just the right amount of knowledge, 20 to 30%, in order to achieve a really strong, coherent cognition that is about to be unleashed upon the world.
And I should also mention here that they did all this testing on a 27 billion parameter model, not even their full-scale DeepSeek model.
So I don't know what these numbers are going to look like on the full model.
This is a small model.
You could run this on your desktop with a GPU, like a video, you know, a gaming card.
You could run this model.
That's unbelievable.
That's just wild.
Now, there's one more thing.
Well, actually, two more things about this.
Again, sorry about all the technical stuff here.
I'm trying to break it down.
DeepSeek is rumored to also be releasing a DeepSeek version 4 light model.
The light model will have blazing inference performance throughput in terms of the number of tokens per second.
And it will do that by, I mean, I'm guessing that it's going to have a more limited window of activation of digital neurons in the sparse attention internal algorithm and routing.
It's just my guess.
We'll see.
It'll probably also have less knowledge, so it doesn't have to look up as much stuff, a lot less knowledge.
So this light engine will be really good for doing simple tasks very quickly.
And yet what we've learned with recursive reasoning and looping of models is that even very small, fast models can become quite capable if you engage them in recursive reasoning.
That is forcing them to rethink their own answers over and over again.
And you can feed their own answers back into them with additional context and ask them to refine and fact check or double check or redo the calculations or whatever you need to do.
So in other words, you're not going to have to wait a long time to get good answers.
You're just going to burn more tokens at a lower cost with a smaller, lighter, faster model that DeepSeek is giving away for free.
So you can download it, install it in your own corporate infrastructure.
It will probably install on a very modest graphics card.
It'll certainly run on the NVIDIA DGX Spark hardware, which is, what, five grand or something?
And it may not be the fastest thing in the world, but it's going to run and you can use that as a server for your entire company.
And then throughout your organization or your company or your nonprofit, whatever it is, then everybody can access the same cognitive engine and different kinds of questions and tasks can be queued up.
But a fast DeepSeek, DeepSeek Light, will speed the whole cognitive functions across the board inside the organization.
So in other words, you're not going to be sitting there waiting for AI to do the work and spit out the answers and thinking, oh, it is faster if I had a person do this.
Instead, the AI is going to be much faster than a human.
It's going to have real intelligence, high-end cognition, and when wrapped appropriately in the right kind of code, which admittedly not everybody knows how to do it yet, but it's going to become more commonplace, you're going to be able to get expert-level answers out of very relatively small, fast engines when they have this technology.
Because it's like you're asking an engine here to do some brain work, and it's only having to use its brain.
It's not having to sort through like encyclopedias of knowledge.
Imagine telling a person to, I don't know, add up the first 100 numbers or digits of pie, let's say, 3.1415.
Now, just keep going.
Add up the first 100 digits, and then you throw that person about a thousand phone books, and all this knowledge and information and science papers like falling out of the sky.
Like, here, why can't you add the numbers?
And the person's like, because you're throwing all this other crap at me.
That's how the language model feels when it's trying to sort through all this knowledge stuff that it doesn't even need.
You know, it's trying to add the numbers of pie, and it's sorting through like what movies did Dustin Hoffman star it?
You know, nobody needs that.
That's why sparse attention is so incredibly powerful.
And this is about to break the corporate world.
That's my prediction.
And the bizarre thing about all this, this is just one science paper of several key papers that the DeepSeek team has released recently.
This is just one.
Every single one of them is a breakthrough.
And I'm not seeing these papers coming out of U.S. AI companies at all.
Google's not releasing papers like this.
OpenAI isn't.
Meta, nope.
Microsoft, nope, nobody.
All the breakthroughs that I can see in AI are coming out of China.
So, personally, I am preparing to set aside some substantial time when the DeepSeek version 4 model is released.
And of course, I'll share that information with you as it happens.
If it becomes the most capable model, as I strongly believe it will, I will upgrade all of my projects to use DeepSeek version 4 where appropriate.
Either, well, the large context window for research is going to be huge, but also the faster inference.
You know, just the sparse attention activation is going to be a game changer.
So you're going to see probably a notable improvement in the logic flow of chapters in the books that are created at BrightLearn and in the answers at brightanswers.ai.
Now, if you've used Brightanswers.ai recently, you notice it's slower than it used to be.
That's because it's involved in a lot more deep thought.
And yes, that's slow.
Well, if I can harness DeepSeek version 4 light to be much faster and use that to help generate at least portions of the answers combined with the larger research context window, I may do that or I may do it as an experiment.
Of course, it's all going to be overlaid with our own AI engine, our own knowledge base, our own secret sauce, as I mentioned before, which is the way that we alter AI engines to have a more accurate worldview on topics like vaccines and climate and pharmaceuticals and natural health and herbs and things like that.
So, in other words, all the engines that I've built so far are about to get even better.
Oh, I forgot to mention one more thing.
DeepSeek version 4 is also excellent at coding.
Apparently, it's rumored to be better than Anthropic Opus 4.5.
Now, Opus 4.5 is the coding engine that I primarily use for all my code.
And it's, you know, Anthropic or Claude code is both amazing and frustrating at the same time.
It is a breakthrough technology, but I still spend crazy hours trying to troubleshoot bugs and trying to get it to do what I want when DeepSeek version 4 very likely is going to be able to cut my vibe coding time in half is my guess.
It could be even better than that.
But if it cuts it in half, because it's able to take on these tasks and to really examine very large code bases in full context and to carry out cognitive assessments and even internal simulations of what the code is doing and to solve complex problems involving multiple routines and large code bases,
then I'm going to be able to get a lot more done in a lot less time, which means you will get more awesome AI engines that I'm building because it'll all be faster thanks to DeepSeek.
That's my guess, by the way.
I can't totally promise that yet, but I'm somewhat confident that DeepSeek version 4 is going to be better at solving code problems than Claude Code Opus 4.5.
That's my guess.
And if that's true for me, it's going to be true for the whole world, which means that all the large code base projects that currently clawed code can't really handle because it's too much code.
Well, suddenly, DeepSeek version 4 will be able to ingest that code and be able to make comprehensive global structural changes to the code or bug fixing at a much larger level or higher level of the code.
And that's going to free up coders to be more creative and to have more throughput of their code projects.
And aren't we all becoming coders now?
Essentially, anybody playing around with AI, we're all becoming coders.
And if you're not yet using AI coding engines like Replit, then you should be because this whole field is about to explode in terms of productivity.
It's about to explode.
Okay, one other thought in all of this and me just looking at this with my native math skills, which are pretty decent, but I'm not a mathematician, so I never really refined high-level math, but I do understand big picture concepts.
And one thing that's become apparent to me about this model and what DeepSeek is doing is that because of some really unique architecture, such as what's called multi-head hashing, that's mapping these ngram, which is, you know, facts and thoughts and stuff.
It's mapping it to its internal embedding tables.
What DeepSeek is able to do is to allow the capabilities of the engine to grow with only a linear addition of engine size rather than an exponential requirement for growth of the engine size.
So in other words, for most LLMs and AI functions, if you want it to be, I mean, this is a simplified version, but if you want it to be twice as smart, you might have to add 10 times as much compute or size to it.
You want it to be three times as smart.
You might have to add 100 times as much, etc.
So that's an exponential curve of adding a much larger set of parameters, but only getting a fraction of that in terms of performance.
And that's why OpenAI is rumored to be trillions of tokens or trillions of parameters, excuse me, a multi-trillion parameter model, but it's not that much better than models that are a fraction of the size.
You can keep growing bigger and bigger, but you don't get a linear output of increased capabilities as a result.
But what DeepSeek is able to do, and other companies have also done similar things.
This isn't unique to DeepSeek, but because of their approach, their mathematical approach on the internal topology of their system, they've been able to allow growth to affect the performance in a linear fashion.
So a model that's twice as big gets roughly twice as good performance.
Now, that's a simplification of it, but that's roughly what's going on.
And that's a huge deal.
That's a huge deal because, you know, look, if you're talking about neural networks, everything is normally squared, you know, right?
I mean, the number of connections just begins to increase exponentially.
Actually, it's not always squared.
Sometimes there's another exponential, but everything begins to increase exponentially, like the number of combinations just starts to explode.
And that's all part of neural networking.
But if you can get, you know, if you can get a corresponding response to a linear increase, then that's like the holy grail right there.
You figured out how to scale and scale your results as you scale the, let's say, the parameter infrastructure or the topology of the model.
So I may not be using all the right terms for those who are machine learning scientists, but I'm also trying to sort of translate this into a little bit more everyday language.
Anyway, the bottom line is most human cognition is obsolete in about 30 days, if I'm right about this model.
And I guess we'll see.
Now, notice I did not say that all human cognition, I didn't say all, I said most.
And I also, I didn't say every job is going to end, you know, in March.
This is going to take a long time for corporations to roll this out, to figure it out, to test it, to modify internal operating procedures, etc.
So you're not going to lose your job tomorrow just because DeepSeek comes out.
But over the next one to two years, if your job involves sort of middle-level cognition, then you should be thinking about how to upgrade your cognitive role in your organization because that replacement is coming.
Not tomorrow, but it's coming soon, let's say.
All right.
Anyway, thank you for listening.
And if you want to use the AI tools that I've built, they are at brightlearn.ai.
That's our AI book creation engine, which is amazing.
Or brightanswers.ai or brightnews.ai.
And we have a lot of new features coming.
I just need more time to vibe code.
And I did hire a vibe coding person, but that person is not working on any of those projects I mentioned.
They're working on a new project that I haven't mentioned yet.
So I'm still the only one on these other three projects.
And that's, and I'm fighting with the AI agents sometimes.
So things are a little slower than what I would like.
One of the main features I'm working on for Brightlearn.ai is full-length audio books.
And that's not just fighting with AI agents.
That's also trying out all these different AI voices.
And frankly, one of the biggest challenges there is how to make the voice more expressive based on the content of the paragraph that the AI voice is performing.
So I don't want an AI voice to read a whole book in a monotone, you know.
And there was a piece of plywood.
You know, come on.
It's got to be more interesting.
It's got to be relevant.
You know, if there's a warning section, it's got to have a warning tone.
If it's just more of a light-hearted section, it's got to have more of a light-hearted tone.
