China’s AI Breakthrough, Time Crystals, Hidden Viruses, & Brightest Cosmic Signal (EP. 9)

Lester Nare and Krishna Choudhary return for Episode 9 of From First Principles, breaking down the latest breakthroughs across AI, physics, biology, and astronomy. From China’s stunning AI leap with DeepSeek to time crystals you can actually see, hidden viruses in our DNA, and the brightest fast radio burst ever detected—this episode spans the cutting edge of science and its global implications. Summary • China’s DeepSeek AI model: geopolitics, open science, and the future of AI competition • Time crystals at room temperature: from theoretical physics to practical cryptography • Hidden viruses in our DNA: new structures decoded with potential for cancer & autoimmune therapies • Brightest fast radio burst: unraveling cosmic mysteries with new telescopes and James Webb Show Notes • Nature: China’s DeepSeek AI paper (1) • Nature: China’s DeepSeek AI paper (2) • Nature: Time crystals with liquid crystals • Science Advances: Viral protein structure discovery • Astrophysical Journal Letters: Brightest FRB

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Lester Nare?

  Hello Internet, this is your captain speaking Lester Nare, joined as always by my co-host and our resident PhD Krishna Choudhary. This is from First Principles. We have a great episode for you this week. We're going to cover four stories in AI, space and immunology, starting with a new story out of China's DeepSeek, which says its AI model costs just $294,000 to train. This is really important and we're going to go a deep dive into why. Followed up by our second story. Sounds like we may have discovered the Ocarina of Time. We may need to get Zelda involved. As scientists just made the first time crystal that you can see. I'm really interested in talking about that one. Yeah, that's cool. The third story is about hidden viruses in our DNA.

• 0:45Lester Nare?

  That could be medicine's next big breakthrough. And we're going to end with space with the brightest, fast radio burst ever detected and how it could help us solve an enduring cosmic mystery. This is from First Principles.

• 1:17Lester Nare?

  My friend. How's it going? Episode nine. Episode nine, 10K followers on Instagram. Woo! We still haven't been shut down by the FCC yet. Yeah, yeah, yeah, yeah. It's coming though. It's coming. We're talking too much science, it's coming. It's coming. They're going to defund us and then ban us. But before they do, we're going to talk about some great stories. The first one, we always end up touching on AI. Yeah. There's a lot of research going on in AI in a variety of ways. Yep. And our first story was a story in Reuters that also had two Nature papers that were related to it. Yeah. The headline on this is China's DeepSeek says its AI model has hit a cost of just $294,000 to train.

• 2:02Lester Nare?

  The sort of byline is in a paper that is likely to reignite the debate over Beijing's place in the race to develop AI. Yeah. This sort of cost, which is significantly lower than the figures that we see in the US. And I know we've talked about DeepSeek and all of this quite a bit. Yeah.

• 2:21Krishna Choudhary?

  Uh, it's a, it's a crazy model and the fact that the team like put out a peer review paper. You know, no one else has done that in the field of AI. Like gone to nature and put out, okay, this is how we trained. This is how we did it. You know, they're, they're actually, it's, it's kind of crazy that China is setting the precedent for open science in the field of AI.

• 2:45Lester Nare?

  Mm hmm.

• 2:45Krishna Choudhary?

  Right?

• 2:46Lester Nare?

  It is very interesting and not only one, but two papers in, in nature, main brand, not, not a nature sub, you know, sub category.

• 2:54Krishna Choudhary?

  This isn't IEEE. This isn't even like, you know, NERIPS. This is nature.

• 2:59Lester Nare?

  And you know, what, what I thought would be helpful, uh, we're going to do sort of two aspects on this story.

• 3:04Krishna Choudhary?

  Yeah.

• 3:04Lester Nare?

  Um, folks might have seen the deep seek news, you know, earlier in the year when there was sort of a, a big outcry about it.

• 3:11Krishna Choudhary?

  Yeah, they released in January, I think.

• 3:13Lester Nare?

  Yes.

• 3:13Krishna Choudhary?

  And then all of our stocks failed.

• 3:15Lester Nare?

  Yes, it was a big deal.

• 3:16Krishna Choudhary?

  Yeah.

• 3:17Lester Nare?

  Um, but January wasn't the start of this great power war over AI.

• 3:22Krishna Choudhary?

  Right.

• 3:23Lester Nare?

  And I thought it would be good to just go over a couple of beats on the sort of geopolitical context that this research paper kind of came out in.

• 3:31Krishna Choudhary?

  Yeah, yeah.

• 3:32Lester Nare?

  And to sort of set the stage, right? There's an AI great power competition between the US and China.

• 3:37Krishna Choudhary?

  Mm hmm.

• 3:37Lester Nare?

  Um, AI, as we know, it has existed for quite some time, uh, you know, before all this generative AI stuff. Um, but in the sort of recent context, uh, we're going to start in 2017 where China launched its next generation AI plan, which said it was going to lead the world in AI by 2030.

• 3:57Krishna Choudhary?

  Uh, they're famous for their five year plans.

• 3:59Lester Nare?

  Right. And the idea is US has been the, the global hegemon forever. China's looking at a way in which it can sort of destabilize that control.

• 4:07Krishna Choudhary?

  Yeah.

• 4:07Lester Nare?

  Uh, and Xi Jinping, uh, leader of the Chinese Communist Party, uh, said that advanced tech is the sharp weapon of modern states.

• 4:16Krishna Choudhary?

  Yeah, that's true.

• 4:17Lester Nare?

  And as we've discussed, you know, on this podcast previously, you know, there is a very strong relationship between them. Military intelligence and national security apparatus within nation states and frontier technologies. AI just being one of those. Um, and then in 2021, what was interesting is the US National Security Commission on AI, which was chaired by, uh, the former Google CEO Eric Schmidt. Warned that American dominance in AI was not guaranteed. So we already have this setup of of that friction.

• 4:49Krishna Choudhary?

  Wow.

• 4:49Lester Nare?

  Now, if we go into the Biden era policies, because the US government, as we know, as it relates to technology innovation, is usually reactive as opposed to proactive.

• 4:59Krishna Choudhary?

  Yes.

• 4:59Lester Nare?

  We look at the internet as an example. They allowed innovation to happen and then they put in a regulatory infrastructure.

• 5:04Krishna Choudhary?

  Yeah.

• 5:05Lester Nare?

  After the fact. With AI, because of the popular conversation from the likes of folks like the richest man in the world, depending on the day, Elon Musk, really ringing the alarm on, you know, AI safety.

• 5:16Krishna Choudhary?

  Yeah.

• 5:17Lester Nare?

  Which has created this accelerationist, decelerationist dichotomy within Silicon Valley.

• 5:23Lester Nare?

  The Biden era was the first administration to take policy in earnest in terms of AI specifically.

• 5:28Krishna Choudhary?

  Okay.

• 5:29Lester Nare?

  And this started in August 2022, when Biden signed the Chips and Science Act, which many people have probably heard the CHIPS Act.

• 5:36Krishna Choudhary?

  Yeah, the CHIPS Act.

• 5:37Lester Nare?

  Two hundred and fifty billion dollars bipartisan bill aimed at boosting US semiconductor manufacturing and innovation. This dovetails with the re-onshoring of manufacturing conversation post-COVID. There was fifty two point seven billion in supplemental appropriations that was specific to semiconductor-related programs.

• 5:54Krishna Choudhary?

  Okay.

• 5:54Lester Nare?

  For 2023 through 2027. The idea being that it was also going to create guardrails preventing recipients like Intel and TSMC from expanding their advanced fabs in China. So we can see the theory of the case here was can we create a choke point at the hardware level? Because these chips were viewed at the time as being the key aspect of the stack that was going to be the driver of progress.

• 6:22Krishna Choudhary?

  Right.

• 6:22Lester Nare?

  And innovation.

• 6:23Krishna Choudhary?

  And TSMC is in Taiwan, which is like now iffy if it's if China's going to do something, right?

• 6:29Lester Nare?

  Correct. China's been doing a huge military buildup and training.

• 6:32Krishna Choudhary?

  Right.

• 6:33Lester Nare?

  Around this idea of we're going to take Taiwan.

• 6:35Krishna Choudhary?

  Yeah, yeah, that's basically their thesis.

• 6:37Lester Nare?

  We're going to take Taiwan and you don't want to be here when that happens.

• 6:41Krishna Choudhary?

  Yeah.

• 6:41Lester Nare?

  To us, the US.

• 6:42Krishna Choudhary?

  Yeah, yeah.

• 6:43Lester Nare?

  And so there's

• 6:44Krishna Choudhary?

  Scary.

• 6:44Lester Nare?

  There are a lot of layers to this. The Taiwan point's a really important one. Now, twenty twenty two, we're still in twenty two, August, CHIPS Act drops. Uh, uh, and then October seventh, twenty twenty two, uh, the October seventh controls were established, which are export controls. Now, they named it this prior to the unfortunate October seventh of twenty twenty three, which is the Israel Gaza conflict. But at the time, uh, this was a restriction on exports of specific Nvidia and AMD chips. The, uh,

• 7:16Krishna Choudhary?

  H one hundreds.

• 7:16Lester Nare?

  H one hundreds, A one hundreds, and the AMD M I two, uh, I my two fifties, uh, which basically meant this was the whole, we have a small yard, high fence.

• 7:25Krishna Choudhary?

  Yeah.

• 7:26Lester Nare?

  Uh, making it really, really difficult to get these sort of frontier chips.

• 7:29Krishna Choudhary?

  Yeah, and the thesis was that like these chips are the future.

• 7:32Lester Nare?

  Yes.

• 7:32Krishna Choudhary?

  And without these chips, you can't do shit.

• 7:34Lester Nare?

  Exactly. That was, that was the theory of the case at the time.

• 7:36Krishna Choudhary?

  Yeah.

• 7:37Lester Nare?

  As a small side note, it's interesting that a month, almost just over a month later, in, on November twenty second, uh, twenty twenty two, Chat G P T launched.

• 7:47Krishna Choudhary?

  Ah, okay.

• 7:48Lester Nare?

  So all this conversation was happening prior even to the, the meteoric rise

• 7:54Krishna Choudhary?

  Right.

• 7:54Lester Nare?

  of the first real, you know, production level, uh, L L M generative A I accessible to millions of people. And the growth curve, as we all know.

• 8:04Krishna Choudhary?

  I mean, that Chat G P T was the moment where now everyone was like, oh, A I is here.

• 8:09Lester Nare?

  Yes. It's not just this thing people are saying, and da, da, da, da. It's not theoretical.

• 8:14Krishna Choudhary?

  I, I can literally chat with it.

• 8:16Lester Nare?

  Yes.

• 8:17Krishna Choudhary?

  And it's like giving me amazing answers.

• 8:19Lester Nare?

  Yes.

• 8:19Krishna Choudhary?

  Yeah.

• 8:19Lester Nare?

  Yes.

• 8:20Krishna Choudhary?

  Yeah.

• 8:20Lester Nare?

  So now we're moving into twenty twenty three.

• 8:23Krishna Choudhary?

  Right.

• 8:23Lester Nare?

  Uh, so throughout twenty twenty three, now the Biden administration is not only trying to create the choke points domestically, but now we're going out to our allies, uh, all across the world to sort of expand that tightening. So this included, uh, in the Netherlands with, uh, A S M L. Right. Japan with Nikon and Tokyo Electron, blocking them from, from providing China access to their lithography tools, which are used to actually build and generate these more advanced chips.

• 8:53Krishna Choudhary?

  Yeah.

• 8:53Lester Nare?

  Uh, this was followed up by an August of twenty three, executive order one four one oh five, uh, which now also restricted investment from U S investors into any China A I or quantum firm.

• 9:07Krishna Choudhary?

  Okay, so they're, they're just like effectively slowly. Like choking all pathways.

• 9:14Lester Nare?

  Right.

• 9:15Krishna Choudhary?

  For.

• 9:16Lester Nare?

  Hardware innovation.

• 9:16Krishna Choudhary?

  Yeah, for hardware innovation.

• 9:18Lester Nare?

  For hardware innovation.

• 9:19Krishna Choudhary?

  Okay.

• 9:19Lester Nare?

  Right, so while this was all happening in twenty three, uh, interestingly enough, uh, there was the very, very sort of public falling out of the founder or CEO at OpenAI, Sam Altman. So you, many folks may remember, there was that huge board battle.

• 9:36Krishna Choudhary?

  I forgot about, yeah, dude.

• 9:38Lester Nare?

  He was ousted.

• 9:39Krishna Choudhary?

  He was ousted?

• 9:40Lester Nare?

  Yes. And this was around, OpenAI was a nonprofit. They were doing a lot of for-profit moves. They wanted to kind of rejigger their structure. And it kind of signified the realization across the Silicon Valley consensus that this thing was going to be bigger, more powerful, more impactful, more money generating than even they had seen, they had predicted. It was happening quicker than they expected.

• 10:06Krishna Choudhary?

  Yeah.

• 10:06Lester Nare?

  Um, so there was that power struggle.

• 10:08Krishna Choudhary?

  Right.

• 10:08Lester Nare?

  Ultimately, the king returned to the castle.

• 10:11Krishna Choudhary?

  Yeah.

• 10:12Lester Nare?

  And we got to his, Sam regot his position as CEO. But all this we've talked about so far has been the US side.

• 10:18Krishna Choudhary?

  Yeah.

• 10:19Lester Nare?

  So in twenty three, China's response, like what has China been doing as the US?

• 10:23Krishna Choudhary?

  That's right. So, yeah, we've been battling internally.

• 10:26Lester Nare?

  Yes.

• 10:26Krishna Choudhary?

  So to speak.

• 10:27Lester Nare?

  And to sort of create this, uh, regulatory regime around access to chips.

• 10:31Krishna Choudhary?

  Right. So what's China been doing?

• 10:32Lester Nare?

  So China, uh, had firms like Huawei introduce their own, you know, what they call frontier chips.

• 10:40Krishna Choudhary?

  Yeah.

• 10:41Lester Nare?

  Uh, with ascend, the ascend AI chip, uh, as well as, uh, shocking the global community when SMIC, uh, released their seven nanometer process, uh, for, for smartphone chips, which again, the idea was TSM, TSMC has really had a monopoly on the seven, five, and I believe three now nanometer chip sizes.

• 11:02Krishna Choudhary?

  Their latest is three, but like sub ten was them.

• 11:05Lester Nare?

  What, right. And, and no one else could really do it. And that was like a really big bottleneck.

• 11:09Krishna Choudhary?

  Yeah.

• 11:10Lester Nare?

  Both for and there's both operational reasons and proprietary intellectual property reasons why that's difficult.

