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Everything X Simulation · Ryder Lee

• 0:06
  Speaker 1: And I kind of want to go gloves off right
• 0:08
  Speaker 1: now because some of this stuff is completely ridiculous that
• 0:12
  Speaker 1: people don't understand how global warming predictions have been made
• 0:17
  Speaker 1: for the past fifty years. I want everyone right now
• 0:21
  Speaker 1: to type into Google or whatever search engine you use,
• 0:27
  Speaker 1: or even into your GPT and just type in how
• 0:33
  Speaker 1: do scientists predict global warming? Okay, and just take a look,
• 0:40
  Speaker 1: and right here you'll see that how do we predict
• 0:45
  Speaker 1: climate change? Okay. To explore and predict how climate change
• 0:50
  Speaker 1: will change, researchers create computer models of the real world. Okay.
• 0:59
  Speaker 1: So so it's a computer simulation model. Okay. So a
• 1:05
  Speaker 1: bunch of scientists and engineers put together a computer simulation
• 1:10
  Speaker 1: model with a bunch of data, and the computer spits
• 1:13
  Speaker 1: out the predictions. It's a damn computer simulation, Dave. When
• 1:19
  Speaker 1: it says model or models, that means computer simulation, okay.
• 1:23
  Speaker 1: And this is very important to understand because it doesn't
• 1:27
  Speaker 1: mean that the model is correct or even true, because
• 1:30
  Speaker 1: it can only work within the information that's fed into it.
• 1:33
  Speaker 1: And once you understand that the entire global warming narrative
• 1:37
  Speaker 1: has been based upon computer simulation models, things start to
• 1:42
  Speaker 1: make sense. Go to any website about global warming. Go
• 1:46
  Speaker 1: to NASA's website. It'll tell you the exact same thing,
• 1:49
  Speaker 1: that global warming is based off of computer simulation models.
• 1:55
  Speaker 1: And you can even take this a step further into
• 1:57
  Speaker 1: COVID or into answer predictions. Okay, type this in to
• 2:03
  Speaker 1: Google right now. Actually, let's just let's just do this
• 2:08
  Speaker 1: ourselves here. Hold on, let me get this off of
• 2:10
  Speaker 1: the screen. Okay, let's type into Google. How do we
• 2:17
  Speaker 1: predict the rate of cancer increasing in the coming years? Okay.
• 2:25
  Speaker 1: Scientists predict increasing cancer rates by analyzing demographic shifts, aging
• 2:30
  Speaker 1: and growing population, lifestyle factors, obesity, diet, and smoking, and
• 2:33
  Speaker 1: cancer registries. Models project seventy seven percent increase in new
• 2:39
  Speaker 1: cases by twenty fifty. This is the key term right here.
• 2:43
  Speaker 1: Models models mean a computer simulation. Okay. And once you
• 2:51
  Speaker 1: understand that all of this stuff is done through computer simulations, okay,
• 2:57
  Speaker 1: you can and how scientists predict anything is all through
• 3:02
  Speaker 1: computer simulation. Here, let's do one even better. Here, let's
• 3:06
  Speaker 1: go to let's go to Phiser's website Mathematical sandbox. How
• 3:13
  Speaker 1: quantitative systems pharmacology steer safer and faster drug development. Okay,
• 3:19
  Speaker 1: So then if you scroll down your predicting patient outcomes
• 3:25
  Speaker 1: from the onset. Quantitative systems. Pharmacology is a high tech
• 3:29
  Speaker 1: branch of biomedical research that aids drug development from discovery
• 3:33
  Speaker 1: through clinical trials and beyond. In this field, scientists build
• 3:38
  Speaker 1: mathematical models to simulate interactions among medications and their targets. Okay,
• 3:47
  Speaker 1: it's a computer simulation model. This is how Phiser tests
• 3:52
  Speaker 1: its medications is computer simulation models. And it pisses me
• 3:57
  Speaker 1: off that people don't understand this. I know you remember
• 4:00
  Speaker 1: Event to a one tabletop exercise, Dave, that was done
• 4:04
  Speaker 1: by the Gates Foundation a few months before COVID hit
• 4:07
  Speaker 1: in twenty twenty to simulate how the public would react
• 4:10
  Speaker 1: to a global pandemic. That was also a computer simulation model,
• 4:16
  Speaker 1: and that one was just a tip of the iceberg.
