All Episodes
Previous Next
May 4, 2022 - Health Ranger - Mike Adams
01:00:52
PHANTOM voters exposed by Bobby Piton: This is how Biden got 13 million extra votes
| Copy link to current segment

Time Text
Welcome everyone to Brighton Conversations.
I'm Mike Adams, the founder of brighteon.com, the free speech video platform, an alternative to YouTube.
And today we have a very special guest who is an expert in numbers, financial analysis.
In fact, he runs an investment firm called Preactive Investments.
That's his website, is PreactiveInvestments.com.
His name is Bobby Pyton, and he joins us today by video to talk about a statistical analysis Sleeper voters, phantom voters, and what happened in Arizona and Pennsylvania.
So welcome to the show, Bobby.
It's great to have you on.
And where would you like to begin?
Well, number one, I'd like to say thank you very much for having me on.
I think it's extremely important that people like yourselves that are offering an alternative to the censorship that's been taking place with mainstream media as well as the corrupt big tech companies that are trying to silence the truth.
It's literally doublespeak is occurring right before our eyes.
They try to tell us that this is what reality is when we all know that it's not.
And so I'm very grateful that you have set up your company and that you're out there putting your money where your mouth is to create an alternative platform to get the truth out.
So thank you so much for having me.
Well, absolutely.
And what you just mentioned is utterly true, that in order to believe that Joe Biden won this election, you have to believe that two plus two equals five or three or something, because if you believe in math, Then you know that his, quote, victory was impossible.
So walk us through some of the things that you've discovered and how that shows the degree of vote fraud, specifically in Arizona and Pennsylvania.
Sure.
So let's go back to the start in terms of, if you don't mind, when I first was testifying, I guess on November 30th now, I had a friend contact me the Friday before.
I only had like two and a half days to prepare to go through over three million voter files.
Her name is Liz Harris.
She was running for office in Arizona and she felt as though something was way off because she campaigned aggressively.
She had a lot of support and she was confident that she should have won that race.
Somehow, she didn't win that race.
At some point, we'll look over the results to see why she didn't win, but she doesn't want to think about that right now.
Her bigger focus is on making sure that President Trump receives justice and rightfully gets the electoral votes from the state of Arizona.
She reached out to me, asked if I would look at the data, help her as a friend.
I looked it over.
I told her, this is going to be pretty complicated.
I can do the work and give you the result if you like.
Basically, we kind of had some conversations back and forth.
Ultimately, she asked if I would be willing to come to Arizona to testify.
I said, sure.
I came in.
I didn't know if I would testify or I would just kind of give my report.
I still came because I do believe that the numbers were glaringly obvious that President Trump I had won the state of Arizona, and it wasn't reflected.
So what I did, and I mentioned this in the testimony, and this was really what kind of sparked The discovery of these phantom voters and the types of groups.
There's five different types of phantom voters that I talk about, but the U voters is what sparked it.
So let me just take it from the top.
There's 15 counties in Arizona, and there's five different classifications of the type of voter you are.
If you're a Republican, a hard Republican, moderate Republican, swing voter, Moderate Democrat or Hard Democrat.
So there's literally just five numeric classifications.
So then there's three classifications of your sex.
It's M, F, and Undefined or Unsure.
Nobody has a straight answer for me on this whole you thing.
So I said, okay, so that's three different types of sex classifications, five different types of voters, And then there's about 1,500 precincts in Arizona.
Basically, in so many words, I took the number of voters, the number of classifications of voters, the number of types of people based on that classification of sex, and then the number of precincts in the state.
And you multiply those three numbers out and you get 22,500 combinations of what could occur.
And then the next thing I did is I took that and then looked at the ages of 18 to 100.
So that's another 82 combinations times the 22,500.
So from that I rolled out 984,000 unique voters across the state of Arizona.
Or unique voter permutations.
Yes.
Well, there's more than, there was 90, I think 82 times 22,500, you're talking, that would be 100 and 1.6 plus million of unique classifications.
Arizona was only using like 984,000 of those possibilities.
Oh, I see.
Okay.
All right.
But in each of these possibilities, there could, of course, be more than one voter, obviously.
Yes, yes.
But I guess what I would say is I wanted to bucket where you fit.
Okay.
For example, if I was a 45-year-old male, and I classified myself as a male, not a U voter, and I was living in a particular precinct, and then living in that precinct, I would be classified as 45, Male, Republican, because I'm a Republican, and then the precinct.
And so they would look at those data points and be like, oh, Bobby, there's another 300 people like you in Arizona.
So that's what I mean by the classification process.
So once I classified all these different types of people based on these various factors, I decided to start to look to see whether or not there's any kind of relationship between these so-called U voters.
So the U voters were people that were undefined.
So I looked at each one of those buckets of U voters across the type of voting style and age across all the precincts.
And from that information, I was able to unroll, so to speak, the fact that regardless of your age, so you went from 18 to the age of 100, the correlation between how they deviated from each other The correlation was like 94%.
And just to give you an idea, you know, that's next to impossible that nobody changes their view along the way from 18 to 100 when men were correlated at 63%.
And then women were correlated about 58, 59%.
Correlated with what, exactly?
So I took the correlation of the type of voting class.
So like if they were a 1, a 2, a 3, a 4, a 5.
So the fact that they were so highly correlated, even though they had different political leanings, That makes no sense.
That's like for every Republican, there was almost like an offsetting equation for a Democrat.
