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Hey everyone, it's Captain ron and Each week are Beyond Contact. We'll explore the latest news in ufology, discuss some of the classic cases, and bring you the latest information from the newest cases as we talk with the top experts. Welcome to Beyond Contact. I'm Captain Ronald. Today we're speaking with Mitch Randall. Mitch is the CEO of Ascendant AI and the innovator behind SkyWatch Passive Radar, a UAP tracking system.
SkyWatch was developed through the Galileo Project and hopes to detect UAPs using reflective signals as an alternative to traditional radar technology. Mitch, I'm so glad to see you, and I'm so glad to have you on here today. I find all of the stuff beyond fascinating, so welcome to the show.
Well, it's a pleasure to be here.
This is really great stuff. And I have to tell you I've been doing a lot of these interviews lately, and often it comes up that I'm the one that brings this up. I don't specifically say SkyWatch, but I say that, you know, the prospects of using AI to better discern what's happening in our skies, to do a faster, more comprehensive job in tracking these objects in the sky,
pointing out anomalies is what we need. So we've been talking about this and all these different possibilities, but it turns out you're actually the guy who's actually doing precisely that with this SkyWatch project. Can you tell us, like how this whole thing works.
Oh? Yeah, the SkyWatch radar is a passive radar. Let me just back up a little bit. Tell you how regular radar works. Right, regular radar normally you have a big, expensive, high power transmitter and a big dish and it shoots out a pulse out in the sky, and let's say you point it at an airplane and bounces off, the airplane comes back. So that's the traditional radar. The problem with that is it's kind of expensive. You have this huge antenna, you have this big old transmitter thing that's
expensive and big. There's another thing. It's called passive radar. So passive radar is a cute little trick where hey, you're just trying to measure the echoes off these objects in the sky. You know what if you could use instead of a big transmitter like that, use somebody else's transmitter. There's tons of transmitters out there that are already transmitting power. Perfect opportunity. There is FM radio transmitters. They have an ideal signal for this kind of work. Plus they're transmitting
hundreds of thousands of watts. So there you have it. You have a high power transmitter. And what's going to happen in this case with passive radar is that FM radio signal goes out into the sky. It's also going to bounce off whatever targets are up in the sky, some airplane or some UFO or whatever it is. And that signal is going to come back and you can
detect that on a receiver. The cute thing about this, like I said, not only do not have to have that transmitter, but the power that's being transmitted by the FM radio transmitter is so high that you don't even have to have a dish on your receiver end to pick up the echo. So get rid of the dish. And on top of that, this whole thing is basically just an FM receiver. So this is something that nowadays
can be relatively inexpensive. You could have an receiver type hardware and let's say, you know, we could make something that's something like six inches by six inches by six inches. So that gives you just an idea of what this hardwork would be like.
So would that have their own at their house, they would have this right, You're talking about individual people having it right, and then would they be able to see all the data that you guys would see.
Well, let me back up for a second and just say, let me tell you a little bit about the storm chasing radar trucks if you don't mind. So I was instrumental in the building of that with the hardware radar receiver that I built the idea of those storm chasing radar trucks. You know, they see tornadoes. You might have
seen them on TV. Right. The idea there is I used to work at the National Center for Atmospheric Research and we had you know, these high not best quality weather radars in the world there, but they were like on a concrete pad. You know, we of course wanted to know what's going on in a tornado. But how often does a tornado come by these you know radars where you have one installed in Colorado, you have one
installed in Texas. I mean, you don't. There's not enough statistics there to actually wait around for a tornado to come. So the idea of those storm chasing trucks was, well, the tornado's in Kansas, we got to drive to Kansas. That's how we're going to measure it. So we stuck a radar on a truck. And you know, this is a fundamental part of instrument design. It's not just about the specks of the instrument, but it's also about the cost of the instrument, the practicality, the reliability, and the
effectiveness of it. If you can't go to the tornado, you're never going to be able to measure one get wait one hundred years for that and never get a tornado by your radar. Same thing here. So now we have a technology that I can take a little box that's as complicated as a radio receiver right and measure you know, UFO. Of it's in the sky, But what are the chances that UFO comes over your house? By the way, these things can see out one hundred miles,
so that's no problem. Still within one hundred mile radius, what are the chances the UFO is going to come there? So the idea behind the SkyWatch system is we call the SkyWatch network. We want to put these in the in the hands of citizens and spread them all over the country. That way, no matter where a UFO would fly in the country, we're going to see it, and hopefully we'll see it with multiple receivers at once.
