From First Principles - 3rd Interstellar Visitor, Rubin’s Sky Camera, AI CRISPR Boost & T. rex Blood Vessels (EP. 4)

Episode Date: August 19, 2025

Interstellar visitor #3 is here. We unpack 3I ATLAS (why it’s moving so fast, why we finally saw a tail, and how Hubble/JWST—and maybe even Juno—could nail down its makeup). Then we dive into th...e Vera Rubin Observatory, the 32-gigapixel camera that will turn the entire sky into a time-lapse movie and supercharge discovery. Next: AI just boosted CRISPR by predicting and guiding DNA repair (Pythia), making edits cleaner—especially in non-dividing neurons. And we close with a crossover of dinos + particle physics: preserved T. rex blood vessels revealed by a synchrotron. Mystery Box: the viral “Black aliens” meme.

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Starting point is 00:00:53 Spend $250 on your first campaign and get a $250 credit. Go to LinkedIn.com slash campaign, terms and conditions apply. Hello, Internet. This is your captain speaking, Lester Nare. I am joined as always by my co-host and our resident PhD, Krishna Chowdhury. This is from First Principles. We have some great stories for you this week, starting off with the third interstellar object to pass through our neighborhood, 3-I Atlas. Is it an alien spacecraft? We'll soon see. We'll follow it up with a story about the Veri-Ruban Observatory, which is related to our initial 3-I-Atlas. Is it? We'll soon see. We'll follow it up with a story about the Verac-Ruburn Observatory, which is related to our initial story on the third interstellar object. We will follow that up with moving into AI. AI meets CRISPR for precise gene editing. Maybe you can fix my knees a little bit, a little rusty. And we will end with a great story.
Starting point is 00:01:47 Shout out to Jurassic Park for a rare T-Rex blood cell vessel found in fossils that show that dinosaurs had the ability to heal their own injuries. And we will end with a mystery. box. This is from first principles. How are you, my friend? Doing pretty good. Episode four. Yeah, we're still here. Shout out to everybody who's tuned in on YouTube, TikTok, Instagram. Yeah, we really do appreciate it. It's been a great, great commentary, great discussion. And we're going to start off with a story that's near and dear to my heart, which is about this interstellar visitor. That's right. So just to kind of set the table for context.
Starting point is 00:02:42 because there's a certain Harvard physicist who has been used in a lot of the headlines around this story, Dr. Avi Loeb, who's the professor of astrophysics at Harvard. And funny enough, for those who might not know, I am the director of operations at a nonprofit called the UAP Disclosure Fund, where we are actively working with members of Congress and the executive branch to push for disclosure around these weird things that are flying around. And it just so happens that our favorite Harvard astrophysicist, Avi Loeb, is one of our advisory board members. So as soon as I saw the headlines of Harvard astrophysicist says, I knew it was Avi. Yeah. And I know.
Starting point is 00:03:24 And you've met him. Yeah. He's extremely, he's hilarious. Yeah. He's just so funny, witty, charismatic. It's not a surprise he's been as successful as he has. Yeah. Because in, you know, in the industry, it's both you have to do the work, but also be able to sell.
Starting point is 00:03:39 it. But I think what's been interesting is how this story has cascaded all over the place. Yeah. It started with an initial observation and it seems like we've had some follow-up observations from, you know, things like the Hubble Space Telescope. So I'm really excited to kind of get your perspective on what exactly is going on here. Yeah. So I hate to break it to you, man, but it's probably not aliens. I tell you this every time. We've known each other for a while. And every time it's been like, Yeah, not this time. Yeah, not this time again.
Starting point is 00:04:16 It's probably an interstellar comet. Okay. But it is still really, really, really cool. And I want to see more pictures. Okay? Putting it out there, it could be other stuff, but it is very likely just an interstellar comet. And so I think what's interesting about this whole concept of interstellar objects.
Starting point is 00:04:37 Yeah. you know, coming into our, you know, into a near earth or into our solar system. It's a relatively rare, at least from our ability to track it. Our ability to track it. That's the thing. It is, it is. The first one was, um, Omuamua, I believe it was called. Yes.
Starting point is 00:04:53 That was in the late 2010s. Yes. So just maybe five, no, like probably less than 10 years ago. Yes. And then the next one that came out was two I borisov. Yes. And then this is the third one. Both of which Avi was, you know, one of the first early movers on really working on them.
Starting point is 00:05:12 And so we don't really have a lot of context or data. No. By which to sort of do analysis on this, which is why it's so important that we've had astronomers using Hubble to sort of point at it and say, hey, what data can we gather around this? Yeah. This one is really nice because we caught it on its way in. Right. Okay? Right.
Starting point is 00:05:32 Or mua, more, we caught it on its way out. So we can't get good data anyways. The data has really high error bars where we don't know if what we saw is like if the number that we got is the true number, if it's plus or minus some big thing. Now we see it coming in. So it's really nice that we can chart its trajectory. Yep. And we can like schedule observation. Yep.
Starting point is 00:05:55 Okay. And that's, I think, going to be key to really understand what this thing is because, you know, this thing is most likely an interstellar object that is. that is just like going through the Milky Way at an incredible speed. That's one of the things I think that's been pointed out in a lot of the news stories is that it's moving so quickly. Yeah. It's moving extremely quickly. And I guess one of the questions becomes, how do we do analysis on, or what are the characteristics that we would look for in an observation like this to distinguish it from just saying like, or what are the, attributes that make you sort of make that conclusion to say this has attributes that are similar
Starting point is 00:06:38 to comets or other sort of rocky objects that we've seen even locally no that's a good question um to really get into that let's talk about sort of the history of how we yeah found this thing right so we found this thing back when it was about four or five astronomical units away from the sun an astronomical unit is the distance from the sun to the earth so it's like four or five eye away from the earth. Okay. That's when we first spotted it. It was like out at near the orbit of Jupiter. So real, I mean, we spotted it relatively close relatively close. Yeah. Um, it's moving extremely fast, 58 kilometers per second. So that's one, um, earth orbit like one, yeah, one earth orbit radius a month. Okay. Which is like really fast. Yeah. Like it takes us years to get to Jupiter. And this thing
Starting point is 00:07:29 is going to be here in like four months. And I want to be specific. When you say orbit, you mean orbit around the sun, not the rotation of here. No, yeah, yeah. This is the radius of our orbit around the sun. It's taking that in a month. So what would take us 12? Yeah, what would take us like years? Yeah, yeah, yeah, makes sense.
Starting point is 00:07:45 To get from here to Mars usually takes us a year. Fair. This thing is going to do it in like. True, because you're talking about traveling through space at a target. Yeah, and this thing is just coming at us like in a month. So this thing is incredibly fast. Okay. Okay.
Starting point is 00:07:58 When it was really far away and it was first spotted, we thought it was like 20 kilometers big which is massive yeah yeah yeah okay that's like a big big comet big asteroid I think in the movie deep deep impact the the asteroid that was hitting Earth or whatever was like one one to three collars I think it was significantly smaller
Starting point is 00:08:20 significantly smaller and that thing did damage right so this thing this thing is like a you know at least it's a life killer it's a mass extinction type thing yep if it came especially at that speed like Yeah, no chance. We'd just be wrecked. So it's incredibly fast, and we thought it was incredibly big. The other thing that we thought was, you know, it was really far away.
Starting point is 00:08:43 We couldn't see any gas coming out of it, like what normal comets do. When they come out from way out there, they usually have a buildup of ice. And then when they get closer to the sun, they should like, you know, start having this tail, which is from all the ice. What's famously known as the cometary tail, which was what was. originally interesting about a muabua was and the problem was we were catching it late so we couldn't have enough data to tell but the lack of a commentary tale was one of the reasons by which it was like well it doesn't look like the other rocks that we've seen fly yeah yeah so this one
Starting point is 00:09:16 it was similar right and um that's when professor lobe came out and was like you know this could be something weird um we should take a closer look it could be um it could be aliens and um a lot of of astronomers at the time came out and said that well it's like too far away for us to really get good data okay with astronomy that's always the name of the game like it's like it's hard to get data on these things um now i think it's been a month since since then a month or two probably since then it's come closer now we see a tail okay we do we do see a tail we see a tail we see we also see a sun facing tail how do you mean okay so if there's the sun the common is moving like this, you'd expect there to be a tail that's going in the back, right?
Starting point is 00:10:01 Behind it's like leaving stuff. Yep. Behind behind. There's also a tail facing towards the sun. Got it. And that is something that we know comets do. Okay. Because of something called sublimation.
Starting point is 00:10:13 You've ever seen dry ice? Like dry ice just goes straight from solid to vapor carbon dioxide. Right. Right. Right. It doesn't go in. There's no liquid CO2, right? Because the, the air pressure is actually just too low to have.