Wait, so just to back up, you're saying that people who identified themselves as male were strongly correlated with a particular leaning class of, say, a strong Republican or strong Democrat.
Is that what you're saying?
No, I'm saying so.
Let's just say, before we talk about you, let's just talk about M's, so all the males.
So if you look at males 18 to 100, there's 82 buckets.
And then we said, okay, Bobby, let's take a look at swing voters 18 to 100.
How do they behave through time with regards to how many numbers?
Like, you know, are people more likely to be a U voter when they're younger or when they're older or in the middle?
How do they bounce around?
Now, if I told you that those two numbers...
Behaved almost identically, mathematically through time, from 18 to 100, you'd be like, that's crazy, that doesn't make any sense.
They shouldn't move together.
Well, what did you actually observe?
What was the correlation showing?
Well, the correlation between men and these other types of classifications, so whether you're a Republican male, 18 to 100.
Or you were a Democrat male, 18 to 100.
Or you're a swing voter, 18 to 100.
The correlation was about 63% with a 30% volatility.
So that basically means, you know, if you're a male Republican and you look at the number of male Democrats, it could be inversely related at different ages.
There might be more that show up at one age and less at another.
That makes sense.
And it's going to bounce around based on life cycle, which is why the volatility was so high.
It could be 60% overall, all 82 years, but some years it might be 10% correlation.
So it's completely unrelated.
Another time it could be 85%.
But overall, the average of those correlations was like 63%.
And for women...
They actually have lower correlation, so that would suggest they're more independent when they go in the voting booth.
They're about 58 to 59 percent.
So the volatility is higher for women, and the correlation is lower, which suggests that women, as they go through their life cycle, they're less predictable than men, in terms of they have more independence.
So that's counterintuitive because a lot of people think men are more independent when they vote.
And actually men pack more with regards to they behave more like their peer group than women do.
And so looking at those two extremes, men at 63, females at 58, 59, 30% swings in what that correlation looks like.
The U's had 94% correlation.
So they just went straight through.
Keep in mind, this is on 460,000 voters.
This isn't like, hey, Bobby, how many people did you look at?
Maybe if you had 100, 200, what's the big deal?
This was a material number of people.
460,000 in this entire state data set.
And now the variation, the standard deviation, I told you it was 30% or so for males and females.
For you voters, it was only 3% standard deviation.
OK, so you're saying the voters that are designated as you, they voted in almost a mysteriously rigid way across all their age groups.
They voted in exactly the same way, which leads us to suspect that it's artificial.
That's your conclusion?
I would say that the way they voted was the way they were directed to vote.
So I call them like digital voters or digital soldiers.
And so let me talk about what I mean by that.
But if you don't mind me interrupting, I'm sorry, but a question just to help our audience understand, because this is the first time we're all hearing this, although, you know, you've been studying it for quite some time.
So let me just back up.
A U voter is undefined in terms of their gender or sex.
Now, what would be the source of that?
Would it be that the voter themselves declined to offer their gender or that it's not even a real person, it was made up and then no gender was assigned?
I mean, how do you get to an undefined gender?
I mean, we know about transgenders and there might be certain people that would check that checkbox before they vote, but Seems like a lot.
I don't think there are 460,000 transgenders in Arizona.
So how are those yous getting there?
That's a wonderful question.
And my understanding is that there is a checkbox that people can put into what their sexuality is as you, okay?
So there's definitely an element of what you just said.
It just so happens there was a report that came out of UCLA In July of this year, with regards to the LGBT community nationwide in different states.
And I happened to look at it because I asked the same question you did.
Hey, is there this many of the population that consider themselves to be LGBT? It seems really high.
It was like 13%.
That would be one in...
Seven, eight people, right, would be LGBT. The number's actually closer to four to five percent in the state of Arizona.
So even if you looked at that, you would know something is way off.
But to answer your question about how they're identified in Arizona, it seems as though that people can click that box off.
Now, keep in mind, I'm doing this analysis in Pennsylvania as well, and there's a congressional race that I'm looking at, and the person, I think that they won.
We're going to find out here once all the data comes through, they're going to make their case.
They told me that there's nowhere in the registration process the ability for a voter to define you.
And they don't know how...
It even came into existence, but it's in the data.
Let me also see, because we're both...
I mean, your focus is math.
I'm a lab scientist and so on, so we're both really particular about numbers and things.
So I just want to clarify something, that even people who identify as LGBT... A gay man, for example, does not believe that he is not a biological man.
He would still check mail.
Just because he's gay doesn't mean he's not going to check mail.
Same thing, a lesbian woman, let's say, is still a woman.
She doesn't deny that she's a biological woman.
She just prefers other women as partners.
So, if you take the entire LGBT group, that's way too large a number of people who would themselves check the U, is my point.
I completely agree with you, but I always work in extremes.
I just assume that that number was all Ts, you know, where they didn't identify.
Okay.
You know, so I'm just letting you know, in my mind, I look at min-max numbers, I'm sure just like you do as a scientist, and I just assume, which is an incredibly low and close to, you know, I think it's an impossible probability, but just to show the extreme nature of it, I just assume they were all in that group, just to show how much left Still is unaccounted for.
Okay.
But I do agree with you.
I think the number of Ts last time I checked was maybe like, I don't know, 2%, 3%, maybe 5% at the high end.
But, you know...
What?
Transgender?