And that requires a classification prompt and analysis of every paragraph in the context of the chapter and the book and figuring out what it's trying to say, what it means, etc.
Oh my gosh, this is really complicated.
And so thus it's kind of slow, but that's coming.
That's coming.
I don't want to put out a crappy full-length audio book that nobody wants to listen to.
In other words, my goal is to put out thousands of audio books over the next, well, just this year, actually.
Thousands of audio books.
But I want them to be good.
I want them to be a pleasure to listen to.
So that's going to take a lot of work.
Anyway, I'm on the job.
And if anybody can make this work, it's me.
That's for sure.
I mean, because I care about audio, you know, I'm an audio engineer.
I'm a musician.
I'm an AI developer.
Like, if anybody can make these books sound good, it's me.
But it's going to take some work.
So have some patience.
And I'll bring you more news when that's available.
Until then, thank you for listening.
No, much appreciated.
And we'll talk to you again soon.
Okay, continuing with the broadcast.
You know, I put out a social media tweet.
Let me read it for you.
This is good.
Because I hear a lot of people really complaining about health insurance costs.
And I understand that because health insurance costs are skyrocketing and they are insane.
And it is a giant ripoff.
And the whole system, the whole medical care system and the health insurance system, it's all a giant ripoff.
So I put out this tweet.
I said, I wonder when people will realize that they would be far better off by purchasing zero health insurance and using the same money to stack gold and silver instead, then negotiating with healthcare providers for cash prices, which are often 80% to 90% lower than insurance prices, when they actually need services like an MRI and essentially building up a stack of metals for any so-called catastrophic medical costs.
The entire health insurance medical industrial complex system is a complete scam and you don't need it.
Stop participating in it.
Save your own money in metals.
Take care of your health with nutrition, sunlight, and basic exercise.
And you'll be far, far ahead at the end of the day.
All you have to do is ask for the cash price from any clinic or doctor, and you'll save 80 to 90% in most cases.
Pay with cash and pocket the savings.
Build up a massive store of metals over time and stop being suckered by the health insurance industry.
And the reason I said this is because I see a lot of people saying, oh, I pay thousands of dollars a year into health insurance, but I barely use it.
And then even when I do use it, then I have to pay hundreds of dollars in the deductible.
Like, why are you participating in that system?
It's a rip-off.
Now, I've heard many stories of people saying that they've paid into health insurance, even for 10 years, let's say, and they're just fretting over the shocking amount of money they paid in the system.
And the money's gone, obviously.
It's gone.
And then anytime if they actually need some kind of medical service, they're shocked at what the hospital is billing the health insurance company because those are rip-off billing prices.
Hospitals charge more if you have insurance.
Whereas if you just offer to pay a cash price or if you just say, I'm not going to pay at all, let's negotiate a cash price for the services, then hospitals will come down often by 80%.
I mean, it's very common, actually, especially for MRIs.
You know, an MRI cash price might be less than $300.
Insurance price might be $3,000 or Medicare price might be $4,000, $5,000, or whatever.
I mean, this is a fact.
Everybody knows this in the industry.
I know people who offer mental health services and a cash price might be $60 an hour, but the government, the VA, or whatever the health insurance is for veterans will pay $200 an hour, right, for the same exact service.
So cash price is always the cheapest price.
So it turns out that if you actually want to save a lot of money and store a bunch of gold and silver, you can simply divert your health insurance costs into metals.
And so here's the question to you.
If you are paying $2,000 a month for health insurance, but if instead, and let's say you've been doing this for the last 10 years.
So, you know, 120 months ending at the end of 2025.
So $2,000 a month times 120 months of purchasing silver, given the actual purchase price each year, the average price for the last 10 years.
How much silver would you have and what would it be worth today?
Now, I'm going to get you this answer, but I'm going to have AI do it because I'm in a hurry.
So I'm going to tell AI to build this thing in a spreadsheet and figure out the answer.
Let's see what it comes up with.
Okay.
It says that, again, if you spent $2,000 a month buying silver for the last 10 years, you would have accumulated 11,600 ounces of silver.
Okay?
11,600 ounces of silver.
And right now, silver is valued at over $90 per ounce.
And I'm just going to go with spot prices.
We're not going to consider the coin premiums or whatever.
But if you do the math on 11,600 ounces of silver, you would have a million dollars of silver.
Now, let me ask you this question.
Do you think that with a million dollars of silver that you could cover some doctor visits or some MRIs or even a surgery if it were necessary?
Could you negotiate with hospitals for cash prices and save a bundle and still have most of that million dollars left over?
And the answer is yes, yes.
So instead of buying health insurance, you could be stacking metal that serves as both kind of like your own in-house health insurance fund and a retirement fund.
Because if you don't use it for health insurance, you've got the metal.
You see what I mean?
So people don't think this way.
They think, I need the health insurance.
It's the only way, you know, it reduces my cost of prescription drugs.
Well, you know what reduces your cost of prescription drugs?
Not taking them by resolving the core issues of your health problems.
Now, I'm not your doctor, so work with a naturopath to do that.
And I understand not in every case can you eliminate prescription drugs.
But if you're spending all this money to save money on prescription drugs, you've given up what could have been a million dollars of silver.
And yet there's nothing to show for it at the end of the day because all the money that you pay into health insurance just vanishes down a deep, dark, black hole.
It goes into the pockets of the health insurance company CEOs and salespeople, etc.
You see?
But in essence, what I'm actually advocating here is what's called self-insurance.
And because health insurance costs are so unbelievably high, self-insurance makes a lot of sense these days.
Self-insurance.
Even if you're not wealthy, just by starting younger, this does work better when you start young, obviously, when you have fewer healthcare concerns and you have more time to accumulate silver or gold, then you can add to this over time.
You can build up a pretty big bank here, a million dollars worth of silver.
And then you can tap into that if you have any kind of health costs.
Or if that makes you nervous, you could buy health insurance for catastrophic things like a catastrophic accident or something.
Or you could buy health insurance with a very, very high deductible, like a $5,000 or $10,000 deductible.
And the cost of that insurance would be much, much lower.
And then you could cover deductibles if you had some great dire need for some kind of medical procedure, like bypass surgery or whatever, then you could pay for that, especially when you negotiate a cash price with the hospital.
So in effect, the insurance market is so out of whack that it no longer makes sense to buy insurance.
That is in the health insurance industry.
Now, granted, it's legally required by law, I think, to have some level of health insurance.
And so even I carry through my company some minimal, I have no idea what it is, some minimal level of basic insurance is dirt cheap.
I don't use it.
Who cares?
You know, my health insurance is superfoods and exercise and sunlight and eating well and things like that.
But I've also been stacking silver this whole time.
So if I had a problem, I could call up the vault, sell some of the silver, use the cash to pay the hospital.
And I would still be way ahead than if I had bought health insurance all these years.
So something to think about, something to think about.
Just as a disclaimer, I'm not your financial advisor.
I'm not your doctor.
I'm not your accountant, whatever.
And most, I would say most financial advisors would oppose what I just said.
They would say it's a bad idea to self-insure.
But that's because most people don't understand math.
Seriously, especially surrounding insurance.
It turns out that people buy insurance not because it's better math, but because it just mentally feels better.
It just feels safer for people.
I'm insured.
You know, I've got coverage.
It's an emotion.
It's not mathematically sound.
Not at all.
It's actually a ripoff.
That's why the health insurance companies make so much money because they're ripping you off.
Obviously, they're charging you more than what they pay out for what you need.
Otherwise, they wouldn't exist.
Same thing's true with car insurance.
Same thing's true with home insurance, etc.
I'm not saying drop all your insurance plans, but I'm saying think about the ripoff of insurance.
Do you really get ahead by buying all this insurance?
Or on your car, for example.
Some people, especially poor people, like to have really low deductibles because they can't afford anything.
So they say oh, I have to have a fifty dollar deductible.
So they get quoted the super high, crazy insurance rate that they pay, that they can't even afford.
They would be far better off to have a five hundred dollar deductible or a thousand dollar deductible and save the difference in silver, you know, save the money and then, on the rare chance that something happened, they could more than cover the difference with the money they already saved.
So low deductibles are chosen by poor people, the very people who are least able to afford low deductibles, because it's high costs.
But again, mostly the reason they're poor is because they don't know how to handle money.
Now, that's not you, those of you listening to this.
You do know how to handle money you, you.
You know exactly what i'm talking about.
But you know how we say that.
Uh, lottery tickets are a tax on people who can't do math.
Well, so are low deductibles on on insurance.
Low deductible insurance policies are a tax on people who can't do math.
So re-examine all your insurance and you might be able to let go of some things or divert some of that money into something that makes a lot more sense, I mean for me personally.
I I don't I hardly insure anything except whatever is legally required by law.
So yeah, i'm driving around with some kind of car insurance because it's required.
They force it on you right, like Obamacare.
But i've known people who buy insurance for everything.
I like they buy cancer insurance, like what you bought cancer insurance.
Like yeah, if I die of cancer it pays out.
You know 50 grand or whatever 100 grand.
Like why would you bet on yourself dying from cancer?
Like that just seems like the dumbest thing imaginable.
You know you're paying a monthly premium to an insurance company that's only going to pay I guess somebody else in your family if you die of cancer and you know they're only going to pay in devalued dollars because it's in the future.
So the premiums you're paying today are with today's dollars.
The payout in the future is with tomorrow's dollars that are worth a whole lot less.
So all the numbers that you use to calculate this you're off because you you did not consider compounding inflation.
Did you dollar devaluation?
No, because people don't consider that.
Because again, people aren't good at math, most people they don't know how to deal with numbers, and if you take the White House numbers oh, inflation is only 2.7 percent.
You're going to get the wrong answer on everything.
Because inflation is not 2.7 percent.
The value of the dollar is dropping more like 15 to 20 percent every year and nobody calculates that, and certainly not the insurance salesperson.
They're not going to calculate that.
They're going to say, you know hey, for only 200 a month you could get a hundred grand.
If you die of cancer.
It's like winning the lottery if you die of cancer.
It's like that.
That again, i'm sorry, but it just seems like the dumbest thing possible is betting on yourself dying from cancer.
Why would anybody do that?
If instead, you take that premium and then you buy anti-cancer nutrients at you know our store or wherever, or you lead an anti-cancer lifestyle, then you don't die of cancer, which seems like a better outcome to me.
