Latest / From First Principles / New Supernova, Virus+Bacteria vs Cancer, Electron Spin, Bee Superfood (EP. 6)

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New Supernova, Virus+Bacteria vs Cancer, Electron Spin, Bee Superfood (EP. 6) · From First Principles

• 0:00
  Hello Internet, this is your captain speaking, Lester Nare, joined as always by my co-host and our resident PhD, Krishna Chowdhury.
• 0:08
  This is from First Principles.
• 0:11
  We have a great episode this week.
• 0:12
  We're going to cover four new breaking research science stories, starting off with...
• 0:17
  Move over Taylor Swift tour tickets because this cosmic event just sold out the night sky as scientists just caught a brand new supernova in action.
• 0:28
  Followed up by, unlike Ryan Reynolds and Robert Downey Jr. on set of the new Avengers movie, who can't stop fighting, viruses and bacteria apparently are teaming up to battle cancer.
• 0:40
  This is an interesting one.
• 0:42
  Our third story, politicians keep spinning the news, as we know, but scientists have figured out how to spin electrons, and it could power the next generation of tech.
• 0:53
  And we will end our story with forgetting about billionaires and the race to Mars because the real heroes are scientists who are racing to save the bees because no bees means no breakfast.
• 1:06
  Let's get after it.
• 1:07
  This is From First Principles.
• 1:24
  Hello, my friend.
• 1:25
  How are you?
• 1:25
  Pretty good.
• 1:26
  Pretty good.
• 1:27
  We are back for episode six.
• 1:30
  Yeah.
• 1:31
  Still here.
• 1:32
  Yep.
• 1:32
  Still cooking.
• 1:33
  Still going.
• 1:34
  Still cooking.
• 1:35
  And we have a couple of interesting stories.
• 1:37
  We'll dive into the first story here, which I made a Taylor Swift reference.
• 1:42
  Mm-hmm.
• 1:44
  I think this is going to sell more tickets.
• 1:46
  It's definitely going to sell more tickets.
• 1:48
  And this... Across the universe.
• 1:50
  Across the universe.
• 1:52
  Headline from CNN, new type of supernova looks like nothing anyone has seen before.
• 1:59
  Yeah.
• 1:59
  Astronomer says.
• 2:00
  Yeah, it's pretty insane.
• 2:03
  It's an unprecedented discovery.
• 2:05
  It's a new type of supernova that's super rare.
• 2:08
  I'd like to call it a naked supernova because we're seeing the guts of a star before it explodes.
• 2:13
  It tells us everything about how supernovas...
• 2:17
  and also like how we form, you know, the atoms that make us up.
• 2:22
  This is pretty cool.
• 2:23
  We're gonna rate this episode MA because we're talking about naked supernovas.
• 2:28
  The byline on this CNN article, again, the story is coming out of a combination of institutions.
• 2:34
  Yeah.
• 2:35
  We have Northwestern, Caltech, and the Wiseman Institute.
• 2:40
  And the byline goes, astronomers have observed what they are calling a new type of supernova,
• 2:45
  which has provided an unparalleled glimpse into what happens deep within a star just before it explodes.
• 2:52
  Right?
• 2:52
  Yeah.
• 2:53
  This is like Taylor Swift's first album.
• 2:55
  We're looking deeply in.
• 2:56
  Yeah, this is like the first album.
• 2:58
  Yeah, not all the random modern nonsense that she's doing now.
• 3:03
  Sorry.
• 3:04
  I'm a huge fan of Taylor Swift.
• 3:06
  Yes.
• 3:06
  But like when I was in high school and college, the new stuff, not so much.
• 3:12
  So we've talked about this before, and I think I have a little bit of an understanding.
• 3:16
  You know, supernovas are when these stars just explode.
• 3:20
  Yes.
• 3:21
  At the end of their life.
• 3:21
  At the end of their life.
• 3:22
  Yeah.
• 3:23
  But tell me more about what this story means, this research and why it matters.
• 3:28
  Yeah.
• 3:29
  So studying supernovas is extremely important for understanding not just like how stars live their life, but also like how we get the atoms that make us up.
• 3:40
  OK, because stars like our sun only create atoms up to the element iron.
• 3:48
  Okay.
• 3:48
  Okay.
• 3:49
  But you know, the periodic table has a lot of elements after iron.
• 3:52
  It's very large.
• 3:52
  Every single element after iron was created in a supernova explosion.
• 3:57
  Interesting.
• 3:58
  Okay.
• 3:58
  And so understanding supernovas at a granular level tells us something about like how...
• 4:05
  these higher order elements formed.
• 4:07
  We're trying to figure out all the ingredients.
• 4:09
  Yeah.
• 4:09
  And supernovas help us figure out a large set of those ingredients after iron.
• 4:15
  Yeah, yeah, yeah.
• 4:16
  Supernovas are like the crucible for finding elements like gold, nickel, zinc,
• 4:23
  All of these things that are like pretty important for daily life on Earth, but also just for like making us.
• 4:28
  Yeah.
• 4:28
  Right.
• 4:29
  And there are these stars are these cosmic crucibles.
• 4:32
  Right.
• 4:33
  Like in the beginning.
• 4:34
  In the beginning.
• 4:35
  Yeah.
• 4:36
  In the beginning after the Big Bang, there was only really two elements, hydrogen and helium.
• 4:40
  Right.
• 4:40
  Right.
• 4:41
  But clearly we're made out of a bunch of other stuff.
• 4:43
  OK.
• 4:44
  Now, every element up to iron can be made by smaller stars like our sun.
• 4:51
  Okay.
• 4:51
  The sun can make stuff like oxygen, carbon in very trace amounts to get the real kinds of
• 5:00
  Abundance that we see on earth you need bigger stars to make those kinds of elements.
• 5:05
  Okay, and then to get anything above iron You need the star to explode.
• 5:09
  Okay, that's because there's something fundamental about the nuclei of atoms Okay
• 5:15
  Fusion, which is the process of taking lighter nuclei and fusing them to make bigger nuclei.
• 5:21
  So, you know, the fundamental form that's happening in our sun is hydrogen, four hydrogens fusing to make a helium.
• 5:29
  And then helium can fuse to make carbon, three of them.
• 5:33
  That process requires the energy of the nuclei to be lower than the constituents that made it up.
• 5:42
  Because of the second law of thermodynamics, the energy of the stuff that was making up the product has to be higher.
• 5:50
  That way, it's thermodynamically more favorable to make that.
• 5:54
  Does that make sense?
• 5:55
  You lose a little bit of energy when you make stuff.
• 5:57
  Yeah, yeah, yeah.
• 5:59
  And the universe wants to dissipate heat because of the second law of thermodynamics.
• 6:02
  And so this process actually dissipates heat, which is fine.
• 6:06
  Great.
• 6:07
  The universe is like, you guys do that all you want.
• 6:09
  Once you get to iron...
• 6:11
  Fusing elements higher than iron means that you need to inject heat.
• 6:16
  Okay.
• 6:16
  So, and that's something that the thermodynamics doesn't let you do, right?
• 6:19
  Because second law of thermodynamics says that like the energy should go off everywhere, not concentrate into a single spot, right?
• 6:27
  The entropy should increase, not decrease.
• 6:29
  But this requires a decrease in entropy.
• 6:32
  And in order to get anything higher than iron, the energy per nucleon is actually higher,
• 6:41
  Giant energetic event to actually start fusing stuff from iron to make zinc and gold and copper and uranium and all this other stuff.
• 6:50
  This is why the explosion matters.
• 6:52
  Yes, and this is why the explosion matters.
• 6:54
  Now, supernova, we've characterized supernova all over the universe, okay?
• 7:00
  The usual supernova is either a big star collapses, it can no longer hold its own weight, so it collapses, it explodes, and then you get this kind of stuff, right?
• 7:10
  And usually with supernova, you get to see the star as a whole collapsing.
• 7:16
  Okay, this one is pretty crazy because like there were these intermediate stages where the star sort of shed its outer layers.
• 7:24
  Okay.
• 7:25
  And you got to see the real core of the star.
• 7:28
  Right.
• 7:28
  And we got to see like the inside and we got to confirm a lot of these models that we have about stellar evolution.
• 7:35
  This is a really important point because our models are only as good as our observations.
• 7:40
  Yeah, yeah.
• 7:40
  That provide, quote unquote, the training data for the models we create.
• 7:45
  And so as we start looking at stuff that we haven't seen before, it allows us to refine our understanding of the universe even more each time we see these new novel use cases.
• 7:58
  Yes, exactly.
• 8:00
  The prevailing model, and it's, I guess, been confirmed by this particular supernova, is this thing called the onion skin model of big stars.
• 8:12
  What ends up happening is you've got a big star.
• 8:13
  Every star basically starts off with about 75% hydrogen, 25% helium.
• 8:20
  Um, once you start off with that, the first thing the star does is the cheapest thing to burn is hydrogen.
• 8:26
  Okay, it's super easy.
• 8:27
  It wants to turn into helium.
• 8:29
  You just give it a little pressure and a little bit of heat and it's like, alright, I'm going to go into helium.
• 8:33
  Now, pretty soon the hydrogen starts running out for these big stars within like 10s to hundreds of millions of years.
• 8:41
  And then what's going to end up happening is the core is going to run out of the hydrogen.
• 8:45
  So it's going to start contracting because there's not enough hydrogen to push out.
• 8:49
  There's not enough fusion happening to push out the gravity pressure.
• 8:52
  So it's going to start contracting.
• 8:53
  As it contracts, the heat is going to go up.
• 8:55
  The pressure is going to go up.
• 8:57
  And all of a sudden, helium burning is going to turn on.
• 8:59
  Got it.
• 9:00
  Okay.
• 9:00
  So now the helium is going to start burning into carbon and oxygen and things like that.
• 9:04
  Right.
• 9:05
  And when that helium burning starts, the outward radiative pressure is going to get really big.
• 9:10
  Yep.
• 9:11
  So then the outside is going to expand.
• 9:13
  And that's when you get these red giants like Betelgeuse.
• 9:16
  Yes.
• 9:16
  Right.
• 9:17
  Or even the sun is going to end up doing this at some point.
• 9:19
  Some French people were commenting on our pronunciation of...
• 9:24
  Oh, I don't.
• 9:25
  I don't.
• 9:25
  Betelgeuse.
• 9:26
  I don't.
• 9:26
  I don't respect the French.
• 9:29
  Yeah.
• 9:30
  So whether you say Betelgeuse or Betelgeuse, we won so we can decide how we say.
• 9:34
  Yeah.
• 9:34
  Yeah.
• 9:35
  And you surrendered.
• 9:36
  Sorry.
• 9:37
  Zebra, not zebra.
• 9:40
  But this onion model, celestial onions.
• 9:42
  Yeah.
• 9:43
  And so this expansion of the outer shell.
• 9:45
  Yeah.
• 9:46
  So you start expanding the outer shell and you become this like red giant, right?
• 9:50
  And then the core has like contracted though.
• 9:53
  And now it's starting to burn helium.
• 9:55
  Well, pretty soon it's going to run out of helium too.
• 9:56
  Yeah.
• 9:57
  And then it's going to go into this thing called the CNO cycle, which is the carbon, nitrogen, oxygen cycle, where this cycle between these three elements that's going to start burning helium because carbon is a 12.
• 10:09
  Oxygen is a 16.
• 10:11
  Yes.
• 10:12
  Right.
• 10:12
  So you're going to go from carbon.
• 10:14
  You're going to add a helium and then you're going to go to oxygen.
• 10:17
  But iteratively.
• 10:18
  Yes.
• 10:18
  And so it becomes this sort of cycle of trying to burn the fuel that you have.
• 10:25
  So the carbon is going to go, but then that's going to start running out, and you're going to start making silicon and burning the silicon, and then there's going to be this iron core.
• 10:34
  So you have this onion skin model of all of these different processes happening in a star, where the center is this iron that's not doing anything.
• 10:42
  Right outside, you have the silicon that's burning.
• 10:44
  Right outside, you got carbon, nitrogen, oxygen that's burning.
• 10:47
  Right outside, you got helium that's burning, and outside, you got helium.
• 10:49
  Hydrogen that's burning that's been the model that we know can happen from fundamental physics, right?
• 10:55
  We understand nuclei very well We understand the atom really well We understand the strong nuclear force really well so we can like say okay These are the energy scales where these things happen if I were to simulate this in a star Then it would happen at these radii because that's where the pressure and temperature is ideal for this kind of stuff and
• 11:15
  So this is the onion skin model, right?
• 11:17
  Yes.
• 11:18
  And we've confirmed sort of the outer layers of that onion skin.
• 11:22
  But like the deeper part, that silicon and the iron part, like that stuff's been elusive and it's sort of we're just going off.
• 11:29
  Well, we know how the stuff works and we know how the nuclear works.
• 11:34
  So it's probably right.
• 11:35
  Right.
• 11:36
  But now we've made this observational confirmation that this model that we have of the onion of the...