Starting point is 00:10:27 that so the phase changes go straight from solid to gas same thing is happening on this comet like the water ice is getting bombarded by the sun's rays and then it's just boiling off there's no like so it's called sublimation and that creates this like gaseous sort of water vapor halo around the comet the Hubble the Hubble Space Telescope made an observation of it not too not too long ago yes and it updated the size of this thing the size of this thing we thought it was 20 kilometers, it's now something like 0.3 to 5 kilometers. Okay.
Starting point is 00:11:01 Significantly smaller. Yes. And it is most likely smaller than one kilometer. Okay. Okay. Now, also, what's interesting is the air bar is so massive. It's going from 0.3 kilometers to 5 kilometers, right? It's a pretty wide range.
Starting point is 00:11:16 It's almost tenfold. Yes. In the variation. And that's just because, like, with comets, the nucleus is shrouded now in this. In, like, if you look at that photo, right? Yes. The nucleus is shrouded by this gas now. Right.
Starting point is 00:11:29 So now it's really hard to resolve like what's happening on the very inside. It's a force field, I promise. Yeah, it's something like that. It could be. But I think what's interesting here, and this kind of goes to why the instruments we use for detection really matter. Because it allows us to get sort of a high fidelity data set to then be able to do analysis. And also being able to do so repeatedly over time, such that we can continue to refine. Yeah, yeah, yeah. And as it gets closer and closer, we're going to be doing more and more. Because this is, I mean, at the end of the day, this is an incredibly interesting object, okay? Right. If we were to run back the clock on where this object came from, this three eye atlas, okay, it's an interstellar object. And if we were to run back the clock on where it came from, it would come from the depths of the Milky Way and especially in this region of the Milky Way that's like right above our disc. Okay. Okay. It's called like the thick disc. Okay. So the Milky Way is like this.
Starting point is 00:12:26 right you've you've seen the the Milky Way across the sky yes most of that stuff is in the thin disc okay that's where the like stars and the and the gas sort of is so when you look up at the night sky in the National Park or in a really dark area you'll see it going across the night sky that's usually just the thin disc right above that thin disc is something called the thick disc okay and this has an old population of stars okay really old okay okay like older than our solar system And if this object came from up there, and it's like sort of, you know, crossing down into our neighborhood, then it came from those objects, which means that, you know, we're estimating this thing to be seven billion years old. Wow.
Starting point is 00:13:10 Okay. Which is older than our solar system. Right. So this is actually the oldest object that we, that we've seen in our solar system, which is. It's older than everything else. That's around, it's basically like, it's, you know, a quarter of the age of the, no, about half the age of the universe. Which is fascinating. Yeah.
Starting point is 00:13:28 I mean, we're about a third, right? Right. But like, yeah, this thing's like half. Look, I'm not saying it's aliens, but they've had time. They have had time. And they might live up there, you know? So, but we definitely know that it's old. Like, if it's a naturally occurring rock and it came from up there, it's probably really old.
Starting point is 00:13:45 Very old. Fascinating. The other thing that's kind of crazy is like how fast it's going. So how do we explain that? Right. Well, that can be explained by just close encounters. of the gravitational kind. Right.
Starting point is 00:13:58 Okay. So it was passing through, you know, through from the thick disk, through the thin disk. And at some point it passed a very, very massive object. Yeah, it passed a very massive object in exactly the right.
Starting point is 00:14:10 I mean, this thing's been around for seven billion years, right? So, and if it's like out here, who knows how long it's been roaming the cosmos. Right. Right. So, you know,
Starting point is 00:14:19 in the three body problem, if you remember, right, like tiny little deflections can cause something to just shoot out, right? You can imagine the same thing here. Like spacecraft, NASA uses these things called gravity assists to boost the speed of spacecraft all the time. This thing could have had a very close encounter with a massive object, let's say another star, and it was just like shot out. And then ended up being shot out in our direction. In our direction. Now, the direction that it was
Starting point is 00:14:46 shot out in is very peculiar. Okay. Because the sun and the planets form an ecliptic plane Yep. Where we all sort of like, this is the primordial angular momentum of the solar system coming to fruition as like one plate where all the planets reside. And this thing is coming in at like a really shallow angle, right? Of all the angles that it could have chosen, it did choose this weird shallow angle. Okay. That's a little weird. Okay.
Starting point is 00:15:15 I'll take it. Owo did not do that. Okay. Right. So it's, you know, you could say, well, you didn't use it for that one. And then how you're using, you know, so like it, it, again, it could just be coincidence. This is the first three that we've done. And this is one that like it's, um, as, as people are saying, it's like taking a tour of the solar system, right?
Starting point is 00:15:36 It's going through Jupiter. It's going to visit Jupiter. It's going to see Mars and Venus. It's not going to see Earth. We're actually going to be on the other side of the sun. Got it. So it's going to like, if the sun is here and we're here, it's going to like move over there. It'll pass through generally where our orbit would be.
Starting point is 00:15:51 We're just in the wrong place. Yeah. We're just in a wrong place. at that time but but then it's going to go see Jupiter later and actually there's a there's a proposal out in as for physical letters yes I think by Professor Avilob that wants to get the Juno spacecraft which is around Jupiter yes they just want to like boost it a little yes and they calculated how to do it you boost it a little you get it in a higher over around Jupiter and then it'll make a really
Starting point is 00:16:18 you can turn it and yeah it'll make a real close encounter I think that would be really cool actually personally I think that would be a great use of juno what so I mean it seems like and this is a call to those who may be watching that are in the annals at NASA yeah making decisions given we don't have a lot of historical data about interstellar objects passing through our solar system it seems like and the fact that they're always chance opportunities yeah this seems like an incredible opportunity with relatively low lift. Yeah. We've done the math.
Starting point is 00:16:54 We've done the math. Yeah. It can be done. Do we want to waste the fuel? Hey, look, when's the next time we're going to get a chance to capture an interstellar object at that proximity? Yeah. Especially given where our orbit is, that means like on Earth observatories.
Starting point is 00:17:08 Yeah, we're not going to be able to because we can't like point at the sun. Right. It's going to be behind the sun. So like what are we going to do? Already though, like so many people have like imaged it. Hubble Space Telescope imaged it. the very large telescope, the BLT that we talked about in one of the previous episodes, that imaged it.
Starting point is 00:17:25 Gemini North, another telescope that we've talked about in previous episodes, that imaged it in Hawaii. So we've had like tons of interest in this thing because it's obviously interesting. It's a seven billion year old object that's coming to visit us. Right, right. It's incredible. We want to, we have to have the doorman to check to make sure security is tight. Yeah.
Starting point is 00:17:46 Who are you and what intentions do you have with the? our daughters. Yeah. And it appears that it's going to be making its closest sort of approach to us in the late October, early November 2025 timeframe, which is why everyone's freaking out that there's an alien invasion in November. Yeah, yeah, yeah. I mean, if we find out it's aliens, then the stock market crashes.
Starting point is 00:18:11 I don't know what happens to Bitcoin, you know. But we will find out soon. It's not too long away. Yeah, it's not too long away. And actually, you know what's hilarious? Sixth of August. What's today's date? The 12th.
Starting point is 00:18:23 Yeah. So six days ago, the James Webb telescope imaged it. Oh, interesting. But they haven't released the day because there's a three-month embargo on whoever gets the time. Like, so whoever, like, had that time was like, I'm going to point it here and then, like, imaged it. And I'm sure that if, like, that's another thing that gives me, like, some security is, like, I'm sure if that dude, like, saw something weird, it would have. NASA would have been like, no. Okay, yeah.
Starting point is 00:18:49 It would have, we would have seen this. We would have like, someone would have said something. Right. By now. So it's been six days. It's probably something extremely interesting and this guy's scrambling to get his paper out before the public gets the data. Right. That's, I.
Starting point is 00:19:03 But it was like six days ago. And it's also going to image it again in December. Okay. So it's actually scheduled in December. Okay. Perfect. Perfect. So, so.
Starting point is 00:19:11 Because that's when the earth is going to be at exactly the right spot to see it again. Because James, James Webb is also, it's still tied to Earth. Ah, right, right. It's not like just out there. It's out there, but, but so it's like now and then we're going to have like a few months where we can't because we'd have to point it towards the sun. Which is why Juno is so important. Yeah. NASA, send Juno out there.
Starting point is 00:19:32 Let's take some pictures. Yeah. We want to see it. It does look really beautiful and brilliant in the, in the imagery you do have from Hubble. Yeah. And you can see it's clearly moving, right? Right. Because like the streaks that you see there.