I don't know, is that weird?
To say it's better to invest in things so you don't die of cancer seems like the best insurance is investing in your health right, But why is that considered weird in society?
Because people are brainwashed into thinking that cancer is random.
Well, you have no control over your cancer.
Thus, you need insurance because it's a random event.
It's not random.
Every single person who has cancer developed it over time through cause and effect.
I'm not saying it's their fault.
It could have been without their knowledge.
It could have been exposure to environmental toxins, exposure to 5G towers right outside your apartment window or something.
Or some people trusted the jabs, took the jabs, and died from the turbo cancers.
Not their fault, but it's still a cause and effect.
You control your health outcome more than anybody else in the world.
And if you want to reduce your risks of dying from cancer, then choose to lead an anti-cancer lifestyle, which is exactly what I teach.
And that's what's on my website, naturalnews.com.
Go there, read the articles.
We've got an amazing assortment of articles about anti-cancer solutions, alternatives, nutrients, foods, lifestyles, light therapy, amazing things.
So, you know, hey, I guess everybody gets to make a choice, but I would hope that more people would choose to live rather than have a payout if they die.
It's like I remember seeing years ago at airports in Europe, they would have little vending machines where you could buy like a $25,000 euros or whatever, death policy right before you got on the plane.
You know?
So you could pay money to bet that you're going to die on this flight.
Now, you know, one obvious question is, who's going to know you bought the policy?
I mean, what a clever little scam.
Here, we'll sell you policies right before you get on the plane.
If you die, and nobody knows.
I mean, nobody knows you have the policy.
Unless, what, you buy the policy and then text your whole family, I just bought a policy.
It's going to pay out if I die.
I'm taking a flight.
And the family is going to say, well, I hope your flight is safe.
Sure wouldn't want to collect $100,000 if your plane goes down and you are obliterated.
That's just a weird conversation.
Why do people do that?
You know, and the person, oh, don't worry.
It's going to be fine.
It's on Malaysian Airlines.
We're flying over the Indian Ocean.
Everything's going to be fine.
All right, no, it's TWA Flight 800.
It's going to be fine.
Don't worry.
Okay.
Okay.
Bad timing for that horrible joke.
I'm sorry.
What was that Malaysian Airlines flight anyway?
They still haven't found that plane, have they?
Just like they still haven't found the plane that they claim hit the Pentagon on 9-11.
That's pretty bizarre if you think about it, because if a plane hit the Pentagon, there would be, you know, landing gear and wing parts and luggage and probably people's body parts all over the lawn inside the building.
You know, they'd be peeling people off the walls of the Pentagon, right?
There would be airplane seats, a hydraulic fluid, maybe a couple of two-dimensional pilots up front.
You know, there would be part of a nose cone.
There would be a black box.
There would be, I would imagine, some jet engine parts.
Maybe a tail number, you know.
Do you realize that none of that was ever located at all following the so-called airplane flight into the Pentagon on 9-11?
That's 2001.
And you know why?
You know why they never found that plane?
Because it wasn't a plane.
Yes, you got the right answer.
Of course it wasn't a plane.
Because planes don't just vanish on the Pentagon lawn.
I mean, a plane could vanish in the Indian Ocean.
It's a big ocean.
The water's deep.
A plane could vanish into a jungle somewhere, maybe.
Can't vanish on the front lawn of the Pentagon.
But that's what we were told.
And most Americans still believe that.
You know that?
Most Americans still believe that.
They still think a plane hit the Pentagon because that's what George Bush told them.
And they're too stupid to think for themselves, aren't they?
Like, where are the wheels?
If the plane hit the Pentagon, would the wheels vanish?
Would the jet engines vanish?
Would all the people, all the luggage, all the everything, would it all vanish?
Nope.
Probably not.
There would be wreckage.
So, no, no, an airplane didn't hit the Pentagon.
What actually happened to that airplane?
See, that's an even more interesting question because the media told us that's a specific flight number with a couple hundred people on it.
Where did that plane go?
It certainly didn't crash into the Pentagon.
We know that.
Duh.
Where did it go?
Yeah, ponder that one.
All right.
Well, of course, you've been lied to by the government forever, and the lies continue to this day.
And, you know, speaking of government deception, I've got a report here for you.
It's called Why Trump Needs a Left Wing Armed Revolt to Secure the Midterm Elections.
See, Trump actually needs this uprising.
That's why the ICE agents are going insane, provoking people and, you know, grabbing Americans and throwing them to the ground and beating them up.
It's like, where's your ID?
Where's your ID?
Like, I'm an American.
Prove it.
Prove it.
Could you prove you're an American?
I could prove I'm an American, I guess.
Yeah, the government sucks.
Oh, yeah, you are American.
The IRS sucks.
And the Fed.
Okay, pure American.
Yeah.
I got my concealed carry and the Tampa Bay Buccaneers suck.
Okay, that's too American right there.
A little bit too American.
That's the only football team I know, by the way.
And I only know of them because my co-host, Todd Pittner, lives in Tampa, and he's a fan of the Buccaneers, even though they are the suckiest football team, apparently, ever.
That's actually a fact.
But anyway, whatever.
Trump needs a left-wing uprising.
And so how do you do that?
You send out a bunch of hooded goons all over the country to just harass everybody until there's an uprising.
And then when the uprising happens, you declare an insurrection and then you deploy the military.
And then the military counts the votes in the midterm election.
So that is the plan.
And it's being carried out like clockwork right now.
So I'm going to give you that report next.
And following that, we will have, what are we going to have?
Oh, yeah, we have an interview with an author of a book that questions the whole theory of virology.
Before we get to that, I'm going to play a short video I recorded today about our store.
We have an overstock sale.
We overproduced a couple of products.
It's like five of them, actually.
And so we've got them on deep discounts, 40%.
I think it's 40% off.
And that URL is healthrangerstore.com slash overstock.
All one word.
HealthRangerStore.com slash overstock.
If you want to take advantage of these, or you could shop from our hundreds of other lab-tested, high-nutrient-density products, you know, things that could help you not have to cash in an insurance policy like I died from cancer.
You know, it's like winning the lottery.
No, that's instead.
Instead, take care of your health.
Have good nutrition.
And you can do that through our store, healthrangerstore.com.
So check out this short message, and then we'll go to the special report and today's interview.
Okay, this is pretty rare, but we have an overstock sale at healthrangerstore.com on just a few products, but some of them our customers really love.
So let me show those to you.
Right now, you can save 40%, a very limited supply of the super protein formulations, both the regular and the chocolate that you can see there, as well as apple slices and mango slices in a really great individual format, great for travel, and the collagen joint support stick packs for an instant drink mix with blackcurrant in there, by the way.
Also, the situation is we overproduce these because we had to purchase very large lots of very specific ingredients.
And it's probably my fault.
You know, my team was asking me, well, you know, we have all these ingredients.
It's probably going to produce too much.
Should we just produce it anyway?
I said, yes, just overproduce it.
And if we end up with too much, then we'll just offer a discount to our customers.
And that's what we're doing right now.
So these products are labeled to expire a few months from now.
But I don't know if you know this, we store all of our products in an environmentally controlled, climate-controlled, air-conditioned environment that is fully insulated.
The entire building is fully insulated.
And the dirty little secret of the supplements and superfoods industry is that most products are stored in warehouses that get way crazy hot, especially during the summer months.
And that can be true at, you know, even Amazon or other major fulfillment houses.
They're not, the different warehouses are not always or rarely actually climate controlled.
So our products have actually a longer actual shelf life compared to most products, but the FDA limits us.
We can only put a certain amount of time on the product.
And that amount of time is coming up in a few months for these products, even though realistically they can be used for much longer safely.
So that's the situation.
So, hey, we overproduce.
You get it at 40% off.
And you get to help support us and acquire these really amazing products.
So here it is, organic super protein, the chocolate formula.
This is based on the Boku superfood formulation.
And let me just show you here.
If you scroll down, let me show you the ingredients because it's like, oh my goodness, look at all the stuff that goes into this.
I mean, it's not easy to source like organic Satcha-inchi protein powder and carrot powder and then cranberry flour.
Cacao sometimes can be difficult, you know, etc.
So this is just one of the products.
There are others here.
Sourcing is becoming more difficult because of supply chains and tariffs and things like that.
And very often we just have to buy larger lots than what we want to buy.
So anyway, our loss is your gain for right now while supplies last.
It's a pretty limited supply.
So take advantage of it.
Just go to healthrangerstore.com slash overstock.
Healthrangerstore.com slash overstock.
And you'll see the products that are on sale 40% off while supplies last.
And it's a very limited supply right now.
It's just these, what, five products at the moment.
Many other products we can't keep in stock, you know, because there's so much demand for clean food and clean supplements and lab-tested products.
And I can't wait, by the way, to show you our new lab.
It's up and running.
It looks awesome.
I've shown a couple of people the lab so far.
They're just blown away.
I'm going to give you a video tour with all our new equipment, you know, all the mass spec equipment, the ICPMS, the triple quads, the single quad, the gas chromatography, the ion chromatography.
We've got a number of instruments there.
I'm going to walk you through some of the sample prep and some of the testing that we do because nobody is as committed to clean food as we are.
Nobody in the world.
We do more testing than anyone, period.
End of story.
Mic drop.
We just flat out do more testing for glyphosate, for heavy metals, for aflatoxins, for microbiology, and many other things, depending on like atrazine, depending on the product.
So, super clean food, super clean supplements.
Shop with us at healthrangerstore.com for all the regular products.
And then, if you want the overstock sale price products while they last, that's healthrangerstore.com/slash overstock.
And thank you for your support.
Okay, welcome to this special report.
Mike Adams here.
Every administration wants the political enemies to attempt an uprising against it so that the administration in power can claim, oh, it's an insurrection, and then you know, arrest and round up everybody.
That's the opposition.
The Democrats did this to Trump and his supporters in 2020, right after the election, you know, leading to January 6th of 2021, where hundreds of thousands of peaceful, mostly peaceful Trump supporters were simply protesting the rigged election because it was rigged.
They stole it from Trump in 2020.
Now, exactly the flip side is happening where Trump wants to provoke an insurrection by the left.