• 11:43
  how stars create these layers has now been experimentally Yeah, because we've gone to the deepest parts of the onion.
• 11:51
  Somehow this particular star, it's called Supernova 2021 YFJ because it was discovered in 2021.
• 11:58
  Somehow this particular supernova shed its outer layers
• 12:02
  Through a process that we might get to later on.
• 12:05
  Yes.
• 12:06
  And so what we could see is the inside, that silicon part that we had never seen before.
• 12:12
  Yeah.
• 12:12
  And when they first discovered this supernova, they were like, what are those lines?
• 12:18
  Silicon?
• 12:19
  That's crazy.
• 12:19
  Yes.
• 12:20
  And immediately they knew that they had like a candidate for an extremely rare event.
• 12:24
  Mm-hmm.
• 12:25
  And it was really exciting when they caught this in 2021.
• 12:28
  So the idea here in part is that timing kind of matters.
• 12:34
  Like we caught it timing wise when it was at that stage when we made the observation.
• 12:39
  It was in this state that allowed us to see that.
• 12:43
  Yeah, but the thing is we've seen supernova with this timing before.
• 12:49
  Oh, so this one is special.
• 12:50
  This is even rare.
• 12:50
  This is like special.
• 12:51
  This is special.
• 12:52
  This is a special supernova.
• 12:55
  They actually calculated the event rate of this thing, and they said it was 30 per cubic gigaparsec per year.
• 13:04
  And that didn't mean anything to me because I don't really know.
• 13:07
  Like, I don't have an intuition.
• 13:08
  I know what a gigaparsec is, right?
• 13:10
  It's 10 to the big parsec, which is like something to do with the parallax between the Earth going around the sun.
• 13:18
  And I was just like, okay, so how does this work?
• 13:21
  So I looked it up.
• 13:22
  The universe...
• 13:24
  The observable universe is 30 gigaparsecs in diameter.
• 13:29
  Okay.
• 13:29
  Okay.
• 13:30
  So let's assume it's a sphere.
• 13:32
  So we'll say the radii is 15 gigaparsecs.
• 13:35
  That's the observable universe, right?
• 13:39
  Volume of a sphere is 4 thirds pi or cubed.
• 13:42
  So 15 cubed is like 3,000.
• 13:46
  3,000 times 4 thirds times pi.
• 13:48
  Let's say the 3 and the 3 cancel.
• 13:50
  We're going to be engineers now.
• 13:52
  Right?
• 13:52
  Pi is 3.
• 13:53
  like the engineers like to say.
• 13:55
  So then that's about 3,000 times 4.
• 13:59
  It's about 12,000 gigaparsecs.
• 14:03
  And then you've got this event rate, which is 30 per gigaparsec per year.
• 14:07
  So that gets you to about 300,000 per year in the whole universe.
• 14:12
  And that's actually insane.
• 14:15
  Dude, 300,000, that's a countable number of zeros.
• 14:18
  There's only five zeros after the three.
• 14:20
  A countable number?
• 14:21
  You know, like the universe is like what?
• 14:24
  Billions of billions of trillions of stars and all this other stuff.
• 14:28
  Like there's only 300,000 events in the entire observable universe in a single year.
• 14:36
  That's like actually extremely rare.
• 14:38
  And so the idea is we really caught a needle.
• 14:42
  No, this thing is.
• 14:43
  Yeah, this thing was this thing was insanely hard and insanely rare.
• 14:47
  And we caught it because of.
• 14:50
  some of the efforts that we've done in astronomy when it comes to this time domain astronomy.
• 14:55
  We had a previous episode where we were talking about the Vera Rubin Observatory.
• 14:59
  The Vera Rubin is going to catch more of these things, right?
• 15:01
  Right.
• 15:02
  This one was caught not by the Vera Rubin Observatory.
• 15:05
  It was caught by the Zwicky Transient Facility.
• 15:08
  Okay.
• 15:08
  Okay.
• 15:09
  This is a facility that basically commandeered one of the observatories on Palomar, Mount Palomar, which is just south of us.
• 15:18
  Yes.
• 15:18
  Near San Diego.
• 15:19
  Yes.
• 15:20
  It's a Caltech Observatory.
• 15:23
  The Zwicky Transient Facility uses a telescope that's much smaller and a camera that's much smaller than the Vera Rubin.
• 15:28
  Yes.
• 15:29
  But it was kind of a precursor to understand what are the challenges going to be when we make the Vera Rubin, right?
• 15:37
  You want to do, in science, you want to do baby steps.
• 15:39
  You want to be like, okay, let's start with, in this case, a 48-inch telescope, which is just like a little bit more than a meter.
• 15:46
  Okay.
• 15:47
  It's like 1.3 meter telescope compared to Vera Rubin's 8.
• 15:51
  And then the camera is way smaller.
• 15:53
  This thing started in 2017.
• 15:56
  And it does something very similar to the Vera Rubin, which is like go through the northern sky because it's in the northern hemisphere.
• 16:03
  It goes through the northern sky every three days.
• 16:06
  Okay.
• 16:06
  Every three nights, I should say.
• 16:09
  So it's doing sort of the same thing.
• 16:10
  So we could have a dry run on what the challenges would be for the Vera Rubin by operating this Zwicky transient facility.
• 16:18
  In the tech world, we always love to say, let's have a crawl, walk, run approach to this problem.
• 16:25
  And this is a very similar idea.
• 16:26
  And this is exactly that.
• 16:27
  You've got to crawl first.
• 16:28
  Okay.
• 16:29
  What are the challenges to be able to walk?
• 16:30
  Yep.
• 16:31
  We walk.
• 16:31
  And now we're running with Verubon.
• 16:35
  But there's an important point that the crawl or walk stages still have value.
• 16:40
  Oh, yeah.
• 16:41
  In and of themselves, independent of the fact that we continue to increase our capabilities and other tools.
• 16:46
  Yeah.
• 16:47
  Yeah, it's it's it's I mean, we always do this in science, right?
• 16:51
  We've got limited funding, so we better get it right.
• 16:53
  So you always want a beta test before you actually launch the product.
• 16:56
  Right.
• 16:57
  Right.
• 16:57
  We're going to spend billions and billions.
• 16:59
  Yeah.
• 16:59
  We want to make sure that it makes sense.
• 17:01
  Exactly.
• 17:02
  Yeah.
• 17:03
  So the Zwicky transient facility, it's been online since 2017, and this was caught in 2021.
• 17:09
  Okay.
• 17:09
  It was caught on September 7th, 2021 at like 9.56 UTC.
• 17:15
  And as soon as it was caught, they knew this was a candidate for something big.
• 17:21
  Okay.
• 17:23
  So immediately afterwards, that night...
• 17:26
  The Keck telescope, which goes online right after California, because Hawaii is basically downstream in terms of the night sky from us.
• 17:36
  Whoever was in charge of the Keck telescope got the telegram or whatever and was like, oh, maybe my research can take a hold for a bit.
• 17:46
  He pointed the Keck telescope there, and he got the spectra.
• 17:50
  Because the Zwicky transient facility at Palomar
• 17:53
  It's only looking for changes in brightness.
• 17:55
  Okay.
• 17:56
  So it caught the supernova, which is basically, oh, there's a bright star that appeared there that wasn't there before.
• 18:01
  The Keck telescope was like, I'm going to point there.
• 18:04
  And it got the spectra.
• 18:05
  And the spectra was unlike anything you've ever seen before.
• 18:09
  Okay.
• 18:09
  It had lines of ionized silicon, sulfur, and argon.
• 18:14
  These are pretty heavy elements.
• 18:16
  Okay.
• 18:16
  Still lighter than iron.
• 18:17
  Yes.
• 18:19
  But pretty heavy.
• 18:20
  Yes.
• 18:21
  Okay.
• 18:21
  And this is something that we've like never seen before.
• 18:24
  The main thing was it also didn't have any hydrogen lines.
• 18:28
  Interesting.
• 18:29
  That's weird.
• 18:30
  Yeah, yeah.
• 18:31
  Every star has hydrogen.
• 18:32
  Yeah, yeah, yeah.
• 18:33
  So what's going on there?
• 18:34
  Right?
• 18:34
  Every star has hydrogen.
• 18:36
  But this guy had like sulfur and like argon, but no hydrogen.
• 18:41
  So then they were immediately like, oh, this is weird.
• 18:43
  Yeah.
• 18:44
  This is weird.
• 18:44
  So then there were a bunch of telescopes that worked together for 120 days after this explosion to just keep monitoring it.
• 18:53
  We had the CAC.
• 18:54
  We had the VLT down in Chile.
• 18:56
  We had the Lake Observatory, which is right outside San Jose in California.
• 19:00
  We had the Liverpool Telescope in England.
• 19:02
  Liverpool!
• 19:04
  Yeah.
• 19:05
  Little Scousers look too.
• 19:07
  Yeah.
• 19:07
  And then we had the Nordic Optical Telescope as well in Norway.
• 19:10
  Mm-hmm.
• 19:11
  So we had all of these telescopes working in conjunction to keep track of this thing for 120 days.
• 19:17
  It was an incredible effort across the globe to try to just have, like, you know, full surveillance on this guy.
• 19:24
  Right, right, right.
• 19:25
  Because immediately from that very first spectra that Keck took, it was like, this is something new.
• 19:32
  This is something crazy.
• 19:33
  Everyone drop your pencils.
• 19:34
  Yeah, everyone was like, okay, this is... And it turns out it's a new type of supernova.
• 19:40
  Mm-hmm.
• 19:40
  We thought we had categorized the supernova.
• 19:42
  There's like the supernova where the star explodes.
• 19:45
  There's the supernova where a white dwarf starts siphoning mass from another binary star that we've talked about in an earlier episode.
• 19:53
  And then that white dwarf reaches a mass limit and then that explodes.
• 19:57
  So there's all these other types of supernova.
• 19:59
  But this had a signature that was unlike any other.
• 20:01
  It was like a rare Pokemon.
• 20:03
  We ran up on Zapdos, Mew, Mewtwo.
• 20:06
  Yeah.
• 20:07
  And as soon as we said, every human was like, okay, we got to track this guy.
• 20:13
  We got to see what he's doing.
• 20:14
  I think one thing that's so interesting about this is it's a great reminder of the inherently collaborative nature of science.
• 20:20
  Yeah.
• 20:21
  Because...
• 20:22
  Astronomy especially, dude.
• 20:23
  Because we have to make observations.
• 20:25
  And necessarily because of planet Earth and that we have different tools on different points on the sphere.
• 20:33
  Yeah, and the Earth is rotating.
• 20:34
  So I only got like eight hours of good nighttime.
• 20:38
  Right.
• 20:38
  And then we're like, hey, you call up the Liverpool folks.
• 20:41
  Hey, it's coming your way.
• 20:42
  Yeah.
• 20:42
  You know, click.
• 20:43
  And they're like, okay.
• 20:46
  This is really...
• 20:47
  Okay, this is really...
• 20:48
  So, I mean, this is a pretty, you know, given we already have a really robust, you know, starting point in terms of already having theoretically and experimentally or observationally captured, you know, a whole catalog of types of supernovas.
• 21:04
  The idea that we found a supernova that's like this 300,000 per year in the universe.
• 21:12
  In the observable universe.
• 21:14
  In the observable universe.
• 21:15
  That's insane.
• 21:18
  As we've talked about previously, is very large.
• 21:21
  Yeah.
• 21:22
  Yeah.
• 21:22
  Very, very, very large.
• 21:26
  The opportunity, again, this is rarer than Taylor Swift and Travis Kelsey's engagement.
• 21:33
  No, this is much more rare.
• 21:34
  This is rarer than.
• 21:35
  I don't know how many Taylor Swifts are out there in all the galaxies.
• 21:38
  Yeah, right.
• 21:38
  Right?
• 21:39
  It could be quite a bit.
• 21:40
  Yeah, there's billions and billions of galaxies.
• 21:42
  Right.
• 21:42
  Right?
• 21:43
  Billions of billions.
• 21:44
  Billions of billions.
• 21:45
  Like 10 to the 9 times 10 to the 9.
• 21:47
  Right.
• 21:48
  Right?
• 21:49
  But here there's like 300,000 of these.
• 21:51
  Right.
• 21:51
  Which I know what 300,000 means.
• 21:53
  Yeah, that's... Like, I can visualize that.
• 21:56
  Yes.
• 21:56
  I can't visualize the universe.
• 21:57
  Right.
• 21:58
  But I can visualize that number.
• 22:00
  Look, there are... That's insanely small for the universe.
• 22:02
  Houses used to cost $300,000.
• 22:04
  Yeah.
• 22:05
  Right.
• 22:06
  And they still do in some parts of America.
• 22:08
  That is true.
• 22:09
  Not in L.A., I'll tell you that.
• 22:10
  Southern California is not a beneficiary of that level of cost of living.
• 22:14
  Yeah.
• 22:15
  But exceptional discovery.
• 22:18
  Again, Northwestern, Caltech, Wiseman Institute.