Starting point is 00:19:45 Yes. Those are stars. Right. That are not moving. So the telescope had to like track it. Yes. And then as it was tracking it, the stars were like making streets. Nice, nice space long exposure.
Starting point is 00:19:57 Yeah. So while it may not be aliens yet, it will give us more data to sort of like that in the sort of AI analogy, it's like that training data set of what we know is sort of prosaic data. And such it gives us a better way to then tune for future potential visitors. if they're not already here. Yeah. And it's going to be really interesting to see, like, once it gets closer and we take more data, it'll be really cool to see what this object is made of. Right.
Starting point is 00:20:27 Right. Because, like, we know what solar system comets are made of, but are these older solar systems somehow different? Do they have different characteristics? We've already found water on it, which is very characteristic of a comet. So, you know, in that respect, it's very similar. And we're expecting to find CO2 and carbon monocon. side, but it'll be interesting to see what else comes out, right?
Starting point is 00:20:50 Like, maybe there's like some other exotic chemical that we didn't even think a comet would have. This actually ties to the story we previously covered about the importance of discovering the first molecule in the universe and how that then has this sort of butterfly effect in terms of how everything forms downstream. And this would be great insight to understand those earlier solar systems. Yeah. And what's kind of going on there?
Starting point is 00:21:17 This also makes me think we should do another episode on the idea of pansepermia, where it's the idea that life is seeded from these comments that are traveling interstellar and carrying things like water. Yeah. Like that would be, I mean, this thing is carrying water, right? What else is it got? Right. It would be so interesting to see.
Starting point is 00:21:37 And like, you know, the other thing I want to say is we've only seen three, right? And the reason we've only seen three is probably our. inability to see the rest. Fair. Right. This might be super common. Right. We've only had like a giant network of telescopes doing this kind of stuff for not very long.
Starting point is 00:21:57 Right. Right. Right. So it's not like, you know, all of a sudden someone turned on right. The interstellar button. Right. And now, like in 2015. Right.
Starting point is 00:22:06 Right. And for that, we need like telescopes that are dedicated to just like finding this kind of stuff. Which means we need to fund science. Yes. Yes. And for that, we actually have a telescope now. Right. And this is our second story, which is this is an NSF National Science Foundation and DOE, Department of Energy, collaboration for the Veri-Rubin Observatory. So the sort of headline on the NSF.gov website is beginning in 2025, NSF DOE Ruben Observatory will embark on the legacy survey of social. base in time, a 10-year survey of the night sky using the biggest camera ever made, capturing an ultra-wide, ultra-high-definition, time-lapse record of the universe,
Starting point is 00:23:01 which sounds incredible. And so tell me, help me understand the importance of this new observatory and what actually is. You know that previous story we were talking about? Yes. With 3-Eye Atlas. Yes. If Veri-Ruban Observatory had gone online a month before it did, it went online in July. If it went online in June, it would have found this object within three days.
Starting point is 00:23:32 That's important. Okay? That's what this observatory is doing. This observatory is American exceptionalism at its finest. Hurrah? It really is. Nice shirt. Nice jersey.
Starting point is 00:23:44 You see these four stars? Yeah. That means we're winners. How do we get the women's team? Okay, got it. All right. Well, hey, we'll take what we can get. We'll take what we can get.
Starting point is 00:23:58 Yeah, this observatory is, yeah, it's like one of the greatest observatories that mankind has ever built. It is very different from other observatories, very, very different in that traditional observatories. The whole point of the observatory is like the way it works is, you're an astronomer you got some idea for a bit of research that you want to do so you write to the observatory funders or like whoever's in charge of like allocating time and you say this is what I want to look at this is how many nights it's going to take this is why it's important for science research blah blah blah and then they get a bunch of proposals and then they allocate the yearly time budget to whatever you want to see this observatory has no such thing okay okay okay There's astronomers can't bid for time. And yet astronomers are super excited about it. Okay. This observatory's only job is to take a picture of the night sky, the entire night sky, every three nights.
Starting point is 00:24:59 And that's it. That's it. That's it. Like robotic clockwork. Okay. It's almost like just a robotic telescope. Yes. It takes a picture of the entire night sky every three nights.
Starting point is 00:25:12 Now, that is impossible with other telescopes. It's okay this thing had to be engineered Specifically for that test It seems like a brilliant use of time and money because you know the it creates this baseline data set That's very robust that creates a treasure map effectively Yeah for people to then say okay If I look at what's gonna come out of the Rubin Observatory you can get a baseline reference point and say hey this looks interesting over here.
Starting point is 00:25:47 Yeah. And then we can zoom in with other tools that are maybe more specialized for any number of different types of observations. Yeah. It's, and it's not just a baseline. It's like, it's actually going to find new things out of the box. Actively. So people can just look at it and be like, oh, that's new.
Starting point is 00:26:04 Yeah. And in fact, I mean, it's going to have so much data that, like, people can't afford to look at it. Right. There's just too much data. They're actually going to have artificial intelligence looking through and combing through the data. Okay, so let's get into it because there's, there's,
Starting point is 00:26:17 so much this thing started 15 years ago 15 to 20 years ago there's these things called decadal surveys in astrophysics okay so I mean you know people might think that like scientists are just like they just have like ideas and then the government's like oh okay here's like 400 million dollars right that's that's not how it works a bunch of scientists have to come together because this is a lot of money observatories are incredibly expensive right every little thing you're doing is that the cutting edge of science and technology. You're making the biggest camera. You're making the biggest lens. You're making the largest system for like distributing data and like finding stuff in data, right?
Starting point is 00:27:00 All of this stuff is at the cutting edge, right? It's going to employ like hundreds and hundreds of researchers, right? Sometimes thousands. So in order to justify this kind of spending, there has to be a consensus in the community to actually say, look, this is the total budget that NSF and the government are giving us. How are we going to make use of it with big projects? Because this stuff is big. Okay, this is hundreds of millions of dollars. And I want to make the note that I don't know if it's hundreds. I don't know how many million this is actually. This is also work that the private sector won't do. No. Why would that? Because there's no clear profit, you know, immediate profit value to investing that amount of capax no this one this particular one was really
Starting point is 00:27:47 nice because you know congress has a mandate that i think by 20 2030 they want to catalog all like 90 percent of all near earth objects that are bigger than 140 kilometers okay they want to just get a catalog of them all and NASA was like all right well if you want that we're going to need money to make an observatory exactly like this. This thing is going to catalog something like 65% of it. Okay. Okay. And what was funny about this particular project is in 2018,
Starting point is 00:28:24 Congress actually gave them more money than they asked for because they wanted it done faster. Yeah. But at that point, they weren't limited by money. They were just like, no, we got the best people here. Yeah. There's not anyone else who can do. what we're trying to do like like making a 32 gigapixel camera takes time grinding this lens takes time like you this is not a throw money at the problem kind of problem right this is now
Starting point is 00:28:53 we have the money but it requires time to get this right so that like when we see first light with the telescope it's going to be banger and it's so funny because it's the one time Congress was like at four scientists they were like you know what yeah here have more and and it's the one time that We were like, oh, I wish you. There's so many other. I think what's interesting about this is this idea, you know, how times change, right? You know, it's not a guarantee that the funding will always be there. And this is 2018.
Starting point is 00:29:23 So this is during the first Trump administration. Right. Right. So it's not like, you know, right. It's not a party type thing. It's just some, like sometimes we really like science. And then all of a sudden, I don't know, something happens. COVID in this case.
Starting point is 00:29:35 I will note that on the NSF.gov. website they mentioned the amount of data gathered by the Rubin Observatory in its first year alone will be greater than the data collected by all other optical observatories combined. Yeah. Which is a massive, massive amount of data. It goes on to say countless discoveries in improving our understanding of the nature of dark matter, dark energy, and other longstanding cosmic mystery yeah yeah yeah it's got it's got it's got four mandates okay the first thing is so okay first actually let's get into let's get into what this thing is
Starting point is 00:30:15 doing okay okay so this this Vera Rubin telescope it's it's an eight meter telescope okay it's it's not like the Keck or the James Webb where it's a bunch of segmented mirrors this is a single solid mirror wow on the bottom okay okay it was made in the University of Arizona okay the University of Arizona There's a lab there that is the world's best at making single big mirrors. Okay. Okay. And so when time came to make this, it's like, okay, we all know University of Arizona is going to do that.