• 11:16Krishna Choudhary?

  Yeah.

• 11:17Lester Nare?

  Um, they also then had uh their other big conglomerate technology companies, Baidu, Alibaba, uh, begin to put out their own chat GPT type L L M. So we had Quen, we had Ernie Bot.

• 11:30Krishna Choudhary?

  But nobody really.

• 11:31Lester Nare?

  No one really.

• 11:32Krishna Choudhary?

  No one really cared, right?

• 11:33Lester Nare?

  No one cared. They were all trained on the cut down Nvidia H eight hundred GPUs, which were still allowed to be sold to China, but they were.

• 11:40Krishna Choudhary?

  Right.

• 11:41Lester Nare?

  Uh massively sort of handicapped.

• 11:43Krishna Choudhary?

  Yeah.

• 11:43Lester Nare?

  Um. Interestingly, now now we're sort of getting into twenty twenty four, which is more of the same. But we talked about the intersection of the national security state, the intelligence community, military intelligence, and frontier technologies.

• 11:57Krishna Choudhary?

  Yeah.

• 11:58Lester Nare?

  And Mark Andreessen made this interesting uh note in a podcast where he basically was trying to call out the folks who are called D cells or the folks who are really uh heavy on A I safety.

• 12:10Krishna Choudhary?

  Uh deceleration. Okay.

• 12:11Lester Nare?

  Yeah, the decelerationists who are saying, let's slow down, let's slow roll.

• 12:15Krishna Choudhary?

  Elon is a famous one.

• 12:16Lester Nare?

  Elon is arguably the most famous decelerationist. And Mark Andreessen's point was, if you believe that this threat is as as existential as nuclear weapons.

• 12:27Krishna Choudhary?

  Sure.

• 12:27Lester Nare?

  You're still allowing these Open A I employees to go to an unprotected, unsecured building in the same way that, not in the same way that like nuclear facilities are protected from a.

• 12:38Krishna Choudhary?

  Yeah.

• 12:38Lester Nare?

  Operational security perspective. So he's like, if you believe this to be true, the entire operating infrastructure of these companies needs to change.

• 12:45Krishna Choudhary?

  Yeah. That's fair, actually. I didn't I didn't I never thought about that, but yeah.

• 12:49Lester Nare?

  It it's it's a fair argument, right?

• 12:51Krishna Choudhary?

  Yeah.

• 12:51Lester Nare?

  And in twenty twenty four, in on June thirteenth, after all this board kerfuffle in twenty three, the former head of the National Security Agency and commander of U S Cyber Command, uh Paul Nakasone was added. To the OpenAI board, which was the first salvo in what I like to call the nationalization of the frontier models in the United States.

• 13:14Krishna Choudhary?

  Got it.

• 13:15Lester Nare?

  Right? Now, the national security state has a seat at the table. Shortly after, OpenAI announced several projects with the Pentagon.

• 13:23Krishna Choudhary?

  Yeah.

• 13:23Lester Nare?

  The OD around using it. So this is all background leading up to the Sputnik moment for China.

• 13:30Krishna Choudhary?

  That was a big one.

• 13:31Lester Nare?

  Which is in January of this year, twenty twenty five, when the Chinese startup DeepSeek released their R1 model, which was claiming at the time a ChatGPT four level reasoning. So this is like our best, most frontier. This is pre ChatGPT five, which we now have today in September, fully trained on Nvidia H eight hundreds.

• 13:55Krishna Choudhary?

  Yes.

• 13:55Lester Nare?

  The the not good chips.

• 13:56Krishna Choudhary?

  The not good chips, yeah.

• 13:58Lester Nare?

  Using a mixture of experts' techniques for the training alongside with reinforcement learning at what we now understand to be a sub three hundred thousand dollar training cost. Now, it's important to note, the amount of money that Anthropic, OpenAI, Meta has raised to train Grok to train their foundation models is in the order of tens of millions, hundreds of millions of dollars.

• 14:22Krishna Choudhary?

  Yeah.

• 14:23Lester Nare?

  So these are, this is in orders of magnitude.

• 14:25Krishna Choudhary?

  Magnitude less.

• 14:26Lester Nare?

  Difference.

• 14:26Krishna Choudhary?

  Yeah.

• 14:27Lester Nare?

  And so what we ended up creating by doing this choke point on the hardware side was, you know, necessity is the father invention or whatever, right?

• 14:38Krishna Choudhary?

  Yeah.

• 14:38Lester Nare?

  China then said, okay, let's innovate on the training model and infrastructure to try to get the same efficacy.

• 14:44Krishna Choudhary?

  On the algorithms.

• 14:45Lester Nare?

  On the algorithm and the software, not on the hardware. So this created a huge,

• 14:53Lester Nare?

  you know, surprise.

• 14:54Krishna Choudhary?

  Yeah.

• 14:54Lester Nare?

  From a lot of US observers, because the the the consensus was if we choke off the hardware, they got nothing.

• 14:59Krishna Choudhary?

  Yeah.

• 15:00Lester Nare?

  And this totally blew that out of the water. So at first, there was fascination, which was immediately followed by the national security narrative taking over.

• 15:08Krishna Choudhary?

  Yeah.

• 15:08Lester Nare?

  An interesting point about what China did with DeepSeek was it was also, if we exclude Llama, Meta Meta's Llama, which models, which are open source, open weights.

• 15:19Krishna Choudhary?

  Yeah.

• 15:20Lester Nare?

  But arguably weren't as competitive as R1.

• 15:23Krishna Choudhary?

  Mm hmm.

• 15:24Lester Nare?

  China was the first frontier scale open weight model.

• 15:28Krishna Choudhary?

  Yeah, yeah. They just polished their weights.

• 15:30Lester Nare?

  Right. Which the the point here is then you can take it and make it into whatever you want to. So the app for DeepSeek became the number one most downloaded app globally. Oh, I didn't know that. It was then banned in India, Italy, Australia, Taiwan, because the national security narrative came in and it was like, this is a propaganda tool, it's a, it's a data siphoning tool. Yeah. Uh, don't trust DeepSeek, but it strategically left out the point about the fact that you could download the model. Yeah. Run it locally and change the weights however you wanted to. So with DeepSeek, if you tried to look up Tiananmen Square. Yeah. You weren't gonna get an answer. Really? Right. So they were, you know. Oh, classic. Doing a little bit on the. Yeah, yeah, yeah, of course. On the information control, but it's open weights. Yeah.

• 16:15Lester Nare?

  So if you want the Tiananmen Square answer, you can do it on your own, but. Oh, interesting. I see. Yeah. The narrative really tried to avoid talking about that point. At the same time, people started calling OpenAI closed AI. Yeah. Because they had never had an open source model. They'd never had a research paper, peer review paper. Right, yeah. Around their process. So now this brings us to where we are today. Yeah. With these two new papers in nature, uh, which go a little bit deeper into how DeepSeek went through their process and we'll sort of talk about this. But I think that background is important context to understand, like, why does DeepSeek matter? Yeah. Why is it uniquely different than ChatGPT, than Claude, than, you know.

• 17:00Lester Nare?

  Gemini. Gemini, all these other models. A- and why is it important that they actually have a peer review paper? We always talk, a lot of the US conversation around science research is, oh, China's papers, they fake the data. Yeah. They're not really good. They're not where we are. And I think this, this has been a, a unfortunate, uh,

• 17:24Lester Nare?

  viewpoint in the US about China generally, not only with cars, saying they just steal our stuff. Also with this, that is a little bit outdated. It is, definitely. We're seeing with cars, the best EV cars in the world are made by China. It's not arguable. They make them cheaper, faster, better, stronger. Yeah. Uh, which we've now put tariffs on in order to say, oh, don't look here. There's no problem. Ford is still the best. And AI is taking a similar, in terms of our posture, a similar. Political stance that China doesn't really know what they're doing. This is not really a big deal. Blah blah blah. I think we need to be careful about ascribing a narrative that may have been true fifteen, twenty years ago.

• 18:05Krishna Choudhary?

  Yeah, that's certainly not true now.

• 18:07Lester Nare?

  That's certainly not true.

• 18:08Krishna Choudhary?

  We've covered Chinese research. We've covered the hexagonal diamonds.

• 18:12Lester Nare?

  Yes.

• 18:12Krishna Choudhary?

  That were first created by China. Everyone's been going after them.

• 18:15Lester Nare?

  Yes.

• 18:15Krishna Choudhary?

  But two labs in China were going after them and actually one of them succeeded, right? Like, and it's, the proof is in the pudding.

• 18:22Lester Nare?

  Yes.

• 18:23Krishna Choudhary?

  They made it. They have all the tests.

• 18:24Lester Nare?

  Right. And there's peer review paper, again.

• 18:27Krishna Choudhary?

  And it's out in nature.

• 18:28Lester Nare?

  It's out in nature.

• 18:29Krishna Choudhary?

  Right?

• 18:29Lester Nare?

  Um, and we always talk about, well, da da da, this and that. So now that we've given that context, let's talk about these two new papers.

• 18:36Krishna Choudhary?

  Yeah, these papers are um, pretty incredible in the fact that they are the first peer reviewed paper from a sort of premier AI large language model, right? You have like, obviously ChatGPT, Gemini, Grok, all of these large language models, but they haven't actually published anything that shows sort of, okay, that, that, you know, I I'm sure that the, the team at DeepSeek has kept some secrets to themselves. But the fact that they've actually gone out and published this peer reviewed paper is, I think, quite a watershed moment for the AI community, right? Because they're trailblazing this idea that maybe AI is a part of open science.

• 19:19Krishna Choudhary?

  And maybe it should be out in the open, just like normal science, right? Where it's like you, as a scientist, you find something cool or you make something cool. You put it out in a peer reviewed paper, right? And you get, let experts actually talk back to you and then like, see how things actually work, right? You want to get into the nitty gritty of it. Um, in the technical details, this paper is quite interesting. Because it tells us some of the tricks that they used in actually making it possible to train something like DeepSeek on perhaps only H one, H eight hundreds. Again, maybe not, right? There's always a possibility that they're not totally forthcoming.

• 20:00Lester Nare?

  Right.

• 20:00Krishna Choudhary?

  But. They've they've sort of laid bare some of their strategies and I think that's quite interesting.

• 20:07Lester Nare?

  I I want to actually just do make two small

• 20:10Krishna Choudhary?

  Yeah.

• 20:10Lester Nare?

  context notes that I think are interesting here. One is, one is that the the founder of DeepSeek are his, his story is that the reason they ended up creating uh R1 was actually he was doing uh uh the trading, like financial tra- like finance trading.

• 20:28Krishna Choudhary?

  Right, it was related to a hedge fund.

• 20:29Lester Nare?

  It was a hedge fund.

• 20:30Krishna Choudhary?

  Yeah.

• 20:30Lester Nare?

  They were like, we want a more powerful model to utilize for, so it wasn't even their core. It was an outgrowth of another

• 20:39Krishna Choudhary?

  Yeah.

• 20:40Lester Nare?

  like need. And then I want to talk about this open sourcing concept of like why China did the, like, why are they doing this open source, open weights?

• 20:48Krishna Choudhary?

  Yeah.

• 20:48Lester Nare?

  move. There was an interesting um uh there's a podcast, the BG2 podcast with two US investors. Um Brad Gershner and Bill Gurley.

• 20:59Krishna Choudhary?

  Okay.

• 20:59Lester Nare?

  And they've been talking about this a lot. If you look at China's strategy generally as it relates to, if you're in a world where the US already has dominance in a lot of these technologies that are closed source, from a, from, from a, how do we remain competitive angle? This is actually what Facebook did by trying to have Llama be open. Is the, the best thing you can do to battle closed source is to create an open source ecosystem.

• 21:22Krishna Choudhary?

  Right.

• 21:22Lester Nare?

  That now becomes competitive with that closed source because you're gonna then now get input from a wider array of experts.

• 21:28Krishna Choudhary?

  Yeah.

• 21:29Lester Nare?

  That invest in your version of the future.

• 21:31Krishna Choudhary?

  Mm hmm.

• 21:32Lester Nare?

  And so for China, there was an incentive geopolitically to go open source being a second mover as the means by which to combat the closed source dominance of the US. So oh, the, this DeepSeek model is not an isolated incident of China using open source as a way to backstab

• 21:52Krishna Choudhary?

  Right.

• 21:52Lester Nare?

  US's closed source dominance.

• 21:54Krishna Choudhary?

  Yeah, there's like a, there's, there's a strategy.

• 21:56Lester Nare?

  Yes.

• 21:57Krishna Choudhary?

  Behind this.

• 21:58Lester Nare?

  That is a larger part of how China is trying to it it it spread its influence across these areas in which the current West's control and and buy-in is waning.

• 22:11Krishna Choudhary?

  Yeah, I mean, I think they figure that like the world is a really big place, okay? And these developing economies are exactly that, developing, right? They're getting bigger, people are getting more affluent, technologies there are gonna start getting better and better. And they're gonna require AI to keep up with the rest of the world, right? And maybe they don't wanna pay whatever royalties, right, to to these closed systems. I think, I, yeah, I think, I think it's really cool. And I think the idea that Deepsea came out, right? With their model in January, I think it was also a watershed moment for the rest of the AI community.

• 22:53Krishna Choudhary?

  In terms of finding out the efficacy of something like a pure reinforcement learning approach, okay? Rather than some of the techniques that ChatGPT and these other firms had used, which was a supervised fine tuning. Or this sort of human feedback reinforcement learning, which always requires a human in the, in, in the loop.

• 23:15Lester Nare?

  Yes.

• 23:16Krishna Choudhary?

  Right? What these guys did was um, kind of a pure reinforcement learning approach. And that's something that they've laid out in this paper in Nature, okay? The idea is that sort of traditional LLM reasoning models, what they do is they require human input in order to steer them towards the correct answer, right? In order to be like, okay, this is, this was not quite what I wanted, this is, this is what I wanted, right? There were a bunch of like Kenyans that were hired by OpenAI to basically do this, right? And I don't know how many, but like that was a whole thing back in the day. And, you know, that's fine for, that, that's fine, but it's, it's quite expensive in terms of. Like getting human annotated chain of thought data and so on and so forth.

• 24:00Krishna Choudhary?

  But on the other hand, there's actually a disadvantage to using humans. Because then you are limited to human reasoning. Okay, there could be other ways to reason about a problem that wouldn't quite occur to a human being. That perhaps if we gave the entire control to the machine itself, the machine could figure out on its own. Right? So, so there's an inherent disadvantage that I think these guys at DeepSeek actually like latched on to. Right? And they figured that what we could do is we could, we could use a pure reinforcement learning strategy. Where there's a reward signal. So the way the reinforcement learning works is you've got your model, right? And then it tries to find an answer.