So, in other words, Trump took the same idea from the Democrats and Nancy Pelosi and the Capitol Police from 2020 or 2021.
And Trump is deploying that exact same strategy against the left, and the left is falling for it.
So, I'm trying to help explain what this means and where it's going.
When you see these masked ICE agents dragging people out of their cars and, you know, beating an old lady on the street or whatever they're doing, you know, tackling an American kid who's a cashier at Target, throwing him to the ground, body slamming him, making him bleed, and then letting him go a few minutes later when they realize he's actually an American.
None of these things are accidents.
It's clear to me that ICE agents have been given orders to be overly aggressive to provoke anger and hatred from the left.
And this is why these ICE agents are told to wear masks.
Because anytime a group is wearing masks, you know, you saw it from the left, you saw it from Antifa, it's because they're provocateurs and they don't want to be identified.
ICE is doing the same thing right now.
So ICE has become really a provocateur psyop.
They're not just out there to remove illegals.
And for the record, I agree that we have to remove illegals.
I have no problem with that because I support strong borders and I support our ability as a nation to say no to immigrants if we don't want them to come in.
Even though I'm pro-immigration in terms of legal immigration.
But what ICE agents are actually doing right now is way beyond enforcing laws about the border or illegal immigration.
What they are doing is provocateur operations.
They want to be on video doing crazy things to Americans.
They want to be seen as violating the civil rights of Americans because Trump wants the left to attempt an uprising.
And why?
Because it's going to play right into the Insurrection Act.
And right on queue, Trump just announced that he may have to invoke the Insurrection Act in Minnesota because of the lawlessness on the streets.
And there was an incident that just happened the other night where a bunch of the left-wing protesters, apparently they broke into some ICE vehicles and ripped the in-vehicle safe out and took, I think they took weapons and ammo and some IDs and things like that.
And that was bait.
That was just, that was put there to let them do that so that Trump could say, oh, look how bad they are.
Okay?
So again, there's no difference between Republicans and Democrats.
Really.
At the end of the day, it's the same uniparty.
But they fight with each other as factions within the uniparty.
But they use the exact same tactics on each other.
So this is a left-wing tactic that Trump is using against the left.
It's kind of like Judo or something, you know?
And the left is falling for it.
They are falling for it.
And every leftist podcaster and influencer right now is screaming that, oh my God, Trump, the tyrant, and he's harming Americans and threatening Americans and shooting.
One guy got shot in the leg and one kid got his eye shot out or something with a non-lethal weapon.
Maybe it was a paintball or something.
And the left is running with this, which is exactly what Trump wants them to do.
And why?
Why?
Because at the end of the day, this is an election year.
The midterm elections are coming up not that far away now.
What?
10 months or something?
A little over 10 months.
And Trump knows what you and I know, which is that the Democrats are absolutely going to cheat in the midterm elections.
They're going to cheat every way they can because they are cheaters.
The only way they stay in power is by cheating.
You know what they're going to do.
The same thing they did in 2020.
The same thing they do in every midterm election.
They're going to just cheat and cheat and cheat until they get the numbers they want and then claim victory.
And then they're going to control the House and the Senate.
And then they're going to use the House to impeach Trump.
And then they're going to use the Senate to try to convict him, but they won't have a two-thirds majority.
So that won't work.
But they're going to run the House and run the investigations.
And what the Trump group fears is investigations into the crypto shenanigans of the Trump family because there's a lot of insider trading that's going on there.
Oh, yeah.
There's a lot of things that could be prosecuted.
And so what Trump wants to do is make sure the Democrats can't cheat in the election.
And that's a goal that I agree with.
Yeah, we have to make sure the Democrats can't cheat.
How do you do that?
You have the military count the votes.
And how do you have the military count the votes?
Well, you have to have a national emergency to where you deploy the military, especially in blue cities.
Huh.
Starting to see how this comes together now?
So what you do is what's happening right now.
You send out ICE agents with masks to harass the people in blue cities.
You know, beat them up, throw them on the ground, pull them out of their vehicles, shoot them, you know, punch them in the face and make sure it's all caught on video.
Okay?
Shoot them, like they shot Renee Good.
I mean, that guy was trigger happy.
You know, that shot was not necessary.
She was on her way out of that situation from what I saw.
But ICE is being told clearly to provoke all of this and cause a left-wing uprising just in time for the Insurrection Act and the deployment of soldiers before the midterm election.
Now, importantly, you're not going to see soldiers nationwide in every city and every town, and especially not in rural areas, because remember, the point of the soldiers being on the ground is to count the votes.
And even, I would say, to count the votes honestly.
You know, if the election is honest, the Democrats lose.
Trump doesn't have to cheat in the election.
In other words, to have the GOP do well.
Because most Americans absolutely hate the Democrats.
And yeah, a lot of Americans hate what Trump is doing right now, but most of those people were never going to vote conservative anyway.
So you have the military count the votes.
You have the military watch.
You have the military make sure there's no ballot stuffing at 3 in the morning, etc.
And that's how Trump defends his power base in the House and the Senate for two more years.
And there's a very good chance that this is going to work.
Meanwhile, if Trump wants to, he could completely dismantle the Democrat money laundering campaign finance fraud machine.
Some of that is happening.
After all, USAID was dismantled, and Trump and his crew are exposing the situation in Minnesota with the Somali child care learing center, massive fraud.
And no, I don't think Nick Shirley just stumbled across this story and spontaneously just became an overnight sensation just by chance.
No.
This story was handed to Nick Shirley.
I'm convinced of it.
It's obvious.
And it was timed.
It was timed for this exact reason.
So Nick Shirley is playing a part in this series of events, planned events, to cause a left-wing insurrection.
Not nationwide, because leftists don't live everywhere.
They mostly live in their blue cities.
And that's where this is going to be focused.
And that's where the troops will be focused.
So if you don't live in a left-wing city, you're not really going to be dealing with troops in your face every day.
You'll see a lot of videos of ICE agents dress up like government goons and thugs and beating people.
Yeah, you're going to see a lot of that because that's on purpose.
But they're not going to come to a rural county and start beating up Christian conservatives, little old ladies going to the grocery store.
They're going to reserve those activities for the blue cities because that's where they need the uprising.
Now, remember, the more violent the left gets, the better this works for Trump.
So if leftists, and many of them are already talking about things like, oh, we've got to shoot, you know, shoot these agents and send them home in body bags and nonsense like that.
You notice that all that is allowed?
It's allowed on TikTok.
Huh.
I wonder why.
You notice on TikTok, you can't criticize Israel, but you can call for shooting ICE agents.
Yeah, why is that?
Because it's all by design.
Same thing on X. You can see lots and lots of videos.
You can share videos on X that have leftists calling for killing ICE agents.
That would never be allowed if they were videos of, let's say, Israel bombing children in Gaza.
Oh, that's not allowed.
But in this case, X got the memo.
Elon Musk is complying and allowing X to promote videos calling for violence against government agents.
Again, all by design.
So this is allowed on YouTube.
You see, you get the picture?
This is allowed everywhere because it's all about incitement of the violence.
And to some extent, it will work.
There will be some lone wolf leftists who think they're like woke Rambo or something.
You know, instead of a headband, it'll be like a rainbow.
What do they call them?
A rainbow scrunchie on their man bun, Rambo, you know?
That kind of person who will think that he can shoot up a bunch of government agents or something.
He'll run around with an AR-15.
And fortunately for all of us, leftists are really horrible with firearms.
They can barely hit anything.
But nevertheless, this is exactly what Trump wants.
He wants left-wing violence.
He wants a mass shooting carried out by a radical leftist that can be captured on video.
And then Trump can say, look, man, it's getting bad out there.
The left, you know, they're running a civil war now.
They're shooting and killing federal agents.
We're going to have to deploy the military.
We're going to have to deploy the Insurrection Act in 25 major cities, making sure that those cities include the swing states, the cities that count the votes for the swing states, which also includes Minnesota, obviously.
Go figure.
Or really, I mean, any state where it's a tight race, because, you know, swing states don't matter as much in the midterms as they do during a presidential election year, but they still matter in terms of control of the House and the Senate.
The goal of all of this is to really depict the radical left as insane lunatics, which they are, and to use that to crack down on the left.
Now, again, this is a left-wing tactic.
This was what was used against Trump and conservatives by the Biden administration.
So the suckers in all this are the people who go along with it or who are sort of hoodwinked into joining these violent protests or committing acts of violence against others.
Those are the people who are the useful idiots.
So if you're a leftist listening to this and you get so angry at Trump that you're dumb enough to pick up a gun and run around and try to shoot somebody, you're playing right into Trump's hands.
It's exactly what he wants.
It was the same thing under Biden.
If you were a conservative and you were angry enough to pick up a gun and try to shoot government agents at that time, that's exactly what the Democrats wanted.
They wanted to paint you as domestic terrorists.
And they did.
And the media went along with it.
Although, of course, right now, the media is siding with the left and not with Trump, as is usually the case.
So my advice to everyone is to don't be a fool.
Don't get suckered into these kinds of actions.
Don't join violent protests.
Don't bring weapons.
I mean, of course you have the right to peacefully protest and walk around with a sign.
You know, a sign like Trump can kiss my rump, you know, whatever.
And by the way, nobody cares about your stupid sign, but at least you're not being a violent terrorist, you know.
But if you come to these groups or protests with weapons, or you think you're joining some uprising resistance group that thinks they're going to take over and they're going to conquer Washington, D.C., and they're going to arrest Trump and we're going to go, you know, tomorrow.
Yeah, that's a Fed operation, by the way.
You're being recruited to be arrested and thrown in prison.
So enjoy your long sentence for stupidity for taking part in such an action.
Now, some cities will burn during all of this.
Well, some portions of some cities will burn.
There will be some domestic disruptions.
But overall, it actually won't interfere that much with a lot of operations in the United States because they're not located in the blue cities.
So remember, this is going to be a very local type of disruption event in the blue cities.
Most Americans will be able to just continue life as usual.
And although they might see reports of this on YouTube or the news or wherever, the truth is it's not really harshly impacting most people's lives.
Yeah, some of the images are going to be shocking.
Yeah, there's going to be bloodshed in America.
Absolutely.
Yeah, there's going to be left-wing terrorists who start doing crazy, insane, violent things.