• 22:24
  So a little bit of everything, you know, America heavy.
• 22:26
  America Heavy, yeah.
• 22:27
  You know, but a little international collaboration.
• 22:29
  Yeah.
• 22:29
  There's also, like, a Chinese group because a Chinese group actually had access to Keck at the time.
• 22:35
  Uh-huh.
• 22:36
  And we were like, yo, this is dope.
• 22:39
  And they were like, yeah.
• 22:42
  We'll move it.
• 22:43
  Look, even given the geopolitical... No, dude.
• 22:47
  Everyone knows when you see, like, a supernova, it's like, let's just check its lines.
• 22:51
  And once they checked its lines, it's like, oh, this is...
• 22:54
  This is a good paper.
• 22:56
  I'm going to be on it.
• 22:57
  It reminds me of kind of how anytime we talk about space, it sort of melts away.
• 23:02
  Yes.
• 23:03
  Because we're on a single planet, and we're trying to make sense of whatever the hell is out there.
• 23:09
  Yeah, right.
• 23:10
  I think everybody who's an astronomer understands the speck of dust that we're on and the insignificance of all of these geopolitical conflicts when it comes to understanding a universe that is gigaparsecs on gigaparsecs big.
• 23:24
  I think the first time I heard the word parsec in general was Star Wars.
• 23:30
  That's how they talk about traveling in between.
• 23:33
  It's five parsecs.
• 23:35
  Yeah.
• 23:36
  Let's do a jump drive.
• 23:37
  Yeah.
• 23:39
  Great story on the new supernova.
• 23:41
  Yeah.
• 23:41
  It's an amazing dude.
• 23:43
  And I think it tells us a lot about like.
• 23:46
  First of all, like how we get the elements that we have.
• 23:50
  Yes.
• 23:51
  Right.
• 23:51
  It also tells us a lot about this onion skin model.
• 23:54
  The fact that we're right.
• 23:55
  Yes.
• 23:55
  Because it turns out like, so one of the questions is like, why do we, why are we seeing only sulfur and silicon, but we're not seeing hydrogen?
• 24:03
  Yes.
• 24:03
  It could be because like what's, what's ended up happening is this things, this star has been like pulsing.
• 24:08
  Right.
• 24:08
  And as it pulses, it removes these outer layers.
• 24:12
  Right.
• 24:12
  So that when it finally like exploded, right.
• 24:15
  The only layers that were left were these silicon layers, right?
• 24:19
  And so the light that we're seeing is coming through these silicon and sulfur layers, and then that's what we're seeing.
• 24:25
  Yeah, there's still actually a mystery in this discovery.
• 24:29
  There were faint lines of helium and carbon, okay?
• 24:33
  Which is weird because helium and carbon should be like...
• 24:36
  out there.
• 24:37
  But we don't see any nitrogen, which should have been inside.
• 24:41
  Right?
• 24:41
  So like, if we don't see nitrogen, that means the nitrogen layer is already gone.
• 24:44
  Yes.
• 24:45
  But like, there's still helium.
• 24:46
  So how did the...
• 24:47
  So how did the... Yeah.
• 24:48
  How did the nitrogen dissipate without helium?
• 24:50
  Yeah.
• 24:50
  And there's...
• 24:51
  It's still a mystery.
• 24:53
  People think that it's probably like this thing is part of a binary star system.
• 24:57
  Okay.
• 24:58
  And then the star system, the other star has a bunch of helium that like, we're like seeing through, right?
• 25:04
  Because what we're seeing through is like...
• 25:06
  Like, the light coming from the supernova is, like, effectively, like, white light.
• 25:10
  Right.
• 25:10
  Okay?
• 25:11
  It's just pure energy from this collapse into an explosion.
• 25:16
  But, like, the lines that we're seeing are the stuff that's getting in the way.
• 25:20
  Right.
• 25:21
  Right?
• 25:21
  And so helium might be, like, this thing that's coming from the binary star.
• 25:25
  There's still a lot more that we can do from finagling the data.
• 25:30
  Right.
• 25:31
  But...
• 25:31
  Yeah, it's super exciting because it's a totally new type of supernova, right?
• 25:36
  Extremely rare.
• 25:37
  It's like nothing we've ever seen before.
• 25:39
  And it's great that it confirms these models that we have just built on fundamental physics.
• 25:44
  Right.
• 25:45
  These are models based on just what we know about nuclei from experiments that we've done on Earth.
• 25:52
  And we can extrapolate.
• 25:53
  And it's insane that we can extrapolate from what we understand from the strong nuclear force and how protons and neutrons interact.
• 26:01
  from what we've done on earth to like then go all the way and see this thing that's like, you know, half a mega parsec away, 120 days of data.
• 26:13
  Right.
• 26:13
  Yeah.
• 26:13
  It's, it's, it's really cool to success.
• 26:16
  And that's what I mean when I say like, you know, we're pretty good at physics.
• 26:19
  Yeah.
• 26:20
  This is what I mean.
• 26:21
  Like we're, we're pretty good at like making a model of a giant star that's 16 to 50 solar masses and be like, okay, it should be like a shell thing.
• 26:31
  Because the gravity here and the pressure here means that the temperature is going to be at this much and the pressure is going to be at this much, which means that what I know about nucleosynthesis means that these are the kinds of elements that should be there.
• 26:43
  Right?
• 26:44
  Yep.
• 26:44
  We can trace all of these things just on a chalkboard.
• 26:49
  It's really incredible.
• 26:51
  We love a good story that takes rare space-based events.
• 27:01
  connects it to the history of scientific discovery that we've already established on our little third rock that goes around the sun.
• 27:10
  Yeah.
• 27:11
  And know that, oh, yeah, we've been right.
• 27:13
  Yeah.
• 27:14
  It's really cool.
• 27:14
  We've been right.
• 27:15
  And then there's some enigma.
• 27:17
  And that's probably because there's like some other thing that we're not seeing.
• 27:21
  And we have the tools to see it.
• 27:25
  Great.
• 27:27
  I love our space stories.
• 27:28
  Yeah.
• 27:29
  Yeah.
• 27:29
  And I can't wait to see how many Vera Rubin is going to catch.
• 27:33
  Oh, my God.
• 27:33
  Right?
• 27:34
  Now that it goes online.
• 27:35
  Check out our episode three or four because we do a deep dive on it.
• 27:40
  And I still.
• 27:42
  The greatest observatory.
• 27:43
  Ever created by humanity to date.
• 27:45
  Yeah.
• 27:46
  To date.
• 27:47
  And I just I think about it a lot, actually.
• 27:49
  Every day I'm like, oh, it did another.
• 27:51
  Yeah.
• 27:52
  And you can just go online and check.
• 27:53
  What did it find?
• 27:54
  The Explorer, the online Explorer is incredible.
• 27:58
  The data access, which we talked about, is incredible.
• 28:01
  It's for everybody.
• 28:03
  And so we've started like we always do.
• 28:07
  Or regularly do something very big.
• 28:09
  We're now going into the opposite direction.
• 28:12
  And our next two stories are going to be stuff that's very, very small.
• 28:16
  There's been a lot of this news or rumors and gossip that there's been turmoil on the set of the new Avengers movie.
• 28:25
  Yeah, I saw a lot of memes about it.
• 28:27
  And the details are a little fuzzy.
• 28:29
  But apparently Robert Downey Jr., RDJ, Iron Man, who is the tentpole of the whole franchise, the only reason it exists, has been having some conflicts with...
• 28:43
  one of the more aggressive characters in the Marvel Universe, Deadpool, a.k.a.
• 28:48
  Ryan Reynolds, who apparently can't stop fighting each other on set.
• 28:52
  But weirdly, how this connects to our story is our story number two is that apparently a virus and bacteria are teaming up and are able to battle cancer as if it's Thanos in Endgame.
• 29:05
  Yeah.
• 29:06
  There are no five rings on the thingy.
• 29:09
  No, but this team up could actually change the game for cancer therapy.
• 29:15
  So this story is coming out of Columbia Engineering.
• 29:18
  Researchers at Columbia Engineering byline is researchers at Columbia Engineering have built a cancer therapy that makes bacteria and viruses work.
• 29:29
  work as a team.
• 29:31
  It was published in Nature Biomedical Engineering.
• 29:34
  And the Synthetic Biological Systems Lab shows how their system hides a virus inside a tumor-seeking bacterium and smuggles it past the immune system and unleashes in it, inside these cancerous tumors, unleashes the force.
• 29:52
  Dude, it's insane.
• 29:54
  So there's an immigration story here.
• 29:56
  Yeah, yeah.
• 29:56
  We love, there's a smuggling story here.
• 29:58
  There's really, yeah.
• 30:00
  Columbia was obviously the center point for a lot of controversy as it relates to.
• 30:04
  Yeah.
• 30:05
  No, they're doing good work.
• 30:06
  Science and research and funding.
• 30:08
  But tell me, you know, this sounds like a great buddy cop movie.
• 30:12
  It is.
• 30:12
  It is exactly that.
• 30:13
  Okay.
• 30:14
  Yeah, it is exactly that.
• 30:15
  It's like.
• 30:16
  It's like two cops that are teaming up to take care of a bad guy.
• 30:22
  It's almost like, what's the one movie where they take the criminals and then they're like, Suicide Squad.
• 30:30
  Oh, yeah.
• 30:31
  Right?
• 30:31
  Where they're like, they take the criminals and then they're like, okay, we're going to make you good now.
• 30:35
  And then you're going to get the even worse bad guys.
• 30:38
  That's what this is.
• 30:39
  Okay.
• 30:39
  Got it.
• 30:39
  Right?
• 30:40
  You know what I mean?
• 30:40
  Yeah.
• 30:41
  Because it's like bacteria.
• 30:42
  We don't like that.
• 30:42
  Right.
• 30:43
  viruses we don't like that but the two of them together are now fighting cancer which we really don't like it's a super evil duo to fight the even more even more evil yeah it's that it's that it's that um the the meme with um thor being like i know i can't but
• 31:03
  But she can, you know what I mean?
• 31:05
  But it's like this virus bacteria chimera that they've created.
• 31:10
  It's an incredible paradigm shift in cancer treatment.
• 31:14
  So what I understand about cancer treatment, which is very little, is fundamentally it's very like the existing options we have for the patients, whether it's chemo, it's like very hard on the body.
• 31:27
  Yeah, it's very hard on the body and it's also very nonspecific.
• 31:31
  That's the main thing.
• 31:32
  It's a shotgun approach.
• 31:33
  Yeah.
• 31:33
  Yeah.
• 31:33
  It's just like, it's just like, it's just like with chemo, all you're doing is targeting, um,
• 31:41
  cells that replicate really fast.
• 31:42
  Okay.
• 31:43
  So you're getting rid of the cancer cells, but you're also getting rid of hair cells because they, hair follicles because they replicate really fast.
• 31:50
  Bone marrow, they replicate really fast.
• 31:52
  Digestive cells that replicate really fast.
• 31:54
  That's why you get nausea, anemia, hair loss, you know?
• 31:58
  Yes.
• 31:59
  So it's nonspecific.
• 32:00
  Yes.
• 32:00
  And then with radiotherapy, it's like sort of like, you know, you're just sort of blasting some location.
• 32:07
  And sure, you can get specific with like proton cells,
• 32:10
  therapy and things like that but at the end of the day it's not like targeting from a biological sense only the cancer cells right right right so over the years we've had these things called adaptive therapies okay and adaptive therapies what they've done is sort of target only the cancer cells and leave everything else alone right okay there's been there's been sort of a bunch of approaches
• 32:33
  there's been this thing called CAR T therapy, which is where you take the body's own immune cells and then you engineer those immune cells to then target the antigen, which is like,
• 32:48
  sort of a marker on these cancer cells.
• 32:50
  So you train the body's own immune system to then target these cancer cells and recognize these cancer cells.
• 32:57
  The problem with that therapy is, okay, it's got to be extremely specific to the patient.
• 33:02
  You've got to literally extract immune cells from the patient and then you've got to engineer those...
• 33:07
  On a per patient basis.
• 33:08
  On a per patient basis.
• 33:10
  And then also at the end of the day, a lot of these cancers are clever, dude.
• 33:14
  They've created methods to actually create cold tumors.
• 33:18
  It's what we call when they suppress the immune response.
• 33:23
  Okay?
• 33:24
  Even with the CAR-T and all this stuff, like they're suppressing the immune response actively because they're secreting stuff that confuses the immune system.
• 33:32
  Right?
• 33:33
  It's like you say, oh, we're going to build a wall.
• 33:34
  And they're like, we have ladders.
• 33:35
  Yeah, yeah.
• 33:38
  Or like we're making the wall invisible.
• 33:40
  And then it's like, oh, okay, now my immune system can't actually see everything, right?
• 33:45
  So over the years, we've shifted towards something called adaptive therapies, which are these like single agent biotherapies where...
• 33:55
  We're now actually leveraging biology itself to attack biology.
• 34:01
  Okay.