Yeah, as a percentage of the group of the LGBT. Oh, of the LGBT. Okay, yeah, yeah, right.
I would agree with you.
It's a small minority of all LGBT. It's a tiny sliver.
So 2%, 3% of 5%, you're talking 10 basis points.
That'd be like 1 out of 1,000 people.
Exactly, right.
Okay, so basically what they told me in Pennsylvania was, look, Bobby, We've been whacking our brains.
You identify all these U-voters in Pennsylvania, too, from the data.
And it's classified as such.
But there's nowhere that people can actually check this off.
So we're trying to understand...
Who created these U's?
Where did it come from?
So an interesting thing about Pennsylvania that came...
You know, their data set was a little different than the state of Arizona.
They had state data.
I had national data in Arizona.
But with the state data, what they found...
It was these U voters all of a sudden showed up in 2004, a bunch of them.
It was like, I think, 60,000.
And, you know, I didn't know this because I didn't have this data at the time I was testifying in Arizona.
I said, I think that this fraud, based on the numbers, based on the way the trajectories work, has been a creeping fraud over two decades.
And I said, you know, it's probably going back to 2008, but it could be as early as before 2000, right?
I made that claim based on just doing, instead of doing extrapolate, I destrapolate it.
I just went backwards from the numbers.
A question.
I'm sorry to keep interrupting you, but I think our audience is going to have some of the same questions.
If they were going to commit fraud like this, why wouldn't they just...
Say that the ghost vote, the phantom voters, why wouldn't they make them male or female?
Why would they make them you?
That's a great question.
So I'll go and answer that.
Okay.
Have you ever seen a movie?
Keep in mind, this explanation, I kind of hammered it out yesterday because I was trying to wrap my head around how to explain it because it's a little tricky.
Because you want to make it as tangible as possible for our minds to visualize.
Have you seen the movie Bloodsport by chance with Jean-Claude Van Damme?
Yeah, back in the 1980s I did.
Yeah, a long time ago, right?
It's a little cheesy, right?
Right.
Okay, so this image popped into my head to explain this.
There's a scene in the movie where he's at a bar, there's a woman that's being bugged by a couple gentlemen, and Jean-Claude Van Damme walks up and says, hey, you know, you guys got to leave her alone.
Do you remember that scene?
Yeah.
I don't recall that scene though.
So I tweeted it out.
So basically the scene is as follows.
These guys are bugging her.
They're going to fight Nakumite.
And then all of a sudden they say, no, leave us alone.
Take your two cents out of here.
But if they fight, they're disqualified.
So basically he says, okay, I'll tell you what.
If I can pull this coin out of your hand, I get the girl and then you guys have to leave, right?
That's what he basically said.
She kind of scoffed.
I understand she scoffed.
Next thing you know, they put the coin in his hand, and basically he goes, go.
They say, go.
So he pulls the coin out of their hand, and they can feel that there's still a coin in their hand.
And they say, you lose.
And the guy opens his hand, and the coin is switched out.
And then he's holding the coin that the guy had in the palm of his hand.
So what the U voters' purpose is, I want you to imagine I'm a voter.
I happen to be 45 years old.
And I go in to vote.
And I click on all these different people I'm voting for.
And that click in the system is like sitting in digital limbo.
It's just kind of sitting there.
It's like, okay, Bobby, click this person, this person, this person.
But he didn't hit send yet.
But they know what I clicked.
Okay?
So then, using the same technology that high-frequency trading uses in the stock market, might be a millionths of a second, the moment I hit send, The algorithm takes that spot.
So let's just say I do Republican.
So I vote Republican.
I'm a 45-year-old male.
The model says, wait, he voted 45-year-old male.
There's too many 45-year-old males voting Republican this election cycle.
We forecast 60% of the males.
He's pushing the number up to 70%.
So we have a little leeway to steal some of those votes.
And so the model looks at this distribution, this probability map, and says, we can take his vote.
Because if all the 45-year-old males vote similar to what they did in the past five elections, nobody's going to notice.
Okay?
So then what they do is they load the spring with the 45-year-old male that is a Biden supporter.
And then they put that U, that 45 U, they put in a B vote, right?
So let's just say in this case the Biden vote.
So then the moment I hit send, they take that 45-year-old U, they shoot it over, swap out my vote, put the B in.
And then it accepts that that's who I voted for, that I voted for Biden.
I don't see it.
I don't get a receipt.
I don't know who I voted for.
There's no way I can spot check my transactions like you could on a credit card transaction.
So then the next question is, well, Bobby, how do you prove this, right?
Well, it turns out in Pennsylvania, out of a voter file of over 500,000 200,000 modifications occurred on November 4th to the voter files.
Wow.
And so guess what happens with the U's?
The U's have no vote.
A lot of the U's have no vote in them.
And they're like, Bobby, what are you saying?
You said that these U voters are involved in this scam, but there's nothing in them.
When we look at the files, we see there's no vote.
I said, yeah, you're not going to see a vote because their vote, in a sense, annihilates the vote that was in the person's 45-year-old bucket, 45-year-old mail bucket.
And it happens so fast that the only way you can really witness it is you need to look at the tape, the tick by tick tape of all the votes.
You need to look at the timestamps of digital transactions into the microsecond arena.
I'm assuming that if they pulled this off, there has to be those systems that had to be coded.
And today, right before I came on here, about less than an hour ago, I saw that the Maricopa County in Arizona They're refusing to deal with a request for a court order to turn over the machines.