Starting point is 00:30:48 That's your job. You do it. Okay. They made this massive mirror. This mirror is extremely wide, right? Eight meters. But it's also like the field of view of the camera, the way the mirror is shaped
Starting point is 00:31:06 means that the field of view is extremely large okay what does that mean that means like so most telescopes when they look at the night sky they're looking at a patch of the sky that's smaller than the full moon you're looking at a very narrow very yeah very like like you know you hold your thumb out and it's like that big and they're looking like that
Starting point is 00:31:22 okay so even sometimes smaller same thing with James Webb the Keck telescope in Hawaii Hubble same thing this thing is gonna move is gonna look at a spot in the sky that's like 45 full moons. Oh, wow. At the same time.
Starting point is 00:31:39 It's like a palm. It's like a palm. Okay. As big as a palm. Right. It's a thousand times the field of view of Hubble. Okay. Now, if I want to look at something really close for a really long time,
Starting point is 00:31:54 this isn't the thing to do it. But if I want to see the whole night sky in three nights, this is the thing to do it. What this thing is going to do is, 30 seconds, then it'll take five seconds to move, 30 seconds, then it'll take five seconds to move, 30 seconds, 5 seconds to move, 30 seconds, and it'll map out the entire night sky every three nights. So it's made, in all of the filters. It's making almost this giant, it's panorama is not the right word, but this giant mosaic of these 30 second snapshots that ultimately will create this sort of 3D. Yeah, it'll be like the, the Vegas sphere.
Starting point is 00:32:30 Yeah, yeah, yeah, yeah, yeah, yeah. But like every night. Every night. Okay. It's 60 petabytes of data over 10 years. I was literally going to say I don't envy the data. 60,000 terabytes of data. Like every night, it's going to be making like incredible, incredible discoveries
Starting point is 00:32:47 because it's observing the whole night sky. Which is something we've never done in this way before. Yeah, yeah, yeah. And each of these pictures is going to be 32 gigapixels. Right. So that's 32,000 megapixels in my palm, right? That I'm like with a, giant eight meter aperture right right the camera actually the camera was built by
Starting point is 00:33:08 Slack oh um Stanford linear accelerator lab different slack yeah yeah not not not not the not the not the not the works works not man oh yeah yeah yeah again the private sector isn't going to do this right but the government and slack slack slack is part of the DOE so slack made this camera the camera is like gonna fit in this room okay okay it's like as tall as you are you are I okay and it's like as as why you You can imagine. It's the world's largest camera. Yes.
Starting point is 00:33:36 32 gigapixels. Yes. Right. I mean, in 30 seconds, we want an exposure on this small patch of the sky. It's incredibly detailed, dude. You see like galaxies you've never seen before. In the first two days, it discovered like thousands of galaxies. Right?
Starting point is 00:33:54 In the first two days, it discovered 2,000 asteroids that we've never known existed. And it's like, wait, wait, wait, wait, wait. like yeah right those are asteroids like that could that could be bad right in the first two days two thousand asteroids that we should definitely know about and we don't there's a million known asteroids right now this thing is forecasted to get five million more more in the next 10 years so over the past 200 years we've observed a million right and now in the next 10 we're going to observe 5 million because of this thing because all it's doing is taking a picture of the entire night sky every night.
Starting point is 00:34:32 Yes. And then it's going to look for, it'll be super obvious. Right. When an asteroid moves, right? When a small point of light moves, we can literally track it over the whole year. This seems like a perfect use case for, you know, AI detection and anomaly detection algorithms because we have a decent amount of data to create sort of structured algorithms as a starting point that will identify things like asteroids, et cetera, et cetera.
Starting point is 00:35:00 And then we'll put the media buckets. And AI is really good at that kind of stuff, right? And anomaly detection is like huge. And so we'll have these buckets of stars, asteroids, galaxies. And then there'll be this fun other bucket where it'll just see. I mean, it's like putting on glasses when you're like really blind or turning on the lights further, further down into a room where it's like we've seen some stuff. Yeah. But we've not really seen at all.
Starting point is 00:35:25 And it is going to be an incredible. amount of the fidelity to me is what's crazy. Yeah, and the clarity of the images and the amount of light gathering power that we have here is going to be insane. Like the first thing that, like, there have been surveys in the past. Sure. Right. Like Harvard has like a Harvard plate archive, which is like back when they were photographic plates.
Starting point is 00:35:51 Yes. Palomar has one, Mount Palomar. You know about that one. Yes. And then the most famous one before this was the Sloan Digital Sky Survey. That was in New Mexico. And back then, like, you know, there's no, I mean, there's internet, but for this amount of data, there isn't. And so, like, dudes literally had, like, dude literally had to, like, fill up luggage with, like, the data and then bring it to the university, like, physically.
Starting point is 00:36:18 Right. Right. Now, this thing takes a photo within a few seconds. It's to California, to France. And then within another, within another, like, few seconds, it's going to be checked. across every other photo that we've taken of that spot in the sky because the telescope's tracking where it looked, right? And then maybe Hubble looked there, maybe VLT looked there like five years ago or 10 years ago. You check around there. And then if there's anything different, it's going to
Starting point is 00:36:42 flag and go across to all the astronomers everywhere being like, hey, there's something cool here. I want to be on that. And so like every, every like minute that it's observing, we're going to be seeing these things. And the cool thing about this is there's no embargo on the data. Okay, you know how I was saying about like the James Webb telescope? Yes. Three months, right? You get three months to massage your data, get your paper out. Here it's like it's out.
Starting point is 00:37:08 It's out like that night. It's not only a new technical innovation in and of itself. It's a first of its kind observatory, but also the workflow that is accompanying the observatory in terms of data access to a wide community of scientists is also fundamentally different. It's fundamentally different. And it's like it took like the software. the kind of software that was required to do this and the kind of electrical experience and all of that stuff, that could only happen in America.
Starting point is 00:37:39 Like the amount of cloud computing that is happening because of this thing is like something that it's actually being handled by Fermilab and the University of Illinois. Because like particle detectors, they have experience with like ridiculous amounts of data how to make sense of it. Yep. Right? This is a great problem that now they can solve. So the University of Illinois is actually in charge
Starting point is 00:38:04 of this whole data pipeline that's happening. And they're still massaging it out right now. Like the telescope is live, right. But like this is a part of the pipeline that they couldn't really test until they started getting the photos. It's still in beta. Yeah, like, everyone was focused on, okay, let's just get the photos.
Starting point is 00:38:20 Right, right, right. Now it's like, okay, how do we get the photos to everyone? Right. And it's slowly coming about. Now, you know, I said something about how, there's no embargo on this data. So the telescope takes a photo tonight, it's out. Now we have public access to this data
Starting point is 00:38:38 through the Verraubin website. There's actually like citizen science efforts going on because as you said, right, machine learning is gonna be really, really powerful for detecting anomalies and detecting new objects in this data. But what does machine learning need? Training data. Yeah, training data sets.
Starting point is 00:38:56 Training data. Yeah. And so how to how is the like all of the all of the training data like you know the LLMs. Yes. The training data is coming from humans writing on Reddit and all this other crap right? The internet right. The internet. Yeah, right.
Starting point is 00:39:09 So like there's all this text on the internet. That's your training data. But that text fundamentally had to come from human beings for it to learn how to speak like a human being and like language and logic and all that other stuff. Right. This we're going to have citizen scientists doing like training annotations. Yeah. Yeah. on the data.
Starting point is 00:39:28 So already something like 100,000 images, it's only been like less than a month. But already 100,000 images have been looked at and labeled for comets. Yep. Okay, because comets look a little bit different from asteroids. So there's a bunch of people on their, and you guys can like go and be a part of this effort. Right.
Starting point is 00:39:50 Like you basically identify, is it an asteroid, which is just a point like thing that is moving? Or does it have a little bit of. fuss around it. Right. Okay? And that's your job. We need more reinforcement learning from humans.
Starting point is 00:40:03 Yeah. And so I actually didn't know that. That's fascinating. Yeah. So these guys are just, this is just, yeah, classic data annotation. Yep. And then we can then train the machine learning algorithm and the AI for the future. Yes.
Starting point is 00:40:16 And then we won't need. We can have them like do other stuff. Like, okay, is this a spiral galaxy or an elliptical galaxy? You know, all sorts of stuff. This is, I think one of the things that's so. fascinating about that part of the story is it is this reminder we always talk about which is that science is for everybody right and it should be accessible for everybody so it's actually really heartening to hear yeah this one i really like that that like you know they got all this funding
Starting point is 00:40:41 from the american taxpayer but they're giving it back right not just to the american taxpayer but to the world right right kind of cool very i think i think i think it should make us very proud as americans that we are still at the forefront of astronomy yes you know ever since the 1920s yes Like, we built the biggest telescope in the 1920s, and we haven't stopped. Yeah, one day, the biggest, the best. Yeah, that, I think we really do understand that adjective. Biggest. It's like, okay.