• 34:02
  Okay.
• 34:02
  So there's two approaches.
• 34:03
  One approach is to use bacteria.
• 34:05
  Okay.
• 34:06
  What we do is we take some bacteria and we try to get that bacteria to attack cancer.
• 34:13
  Yes.
• 34:14
  Okay.
• 34:15
  There's some advantages to this.
• 34:16
  The advantage is there are certain types of bacteria, like salmonella, that like anoxic environments.
• 34:24
  So, environments that don't have a lot of oxygen.
• 34:26
  Tumors tend to have not a lot of oxygen, especially at their core, because the blood vessels are on the periphery.
• 34:32
  And at the core, the oxygen is getting to it.
• 34:35
  So, the bacteria naturally are like, ooh, I like that.
• 34:38
  And then they get to the core, and then they start sort of...
• 34:41
  you know, destroying the cancer from within.
• 34:44
  The problem with that is they get to the core, but they're not really attacking the periphery and they're not attacking like maybe a metastasis that happened somewhere else, right?
• 34:54
  And the other problem obviously is like, okay, like you're literally giving me salmonella, right?
• 34:58
  You can like, you can genetically engineer and everything, but like,
• 35:03
  It's still bacteria.
• 35:05
  You're giving me a pathogenic bacteria, right?
• 35:07
  And there's a risk of systemic infection and dose-related toxicity and all this other kind of stuff, okay?
• 35:15
  The other way to approach this problem is with viruses, okay?
• 35:19
  You have something called oncolytic virotherapy.
• 35:22
  Where you take viruses that attack cancer cells and you inject that into the patient, right?
• 35:31
  Now, with oncolytic virotherapy, there's two problems.
• 35:35
  One is the delivery challenge, okay?
• 35:37
  You got to really get into the tumor and like put that in there, okay?
• 35:41
  Inject direct.
• 35:42
  So if there's a tumor that's very, very deep or if there's like some random tumors elsewhere that haven't been identified, okay?
• 35:49
  Yeah, out of luck.
• 35:50
  It's not like a systemic approach.
• 35:52
  Yeah.
• 35:53
  And the other thing is the immune system of the body has already been primed with a bunch of viruses that you've seen over the years.
• 36:00
  Right.
• 36:01
  So the immune system itself is going to be like, you're not getting in.
• 36:04
  What are you doing?
• 36:06
  And then the immune system is going to attack that virus.
• 36:08
  Right.
• 36:08
  Makes sense.
• 36:09
  So this particular therapy called the capsid
• 36:12
  C-A-P-P-S-I-D, right?
• 36:16
  With two Ps.
• 36:17
  Yes.
• 36:18
  This particular therapy is getting the best of both worlds.
• 36:23
  Okay?
• 36:23
  Yes.
• 36:24
  It's combining the virus, which is really good at killing...
• 36:28
  the cancer cells, but it's hard getting in.
• 36:31
  It's got a tough time getting in.
• 36:32
  It can't get past the security at the door.
• 36:34
  It's yeah.
• 36:35
  So it's the virus is becoming like the Greek soldiers inside the Trojan horse.
• 36:42
  And the bacteria becomes a Trojan horse.
• 36:44
  Okay, because the bacteria has an easy time getting into the center of the tumor.
• 36:49
  Right.
• 36:49
  And it knows where to go because of the anoxic environment.
• 36:52
  It's seeking this place without any oxygen.
• 36:54
  So it goes to the center of the tumor.
• 36:56
  So what this team at Columbia Engineering is doing is combining both of those therapies to give this like two pronged approach.
• 37:05
  It's a synergistic.
• 37:07
  Yes.
• 37:07
  Biotherapy.
• 37:08
  Yes.
• 37:09
  That combines the best of both worlds.
• 37:11
  Yes.
• 37:11
  To target the tumor.
• 37:14
  Yes.
• 37:14
  And then infect the tumor with the viruses.
• 37:17
  Yes.
• 37:17
  And then also have that viral effect.
• 37:21
  um infection spread to other tumors in the body dude it's it's like it's almost out of science fiction i can't like the amount of stuff that needed to happen yes for this to be a reality right where we're now manipulating viruses bacteria
• 37:38
  Together.
• 37:39
  In combination.
• 37:40
  In combination.
• 37:40
  We're both burning together.
• 37:42
  Yeah, dude.
• 37:43
  It's actually insane.
• 37:44
  It looks like this.
• 37:45
  So, capsid.
• 37:47
  It looks like it's short for coordinated activity of prokaryote and
• 37:52
  The coronavirus of safe intercellular delivery.
• 37:57
  Yes.
• 37:57
  Prokaryote means a type of life that doesn't have a nucleus.
• 38:01
  So that's bacteria.
• 38:03
  Right.
• 38:03
  Okay.
• 38:03
  And coronavirus is the particular type of virus that they've used to genetically engineer to create this kind of viral therapy.
• 38:10
  Not coronavirus.
• 38:11
  No, not coronavirus.
• 38:13
  Yeah.
• 38:14
  This is like a type of...
• 38:16
  It's a Seneca virus.
• 38:18
  Yes.
• 38:18
  Seneca virus A.
• 38:20
  Yes.
• 38:20
  Yeah.
• 38:20
  Yes.
• 38:22
  This is... Dude, it's a game changer.
• 38:24
  And there's a lot of hurdles that you have to get through.
• 38:29
  Right.
• 38:30
  Because like...
• 38:31
  Okay, for example...
• 38:33
  So one thing would be like, okay, I've got this bacteria and it's got a viral DNA inside.
• 38:39
  Like what's to guarantee that the viral DNA isn't just going to like express itself not in the tumor?
• 38:45
  What I'd like is for the virus to only target the tumor, right?
• 38:48
  I don't want it to.
• 38:49
  I got a bunch of healthy cells, right?
• 38:51
  I don't want a viral infection everywhere.
• 38:53
  Then we're back to the same issue with the chemo and radiotherapy, which is it's nonspecific.
• 38:58
  It's nonspecific.
• 38:59
  So how do I make this specific, right?
• 39:00
  So they engineered a way such that the viral DNA would only be expressed once the bacteria was inside the tumor.
• 39:09
  That's sick.
• 39:09
  Once it's in the club, then it goes in.
• 39:11
  Once it's in the club, then that's when it does all of its shit.
• 39:14
  Right.
• 39:14
  Right?
• 39:15
  And the way they did that was they attached it to a promoter.
• 39:18
  Yeah, we talked about it.
• 39:20
  The gene expression that's happening would only be expressed once the bacteria was in its environment where it wants to be pathogenic.
• 39:29
  And then once it did that, the viral DNA now starts transcribing.
• 39:33
  The other thing that was really cool that they did was they included a T7 RNA polymerase.
• 39:40
  So you've got this DNA that is really the viral DNA inside the bacteria, right?
• 39:46
  Yep.
• 39:47
  And what you want to do, usually what you want to do is viruses, they hijack the host cell, right?
• 39:53
  And then they replicate DNA using the host cell.
• 39:56
  Yes.
• 39:56
  This thing's got its own machinery to replicate the viral DNA.
• 40:02
  So it doesn't need to require the host cell.
• 40:03
  Because the host cell is cancerous.
• 40:05
  It could be doing all sorts of...
• 40:06
  Random crap.
• 40:07
  Right.
• 40:07
  Right?
• 40:08
  Like, it's like replicating like crazy.
• 40:10
  Yes.
• 40:10
  So it's doing all sorts of crap.
• 40:12
  And so it's maybe not as dependable as a mechanism.
• 40:15
  Yes, exactly.
• 40:16
  We don't want to depend on this dysfunctional machinery of cancer cells in order to replicate the virus that is going to destroy the cancer cell.
• 40:23
  Yep.
• 40:23
  Right?
• 40:24
  So we've created our own little polymerase that will do that.
• 40:28
  Mm-hmm.
• 40:29
  Which is really cool.
• 40:30
  Yes.
• 40:31
  Yeah.
• 40:31
  Yes.
• 40:32
  I want to make a quick shout out to Charles M. Rice, who is an expert in virology at the Rockefeller University, who was a part of this study and collaborated with the Columbia team.
• 40:43
  So I want to make sure we give.
• 40:44
  Right across the island of Manhattan.
• 40:47
  Oh, there you go.
• 40:47
  Rockefeller and Columbia.
• 40:49
  Right.
• 40:49
  East side versus west side.
• 40:50
  A little quick yacht trip across there.
• 40:53
  So just making sure that we give Charles a shout out there.
• 40:57
  as well as, again, the team over at Columbia.
• 41:00
  Yeah, dude, it was insane.
• 41:01
  And, dude, you want to hear the experiment that was, like, nail on the coffin?
• 41:06
  Yes, because we love talking about experimental design.
• 41:08
  Yeah, the experimental design here is amazing.
• 41:10
  So they got these mice models.
• 41:13
  Yes.
• 41:13
  Again, transgenic mice models that sort of mimic the small cell lung cancer.
• 41:20
  Okay?
• 41:21
  100% survival rate.
• 41:23
  Jesus.
• 41:24
  Okay.
• 41:25
  Here's what they did.
• 41:26
  And this is, and not just that.
• 41:27
  Okay.
• 41:28
  Here's what's crazy.
• 41:28
  Okay.
• 41:29
  So this mouse model has a tumor in each of its lungs.
• 41:33
  Okay.
• 41:33
  Right flank, left flank.
• 41:35
  What they did was they injected this therapy into the right flank.
• 41:41
  And the therapy killed the cancer in the right flank, and then it went to the left flank and killed it there too, right?
• 41:48
  Because the virus inside the right flank lung does the infection, creates these antibodies, right?
• 41:56
  And these viral particles.
• 41:57
  Those viral particles then travel through the bloodstream and start targeting the cancer in the other location as well, right?
• 42:06
  And the whole point was now we've...
• 42:08
  the immune system is now overrun because before if we just inject the viral particles, the immune system is going to be like, that's not enough.
• 42:15
  Right.
• 42:16
  But now we have this full-fledged viral inflection.
• 42:18
  Right.
• 42:18
  But all this virus is targeting are cancer cells.
• 42:21
  Right.
• 42:22
  Right.
• 42:22
  It just wants to eat cancer cells because that's what the particles are sort of lock and keying into.
• 42:28
  Yes.
• 42:28
  You know?
• 42:30
  So now you can put this into one part.
• 42:33
  And as long as if it's the same cancer that spread to other parts of the body,
• 42:37
  It'll target those other cancers.
• 42:40
  This is so important.
• 42:41
  It's so cool.
• 42:42
  This is so important.
• 42:44
  Because this goes back to what we talked about at the beginning of the story, which is it's no longer nonspecific.
• 42:49
  And not only is it nonspecific, you can insert it into the sort of body in a singular location.
• 42:59
  And it will independently locate and then also kill other similar cancer locations for that exact same targeted focus.
• 43:09
  Yeah, yeah.
• 43:10
  Which...
• 43:11
  Again, for patients, like this comes back to like, what is the impact for, you know, research like this on real people?
• 43:17
  It's like these therapies can become much more, can be more effective with less of an impact on the body.
• 43:26
  Exactly.
• 43:26
  And these like other ways in which the nonspecific therapies...
• 43:30
  Yeah.
• 43:30
  Which we have available to us now.
• 43:31
  Yeah.
• 43:31
  Like CAR T therapy is a specific therapy that happens like patient by patient.
• 43:35
  Yes.
• 43:35
  But it's got problems, right?
• 43:36
  Like the CAR T therapy, these immune cells, for example, they can't get to the center of the tumor.
• 43:44
  Right.
• 43:45
  Because the tumor has these natural mechanisms where it wants to fight off the immune cells.
• 43:48
  Right.
• 43:49
  Right.
• 43:49
  On the other on.
• 43:50
  And then also, you know, it's CAR T therapy.
• 43:54
  You got to train these immune cells to identify specific antigens.
• 43:58
  But cancer is just like such a to work with because cancer is always mutating.
• 44:05
  Right.
• 44:06
  So, OK, you don't like this antigen, I'll give you another one.
• 44:08
  And then the CAR T therapy is not going to work because it's only trained on a single antigen.
• 44:12
  Right.
• 44:13
  And now I've just changed the shape to how you recognize me.
• 44:17
  And like my ID is now different.
• 44:19
  Right.
• 44:19
  And so you'll just let me go.
• 44:21
  Right.
• 44:21
  And so here with the viral DNA is constantly evolving as well.
• 44:26
  Right.
• 44:26
  So it can.
• 44:28
  mitigate this heterogeneity right this like difference right that's happening with these rapidly mutating cancer lines right which is one of the key aspects of why cancer is such a pernicious issue to yeah dude it's so hard because it changes so fast but this we're like harnessing the fact that viruses also do that do that and they and they create like all of these different versions and then one works yeah and then that'll go and then and then like it'll find another version that'll work
• 44:56
  You know, it's like synthetic biology, which is crazy to think about.
• 45:00
  Like we're literally engineering.