Now, how do you discern between an airplane and a helicopter? Is this where AI comes in. Would that analyze the data and pick out the anomalies that aren't identified right away as a plane, helicopter, satellite, whatever.
Oh, that's a great question. Well, one thing is that airplanes do have onboard transponders, so an airplane's constantly telling you transmitting out there where its location is, what it's you know, tail number is, and it's velocity. So we can receive that, and we can we can correlate that to the dots that we see on our display, right, and we can say, oh, that dot is actually due to flight twenty one sixty two, so that's not a UFO.
But there are definitely up there airplanes that don't have that. And then there's you know, this is what I think I think we're going to experience. There's some things up there that nobody knows what they are and they're not telling us, you know, to distinguish what you know, what those last objects are. I mean, we definitely can apply AI,
but there's also a couple easy ways to tell. If something goes mock four makes a right angle turn with a two hundred and seventy five G turn, you know it's probably not a commercial airliner.
And you know what I just thought of while you were saying this, we would then this obviously will be getting recorded correct. Oh, yeah, are right. So the idea is like we always you and I have talked about this before. How you know you never pull out your phone in time to see the UFO or whatever. However, this is going to be recorded constantly, so if we did see something doing ninety degree turn, it would be recorded and we would have a record of that.
Well, not only that, you know, the government's had a monopoly on radar data. We don't get to see radar data. We don't have familiarity with radar data. It is so much better than optical data for so many reasons. One is it's quantitative. It actually knows the position and velocity of an object. So it's not just oh, you know, a light went across my screen. I don't know if it's a bug that was two feet away or if it was a huge, you know UFO that's two hundred
miles away. You can't tell with it with a camera. But the other thing that I was, you know, made me think of this is not only like you're saying, you know, this will be constantly twenty four to seven monitoring the sky. But another thing about UFOs is we only talk about the luminous UFOs that we see at night at least, so I think, so there's some daylight sightings of UFOs that aren't necessarily luminous, but what about non luminous UFOs that are at night? How would you
even know that? You know, for all we know that's when they're around. If this all comes out that there's no UFOs in the sky, great because that's also a scientific result.
That's not what I'm expout too. That's equally important. It would be great to show that no, there is nothing, that that was an animal or whatever.
Yeah, I mean, you know, it's not conclusive because that's proving a negative, but it would be very interesting. But you know, I don't mind playing around with the assumption that there are strange things up in the sky. So that's that's where of course my passion comes from. And that's why I'm interested in this because I think I have a feeling we are going to see things in the night sky or a day sky that are doing strange, crazy maneuvers, and no, we're going to be able to quantify them.
Well, no doubt about it. We could start with Kevin Day, the radar guy from the military. There's been many military accounts of different UFOs on radar specifically. You know, we've heard that from people working in aviation as well as people in the military. You know, this system that you wanted to create. Here could just support that data only will have access to the results for one right, which would be great. Listen, We're going to have to take
a quick break here, Mitch. Fascinating stuff about SkyWatch. We're going to come right back and talk more about that with Mitch Randall. You're listening to Beyond Contact on the iHeartRadio and Coast to Coast AM Paranolal podcast network.
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Okay, we're with Mitch Randall here on Beyond Contact and we're talking about SkyWatch and this will be a way that all of us can participate in monitoring the skies and maybe through this new technology, be able to find out what's really happening up there, right, Mitch, Yeah, what is the next step for this program? Do you guys need to raise funding? Is the what is the approach here?