And yeah, there's going to be violence from ICE agents who are going to beat innocent Americans in order to provoke this violence.
Yeah, you're going to see all that.
But those are going to be really small, relatively small events that are amplified by videos and media and social media.
And it's not going to be a day-to-day life type of situation for most Americans.
So my advice is focus on your freedom, grow your own food, stack gold and silver because the currency is going to shit.
Get yourself informed, gain skills, learn new things, use our free book creation engine at brightlearn.ai.
You know, create the books you want, learn whatever you want, do these things, and don't go to the riots.
Don't go to the protests.
Don't get involved in revolts or uprisings or resistance movements.
And also, for me, I was like, don't even bother voting because it doesn't even seem to matter.
But whatever, vote if you want to.
I think I'm done with that.
You know, be smart, and we'll see what happens.
Now, as I said earlier, it's clear that we live under a uniparty, so the outcome of the election doesn't really matter as much as you might think.
It matters to the factions.
It matters to Trump and his family, because if the Democrats ever get back in power, Trump's people are going to jail for a long time.
The Democrats will make sure of it.
So the real game for Trump and his people is to absolutely make sure that Democrats never win an election again.
And that's actually possible to achieve.
And in some ways, America would be much better off if Democrats never win an election again because they hate America.
They want to destroy this country, and they're insane.
They still think men can have babies.
For example, they still think mutilating children's genitalia is medicine or health care.
They're completely insane.
So I wouldn't mind if Democrats never win an election again.
But if they do, Trump's family's going to prison.
That's for sure.
So that's what this is.
This is a faction warfare action.
Gosh, that almost rhymes.
Faction action that just involves deploying certain acts of escalated violence and sort of recruiting the public to take part in this great theatrical grandstanding operation to make sure the Democrats can't cheat in the election.
That's what's happening.
Okay.
So once you understand that, yeah, maybe you can be a little less freaked out about it.
Just buy gold and silver, grow your own food, get off grid, get out of the freaking cities, you're going to be okay.
And, you know, America's toast anyway, by the way, the empire's toast.
The dollar is about to collapse.
The rule of law doesn't even exist.
Trump doesn't even follow the rule of law anymore.
I mean, even if Trump stays in power for now, the empire collapses before long anyway.
So the real goal is for you to safely navigate all of that.
Make sure you're as self-reliant as possible.
Make sure you've got your own money supply, i.e. gold and silver and private crypto, like Xano or Monero, for example.
Get off grid.
That's how you're going to survive this because the big collapse is coming.
It may be years away, but it's coming.
The dollar will not survive this.
And the United States of America, as we know it, will not exist much longer.
It's just about done.
But this chaos that you're seeing right now, this is not the big, the grand finale.
That's not what this is.
This is a small little bit part in the lead up to the grand finale.
So keep it all in context and don't panic.
All right.
Thanks for listening.
Take care.
All right.
Welcome to today's interview here on Brighteon.com.
Can you catch a cold?
We've all been taught that.
Most of us grew up believing that.
I believed it for a long time.
Not anymore.
But we all believe that there's some invisible thing called a virus that if it comes out of one person, that it can be transmitted to another person.
And then that person would redevelop the same symptoms that the first person experienced.
And that's called viral transmission.
And almost everything that's happened in our society since COVID has been driven by this belief in viral pandemics and epidemics and flu and warnings about the flu season.
What if it was all bullshit?
That's the question of the day.
And our guest today is an author and much more, but he's the author of a book called Can You Catch a Cold?
His name is Daniel Reuters.
His book is found at Amazon and booksellers everywhere.
And today, we're going to interview him for the first time to ask these questions.
Is there such a thing as a viral epidemic or pandemic?
Is there such a thing as a viral flu that can make you sick?
So welcome to the show, Daniel.
It's an honor to have you on today.
Thanks for joining me.
Hi, Mike.
Thanks so much for having me.
It's an honor to be here.
It's great to have you on.
Now, this is the first time we've ever met, and I actually love that we haven't spoken before.
And so I get to ask you for the first time about yourself and how you came to write this book.
So for the sake of myself and our audience, can you please give us a little bit of your background and what led you to this topic?
My background in natural medicine.
So I studied as a naturopath in naturopathic medicine and nutritional medicine.
I graduated, I think, roughly in around 2010 and went into clinical practice, worked my way up through the educational system.
So I was employed by a range of colleges and eventually a university.
I worked as a senior lecturer at the university and resigned in 2022 after I sort of couldn't bring myself to continue working in that position.
I couldn't ethically teach the curriculum that I believed was broken.
And in my undergraduate degree, I learned these principles that germs don't make you sick.
And I thought, what a load of nonsense.
I'm here to learn science.
Why are we learning this old school crackpot natural medicine stuff?
And I discarded that understanding for over a decade until I heard some doctors in 2020 talking about this idea, floating it again after many years of discounting it.
And I thought, maybe I should just go and revisit that and see if there's anything to it.
And that led me down a path of eventually writing the book, Can You Catch a Cold? Just to provide the evidence and almost a documentation of all the papers and things that I had read to inform myself about this topic.
Okay.
Wow.
So that's a fascinating background.
It also establishes that you've studied and taught a lot of information in this space, and you're clearly a critical thinker.
But of course, people like you are, your conclusions about verbology fall far outside the mainstream system and far outside what most people believe.
In your view, what is the most compelling simplified evidence, if that's possible, that allows us to share your conclusion that there isn't actual, that there aren't viruses that can propagate epidemics?
I don't know what's going on inside the human body at all, Mike.
I mean, I used to think that I knew, but I don't anymore.
The more that I learn, the more I realize how little I actually know.
So as I said, I don't really know what's going on at the micro level inside us.
For me, it's all a guess.
And there are reasons for that.
Maybe we can get into that later.
But the basic underlying principle of all this, or the philosophy, is that when someone's sick and they come in contact with a healthy person, they spread their illness to the healthy person.
Now, that should be a relatively easy thing to demonstrate.
Right.
You put a group of sick people in a room with a group of healthy people and you see what happens.
At the most basic level, we should see that the healthy people fall sick.
And I believe that these experiments have been done as do most of my colleagues.
We were of the opinion that we had this empirical evidence and this empirical data to back up this so-called phenomena that we think we observe.
And I went looking for that evidence.
And believe it or not, there's many dozens, if not hundreds of studies for all different kinds of illnesses that we are told are contagious, where they've taken healthy people, sick people, put them in a room together and observed the effects.
And by and large, not a lot happens.
The sick people don't seem to make the healthy people unwell.
So that's a major problem for the theory that we're told.
Yes, but a clarification.
It's commonly seemingly observed by people that, for example, people go to a trade show event or they go to a public speaking event and they come back sick very often.
And they think and they say, well, I must have been exposed to something there.
It must have been a sick person running around the trade show, made me sick.
I come back and I'm sick.
What would your answer to that be?
And let me just add an asterisk.
I happen to know that air travel is incredibly toxic all by itself.
You could travel on an airplane by yourself and get sick.
But what's your explanation for why people feel like that's what they are experiencing?
This is the entire premise of the book.
So it's broken into three parts.
And one of the parts is to look at the evidence for contagion.
And it's apparent that there's some problems with our underlying theory and our underlying standing, our underlying understanding.
I think we just need a course correction there to really reevaluate what we think we know.
And the other part, or a large part of the book, is providing alternative theories or explanations about why we might fall ill.
So I think I've posed maybe half a dozen or so different reasons there about why it may appear that people fall ill.
Again, I don't know if any of those are correct, but they all have validity and they've all been discussed at length in the literature.
So we owe it to ourselves to explore those things in greater detail, but we never have because we've been looking at this paradigm called germ theory with the blinders on for 120 years and we've never taken the time to adequately assess these various other explanations.
So I'll just give you one potential alternative explanation is the belief that healthy people, that sick people make you sick.
So there are experiments that are being done where people have been told in a controlled setting that they're being exposed to flu germs and they get ill very quickly.
There was one experiment where they took a group of people, put them in a room and said, okay, we're going to give you the flu germs now, expose the person to the germs.
And within a matter of hours, they were coughing and sneezing and spluttering and up all night shivering.
The nurse comes in the next morning and says, it's an April Fool's joke.
We didn't actually infect you with flu germs.
We gave you salt water.
And they got better within 15 minutes.
So that demonstrates to us that belief alone is enough to induce the symptoms of a cold or flu.
So we're told from a very young age that when you come in contact with someone with symptoms, they will make you sick.
So is it possible that we believe that in that explanation and that phenomenon so much that when inevitably one day we do come in contact with someone who's ill, we get sick because we use the power of our mind through a thing called a nocebo effect.
Obviously, there are many other potential explanations going on, but that is just one of them.
That's a very powerful point that you just made there.
And I've got two comments on that.
Number one, since I stopped believing in the theory of verbology, I have never been sick.
So that's interesting.
I mean, the worst symptom I've had is maybe a very slightly sore throat, which just could be from me overexerting talking because I do this professionally.
And sometimes I'm screaming in my podcast.
And that's probably overworking.
But whatever.
So belief is very powerful.
And for people who might question that, I would like to point out there are documented studies and experiments in the realm of hypnosis and mind-body medicine that clearly show that when people believe they have been touched by poison ivy, for example, their skin will break out in itchy hives and rashes consistent with what they understand as symptoms of poison ivy, even if it was not poison ivy at all.
So I just want to clarify that to our audience that the mind makes it real if the belief is in place, but that speaks to the toxicity of pushing the belief itself.
So in other words, the theory of the virus is the virus.
In other words, you could say that.
Yeah.
Your mind is infected first, and then your mind makes it real.
I mean, at least that's one explanation.
What about the electromagnetic exposure or electropollution theory?
You know, radio waves and 5G and everything else.
I assume that's probably one of the theories that you perhaps considered?
I did.
I didn't find a huge amount of evidence to demonstrate cause and effect relationships there.
So it was very difficult for me to, with any certainty, say that when you're exposed to electromagnetic frequencies, that it might cause colds or flu.
It very well may.
I did find some evidence for that and did reference in the book, but I didn't focus a lot of my time and attention on it because I wanted to stay away from speculation as much as possible.
So, again, there might be evidence out there to show that this actually occurs on a greater level than I found.