They will not turn over the machines because I outlined this fraud.
I said, this is the way they did it.
They never thought, I don't think they thought that someone would figure out or make the connection between how the financial markets, the know-how from there, from the mathematics, And technology would be able to be used in such a malicious manner in the voting structure of this country.
So, this is fascinating, what you've discovered.
Obviously, I've got quite a few questions for you, but if I can summarize what you're saying, it's that these you phantom voters are sort of proxy surrogates, temporarily holding a set of results that can be used to overwrite In real time, the vote of someone in a particular group that the tabulation system identifies as someone whose vote could be overwritten without raising suspicion.
That's correct.
That's a great...
Thank you so much.
You literally just told me back what I said, I think.
Okay, great.
Well, you did a great job explaining it.
So then, do you think that this is happening in the tabulation systems Or in the vote machine, it doesn't seem like the voting machine.
I don't know how they work in every district, but the voting machine doesn't know who you are At the moment you're voting, does it?
That's a great question.
So I had someone from the White House ask me that very question.
I was on the phone with some people from the U.S. Congress that represent the great state of Arizona, and they asked me that question.
They said, Bobby, how can they figure that out?
And I said, well...
You know, if you gave me a bunch of money and you said, Bobby, I need you to design this, right?
And you said, Bobby, figure out.
And I said, you know, I would never design this.
It's against my moral compass.
But in order to kind of crack how they're doing it, you have to think as though you were hired to do it.
And I said, so in China right now, you can look this up.
This isn't news.
There's over, you know, they have an AI technology that can analyze a billion people in real time.
Based on facial recognition.
And, you know, a lot of people think facial recognition is just your face.
It's not just your face.
It's the way you move.
We have a signature on how we walk through this world.
Yeah, gait analysis.
Yeah, the top of our heads factor into it.
You know, there's so many micro-factors As to what we are, everybody just kind of remembers facial.
It's like they think facial.
So my guess is, if they've hijacked, theoretically, and I'm not saying they have done this, but if you're paying me to figure out how to do this, I'd be like, look, if a lot of these places have camera systems, and we know what, we can hack into them, and we pull that information up to the cloud in real time, We can get an estimate as to which voters were coming in.
So if 45-year-old males, let's just say me, for example, if I voted in every election before 9 a.m., and then I know that if I don't come in before 9 a.m., my probability of voting drops to 20%, they're going to know that I'm somebody that they can do something with.
They just haven't figured out what yet.
And so the probability map, they tilted the odds in their favor by requesting all this early voting.
Because as a result of early voting, you can change the distribution profile.
You cut the number of computations significantly.
The exponential effect of the sample size, as you know, if you keep chopping away at it, you cut the amount of processing power that's needed.
What I'm saying is, because of this, This is why I think there's been a foreign actor involved in this.
This was not a simple thing that can be done.
But that being said, if you paid me enough money with tools on the shelf right now in the United States, all over the world, I have no doubt that I can...
I can rig a local election through technology if you gave me the ability to put in the algorithms into the source code of the voting machine.
And my understanding is these voting machines, anywhere from one to three days before the vote actually took place, they were people uploading updates.
That's right.
My guess is that those updates were probability maps.
Wow.
So, and this is doubly troublesome because, of course, after a person votes, they get no receipt of their vote.
There's no way to track it later on, not even to go to a website and log in and give ID or something and see your vote.
So it's a black box voting system.
There's a secret algorithm.
The Dominion Company claims, you know, intellectual property, trade secrets, protection of that algorithm, which is, that's insane all by itself, because this powers our republic here.
It should be open source.
Every election should be open source.
And I think arguably now, we should all go back to paper ballots.
Absolutely, because that's in depth.
Yeah, that's air-gapped, exactly.
But what you're talking about, I just want to point out to the audience that even with the possibility of facial recognition feeding into how the machines decide which votes to steal...
Our audience should know that that doesn't even have to be very effective to still steal the election.
In other words, if you just get a 10% advantage by doing that, that's enough to steal almost every election.
So it doesn't have to be 90% accurate.
Yeah, just a 3% advantage.
Vegas makes billions of dollars by one or two percentage.
That's right.
That's it.
Yeah, exactly.
All right.
So then, well, and plus on top of this, let's not forget The Democrats were able to pause the counting to assess the current status of elections in the swing states and then to adapt their ballot fraud after the fact and bring in more votes for subsequent days.
And that's due to the COVID-19 lockdown artificial extension of voting day or election day has now become election month, thanks to the Democrats.
So on its surface, that is also fraudulent.
Yeah.
Well, I think what happened, the reason why they locked it down and they said stop voting is because all the assumptions based on past records, and this is what I've kind of deciphered.
A lot of people that were voting for Trump, they didn't want to tell the pollsters the truth because they were vilified.
So as a result, it's kind of ironic, but as a result of this other side being so vicious toward Trump voters, they didn't have good information to program their algorithms.
Right.
If they treated everybody fairly, they would have had better data to calculate what the odds were.
But because there were so many people that were refusing to tell you what the heck and what they really thought, they had to base their odds off of past elections, which don't always predict future.
You know, they just don't because every circumstance is different.
So that's that's the whole that's the whole, you know, ironic thing about the situation.
The way they treated all those voters bit them in the ass.
Go ahead.
Well, you can finish your thought and then I'll have a question.