• 24:45Krishna Choudhary?

  This works for well-defined tasks where there's a right and wrong answer. And there's a really nice way to compare your answer to the right answer and figure out what a reward should be. A reward being if my answer is closely aligned to the right answer, then I'm on the right track. And the strategy that I've been using is sort of on the right track. And otherwise, maybe I need to try a different strategy. It's actually very close to how neural systems work, right? We, we've studied reinforcement learning like at the biological level when it comes to like, you know, a rat trying to find cheese in a maze, right? We've, we've literally gone into the brain and found that these how,

• 25:28Krishna Choudhary?

  at the nitty-gritty level, at the cellular level, how this stuff works. And now, and now we're kind of translating that into the AI neural network space, the artificial neural network space. So if we use pure reinforcement learning, what that does is it bypasses human labeled reasoning steps. And then we can actually. Explore just computationally the entire paradigm of how to solve a problem. Which is, I think, very cool. Um, so that's one of the things that's revealed by this paper, the fact that they used pure reinforcement learning. Okay, um, it was this autonomous exploration and a development of problem solving strategies.

• 26:08Krishna Choudhary?

  And what you could see, and what they reported in the paper, is you could see the the network sort of use that RL technique, reinforcement learning, to get better at finding the right answer. So what what they noticed is, um, for example, the length of the answers would get progressively longer. Because the neural network wanted to get better and better at finding that right answer in this large language model type of thing. They also had this thing called the aha moment, which is when I was like, oh, this is like working way better than we thought. Which is when, you know, in the chain of thought, you can actually output the thought that this thing is doing, right?

• 26:49Krishna Choudhary?

  And, um, the model would start using the world, the word wait.

• 26:57Krishna Choudhary?

  That was never explicitly put into the training regime, okay? But what the model would start doing is, as it was thinking, if it was trying to get to an answer, and it was like sensing that it was rushing things and just trying to get it done quickly, it would use this thing wait.

• 27:14Krishna Choudhary?

  And then, and then it would backtrack and try to figure out if there's a better way to rethink what it had just thought. And then keep going. That's like Yeah. Some meta level, like weird, weird stuff, dude. Like that it's just using this word wait in the context that the word wait means wait, and let's try to figure out what we just said in a, in a, in a nice way. You know, I think, I think that's, that's, that's kind of crazy to backtrack and then. So it developed these autonomous sophisticated reasoning patterns to try to, you know, solve the problem. And it's no longer limited by the human guided approach.

• 27:54Lester Nare?

  Right, right.

• 27:55Krishna Choudhary?

  Right?

• 27:55Lester Nare?

  Which also has bias issues.

• 27:57Krishna Choudhary?

  Yeah, exactly.

• 27:58Lester Nare?

  Human reinforcement learning.

• 28:00Krishna Choudhary?

  Yeah.

• 28:00Lester Nare?

  Because now, if you have a bunch of Kenyans doing it.

• 28:03Krishna Choudhary?

  Yeah.

• 28:03Lester Nare?

  There's cultural differences.

• 28:05Krishna Choudhary?

  Exactly.

• 28:05Lester Nare?

  There's educational differences. And so you, you, this is where people sort of have concerns about the Silicon Valley elite being the ones controlling the parameters and mind space that these models sort of have. So it, but this is like a very pure play.

• 28:24Krishna Choudhary?

  Yeah.

• 28:25Lester Nare?

  Version that kind of abstracts away the need for, at least in some cases, for the human input to be such a big driver in how it determines answers.

• 28:34Krishna Choudhary?

  That's right, yeah. So, so that was the reinforcement learning part, right? Which is like, okay, tha- that's a training strategy. They also had this philosophy sort of of efficiency over everything, right? Because of what you talked about where, you know, the powers that be, let's say, have crippled their access to hardware. So what can we do? We can innovate with algorithms and we can innovate with strategy. So there, there's a two-pronged approach that they at least revealed in this Nature paper. The first one is this idea of mixture of experts, right? This architecture where what you can do is have a giant model. The DeepSick model itself is, um, six hundred and seventy-one billion total parameters,

• 29:17Krishna Choudhary?

  which is on par with some of the big ChatGPTs and things like that. I think ChatGPT five has like on the order of trillion or more. But some of the earlier models have hundreds of billions, so it's in the same regime. But when it comes to actually inference, the number of active parameters used is only thirty-seven billion. Okay, which is twenty times less than the total size of this network. Because what they're doing is, they've got, they've got this sort of network on top.

• 29:45Lester Nare?

  Yes.

• 29:45Krishna Choudhary?

  That, that comes in in the very beginning and it's kind of a router. Okay, what it does is, you've got, you've got the six hundred billion parameter network. But if you ask it a certain question, there's only a certain subset of that network that would be very good at answering that question. And that becomes that thirty-seven billion. Part. So you you they've they've implemented this router mechanism that takes in the prompt of whatever you put in and then it sort of routes that prompt to a subset of the network and now inference becomes faster, it becomes less expensive in terms of maybe you don't need an H one hundred GPU, right? Maybe you can do with that H eight hundred.

• 30:29Krishna Choudhary?

  Or you know, that that previous model and you can actually like get a quick answer and it'll be just as good. Right. Right? So that's one of the strategies that they used. The other strategy that they used was during training, they had this um idea of using um a reward system, right? In in reinforcement learning, you have to have a way of sort of quantifying how much the reward is and then steering the network towards getting more of that kind of reward, right? So the way that traditional L L Ms um have been trained is through this process called proximal policy optimization, okay? P P O.

• 31:11Krishna Choudhary?

  It's this idea that you have your policymaker, which is your L L M, that's like actually outputting the the language that gets output whenever you do the chat. But then there's this thing on top, which is kind of like the critic model. And what that critic model is doing is it's during the training process, it is taking the output of the policy, which is the output of the model, and then it's trying to guess at what the reward is going to be, okay? And then what you can do is you can use this critic model and the advantage that you get, the advantage being what is my guest advantage at this particular strategy? That's what this critic model calculates and what this critic model does is feed back that advantage

• 31:56Krishna Choudhary?

  to the big L L M to tell it, okay, you're on the right track, this strategy is working or no, it's not working. Crucially, this is very expensive because now you've got two models that you're training, right? You've got two models and as the L L M gets bigger and bigger, the critic model has to get bigger and bigger to try to figure out how to calculate that advantage in whatever scenario, whatever game you're playing, whether it's text generation, whether it's whatever, right? So if you've got a bunch of H one hundreds, that's fine, right? If you've got billions of dollars of funding from random V C firms, that's fine. But if you're deep seek That's no longer tenable.

• 32:36Lester Nare?

  Mm hmm.

• 32:36Krishna Choudhary?

  So what these guys did was they used a different strategy called group relative policy optimization.

• 32:41Lester Nare?

  Okay.

• 32:42Krishna Choudhary?

  Okay, they don't have this second critic model that they're doubly training, right? They don't have this two X parameter blow up.

• 32:50Lester Nare?

  Mm hmm.

• 32:51Krishna Choudhary?

  What they have is their original L L M. And what it's gonna do is it's gonna output a bunch of different answers. Okay, let's say for the sake of argument, let's say ten different answers. And then what it's gonna do is it's gonna calculate the reward for each, which we can get because this is a reinforcement learning strategy. And there's gonna be a mean and standard deviation. There's gonna be a distribution that you can calculate about that ten different strategies. There's gonna be some that are above the mean, which means that that is better than those others. The whole idea is you're trying to get this idea of advantage. Which are the strategies that give me advantage and which are the strategies that don't?

• 33:33Krishna Choudhary?

  In the ones before, in the traditional L L Ms, the ones that we're doing in the States and in the West. We've got this separate neural network that is calculating that advantage and telling the the original one where to go. Here, the original one is coming up with different answers. And then creating a distribution out of that and then figuring out, okay, I should I should go here to this part.

• 33:54Lester Nare?

  Mm hmm.

• 33:54Krishna Choudhary?

  Whatever I did here, that's what's good. Whatever I did here, that's what's bad because I came up with eight, ten different answers. These guys were bad, these guys were good.

• 34:02Lester Nare?

  Yes.

• 34:02Krishna Choudhary?

  Right, so you don't need this second

• 34:04Lester Nare?

  Right.

• 34:05Krishna Choudhary?

  giant neural network to train.

• 34:07Lester Nare?

  Mm hmm.

• 34:07Krishna Choudhary?

  Right, so it's it's it's a really interesting strategy where you're choked by the hardware.

• 34:15Lester Nare?

  Yes.

• 34:15Krishna Choudhary?

  But you're saying, okay, well, I've got a few tricks up my sleeve.

• 34:19Lester Nare?

  Yes.

• 34:19Krishna Choudhary?

  Right?

• 34:19Lester Nare?

  Yes.

• 34:20Krishna Choudhary?

  I I think it's I think it's rather cool.

• 34:22Lester Nare?

  I I think that this is an important, you know, there there is always because of this nexus between nation states trying to accrue and maintain power. And the importance of frontier technologies to that goal.

• 34:38Lester Nare?

  We're always gonna see policy impact how these technologies grow and progress. The Biden administration made a bet that hardware strangulation to China was the best path at creating advantage for the US in the race.

• 35:00Krishna Choudhary?

  And it was a well-informed bet, right? Because like, everyone who had been doing AI thought that that was the masterpiece, right? That the hardware was it. Right? Ever since, ever since twenty twelve, when AlexNet came out.

• 35:14Lester Nare?

  Yes.

• 35:14Krishna Choudhary?

  And what they could do is actually use GPUs to train in parallel.

• 35:18Lester Nare?

  Yes.

• 35:18Krishna Choudhary?

  And then just all of the mathematics of matrix multiplication and back propagation could be done on GPUs. That's when it was, you know, ever since then, we've sort of taken for granted that, oh, GPUs are really what matter. But, but we've created good enough GPUs.

• 35:33Lester Nare?

  Yes.

• 35:34Krishna Choudhary?

  That, we've taken for granted that like, the best GPU is always the best. But actually, the H eight hundred is like a good enough GPU now.

• 35:41Lester Nare?

  Yes.

• 35:42Krishna Choudhary?

  That it can do enough of the math.

• 35:46Lester Nare?

  Yes.

• 35:46Krishna Choudhary?

  That now we, now these guys can, can actually go and, you know, start.

• 35:52Lester Nare?

  Start, start tweaking the knobs.

• 35:54Krishna Choudhary?

  Yeah, start tweaking the knobs.

• 35:55Lester Nare?

  It, it's a really, you know, the cost difference is crazy. The equivalence of efficacy of the models, given the cost difference is even crazier. And it is going to continue to be this, this hardware-software tension. Where do you innovate more? Uh, where has the most, uh, aggregate value in terms of continuing to increase the power and efficacy of these models? It's gonna continue to be a rolling story.

• 36:24Krishna Choudhary?

  Yeah.

• 36:25Lester Nare?

  I think, again, to your point at the top of when we started this story, it is very interesting that for the amount of time, I remember using GPT two uh, in my company, trying to see, you know, trying to gauge, when is this stuff gonna be ready for production? Years ago. And it is, uh, the jury is not out.

• 36:48Krishna Choudhary?

  Yeah.

• 36:48Lester Nare?

  Yet, on.

• 36:51Lester Nare?

  On this journey to AGI and artificial superintelligence, which of these two levers that we're pulling are going to create those incremental? Because we've sort of seen the models are kind of starting to aggregate at a similar level of performance.

• 37:07Krishna Choudhary?

  Yeah.

• 37:08Lester Nare?

  And the the gains from your walled garden are becoming less and less.

• 37:13Krishna Choudhary?

  Yeah.

• 37:14Lester Nare?

  And this is a classic battle in every technology revolution that's ever existed in terms of the tension between closed source and open source.

• 37:24Krishna Choudhary?

  Yeah.

• 37:25Lester Nare?

  Open source has always been, you know, all servers run on Linux.

• 37:28Krishna Choudhary?

  Yeah.

• 37:29Lester Nare?

  Is open source. Why is that?

• 37:31Krishna Choudhary?

  Everyone uses Python.

• 37:33Lester Nare?

  Everyone uses Python, open source. And the reason, the theory of the case is when you open source, there's a more of a distributed incentive to create security.

• 37:40Krishna Choudhary?

  Exactly.

• 37:41Lester Nare?

  Because everyone wants it to work. You're having more viewpoints inputting into the the system itself. And you're limited by your resources if you go closed source by your talent. The way in which in the US we deal with that is Facebook gives billion dollar offers to the best AI researchers. But at some point, th- this is the forever tension in technology revolutions. And it's interesting to see it play out in this geopolitical sphere where the the the winner or the the import of the battle is so high.

• 38:15Krishna Choudhary?

  Yeah, yeah, the stakes are really high.

• 38:17Lester Nare?

  It's really high.

• 38:18Krishna Choudhary?

  Yeah, yeah.

• 38:19Lester Nare?

  Um, and so great first story, I I love the AI story is always great because a lot of times people just talk about the end product. We haven't had a lot of research papers to talk about.

• 38:29Krishna Choudhary?

  It's it's kind of cool that like, you know, we got a sort of, you know, look under the box to see to see how it all worked. And they and they were also forthcoming about some of the challenges that they had. Like they, um, you know, when they, when they first started out with DeepSeek R one zero.

• 38:44Lester Nare?

  Yes.

• 38:44Krishna Choudhary?

  Which is the one that they didn't release. They were having this trouble where like the output would be like half Chinese, half English. Right? So then what they did was they had cold start data. So it wasn't completely all blind reinforcement learning. What they did was they primed the model with human data. Okay. To to actually sort of give it a running start.

• 39:05Lester Nare?

  Yes.

• 39:06Krishna Choudhary?

  And not have it like from the very beginning, start doing random, random stuff. So what you do is you you can have a small subset of human labeled training data.

• 39:14Lester Nare?

  Yes.

• 39:14Krishna Choudhary?

  That like creates a sort of. Neighborhood of parameters, okay? Where, where, okay, like the, the model sort of settles in on this neighborhood of where the numbers should be for all of these weights. And then you can fine tune it. And fine tuning is, is a coarse grained word because obviously like a lot of training was done afterwards, but like after that initial sort of like, okay, don't do like the stupid stuff of like half Chinese, half English. But then now get into the, you know, how do you problem solve? How do you, how do you, how do you actually make a really nice L L M? So, so they were forthcoming about some of their challenges, which I think is, is kind of interesting.

• 39:53Lester Nare?

  And again, it goes back to the sort of the narrative violation that the current C C P has put ourselves in where in the U S, we're still viewing their operating system as what it was 20 years ago. But they are being nimble and understanding the changing environment and trying to reposition.