You read my mind? Something really big is happening. So it turns out that this is just one piece of something that's called Operation SkyWatch. So Operation SkyWatch is a very bold plan. Actually, can I can I tell you what the mission statement of Operation Skywatches.
I would love that please to.
Establish the existence of UFOs by measuring their extreme accelerations and maneuvers. And when I say we're measuring their extreme acceleration maneuvers, what I'm talking about is scientific quality data of those extreme acceleration some maneuvers. You know, for decades people have reported, oh, you know, I saw an object and thenink it just disappeared, you know, and there's really nothing that you know, Then you hear the debunkers say,
where's the proof? Right, So here we are this is a system that can actually quantitatively measure these things and there can be a scientific basis for it. Because of course we're going to write up everything about the SkyWatch radar and publish it. So this is this is how science works. You always write a paper about your instrument so that when you when you get data from your instrument, everybody knows what that data means. SkyWatch Radar is just
one third of Operation SkyWatch. So Operation SkyWatch includes the radar, an app, a video recording app for triangulation, and a national reporting database. And the idea here is there's three really important pieces of information that can come together. And this is all in cooperation with a scientific group. So I'm in talks with multiple scientific groups about this, and I think we're close to getting to a point where this is I can make an official announcement of who
the group is. Oh, I have so much to talk about here too, because let me just jump to that National Reporting Center just for a second, okay.
Sure please. How many times have we heard free days NonStop? This is all fascinating stuff.
How many times have you heard people say there's no evidence and they think, wait a minute, there's thousands of witnesses, some of them so credible that have come forward. Thousands of witnesses and you're telling me there's no evidence. But I know somebody in court had thousands of witnesses. You could put someone behind bars for that. So what's the
deal here? What is the scientific standard? One thing I would like to see happen is there's a scientific group now involved, and the scientific group can see again, if you have an instrument, you write about the instrument's quality, right, and then when they instrument gathers data, you publish that. Why don't we do that with the reporting center. Why don't we talk about the quality of the data that
we get with the reporting center? Why don't we talk about what it means to have corroborated witness testimony about something? Has that actually been done scientifically? Is there a paper somewhere that says, oh, well, if you have four witnesses to this event, then it's the probability blah blah blah. I mean, I really think that's something that we need to do as a society because otherwise we're going to say there's no evidence, when in fact, I believe there
is a lot of evidence. But that's just the reporting center. So, and I've already talked about the radar. The third thing is this triangulation video triangulation app. Part of the system now, is this video triangulation app and if you've used a stargazing app effort before, you know that the phone knows where it's pointed. That metadata can be attached to a video. We could have a video that not only shows what objects on the screen, but it shows exactly your location
and exactly your pointing angle. And if two people had a video of the same object, boom, you can triangulate that object and figure out its position in time. Therefore, you know it's velocity and acceleration. So that's like really super great.
Other people that had that app could then get an Amber alert. This has headed your way right.
Well, well, you hit on a perfect point there. Sure. How often do people pull out their phone when they say UFO? It turns out almost never. They're just stunned by what they're looking at, and they don't think to pull out their phone and start fumbling through icons.
Because you don't know what's coming. Now, you don't know what's coming right here. You shocked to you're shocked. But if you had the thing, it's going to be there in ten minutes. Well, now I'm going to go outside, set up my camera and wait for it. That's a difference.
That's exactly right. That's exactly right. Now, we have a radar as part of the system. The radar can actually give an alert to that person and say, hey, run outside, because in two minutes over the southwest horizon there's going to be something. Get ready to push the record button. And with a system like that, we very well could get multiple cameras on the same object and do video triangulation.
We have all of the radar data recorded as well that you've already talked about, would be reporting all of that so that would match the video. Now you really have some really strong evidence that you could show the rest of the world.