So, you know, getting to those initial probabilities, I think the reason why they paused the machines and they shut them down is because the assumptions as to how many people of different age groups that showed up to vote blew through their maximum numbers.
They usually set a min-max range.
And it might be within two, two and a half standard deviations, you know, where they're like, okay, it's going to be here.
But what ended up happening is they had three, four, five standard deviation events.
And then that caused these overflows which they never forecast into their models.
So the models did not have enough, I guess you would call it almost like catastrophic insurance.
You know, you should always plan a system For catastrophic failure.
Yeah, you've just nailed it, because then their cheat had to go as a five standard deviations kind of event in order to counter the outpouring of Trump voters that was unexpected by their own models because their models were rigged, or I should say their models were faulty, inaccurate.
So, and then...
Yes?
I said garbage in, garbage out.
Yeah, that's right.
And so then their massive steal left a trail, a trail of evidence that is impossible to miss if we have access to the votes, the machines...
And the outcomes.
So the forensic audits in this case become absolutely crucial.
And there have been some forensic audits ordered.
Remember Jenna Ellis' team, I think, imaged the hard drives of 22 machines.
I believe that was in Antrim County, wasn't it?
I think so.
I know that I've been reading some reports where up to 68% of some of the machines had faulty issues, I think, in Michigan.
And so, you know, like you said, it's very disturbing.
But one thing I want to say about this whole process in identifying these so-called phantom voters is, you know, After I did my testimony in Arizona, Liz Harris called me up the next day and said, Bobby, you have four days or five days to get me the list of all these people.
And I'm like, you just volunteered me out?
And she goes, they asked me, they said, you gotta supply proof that these people are, in fact, ghosts.
You know, that they're phantom voters.
So then I went to work on that process.
Identifying that use was instrumental in figuring out the different types of classifications and buckets of these phantom voters.
Because they're not just one type of phantom voters.
I can run through that real quick if you like, and then I can explain some of the results that she gave me from Arizona, or I can start with the results in Arizona first and then go into the phantom voters.
Do you have a preference?
Yeah, well, I'd like to understand what your investigations turned up into these phantom voters.
Did they turn out to be fictional people?
And then also, before we get to that though, I just want to mention that your entire argument here is actually making the justification for President Trump to order the military to seize the physical ballots and then recount the physical ballots.
Separate from the machines, even by hand if necessary, or in an air-gapped environment or with some open source code, you know, sterilized machines, you might say.
But if he did that, then all of this fraud that you're describing, those algorithms would not be present in that recount.
Right.
I think that's a wonderful idea.
I think he absolutely should do that because I think that, you know, aside from American, you know, our way of life and people believing in American democracy as well as, you know, making sure that our American identity is under attack.
It's not just democracy under attack.
It's our identity as a culture, as a people.
And so that's why it's so much more severe that if people feel as though the end result is rigged, you're basically, you feel like you're rigged if it's part of your identity.
And I think that's the thing that's most troubling about this.
So the more that can be done to prove this out, that's why when I did this, just so you know, when I created my samples and I identified these U-voters, It's not just Democrats, buddy.
It's Republicans going back decades.
That's why I called for a complete audit going back 30 years.
There's been cheating going on by both parties at varying degrees, and I don't know if there's backroom deals as to who's winning what seat, but this is why when you're an incumbent, you very rarely ever lose.
Right.
And, you know, because they knew that they controlled the rig, right?
Well, it's kind of like ripping down the curtain protecting the Wizard of Oz here.
You're now seeing the machinery and people are waking up and realizing, oh my gosh, we've been living in an artificial matrix.
We haven't had a democracy or a constitutional republic for decades.
Probably Nancy Pelosi is not the legitimate leader of the Congress because the 2018 midterms were rigged.
Yeah.
So how far back, you know, obviously we need to look at those elections.
Maybe President Trump was never actually impeached by the Democrats.
Well, all I can tell you is that if they get the data, I know how we can set it up and make it visual going back 30 years.
Wow.
And whether or not they want to prosecute, you know, I did, when I wrote a letter to the Arizona State Legislature, 47 Republicans in both the House and Senate, I wrote two letters trying to convince them to decertify.
And one of the things I wrote in the letter was, look, You know, this is all going to be proven.
So I think I speak for a lot of Americans that say, if you were in on the scam and you were committing small cheats, because that was what everybody was doing, I don't really care.
You know, maybe you get banned for life, you pay a monetary fine, and no jail time or something.
I can live with that.
And most people, when I tweeted that, said yes.
But I said, if you were a ringleader, if you were organizing this, and you were the one that was calling the shots and recruiting more people to perpetrate this fraud, you don't get a pass.
I think your family, all the money that you cheated should be confiscated in the court of law.
You should get jail time.
So I said, for all of you in the Arizona legislature that didn't do much, but you just kind of went along to get along, now's your time to come clean.
And I think the American public will be forgiving.
But the moment it crosses that point where you could have come clean and you didn't, then I say we use all the power invested in the Justice Department to prosecute.
Well, and committing fraud on just one ballot is a five-year prison sentence under current federal law, by the way.
Do the math.
They're going in for life.
Yeah, exactly.
No, I was joking.
We're going to have to invent longevity pills just to sentence them for 5,000 years.
But one of the big challenges in all of this, as you know very well, is...
For people to understand what you're explaining, they have to be able to grasp some of these mathematical concepts.
And as you're well aware, I don't think I'm saying anything unsurprising, we live in a nation of mathematical illiteracy.