• 40:11Krishna Choudhary?

  Yeah.

• 40:12Lester Nare?

  Again, you can argue that it's contrived or not.

• 40:15Krishna Choudhary?

  Yeah, I mean, you, you know, knowing China, of course, there's stuff that we don't know about, right? Of course, probably like DeepSeek is entrenched with the C C P. I'm just saying, you know, like, I'm just saying it's probably true. But they're doing the work, they're, they're publishing peer reviewed papers, they're, they're, you know, coming out with cutting edge A I and they're doing it without the H one hundreds or at least not with the kind of access that, you know, companies have in America. Perhaps they do have H one hundreds from shell companies in Bhutan or whatever.

• 40:50Lester Nare?

  Which is, which is one of the arguments. Yeah, like. That they've been doing this illicit market trading in order to get access to it. But the point is they don't even need it.

• 40:56Krishna Choudhary?

  Yeah, yeah, it turns out like, you know, people, people are now, now that this is out, they're going to try using these strategies now. And we're going to see if, if the rubber meets the road.

• 41:06Lester Nare?

  And, and you know, now since, oh, DeepSeek came out. Uh, Meta was already releasing open weight models.

• 41:14Krishna Choudhary?

  Yeah.

• 41:14Lester Nare?

  And they've continued, I think they've actually incorporated some of the mixture of experts' architecture into the Llama models.

• 41:19Krishna Choudhary?

  I think people are taking this sort of reinforcement learning strategy very seriously too. Where they're saying, okay, maybe I don't need a bunch of Kenyans to just keep annotating my outputs, right?

• 41:29Lester Nare?

  Correct.

• 41:29Krishna Choudhary?

  Yeah.

• 41:30Lester Nare?

  And we now, just in the last month and a half, have an open source, open A I model. And it is very

• 41:37Krishna Choudhary?

  Right.

• 41:38Lester Nare?

  easy to argue that we would not have an open. Waits OpenAI model without DeepSeek.

• 41:47Krishna Choudhary?

  Yeah.

• 41:47Lester Nare?

  There was not an incentive for.

• 41:49Krishna Choudhary?

  No, why would they do it?

• 41:50Lester Nare?

  OpenAI to do so, but they had to answer to investors and the competition, etc. Great, great update here. We'll definitely be touching on AI more. We're gonna go to our next story, which I'm very excited about, because I don't know what any of it means.

• 42:02Krishna Choudhary?

  Yeah.

• 42:03Lester Nare?

  The headline on our second story, scientists just made the first time crystal that you can see. We have an Ocarina of Time.

• 42:12Krishna Choudhary?

  Yes.

• 42:13Lester Nare?

  Physicists at the University of Colorado Boulder have created the first time crystal that humans can actually see using liquid crystals that swirl into a never-ending pattern. When illuminated by light, they put out their paper in Nature Materials. There's been a lot of coverage of this one.

• 42:29Krishna Choudhary?

  Yeah.

• 42:29Lester Nare?

  I always see all these TikToks about.

• 42:30Krishna Choudhary?

  I really love it.

• 42:31Lester Nare?

  Time crystals and all this.

• 42:33Krishna Choudhary?

  Yeah, it's very Marvel, very Doctor Who.

• 42:36Lester Nare?

  Yeah, yeah, yeah, yeah.

• 42:37Krishna Choudhary?

  You know, like, this is how we beat Thanos.

• 42:39Lester Nare?

  Mr. Strange, Doctor Strange.

• 42:40Krishna Choudhary?

  Yeah, yeah, all sorts of, yeah.

• 42:42Lester Nare?

  So, so help me understand, you know, what exactly is, is going on with this time crystals paper?

• 42:46Krishna Choudhary?

  Yeah, so, well, fir- first, let's talk about what are time crystals?

• 42:51Lester Nare?

  I would like to know that.

• 42:52Krishna Choudhary?

  Okay, so, before we even do that, normal crystals, okay? We talked about diamond the other day.

• 42:58Lester Nare?

  Yes.

• 43:00Krishna Choudhary?

  The simplest crystal I can think of is table salt.

• 43:02Lester Nare?

  Okay.

• 43:03Krishna Choudhary?

  NACL, sodium chloride. You can imagine there's a sodium atom and a chlorine atom, sodium atom, chlorine atom, sodium gla- atom, chlorine atom. In this regular sort of chessboard-like structure, but a 3D sort of chessboard of sodium chlorine, sodium chlorine. The reason why this is a crystal, right? What characterizes it as a crystal is you've got a discrete space symmetry breaking, okay? This is a technical term in physics that just means if I take the crystal and I move it over by one spacing, I will get the same thing back.

• 43:39Lester Nare?

  Okay.

• 43:39Krishna Choudhary?

  Okay, you can imagine I've got the NACL, and then there's another NACL here, right? I can take that entire crystal and move it by a whole. Molecule and I'll have the same thing repeating, right? Just like in a chessboard, right? Imagine an infinite chessboard. That thing is a crystal in some sense, right? It's a 2D crystal because there's black, white, black, white. If I'm, if I'm, take up the chessboard and I move it over two sort of squares. I'll get the same exact chessboard, right? So that's what's called symmetry breaking in space. Okay, where it's no longer continuous because you can't just arbitrarily move this thing around. You have to move it by the lattice spacing, right? The lattice constant of the crystal.

• 44:22Lester Nare?

  Yes.

• 44:23Krishna Choudhary?

  So that's what makes it a crystal.

• 44:25Lester Nare?

  Okay.

• 44:25Krishna Choudhary?

  And it's also resilient to forces and stress, right? Like a diamond, for example, great way. I, I put stress on it. The crystalline structure of the carbon atoms isn't really going to change. Because the, the way that these carbon atoms are bonded to each other. They're resilient to like push and pull, you know? I heat it up, that, that structure is going to be resilient.

• 44:47Lester Nare?

  Yes.

• 44:48Krishna Choudhary?

  Right? So there was a guy Frank Wilczek, he was a Nobel laureate. He won the Nobel Prize in 2004 for discovering something called asymptotic freedom. Which has to do with the ways that quarks behave inside the atomic nucleus. Um, we can get into that some other day.

• 45:04Lester Nare?

  I think we need some asymptotic freedom in the US right now, but that's a whole nother story.

• 45:08Krishna Choudhary?

  That's a whole nother story as well for another day. But um, he, he won the Nobel Prize in 2004 and he's been very active in physics ever since. He's discovered things like called axions and like he's done stuff with cosmology. Um, and one of the things that he proposed back in 2012 was this idea of a time crystal. Okay, so he figured it, it's, it's a very interesting, quite simple argument, okay? He said that the laws of physics are symmetric to space translations, right? Meaning if I do a, if I do an experiment here. And then I, you know, take up the experiment and I move it somewhere else. The results of the experiment should be the same, right? If if all the environments are the same.

• 45:51Krishna Choudhary?

  And that's because there's no special coordinate in the universe, right? There's no like, like, there's no like, oh, it's just like here is where where things happen, right? There's no um, there's no special spatial coordinate. Well, similarly, the laws of the universe are also symmetric in time, right? If I do an experiment now and then I do it the next day, should be the same. Yeah, yeah. So if we have things that break spatial symmetry by creating crystals in space, right? Where you have clearly like carbon. Yes. Making the diamond or NACL making table salt. So you clearly have spatial crystals. What if I have a breaking of the time symmetry to create a time crystal? And what would that look like?

• 46:36Krishna Choudhary?

  What what that would look like is you've got some kind of periodic system that returns to its original form periodically, right? So just like how with a space crystal like the chessboard, I can take it up and I can move it in space and then put it back and it'll be the same thing. In time, for example, a sine wave, right? Mathematically, a sine wave is symmetric in time. Yes. To that period, right? I can pick up the sine wave, I can move it one entire period and put it back and it'll be the same sine wave. Yes. I should be able to have that in like the physical world. Okay. Okay? Because, you know, it's it's kind of same same, right? Theoretically. Theoretically, it should be possible. And it kind of makes sense.

• 47:21Krishna Choudhary?

  If if I have the same sort of symmetry breaking in space, I should have the same sort of symmetry breaking in time. Well, it wasn't quite that simple, okay? Never. So ri- right after he published that, it was it was, you know, Frank Wilczek is doing this Nobel Prize winner. He's a very famous physicist. So everyone's like, okay, is this possible? And actually, it turns out the way that he had envisioned it, it is not. So um, people came out and they published something called the no-go theorem for time crystals, which was that? Frank Frank Wilczek's original idea was that th- this time crystal is going to be in the ground state, which means it's in its lowest energy state. There's nothing pumping on it. It's just, you know, crystals can be in their lower energy state, right?

• 48:02Krishna Choudhary?

  I can cool a crystal down to like near zero Kelvin and it's going to remain in its crystal form. And that's what really like that means that it's an inherent property of the of the material itself. Right? And it's not something that coming from outside creating this order. Frank Wilczek's idea was that you can have a a system that is in its ground state. Right? And it's lowest energy state. There's nothing coming in and it's still gonna behave in this sort of periodic manner. Yes. Okay, that turns out can't be the case. Okay. Okay, so the no-go theorem said that a true equilibrium ground state cannot have persistent periodic motion. Meaning like if you've if you've cooled something down to its ground state, it's gonna be stationary. Right.

• 48:44Krishna Choudhary?

  And that kind of makes sense, right? Because if it's moving around in its ground state, that means there's some kinetic energy that I can extract. And it's not really the true ground state. Yeah. Right? Okay, so that's fine. But then people started wondering, alright, fine. I don't need something to be in equilibrium at its ground state. What if I pump it with stuff? Can I create a crystal that way? What if I pump it with energy? So it's now a non-equilibrium state like? There's there's energy coming in and then there's energy going out. But the way that this energy is transformed inside the system creates this periodic motion within the system. Right? Turns out that was possible. Okay. And for the longest time, people were studying these things called discrete time crystals.

• 49:27Krishna Choudhary?

  Um, they were systems that were kept out of equilibrium by this outside force. And it's not as simple as just like you just pump it rhythmically and then this thing goes by that. You know, then it's like, oh, like me on a swing, like doing my legs is a time crystal. Right? Like me at the playground is a time. No, no, that's not. It's not quite as simple. What you need is you need you need the the pumping to be done at a certain frequency. And then the the the crystal itself is doing it at a different frequency. Maybe it's at a harmonic, right? And um, there were specialized quantum systems that could do this, right? There were nuclear spins, trapped ions, cold cold atoms at extremely low temperatures, quantum weirdness. You know, it's like cool. Yeah. But.

• 50:12Krishna Choudhary?

  It's cool, but that's about it.

• 50:14Lester Nare?

  Yeah.

• 50:14Krishna Choudhary?

  Right? Like, maybe in a hundred years, it can, it can lead to like, you know, quantum devices and things like that. This paper is very cool because it's doing it in a classical system, which means no quantum weirdness. And it's doing it at room temperature.

• 50:29Lester Nare?

  Wow.

• 50:30Krishna Choudhary?

  And it's doing it at a big enough scale that we can see with our naked eye.

• 50:34Lester Nare?

  This is giving me L K ninety-nine vibes.

• 50:36Krishna Choudhary?

  It, yeah, but this is out of U C Boulder.

• 50:38Lester Nare?

  Yeah, so it's legit.

• 50:39Krishna Choudhary?

  And so it's pretty legit. U C Boulder has probably the best A M O department out of anywhere in the world.

• 50:46Lester Nare?

  Okay.

• 50:46Krishna Choudhary?

  Okay, atomic molecular optical. Those guys, those guys do it.

• 50:51Lester Nare?

  Let's invest in our university research institutions.

• 50:54Krishna Choudhary?

  Like, I mean, you know, Boulder has like the most PhDs out of any, out of any city.

• 50:58Lester Nare?

  I heard this recently.

• 50:59Krishna Choudhary?

  Yeah, and a lot of it has to do with U C Boulder. Out of U C Boulder came NIST, which is the National Institute for Standards and Technology.

• 51:05Lester Nare?

  Yes.

• 51:06Krishna Choudhary?

  There's a bunch of other science labs just in Boulder. U C Boulder itself has like four Nobel Prizes in physics just for A M O. Okay, like, not like, okay, there's one for cosmology, one for, it's just all like in the lab making like materials, right? They, they, they made the first Bose-Einstein condensate.

• 51:22Lester Nare?

  Mm-hmm.

• 51:22Krishna Choudhary?

  They're the ones who figured out how to trap ions using lasers and cool them down using lasers. So they're very good. So when a paper comes out of U C Boulder and it's in A M O, it's like, okay, these guys probably talked to their department and if it didn't pass like their.

• 51:37Lester Nare?

  Their own, yeah, they have the best in the world there.

• 51:39Krishna Choudhary?

  Yeah, yeah, yeah, it's like, so, so it's, it's, it's a really cool little thing that they've made out of liquid crystals. Right? These are the L C Ds.

• 51:48Lester Nare?

  Mm-hmm.

• 51:49Krishna Choudhary?

  And, and they made a, a macroscopic time crystal, okay? The, and, and what you can do is, wha- what's really cool is, first of all, you don't need a laser or oscillating magnetic field, like in those old time crystals. In the old ones, you needed a quantum system and you needed a laser, which means coherent light, a single frequency. And then you, or like a magnetic field that's oscillating at a single frequency and then that sort of. You know, drives this quantum system to to do this periodic motion. This is just like a light. You just shine a light on it and then it uses the energy from that light to create this periodic motion. Okay, and um it just uses LCD like liquid crystal technology, pneumatic liquid crystals.

• 52:33Krishna Choudhary?

  So the way that liquid crystals work, like, you know, you've used liquid crystals before. Um, it's it's a really simple technology. It actually won the Nobel Prize. Um, the idea is, so what does it mean by a liquid crystal? Okay, a crystal you usually think of as a solid, right? A solid meaning that you've got atoms in a regularly spaced pattern and they don't really move. In the liquid crystal, you've got molecules that are all sort of uh, you can think of them as like rods, many tiny rods. There are molecules that are elongated. And you can manipulate their direction using an electric field. Okay? So if you put an electric field in this direction, all of the molecules align in that direction.

• 53:19Krishna Choudhary?

  And you can have an electric field in this direction, which means all the molecules align in this direction. And what these molecules do is because they're small enough, they can actually influence the propagation of light. Hmm. Okay, and so that's exactly how liquid crystal displays work. What you do is you have a backlight, okay? That like lets and then you have a polarizer that polarizes all the light, so all of the electric fields are propagating in one direction. And what you can do is you can have a liquid crystal interface in between another polarizer. So now, if the light gets to the other polarizer and it's polarized in the same direction, it's going to be let through. But if the light is polarized in a different direction, in the perpendicular direction, then it's going to be blocked.