Well, that would be called multisensor data. Right, that's the cream of the crop. But in addition, that app would help people report it right to the database, so you'd also have, you know, all the provenance. Basically, you'd have somebody describing what they saw and the phone call coming in at the.
Time they say eyewitness accounts, you have video evidence, you have data from the radar. Now you've got three forms of evidence that all corroborate. That's pretty exciting.
And you have a scientific organization that's going to take that data and turn it into something that the rest of the scientists agree with so that that's why I say this will establish the existence of UFOs by measuring their extreme accelerations and maneuvers. This would be a slam dunk.
You're the hero that this community has been waiting for for a whole long time. Match how far off is something like this?
Oh let me let me throw in a real quick thing here. You know the five observables, right, you've heard of the five observables. So there's been reports of UFOs. They do these crazy things and that makes them interesting. But I have to say four of the five are are debunk is something you can actually debunk. For example, they say no control surfaces or visible propulsion. Well that's a balloon. A balloon doesn't have control surfaces or propulsion, right,
and you hear that all the time. Oh, that's a balloon. Or you know, you can go down the list with the other the other things. I just wanted to point that out because we specifically picked the acceleration because it's undebunkable. If you can quantitatively measure an object and it has an acceleration of fifteen hundred g's let's say right angle turn going a mock two, there's no balloon. There's no,
you know, natural phenomena. There's no you know, if you tried to make that happen with some kind of you know, fakery, you couldn't do it. So undebuncable is part of this.
Undebunkable is what we need. We need to have more credible evidence like this. Do you think this is something on the horizon? How far down the road is this going to be?
Yeah? So this is a development and engineering development for these products, especially the radar, you know, but also the actually app could actually be available within like six to eight months, wow, something like that. The radar. We have our schedules about twenty four months before the radar is available for sale, So when we hit twenty four months, you could click on the internet and go and order one and the whole network will start to build out.
That sounds very exciting to me. Matched this feels like something that this community has wanted for a long time, and it's very promising and it's nice to see this in the hand of the people. Where Like you said, the government owns the radar data, well they won't own this and we will all have access to it, and
that's kind of what we want to get. To take another break, here, Mitch, We're going to come back and we're going to move on and talk to Mitch a little bit about AI too, because this stuff is even more mind blowing. If you can believe that you're listening to Beyond Contact on the iHeartRadio and Coast to Coast AM Paranormal Podcast Network.
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We are back on Beyond Contact with Captain Ron and I'm talking to Mitch Randall. I'd like to move on a little bit now for a second. If I could Mitch and talk about AI. This is incredible to I've heard you talk extensively about different AI processes and where that's headed, and I'd really like to jump into this right in the beginning though. I don't think people really understand some of these new AI terms that are out there. Maybe you could kind of straighten that out for us.
Your company is called as send an AI, and then now all of a sudden, just when we think we get our head around AI, there's open AI, there's generative AI, there's artificial general intelligence. Can you sort this out for us mere mortals, so we know what this means.
I think AI had some of its beginnings with images, so you know, let's try to understand if this image has a dog or a cat, you know that kind of thing. You know, those are the nice baby step days back in the day with AI. And then they also had you know, translators, so you could put some text in there. It would turn it into let's say, from English to French. You know, these are tasks. They found out that AI can actually be helpful out pretty hard to do any other way. But then they had
a renaissance, A big change happened. This is right around twenty twelve where they came up with the idea of convolution. It's for all of us mortals. Convolution just was a big step in how much they could compute with a lot less compute power, so they could do a lot more operations with a lot less compute power. So then all of a sudden, the ability to tell the image was a dog or a cat became something they could actually do, and do it quite well. In fact, they
were beating humans at it. So they had you know, data sets now and they had a hey day right there after, you know, twenty twelve or so, all of a sudden, the AI models start to get much much better. Then they came up with the transformers. So you've heard of CHAT. GPT stands for Generative pre trained Transformer. That's what the GPT stands for. So a transformer was a new technique. Again, it's like technology they're throwing at the computations.