• 45:02
  Right.
• 45:02
  Like little tiny micro molecular robots to now just target these bad guys, these cancer cells.
• 45:09
  Right.
• 45:10
  I mean, we're far away from like FDA approval.
• 45:13
  Right.
• 45:14
  There's lots of concerns, obviously.
• 45:15
  Right.
• 45:17
  I talked about mutation just now, right?
• 45:19
  Like what's stopping this virus from mutating into like its original version of where like I hate it.
• 45:26
  Yeah.
• 45:27
  Right.
• 45:28
  So, yeah, it's like we've created our own micromolecular suicide squad.
• 45:33
  Yeah.
• 45:34
  But we haven't like there's still the concerns, but they are still the suicide squad.
• 45:37
  Yeah, they're still the suicide squad.
• 45:38
  So like in order to get to actually like human trials, because right now they've done it on mice and they've done it in vitro sort of human cell lines and things like that.
• 45:46
  In order to get it to sort of FDA approval, we have to, first of all, mitigate the risks.
• 45:53
  One of the ways that they're actually doing it, and they described it in this paper, is instead of a single nucleotide mutation that will take the virus and put it back into its wild type, which is the part that we don't like, they made it two mutations.
• 46:07
  Okay.
• 46:08
  So what that means is now like, you know,
• 46:11
  If the probability of like going to a mutation was 1 over 100, now it's geometric.
• 46:16
  So it's 1 over 100 squared.
• 46:17
  So 1 over 10,000, which is like obviously way better than 1 over 100.
• 46:22
  You can imagine like doing this for multiple single nucleotide mutations.
• 46:26
  We also need to test it on higher order organisms, right?
• 46:31
  Right now we did it on mice.
• 46:32
  We need to like start graduating and slowly going towards human beings.
• 46:37
  Yes.
• 46:38
  But I think it's extremely promising.
• 46:40
  The other thing is like this thing, like it's currently been targeted for neuroendocrine like cancer cells.
• 46:46
  So it's like, you know, small cell lung cancer and things like that.
• 46:49
  But one can imagine this is a modular thing, right?
• 46:52
  The bacteria could have any sort of virus and the bacteria could be any other kind of bacteria that we sort of engineered to get in here.
• 47:00
  So it's this like, you know, Lego block thing that we talk about all the time where it's like, it's like we can have different types of Lego blocks that we put in here and here.
• 47:09
  It's this modular thing that we can adapt to different kinds of viruses.
• 47:12
  I think it's, I think it's extremely special.
• 47:15
  Adaptive biotherapy.
• 47:16
  Yeah.
• 47:16
  It was what you sort of started with.
• 47:17
  I mean, there's a key insight here fundamentally that has so many different paths that it can now go down because it's a key.
• 47:28
  It's similar to how CRISPR was a key insight.
• 47:31
  That's right.
• 47:31
  That had then multiple of these like.
• 47:33
  Yeah, because it was modular at the end of the day.
• 47:35
  At the end of the day.
• 47:36
  Yeah.
• 47:36
  It's not just an acute, specific, singular insight.
• 47:41
  And that's what's, again, so fascinating about this study in particular in terms of the now instead of there being one door, two doors, three doors.
• 47:49
  Yeah.
• 47:49
  Now it's like we can just mix and match and get a bunch of doors.
• 47:52
  Every door you want.
• 47:54
  is potentially available.
• 47:56
  Yeah, it's pretty cool.
• 47:57
  Obviously with the caveats of, you know, downstream research to mitigate this.
• 48:00
  Yeah, and obviously we need to make sure it's safe, but I think this is really promising.
• 48:03
  Fascinating.
• 48:05
  We're, you know, we're moving into a place, again, we talk about this a lot, between the fundamental research stuff in sort of this, you know, biotech arena,
• 48:17
  and then you add the ability to then sort of rapidly iterate with things like AI, progress is going to continue to be... Yeah, it's going to be really cool.
• 48:25
  Yeah, fascinating.
• 48:26
  It's going to be awesome.
• 48:27
  And while we have a lot of progress in some of these biomolecular research areas, one area we don't have a lot of progress is in politics, where politicians continue to like to spin the news.
• 48:40
  But our third story is that scientists have figured out
• 48:44
  how to spin electrons.
• 48:46
  That's right.
• 48:47
  And it could maybe power the next generation of tech.
• 48:51
  This next research paper is out of the National Research Council of Science and Technology in Korea, most famously known right now for K-pop demon hunters.
• 49:02
  And Squid Games.
• 49:03
  Yeah.
• 49:04
  But Korea has a huge technical.
• 49:07
  Yeah.
• 49:08
  That's where Samsung is.
• 49:09
  Right.
• 49:09
  Like a huge.
• 49:10
  In terms of the amount of people.
• 49:11
  One of the big fabs in the world.
• 49:13
  In the world.
• 49:13
  Like they have a huge population of like highly technical people.
• 49:17
  And.
• 49:18
  This study is fascinating.
• 49:19
  So this was a little bit different for me.
• 49:21
  So the headline here is turning spin loss into energy.
• 49:25
  New principle can enable ultra low power devices.
• 49:28
  So one of the things we've talked about in the previous episode is if we look at all the technology revolutions that are currently happening, the one underlying thing that's true and is a part of the great power war that all these nation states are having is we need more power.
• 49:43
  Yeah.
• 49:43
  If we want to have all this AGI.
• 49:45
  That's right.
• 49:46
  Artificial general intelligence, all these things.
• 49:48
  We need a lot more power.
• 49:50
  Yeah.
• 49:51
  The Chinese are solving it right now by building nuclear at levels we've never seen before.
• 49:56
  But this maybe has sort of some impacts in this power generation problem set.
• 50:01
  So, yeah, it lets us.
• 50:03
  I mean, it lets us do more with less.
• 50:05
  Okay.
• 50:05
  At the end of the day.
• 50:06
  Okay.
• 50:06
  Right.
• 50:06
  It lets us compute more with less.
• 50:09
  If...
• 50:09
  this becomes an economically viable and a commercially viable product.
• 50:14
  Okay.
• 50:15
  Okay?
• 50:15
  So I will give you that caveat, but it's a proof of concept of something that people have been after for quite a while.
• 50:21
  Okay?
• 50:23
  In order to get into the idea of Spintronics, which is this new paradigm of electronics.
• 50:30
  I think Spintronics was just actually performing at Burning Man.
• 50:34
  Is there a band that does that?
• 50:37
  I'm pretty sure Spintronics is an EDM DJ, literally right now.
• 50:39
  That's hilarious.
• 50:40
  I hope he's good.
• 50:40
  Because Spintronics could be the future of electronics.
• 50:46
  So in order to really understand the story, I think I've got to tell you a little bit about Spintronics, which is different from Electronics.
• 50:55
  The only context I have is upspin, downspin.
• 50:58
  That's good.
• 50:58
  Yeah, that's already plenty.
• 51:00
  Okay, that's already plenty because it turns out the electron has both a charge.
• 51:05
  Yes.
• 51:06
  A negative one, let's call it.
• 51:07
  Yes.
• 51:07
  And it's got a spin, but the spin can be both positive one and negative one.
• 51:10
  It could be spinning this way or it could be spinning the other way.
• 51:15
  So conventional electronics, like the ones in your lights, in this computer, everywhere else, right?
• 51:21
  Most of that is exploiting the charge of the electron.
• 51:25
  Only.
• 51:26
  Right?
• 51:26
  It's only exploiting the charge of the electron.
• 51:29
  Current, for example, is the flow of charge, where physical electrons are flowing, right?
• 51:35
  And memory, for example, is the storage of charge, like a one...
• 51:41
  means that your capacitor is charged and a zero means your capacitor is discharged.
• 51:45
  That's how you get memory.
• 51:48
  And that is pretty soon going to run into some problems.
• 51:52
  Okay.
• 51:52
  Because Moore's law is not forever.
• 51:54
  You know about Moore's law, right?
• 51:55
  Yes.
• 51:56
  Like everything doubles.
• 51:57
  every two years yeah whatever it is um well we're we're pretty soon getting to that limit where um moore's laws is running into fundamental physics it's slowing down we can't get because the idea of that you you doubled in the amount of transistors on a chip yeah every 18 to 24 months we're already at like three nanometer chips yeah like tsmc and apple yeah but
• 52:20
  We can't.
• 52:22
  It's hard to get much smaller than that.
• 52:23
  Yeah, it's hard to get much smaller.
• 52:25
  And the problem we're starting to have is power dissipation.
• 52:28
  Okay.
• 52:29
  Because if we have capacitors that are that small, then now we're starting to get into like, we can't store charge for that long on such a small capacitor.
• 52:39
  Pretty soon we're going to have to keep like, you have to keep charging up the capacitor to keep it at that.
• 52:44
  Otherwise it's going to decay and then you're going to lose memory.
• 52:47
  Right.
• 52:47
  So so that's that's one of the things.
• 52:50
  Right.
• 52:50
  Silicon chips consume an insane amount of power.
• 52:54
  Yep.
• 52:54
  Right.
• 52:55
  Which is why everybody's like, oh, like one query in Chachi Bti cost this many gallons of water.
• 53:00
  OK. Yeah.
• 53:00
  Like, yes.
• 53:01
  Crypto has the same problem.
• 53:02
  Yeah.
• 53:03
  Crypto has the same problem.
• 53:04
  Yeah.
• 53:05
  The other the other big thing is called the Von Neumann bottleneck named after John Von Neumann.
• 53:10
  Oh, he did the probes and the bottleneck.
• 53:13
  Oh, dude.
• 53:13
  Von Neumann did like everything.
• 53:15
  Von Neumann was one of those few individuals where other people like Fermi would be like,
• 53:29
  How did you do that?
• 53:30
  Was he a magician more than he was a sage?
• 53:32
  He was.
• 53:33
  He was a magician more than he was a sage.
• 53:35
  But he had its caveats.
• 53:40
  And we can get into that in another episode.
• 53:42
  There was one thing where he proved that the Copenhagen interpretation of quantum mechanics was the only interpretation of quantum mechanics.
• 53:51
  And because it was von Neumann who proved that, everyone else...
• 53:55
  would just not question it.
• 53:57
  Like if somebody were to question it, they'd just be like, yeah, but von Neumann proved that Copenhagen interpretation is the only interpretation of quantum mechanics.
• 54:05
  And that would just settle the debate.
• 54:06
  Right.
• 54:07
  Right.
• 54:07
  Which is why it took like 30 years for someone like, um, like Bell's inequality and for, for someone with different versions, like the, the pilot wave theory and all this other kind of like all these other different versions of quantum mechanics, because literally von Neumann,
• 54:24
  had an incorrect proof to prove that, anyways, the Copenhagen interpretation was correct.
• 54:30
  Anyways, but he was an incredibly smart guy.
• 54:33
  And he actually, he characterized this thing called the Von Neumann bottleneck now, which is this difference between how memory and processing units work.
• 54:43
  Okay.
• 54:43
  Because fundamentally, you know, before we had solid state drives.
• 54:47
  Right.
• 54:47
  We had this.
• 54:48
  And even now that we have solid state drives, we have this separation between RAM and hard disk.
• 54:53
  Right.
• 54:54
  Okay.
• 54:54
  Right.
• 54:55
  Right.
• 54:55
  And the hard disk is where you store your permanent memory.
• 54:58
  The RAM is where you're doing the computation of whatever the thingy that you're doing.
• 55:02
  So, for example, if I want to have a local, if I want to take OpenAI's open source model and run it locally on my computer.
• 55:09
  Mm-hmm.
• 55:10
  I need a Mac that has a lot of RAM.
• 55:14
  Yeah.
• 55:14
  Not necessarily a big hard disk.
• 55:16
  Yeah, not necessarily a big hard disk, but like something that will compute efficiently.
• 55:20
  Correct.
• 55:20
  Like currently now.
• 55:21
  Now.
• 55:22
  Right.
• 55:23
  And so there's a need for a new paradigm where perhaps maybe memory and RAM are the same thing.
• 55:30
  Okay.
• 55:30
  Right.
• 55:31
  Okay.
• 55:32
  And with these increasing demands with AI, big data, and all this other kind of stuff, we want to have a new paradigm where it doesn't cost us that much power to upkeep all of this amount of stuff.
• 55:43
  Makes sense.
• 55:44
  Okay?
• 55:44
  And so that's where the idea of Spintronics comes in.
• 55:48
  Because there's two paths here.
• 55:49
  It's just...
• 55:49
  Increase the amount of power availability is like the brute force way.
• 55:53
  And it's like be more efficient with the power we have is this way.
• 55:57
  Yeah.
• 55:57
  And like even if we were to increase the amount of power availability, like we'd have to increase the size of our computers because we've reached the sort of limit of like how dense we can make stuff before the power consumption per square inch goes away.
• 56:12
  Johnny Ive would not be very happy with that.
• 56:14
  You know what I'm saying?
• 56:15
  Yeah.
• 56:15
  But you know what I'm saying?