• 54:00Krishna Choudhary?

  And what you can do is use an electric field to manipulate the liquid crystals in the middle to influence the propagation of light. That's the fundamental technology. Okay, so you can have an electric field that sort of rotates the light. And then if it rotates in exactly the right way, then the light is gonna go through and I'm gonna see something. But if there's no electric field, or if I make the electric field this way, then all the rods are gonna be, you know, sort of in the perpendicular direction, the light is not gonna rotate and I'm gonna get blocked. Yes. And that's fundamentally how liquid crystals work. There are these, they're liquid in the sense that, you know, just how in a liquid, the molecules can move around. In this case, these liquid molecules, these rod-like molecules can move around, and they can be controlled by an electric field.

• 54:45Krishna Choudhary?

  And they can be controlled by light itself, right? Yes. So they figured, what I can do is I can create a liquid crystal, and this liquid crystal has exactly the right properties, where it can sort of act like a giant sort of, I guess, okay, so this liquid crystal can be oriented in such a way, that when it's shined on by light, what you're gonna get is deformations in the crystal, okay? Tiny little deformations. So what you can imagine is,

• 55:26Krishna Choudhary?

  let's say all of the liquid crystals, all of these rods are oriented in one direction, okay? And now what I do is, I introduce a tiny kink in this lattice. So they're all oriented in one direction, but I've taken like a tiny little neighborhood and I've like bent them in a certain way, okay? What you can do is create a material such that that bend, which becomes this sort of topological defect. Yes. This like idea of like, okay, this neighborhood has a tiny little bend or a twist. That twist can then influence the stuff around it, which can influence the stuff around it, which can influence the stuff around it. And what you get is this sort of traveling wave of disturbance. Yes. Okay? They're what are called topological solitons in physics. This idea that like,

• 56:11Krishna Choudhary?

  I've got this like disturbance and that disturbance kind of acts like a particle. Okay, because um it travels the same way as a particle. The orientation of that disturbance can have a charge in the sense that if I twist it clockwise, then it's a plus one. And if I twist it counterclockwise, it's a minus one. And that charge is conserved in the same way that sort of charge is conserved if I were to have like electrons moving around, right? And they can cancel each other out, kind of the same way that charges cancel each other out, right? So they they created this thing and they actually did the numerical calculation. So they they they wrote down an equation for how these solitons would interact with each other.

• 56:52Krishna Choudhary?

  And all of these deformations act like little quasi particles that interact with each other and have a physics to themselves.

• 57:01Lester Nare?

  Yes.

• 57:01Krishna Choudhary?

  That is an emergent property of the little tiny rods themselves.

• 57:06Lester Nare?

  That initial disturbance that has now created a cascade.

• 57:09Krishna Choudhary?

  Yeah.

• 57:09Lester Nare?

  That is now independent of the initial source necessarily being.

• 57:13Krishna Choudhary?

  Yeah. And and and it's like it's on top of the rods themselves. The rods actually aren't the particles anymore. It's like the the way in which the rods are oriented becomes a particle mathematically, right? You can like describe like you can describe the twist itself as this thing that propagates rather than the rods. Cause the rods are just staying where they are.

• 57:37Lester Nare?

  Right.

• 57:38Krishna Choudhary?

  Right, that's the crystal part of it. But the the the way that the rods move, that disturbance moves around like a particle.

• 57:46Lester Nare?

  This is really.

• 57:47Krishna Choudhary?

  Which is kind of cool, right?

• 57:48Lester Nare?

  It's very, that's like very interesting.

• 57:50Krishna Choudhary?

  Yeah, dude, solitons have been around like I think in the eighteen hundreds, there's this British guy, forget his name. Um, maybe we'll put it up.

• 57:57Lester Nare?

  Yes.

• 57:57Krishna Choudhary?

  But um it's a funny story because what he saw was he was he was, you know, these British physicists back in the day were very rich, right? So he's on horseback in the countryside, right? And he's like, he's like on horseback and he sees a canal and then there's a boat and the boat like breaks suddenly, okay? And when the boat breaks suddenly. He created this wave and he noticed that the wave just kept propagating. And then he was on horseback and he's got nothing to do. He's probably, you know, got a estate.

• 58:24Lester Nare?

  Right.

• 58:24Krishna Choudhary?

  That like gets him money.

• 58:26Lester Nare?

  Yes.

• 58:26Krishna Choudhary?

  Like in Downton Abbey or whatever. So he's like, fuck it. I'm gonna, I'm gonna follow this wave. And he followed it for two miles. There was a wave that kept reinforcing itself and it acted kind of like a particle, right? In the sense that the wave didn't really dissipate until two miles later. And he could follow this thing and he discovered the first soliton. There's a little plaque where he lived.

• 58:48Lester Nare?

  Yeah.

• 58:49Krishna Choudhary?

  Where it's like, this is the guy who discovered the first soliton. And um, ever since then, they've been observed in all sorts of sort of material sciences. You've, we've observed them in biology and quantum systems. And this is exactly one of those things where it's like, there's a wave that's being propagated. And that wave sort of reinforces itself because of the way that the, the, the medium itself works.

• 59:11Lester Nare?

  Works, right, right. It's, it is a combination of that input and the structure of the medium.

• 59:15Krishna Choudhary?

  Yes, exactly.

• 59:16Lester Nare?

  The liquid crystal.

• 59:18Krishna Choudhary?

  Yeah.

• 59:18Lester Nare?

  And the structure of the liquid crystal, crystal enables it to continue the propagation of the wave. Independent, like as, as a, as an, as an emergent property of the structure's initial condition.

• 59:31Krishna Choudhary?

  Exactly. Yeah, yeah. And so they, they, they figured that they could use this to make a classical.

• 59:37Lester Nare?

  Yeah.

• 59:37Krishna Choudhary?

  Time crystal.

• 59:38Lester Nare?

  Right.

• 59:38Krishna Choudhary?

  Because this is not quantum. This is, this is just, the, the rods themselves are like, you know, multiple, many, many atoms big.

• 59:45Lester Nare?

  Right.

• 59:45Krishna Choudhary?

  So these guys are interacting through just classical effects.

• 59:48Lester Nare?

  Yes.

• 59:48Krishna Choudhary?

  Right? And so what you can do is you can have a liquid crystal embedded inside glass, right? That have these two layers and as one layer sort of moves, it influences the light on the other layer. And then that thing moves and there's this feedback cycle, right? And that feedback cycle is what creates this propagation of. The time crystal and it's it's really a space time crystal because what you're seeing

• 1:00:11Lester Nare?

  Right.

• 1:00:12Krishna Choudhary?

  You can you can actually you can actually look at the videos and you can see like this the the colors move in real time and and the wavelength is like you know about half a millimeter to a millimeter which means you can see it with your naked eye and and it's moving through this liquid crystal in this sort of propagating you know traveling wave right and it it it was huge because one of the one of the big things that defines a crystal right is it has to be as I said before um crystals have to be resilient

• 1:00:45Lester Nare?

  Yes.

• 1:00:46Krishna Choudhary?

  To stress

• 1:00:46Lester Nare?

  Right.

• 1:00:47Krishna Choudhary?

  Okay.

• 1:00:47Lester Nare?

  Right.

• 1:00:47Krishna Choudhary?

  If I take a diamond and I press it or I heat it up the diamond is gonna retain its temperature so how did they actually test that here well what you can do is you can like poke it

• 1:00:56Lester Nare?

  Yeah.

• 1:00:56Krishna Choudhary?

  And the the the pattern stays which means that it is a true time crystal

• 1:01:02Lester Nare?

  Right it is resilient to

• 1:01:04Krishna Choudhary?

  To the poking

• 1:01:05Lester Nare?

  The poking of it already has

• 1:01:07Krishna Choudhary?

  Yeah it's got some time crystal going through and then when I poke it the time crystal sort of like it recovers where I poke it of course it's gonna like mess up but I remove it and then the the the crystal regains its properties

• 1:01:20Lester Nare?

  Yes.

• 1:01:20Krishna Choudhary?

  The other thing they did was they would they would um vary the brightness of the light

• 1:01:23Lester Nare?

  Yes.

• 1:01:24Krishna Choudhary?

  Because it can't be that like you know it depends really heavily on the brightness of the light so they they randomly vary the brightness of the light the crystal kept going which means that what what this is is really an intrinsic property of the material itself rather than the drive that's coming from the outside

• 1:01:39Lester Nare?

  Yes.

• 1:01:40Krishna Choudhary?

  Right?

• 1:01:40Lester Nare?

  No that that's a very that that's exactly

• 1:01:42Krishna Choudhary?

  And and and and then the final the final nail in the coffin for me was um what they did was they would turn off the light and then they would turn it back on again and if this is not a true crystal if this is simply a response to the light then when I turned it off I mean sorry when I turned it back on the crystal would start up at exactly the Same phase every time, meaning I turn it on. Five minutes later, the same pattern, I mean, sorry, five seconds later, the same pattern emergence as at exactly the same spot. But what what would happen was they would turn it off and then they turned the light back on. And it would randomly order itself. The same crystal would start.

• 1:02:24Krishna Choudhary?

  But at different starting points in that way, you see what I'm saying, like the phase offset was completely random.

• 1:02:30Lester Nare?

  Yes.

• 1:02:30Krishna Choudhary?

  Which again tells you this is not a property of the outside drive.

• 1:02:34Lester Nare?

  Right.

• 1:02:35Krishna Choudhary?

  It's a property of the of the material itself. So this is truly a time crystal that is macroscopic and it's something we can see.

• 1:02:43Lester Nare?

  This is, this is, I mean, this is.

• 1:02:45Krishna Choudhary?

  Right.

• 1:02:45Lester Nare?

  This is, this is really fascinating.

• 1:02:46Krishna Choudhary?

  It's really cool and and like, okay, you might be thinking, okay, this is like, this is cool, right? Then I got into reading about the applications.

• 1:02:56Lester Nare?

  Okay.

• 1:02:56Krishna Choudhary?

  Okay.

• 1:02:57Lester Nare?

  Yeah.

• 1:02:57Krishna Choudhary?

  The applications for this are like.

• 1:03:01Krishna Choudhary?

  Like, science fiction to me, okay? Most of them have to do with like. Cryptography and security, okay? First one I'll tell you about. Imagine. We make this thing cheap. We can stick it on a dollar bill.

• 1:03:18Lester Nare?

  Oh, right, as a, as a.

• 1:03:20Krishna Choudhary?

  As a.

• 1:03:21Lester Nare?

  Signature.

• 1:03:21Krishna Choudhary?

  As a cryptographic signature now, if you want to test whether your Benjamin is a real Benjamin. You take your iPhone flashlight, stick it on there, it's gonna have this pattern, right? Because all it needs is an external drive and the pattern is we can make it really hard to duplicate.

• 1:03:37Lester Nare?

  Yes.

• 1:03:37Krishna Choudhary?

  Right? So you know that strip that's on the Benjamin?

• 1:03:39Lester Nare?

  Yes.

• 1:03:40Krishna Choudhary?

  We can have that strip be a time crystal that like, like literally like. Propagates.

• 1:03:45Lester Nare?

  Yes.

• 1:03:45Krishna Choudhary?

  Right? And then you'll know, okay, that's a real one.

• 1:03:47Lester Nare?

  It has a signature that.

• 1:03:48Krishna Choudhary?

  And it's gonna be so hard to duplicate.

• 1:03:50Lester Nare?

  Right, right.

• 1:03:51Krishna Choudhary?

  Right?

• 1:03:52Lester Nare?

  Right, that, that, that.

• 1:03:53Krishna Choudhary?

  That's so cool.

• 1:03:54Lester Nare?

  No, that's very, I, this, that's actually really.

• 1:03:56Krishna Choudhary?

  Yeah, and the other one is like two D, like, so you know, usually we have two D barcodes, like a QR code. Is a two D. Now you can have a two D plus one barcode. You can have, you can have, um, a QR code. That. is 2D and then when you shine a light on it the QR code itself changes into different QR codes you can have multiple QR codes on top that have different periodicities so that like let's say one is like two seconds and the other one is three seconds and the other one is five seconds well then the next time that it's going to become a full QR code is gonna be five times three times two which is 30 right so you're gonna have to wait 30 seconds to get

• 1:04:39Krishna Choudhary?

  the actual QR code right you can you can imagine you've you've you've like you've introduced a whole new dimension

• 1:04:47Lester Nare?

  yes

• 1:04:47Krishna Choudhary?

  to to security

• 1:04:49Lester Nare?

  a manipulatable dimension

• 1:04:50Krishna Choudhary?

  yeah and and and the whole point is this is this is at room temperature

• 1:04:55Lester Nare?

  right

• 1:04:56Krishna Choudhary?

  and it's macroscopic it's something I can see I don't need a a telescope or like weird ions and lasers to actually oh look it's doing the thing

• 1:05:06Lester Nare?

  this is why I made the the LK99 reference not because of whether it was real or not real but because it's room temperature and macroscopic and the reason why that's material is that means the the the the transition from theoretical to production application

• 1:05:22Krishna Choudhary?

  yeah now we just gotta make it cheap which is honestly kind of like the easier part of the innovation right you know

• 1:05:28Lester Nare?

  it's an engineering problem

• 1:05:29Krishna Choudhary?

  yeah now it's like okay cuz we can make LCDs real cheap now right

• 1:05:33Lester Nare?

  right this is

• 1:05:34Krishna Choudhary?

  and like this this you know it's not it doesn't need a power source you just need to put it on there the power source is the light that I'm gonna shine on it it's kinda cool

• 1:05:43Lester Nare?

  I'm seeing from the um from the abstract here uh their potential uh techno uh technological utility includes optical devices photonics spacetime crystal generators telecommunications anti-counterfeiting design and again this is just a first that we haven't even

• 1:06:00Krishna Choudhary?

  yeah I mean I only I only talked about the the anti-counterfeiting and the security part but yeah as you said devices all sorts of stuff

• 1:06:08Lester Nare?

  there's all sorts of implications in terms of what we can get out of now this fundamental yeah like implementation experimentally at room temperature in a macroscopic form which is

• 1:06:20Krishna Choudhary?

  yeah I mean there's a reason why it was like picked up by so many news outlets

• 1:06:23Lester Nare?

  yeah it was yeah it was

• 1:06:24Krishna Choudhary?

  this is quite a big deal yeah

• 1:06:26Lester Nare?

  this is quite this is quite good they didn't get the they got nature materials they could've put it in nature but they said we'll put in nature materials

• 1:06:32Krishna Choudhary?

  they probably tried in nature first usually everyone does

• 1:06:37Lester Nare?

  first time crystals that you can see Really interesting story and the background is also

• 1:06:43Krishna Choudhary?