• 4:18
  Speaker 1: This is how every company, organization, government, and scientists did
• 4:24
  Speaker 1: their information is through computer simulation models. Okay, my rant's over.
• 4:31
  Speaker 2: Well, I'm just wondering what the model and Event two
• 4:33
  Speaker 2: to one, how closely it replicated the outcome of how
• 4:36
  Speaker 2: people behaved on the planet during that time, or you know,
• 4:40
  Speaker 2: you know, at the end of the model run, they
• 4:42
  Speaker 2: had to have known that there would have been a
• 4:43
  Speaker 2: pushback effect where people would have seen through the illusion
• 4:46
  Speaker 2: said hey, enough enough, these guys are asking too much.
• 4:48
  Speaker 2: Now there's never going back to normal. You're just disrupting
• 4:51
  Speaker 2: the lives, like to the uber now it's like this
• 4:53
  Speaker 2: isn't gonna work anymore, Like it doesn't make sense. Like
• 4:56
  Speaker 2: that had to have been built in the model too.
• 4:57
  Speaker 2: I'm wondering how closely it ran with that until the
• 5:00
  Speaker 2: up to phase where they knew they had to turn
• 5:01
  Speaker 2: it off because uh, it wouldn't it would generate too
• 5:05
  Speaker 2: much social unrest of people pushing back against their policies
• 5:08
  Speaker 2: that they just said, Okay, it's over, everybody go back
• 5:10
  Speaker 2: to normal again. We're all good bye. Thanks for the data.
• 5:15
  Speaker 1: Yeah, it's just unbelievable that this is the way that
• 5:20
  Speaker 1: everything is ran. And you can do this with anything.
• 5:24
  Speaker 1: Type anything into Google and how science scientists predict whatever.
• 5:32
  Speaker 1: This is how they do it.
• 5:34
  Speaker 2: It's computer syn this is how we do it. Get
• 5:40
  Speaker 2: this is how scientists do it.
• 5:45
  Speaker 1: I had to get that off my chrust. I've been
• 5:46
  Speaker 1: holding onto that one for a long time. Dave yet
• 5:49
  Speaker 1: me too.
• 5:49
  Speaker 2: I've been wanting to dance for a long time. I'm
• 5:51
  Speaker 2: glad I could you know, let a little let a
• 5:53
  Speaker 2: little loose here on the on the show. And there's
• 5:55
  Speaker 2: another virus that's coming out of India that now they're
• 5:58
  Speaker 2: starting to clamp down an airports across Highland and Lao
• 6:00
  Speaker 2: and Malaysia as of today and Singapore if you haven't
• 6:03
  Speaker 2: read it, I forget the name of it. Came out
• 6:05
  Speaker 2: of India as some kind of animal came jumped into
• 6:07
  Speaker 2: a human or whatever. Now they're starting to not lock
• 6:10
  Speaker 2: the airports like they did before, but they're setting up
• 6:12
  Speaker 2: all these screeners and all these kinds of crazy things
• 6:14
  Speaker 2: like they did in the beginning of COVID. It's starting again,
• 6:16
  Speaker 2: but it's see in Southeast Asia as of two day,
• 6:20
  Speaker 2: so the airports are being frightened and paralyzed. Expect delays
• 6:24
  Speaker 2: because you're gonna have to go through extra health screening.
• 6:27
  Speaker 2: I kid you not. It's begun again. I forget the
• 6:29
  Speaker 2: name of it specifically started in India this time.
• 6:36
  Speaker 1: Well, there seems like there's a new one every couple
• 6:39
  Speaker 1: of months around flu season. Whenever winter hits too, there's
• 6:42
  Speaker 1: something new. I mean, how many variations of COVID do
• 6:45
  Speaker 1: we have? We had like five or six different variations
• 6:48
  Speaker 1: that all happened back to back to back to back.