But yeah, I mean, I found more evidence for the psychological side of things, the toxicological side of things, the environmental side of things as well.
So exposure to various meteorological effects like changes in humidity and temperature.
These were the sort of real standout ones that I came across.
But just a note on the whole side of belief, Mike, or the power of belief.
I included many different examples of people becoming sick one after another, same time, same place, where researchers and doctors came in to investigate what the cause was because they thought it was a contagious illness, but it actually wasn't.
And they put the answer down to a thing called social contagion, which is a phenomenon that they don't really know how to explain.
Where they see a contagion-like effect, they go in, they look for a germ, they can't find it, and they say, Well, it must have been a psychological thing, a mass psychogenic illness.
And I mean, there's also experiments where they've told people who have asthma that they're going to give them a substance that causes an asthma attack.
So they give it, the person gets the asthma attack.
And then at the height of the attack, they say, Okay, now we're going to give you the drug that cures the asthma attack.
They administer it, asthma attack goes away.
But little did the participants know that they were actually being given the drug that treats the asthma attack first.
And then to treat the asthma attack, they were being given the substance that is meant to cause the attack.
So it had nothing to do, the effects had nothing to do with the drug or the substance they were being exposed to at all, and everything to do with the story that they were being told and their belief in that story.
You know, it reminds me of clinical trials for antidepressant drugs where there's a placebo group, and you know, and then there's the group that receives the actual chemical.
And usually the participants in these studies, they want to be among those who receive the quote real medicine, but they're told that the medicine can have side effects that are negative.
And then if they begin to experience the negative side effects, they get very happy believing that they've got the real drug and then their depression ends.
So it's like, yes, I'm having weird side effects.
That's awesome.
Now I'm happier.
And then that ends up showing that the antidepressant works, even though it just caused side effects.
Yeah, Irving Kirsch did some great work on this back in the 90s.
It's incredible.
It's a professor from one of the major universities.
So, yeah, being able to work out whether or not you're being exposed to an active substance plays a major role in these blind studies.
And that was another point that I made in the book: in any of these contagion experiments where they say they're exposing people to flu germs, they don't control for these aspects of things like contain of the nocebo effect.
They don't control for that.
So how do you know that it wasn't the person's belief that created the symptoms that you observed?
How do you know that it was actually a germ or a virus?
So, yeah, there's many confounding variables or external factors that might influence the outcomes of these experiments where they've put healthy people and sick people together in a room or exposed healthy people to their bodily fluids, for example, and observed symptoms.
There's many other explanations for that that haven't been controlled.
And it's for those reasons that I can't hand on heart say that, yes, a germ ain't too ill because these other things could have explained away the negative effects that occurred in any of these people who got ill.
And until such time as we do that, then we can't say for sure that contagion has been empirically demonstrated.
Okay, let me give out your website.
I've got another angle to cover with you here.
So your website is humanly, H-U-M-A-N-L-E-Y, humanly.com.
And we'll talk about, you know, I'll give you a chance to plug it later what people can find on your website.
Just want to give that out.
But let me mention this angle here from a lab standards angle.
So you may or may not know, but I founded and owned a very accomplished MassSpec food laboratory.
I'm a published food scientist.
I develop methods in mass spectrometry and chromatography.
And so it's routine.
I mean, in our lab, it is ISO accredited.
We're audited, inspected.
We pass proficiency testing, et cetera.
We know exactly what we're doing.
So that is dealing with heavy metals or glyphosate or atrazine or aflatoxins or what have you.
Well, a few years ago, I reached out to our standards providers to ask if I could acquire a standard of SARS-CoV-2 because I wanted to start testing for the presence of SARS-CoV-2.
Now, and I'm sorry for the long explanation, but you'll appreciate this setup.
When I want to test for mercury, I buy a mercury standard and it has mercury in it at a specific concentration, like 100 micrograms per milliliter or whatever, and it's stabilized in nitric acid at some concentration.
Okay, so I can push that into the instrument.
And the instrument, I can say, this is 100 parts per million mercury.
And then I can dilute, I can make a curve.
I do a five-point curve.
And then I can take an unknown sample and I can say how much mercury is in this unknown sample, compare it to the physical mercury that you saw at the atomic level, because we're talking about atomic mass spectrometry.
Okay.
To me, that all makes sense.
But then when I went to try to buy a standard of SARS-CoV-2, I found out it doesn't exist.
It doesn't exist.
And what the companies labeled as standards were not standards.
They were not isolated.
They were like cow serum, cow blood, and pig blood, and human snot from somebody who they said was symptomatic.
They got a woman coming off an airplane who had the sniffles and they grabbed her mucus and they put it in there and mixed it with the cow blood.
And they're like, that's a standard.
Like, what are you talking about?
That's not a standard.
You need an isolated solution that's nothing but SARS-CoV-2 and nothing else with homogeneous particles with a specific molecular weight that I can put through a chromatography column and I can get a peek.
And none of that exists is my point.
I'm sorry for the long explanation.
What's your reaction to that?
Like, none of that exists.
You're exactly right.
You need to have a gold standard for whatever it is that you're testing for.
So for something like mercury, for example, we have that gold standard.
You can go out into nature and find mercury and get your gold standard and then develop your test from that standard.
But when it comes to a lot of these things that happen in laboratories, there's leaps and bounds of logic and assumption that are made in those first initial steps where you start taking a crude sample and then immediately adding things to it in the process that is claimed to isolate the thing you're looking for.
Now, unless you control for those initial steps, you don't know whether or not they're actually confounding the results, i.e., causing the effects that you're looking for.
So you have to control for those steps to show that the addition of the thing to the sample doesn't, A, create the thing you're looking for, or B, change something inside the sample away from what it is like when it's inside your body.
And the only way you can do that is by having a gold standard to compare your results to when you start adding these things in.
So without that, then I think, you know, it's a bit uncertain as to whether or not you're seeing in the lab is actually reflective of reality.
Well, and that can be.
To add to that, you know, in metals or pesticides or chemicals or chemical markers in foods or caffeine or whatever, you actually have the physical molecules available as standards.
I can buy a caffeine standard.
You know, I can buy ascorbic acid as a standard if I want.
But when it comes to virology, all the equipment, you download digital libraries.
So there are no physical standards.
It's a download from the company that sells you the equipment that they claim detects this thing, but you never actually have the thing.
Isn't that bizarre?
Yeah, I liken it to a baker baking a cake.
So if there's a claim that's made that chocolate cakes in nature cause disease when you eat them, well, you have to say to the person making that positive claim, show me the chocolate cake in nature first.
Right.
And if that person said to you, yeah, I'll show you the chocolate cake, step into my kitchen and I'll take some flour and chocolate and milk and sugar and mix it in a bowl and put it into an oven at 180 degrees and bake it on high for 90 minutes, ta-da, there's your cake.
That's proof that chocolate cakes exist in nature.
And when you eat them, you get sick.
I'd say, well, hang on, show me the cake in nature first because you're saying that they do exist in nature and they do make you ill.
I don't want to see it in a kitchen after you've mixed a bunch of stuff together.
I want to see that the cake in reality.
And this is, to me, is kind of what happens in these labs.
It's like step into my lab, let me take some bodily fluid from you and I'll mix a whole bunch of stuff together.
And then I get an effect and then I make a story up about that effect, which I don't think we can validate.
So it's a major problem.
No, but you've nailed it right there.
That this is a story.
It's a narrative that's been pushed by virology, the virology community for so long.
And they've built an entire library of science and medical journals all around it for decades and a lot of profits too.
There's a tremendous amount of business that's conducted based on this idea.
For example, the flu season.
And even right now, we're told, oh, the super flu is spreading in 35 cities.
You know, you better get your flu shot.
And yet, during COVID, the flu somehow completely vanished in 2020, which, and then I studied, you know, how does the CDC determine when someone has, quote, the flu.
And that is so loosey-goosey, it wouldn't pass a high school science paper test.
I mean, they literally just make that up.
But what have you observed about that?
This is an issue that the researchers and doctors and scientists came across as well in their studies with colds and flus.
One of those things was: how do we define what a cold and flu is?
They spoke about how difficult it was to actually objectively list or come up with a definition as to whether or not a person has a cold or flu or not.
And because those definitions were so arbitrary, they had a lot of leeway as to whether or not they believe someone was sick or not after coming in contact with an unhealthy person.
One of those studies, they just said, look, if you sniffle three times in 24 hours, we consider that to be a positive sign of a cold.
I mean, it's so arbitrary.
And yeah, it's not as though in these experiments, people were coming down with the definite cold and flu symptoms that we would all think that a person experiences.
Sometimes it was, you know, one cough and three sneezes or sniffles in a set period of time.
And that was considered to be a positive case.
So, you know, another thing that was very interesting, Mike, as well, is that in some of these experiments, they took bodily secretions from people and injected them into their blood or into their nasal cavities or eyes, ears, nose, throat.
And in some instances, people did become unwell.
And they said, well, wow, that's proof of contagion.
However, that's an unnatural route of transmission.
So it's claimed that when you come in contact less than six feet of someone, they cough and sneeze and they emit the germs to you.
But in these studies, they were actually taking large quantities of bodily fluid and putting it directly into another person, which is not how it happens out there in reality.
And people were getting symptoms.
Now, what's interesting is that inside the bodily fluids of a sick person, so-called inflammatory markers increase in concentration.
And those markers are claimed to be the driving factors behind why we get symptoms.
Now, what happens, interestingly, is that when they take those inflammatory markers or mediators and expose healthy people to them, they get symptoms of colds or flu.
So just by exposing someone to so-called infected bodily fluids and observing illness doesn't necessarily mean it was a virus.
It could have been inflammatory mediators.
It could have been belief.
It could have been a wide range of things.
So again, it seems that the waters are very muddied and uncertain in this field as to what's really going on.
I don't claim to know what's going on.
Like there might be germs out there making people sick.
There might be viruses.
I don't know.
But until such time as we actually go and do better science and control for these external factors and variables, we just we're flying blind, essentially.
Yeah, I'm with you on that.
I mean, I'm scientifically trained and I have a curious but rational mind.
I'm open to an explanation of germ theory if it can be proven.
But if there are germs that may make people sick, I should be able to buy a standard of germs as an ISO-accredited laboratory to be able to study those germs.