  Yeah, it's a great one.

• 1:06:44Lester Nare?

  Helpful to understand. We live in LA, so we know a lot of people that like to talk about crystals. This is a little bit different than those crystals.

• 1:06:49Krishna Choudhary?

  Mm-hmm. Yeah, this one actually works.

• 1:06:52Lester Nare?

  Speaking of California, for our third story, we're now going to move into the immunology space. Headline, hidden viruses in our DNA could be medicine's next big breakthrough. Scientists at La Jolla Institute for Immunology, when they're not out surfing on the beautiful sand beaches of San Diego, have decoded the 3D structure of an ancient viral protein hidden within our DNA.

• 1:07:18Krishna Choudhary?

  Our own DNA.

• 1:07:18Lester Nare?

  Our own DNA. This protein found on cancer and autoimmune cells has a unique shape that could unlock new diagnostics and therapies. This was published in Science Advances. Again, this is another California university. We have the most papers, the most patents, the most

• 1:07:38Krishna Choudhary?

  We got it.

• 1:07:39Lester Nare?

  Laureates. I just always have to make sure people know that we are winning.

• 1:07:41Krishna Choudhary?

  Yeah, we are winning. We are, we are winning. This is La Jolla, California, baby.

• 1:07:45Lester Nare?

  Yes.

• 1:07:46Krishna Choudhary?

  It's, um, it's right next to UC San Diego. UC San Diego is an amazing, amazing crucible for biotechnology and molecular biology research. It's kind of like the Silicon Valley for biology in some sense. Um, and this is a really groundbreaking achievement. It's the first time that we have ever published the structure of a human endogenous retrovirus, okay? And this is a virus that hides within our own DNA, you and ours.

• 1:08:14Lester Nare?

  I didn't even know that was possible.

• 1:08:15Krishna Choudhary?

  Yeah, this is crazy, dude. Eight percent of our DNA is viral endogenous DNA. Eight percent of our genome, approximately 98,000 annotated insertions are viruses that are like infiltrating, that have infiltrated. Dude, it's, it's, they're like, they're like sleeper cells, dude.

• 1:08:35Lester Nare?

  I was, this is when people say the aliens, uh, manufa- uh, created

• 1:08:39Krishna Choudhary?

  No.

• 1:08:39Lester Nare?

  They would argue, look, this is exactly what I'm talking about. The little viruses are there writing our stuff.

• 1:08:44Krishna Choudhary?

  It's crazy, it's crazy to think about. So, so first of all, I was like, I was like, how does this even get in, why is this in? My DNA, bro.

• 1:08:51Lester Nare?

  Right.

• 1:08:51Krishna Choudhary?

  Like, wha- what's going on? Okay, so it's it's crazy. These things are called retroviruses. Retrovirus is a is a virus that has, instead of using DNA as its genetic material, it uses RNA as genetic material. And what it does is when it infects a cell, it uses something called um reverse transcriptase. Usually transcriptase goes from DNA to RNA. This is the reverse process. So it's taking RNA and it's making double stranded DNA. So that's reverse transcriptase. And then what ends up happening is that reverse transcriptase goes inside the nucleus of our cells.

• 1:09:26Lester Nare?

  Yes.

• 1:09:27Krishna Choudhary?

  And then there's something called integrase, which is another viral protein that takes that DNA, that bit of viral DNA, and sticks it inside our chromosomal DNA. Now, if this happens to our skin cells, okay, we got like some viral DNA. But if it happens to our sperm and egg, now the next organism that gets that sperm and egg, the enti- all of the DNA

• 1:09:48Lester Nare?

  Has it.

• 1:09:48Krishna Choudhary?

  Is gonna have it, right? It, these are called germ line mutations.

• 1:09:51Lester Nare?

  I was literally saying, going back to our CRISPR story.

• 1:09:54Krishna Choudhary?

  Yes.

• 1:09:54Lester Nare?

  It's the germ line.

• 1:09:55Krishna Choudhary?

  It's the germ line mutations, right?

• 1:09:56Lester Nare?

  Yes.

• 1:09:56Krishna Choudhary?

  So this is a germ line insertion that happens. And then now the virus becomes something called a pro-virus.

• 1:10:02Lester Nare?

  Okay.

• 1:10:02Krishna Choudhary?

  Which is something that's just hanging out in our DNA.

• 1:10:05Lester Nare?

  Yes.

• 1:10:05Krishna Choudhary?

  Eight percent of our DNA.

• 1:10:07Lester Nare?

  Comes from this.

• 1:10:08Krishna Choudhary?

  Comes from this. Dude, that's one in twelve. That's like a lot.

• 1:10:11Lester Nare?

  That's a lot.

• 1:10:12Krishna Choudhary?

  That's a lot.

• 1:10:12Lester Nare?

  I had no, I had no idea this was even a thing when we first put the story in the show notes.

• 1:10:16Krishna Choudhary?

  Crazy.

• 1:10:17Lester Nare?

  I was like, this is fascinating.

• 1:10:18Krishna Choudhary?

  Yeah, yeah, yeah. So all of all of that junk DNA, eight eight percent of that is is is viruses just hanging out. Okay, now, most of these viruses, they get mutations over the years and they can become inactive. Okay? But there's a specific um virus called the human endogenous virus K. The Herv K virus.

• 1:10:36Lester Nare?

  Herv K.

• 1:10:36Krishna Choudhary?

  It's a pro-virus now because it's within our DNA. But this thing is the most recent infiltrator. Okay, and it's because it's the because it's the most recent infiltrator, it has the fewest number of mutations. Right? Which means it's still a problem. Okay, and it actually, so in most um, in most healthy cells, there's epigenetic silencing, okay? Our our DNA is figured out, I don't know who you are. I'm gonna, I'm gonna just put a bunch of like random stuff on you. So that no one ever transcribes you into RNA and then you become a protein. So it, our DNA is very good. If you're healthy, the cell is healthy. It find, it's like, I don't know what this is. It's like a bouncer at a club. Yeah, it's like, you're already in here, but you're cut off.

• 1:11:22Krishna Choudhary?

  It's like, I don't know how you got in, but no more drinks. Okay? Every once in a while, you get something like a cancer cell. Or you get um autoimmune disorders. The cell is losing control and this virus can start acting up. Okay, so it's actually been detected this H. Herv K envelope. The envelope protein that is the, the, the protein that encodes for the envelope of the virus. That's the thing that snuck in. Right? That has been known to be expressed in cancers like breast cancer, ovarian cancer, prostate cancer, melanoma. And also in autoimmune disorders like lupus, um diabetes type one, um SLE.

• 1:12:05Krishna Choudhary?

  These kinds of autoimmune disorders, you can actually see the cells that are affected. Express this Herv K protein. Which means that it is actually a problem. Which means it needs to be solved. Okay, and in biology, a lo- like half the battle is solving the structure. Because all of biology is lock and key, right? You solve the structure of the thing, then you can figure out what other structures can latch on and like mess with it and like. Inactivate it and things like that, right? So the first, first battle is to actually solve the structure. Solving the structure for this thing was really hard. Okay, because it's this envelope protein of a, you know, it used to be back in its heyday.

• 1:12:47Krishna Choudhary?

  Right before it snuck in and now it's like, just like an infiltrator. Back in its heyday, it was the envelope protein for a retrovirus, right? And these envelope proteins are incredibly finicky.

• 1:13:02Krishna Choudhary?

  By design, you want your envelope protein to be finicky because imagine you're a virus, right? And you're getting to the outside of a cell that you wanna infiltrate. You want the protein to first be able to infiltrate through the membrane, and then when it's in the membrane, change its conformation to open up, right? So you want this thing to have this sort of metastability is what it's called, where you've you've got two states. There's this pre-fusion state and then a post-fusion state, right? Pre-fusion, meaning like, how do I get in? Post-fusion, how do I?

• 1:13:32Lester Nare?

  You have the Trojan horse go to the gate in one state, and then when it's inside the gate, it's

• 1:13:37Krishna Choudhary?

  You gotta open up, yeah, right? So, so you want this metastability.

• 1:13:41Lester Nare?

  Yes.

• 1:13:42Krishna Choudhary?

  Now, that becomes a real problem when you're trying to get structure.

• 1:13:46Lester Nare?

  Yes.

• 1:13:46Krishna Choudhary?

  Right? Because you can imagine, you're you're trying to image this thing, but this this thing is in two different confirmations. So like, you don't know what you're looking at.

• 1:13:55Lester Nare?

  Yes.

• 1:13:55Krishna Choudhary?

  And it's just annoying.

• 1:13:56Lester Nare?

  Yes.

• 1:13:57Krishna Choudhary?

  Right? So that's that's the the big thing that this group solved, okay? What they did, the first thing they did was they they took the the protein itself, and they put in, um, they they tweaked the protein in a certain way that they could, like, they created these things called disulfide bridges, which are basically like staples on the protein. What you do is you create, you you put in cysteine, which is this particular amino acid that has sulfur atoms, and those sulfur atoms can find each other and sort of bond.

• 1:14:26Lester Nare?

  Yes.

• 1:14:27Krishna Choudhary?

  So you you you create a a more stable protein.

• 1:14:32Lester Nare?

  Yes.

• 1:14:32Krishna Choudhary?

  That is still very much like the original protein. It it still preserves a lot of the structure, but it prevents the protein but from doing this finicky stuff.

• 1:14:41Lester Nare?

  Yes.

• 1:14:42Krishna Choudhary?

  And then what they do was they use a groundbreaking technology, the one, the 2017 Nobel Prize in Chemistry, called cryo-electron microscopy.

• 1:14:50Lester Nare?

  Okay.

• 1:14:51Krishna Choudhary?

  Okay? It used to be called blobology.

• 1:14:54Lester Nare?

  Blobology.

• 1:14:55Krishna Choudhary?

  Yeah, from all the detractors, all the people who would make fun of these cryo-EM people, it was called blobology. Because back in the day, what you do is you you get a protein, and you like image it with electron microscope.

• 1:15:07Lester Nare?

  Yeah.

• 1:15:07Krishna Choudhary?

  But because of this problem of like, you know, the The proteins move around and then they're not stable and all this other stuff. And you would get blobs, giant blobs, and you'd be like, it kinda looks like this. So all of the X-ray crystallographers and the NMR spectroscopy people, they're like, look at these, look at these blobologists, right? Because with X-ray crystallography and with NMR, I can get down to atomic resolution. I can get to two or three angstroms of resolution where I'm like, that atom is there and it's there. The problem with X-ray crystallography and NMR is it's really good for soluble proteins. So proteins that are found, you know, within the cell, doing their thing. But for these transmembrane proteins, it's very hard to crystallize.

• 1:15:52Krishna Choudhary?

  It's very hard to make them behave properly. CryoEM was a technique that probably could have been used for that. Along came the computing revolution. And now all of a sudden, what you could do is you could take thousands of images in cryoEM. What you do is you have a bunch of proteins that are sort of frozen in this state. Using this thing called vitreous freezing. Where you're not like freezing it with ice, because if you freeze it with ice, the protein's gonna like misfold, right? So you do this like weird like sort of vitreous freezing where the protein retains its structure. You image it a bunch of times and then you feed that thing to a computer. What you're getting is 2D shadows, right? The proteins are in different orientations.

• 1:16:34Krishna Choudhary?

  You get a bunch of 2D shadows, but a computer now can take all of those 2D shadows and say, what is the 3D thing that would create all of these 2D shadows? Right? In 2012 was the big one when it came out. And there was finally a protein that cryoEM had solved that no one else could solve with any other technique. And they solved it to three angstrom precision. And everyone was like, oh, oh, it's here. And then in 2017, they won the Nobel Prize in Chemistry. It was three guys, Joaquin Frank, Yakes Duboishe and Richard Henderson. So blobology now became like a Nobel Prize winning technology. There ain't no, ain't no bunch of blobs now, huh? Where's your Nobel, huh? I think they were, I think they were very vindicated when they actually got it, right?

• 1:17:17Krishna Choudhary?

  So these guys, they actually used the cryo-electron microscopy to get the data from this. After having messed with the protein to create these staples and make it sort of. Stable, right? And this was a very big deal because now you've got the 3D structure for this thing. You can compare it with other retroviruses that have been solved like HIV, like SIV.

• 1:17:40Lester Nare?

  Yes.

• 1:17:40Krishna Choudhary?

  And this one is very different because this, the, the, the, the protein that they came out is like taller and skinnier than the HIV protein, which is interesting in its own right because now we've got this difference. We can now start creating antibodies.

• 1:17:56Lester Nare?

  Right.

• 1:17:56Krishna Choudhary?

  To actually target this thing.

• 1:17:58Lester Nare?

  Lock and key thing you were just talking.

• 1:17:59Krishna Choudhary?

  Exactly, and that's what they did. They weren't done. They created monoclonal antibodies to actually target this thing. And what they could do now is you can actually have diagnostics where, you know, in autoimmune disorders, for example, right? You have these neutrophils, which are these kinds of immune cells. And what they do is they, um, they, they're, they're expressed in these cells. And then in an autoimmune disorder, now your immune cells think that, oh, this is a bad cell. I'm going to attack my own cell, right? So maybe now that we know the structure.

• 1:18:32Lester Nare?

  Right.

• 1:18:32Krishna Choudhary?

  We can actually like prevent that from happening, right? We can, we can train the immune system or maybe cloud the, these antibodies in such a way that the immune system no longer attacks its own. On the other hand, we can also have ways to early diagnose certain cancers because cancer cells express this protein.

• 1:18:51Lester Nare?

  Specifically.

• 1:18:52Krishna Choudhary?

  Specifically, right? So if we get like a blood sample from somebody, we can have an early diagnostic where you have these monoclonal antibodies that'll go and actually attach to these cancer cells and you'll have a marker now be like, oh, I see this HERV K protein.

• 1:19:08Lester Nare?

  Yes.

• 1:19:08Krishna Choudhary?

  That shouldn't be expressed. In a healthy cell, the epigenetics should totally silence it.

• 1:19:13Lester Nare?

  And it's not.

• 1:19:14Krishna Choudhary?

  But the bouncer is not working, right?

• 1:19:16Lester Nare?

  Right.

• 1:19:16Krishna Choudhary?

  So now, now I can, I can, I can start therapies earlier.

• 1:19:19Lester Nare?

  They're, they're still in the club, getting too drunk.

• 1:19:21Krishna Choudhary?

  Yeah.