• 56:16
  I do know what you're saying.
• 56:17
  Like, it's like now we've, like, sort of plateaued in this landscape.
• 56:20
  Yes.
• 56:21
  Right?
• 56:21
  And so, spintronics is this idea of utilizing the electron's spin in addition to its charge to store information.
• 56:28
  Right.
• 56:28
  And to process information.
• 56:30
  Right.
• 56:30
  Okay.
• 56:31
  Okay?
• 56:31
  Okay.
• 56:32
  So the first big win for Spintronics actually happened way back in like the 1990s when we got hard disks.
• 56:42
  The hard disks that maybe we don't use today because we got solid state hard disks.
• 56:46
  But remember the hard disks like way back when like your computer would do the sound?
• 56:51
  Oh, I remember.
• 56:52
  Yeah, right?
• 56:53
  But there was literally a spinning disk.
• 56:55
  Like it was an electromechanical disk that was spinning, right?
• 57:00
  And that spinning disk represented the, you know, 126 gigabytes of memory.
• 57:06
  And everyone was like, oh.
• 57:07
  126 gigabytes of memory.
• 57:08
  But like that was a big deal back in the day, right?
• 57:12
  And the inventors of this, they actually discovered something called giant magno resistance.
• 57:19
  Okay.
• 57:20
  Giant magneto resistance, okay?
• 57:24
  And it's this idea that what we can do is just like a transistor.
• 57:29
  The way a transistor works is you've got like a state of the transistor that lets current through.
• 57:36
  And then there's a state of the transistor that doesn't let current through.
• 57:39
  And that's going to be your zero and one.
• 57:41
  And that's how you sort of represent data, right?
• 57:44
  Yes.
• 57:45
  What these guys discovered, they were Albert Fert and Peter Grunberg.
• 57:55
  They figured out that if I've got two magnets, okay, that are both oriented in the same direction with an insulator in the middle, then current will pass through it because of this quantum mechanical thing called tunneling where the electron will actually go through a barrier because they're equal magnetization, okay?
• 58:15
  But if they're opposite magnetization, then it's going to get stopped.
• 58:19
  And they were like, okay, that could actually be our zero and one.
• 58:22
  And then what you could do is you could control whether it's a zero and one based on the direction of the magnetic field that a particular piece of physical thingy had.
• 58:36
  Right.
• 58:37
  And so the way that the hard disk actually works is you've got this reader.
• 58:41
  Yes.
• 58:41
  Okay.
• 58:42
  So there's a reader that comes down and it's like reading the hard disk like the hard disk is.
• 58:47
  Yes, exactly.
• 58:47
  It's a record player that's like coming down and the hard disk is spinning and the reader actually has these two these two these two things.
• 58:55
  Okay.
• 58:55
  The top one is rigid.
• 58:57
  It's going to stay fixed.
• 58:58
  The bottom one is going to flip based on the the way the disk is moving.
• 59:03
  Okay.
• 59:04
  So if at the time of the disk, the magnetic field is this way, then the bottom one is going to flip this way and it's going to let through current.
• 59:11
  But as soon as it moves and the other one is this way, it's going to flip this way and then it's going to stop current.
• 59:16
  So now my little record player can read zeros and ones and you can pack these little magnetic things super close and have a hard disk that is electromechanical because it's electrical, but it's also mechanical because it's spinning.
• 59:32
  And then that is going to be my sort of memory.
• 59:36
  And now all of a sudden we went from memory being stored in things that were the size of refrigerators to things that could be stored in the size of a computer, a desktop computer.
• 59:46
  So that was a big deal.
• 59:47
  2007, they won the Nobel Prize for it.
• 59:49
  Well deserved.
• 59:51
  And so that was sort of the first big win for Spintronics.
• 59:54
  Got it.
• 59:55
  It was proof that using both...
• 59:59
  Charge and spin in combination can have production commercial application.
• 1:00:06
  Yeah, exactly.
• 1:00:08
  Right.
• 1:00:09
  So now it's like, okay, can we take this further?
• 1:00:12
  Right.
• 1:00:12
  Right.
• 1:00:13
  Because if we could have a ram that was magnetic, right?
• 1:00:17
  Then all of a sudden, like, you know how, like, you're working on a Word document.
• 1:00:20
  Yeah.
• 1:00:20
  And then the power cuts off and you just lose everything.
• 1:00:23
  Yeah.
• 1:00:23
  Like, I had that during finals week, actually.
• 1:00:25
  Dude, junior year, this one time, I was working on my paper, right?
• 1:00:30
  And I, like, worked.
• 1:00:32
  But like an idiot, I didn't save.
• 1:00:35
  So it didn't go to the hard disk.
• 1:00:36
  Because we still have to manually save.
• 1:00:37
  Yeah.
• 1:00:37
  Yeah.
• 1:00:38
  Because we still have to manually.
• 1:00:39
  There was no auto save.
• 1:00:40
  Right.
• 1:00:40
  Yeah.
• 1:00:40
  Yeah.
• 1:00:40
  Yeah.
• 1:00:41
  Yeah.
• 1:00:41
  So I didn't save.
• 1:00:42
  And then the power cuts off for some fucking random reason.
• 1:00:45
  And then all of my stuff was gone.
• 1:00:50
  I literally, like, I'm feeling...
• 1:00:52
  Right, because the RAM didn't store it in the hard disk, but the RAM is a bunch of capacitors.
• 1:00:58
  So if you lose power, then the capacitors go... And then I lose everything.
• 1:01:03
  And I log back in, the computer's like, do you want to go back to the previous save?
• 1:01:07
  And it's like from, like, yesterday.
• 1:01:12
  So imagine if we had a magnetic ram where the memory was stored in the polarization of these magnets.
• 1:01:20
  Now if I take out the power, magnets are going to maintain their polarization.
• 1:01:25
  Right.
• 1:01:26
  So I could have this like way without like this non-volatile.
• 1:01:29
  It's called volatility in a memory.
• 1:01:31
  But I could have a non-volatile memory.
• 1:01:34
  Yes.
• 1:01:34
  Because it's stored in the physical orientation of the magnets.
• 1:01:37
  Yes.
• 1:01:37
  Right.
• 1:01:38
  Yes.
• 1:01:38
  Okay.
• 1:01:39
  Yes.
• 1:01:40
  So that's a great goal.
• 1:01:41
  That's very...
• 1:01:41
  And that's what we want.
• 1:01:44
  And then we can actually bridge this gap between memory and processing.
• 1:01:48
  Right?
• 1:01:48
  Because now all of a sudden, the same paradigm that we're using for memory, we can start using for processing.
• 1:01:54
  And it could be this like bridge between the two.
• 1:01:56
  And so now we don't have this von Neumann bottleneck.
• 1:01:59
  Yep.
• 1:01:59
  Okay?
• 1:02:00
  Yeah.
• 1:02:00
  So this is great.
• 1:02:01
  We want this.
• 1:02:02
  Yes.
• 1:02:02
  We want this.
• 1:02:03
  Yes.
• 1:02:03
  Okay.
• 1:02:04
  There are problems.
• 1:02:06
  As there always are.
• 1:02:08
  There are problems when it comes to what we want to do is we want to reliably switch the magnetization state.
• 1:02:14
  Yes.
• 1:02:14
  Right?
• 1:02:14
  We want to be able to say, okay, this particular unit has a magnetization state of one.
• 1:02:20
  We want to reliably switch it to zero.
• 1:02:22
  Okay?
• 1:02:23
  How do we do that?
• 1:02:24
  Well, usually what we do is we use this thing called spin orbit torques, which use this thing called the spin hull effect.
• 1:02:31
  Okay.
• 1:02:31
  Okay.
• 1:02:32
  And the way that you can imagine this is basically electron spins when you put it through a heavy metal, the heavy metal has a bunch of electron spins that are moving up, moving down, right?
• 1:02:43
  Uncorrelated.
• 1:02:45
  When you put a current through it,
• 1:02:47
  the spin up ones are going to go in one direction and the spin down ones are going to go in the other direction.
• 1:02:51
  The way you can think about this is kind of like the Magnus effect.
• 1:02:55
  If you've ever seen the Magnus effect, you've got a spinning.
• 1:02:58
  There's like these videos of like a spinning basketball that's like thrown down.
• 1:03:02
  And because it's spinning, the way that it interacts with the air around it makes it move in one direction or the other.
• 1:03:08
  Right.
• 1:03:09
  So if it's spinning this way, it's going to move in one direction.
• 1:03:11
  If it's spinning the other way, it's going to.
• 1:03:12
  moving the other direction.
• 1:03:13
  You know where I've seen this is in all those Dude Perfect videos where they try to throw a basketball off of like the Hoover Dam, right?
• 1:03:20
  And they spin it.
• 1:03:22
  in a particular way.
• 1:03:23
  That's exactly right.
• 1:03:24
  That's exactly right.
• 1:03:25
  That's the Magnus effect.
• 1:03:26
  Yes.
• 1:03:26
  Right?
• 1:03:26
  So the spin orbit torque is literally like the Magnus effect happening with electrons and an electric field, right?
• 1:03:34
  You're driving a current this way and the spin in one direction is going to move it this way and the spin down is going to move it the other way.
• 1:03:39
  So what you can do is you can have like this heavy metal layer where you're putting the current through.
• 1:03:44
  Yes.
• 1:03:45
  and a ferromagnetic layer, which is where the magnets are.
• 1:03:48
  And in a ferromagnet, all of the spins are moving, are in the same direction, right?
• 1:03:53
  That's what gives it its big magnetic field, right?
• 1:03:57
  All of the spins are in the same direction, so they all add up to give it a magnetic field.
• 1:04:01
  So now if underneath I have this like heavy metal layer, and I have the spins, the spin going up is gonna go towards the ferromagnetic layer, and it's gonna apply a torque
• 1:04:12
  On the ferromagnetic layer and it's going to change the ferromagnetic layers magnetization.
• 1:04:17
  So all of the magnetic fields in the ferromagnet are going to switch.
• 1:04:20
  Yes.
• 1:04:21
  Okay.
• 1:04:21
  So that's usually how we want to manipulate the magnetic field of these little devices.
• 1:04:27
  Right.
• 1:04:28
  Makes sense.
• 1:04:28
  It's like, okay, you want a one.
• 1:04:29
  I want to switch it to a zero.
• 1:04:31
  I'm going to poke it underneath with this current.
• 1:04:34
  The current is going to induce the spin orbital effect.
• 1:04:37
  And that thing is going to switch the ferromagnetic layer on top.
• 1:04:40
  And then now all of a sudden the thing that was a one is now a zero.
• 1:04:43
  Okay.
• 1:04:43
  Okay.
• 1:04:44
  The problem with this is there's a lot of dissipation.
• 1:04:46
  Okay.
• 1:04:47
  There's a lot of stuff called Joule heating, which is just like the friction.
• 1:04:51
  Okay.
• 1:04:51
  Yeah.
• 1:04:52
  There's a lot of friction that's going on.
• 1:04:53
  It has nothing to do with vapes.
• 1:04:54
  Yeah.
• 1:04:54
  Yeah.
• 1:04:55
  Nothing to do with vapes.
• 1:04:56
  Joule meaning J-O-U-L-E. Like the Joule of energy.
• 1:05:00
  Yes.
• 1:05:01
  Although I'm pretty sure the vape is named.
• 1:05:03
  You know, it might be.
• 1:05:04
  That's something that we should research.
• 1:05:06
  Yeah.
• 1:05:08
  There's also a loss of angular momentum because like all of this, like, you know, just like julieating, the friction is going to lose a lot of the spin, right?
• 1:05:15
  Yes.
• 1:05:16
  Yes.
• 1:05:16
  So what these guys did, what these researchers from Korea, they actually used the dissipation of spin to their advantage.
• 1:05:28
  Yeah, it's something that no one really had thought of before.
• 1:05:31
  Everyone's trying to minimize the dissipation of friction, but they're using the friction to their advantage.
• 1:05:37
  They're actually leveraging the friction.
• 1:05:40
  They had this idea of using the intrinsic spin currents of the ferromagnet itself, okay?
• 1:05:47
  Because there's two types of currents, okay?
• 1:05:49
  There's the electric current, which is literally electrons moving.
• 1:05:53
  But you can also have a different type of current, which is a spin current, okay?
• 1:05:57
  So a normal current is just electrons moving in this way.
• 1:06:00
  There's more electrons moving this way than this way.
• 1:06:03
  So there's charge transferred.
• 1:06:05
  A spin current is where the...
• 1:06:08
  Electrons spinning this way are moving this way and the electrons spinning this way are moving the other way Okay, so now you have the total electric current is zero Because the number of electrons moving left and the number of electrons moving right are exactly the same So there's no charge transfer But there's a transfer of angular momentum because this the spin up is going this way and the spin down is going the other way Right, so you can now start affecting magnetization.
• 1:06:34
  Yes without actually affecting charge.
• 1:06:37
  Yes, so
• 1:06:38
  Right.
• 1:06:38
  Yes.