Starting point is 00:41:08 Biggly. Yeah, we're going to make, we're going to make the biggest. Although we didn't understand that when we tried to build a superconducting super collider in Texas. We almost built it. And then. And then, no, and then we ran out of funding during the Clinton administration. When we had the crazy budget surplus. Yeah.
Starting point is 00:41:24 Interesting. Like Reagan actually like gave money for it. But that would be fine. That was during the Cold War. So maybe, you know, one can. But basically once the Cold War ended. Yeah. Even even the Democrats were like, oh, I guess we don't need science anymore.
Starting point is 00:41:42 You know, it's, it's so annoying. It's unbelievable. Like now there's just a giant tunnel underground in Texas. There's a giant tunnel with graffiti and stuff. Don't tell Elon. We board a tunnel. But we just didn't. put the detectors in because like we ran out of money it's this it's it would have been bigger than
Starting point is 00:41:59 cern you understand yeah it would have dude we would have found the higgs like 20 years ago or something this is why we need to fund it's incredible and like it would have it would have been a larger search search space like we would have answered questions about super symmetry the fact that it doesn't like isn't there in these like we would have answered all that because the luminosity for that texas superconducting super collider was higher than CERN's is right now. Which when it's been ran up. Like when we do stuff, we plan to like it was going to be bright and it was going to be big. Big.
Starting point is 00:42:32 And then and then and then money ran out and then we didn't give the money. And then that's when I think we learned our lesson. And that's when NSF was like, no, we're going to do with whatever limited budget we have, we're going to take big risks and get big rewards. And that's when LIGO sort of got into mix. And that's when people started asking. can we make this gravitational observatory? Right, well, this is the gravitational wave.
Starting point is 00:42:56 Yes. And then finally, LIGO got, LIGO got funding. Like, I think it was sort of a backlash from like that failure. Right. That we had, which was American scientists.
Starting point is 00:43:05 Right. Yeah, we were just like, ah, like we really dropped. And like now, you know, at CERN,
Starting point is 00:43:10 we're kind of like second class citizens. Right. Because to be like part of the fold, you have to contribute something like 1% of your GDP, which is fine for something like the Netherlands. Right, right. But like, the U.S. is all of Europe plus more. It's like you want one percent of our GDP.
Starting point is 00:43:26 No. You know? But it's like, but they need our magnets. Like CERN couldn't work without our magnets. And like a lot of the tech and a lot of the like big electronics was coming from America. So yeah, I think that we didn't, we didn't really like that. And then like we made LIGO. I love that in astronomy we're still like at the forefront.
Starting point is 00:43:46 Like we're making James Webb. We made Vera Rubin. Yep. The Keck telescopes. in Hawaii, like, we're still going at it. There's a new one that's like planned. It's called the Nancy Grace Roman Telescope. That's going to be in space.
Starting point is 00:44:03 It's going to be very similar to the Veraruban telescope because it's going to have a really big field of view. But unfortunately, I think that one has been put on pause because it hasn't been launched yet. Right. And the funding is stopped. So that's something that like we clearly should like really like you know invest in yeah oh you're looking at the photos i want i want people
Starting point is 00:44:27 to understand and we'll look at look at like all of those dots like like all of those dots are previously unknown galaxies it is incredible and it's it's what you can see that's a single like that's that's a single night and the it's basically this map view uh with part of it filled in from where the photos have been taken and it's just going to continue to expand and expand over time. Yeah. And you can just zoom in and it's pixelated for a little bit and then it gets high for and you just keep zooming in. Yeah. And then finally you get to the signal, the noise of the detector. Right. Yeah. But I mean, there is an incredible amount. There are already like go up objects in this in this view. Yeah. Like you see some of these like diffuse galaxies here. Yes. Yes.
Starting point is 00:45:09 Those like were so diffuse that they weren't even caught in the Sloan Digital Sky Survey. Right. Right. But that's like a, the, some of those are totally new galaxies. are pretty close to us that we just didn't even see because like they were they were just sort of like blobs of like you know particulate stars yes with no real structure so they weren't bright enough but now this thing this thing is incredible and the thing is it's going to take pictures of the same spot in the sky right right at the end of the day it's over 10 years right you can start average not even looking at the movie aspect of this right like the the time lapse aspect of it you can start averaging the same spot yep
Starting point is 00:45:46 right and then get insane signaled annoying Right. Right. And then start seeing really faint stuff. Yep. Right? Yep. And so, and this, this is, it's only been a month. And already we have like thousands of new asteroids. You said this place was steps from the water. We just haven't found the steps yet. How much did we save? Enough.
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Starting point is 00:46:50 Don't just dream about the trip. Book it with Priceline. Download the Priceline app or visit Priceline.com. Actual prices may vary, limited time offer. Thousands of new galaxies. This is incredible. I mean, this imagery is unbelievable. It's unbelievable and the amount that we're getting.
Starting point is 00:47:09 The sheer amount, like, you know, it's doing a whole night sky. And then the other thing we got to remember is, like, you know let's say the sun is here yeah yeah let's say the sun is here and the earth is over here yeah okay it's in the southern hemisphere yes so it's only going to be able to see like this part of the sky this in one night right and then as the earth rotates it's going to basically see all of this all of this down here so there's going to be parts like near the equator that we're going to have like a movie for like we're going to have all the photos for five months and then we're not because it's going to be on the wrong side and then it'll be back so then like you know
Starting point is 00:47:47 we'll see like but then there's parts near the the south pole that are just always going to be visible so we'll just have like a 10 year full on movie time lapse of the universe of like the universe in this in this like down here right because it'll always be night time down there right right and so that'll be really cool that's going to I mean the image like even already yeah it this is gonna be it's going to be so awesome this is incredible I want to end the story with this little bio snippet that the NSF put out on who was Verar Rubin. The Rubin Observatory is named in honor of Verar Rubin, a pioneering American astronomer whose observations provided convincing evidence of dark matter.
Starting point is 00:48:31 An invisible substance that makes up over 80% of all the matter in the universe. Rubin's work in the 1970s showed that galaxies were rotating too fast to be held together by visible matter alone, suggesting the presence of an unresolved. unseen mass. Yeah. Her discovery reshaped our understanding of the universe. Dark matter is unlike any known type of matter, and its true nature remains one of the greatest mysteries in science today,
Starting point is 00:49:00 inspiring generations of researchers and science lovers, and one of the greatest observatories that humanity has ever created to date. And so in honor of Vera Rubin, a woman in science. Yeah, she was snubed for the Nobel Prize. which is she should have gotten the Nobel Prize that it's an incredible discovery she did these uh what they're referring to is galaxy rotation curves okay okay it was the first sort of real inkling that okay there's something real wrong like where where is everything where why can't we see it basically what she it's a very simple very simple observation okay that she was making which is that like
Starting point is 00:49:38 stars that are like farther away from the galaxy center should be moving slower right jupiter moves way slower than Earth. Mercury moves really fast around the sun because the closer you are, the stronger the gravity and so the stronger the acceleration, which means you're going to move faster. Okay, fine. What she noticed was the galaxy rotation curves instead of doing this, instead of trailing off as you go farther up, they remain constant. So what does that mean? It means one of two things. Either Einstein is wrong, unlikely. Or there's a bunch of mass there that is contributing to this gravitational pull that we're not seeing. Right.
Starting point is 00:50:17 Okay? Right. And that's where sort of the dark matter debate started. Got it. Is it dark matter or is Einstein wrong? The Vera Rubin Observatory, which is named after her, one of the key like pillars of its creation is this idea of answering that question. Okay. It's like it's, you know, I mean, you saw those photos, right?
Starting point is 00:50:37 Galaxies upon galaxies of stuff. What it's going to be able to do is map out the entire universe. from extremely large distances. Yes. And what we're looking for is structure, large-scale structure. What that means is like, so it turns out the universe is not like completely isotropic in that it's not completely the same everywhere. Right.
Starting point is 00:51:01 There's clumps of stuff. There's clumps of galaxies. And then there's giant voids that are like millions of galaxies big where there's nothing. Okay? not you know you know what I mean low density high density yes and so if we can map out that structure yes of like where the high density is that's you that's where the dark matter is and where the low density is then we can start figuring out how much dark matter there is yes and how that dark matter evolved from the beginning
Starting point is 00:51:31 of evolution we can start making model not evolution from the beginning of the Big Bank from the evolution of the universe from the Big Bang until now like how that dark matter evolved how it shape the creation of this large structure. Yes. And all this other kind of stuff, right? That's one of the things it's doing. The other thing is doing is because it's like just going through galaxy after galaxy,
Starting point is 00:51:51 it's going to catch a lot of gravitational lensing, right? It's going to catch these like instances where the light is bending. Yes. Because of the mass in front of it. Yes. And then once we have that, we can have a better estimate on how much mass there is. Right. To bend that light.