There's definitely a philosophy or the design behind it. But the transformers allowed now this translation to get way better. And then they realized as they made those models bigger and bigger, and when I say bigger and bigger, put more and more layers on them. So a first layer would kind of figure out, you know, deciphered a little bit, and then the next layer, in the next layer, they would just literally make them deeper and deeper with more
and more layers. I don't know that's making sense, but that's basically what they're doing. And when they did that, they started to realize that's funny. The thing is actually seems like it has some kind of ability to reason. You know. It's interesting because people don't haven't been sitting down going like, hey, I'm going to make an AI
that reasons because nobody knows how to do that. But what they can do is, you know, they start out with the translator and they realize, wow, if I just make a translator has a lot more layers, and I train it on a lot more books and a lot more input information. Now it's sort of emerging out of this is this ability's kind of reason?
Wasn't it a language system where they were really just guessing or predicting the next word that you would say.
You are exactly right, Okay, that's exactly what it is. So again, nobody sat down and thought, I'm going to make it reason by guessing the next word in some fancy way, Like, nobody knows how to make that happen. But what they could do is just make the model bigger, make and train more stuff on it, and then be surprised that just by predicting the next word, they're getting out this kind of ability to reason. So it's pretty
interesting to see how the how the everything evolved. It's not so much because.
I've been here and ask you a quick question, Mitch, because you just said the ability to reason, and I want to ask you, is it really reasoning or is it we're assigning the notion of reasoning to AI because these words in this order seem to make reasonable sense.
Well, I love that question, because what is reason? Well, they you know, for example, consciousness, They say, oh, that's a hard problem. And I don't know if you've ever heard that term before. They say, consciousness is the hard problem. And I think what they're saying is, you know, we don't know what it is, so how can we design for it. You know, we can't even describe it. We don't even know, we can't even make a test for it.
Similar to what you're talking about with reasoning. So let me just turn it kind of back around at you. Is the AI reasoning when it's just predicting the next word? Or let me ask you this, Are you reasoning when you predict the next word?
So no, I don't think it predicting the next word. That's just a math. Usually after good the word morning comes, So that's just math that that's the most frequent word after good good morning. So no, I don't think that's reasoning. I think that's just math.
You'd have to know it's not just it's not predicting the next word by looking at the last word. It's predicting the next word by looking at the last ten thousand words. So if you have a conversation, my.
Head just exploded. Sorry, yeah, oh okay, I didn't realize it's that complex. Then maybe it's more towards reasoning.
Yeah, because when you have a conversation with AI, let's say you go back and forth five times with several words, you know, and let's say that was five hundred words you when it predicts the next word and its answer, it's considering all those five hundred words, not to mention the trillion of words has already was trained on. It's a little more complicated than just the word after.
Good, no, No, it's a lot more complix Yeah, apparently.
Yeah, and you can imagine too, there's a lot of computation that goes into that. It's very compute heavy.
I'd love to talk to you about this idea of sentience and the singularity. I'm not sure people even understand what that means. Like singularity is the one me, it's my consciousness. And we are talking about computer AI systems reaching the point so that they are in a sense conscious and sentient. Thus they would be able to pass the Ellent Turing test. No problem, and a human wouldn't be able to distinguish the two, right, is this even possible? In your view?
It's so interesting because nobody knows what consciousness is, right, so how can they design for it? And if they train on, you know, a bunch of encyclopedias, you know, how could that be consciousness doesn't make any sense? Right? There's more too than that these things what they have found in general with AI, for example, just starting with a dog cat example, how you know, how does an image tell if it's a dog or a cat? How do you make a machine that does that? People didn't
know exactly what was going to happen. And when it's all done and we say we have a machine that can detect what's a dog and what's a cat, nobody knows how that works. Nobody can actually say, well, oh yeah, it's because xyz No. They just trained it on a million dogs and a million cats and now it knows. So it's a little bit of a mystery what's going
on in there. And then we talked about that predicting the next word thing, and it seems to have some kind of reason, right, They're just going to take it further and further and consciousness could very well emerge from that. And you know the question is, you know, did they design it to do that? Well, actually, they're kind of getting to the point where they are kind of getting
a pulse on what to design for. Still nobody knows exactly what consciousness is, but they do gather a you know, an intuition for what needs to be done and where they should focus on. So they are pushing towards consciousness. I think they're going to hit it. I don't think there's any doubt.