Most people can't, you know, they can't calculate like a 15% tip to the waiter at the restaurant without using a calculator.
I mean, it's very bad.
How do you translate these concepts, which are based in statistics and correlations and standard deviations, how do you translate those Into the minds of even the lawmakers or court judges or Supreme Court justices.
How do you get them to understand?
Because Scotus Juris, they are not mathematicians either.
Yeah.
Obviously.
Well, that's a great question.
And this, once again, I think this is a, you just handed me a layup for talking about the five classes of phantom voters.
Because Using this set of mathematics, I identified like five different classifications that I think most people can relate to.
And they say, you know, the math helped identify these folks, okay?
So I want you to think of, who cares about the math, Bobby?
Who did you identify?
And let's hear your story as to why you think that they're in on this.
They're part of the Phantom Voters.
Phantom sleeper voters.
Well, the first group is what we would call traditional fraud.
It's a fake identity.
There's no such person exists.
Everybody kind of knows that.
There's a little bit of that going on, and you can understand that if you can figure out who those fake identities are by various checks in the system, great.
That's one group.
So that's a phantom class.
Then the second class is going to be people like Bobby.
So like Bobby Pyton lives in X County.
And then there's somebody named Bob Pyton that lives in Y County in the state, 300 miles away.
Then there's another guy named Robert Pyton in another part of the state.
And you sit there and you're like, how are there...
I'm like multiplying like a gremlin.
There's like three of me, right?
And you're like, okay, So the data sets are so big that if you don't set up the problem properly and pull all these data sets, you can't do the cross check to see that there's three identical bobbies in Arizona or in Illinois.
So that's another type of phantom voter.
So a phantom voter is you've been split three times.
Right, and it's worth noting, too, that when states like California were mass mailing out mail-in ballots, even unsolicited, in order to build the database to do that, they were taking everything, like DMV databases, state Medicaid databases, welfare databases, whatever, combining them, getting the biggest possible numbers they could, sending out those ballots, and you're right.
Somebody could have a different spelling, somebody could use a different initial or without an initial, or...
Robert versus Bob and so on.
Yeah, that's how they flooded the zone.
So that's the second version, okay?
So then the third version is somebody moved out of the county or moved out of the state to what you just said.
And then they're in multiple locations where You know, even though they're gone.
So that's the third.
That's the third classification.
The fourth one is, you know, parents, without even knowing it, had a bunch of their kids come back and live with them in their 20s and 30s and 40s.
So these parents were in their 50s or 60s, and there's two of them, right, in the household.
And then all of a sudden, there's a 30-year-old kid living with them with the same last name, right?
And so that's a classification of a bunch of these fandom voters, too.
You ask the parents, hey, your kids still live here?
It's like, no.
What are you talking about?
They moved out 20 years ago.
But that's the way they're trying to cover up the tracks.
Because a lot of people, when they run it, they're looking for different last names.
They're looking for the obvious ways instead of looking at the data.
So just so you know, one of the reasons why I came up with this And I'll tell you right after I named the fifth one.
So that's the fourth.
And then the fifth one is, people that died recently in a particular county, everybody always looks to say, hey, did that dead person vote?
They're all focused on that county that they voted in, but that's the mistake.
What happens is they take the identity of somebody that died in the county across the state, or even in a different state, and they replicate almost like a fake identity of the dead person's information.
So that then when you look at it, you're like, oh, that person doesn't exist because we have all this information about them.
You've got to name that group the zombie voters.
Yeah, the zombie voters.
They're reanimated dead zombies.
So that's why it's so hard to catch, because people are kind of keying in on certain things, and they want a one-size-fits-all.
That's not the way it works.
You have to continue to create different subclasses within the class of what to look for.
So...
Well, that's a great description, but I just want to comment.
So when people go to vote, when a real person goes to vote, like you and I, Yes.
or zombies, or all the five classes that you described, phantom voters that are kept in the system for the purpose of rigging the outcome.
Yes.
And even if that's not enough, they can just shut down the votes, drag in 500,000 ballots, and add those.
The U voter is the last line of defense.
So if they can't pull off this scam with these other five ways, that's when the U voter comes in and assassinates your vote.
I see.
I call it a digital assassination.
They're killing, either they degrade your vote, that we're only a fraction of a human vote, or they are literally assassinating our vote if we are not part of what they think we should be with regards to their math.
So, of course, nationwide voter ID would clobber this or a requirement that when you vote, you give a thumbprint or if you voted, you get a receipt or like they've done in some third world countries.
You vote in person.
You get a stamp on your hand.
And that means you can't vote again.
And it's all done in one day.
All of those or each of those would have stopped this theft.
So that's it.
Here's I came up with five points.
To answer this, once again, you keep leading me to what I want to say next.
It's awesome.
But basically, you know, the first thing is, there's only one type of passport in this country.
We don't have 40 different types of passports, 50 passports.
So we already have a methodology with RFID technology to have some type of passport or voter ID. Okay, so we agree on that.
Number two is...
Printing ballots, we can set it up in a blockchain type of manner.
So there's a numeric score that's unique and there's a key of who gets what at which precinct based on actual number of people in that precinct.
There's a certain number produced by actual numbers.
By the way, I think a lot of these fictitious and fraudulent people that exist across this country, they're done to manipulate the number of delegates a particular state has.
I think that a lot of these people might have been getting benefits from the state because the state's claiming they're in more need than they really are, and there's a skim going on.