Starting point is 00:52:04 And then we can start discovering things about dark matter. The more data that we get, the more closely we can start scrutinize. stuff like Einstein's general activity, which we sort of take for granted. But, you know, we'd need something like thousands of galaxies. I think it might honestly be somebody did the calculation. It's like on the order of millions of galaxies worth of data. Right. To really start honing in on this question.
Starting point is 00:52:29 And Vera Rubin, given that it's doing this, it's going to be able to do that. Yes. Yeah. It's going to be awesome. Unbelievable. I we're gonna come back to this oh yeah this thing is gonna be in in our zeit guys for the next 10 years right it's gonna be finding crazy stuff like yeah it's gonna be insane like ice cube and LIGO we've talked about ice Cuban LIGO on this podcast before um the only time like Vera Rubin is it's it's on a mandate right it's doing this that's it that's it's not gonna you got something nice to see go look somewhere else except for when ice cube or LIGO see something crazy. Okay.
Starting point is 00:53:10 If they see something crazy and Ice Cube is like, yo, there was a massive neutrina that just came out of there. Yeah. Yeah. Then Vera Rubin's going to be like, I'll take a break. Point it there. And because of Vera Rubin's like big field of view, because like when stuff comes into ice cube, we kind of generally know the direction it came from.
Starting point is 00:53:32 But it's not like other things where it's like, oh, you got to go to that star, look a little bit left, look a little bit down, you're good to go. No. So Vera Rubin's got this giant field of view. It can just point and like start perusing that path of the sky waiting for the signal. It doesn't have to be super specific. It can have a general region of the sky to look at. And because it's so high fidelity, it's going to just get everything both where those neutrinos are coming from. Yeah. And it might see like and it'll have. So the neutrino probably came from like a massive supernova or like like some giant you know quasar bursting or something like that this thing can look and it'll have the image from the previous night right so it'll
Starting point is 00:54:15 just compare immediately be like oh that's different right right right right ah yeah and then it could tell all the other observatories yo look over there yep because it'll actually get the court like it'll have yeah basically the direction of like oh yeah we have all this historical data from the Rubin Observatory, ice cube told us to look, something is different, and the different thing is right there. Yeah, yeah.
Starting point is 00:54:37 Like if we get, if neutron stars create gravitational waves, LIGO is going to find out. LIGO and Cagra and Virgo, but, you know, their resolution is also based on like, whether the gravitational wave hit this thing first before this thing,
Starting point is 00:54:52 right? Their only resolution of direction is like the timing difference between the two. Between the two. And so, and so they're just like, it's in this general,
Starting point is 00:55:00 direction, Vera Rubin can go and be like, okay, let's find it. Like this is, this, it's a long time coming. That's what I was saying. Like in the decadal survey, like 15 years ago, the astronomers came together and we're like, we need something like a large survey telescope. Yes. Whose only job is to survey the night sky because we're tired of living in still pictures. Right. We want to, we want to upgrade to movies. Right. Now. Right. Right. And so we need one telescope that does exactly that. That's actually a great analogy. We're moving from photography to videography in space.
Starting point is 00:55:33 It's a loose analogy. No, no, I mean, and so actually, it was, at first it was called a large synoptic survey telescope. Lame.
Starting point is 00:55:43 And then, and then they renamed the observatory, Vera Rubin Observatory. And then the program now, they kept the LSST. And they called it now the legacy survey of space and time, which is, That's that that is I love that shout out the acronym creators yeah yeah they love their acronym so much they kept it but they just like upgraded like what it stood for it's a great it's a great story I mean I'm so glad this thing is up you can go see it it's it's up and running yeah like you can go right now to NSF.gov and look at the Rubin observatory page and literally see the the field of view explorer of right now they have their first look first images on there from January 23rd one
Starting point is 00:56:27 day I can't you guys have to go look at this the amount of stuff yeah that it captured in one day is crazy and it's the first time the humans have ever seen that it's crazy a lot of that stuff right there's also another spot I don't know if you can find it but like there's an asteroid like explorer where they map out like all the asteroids that Vera Rubin has seen that's incredible and and and so you can just go look I mean it's it's really awesome like it's these are your taxpayer dollars at work You know it'll be.
Starting point is 00:56:57 And it's, it's an incredible gift. It is. I can't wait for, there's this, um, there's this game, video game.
Starting point is 00:57:05 I think it's called Star Citizen. Um, that is a procedurally generated universe, but it's like highly, you know, Oh, dude, I think I've heard about this.
Starting point is 00:57:13 Yeah. It's super high fidelity and like you travel at real space time. Like, you know, real, it's, uh, equivalent to like the actual traveling distances and stuff like that.
Starting point is 00:57:23 Modified a little bit. But what, what I would love to eventually see is someone take this and then replicate an explorable 3D environment. Yeah. With this as the backing data that powers. Yeah, because now we will have five million asteroids. Right.
Starting point is 00:57:37 Right. And they'll be cool to sort of anyway. And they'll be like real. Right. Right. You know, with names and shit. Oh, God. I want to name one.
Starting point is 00:57:44 Let's name one the Krishna Lester asteroid. Yeah, the first principles. The first. FPPA. An amazing story about the brilliance again. A little American exception. in there will give the we'll give the old badge
Starting point is 00:58:00 of this kiss. No, we deserve it. That's dope. This is a good one. This is a good one. We're going to go again like we normally do or regularly end up doing from very, very large and very, very far to very, very, very small and very, very close. Very, very small now, yep. With our next story out of the University of Zurich, which is headlined,
Starting point is 00:58:21 AI meets CRISPR for precise gene editing. And the byline is a research team headed by the University of Zurich has developed a powerful new method to precisely edit DNA by combining cutting-edge genetic engineering with artificial intelligence. And the paper was recently published in Nature Biotechnology. Yeah. So we've talked about CRISPR before. I think most viewers who have come across this video will be relatively familiar with what CRISPR is. So maybe we won't do a deep dive on the basics. But we can touch on what is the insider improvement here that has allowed them to increase that precision of what has been a revolutionary discovery with the underlying CRISPR sort of work that has already been done.
Starting point is 00:59:11 Yes. Yeah. So CRISPR, it's kind of an old technology now. Right. Oh, it's almost 10 years old. And, and, okay, CRISPR, okay? You guys happy? You know, you know, it's a, like, I've been getting all the shit.
Starting point is 00:59:24 That's true. From these TikTok comments. It is spelled, you know, with, it was Chris dash, all right. It's an acronym. Yeah, it's an acronym. It's an acronym that stands for clustered, regularly interspaced, short palindromic repeats. It's not a real word. I can say it however I want.
Starting point is 00:59:41 But I'm going to say, I'm going to say CRISPR now. I got bullied into it. The peer pressure work. Yeah, the peer pressure works, dude. So CRISPR, it's pretty old technology now, almost 10 years old, maybe a little bit more. Basic idea, you get to cut DNA wherever you want in the spot that you want. Before, you could only cut DNA if you looked at certain base pairs and then recognize those with restriction enzymes. Now you've got a custom restriction enzyme that you can be like, okay, I want you to look for ATCGGA,
Starting point is 01:00:15 and then wherever that is, find it and cut it. That's what CRISPR can do. CRISPR only cuts. and once it's cuts, other stuff comes in to repair. Okay? And so far it's just been a sort of cut and hope. Okay?
Starting point is 01:00:34 You cut it at the spot and you hope that whatever machinery is in the cell already is going to come and repair this DNA. And there's not going to be anything weird that happens. Of course, that's not always going to be the case. Of course, you're going to get lucky. Most of the time you're going to get lucky if it's a healthy cell.
Starting point is 01:00:52 But in certain situations, it's not going to go well. There's going to be these repair mechanisms. What they're going to do is sometimes delete a nucleotide or two, and then your whole gene is completely wrecked. You might be working with something called like non-proliferating cells, so cells that don't actually cell divide. Like your neurons. Skin cells, cell divide.
Starting point is 01:01:19 Most of the cells in your body, muscle cells obvious. cell divide, your neurons do not cell divide. So they don't have half the machinery necessary for DNA repair that a dividing cell would have. Dividing cells, they're constantly like replicating DNA, checking to make sure the DNA is correct and all this stuff. But in your neurons, it's like you don't need that. This neuron is going to live until you die. And it's not going to make any more.