• 6:51
  Speaker 1: There's the delta, the beta, theta.
• 6:56
  Speaker 2: Like what and how easily were people led to see
• 7:01
  Speaker 2: that fear factor too? Again, if you're looking into long
• 7:04
  Speaker 2: term climate variability and you understand that crops are going
• 7:07
  Speaker 2: to be lost up to twenty thirty percent lower yields
• 7:10
  Speaker 2: globally than we have now, it becomes simple math like
• 7:13
  Speaker 2: how much do we have in the warehouses and silos
• 7:16
  Speaker 2: and barges and grain storage along like riverbanks or whatever.
• 7:21
  Speaker 2: How much are we going to produce every year? And
• 7:22
  Speaker 2: then there's that Okay, we're going to produce this, Oh,
• 7:25
  Speaker 2: that's ten percent less than we did. Okay, we got
• 7:26
  Speaker 2: to dig into ten percent of the carryover stocks or
• 7:28
  Speaker 2: ten percent of the of the you know, like the
• 7:31
  Speaker 2: warehouse stocks. Okay, well, how much of that do we
• 7:33
  Speaker 2: have left? Cause I have been following this since like
• 7:36
  Speaker 2: about twenty twelve, and I remember that when the World
• 7:40
  Speaker 2: Grain Assessment from the USDA will come out, we were
• 7:42
  Speaker 2: around seven hundred and fifty million tons of grain. Now
• 7:46
  Speaker 2: we sit at around two hundred and fifty million tons
• 7:49
  Speaker 2: of storable grain or carryover stocks. Do the simple math
• 7:54
  Speaker 2: on that that was you know, a little over twelve
• 7:57
  Speaker 2: years ago, thirteen years ago. So if we're at that
• 8:00
  Speaker 2: rate and the declining crop yields are really starting to
• 8:03
  Speaker 2: kick in now, you know, you might be told in
• 8:06
  Speaker 2: the American news, oh, we got lots of grain. Oh yeah,
• 8:09
  Speaker 2: we do, because a lot of people stopped importing from America.
• 8:12
  Speaker 2: So we're sitting on piles of it here. But outside
• 8:15
  Speaker 2: of the rest of the world, and it's not like
• 8:17
  Speaker 2: that prices are higher. There's disruptions outside of where we sit.
• 8:21
  Speaker 2: Why do you think China is scrambling so much to
• 8:23
  Speaker 2: go get grain anywhere and everywhere they can. Well, they
• 8:27
  Speaker 2: understood through history that these four hundred year lows in
• 8:32
  Speaker 2: solar activity disrupt tremendously their production of grains. That's why
• 8:35
  Speaker 2: the dynasties collapsed. So now they're in the modern era
• 8:39
  Speaker 2: where they can go buy it, get it, trade it,
• 8:41
  Speaker 2: do whatever they you know, and give the loans out,
• 8:42
  Speaker 2: do whatever, give us the grains. But it's tight out
• 8:47
  Speaker 2: in the rest of the world. It's surplus here because
• 8:50
  Speaker 2: nobody wants our grains because of this tip for tat
• 8:53
  Speaker 2: trade thing. So it might appear as if in America
• 8:56
  Speaker 2: we got a lot of extra, But are we going
• 8:59
  Speaker 2: to be able to hold that and keep it for
• 9:00
  Speaker 2: twenty years in a silo if nobody wants to buy it. Nope.
• 9:05
  Speaker 2: Carryover stocks are only good for a couple of years
• 9:07
  Speaker 2: past and then once they get past that, they get
• 9:09
  Speaker 2: downgraded into like animal feed that sort of thing. Generally,
• 9:13
  Speaker 2: human consumed grains are in the same year or the
• 9:15
  Speaker 2: following year. So if we're continuing declining, it yields and
• 9:20
  Speaker 2: then the big bread baskets the world, like Ukraine that
• 9:23
  Speaker 2: took thirty million tons of actual real production offline, so
• 9:27
  Speaker 2: Africans were scrambling for where they're going to import grains
• 9:30
  Speaker 2: from because their predominant export market from Ukraine was down
• 9:33
  Speaker 2: to Africa. So now Africa is like out on the
• 9:36
  Speaker 2: world market. So there's a thirty million ton minus from
• 9:39
  Speaker 2: the two hundred and fifty million tons we already had.