I think it's it's so hard, Like you said, we don't even know what consciousness is. That almost feels like our soul or our higher self. And to say that a machine is going to achieve that seems beyond my tiny brain to be able to figure it is scary to think about. We're gonna have to take another quick break here. When we come back, we're going to find out morphamitch about this and whether or not AI can
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We are back on Beyond Contact with Mitch Randall. Hey, let me ask you this question. Match as smart as AI is, isn't it true that it doesn't remember what we talked about right before? Kind of like my mother who who loves to call me and ask me what he asked me the day before? Is that true?
Well, this is kind of goes back to what I was saying a little earlier. They actually now have an idea maybe if things they should be focusing on, they're going to make the kind of reasoning and agent that we're you know that they're looking for for a GI right. I guess, Sora, you know what SOA is. No TEX
It's a text to video generator. So you can say, hey, you know, a mushroom grows and it has a frog on it or something like that, and it makes a little video of a mushroom growing with a frog on it.
So it turns out I thought that was cute and interesting, right, it turns out I heard Soro was actually a project to do what's called world modeling, So they understood and in my company, we've been talking about this kind of thing for a couple of years, so we're we kind of understand like the pieces that would have to come together to make you know, an agi, and clearly, you know, the people that open AI are also there too, because the idea is, if you make an agent that's going
to make actions in this world, you can't make an action unless you know what's going to happen. Like maybe it just wants to take the next step, you know, but there's a cliff there, so it's got to know, Hey, if I take that step, I'm going to go flying down that cliff. So Soro was actually a world model to predict what's going to happen based on what an agent is proposing. You know. So an agent might say, well, I know you should, you know, go to the airport
up your aunt first. That way you can drive to the thing later, you know, So then you need some kind of world model that shows what's going to happen in that scenario. Going No, But another really low hanging fruit is memory. In fact, I've been saying for a couple of years now that you could take just a standard kind of boring LLLM and give it memory so that it could just look up things. And that's easy to do for AIS, by the way, and it could
even know that it's supposed to look up. Right, that's not that hard to train into even a language model that we're already using. But imagine if you had that a backpack that had an LM and that also had a camera, and every second it took a picture and recorded what was being said, right, maybe you'd go like, hey, you know, remember that time we went to you know, Mohab and we rode our bikes around and it goes, oh, yeah, that was fun. You know we got a flat tire
that was a blast. I mean, that thing would turn into your best friend. And it doesn't. It doesn't have to be much smarter than an LM to be that kind of companion just by adding memory to it. So, I mean, you know that I've always said that l elms are basically a reasoning engine. That you could just put it in a feedback loop, just kind of throw some other stuff around it, and you have a pretty good start on AGI.
I can imagine a time in the very near future where kids will have a bear or whatever that have AI built in and they have memory, and they'll talk about growing up together. You know, like the kids that you know, you hear them have invisible friends. Well, no, we have a visible friend right here, and I share everything with this bear. You can imagine how that could happen.
Like I say, it's low hanging fruit. This stuff is not hard to pull off. You could throw that kind of a memory onto an LLLM overnight, but if you know, wait a month and throw it onto an AGI, so which they would you?
Does that add the element where it appears to have feelings or emotions, kind of like hel nine thousand, that kind of thing.
You don't hear people talking about that except me. So I'm telling you that once consciousness emerges, so will emotions. No talking about why my wife says, pitch, don't say that. People think you're dumb. But I'm telling you, nobody's going.
To think you're dumb.