And I think there's just outright fraud where if there's as many phantom voters as I thought in Arizona, they might have sucked out a half a billion dollars of COVID money.
And also don't forget about the PPP loans going to the phantoms.
And maybe California shouldn't even have as many seats in Congress as they do have because of what you just said.
The representation is based on the census.
Maybe the census has a bunch of phantom people in it as well.
So that was two.
One was ID. Number two was airdap blockchain ballot.
So then the third thing was we should have local citizens, you know, local citizens in good standing with veterans.
If veterans are going to go overseas and die to protect our freedoms, They should be the ones doing the physical count of the votes, both Democrats and Republicans, and do it with the civilian population.
So now if you say, hey, Bobby, you know, everybody's scared, COVID, COVID, no problem.
We'll have a veteran, two veterans, one from each party, go to your house, check your ID, and they will help you fill out that vote.
Not help you fill it out, but just like, they will assist with, yeah.
And, you know, or they can go there in person, make sure they watch you download the app, you get an app downloaded for a one-time use, you submit your digital vote, and it's secure.
So that's number four.
And then, you know, the fifth thing was, I said, you know, oh, And I've modified this a little bit.
You know, anybody who trades or invests in the stock market, they have every single transaction recorded in real time, microsecond.
Well, we should have a stock exchange of all our votes that we can see.
Now, granted, I don't believe we should see it in real time.
I think personally, I think that should all be banned.
TV stations, everything shouldn't be recording in real time on the day of the election.
Right, it should be delayed until the next day.
Yeah, but you know what they should do?
Is they should show all the transactions, countywide, precinctwide, statewide, and let everybody watch it like a stock price.
And like, what happened every minute of the day?
Of who came in and who voted, even if you want.
And you can create the mathematical score because then you're like, hey, I went and looked and I got filled.
I filled at this price.
So then if people just do a quick random audit and say, hey, there was 3,000 45-year-old males that voted in Arizona between this half-hour increment.
Can anybody just confirm that they voted for this person?
And you can do random samples.
You don't need to do all three million, as you know, with statistics.
You might be like, we're going to create a random sample of these 82 different age groups, and this is what we want to see.
We want to see if it ties out, because we're all large numbers.
A small subsample of 3,000, 5,000 people would be sufficient to prove out the statistics that happen on the much larger actual dataset.
And I think, go ahead.
Well, no, I have a question on So what's next for this?
And also I wanted to commend you because I believe you're doing this all on a volunteer basis, right?
No one's paying you to do this.
Well, I did it volunteer basis for the state of Arizona, for the entire state of Pennsylvania data.
I am being paid some money for this congressional race.
And they are paying me an amount of money, and if they're comfortable telling the public once they announce, then I'm fine with that.
I'm fully transparent.
But, you know, they contacted me.
They said, hey, you know, and I basically said, look, I proved it out with the free, but I'd like to be paid for my time, and I'm a reasonable guy.
Why don't you tell me what you think?
And they made me one offer, and that was it.
I didn't, you know, I didn't.
And then they said, well, how about we cut it in half?
And I said, well, I like the first one first.
But they're reasonable.
And I said, that's fine.
That's fine with me.
But I haven't received the payment yet.
I think that they're honorable.
They'll pay me.
I don't need a contract.
Okay, so that's fine.
But what about next steps?
I mean, how do we take this discovery that you've found here and get that into the hands of the people who need it, which might be lawyers such as Sidney Powell or Trump's attorneys and so on?
So here's the deal.
Number one, I am communicating with some lawyers that you mentioned.
I prefer not to say the specific ones.
I mean, I might have said it already, but, you know, in other interviews.
But let's just say that I'm working with attorneys, I sign those affidavits, and I'm trying to do my civic duty to say, look, anything I said...
I did it in good faith.
If there's mistakes, please check over all my work.
And that's why I've kind of outlined and posting on my website.
That's why I created that little political tab where I'll be dumping the data.
Like here, go download it, go look at it, go replicate it in your county or state.
We're all in this together.
We need a fair process.
I'm not trying to keep a proprietary formula and figure out how to make a bunch of money, but everybody has to pay me consulting fees.
I'm not interested.
No, I'm just saying that's not why I went down this path.
You know, I went down this path to try to make sure that we have fair and equitable elections.
So you're going to have public data available on your website?
Yeah, I'm going to post it.
I posted a couple things, like my Arizona letter and I think my Arizona metadata.
It's on PreactiveInvestments.com on the right.
And if people want to sign up for the newsletter, There's no charge.
I'm going to do a weekly political commentary and then I have some podcasts and finance stuff that I'll be rolling out.
This was in the works before I got asked to do this.
It just so happens I wasn't ready to do this.
Right.
Because, you know, life works in a mysterious way sometimes.
Yeah, especially when elections are rigged.
So let me ask you about Preactive Investments in the last couple minutes here.
You are an investment firm, so you manage other people's money and manage their investments.
Is that correct?
Basically, I spent 17 years of my career in a mid-size and large firm.
This is all on my LinkedIn profile and stuff, like UBS O'Connor, their hedge fund arm.
I used to trade three to five million shares of stock a day for three years.
I managed a billion dollar book.
One of the things I did with this data, because I never looked at this voting data like this before, and it ties into my profession, is I poured over hundreds of thousands of records with no view of what it should look like.
I just went through it like raw data and just said, what patterns do I see emerge by looking at hundreds of thousands of records?