Starting point is 01:01:43 So for those cells, if we want to use CRISPR and these new genetic technologies, we're going to need a more robust way to control for the repair after the cut the cut no more cut and hope yeah no more cut and hope we want to cut and then engineer right right the cutting was an engineer before it was like the cutting was a hope too and then we upgraded it's like okay now we can engineer the cut now this is the this is like sort of going towards engineering the repair okay they made this AI called pythea okay i hope i'm pronouncing that right okay whatever it's it's um it's named after the oracle at the temple of apollo and delphi yep you know um have you seen 300 yes remember when he goes to the oracle and he's like he's like
Starting point is 01:02:31 should i should i should i go to war and then like he's like now you're gonna lose or something like that but turns out he was bribed by the persians right anyways the oracle of delphi is supposed to tell the future okay and predict the future so this thing is predicting how the repair is going to go Ah, okay? Because the repair mechanisms in cells is extremely complicated, but at the end of the day, there is a hidden pattern. Right. Okay? And that's what AI is all about. Like we just talked about. Yes, it's got to be a complicated set of data, but there has to be some hidden pattern, and AI is really good at picking out those, those hidden patterns. The pattern could be based on the cellular environment. It could be based on like where along the genome that this cut is, that we need this cut to happen. Or like how the chromatin, which is like the proteins that wrap the DNA around,
Starting point is 01:03:28 how that stuff works, right? So all of those things are what go into this AI. And what comes out is a way to predict how the repair is going to go, where we should even do the cut so that the repair is best, right? And like minimal amount of work. And the other cool thing is they've made this kind of like,
Starting point is 01:03:49 glue, this repair glue. What it does is it's it's a custom piece of DNA that guides the cells DNA repair mechanisms to come and do it right. So we're not just like hoping. It's not hoping. Right. It's now it's like it's like nope, it's over here. It's like a runway. Right. For the the enzymes to like come in and be like, oh, okay, cool. I'm going to I'm going to do this repair over here. It's it's it's going to be really nice. There's going to be no more scars. That's what we call them. Like when when when, when Christopher like makes a cut and then like some random crap happens it's called a scar in your gene and it's it's not a good thing right it'll it might even kill the the whole project itself this makes me
Starting point is 01:04:31 think of the scene and foundation if there's any foundation fans out there the apple tv show that's a yeah isaac azamov books um there's a there's spoiler alert uh the one of the people that serves the main, you know, royal family is this, like, sentient robot. And anytime she gets injured, it's just the healing kind of happens in real time. And just the visual of that makes me think of this, this kind of, this new glue, the ability to basically control the healing process. Yeah, at a molecular level. At a molecular level, which is incredible. Yeah. In its own right, and it's on right. And so we're sort of expanding the toolkit for gene editing to not just be able to,
Starting point is 01:05:20 we kind of, we have the map of the, like we know what different aspects of our DNA do. So we can be like, oh, like if we were to cut here, certain outcomes are going to happen. We then created the tool to do the cut. And now we are beginning to develop a sort of planning tool with the AI system that helps us simulate what are the outcomes going to be to a cut and how the body will respond as one aspect. But as the second aspect, we've also created some helpers
Starting point is 01:05:50 to guide that process in addition to being able to sort of look at how that process is going to transpire. So it's not only a planning benefit, but there's also an execution. Yeah, there's a part of this that is execution itself at the molecular level. Which is, and so now when you can cut and heal
Starting point is 01:06:09 and have some level of efficacy, In the entire top-down process. In the entire top-down process from identification to extraction to repair, obviously, my mind goes to the implications. You can now have more consistency in expected outcome to changes made by CRISPR. That's exactly the point, yeah. Which obviously makes it more viable as a therapeutic tool or whatever you want to call it, for any number of reason. Yeah.
Starting point is 01:06:42 Now we can, now we can actually start, like, really targeting and in a safe way. Right. Right. It wasn't safe before. CRISPR, it's, I mean,
Starting point is 01:06:53 it's, it obviously has its applications, but if we want to go into, like, real clinical therapies, right, where we're, we're starting to, like, now go into trials,
Starting point is 01:07:02 like human trials and things like that, we needed this kind of mechanism. Yes. That would control for the aftermath of that DNA. cut right right right right because you know biology if you just do one part it's biology is a nested somebody somebody in molecular biology once told me biology is nested four loops and if statements okay and you don't know where there's a random break yeah that's just written that'll just like crash your whole program right right and so you need to be extremely careful when you start
Starting point is 01:07:34 editing this program right right make sure you like don't get to that break point right right Right. And so this is extremely important for that reason. It's it's it's paving the way to these targeted gene therapies. Yes. It's paving the way for clinical application. We need it to be safe. And this is this is definitely like on the road to that, right? At least in the US. We can't speak for other massive nation states in their perspective on where the ethical line is. Yeah. Yeah. Yeah. But here in the US, in this country where we make big,
Starting point is 01:08:13 beautiful stuff. Yeah. Although this was in Zurich, but whatever. We're going to, we're going to, we're good at borrowing. And we'll make it better. But this is, I think, a really important story, though, because
Starting point is 01:08:26 science always feels to me like, you know, you're sort of, it's, you're playing with God, right? Like, like, you're starting, we're starting to get to a place where we're sufficiently advanced in what we can, in what we can manipulate and what we can engineer.
Starting point is 01:08:40 Yeah, it's getting insane. We're getting into weird, into sort of weird territory. Because again, it's, it's the tool scales. Like once it exists and it gets to that level of efficiency and efficacy, it can be applied to a number of different use cases. This is not like just for X or Y. It's like it is a fundamental concept.
Starting point is 01:09:04 Yeah. Actually, on that note, on that note, one of the, so they tested it on three working. models. Human cell cultures. It worked. So this is in the Petri dish. We grow human cells. On the tropical frog, which is a model organism, I think it's called Xenopus. Yeah, it's the Xenopus frog. It's a model organism that's used for generational studies. Yep. Okay. So they messed around with the DNA here and then the kids and it was passed down and it was like, okay, everything's good there. Yep.
Starting point is 01:09:37 And then so it's called germline studies. Yes. And then it also worked on non-dividing adult mouse neurons from the brain, which is this thing where like, you know, these cells don't have that. Right. As robust of a DNA repair mechanism. Yes. As cells that do divide and we'll need that on a day to day. And it worked in those cells as well.
Starting point is 01:09:59 So now you can start targeting therapies like in neurodegenerative diseases, right? Which would be an unbelievable. That would be unbelievable. It would be unbelievable. Yeah. Like this is this. That's actually a really important small note. Yeah.
Starting point is 01:10:13 That it does work on those non-dividing neural cells. Yeah. Like this sort of like guide, this, this, you know, scar edit that it does worth like guiding whatever the DNA repair mechanism. Because there's some, obviously. Every cell has some. Just not as robust. Yes.
Starting point is 01:10:28 But like with this guide, even that can now, can now, can now do the work. That is fascinating. Yeah. Really, really important story out of being... Just came out. Jessica, this is, we're looking at August 12th. Literally, I mean, today. Today.
Starting point is 01:10:46 It came out today. Came out today. An unbelievable story that's going to have major implications. It's funny. Biotech continues to be super fascinating to me. And while Jurassic Park did involve manipulating, amphibian DNA in order to bring back
Starting point is 01:11:09 the dinosaurs. Our final story of the day is not quite as salacious, but interesting nonetheless. I think it's cute. And the story headline here is rare T-Rex blood cells found in fossils show how dinosaurs healed injuries. The byline.
Starting point is 01:11:28 Blood vessel structures found preserved in a famous T-Rex fossil are helping scientists understand how dinosaurs healed from injuries. So there's no engine involved. There's no Isla Sorna, Isla Nublar. No.
Starting point is 01:11:45 We're not sending mercenary. There's not even any dinosaur DNA. No dinosaur DNA. This is blood vessels. Yeah. And so help me understand. It looks like this study was published in scientific reports from this well-known T-Rex that was unearthed in Saskatchewan, Canada in the 1990.
Starting point is 01:12:05 Yes. I like this story because I really like dinosaurs. One, I really like dinosaurs and I really like physics, particle physics. And this is a combination of dinosaurs and particle physics. I'll take it. Okay. I was like, whoa, what? Okay, let's start with a dinosaur. Yes. Okay, his name is Scotty. He's the largest T-Rex ever found. He was found in Saskatchewan, Canada in the 1990s.
Starting point is 01:12:33 He's named Scotty because once they found him, the paleontologists opened a bottle of scotch to celebrate that they'd found this T-Rex. I thought they were going to name Scotty because he doesn't know. Don't tell him. He probably died 66 million years ago. So just before the Great Mass Extinction, late Cretaceous era, he was probably about 20,000 pounds, lived until his 30s, which is pretty old for a T-Rex. This guy had a crazy life back 65 million years ago. 66 million years ago. There's like all of his bones have like scar tissue,
Starting point is 01:13:12 which means he got in a lot of fights. Yeah, yeah. He was pretty big. So, you know, it's probably like one of the alphas. Yep. A lot of injuries. In 2019, they were doing scans of his bones. And they found an anomaly in his ribs.