• 1:19:22Lester Nare?

  They haven't been cut off.

• 1:19:22Krishna Choudhary?

  Yeah.

• 1:19:23Lester Nare?

  So let's go ahead and.

• 1:19:23Krishna Choudhary?

  Let's go ahead and, and, and try to figure out how, how to get these guys out.

• 1:19:27Lester Nare?

  That's really.

• 1:19:28Krishna Choudhary?

  Right? It, it's, it's the first time that we've done this.

• 1:19:31Lester Nare?

  And the idea is now that we've done it once, but by confirming that this methodology is a means by which you can do so.

• 1:19:37Krishna Choudhary?

  Yeah.

• 1:19:37Lester Nare?

  This can likely be extended to other ones. This is the most recent and all these.

• 1:19:41Krishna Choudhary?

  Yeah, and this this is the one that's like most prevalent, but the the idea of like sort of changing a protein's shape. Using these editing mechanisms where now I can have this like staple disulfide bridge that sort of stabilizes it. Such that I can now do cryo E M. This is a this is a pretty interesting technique. The same group. Um, actually had done it for other proteins and then they tackled this one because this one's hard. Right? This one's like.

• 1:20:06Lester Nare?

  If you can do it with this one.

• 1:20:07Krishna Choudhary?

  Yeah, then it's like, okay, now it's like, now we can. It's a cool one.

• 1:20:14Lester Nare?

  I I I always love our our like microbiology immunology stories because. People don't understand how well we can. Uh, look at and analyze and understand things that are really, really, really, really small.

• 1:20:29Krishna Choudhary?

  Yeah, like we can, we know exactly where to put in the cystine so that the sulfur staples to another sulfur. But it doesn't really change the rest of the structure. That's like to to, you know, have like this thousands of atoms worth of. Protein and know exactly where to put this thing so that I'm just gonna clip this part.

• 1:20:47Lester Nare?

  Yes.

• 1:20:47Krishna Choudhary?

  Because that's the part that's like getting messed up.

• 1:20:50Lester Nare?

  I would like our next Department of Health and Human Services Secretary to be able to describe in detail. Any number of these concepts.

• 1:21:00Krishna Choudhary?

  Yeah.

• 1:21:00Lester Nare?

  Because that is a usually a good prerequisite to say you're gonna actually understand the import.

• 1:21:06Krishna Choudhary?

  Yeah.

• 1:21:06Lester Nare?

  Uh, of medicine for public health.

• 1:21:08Krishna Choudhary?

  Exactly, mate.

• 1:21:10Lester Nare?

  But but that that's a good, I like that one. I like that. And we we've touched on CRISPR a lot on this podcast. We've touched on a variety and it's again, it's interesting again, all of these innovations are happening simultaneously in these cross domain areas. That have not only independent value, but also like collective value.

• 1:21:26Krishna Choudhary?

  Yeah.

• 1:21:27Lester Nare?

  As we move into what we're seeing is gonna be this like. Biotech revolution.

• 1:21:32Krishna Choudhary?

  It is. It really is. We're here.

• 1:21:34Lester Nare?

  For whole AI applying the tools, the fundamental hardware tools. The creativity of how we're problem solving.

• 1:21:43Krishna Choudhary?

  Yeah.

• 1:21:45Lester Nare?

  We're gonna, we're gonna go to our last story, which is a lot of times I do from really, really small now to like

• 1:21:50Krishna Choudhary?

  Yeah, now we're getting really big.

• 1:21:52Lester Nare?

  Now we're getting really big in space. California again, California forever goodbye. Headline, brightest fast radio bursts ever detected could help solve an enduring cosmic mystery. I love how people with headlines make it so unclear what you're talking about. Summary, researchers at University of California, Santa Cruz, we're going to Northern California, use newly, newly developed Chime out trigger telescopes and deep space imaging to challenge long-held assumptions about what causes these mysterious cosmic signals. I think we talked about one of these, if I'm not misremembering, the WOW signal was one of these

• 1:22:32Krishna Choudhary?

  Yes.

• 1:22:33Lester Nare?

  Like radio burst.

• 1:22:34Krishna Choudhary?

  It was a radio burst, right?

• 1:22:35Lester Nare?

  That we initially saw and everyone freaked out and was like aliens.

• 1:22:38Krishna Choudhary?

  Yeah. It could have been and that's not the, we haven't characterized that as a fast radio burst.

• 1:22:45Lester Nare?

  Fair.

• 1:22:46Krishna Choudhary?

  Because we don't really know what the hell that was.

• 1:22:47Lester Nare?

  That's fair. That's kind of like, what was that?

• 1:22:49Krishna Choudhary?

  Yeah, what, what was that?

• 1:22:50Lester Nare?

  Fair. No, that's fair. That's fair. But it seems like we're, we're now using again, the tool, some of the tools we have also, this was in the Astrophysical Journal Letters.

• 1:22:58Krishna Choudhary?

  Yes.

• 1:22:59Lester Nare?

  In terms of the publication, CNN has covered this. UCSC also covered it in their own blog.

• 1:23:03Krishna Choudhary?

  Yeah. It's a collaboration between UCSC, some Canadian institutions, Northwestern. It was a pretty big collaboration.

• 1:23:11Lester Nare?

  That's, again, because we need it. Okay, so what, what, I don't like, what are, because you, because I mischaracterized, what is like this fast radio burst idea? What did they do?

• 1:23:20Krishna Choudhary?

  Yeah.

• 1:23:21Lester Nare?

  Why, like, how are they, why is detecting a bright one relevant?

• 1:23:26Krishna Choudhary?

  Yeah. This one's, this one's incredibly bright, okay? This thing, this thing within a fraction of a second output as much energy as the sun does for like four days.

• 1:23:36Lester Nare?

  Okay.

• 1:23:37Krishna Choudhary?

  But that's, this isn't even the brightest, okay? This is the brightest we've had because it's the closest one to us. But fast radio bursts, the first one was ever discovered in 2007. It was called a Lorimer Burst. It was actually taken from archival data from the Parks Observatory, which is a giant 64-meter radio telescope in Australia. It's been called the greatest scientific instrument that Australia has ever produced. The greatest scientific instrument that Australia has ever produced. And It's the same dish actually was used during the Apollo eleven um broadcast to like broadcast to the TVs around the world because um NASA had like a thing at Goldstone.

• 1:24:20Lester Nare?

  Yes.

• 1:24:20Krishna Choudhary?

  And that they were using.

• 1:24:22Lester Nare?

  Yes.

• 1:24:22Krishna Choudhary?

  But this one was way bigger.

• 1:24:24Lester Nare?

  Yeah.

• 1:24:24Krishna Choudhary?

  And the TV signal that they were getting from this one was just better than the rest. And so the NASA just used it for the whole two and a half hours, which is kind of cool.

• 1:24:32Lester Nare?

  Which is why the Five Eyes ally, you know.

• 1:24:34Krishna Choudhary?

  Yeah, yeah, you know, yeah, Australia, yeah, they got our back when we need it. So, you know, they were on the right side, they were facing the moon, so that was nice.

• 1:24:43Lester Nare?

  Yep.

• 1:24:43Krishna Choudhary?

  Um, so this burst was discovered by Duncan Lamar from West Virginia University. Basically, what he did was he assigned a an undergrad to look at archival data from the Parks Observatory. Okay, and the Parks Observatory at the time had just released a bunch of data. It was a radio telescope that was just beaming up. And um this undergrad would come in every week and despite all of his classes and stuff. He would look at a bunch of data by hand and try to characterize it. And then try to find something interesting and he found something very interesting. There was a brief millisecond duration, five milliseconds, but it was ridiculously bright. On top of that, it was not only bright, it had this very good characterization called dispersion.

• 1:25:27Krishna Choudhary?

  Okay, dispersion is the idea that when light moves through a medium, through stuff, different frequencies are going to propagate at different speeds. This is fundamentally why we get a rainbow, okay? Violet light actually propagates at a slower speed in water than red light does, okay? And because of that, when light goes into a water bubble, the violet light is going to bend differently than red light. And that's what's going to cause the rainbow to come out, okay? And then it gets like sort of focused and we get a rainbow, but the prism is the same idea. When it goes through glass, violet light goes slower and so it's going to bend differently.

• 1:26:09Krishna Choudhary?

  Dispersion is this idea that there's a frequency relation to how fast light moves through medium. And in interstellar.

• 1:26:18Krishna Choudhary?

  Background, right, in the interstellar medium of these ionized particles, right, where it's like atoms without electrons, electrons moving around freely, um, you're gonna have that opposite effect. You're gonna have slower slower light, so slower frequencies, moving slower than the faster frequencies. Just has to do with the different physics that goes on between a glass and a plasma. But at the end of the day, what that means is if there's a transient burst of light, the faster stuff is gonna arrive first and the slower frequencies are gonna arrive later. And that's what's called a dispersion measure. Okay? This thing that they discovered in the Parks Observatory data, which is now called the Lorimer Burst, had this very specific dispersion measure, which showed that it was of extragalactic origin.

• 1:27:03Lester Nare?

  Okay.

• 1:27:04Krishna Choudhary?

  There was so much dispersion.

• 1:27:05Lester Nare?

  Yeah.

• 1:27:06Krishna Choudhary?

  That meant that there was a lot of stuff that it had to get through.

• 1:27:10Lester Nare?

  Yeah, to create.

• 1:27:11Krishna Choudhary?

  To actually create that delay between the fast and the slow. And then when they back calculated, how bright this thing must have been to be that far away.

• 1:27:20Lester Nare?

  Right.

• 1:27:21Krishna Choudhary?

  They were like, oh, this thing was incredibly bright. This was back in 2007. Since then, we've discovered multiple. There's been some that we've discovered where for that brief millisecond duration, this fast radio burst was brighter than the entire galaxy that it came from.

• 1:27:38Lester Nare?

  Wow, okay.

• 1:27:39Krishna Choudhary?

  Okay?

• 1:27:39Lester Nare?

  Yeah.

• 1:27:40Krishna Choudhary?

  So, it's been, it's been, it's been quite an insane sort of last few decades.

• 1:27:46Lester Nare?

  Right.

• 1:27:46Krishna Choudhary?

  Of trying to find these fast radio bursts.

• 1:27:48Lester Nare?

  Right.

• 1:27:49Krishna Choudhary?

  The problem is they're really short-lived.

• 1:27:51Lester Nare?

  Right.

• 1:27:51Krishna Choudhary?

  Okay, five milliseconds.

• 1:27:53Lester Nare?

  Unlike Three Eye Atlas, which we're watching for months.

• 1:27:55Krishna Choudhary?

  Yeah, yeah, which we know for months and we can like coordinate this thing, you know, it's just, it's there and it's gone.

• 1:28:00Lester Nare?

  And it happens.

• 1:28:01Krishna Choudhary?

  And it just so happens, right? So, it's, it's been, it's been kind of challenging to actually find them.

• 1:28:06Lester Nare?

  Right.

• 1:28:07Krishna Choudhary?

  It's been kind of rare. Um, along came this detector called CHIME in Canada, which is the, let me just get the thing right, because I don't want any Canadians to get mad at me. It's called the Canadian Hydrogen Intensity Mapping Experiment, CHIME. Um, it's, it's a massive radio telescope that doesn't look like most radio telescopes. So, you know, most radio telescopes, you've got a circular dish with a, with a receiver and, and, and the light goes that way. This thing is a bunch of half pipes that are just laid out on the ground. Oh, interesting. Giant half pipes, okay, a hundred meters that are laid out on the ground, four of them in a valley in British Columbia.

• 1:28:48Krishna Choudhary?

  Um, as south as you can possibly get because what they're using, they're using the earth's rotation to basically scan the sky. Okay. In this radio frequency. Yep. And you know, Canada's pretty far north. Yeah, yeah. So they wanna get as south as possible. So it's like right across the border from America. Um, and it's this giant thing and it's made such that it's really sensitive. It's got all these capabilities for as soon as a signal comes in, it's kinda like the Vera Rubin in terms of they've got online capabilities to analyze the signal. Yep. And it's also got a really good giant field of view. So it's capturing a big part of the sky as it sort of goes around the earth. And um, very recently, so Chime has, Chime has found thousands of fast radio bursts since twenty eighteen. Okay.

• 1:29:31Krishna Choudhary?

  Okay, it's found a bunch. This one is very, very nice because usually when Chime found finds fast radio bursts, it can't localize where it came from. Right. Because it's got this giant field of view, it just sees sort of a signal. Yes. And it's like, okay, I saw a fast radio burst. Don't know where it came from. So what they did was i- in collaboration with America, they made more Chime stations. There's one in California, there's one in West Virginia, there's one also in Canada. And now what you can do is triangulate. My favorite. Right? And what you can do is if you get a fast radio burst, you're gonna get that signal all over the place and you can triangulate where it came from. And actually resolve what part of the sky it came from.

• 1:30:12Krishna Choudhary?

  Because you have multiple uh, multiple receiving points at different places on the planet. Exactly. Angle at. It's gonna be different and the timing is gonna be different. Yeah. And you can back calculate and see where it came from. Yep. And what they could do is they could resolve it to a really tiny area in the sky, right around the Big Dipper. Um, the equivalent would be to resolve a quarter from a hundred kilometers away. Very tiny, very tiny, tiny spot. Yeah, yeah. Right? And. That gives you the advantage. Because now, if you know that it came from there. Yes. You've got all these other telescopes on standby that can point right there. Right? That's exactly what they did. They got the James Webb. Yes. They called in the big guns. Yeah, they called in the big guns. They called in the big guns, because this one was really bright. Okay.

• 1:30:56Krishna Choudhary?

  Okay, in terms of, this is the brightest fast radio burst that we've ever seen. Because of its proximity to Earth. Not in terms of intrinsic brightness, but because of its proximity to Earth, now it's really exciting, right? Because now we can point optical telescopes to it. Yes. And we can actually see what part of this galaxy that it came from. It came from NGC 4141, which is this barred spiral galaxy. And what it does is, and you can localize the neighborhood of that galaxy. Not just that it came from that galaxy, but it came from this corner of the galaxy. Okay? Um, and now you can point James Webb Space Telescope to it. And James Webb was pointed to it. Yes. It found a faint signal in the infrared. Okay. Right around that same spot. Okay.

• 1:31:41Krishna Choudhary?

  And that probably came from some massive stars, like a red giant or something like that. Now, doesn't quite fit that a red giant or a big star would create a fast radio burst. Okay. Okay? Because those things are like, slow. Right. They're not five millisecond. Right. Time scales. Right. Five millisecond time scales are the stuff of black holes. Right. Neutron stars. They revolve really fast, you know? So there's time scales that sort of correspond to astronomical objects. Yes. Right? And...