• 1:06:38
  And so what they did was they said, OK, like what I can do is I can have a ferromagnetic layer in the middle, which has all of the spins aligned in a certain direction.
• 1:06:47
  And I'm going to I'm going to I'm going to run a current through that.
• 1:06:51
  OK, now the spin.
• 1:06:55
  The spin up is going to go one way, the spin down is going to go the other way.
• 1:06:57
  Okay.
• 1:06:58
  And I'm going to surround it with an insulator on the top and bottom.
• 1:07:01
  Okay.
• 1:07:02
  But one of these insulators is going to be different than the other.
• 1:07:05
  The one on the top is just going to be a normal insulator.
• 1:07:07
  It doesn't like charge.
• 1:07:08
  It doesn't like spin.
• 1:07:09
  Yes.
• 1:07:10
  Okay.
• 1:07:10
  So all of the spin that goes up is going to just bounce right off.
• 1:07:14
  Right.
• 1:07:15
  Okay.
• 1:07:15
  The one on the bottom is going to be something called an anti-ferromagnet.
• 1:07:19
  Okay.
• 1:07:19
  Okay.
• 1:07:20
  So a ferromagnet is when all of the spins are aligned.
• 1:07:23
  Yes.
• 1:07:23
  An anti ferromagnet is when all of the spins are exactly alternating.
• 1:07:28
  Okay.
• 1:07:29
  So it doesn't have a big magnetization.
• 1:07:32
  Yeah.
• 1:07:33
  But like it can act like a spin sink.
• 1:07:35
  Mm hmm.
• 1:07:36
  You know what I'm saying?
• 1:07:37
  I do.
• 1:07:37
  It can act like an angular momentum sink.
• 1:07:39
  So now when I put it through the middle and I have all these spins going everywhere, the ones that go to the top that are of a particular spin are just going to bounce right off.
• 1:07:47
  But the ones that are going to the bottom are just going to sink into this anti-ferromagnet.
• 1:07:51
  And so the stuff that goes to the top, it's going to bounce right back.
• 1:07:54
  And it's going to start changing the spin of the ferromagnet in the middle.
• 1:07:58
  Yes.
• 1:07:59
  Yes.
• 1:07:59
  So now using spin dissipation, which is all of the spins are dissipating at the bottom using this friction.
• 1:08:06
  We're actually taking the leftover stuff and we're flipping the spin.
• 1:08:10
  Yes.
• 1:08:11
  Yes.
• 1:08:12
  Yes.
• 1:08:12
  It's so it's so interesting, dude.
• 1:08:14
  That's so it was it was a way in which to.
• 1:08:18
  find these sort of combinatorial dynamics in a way where it's like we're just like now engineering like what happened.
• 1:08:27
  Yeah.
• 1:08:28
  Such that we get an intended outcome.
• 1:08:30
  Yeah.
• 1:08:31
  And the intended outcome now is instead of instead of the spin dissipation just being a loss.
• 1:08:36
  Yeah.
• 1:08:37
  Yeah.
• 1:08:37
  You now make it a functional component.
• 1:08:38
  Now the loss is actually the point.
• 1:08:40
  Right.
• 1:08:41
  Right.
• 1:08:42
  It's crazy, dude.
• 1:08:43
  The loss, the dissipation is actually the point of the whole study.
• 1:08:47
  Right.
• 1:08:48
  And from this, they've actually made a device that is up to three times more energy efficient.
• 1:08:53
  Because they're harnessing the loss as a feature, not a bug.
• 1:08:57
  Right, right.
• 1:08:59
  It's very nice.
• 1:08:59
  This is such a good point about why framing and perception matters in terms of like, because the initial context is like, oh, this is just functionally a loss in the system.
• 1:09:12
  And there's nothing we can do about it.
• 1:09:13
  And everyone's worried about minimizing it.
• 1:09:15
  Right.
• 1:09:16
  Everyone's worried about like, how do we get the julianing down?
• 1:09:18
  How do we get the dissipation down?
• 1:09:20
  And these guys are like, no, no, no.
• 1:09:21
  Actually, the more the dissipation.
• 1:09:22
  Right.
• 1:09:23
  The better the fidelity in my switching from zero to one.
• 1:09:26
  It's pretty crazy.
• 1:09:27
  So it's like it's using the dissipation as almost like this, not a validation system, but it can create a consistency.
• 1:09:36
  Now, I think what's so interesting about this is this is kind of goes back to why it's important to be able to have so many people attacking the same problem from different directions.
• 1:09:48
  Yeah.
• 1:09:49
  Because the problems are so open-ended and like the blue ocean.
• 1:09:52
  Yeah, yeah, yeah, yeah.
• 1:09:53
  It's like there's no like playbook for Spintronics, right?
• 1:09:58
  Because it's such a new concept, right?
• 1:10:01
  Yeah.
• 1:10:02
  Do you think that this is going to bring a – because of the – I think this could be big.
• 1:10:08
  So even if just from the – so let's take out commercial application for a second.
• 1:10:13
  Even just from now inspiring other research institutions to be like – It's a proof of concept that like, okay, this is a total different avenue that we've not even bothered exploring.
• 1:10:24
  Right.
• 1:10:24
  that now we can start exploring.
• 1:10:26
  And there's some viability there.
• 1:10:27
  Yeah, I can definitely see some research labs now starting to take this more seriously.
• 1:10:32
  So if you're a future PhD candidate, this is an area that... Yeah, this is really cool.
• 1:10:36
  And the other thing, I mean, the commercial applications are actually really cool because the architecture that they used is super simple.
• 1:10:42
  It's a single ferromagnetic layer and a single anti-ferromagnetic layer, which is actually super easy to construct with normal silicon fabs.
• 1:10:51
  So it's not like it's not like some exotic material that they had to dig out of the ground or something.
• 1:10:57
  Right.
• 1:10:57
  Like this is just like nickel, silicon oxide, like stuff that stuff that normal like chips are made out of.
• 1:11:05
  Like so it's not it's not that exotic.
• 1:11:08
  Yeah.
• 1:11:08
  To like try to now replicate this and make this bigger and make this smaller and blah, blah, blah.
• 1:11:13
  So to extrapolate from that, so kind of what you're saying is if I already am TSMC or I'm Foxconn and I'm assembling Apple chips or all these other chips and I have this machinery infrastructure.
• 1:11:25
  Yeah, it's not too difficult.
• 1:11:28
  I can potentially, there's some reuse of my existing infrastructure from a mass manufacturing scale perspective where it's like we change order of operations, some of the ingredients.
• 1:11:39
  Yeah, yeah.
• 1:11:40
  It's like viable.
• 1:11:42
  It's viable.
• 1:11:42
  In some sense.
• 1:11:43
  Yeah, you know, it's like, I mean, there's still a lot more that needs to go on in terms of connecting this to modern infrastructure and like current computing infrastructure and things like that.
• 1:11:52
  But the viability of this is not like something that's like really far ahead.
• 1:11:57
  We don't have to rebuild the entire stack.
• 1:11:59
  No, we don't.
• 1:12:00
  Yeah.
• 1:12:00
  In order to.
• 1:12:01
  That is actually a very important.
• 1:12:04
  Yeah.
• 1:12:04
  Yeah.
• 1:12:04
  I think it's an important point.
• 1:12:05
  Yeah.
• 1:12:05
  Point.
• 1:12:07
  Fascinating.
• 1:12:07
  That's not where I thought we were going to go with our K-pop demon hunters.
• 1:12:12
  Yeah.
• 1:12:13
  Starting point.
• 1:12:14
  But using electron spin to an advantage, one man's trash.
• 1:12:20
  is another man's treasure.
• 1:12:21
  That's exactly what this is.
• 1:12:22
  Yep.
• 1:12:22
  Which is so fascinating.
• 1:12:25
  We're going to go to our last story.
• 1:12:28
  It's not about billionaires racing to Mars.
• 1:12:30
  No.
• 1:12:30
  It's not that important.
• 1:12:31
  They're not the real heroes.
• 1:12:33
  No.
• 1:12:33
  The real heroes are the scientists racing to save bees.
• 1:12:39
  And...
• 1:12:40
  The headline on this story coming out of the University of Oxford is that scientists make superfood that could save honeybees.
• 1:12:48
  This was in the BBC from our friends across the pond.
• 1:12:52
  And the byline is scientists have developed a honeybee superfood that could protect animals against the threats of climate change and habitat loss.
• 1:13:00
  So all I know about bees is what I see on all these memes and trending stories about we got to save the bees because they're such a critical part.
• 1:13:09
  of like the circle, the circle of life.
• 1:13:13
  And if the bees go away, there's like a collapse of the ecosystem that arises.
• 1:13:17
  And agriculture, like human agriculture.
• 1:13:19
  That sort of arises out of that.
• 1:13:21
  So this is like an important, like this is, how does this connect to my everyday life?
• 1:13:25
  Like this matters a lot.
• 1:13:27
  Like your food.
• 1:13:28
  Like if you like food, you're gonna wanna save the bees.
• 1:13:32
  So what exactly is going on here?
• 1:13:35
  Yeah.
• 1:13:36
  Bees are extremely important.
• 1:13:37
  And I think it's urgent for us to address this.
• 1:13:41
  Okay.
• 1:13:42
  Because we are facing like a death spiral when it comes to how our agriculture sustains itself.
• 1:13:51
  I have some numbers for you.
• 1:13:53
  35% of the world's food crops depend on animal pollinators.
• 1:13:57
  Bees are the things that take the female part of one flower, put it into the male part of another flower, and then we get fruit.
• 1:14:07
  So anything that has fruit really requires pollinators.
• 1:14:10
  Something like one in three bites of human food requires a pollinator.
• 1:14:16
  The economic value is something like $500 billion.
• 1:14:19
  In the U.S. alone, it's something like $30 billion annually.
• 1:14:24
  And a single honeybee's pollination, like a single honeybee colony's pollination, is worth 100 times more to the community than it is to the beekeeper.
• 1:14:35
  Oh, interesting.
• 1:14:36
  Okay.
• 1:14:37
  Like we've seen, you know, when we go out to Los Olivos and all these other guys, like we see these bee communities, right?
• 1:14:45
  Like, yeah, that bee colony is worth a hundred times more than it is to the bee colonies.
• 1:14:51
  So instead of focusing on cutting programs, Doge should have focused on saving the bees.
• 1:14:56
  Yeah.
• 1:14:57
  If only, right?
• 1:14:57
  We would have saved more money.
• 1:14:59
  If only.
• 1:15:00
  Yeah.
• 1:15:01
  And those bee populations are declining.
• 1:15:04
  Okay.
• 1:15:04
  Something like 40% per year.
• 1:15:06
  Like rapidly.
• 1:15:07
  Rapidly, dude.
• 1:15:09
  It's the losses in 2025 are projected to be around 60 to 70%.
• 1:15:14
  Okay.
• 1:15:14
  And this comes from a variety of factors.
• 1:15:16
  It's environmental, climate change, like warmer temperatures are not good for the bees.
• 1:15:21
  Plants bloom at times the bees are not active.
• 1:15:25
  And one of the other big ones is a core nutritional gap between when you have these like colonies that are sort of reared by beekeepers.
• 1:15:36
  there's a nutritional gap between what the beekeepers can give to the bees and what they actually require.
• 1:15:44
  And it's been really hard to actually bridge that gap because what they're really lacking is these things called essential sterols.
• 1:15:52
  It's like cholesterol and other types of fatty acids that are really hard to synthesize in an industrial manner.
• 1:15:59
  Because a lot of times what these beekeepers do is they're not relying on the flowers to feed the bees.
• 1:16:07
  They have artificial feed.
• 1:16:09
  But you're not able to fulfill the entire nutritional needs.
• 1:16:15
  And that is what this...
• 1:16:17
  paper is addressing.
• 1:16:18
  What they did was they bioengineered yeast to make all of the essential oils that bees require.
• 1:16:24
  This is, okay, fascinating, right?
• 1:16:26
  So we have a key issue, the collapse of the bee population, which is fundamental to the entire agriculture and ecosystem infrastructure that enables human life as we know today to exist.
• 1:16:36
  We currently have a variety of very sort of impactful, like the job that beekeepers are doing is a valuable addition to trying to do something about the problem.
• 1:16:47
  Yeah.
• 1:16:47
  But they're fundamentally limited because the fee that they're providing is not sufficient for the needs of these populations.
• 1:16:56
  Exactly.
• 1:16:56
  We're trying to continue to sustain.
• 1:16:57
  Yeah, yeah.
• 1:16:58
  And so...
• 1:17:00
  Again, synthetic biology came to the rescue.
• 1:17:03
  What this team at Oxford did was they took yeast, a bio-safe yeast, so something that's okay for consumption, and it had high levels of acetyl-CoA, which is acetyl-CoA enzyme A.
• 1:17:17
  It's something that every molecular biology person is going to know about.
• 1:17:21
  It's something that's used in the Krebs cycle.
• 1:17:23
  It's something used...