Starting point is 01:13:27 Okay. Okay. Where it seemed that something like angiogenesis had happened. Do you know what angiogenesis is? I do not. It's basically the formation of new blood vessels during healing. So if we break a bone or something like that and we're like trying to heal, new blood vessels will form in that spot to bring the repair mechanisms to that spot to create new bone and things like that. So it seems that like in this part of the ribs, maybe fractured a rib and then it healed.
Starting point is 01:13:54 And there was scar tissue from new blood vessels forming within that rib. And that's very interesting Because in the fossil record, it's incredibly difficult to preserve soft tissue Right. Okay? Like the stuff that gets preserved are like shells, teeth, and bone. Why? Because they have like these like higher elements, right?
Starting point is 01:14:18 They've got like calcium basically. And calcium is easy to preserve because it doesn't really decompose. The calcium just sort of stays there. And it becomes part of the. fossil and then that's it. With soft tissue, you can have like bacteria, fungus, whatnot, eating you up. Yep. And so you're not going to get it. But this was, this was blood, blood vessels. And because the blood vessels have a high bit of iron, there's a chance that this got preserved because of that iron. Oh, because the high level of iron in there. Now the question is, why,
Starting point is 01:14:55 why haven't we seen this kind of stuff before? Well, it was sort of just a sort of, assumed that blood vessels would not be preserved because they were soft tissue. But this is sort of an encased inside of a bone, right? So it's this rare glimpse into the vasculature of a T-Rex, which I think is like incredible. Okay. So now the question is this stuff is inside bone. How do we get to it? This is where the particle physics comes in.
Starting point is 01:15:21 Okay. So this group at the University of Regina in Canada, they used particle physics to look inside the bone and identify the blood vessels, identify the kinds of compounds in the fossil. It was through particle physics. It's incredible. So they, I mean, basically what they want to do is they want to x-ray this thing. But you can't use like lab grade x-rays because x-rays are too dim and this fossil is huge. Yeah, yeah, yeah, okay? It's not going to like go through that bone. So what they did was they got a synchrotron from the Canada light source, also. one says sketch one that synchrotron is used for like all sorts of stuff like you know if you want to send
Starting point is 01:16:03 if you want to send like electronics into space you want to see that it can handle space weather yeah like space radiation so you stick it in there you blow it up and then see if the electronic glass so i don't know i don't know what it must have looked been like when they got a email from like the museum being like we want to we want to put a t-rex bone and they're like what do you what are you talking about Yeah, they got this synchrotron. A synchrotron is basically, it's like a way to accelerate electrons really fast, round and around in a circle, extremely fast with magnets, alternating magnets. And then what you do is when the electron accelerates because of electromagnetism,
Starting point is 01:16:47 there's a charged particle accelerating. It's going to give off radiation. Yep. And that radiation is in the x-ray. It can actually be in very broad range, but you can tune it extremely, precisely by tuning the way in which these electrons, the speed and the curvature of the path of the electrons. Yep. Right. So this particle detector is really nice because you get like sort of monochromatic x-rays.
Starting point is 01:17:14 Mono, like the same color in some sense, right? It's the same frequency of light, and it's an incredibly powerful beam. So the first thing they did was they just put it there. They x-ray it. Then you rotate the fossil x-rayed again, rotate the fossil x-rayed again. You get 2D projections each time. And then with a sophisticated computer algorithm, you put it together and you can reconstruct the 3D structure.
Starting point is 01:17:37 And you can see inside because this x-ray beam is so powerful that you can actually see inside. And you can actually start like looking at T-Rex blood vessels, which is pretty cool. Very cool. Like we're seeing blood vessels from an engineering that happened 66 million years ago using like electrons and x-rays. I mean, it's clever.
Starting point is 01:17:57 It's a great story. Yeah, no. Very, very clever. Yeah. Dr. Hammond, the founder and creator of Jurassic Park, would be very proud. You'd be very proud, yeah, yeah. It'd be like, this is good old-fashioned science, you know? And the other thing that they can do is they can use the x-rays to talk about, like, x-ray fluorescence
Starting point is 01:18:18 and get into, like, what are the compounds that are in there? Okay. Okay, because what you can do is you can tune an x-ray to, like, start kicking out whatever. like let's say there's like some atoms in there like heavy atoms you can kick out an electron it's in its lower shell and then now you've created a hole in its lower shell in order to fill that the atom borrows an electron from the very top and sticks it in there now that's going to release an x-ray and the the the the frequency of that x-ray is going to tell you what kind of element did that right and then from that you can tell the ratios of the elements right and from that you can then tell
Starting point is 01:18:55 stuff about the fossilization process of how exactly this thing got preserved because if we can tell that then when we find new dinosaur bones right we can like be more careful about like not just like manhandling it in some way that like destroys this kind of evidence that we could be looking for later yes yes this is so there's almost this bumper cars thing where by shooting the x-rays in we dislodge an electron and we use that detection of that dislodge of electron to understand the underlying chemical composition that makes up what's in what's in the blood vessels which i'm assuming is how we understood that it's had high iron yeah yeah and it had a high iron we also detected calcium we detected iron and manganese in the blood vessels um like just
Starting point is 01:19:46 really really cool stuff like stuff that we could never have done without this marriage of particle physics and paleontology. I was going to say this is kind of like a crossover episode. Yeah. Because I imagine it's not necessarily super frequent that we are utilizing this methodology. No, but now it certainly is going to be used a lot more, you know? And so I think it's a really cool story about how we can take techniques that we use for one thing and then in a completely random scenario, you know, discover stuff about dinosaurs. Who said science wasn't created? Yeah. Yeah. I thought that was really cool. This is a really, I, as you know, a huge Jurassic Park fan.
Starting point is 01:20:25 The new one was Scarlett Johansson and Marashaw. I haven't watched it. I probably will. It was, I saw it in theaters. I love Jurassic Park. It was okay. Yeah. It was okay.
Starting point is 01:20:36 The family was a little annoying. But I love the original Jurassic Parks. The new ones have just. The original is classic. I think Lost World is underrated. That's the second one, right? That's an amazing one. I think that one's underrated.
Starting point is 01:20:48 but fascinating story. And we're going to wrap up here with a special little mystery box, which means that one of us doesn't know what the story is. And this is not really a story, it's just a headline. Okay. And I'm bringing this up because of our initial first story around 3i Atlas, the third interstellar object we've detected. And I thought this was hilarious because I saw this come up on my TikTok
Starting point is 01:21:16 as people making memes about it. And I didn't really understand what was going on. And so the headline of this story is NASA scientist says he saw seven foot tall black skin-raced aliens that looked like African-Americans stepping out of a mile-long ship. So the byline, a former NASA scientist is making explosive claims about an alien encounter at an Air Force base. He describes a mile-long ship landing and hundreds of beings getting off
Starting point is 01:21:51 who were a black race looked like African Americans. African Americans. There's my African American. He's on a ship. He came from outer space. And we're around seven feet tall. He said they had an arrogant look
Starting point is 01:22:10 of conquerors that had never been conquered. Oh, my God. So the only reason the reason I brought this up is the memes are fantastic. I got to see these memes. You got to forward them. So it's, you're now basically having a bunch of black people like you, right?
Starting point is 01:22:26 Acting as if the, the African American aliens are landing and they're usually playing loud music. The sub is just going crazy. The guy to repair shop like me, like, come here, come here, you just hear this booming subwoofer music in the background. It's not a real story. That's so funny.
Starting point is 01:22:43 It's the memes are fantastic. Please keep them coming if you see any of them and you want to send them to me send them to me It makes me laugh every time Obviously This is not an official NASA position No of course not so NASA did not say it was white people though they'd be like oh maybe The joke is this is why we can't get disclosure about UFO Yeah, it's because all the aliens are black
Starting point is 01:23:09 All the aliens are black So look everybody we can't get disclosure the aliens are black I hate to break it to you. This, another fantastic episode, Interstellar objects, the Veraruban Observatory, another follow-up on CRISPR, which continues to just have updates constantly,
Starting point is 01:23:29 and a little fun with our T-Rex blood vessels and the intersection of paleontology and particle physics. Yep. With this, we will end another fantastic episode of From First Principles, I am your host, Lester Nare, joined again, as always, by my co-host, fellow Princeton Tiger, and our resident PhD, Krishna Chowdry. We'll see you guys next week. All.
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