I should be able to, you know, open the vial under a fume hood.
Let's say I should be able to put it under a microscope.
Maybe it's an electron microscope.
And I should be able to see a bunch of particles that are basically the same size and shape.
And then there's the germs.
There they are.
Oh, the villains.
I found them.
And to date, no one has done that.
Now, we can do that with fungi or fungal spores.
We can do it with bacteria.
We can look at like VX nerve gas chemicals on a chromatography column.
We can see it in the peak.
We know the mass to charge ratio.
We can look at the chemical composition through a variety of means.
We have all these other ways to prove the existence of all these other things that can make people sick, like exposure to toxins.
But viruses, none of that's true as far as I can tell so far.
Is that also what you're seeing?
Or have I said something just now that maybe you've got better information?
I tend to agree with what you're saying.
I think it's very difficult to prove conclusively that these particles are what they're claimed to be.
So yes, you can do electron microscopy or some kind of chemical analysis or genetic sequencing on some bodily fluids, but you have to have your gold standard first.
You've got to show that the thing you're looking for exists in nature in reality, get your gold standard and then go from there.
But again, that's never being done.
And I don't think it can be done because, you know, the very, we say that these things exist in the bodily fluids of a sick person.
So show them there in the first place.
Take the bodily fluids and then show the virus in there without anything being added in from the outside, any external factors.
Right.
But they've never done that.
No.
They've always added things into that SNOT sample first, meddled around with it, and then they start to analyze it.
Well, how do you know that doing these various steps in your methodology hasn't confounded your variables?
And again, there's sort of no explanation for that.
They just assume that those steps don't confound the variables.
So assumption is the antithesis of science, Mike.
You know, this is why we do science to get around belief and around assumption.
Right.
So when you follow the trail of breadcrumbs all the way back, you know, to these foundational steps, we find that, hey, these various steps haven't been controlled for.
How do you know that they didn't confound your variables or confound your results?
And this is very important, what you just said, because many labs do drug testing, right?
So you pee into a cup or maybe they take a blood sample.
They run it through equipment like what I have and they can actually pull out a drug.
If somebody has, you know, cocaine or meth or whatever, that can actually be isolated from the blood with very high purity using selective methods, you know, elution time windows for chromatography.
So you can actually pull the cocaine out of a person's blood, but they've never pulled viruses out of someone's blood that I'm aware of.
It's never happened.
Have you ever seen a study where they took a person who was, quote, infected with even Ebola, you know, so-called whatever it is, were they able to pull Ebola out of that person's blood?
And then here it is.
We found the Ebola and stick it under a microscope and there it is.
Has that ever happened?
I don't, it might have been, but I don't think it has.
And I mean, this is admitted in many papers is that they don't see these particles in tissue samples or bodily fluid samples directly taken from a sick person.
They have to meddle around with it first in a lab in a cell culture to see the virus.
And they say it's because there's not enough virus to see or the virus is too small.
So that might be true.
But again, you've got to be that pesky five-year-old, Mike.
You've got to ask the question, how do you know that?
Right.
So how do you know now I've taken a sample and put it in a culture flask and added something to it that it didn't create the little particles that I'm observing in the electron micrograph?
And again, you can't do that.
So yeah, it's a major problem.
And I'm not sure if there's any way around that.
And I kind of think that a lot of these uncontrolled steps that occur in these labs will never be able to be controlled for.
Because how do you actually see the thing on a micro level first without bringing in external variables which might confound your results?
It's a very tricky thing to do.
So with something like cocaine, for example, I mean, you can get some pure cocaine and then you can do a controlled study.
You can get a group of people, give half of them cocaine and half not, and then go and test or devise a test for that and see with what level of accuracy and specificity does my test show or detect people have had cocaine.
And you can, you know, show that, yes, it has a very high degree of certainty.
It's like 99% or 100% accurate.
But you can't do that with a cold or flu virus, which I think is interesting.
Right.
Well, and so I'm sorry, but let me mention another huge aspect of this that maybe you haven't covered in your book, but it's of great importance to food safety.
So, you know, my company manufactures food.
That's why we use our lab to test all of our food for all these possible contaminants.
And we test for various microbiological contaminants such as listeria and E. coli and salmonella, et cetera.
And all those things we can see under a microscope.
And so we use an incubation method that in some cases takes 72 hours.
And then we have a, you know, we have automated equipment, et cetera, right?
So we incubate a certain sample size.
And then if it grows listeria, then, you know, the color changes of the test vial, et cetera, right?
And this is all well validated.
Well, a few years ago, we were approached by a company that said, no, you don't have to do any of that.
All you have to do is test for the genetics of a virus or the genetics of bacteria.
But they also specifically mentioned viruses.
Like, what if your food's contaminated with viruses?
How are you going to know?
Because that's not going to show up in the E. coli test.
So I said, well, what you have to do is use this PCR equipment in order to test for the presence of the genes of the viruses or the bacteria.
And I said, I met with the sales reps and I said, okay, that sounds great.
We could save a lot of time.
Does your instrument give me quant information?
Does it tell me the level of contamination?
How many units did it find per gram or milligram of the sample?
And they said, no, that's not possible.
There's no quantitation information at all that comes out of PCR.
And that's when I said, wait a second, you mean to tell me that food companies all across this country are using your technology to say that food is safe when there's no way that your tech can know how much of anything is in the food?
And basically they admitted that's the case.
So food safety is some of it's just a fraud as far as I can tell.
And we don't use that method.
But what's your reaction to my story that I just told it?
Because that's all true.
Yeah, I think there's some major oversights that need to be addressed.
And again, like, can we actually address these?
Is it possible to do it?
Or is it an impossibility?
And the only way you can really know is to do the proper science.
And that's essentially what I've advocated for in the book, is to go back to the foundational papers, look at the methods and say, right, have we dotted our I's and crossed our T's and controlled for all the variables as best we can?
And if not, then why not?
And if not, can we?
And if we can, how about we go back and do these experiments again and show with certainty that what we say is going on out there in reality is actually transpiring.
So I think the more work we do in a lab on these things, which are really they should be answered through empirical research, so direct observation with our five senses, the research in a lab is not reflective of that.
It doesn't tell us anything about what's going on in reality out in nature.
All we can say for sure is that when I do XYZ methods in a lab, I get this result.
And it may be consistent and might get consistent results, but does it have external validity is the question, which means is there applicability to the real world?
In a lot of these cases, I don't think there is because they're doing things that we just don't see happen out there in nature.
So there's also, I want to talk about the culture of science, which has become, I have to say, it's an obedience cult today.
And the reason I say that is because if you go into any lab and you start to ask the questions that you and I are asking, you won't be taken seriously.
They'll say, oh, no, no, no, you have to accept these statements as true, even though there's no real evidence behind it.
That's the foundation of the science.
And there's this gap of rationality.
But I mean, I've found that I have a lot of success in my science developing new methodologies like glyphosate quantitation without using post-column derivatization techniques that are very toxic.
I developed that method because I didn't listen to the cult.
They said it can't be done.
And I said, yeah, bullshit.
I'm pretty sure it can.
And now we've validated the method.
Sorry about my language, but that's just what it is.
But what do you say about the cult of science that exists today?
I think there's been processes and an understanding that's been arrived at somewhere along the line and then passed down from professor to student.
And then that student becomes a professor eventually and passes it down to their student.
And that's all they've ever known.
And it's written in the textbooks and they pay a lot of money.
Well, I certainly did for my degree because I spent a lot of time learning these various bits of information and you hold them very preciously to your heart because you believe it to be true.
And then if someone questions the knowledge that you've learned over the years and spent a lot of time and money on, well, maybe you're not so willing to question those things because it may challenge everything you think you know.
So we have to have some kind of humility to be able to re-evaluate these things and say, right, we are looking for what's really going on, regardless of what it might be.
If it doesn't suit the underlying story that we've been told or held for a long time, I'm willing to challenge it and that's okay because we're doing science.
But it seems now as though there's so many preciously held beliefs that cannot be challenged simply because we've believed them for a really long time.
And that sort of forms the fabric of our society.
And if you challenge those things, then it may disrupt the way that we live our lives and how society functions.
And, you know, that, again, isn't science.
That's more like we're getting into the realm of politics now.
So it's interesting that throughout most of the history of the human species, knowledge was passed down through storytelling, especially in the pre-writing era, right?
Pre-alphabet, pre-written language era.
It was passed down with stories.
And, you know, whether it's Native American or ancient Tibetans or Amazonian tribes, they all had stories and they would tell stories that today we might find to be fantastical.
It's like, oh, the angry God in the sky came down and ate the moon and this and that, right?
And today we look at that and we think that's silly.
But yet we in our Western culture, we do the exact same thing.
We tell these stories about viruses.
It's really no different and it has no more scientific basis than the ancient indigenous tribe stories.
At least that's my comment.
What do you say?
Yeah, these are all stories that I don't think have been validated.
We're trying to explain complex things that happen out there in nature, which we don't really fully understand yet.
And if you look at the root word of virus, it means poison.
And our ancestors, and this is why I went into the history of colds and flus in the book to the extent that I did, because I think that our ancestors actually had a far better grasp on what colds and flus might actually be and what causes them than we currently understand today.
So the root of the word is poison, like a virus.
And the root of cold and flu is essentially the symptoms that you get when you're exposed to changes in temperature or weather conditions.
That was where these words derived from.
So maybe our ancestors actually knew far much more than we give them credit for.
Yes, yes.
But, you know, that's the age-old story, isn't it?
Don't go outside in the cold and the wet because you'll catch a cold.
So I'm not parents really wrong about that.
But, okay, I was told that if you go outside, if your hair is wet and you go outside and it's cold, you will catch influenza.
Now, that never made sense.
Even today, it doesn't make any sense at all.
How do germs know that my hair is wet and come to me from the cold weather?
Right.
So even the stories as they are told today don't make any sense at all if you just stop and think about it for two seconds.
This is what's so bizarre to me is we still have people telling these stories to their children or a doctor telling a story to a patient.
Like, you don't have an immune system until I give you one.
You know, it's like, come on.
Yeah.
There seems to be a range of different things that probably happen.
Again, I don't know for sure what's going on in there inside the human body, but a range of different things that may happen when we're exposed to changes in temperature and changes in weather conditions.