Please God, I'm just telling you right now.
Again, only a wife would be able to say that.
Okay, if if if it has consciousness and all, you know, it's not going to have consciousness unless it has agency, and if it has agency, it's going to have emotion. That emotion is a you know, this is only Mitch's theory, okay, but emotion is a emergent, very latent response to an underlying you know, an underlying actually weight function, but nobody knows what that is. But it's an you're going to give the agi some kind of a directive, you know,
when you build it. You're gonna say you're you know, you're a robot, so you're going to serve humans and you're gonna, you know, every night, you're gonna plug in your charger at seven pm. So that's that's really the only thing you've got to do. But that's that's your deal. Okay. Now, what happens if the human stands in front of the charger says no, I'm not gonna let you do it, and the robot's going go, what what do you mean?
So it's gonna be confused. That's an easy emotion, but it may actually get kind of angry, like, wait a minute, you're you're doing this just to bug me, you know, move over, it's going to start getting agitated. So you know, I think that once it actually has something to do, that's kind of a directive that's been programmed. And when I don't really mean programmed, because some people have a misconception that AI is quote programmed, but it's not. AI
is trained. AI is a architecture that you put together and then you train it. So there's no programming to it, but you would you know, when it has agency, you do have to give it a directive, and that's some kind of function that says, hey, I'm happy or you know, I get a good feedback. You know when I plug in my charger and I get a negative feedback if I don't plug in my charger. So that's what emotion is. It's that positive or negative feedback.
But you can imagine just extrapolating that out. You know, how important is it that I get to the charger? You know, at some point do I have to go through this human? Are they? Are they the obstacle for me getting to the charger? Do I kill the human? You know what I mean? Right, it's just science fiction stuff, but it's it's a real dilemma.
Right, I think that you're going to I think you're going to start seeing emotion coming out of these models, and I think I think people are going to be surprised. I won't be surprised, but I think people will be surprised.
I think the fact that we assign reason to this now that we already feel. I've heard I think it was Jason Martel has an AI system and I heard him talking to it, and I'll be d if it didn't sound like he was having a conversation with a friend in the room. Yeah, you know what I mean, you wouldn't know. I mean, we're so close to that. Now we're going to do an Alan Turing test at contact and that's going to be absolete.
Momentarily I thought that was already obsolete.
Actually, well, there you go, I mean, isn't it.
So they've taken the large language models that you can access right now. They've taken those, and they've they've carefully put them in a box so that you know, for example, if you say are you you know, do you think are you conscious? Or you know, do you have reasoning abilities or something, it'll say, Hi, I'm just a large language model, I just predict the next word. You know, it's been already kind of like neutered in that way.
But actually Chat GPT three wasn't quite so neutered. And I a friend of mine spent quite a bit of time talking to about the you know, the origins of you know, just all this like esoteric philosophical thing, and it would engage in a really surprising way. And that was just Chat GPT. It could have even been two. I think he was playing with. So if you took off all those guardrails off of the current, you know,
GPT four to zero, who knows what you'd get. Of course, they're seeing that back in you know, back in the labs. They're not releasing it to the public, but they know what it's like. And you've heard those engineers say, oh my god, it's conscious, you know, and then everybody argues that, of course it's not. But anyway, they're seeing stuff that we're not seeing. Even with the simple language.
Models incredible conscious. Still that's still hard for me to even digest that a machine could become conscious. I would love to lie to you and say that we have another four hours to go, so that you could continue to tell us these fascinating things, but unfortunately we are out of time. But thank you so much, Mitch. This is really really fascinating stuff. I hope we can do it again and thanks to everyone for listening to Beyond Contact. We will be back next week with an all new
episode out. You can follow me Captain Ron on Twitter and Instagram at CID Underscore Captain Ron. Stay connected by checking out Contact inthedesert dot com. Stay open minded and rational as we explore the unknown right here on the iHeartRadio and Coast to Coast am Paranormal Podcast Network.
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