• 9:42
  Speaker 2: Plus the declines are coming in. We got all the
• 9:46
  Speaker 2: you know, trading bargains with all the fertilizers, the herb sides,
• 9:48
  Speaker 2: pesticides that are not manufactured in America, and you start
• 9:51
  Speaker 2: to look around the imbalance is occurring currently. If you
• 9:56
  Speaker 2: were modeling this out, you would scratch your head and say, hmmm,
• 10:01
  Speaker 2: I wonder when we really need to wait to tell people,
• 10:04
  Speaker 2: because I was super clean after doing the research and
• 10:07
  Speaker 2: speaking with all those experts that were like one hundred
• 10:10
  Speaker 2: x above me, understanding all of this for those years
• 10:13
  Speaker 2: on end, doing endless interviews and reading, you know, tent
• 10:17
  Speaker 2: doing like you do, like ten thousand hours of research
• 10:19
  Speaker 2: to understand what this thing is and how it is
• 10:22
  Speaker 2: going to affect us. Here came to the conclusion that well,
• 10:26
  Speaker 2: you know, maybe you wouldn't want to tell everybody because
• 10:28
  Speaker 2: they're going to panic in advance. But at some point
• 10:31
  Speaker 2: we're going to come to that rollover period. And you know,
• 10:34
  Speaker 2: and I kept saying, okay, just on like a fifty
• 10:36
  Speaker 2: thousand foot view napkin math, prices are going to go double,
• 10:39
  Speaker 2: and then they're going to go triple. And at some
• 10:41
  Speaker 2: point they're going to get into the runaway where you're
• 10:44
  Speaker 2: spending a huge amount of money on food and basics,
• 10:46
  Speaker 2: and it's going to disrupt the economy, and that in
• 10:48
  Speaker 2: itself will disrupt happiness or harmoniousness how they termed it
• 10:52
  Speaker 2: in China, and that would set off a whole you know,
• 10:55
  Speaker 2: chain of events, and uh, you know, you get the
• 10:59
  Speaker 2: political you get the population, migration, and the economy heading
• 11:03
  Speaker 2: into greatly inflated prices. And I was saying, you're going
• 11:07
  Speaker 2: to look for a two to three x increase in
• 11:09
  Speaker 2: food prices, and sure enough we sit here today. I
• 11:11
  Speaker 2: would challenge anybody I'd go back to twenty thirteen, twenty
• 11:15
  Speaker 2: fourteen and look at what your grocery bill was compared
• 11:17
  Speaker 2: to today. This is going to continue into the future
• 11:22
  Speaker 2: the same. It's not going to pull back to like
• 11:23
  Speaker 2: twenty thirteen prices again, We're just going to continue to
• 11:26
  Speaker 2: go up and up and up, and the more than
• 11:29
  Speaker 2: a dollar de values and they'll higher the price of
• 11:31
  Speaker 2: all the PreCure's metals go and all the commodities, coppers, zinc, whatever,
• 11:35
  Speaker 2: you never name anything, it's going up. And the food prices.
• 11:38
  Speaker 2: I really believe this is the last year they can
• 11:40
  Speaker 2: control the food prices, because if the comax can't control
• 11:43
  Speaker 2: the silver price, and they're not gonna be able to
• 11:45
  Speaker 2: control the gold price anymore, which is the entire base
• 11:49
  Speaker 2: of the monetary system globally, they were not gonna be
• 11:51
  Speaker 2: able to press that on paper anymore. Do you think
• 11:54
  Speaker 2: they're going to be able to suppress the price of
• 11:56
  Speaker 2: say corn and soy on an international market, I'm going
• 11:59
  Speaker 2: to say no way. Yeah,