Now, one of those things is that our lungs are constantly cleaning themselves.
We've got these little broom-like structures called cilia that line our respiratory tract, and they're constantly sweeping out all the inhaled matter that we breathe in throughout our day.
But when there's a change in humidity and temperature, that process, those little cilia, are inhibited and they no longer sweep out and clear out the inhaled debris to the level that they did when the temperature was as it was before.
So if you're breathing in a whole bunch of junk and then the temperature or humidity changes and now your body's own ability to clear that stuff out is impaired, but you're still inhaling the same amount of stuff in the air.
Well, now it's going to build up in your lungs.
And it seems that the body mounts a certain response, i.e., producing lots of mucus, coughing, sneezing, and sloughing off the lining of your respiratory tract to clear that inhaled particulate matter out of you.
So this may be a conservative and adaptive response rather than so-called infection with a germ.
Good point.
So, you know, is that a potential cause of colds and flu is exposure to these weather changes?
Certainly we know when people get exposed to conditions where there's a lower humidity or a change in humidity, it dries out your respiratory tract.
Now, is it just that you're now building up a bunch of gunk into your lungs and you've got to now clear it out?
Or is it that your lungs become dry and now you're more susceptible to the viruses that are in the air that you're breathing in and they infect you and make you ill?
This is a major question that we have to get to the bottom of.
And also, there's a environmental effect or is it a virus?
These changes in humidity and temperature that used to exist in nature were very slow transitions, but now in indoor environments, you're going from a building to the outside or in an airport into an airplane.
And these sudden changes can be more rapid than what the human body ever evolved to be able to handle, right?
So those could be issues as well.
But I want to ask you, the forward to your book, again, your book is called Can You Catch a Cold?
Question Mark.
And I love the fact that you're asking the question.
I love your humility, Daniel, that you're not claiming to know everything about what's happening in the body, but you're asking questions.
That's the right approach, I believe.
But the forward was written by Dr. Samantha Bailey, who we interviewed here.
And as I recall, she was writing hundreds of letters to various universities and science institutions all over the world, asking for one of them to show proof or any evidence of the infectiousness of an isolated virus, to put it simply.
And last time I spoke with her, which admittedly is a couple of years, not one institution responded with any evidence that that ever happened.
Do you have any more recent knowledge on her efforts?
I think Dr. Sam Bailey and her husband Mark have done a lot of great work in this area, as have people like Christine Massey.
So she's made hundreds of years.
Oh, I'm sorry.
It was Dr. Massey that was writing the letters.
Yeah.
Yeah.
Thank you for the clarification.
No, but I did interview Dr. Samantha Bailey after that.
I may have conflated those two people, but I apologize for that, but please continue.
That's okay.
Yeah, there's a lot of work.
And Dr. Bailey or Drs. Bailey have been in contact with some of these mainstream institutions and having these hard conversations as well.
And I don't think there's been any major updates or revelations in regards to getting this information that we're looking for.
And I'm not sure if there ever will.
I guess at the end of the day, the thing we have to ask ourselves, is the underlying story that we're being told true.
If it is, fantastic.
We can just go about our life and do the things that we can do, do our best to build our immune system and protect ourselves.
But if the underlying story requires some course correction, does it necessarily mean that we need to do things differently?
Well, maybe, maybe not.
I mean, the fundamental principles are that if you don't eat a good diet, if you don't get enough sunlight, if you get exposed to toxins and poisons in your environment, they can all impair your immune system.
And you're now at or more susceptible of being infected by a germ.
But on the flip side, if a cold or a flu is a conservative process, it's actually designed to assist your body clearing out things that you've been exposed to in the environment.
Well, maybe you still need to do those things that we've just mentioned anyway.
Getting out in the sun, getting good food, breathing clean air, moving your body, not because it's building up your immune resilience or your immune system, but by reducing your overall toxic load.
So either way you sort of look at it, you're still doing the same thing.
It's just the underlying story might not be true.
So if it's not a germ, then it takes the fear away of being in contact with your fellow man who has symptoms because it means that they can't necessarily transmit anything to you, which is different, very different to the way that you look at it on the flip side, that it's actually that a cold or a flu is earned or it's a consequence of environmental factors rather than a little microorganism out there lurking in the shadows trying to get you.
And as I mentioned earlier, Mike, there's been hundreds of these experiments that have been done trying to demonstrate that this phenomenon occurs.
And the doctors and scientists have basically thrown their hands up in the air at one point in time and said, it's almost impossible to, well, yeah.
It's almost impossible to show this.
Right, right.
But I want to mention there's a liberty factor in all of this because governments, when people believe in the theory of infectious virology, governments can use that belief to take away their civil liberties.
They can force people to lock down in their homes.
They can try to coerce people to take vaccine jabs that they otherwise would not want to take.
And in some countries, they just literally force you to do it.
They can shut down businesses and ruin economies.
All of this happened in the COVID era.
And it was all based on the widespread belief of virology that, as it turns out, is not rooted in rationality or evidence at all.
So tyranny comes from ignorance in this case, doesn't it?
Yeah, absolutely.
So you could say that that may be the root cause of all of these issues.
If we lived in a truly democratic and scientifically minded society, Mike, I think what happened in 2020 would have gone very different.
And I'm not sure that people really consider how different that outcome or that sequence of events may have been.
So rather than saying, Rather than the peak health bodies and governments around the world saying, we know this for a fact, there's a germ out there that's going to come and get you and it's going to infect you and you need to do these things to protect you.
Maybe the conversation should have gone.
It's our best understanding currently that this is how the theory works, but we're not 100% sure.
And because we're not 100% sure, therefore we can only make recommendations for you to do these things.
And if you don't treat it, no problems.
Right.
I hear you.
Instead, they attacked everybody who questioned it.
They labeled them the disinformation dozen.
They de-platformed and de-banked people because they, the government, they were so sure that they had the only answer of truth.
Even the FDA mocked people for using ivermectin, which seemed to help a lot of people with various symptoms, etc.
They even mocked the existence of the immune system.
They said it's a conspiracy theory in some cases that the immune system even exists.
Imagine that, right?
So that's how far we went down the deep hole of ignorance and tyranny.
Very bizarre time.
But so I appreciate your work, Daniel, because you're helping us see through the delusions and the illusions and maybe have a better future if we can return to some standards of critical thinking, rationality, and evidence.
Is there anything else you'd like to add here as we wrap up the hour with you?
Don't believe anything I've said.
Don't believe anything that I write in the book.
I've put over a thousand references in that book and had a number of subject matter experts review the book.
So I actually had a virologist and microbiologist review it, someone who I trust and had a psychologist overview and help me with some of the chapters in that book because we have a focus on some of the psychological aspects as well.
So we really tried to do the best we can or the best we could to make sure all the information presented in there was as accurate as possible.
So even though we've done our best, don't believe anything that's written on those pages.
Go and do your own research.
Look at those references, read them for yourselves and come up to your or come up with your own conclusion.
Now, if it just so happens that your conclusion is, say, different to my worldview or your worldview, Mike, that's fine.
But at least you did the work to come to that conclusion rather than just being blindly or just blindly believing what you've been told.
Well said.
I have the same view.
I respect somebody who has thoughtfully considered a position, but that's extremely rare today.
It's almost non-existent, actually.
People don't have time.
They're so busy just trying to survive in this crazy world that they have to take the word of experts because they've got to put food on the table.
So they've got to be working 40, 50, 60 hours a week and doing all the other things just to survive.
So they don't have the ability to go and look for themselves.
And even if they did, they may not necessarily have the skills and the ability to critically appraise the literature in such a way.
So they are really reliant on others to inform their worldview.
So it's a very difficult thing, Mike, to have conversations with people about their worldview.
And those worldviews are based upon beliefs and opinions rather than facts, because you can't come at them with facts to disprove their beliefs and opinions.
The only way you can really challenge that is, well, I'm not so sure you can.
It just seems that these beliefs and opinions have become so ingrained in us that we're just unwilling to think about things outside the box.
And that may be for a number of reasons.
Probably don't have time to get into that now, but it's certainly going to be interesting to see where things go over the next few years, certainly given that More and more people are questioning the story that they've been told.
Seems like the cat is sort of out of the bag now, and it may just give us the opportunity to course correct and align with how things might really truly be working rather than just blindly following what is written in the textbooks or professed by a person standing at the front of a hole.
Well said.
And I would just add that the human brain typically uses only about 20 watts of power.
And even though it's a miraculous cognitive, neurological, computing, holographic machine, and much more than that, it's beyond physical.
It's still very limited in power.
So people take cognitive shortcuts and they believe whoever claims to have authority.
And that's a coping mechanism to live in a world without having to become an expert in every area.
No one can.
So you believe so-called authorities.
And then those authorities, they end up becoming a priesthood protecting a series of false stories.
And that becomes science.
And I say that as a scientist myself.
I'm a scientist.
I'm a published scientist.
But I'm one of the few that still is willing to ask questions like you are.
So thank you so much.
The book is called Can You Catch a Cold?
Daniel Reuters, R-O-Y-T-A-S.
You can find it at booksellers everywhere.
And be sure to check out Daniel's website, humanly.com.
And that's spelled with L-E-Y at the end.
Humanly, or whatever you want to pronounce, humanly with L-E-Y.
Thank you so much, Daniel.
It's been a pleasure.
Thanks for putting up with my crude humor at times.
But we really appreciate you.
Love to have you back.
Thank you so much, Mike.
It was a pleasure speaking with you.
Really appreciate the opportunity.
You too.
Had a great time.
Thank you for all you're doing.
And thank you for watching.
This has been another interview here on Brighteon.com, where we are exploring the world and our reality to help empower you with knowledge and information that helps you get better.
And I don't believe in virology, infectious disease theories anymore, but I do believe in nutrition.
So this is what I'm drinking today.
And I do believe in fitness.
I believe in sunlight.
I believe in nature apathy principles.
And that's why I don't get sick.
So, hey, if you also want to not get sick anymore, listen to interviews like this and share the information with others and upgrade your nutrition, your food, your lifestyle, your quality of your sleep, your exposure to natural sunlight within reason.
You're going to get better and healthier as a result.
So thank you for listening.
I'm Mike Adams here, the Health Ranger of Brighteon.com.
Take care.
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