• 1:17:24
  Like it's like essential for energy in a cell.
• 1:17:28
  And what they did was they commandeered this process using our favorite thing, CRISPR-Cas9.
• 1:17:33
  Yeah.
• 1:17:34
  Yeah.
• 1:17:34
  So they got CRISPR-Cas9.
• 1:17:35
  And what they did was they got genes from green phytoplankton, tomatoes, potatoes, because these are the genes that make these particular sterols, right?
• 1:17:45
  These genes.
• 1:17:45
  Beans, potatoes, tomatoes, chicken, turkey.
• 1:17:50
  Yeah, exactly.
• 1:17:51
  They snipped out these genes using CRISPR-Cas9.
• 1:17:54
  They put it inside the yeast.
• 1:17:55
  And then the yeast is now starting to make these essential oils in some sense for the bees.
• 1:18:01
  And then what they could do is they could heat inactivate those yeast, dry it up.
• 1:18:05
  And then that would become feed for the bees.
• 1:18:09
  Right.
• 1:18:09
  And it also provides proteins for the bees, lipids, vitamins.
• 1:18:13
  It became this like one fits all product for bee feed.
• 1:18:18
  And the results are, dude, absolutely insane.
• 1:18:21
  The bees that had this particular feed, 15 times more viable pupae.
• 1:18:27
  Like 15 times more viable.
• 1:18:29
  15X.
• 1:18:29
  15X.
• 1:18:30
  Not a 15%.
• 1:18:31
  No, not 15%.
• 1:18:32
  15X.
• 1:18:33
  This is a paradigm shift.
• 1:18:34
  Yeah, no.
• 1:18:35
  This could, like, save our ass.
• 1:18:37
  This is a really big deal.
• 1:18:39
  This could... And rich colonies continued to rear the brood for, like, 90 days up until the experiment ended.
• 1:18:47
  And then they were like, okay, I guess we got our data.
• 1:18:50
  Because these guys were just going at it, right?
• 1:18:52
  And before, the pupae, the larval stage, was the part that was getting affected.
• 1:18:57
  Right.
• 1:18:57
  Because they're the ones that, as they grow, they really require these nutrients.
• 1:19:02
  I mean, it's not the baby formula versus breastfeeding.
• 1:19:06
  No, but this is even worse.
• 1:19:07
  This is like, at least baby formula has all the essential ingredients.
• 1:19:11
  Fair.
• 1:19:11
  Right?
• 1:19:12
  This didn't even have.
• 1:19:14
  It's like all you're eating is rice.
• 1:19:16
  You're going to get wrecked.
• 1:19:17
  Yeah.
• 1:19:17
  You know?
• 1:19:17
  Yeah, yeah, yeah.
• 1:19:18
  Yeah, this this reminds me or has a little bit of a correlation to what the the new company that Friedberg, David Friedberg.
• 1:19:31
  Oh, yeah.
• 1:19:32
  Creating around trying to increase the yield of crops.
• 1:19:35
  It's different.
• 1:19:36
  It's different, but it's similar.
• 1:19:37
  Yeah.
• 1:19:38
  Yeah.
• 1:19:38
  It's precision sort of nutrition.
• 1:19:40
  Right.
• 1:19:41
  Yeah.
• 1:19:41
  Right.
• 1:19:41
  At the at the sort of like, you know, the level of what you're trying to give.
• 1:19:46
  Human sources in this case.
• 1:19:47
  Yeah.
• 1:19:47
  Yeah.
• 1:19:48
  But like we can actually go in.
• 1:19:51
  Finagle.
• 1:19:52
  Yeah.
• 1:19:53
  And and increase outcomes.
• 1:19:55
  Positive outcomes.
• 1:19:57
  15x is 15x is crazy, dude.
• 1:20:00
  Crazy.
• 1:20:01
  Like this is this could be a game changer for bee populations worldwide.
• 1:20:04
  And the other big advantage is like, you know, when you have beekeepers with bee colonies like this.
• 1:20:10
  they are constantly competing with native bee populations and native pollinators to get the food.
• 1:20:17
  Now, if we've got a complete diet for these bee colonies, then the native population that is like there in the ecosystem doesn't have to compete with the agricultural population that is there to pollinate all this stuff, right?
• 1:20:29
  Like there's an ecosystem balance that is happening.
• 1:20:33
  Yes.
• 1:20:33
  That is like even better, right?
• 1:20:35
  Because then, yeah, it's...
• 1:20:38
  there's currently this resource scarcity.
• 1:20:41
  Exactly.
• 1:20:42
  And so the sort of farm-raised versus wild have to compete in that resource scarcity environment.
• 1:20:47
  Exactly, but now they don't have to.
• 1:20:49
  That's a big, that's actually.
• 1:20:50
  That's a really big one for me, actually.
• 1:20:53
  No, that's a really big deal.
• 1:20:54
  Right, like.
• 1:20:54
  That's a really big deal.
• 1:20:55
  Yeah.
• 1:20:57
  I think it's really cool.
• 1:20:58
  I mean, again, Christopher Cas9, dude.
• 1:21:00
  I think this might be the – It's stuff that you'd never think about.
• 1:21:03
  I think we've covered it in at least half of our stories.
• 1:21:06
  Yeah, yeah.
• 1:21:07
  And every time it's, like, so cool.
• 1:21:09
  And it's also just, like, one little variable in, like, the story is something totally not related.
• 1:21:15
  Yeah, yeah.
• 1:21:16
  But without it, it wouldn't work.
• 1:21:17
  It wouldn't work.
• 1:21:18
  And, again, this is the compounding value of these, like, key insights similar to, I think, what was the first story we talked about?
• 1:21:28
  the key insight on the second story, the viruses and bacteria, is gonna have all these tendrils.
• 1:21:34
  Exactly.
• 1:21:35
  That we might hear a story about saving the bee population because we'd use the same virus bacteria.
• 1:21:40
  Yeah, yeah.
• 1:21:41
  I'm being a little facetious.
• 1:21:42
  No, but totally, dude.
• 1:21:44
  Like the bacteria virus thing could be like a chimera that could be used for all sorts of random crap.
• 1:21:50
  Yeah.
• 1:21:50
  So this is a real superfood.
• 1:21:52
  I think it's really cool.
• 1:21:53
  We need to save the bees.
• 1:21:54
  Yeah, I love the bees, right?
• 1:21:56
  I don't like getting stung.
• 1:21:58
  Right.
• 1:21:58
  And when a bee comes near me, I'm like, but I like bees and what they do.
• 1:22:04
  Yes.
• 1:22:05
  Right?
• 1:22:05
  And we understand their importance to the ecosystem.
• 1:22:07
  Yeah, yeah, yeah, exactly.
• 1:22:08
  Yeah.
• 1:22:09
  It's for the entirety of the planet that we love.
• 1:22:12
  And I think this sort of just brings up a last note we can wrap up with, which is all of these stories only get enabled
• 1:22:22
  in the world we live in by funding.
• 1:22:23
  Yes.
• 1:22:24
  Like, this stuff costs money.
• 1:22:27
  Exactly.
• 1:22:27
  And we've sort of had a re-underwriting of the importance of fundamental science research, particularly in the U.S. Yeah, it's been really bad.
• 1:22:34
  It's been tough.
• 1:22:39
  As California natives, we are home to, in the US, the largest population of Nobel laureates, patents, research institutions.
• 1:22:49
  We really are the driver of a variety, there's other places obviously, but we are one of the key players in the state of California to drive this fundamental research that is literally going to be species and individual life and family saving outcomes.
• 1:23:07
  in our lifetime, right?
• 1:23:10
  And one of the challenges that we've seen is that the University of California California research grant system has, there's been an attempt to gut it from its funding.
• 1:23:21
  And we'll just end on this story that just came out in the last week.
• 1:23:25
  You know, this has been a debacle in the courts because in the US we're a big legal system.
• 1:23:30
  The Ninth Circuit,
• 1:23:32
  has now denied the federal government's attempt to stop the reinstatement of the University of California research grants, at least a third of that funding, which is probably in the order of about hundreds of millions of dollars, that was frozen and was potentially just poof, gone away, that the courts have said that's not going to happen.
• 1:23:54
  I just and you know, I mean, if I may, I just got to say like it, this, this story actually makes me appreciate America a little bit because I come from a country, right?
• 1:24:04
  I grew up in India for a minority of my early life, right?
• 1:24:09
  Like until I was 12 years old.
• 1:24:11
  And in the in in countries like that, the federal government is basically a say, I say what happens and then it happens.
• 1:24:21
  Yes.
• 1:24:21
  But here, because of the federalism and this distribution of powers that is still somehow intact, despite the president's attempts to undermine it, right?
• 1:24:31
  We've got a judicial system now that can just be like, nah, you're not...
• 1:24:36
  I ain't jocking that.
• 1:24:37
  Yeah, you're not doing that.
• 1:24:39
  And then now it just got reversed.
• 1:24:40
  And everyone's like, okay, cool, we get funding back.
• 1:24:42
  Right.
• 1:24:42
  You know, it's like not...
• 1:24:45
  The resilience of the American system to little tiny blips up or down.
• 1:24:51
  I think that's great.
• 1:24:52
  And yeah.
• 1:24:54
  If you've never read the Federalist Papers or you don't really understand.
• 1:24:58
  Alexander Hamilton.
• 1:25:01
  If you've never been in the room where it happens, there's really interesting intellectual thought that went into the fundamental structures that ultimately created the system we have today.
• 1:25:12
  And a lot of it was written down.
• 1:25:14
  Yeah.
• 1:25:15
  Thank goodness.
• 1:25:15
  Thank goodness.
• 1:25:16
  Yeah.
• 1:25:16
  Because we can actually see.
• 1:25:17
  And we take it seriously.
• 1:25:18
  Yeah.
• 1:25:19
  Yes.
• 1:25:19
  As a country.
• 1:25:19
  Yes.
• 1:25:20
  It's like, no, you can't.
• 1:25:21
  It says right here, you can't do that.
• 1:25:23
  Right.
• 1:25:24
  And it's going to continue to be, as always, you know, one of the planet's greatest experiments ever.
• 1:25:30
  It will always ebb and flow.
• 1:25:32
  Yeah.
• 1:25:33
  And of course, like this Ninth Circuit is going to go up.
• 1:25:35
  Probably Trump is going to like come back.
• 1:25:37
  Like come back.
• 1:25:38
  It's going to go to the Supreme Court and then we're going to be gritting our teeth again.
• 1:25:41
  But like the process is working.
• 1:25:44
  Right.
• 1:25:44
  Right.
• 1:25:44
  The you know, I know there's a lot of anti bureaucracy and anti institutional thinking nowadays, which there does need to.
• 1:25:51
  Yeah, that's fine.
• 1:25:52
  And they're not perfect and they can always be better.
• 1:26:00
  Exactly.
• 1:26:01
  Total sort of chaos.
• 1:26:04
  Like imagine if we'd had no checks and balances.
• 1:26:06
  Right.
• 1:26:07
  How far down the rabbit hole we would have gone.
• 1:26:09
  Right.
• 1:26:10
  It's insane.
• 1:26:10
  Right.
• 1:26:12
  Just a nice little pseudo mystery box because we focus so much on like breaking fundamental research.
• 1:26:19
  Yeah.
• 1:26:19
  But it couldn't be possible without.
• 1:26:21
  It would not be possible without federal funding because it's not yet commercially viable.
• 1:26:26
  No.
• 1:26:26
  Private entity, private corporations.
• 1:26:30
  Some aspects of this stuff they will do if it's very specific to their, like, use case.
• 1:26:34
  But the majority of it, it's too early.
• 1:26:36
  And we otherwise... Again, we talked about a story even today where this sort of using electrons spin to an advantage.
• 1:26:43
  No.
• 1:26:44
  Like, that's not getting...
• 1:26:45
  You know, that's been almost all academics.
• 1:26:47
  Spintronics.
• 1:26:48
  Meta, Apple, Amazon.
• 1:26:50
  They're waiting for it.
• 1:26:51
  They're waiting.
• 1:26:52
  And then they're going to be like, oh, I can do that.
• 1:26:54
  And then they're going to implement it.
• 1:26:55
  So it does really matter for all the things we care about and all the things we're going to need as life on planet Earth continues to get harder and harder for a number of reasons.
• 1:27:06
  Yeah.
• 1:27:07
  Fascinating stories.
• 1:27:08
  We talked about new supernovas, an unforeseen buddy cop movie between viruses and bacteria for cancer treatments, figuring out how spin electrons can power the next generation of tech, and saving the bees.
• 1:27:25
  with superfood.
• 1:27:28
  It's just, again, every week I'm just like mind blown.
• 1:27:31
  And if you love getting into the weeds and talking about stories from First Principles, please join us next week.
• 1:27:38
  I am your host again, Lester Nare, joined as always by our co-host and resident PhD, Krishna Chowdhury.
• 1:27:47
  This is From First Principles.
• 1:27:49
  We will see you all next week.