But I like to do that.
I think it's soothing.
So it's not for everybody.
So what I do at Preactive is my big focus is on creating metadata from fundamental factors, whether they be qualitative.
So qualitative things that are unique about a company.
And I create a mathematical score for those qualitative factors.
Factors that I think lead to success.
And then the financials, which are quantitative, as well as how things price in the market.
So there's information across the spectrum.
And so at Preactive, my focus is on quantifying those factors and trying to optimize portfolios using probability maps.
So that's why it's like, you know, people are like, well, this guy knows a lot about these probability maps.
That's what you do.
A lot of the principles from artificial intelligence design, and that's why I call it augmented intelligence.
I actually have that domain.
So I look to augment our intelligence by using superior methods of processing the data that everybody has.
At least that's what I'm attempting to do.
Okay.
So then just a question for you on the market situation.
You know, we've seen so much quantitative easing since I think October of last year was when the Fed really started dumping again.
You know, lots of money into the market.
Many people believe that many of these corporate stock prices are wildly overvalued.
What's your take just on the big picture of what the market looks like right now?
I was worried you might ask this one, but this one I would very happily answer once my answers go through my compliance department.
Oh, okay.
All right.
Fair enough.
Because I do have a strong opinion based on actual data.
You know, I could be wrong on my opinion based on this data.
But, you know, I think we're going to do a newsletter and maybe that'll be a good podcast to do.
And maybe if you want, if you want to do one on the state of the economy or the markets, maybe in a few weeks when things kind of calm down for me, maybe sometime next year, I'd love to, but I need to, you know, they need to see the evidence.
Just like, you know, all these people are asking me for evidence.
If I'm going to go publicly and state stuff, And I don't have a problem with that.
I don't have a problem saying, here's my evidence, here are all my source materials, ask me anything before I say it.
And frankly, I wish the press did things that way.
Why do we have a press that can keep lying and never be held accountable?
Well, I'll tell you what, just as you have identified zombie voters, I have a feeling When we talk about that in the future, you may be talking about zombie corporations.
You know what?
I think there might be some laundering operations taking place through some companies, unfortunately.
I don't have any idea how many there are, but that's something that I think we should definitely look into as a society.
Well, you know, the year of 2020 here is the year of vision where so much is being exposed and people's models of the world around them are being fractured because they're realizing how much is artificial.
You know, the elections are fake.
The news is fake.
So much of the science is fake.
The financial markets are in many ways rigged and so on.
You know, you start seeing that banks own ships.
That are seized in dock and contain thousands of pounds of cocaine.
And you're like, wow, this is not the banking system that I thought we signed up with.
That's 2020.
We live in very scary times.
Can I just say one thing?
I think things are going to be extremely volatile over the next few weeks as all this comes to light.
Your viewers, what I would say is pray as much as you can to whichever God you pray to.
You don't need to panic, but have some more non-perishable food items on hand.
Have an emergency plan in place.
This is stuff you should do anyways.
Not just now, but right now, there's a higher probability of you needing it now than maybe during other times.
And then the other thing I would say is, with this emergency plan, there's strength in numbers.
Have other people, other friends, family be with you if something gets crazy where they cut the power.
And the last thing I would add with is, Even if your power goes down, you might want to shut off your phones.
And I know that's counterintuitive, but I just have a bad feeling that if the phones are on, it could lead to something else.
And I don't know what.
Whoa, an epic tease there from Bobby Pyton.
Okay, I'm not sure what that means either, but there are a lot of reports of things that are about to happen.
I mean, hey, somebody just cyber hacked the National Nuclear Security Agency, I think.
Somebody just got a hold of all of our nuclear secrets, our power grid.
And also even nuclear fuel refining operations.
And I think it's China.
I think China got all that.
The media is reporting it's Russia.
But I think it's China.
Anyway, that's beyond the scope of this.
Bobby, I've got to say, this has been a really intriguing interview.
I would love to have you back on to talk about finance and so on.
Let's get Trump a second term first here.
And then we'll move into that.
Because it's going to be a bumpy ride no matter what.
That's for sure.
I agree with you.
Yeah.
So thank you very much.
God bless you.
God bless all your viewers.
And God bless America.
Let's pull through this and we're going to come out stronger on the other side.
All right.
Well said.
And folks, check out his website, PreactiveInvestments.com, with more downloads coming and more podcasts from Bobby.
And maybe he and I will get a chance to talk again soon.
Thank you so much, Bobby.
It's been a real pleasure to be able to speak with you.
Have a wonderful weekend.
Thank you so much.
Thank you.
Survival Nutrition is our new free audiobook that you can download right now from survivalnutrition.com.
In this nearly eight-hour audiobook, you will learn life-saving secrets of how to use food, nutrients, plant molecules, trace minerals, and chemical compounds to save your life, even in a total collapse scenario.
I'm Mike Adams, the Health Ranger, and I'm the author of Survival Nutrition.
I founded and run a multi-million dollar food science laboratory, and I'm the author of the best-selling science book, Food Forensics.
I'm also a prepper, a patriot, and a survivalist.
I can teach you how to survive what's coming by growing your own food, medicine, and antibiotics that can help keep you healthy and alive even during the worst of times.
At survivalnutrition.com, you'll be able to instantly download the full free audiobook as MP3 files.
Keep a copy of all these files on your local hard drive and print out the full guide just in case we lose the power grid.
▲
Export Selection