• 1:32:14Krishna Choudhary?

  So, so now it leaves us with a conundrum. It's like, where did this thing come from? There's hypotheses, there's not good data. Because again, this is the first time, I mean, Chime and the, the Chime outrigger stations only came online like this year. Okay. So this is the first thing that it's found. And it's very exciting because it's kind of a proof of concept that it's like looking and it can find it. And then we can go off with, with James Webb Space Telescope, with Keck, with Gemini and point it at that. And then actually see a follow-up observation, right? So we still don't know really where this thing came from. What we do know, which is very interesting, is this might be a one-off. Most of the fast radio bursts that we've seen, they seem to be repeating fast radio bursts, right?

• 1:32:59Krishna Choudhary?

  Where they've, they've got this rhythmic sort of structure. The rhythm can be very long. It can be from days to months to years. But... They've got this rhythmic thing where it's like, okay, you've got one really bright one. But then every once in a while, the same source should put off like sort of smaller bursts.

• 1:33:15Lester Nare?

  Which I think is why it matters that we have this this multi this multi sensor data confirmation. Uh, multi sensor collaboration to be able to isolate a smaller point in the sky. Because if we do find these rhythmic sources, we can point these things, these other tools there. For longer periods of time.

• 1:33:34Krishna Choudhary?

  Exactly.

• 1:33:34Lester Nare?

  To try to potentially catch what is this? It reminds me of the transients conversation we had the other day where it's like. There's this rhythmic pattern of the planet, the exoplanet going in front of a star.

• 1:33:43Krishna Choudhary?

  Yeah.

• 1:33:43Lester Nare?

  And so you have to monitor it for certain periods of time to understand that it's not a one off.

• 1:33:47Krishna Choudhary?

  It's not a one off, yeah.

• 1:33:48Lester Nare?

  Um, and so what's interesting here is like what we're potentially seeing with this specific really, really bright one. May have been a one off.

• 1:33:54Krishna Choudhary?

  It may have been, I mean, we think it's a one off because Chime was going around. That same spot in the sky for the past like seven years. It's had hundreds of hours in that region of the sky.

• 1:34:05Lester Nare?

  It's the only one.

• 1:34:05Krishna Choudhary?

  So we've only seen it once, right? And it would have, it would have found even this even smaller radio bursts, but it hasn't.

• 1:34:12Lester Nare?

  Hasn't.

• 1:34:13Krishna Choudhary?

  And so it's like, what could be this one off thing? It could be they're they're thinking it might be a magnetar, which is this. A magnetar is a.

• 1:34:22Lester Nare?

  Not a Pokemon.

• 1:34:23Krishna Choudhary?

  No, it sounds like one though. Um, a magnetar is sort of a newly born neutron star. That's highly magnetized, so it's got really powerful magnetic fields. And it's in a sort of new stellar neighborhood that has magnetic material around it. So it can create these fast radio bursts by sort of, maybe it's like accumulating material and then it blows up or something. Uh, maybe it's accumulating material from the red giants that the James Webb Space Telescope saw. The James Webb saw some signal, they just don't know, it's like not good enough, right? And because it's transient, it only happened for a little bit and then and then and then it's gone. It's not like a star that I can just keep looking at and and getting data, right?

• 1:35:05Krishna Choudhary?

  Um, it could be a magnetar, it could also be a colliding neutron star. But if it was colliding, you know, sort of revolving colliding neutron stars, we would have seen LIGO.

• 1:35:15Lester Nare?

  Yeah.

• 1:35:15Krishna Choudhary?

  We would have seen gravitational waves, which we haven't in the hours preceding or since. So maybe the the collision is gonna happen.

• 1:35:23Lester Nare?

  Mm hmm.

• 1:35:24Krishna Choudhary?

  Later, and this is like, maybe they're getting close and doing some weird dance. And then that like released a giant fast radio burst.

• 1:35:30Lester Nare?

  Mm hmm.

• 1:35:32Krishna Choudhary?

  But i- it's a new, it's a new scale of astronomy, right? Where before we had like only a few stations that were relying on the Earth's rotation.

• 1:35:40Lester Nare?

  Right.

• 1:35:40Krishna Choudhary?

  To like maybe catch something.

• 1:35:42Lester Nare?

  Yes.

• 1:35:42Krishna Choudhary?

  Right? And, and now we've got a dedicated sort of instrument.

• 1:35:45Lester Nare?

  Yes.

• 1:35:46Krishna Choudhary?

  That is doing it on the northern hemisphere. You can imagine we can create a global celestial.

• 1:35:50Lester Nare?

  Yes.

• 1:35:51Krishna Choudhary?

  Radio instrument that now does this. Actually, the VLA also took a look at it.

• 1:35:55Lester Nare?

  Yes.

• 1:35:56Krishna Choudhary?

  Because now that we can locate it here.

• 1:35:57Lester Nare?

  Yes.

• 1:35:58Krishna Choudhary?

  The VLA took a look at it for like several days afterwards, trying to see if there's gonna be a um, a repeat.

• 1:36:04Lester Nare?

  Yes.

• 1:36:04Krishna Choudhary?

  Didn't see one. So this does-

• 1:36:06Lester Nare?

  Being the Very Large Array.

• 1:36:07Krishna Choudhary?

  Yes, the Very Large Array in New Mexico, which is a giant interferometer.

• 1:36:11Lester Nare?

  Yes.

• 1:36:11Krishna Choudhary?

  Of a bunch of radio dishes on train tracks.

• 1:36:13Lester Nare?

  For those who, I think the movie was, uh.

• 1:36:16Krishna Choudhary?

  Contact.

• 1:36:17Lester Nare?

  Contact with, uh, uh, Jodie Foster.

• 1:36:20Krishna Choudhary?

  Yeah.

• 1:36:20Lester Nare?

  Yeah, it was-

• 1:36:21Krishna Choudhary?

  Written by Carl Sagan.

• 1:36:22Lester Nare?

  Written by Carl Sagan was at the, the Very Large Array.

• 1:36:24Krishna Choudhary?

  Yeah.

• 1:36:24Lester Nare?

  Uh, class, but, but again, this is, this, this goes back to, I'm glad the outriggers were able to get out before funding got cut.

• 1:36:31Krishna Choudhary?

  Yeah.

• 1:36:31Lester Nare?

  Um, this is why things like, you know, Chime, the Verarubin, which have this very specific use case of sky surveys. That are not, uh, that are just saying, we're just gonna get this.

• 1:36:42Krishna Choudhary?

  Yeah.

• 1:36:42Lester Nare?

  This data set, no-

• 1:36:44Krishna Choudhary?

  Because we don't know where to look.

• 1:36:45Lester Nare?

  We don't know where to look.

• 1:36:47Krishna Choudhary?

  We're just looking everywhere.

• 1:36:48Lester Nare?

  So we're gonna create this map.

• 1:36:49Krishna Choudhary?

  Yeah.

• 1:36:50Lester Nare?

  And then that'll help us know where to look.

• 1:36:51Krishna Choudhary?

  Yeah.

• 1:36:52Lester Nare?

  And then everyone can write their proposals to then use these specific other tools to then look much more deeply.

• 1:36:58Krishna Choudhary?

  Yeah. And it's, it's kind of, it's, I mean, fast radio bursts are only 20 years old. You know, in terms of the grand scale of astronomy.

• 1:37:05Lester Nare?

  Right.

• 1:37:05Krishna Choudhary?

  That's a hundreds of years of old science.

• 1:37:08Lester Nare?

  Yes.

• 1:37:08Krishna Choudhary?

  Right? Like, only 20 years ago, we found the first one. And these things are so ridiculously bright. And it's like, what could possibly be making?

• 1:37:18Lester Nare?

  Yes.

• 1:37:18Krishna Choudhary?

  Something that is as bright as a galaxy for a fraction of a second.

• 1:37:21Lester Nare?

  Right, right.

• 1:37:22Krishna Choudhary?

  You know?

• 1:37:23Lester Nare?

  Uh, don't get the Dyson Sphere people in on this. Be like, oh, obviously.

• 1:37:27Krishna Choudhary?

  Yeah.

• 1:37:28Lester Nare?

  It's a, it's a alien civilization that's harnessed the power of a planet. And then when they recycle their-

• 1:37:32Krishna Choudhary?

  Yeah.

• 1:37:33Lester Nare?

  Generatron, it sends out this massive, I'm being facetious.

• 1:37:37Krishna Choudhary?

  Yeah. We should have a, we should have a, an, an episode about Freeman Dyson, though. He's one of my favorite physicists.

• 1:37:42Lester Nare?

  Same.

• 1:37:43Krishna Choudhary?

  He's one of my favorite physicists of all time.

• 1:37:44Lester Nare?

  Love, love Dyson.

• 1:37:46Krishna Choudhary?

  Yeah.

• 1:37:46Lester Nare?

  Um, very clever.

• 1:37:48Krishna Choudhary?

  Yeah.

• 1:37:48Lester Nare?

  Interesting.

• 1:37:49Krishna Choudhary?

  Really funny, too.

• 1:37:49Lester Nare?

  Yeah, yeah.

• 1:37:50Krishna Choudhary?

  Yeah, really funny guy.

• 1:37:52Lester Nare?

  brightest fast radio bursts ever detected.

• 1:37:55Krishna Choudhary?

  Yeah.

• 1:37:55Lester Nare?

  Because of the some of the tools that we have, it's such a new area.

• 1:37:59Krishna Choudhary?

  Such a new area.

• 1:38:01Lester Nare?

  And we haven't figured it all out yet.

• 1:38:03Krishna Choudhary?

  No.

• 1:38:04Lester Nare?

  There are really.

• 1:38:05Krishna Choudhary?

  No, there are mysteries out there in the universe.

• 1:38:07Lester Nare?

  And and it we we are doing good work to try to narrow.

• 1:38:12Krishna Choudhary?

  Yeah.

• 1:38:13Lester Nare?

  The the path towards discovery around some of these things.

• 1:38:16Krishna Choudhary?

  Yeah, and it's like, you know, when the Vera Rubin, I was listening to the um, the press conference for the Vera Rubin the other day. And they were talking about, they use Donald Rumsfeld's unknown unknowns.

• 1:38:27Lester Nare?

  Classic.

• 1:38:28Krishna Choudhary?

  But it it actually, it actually made sense here because you know, there are the known unknowns. Which is like, what is causing the expansion of the universe? What is dark energy? What is dark matter?

• 1:38:39Lester Nare?

  Yes.

• 1:38:40Krishna Choudhary?

  What are these fast radio bursts?

• 1:38:41Lester Nare?

  Yes, we know that they're there, but they're unknown and what they.

• 1:38:45Krishna Choudhary?

  And in what they are.

• 1:38:46Lester Nare?

  Right.

• 1:38:46Krishna Choudhary?

  And then he said, what I'm really excited about with the Vera Rubin is the unknown unknowns. Because before two thousand seven, fast radio bursts were an unknown unknown, right?

• 1:38:56Lester Nare?

  Yeah.

• 1:38:56Krishna Choudhary?

  People couldn't even imagine that something like this would exist.

• 1:38:59Lester Nare?

  Right.

• 1:38:59Krishna Choudhary?

  Where in five milliseconds, it dumps like a ridiculous amount of energy.

• 1:39:03Lester Nare?

  Yes.

• 1:39:03Krishna Choudhary?

  You know, that time scale for that amount of energy is insane.

• 1:39:07Lester Nare?

  And and who knows how many, what number of unknown unknowns.

• 1:39:10Krishna Choudhary?

  The Vera Rubin is gonna find.

• 1:39:11Lester Nare?

  As we have these better tools.

• 1:39:12Krishna Choudhary?

  Yeah, and what the chime is gonna find too, maybe it'll find like, super fast.

• 1:39:16Lester Nare?

  Yes.

• 1:39:17Krishna Choudhary?

  Radio bursts, you know, that are like.

• 1:39:18Lester Nare?

  Right.

• 1:39:19Krishna Choudhary?

  My at the microsecond level.

• 1:39:20Lester Nare?

  Right.

• 1:39:20Krishna Choudhary?

  You never know.

• 1:39:21Lester Nare?

  Never know. You never know. We we always cover a really fascinating array of stories each week. We started with a deep dive on DeepSeek, no pun intended. And the geopolitical power war that is currently happening between the US and China. As leaders, Europe, you know, eat your heart out. Um, you know, Mistral is not really in the same category.

• 1:39:45Krishna Choudhary?

  Yeah.

• 1:39:46Lester Nare?

  We went then to time crystals, the first time crystals that are room temperature and macroscopic.

• 1:39:53Krishna Choudhary?

  That I can see.

• 1:39:53Lester Nare?

  That we can see. Out of University of Colorado Boulder. Implications for any number of use cases anti like, like security features, technology, devices. The third story was really fascinating about hidden viruses in our DNA. Could be big for medicine breakthroughs.

• 1:40:14Krishna Choudhary?

  Yeah.

• 1:40:14Lester Nare?

  Um, the fact that viruses are eight percent.

• 1:40:18Krishna Choudhary?

  Of our DNA.

• 1:40:18Lester Nare?

  Of our DNA. Uh, and that these, there's these indicators that drive cancer and autoimmune diseases. And understanding the structure, understanding the lock now gives the ability to build a key. And then fast radio bursts. Still an enduring mystery.

• 1:40:33Krishna Choudhary?

  Yeah.

• 1:40:34Lester Nare?

  Um, about where is all of this massive scale of light in such a short time scale? What cosm- cosmological.

• 1:40:46Krishna Choudhary?

  Yeah.

• 1:40:46Lester Nare?

  Event.

• 1:40:47Krishna Choudhary?

  Could create something like this.

• 1:40:48Lester Nare?

  Could create something like that. Um, another great week, again, the feedback, we're still in the top charts. On Apple for science podcasts.

• 1:40:57Krishna Choudhary?

  Keep telling your friends.

• 1:40:58Lester Nare?

  Please keep sharing with your friends. The comments are hilarious. You, all you are comedians, some really, really funny comments. I do talk. I don't just sit here and nod my head. Also, my hairline does, is not that crazy. This is not Stephen A. Smith.

• 1:41:13Krishna Choudhary?

  Yeah. And he's not the black guy from New Girl.

• 1:41:16Lester Nare?

  I'm not, I'm not Lamorne Morris. Although I appreciate, Lamorne, if you want to have us on the Lamorning Podcast, we're literally down the street. We'd love to talk to you about science. Uh, my name is Lester Nare, joined as always by my co-host and our resident PhD, Krishna Choudhary. This is From First Principles. We'll see y'all next week. Peace.