humanology 2237 .

Huhnkie Lee

science stories

Transcript

00:00:00Hello friends. Yeah, welcome to Humanology 2237. Happy, uh, happy Thursday morning. Yeah,

00:00:17I took a bath. So it's like 11am. Yeah. So let's do some stretching. Okay.

00:00:33Stretching.

00:00:39All right.

00:01:03Mm hmm.

00:01:25Mm hmm.

00:01:45Mm hmm.

00:02:15Mm hmm.

00:02:43Okay.

00:02:45Okay.

00:02:47Oh.

00:02:57Okay.

00:03:25Mm hmm.

00:03:53Oh.

00:04:11Okay.

00:04:15Okay.

00:04:17Okay.

00:04:19Okay.

00:04:43Okay.

00:05:07Okay.

00:05:15Okay.

00:05:19Okay.

00:05:41Okay.

00:05:45Now.

00:05:54A.

00:06:02Let's see.

00:06:06Let's do a freestyle like animal form. Kung Fu. Okay.

00:06:14Oh.

00:06:20Very Tai Chi. Let's do Tai Chi. Okay.

00:06:30Okay.

00:06:54Oh.

00:07:18Good. Five minutes break. Thank you. Mm hmm.

00:07:29Oh.

00:07:51Yeah.

00:08:11Mm hmm.

00:08:29Okay.

00:08:53Mm hmm.

00:09:13Mm hmm.

00:09:31Mm hmm.

00:09:51Mm hmm.

00:10:19Mm hmm.

00:10:25Okay.

00:10:49Mm hmm.

00:11:17Mm hmm.

00:11:41Mm hmm.

00:12:09Mm hmm.

00:12:31Mm hmm.

00:12:55Mm hmm.

00:13:11Mm hmm.

00:13:36Happy Thursday.

00:13:38Yeah, Thursday is the day where I weekly apply to unimprove my insurance.

00:13:45But I do that after I take a nap.

00:13:47Yeah.

00:13:48Yeah.

00:13:50Ah.

00:13:53Yep.

00:13:56Let's get back to mathematics. Okay.

00:13:58All right.

00:14:08Let's review.

00:14:26The common divisor set theorem that we proved.

00:14:55Yeah, here it is.

00:15:03Hmm.

00:15:07Okay.

00:15:10Yeah.

00:15:13Welcome to human allergy episode number 2237.

00:15:20Yeah.

00:15:23Let's see.

00:15:31Uh.

00:15:35Okay.

00:15:49Okay.

00:15:54We'll make the connection later.

00:16:23Common divisor set.

00:16:27Okay.

00:16:28We have that.

00:16:35Well, there are common divisor set of A and B is the same as common divisor set of A and AY plus BZ.

00:16:44Given A and Z are coprom to each other, okay?

00:16:50So.

00:16:54Uh.

00:17:03We can also say this, okay?

00:17:20Common divisor set of A, B is same as common divisor set of B and AY plus BZ.

00:17:35Given that B and Y are coproms to each other, okay?

00:17:41Yeah.

00:17:43Yeah.

00:17:55Meaning, yeah.

00:17:59B and Y, the coefficient of A has to be coprom or A and Z.

00:18:07Okay?

00:18:10Z means the coefficient of B, they have to coprom to each other, okay?

00:18:14So, yeah, yeah.

00:18:16Good.

00:18:23Mm-hmm.

00:18:26Nice.

00:18:30I'm kind of hungry, okay?

00:18:33It's like 1130 a.m. and I woke up and then I applied to one more job this morning, okay?

00:18:42Yeah.

00:18:44And we'll see what happens.

00:18:51I took a shower, took a shower bath, and I didn't eat anything this morning, so I'm hungry, but, gosh.

00:18:59Yeah.

00:19:17Okay.

00:19:28Okay.

00:19:31Now, so, basically, common divisor set, the way it works is this.

00:19:38Common divisor set of A and B is the same as common divisor set of A and AY plus BZ, that's a linear combination of A and B.

00:19:48Given that A and Z, they're coproms, Z is like the coefficient for the other number.

00:19:59Okay.

00:20:00Coefficient of B.

00:20:02Okay?

00:20:04So, common divisor set of A and B is the same as common divisor set of B and AY plus BZ, given that Y, which is coefficient of A, is coprom with B.

00:20:18Okay?

00:20:20Now, it's a little bit confusing because we are dealing with letters, okay?

00:20:32Now, let's say we're not going to reuse A and B because then it becomes super confusing, okay?

00:20:39We could use N and M.

00:20:43N is equal to M times Q plus R.

00:20:52Euclidean division, given that R is a remainder.

00:20:59When N is divided by M, Q is quotient, R is remainder.

00:21:05Meaning R is between zero, zero inclusive, and strictly less than M because M is the divider, okay?

00:21:21Yeah.

00:21:26So, now R is equal to N minus MQ.

00:21:37Okay?

00:21:39This is a linear combination.

00:21:42We have 1 times N and M times, okay, let's rewrite this.

00:21:54Which is linear combination N times 1 plus M times minus Q.

00:22:05Okay?

00:22:07Just like this, AY plus BZ, okay?

00:22:10N times 1, M times minus Q, okay?

00:22:14Now, N times 1, N's coefficient is 1.

00:22:211 is coprime with any number.

00:22:26Here, 1 and N, they are coprime, okay?

00:22:35We have that.

00:22:36A and Z being coprime, okay?

00:22:39What this means is this.

00:22:43We are making connection with Euclidean division and common divisor set theorem, okay?

00:22:53It's quite exciting.

00:22:56Cheers.

00:23:01Yeah, we got some inspired by, like, internet community, like AI result and other webpages.

00:23:07It helps.

00:23:10Yeah.

00:23:15So...

00:23:40Let's say...

00:24:09A and Z, they are coprime, okay?

00:24:301 and M, they are coprime.

00:24:32And 1, that's coefficient.

00:24:36Let's say 1 is Z in this formula, okay?

00:24:401 corresponds to Z.

00:24:47M corresponds to A.

00:24:53N corresponds to B.

00:24:58Minus Q corresponds to Y.

00:25:02Okay?

00:25:05And then to rewrite this,

00:25:12common divisor set of A and B,

00:25:18M and N

00:25:24is same as common divisor set of M,

00:25:32comma,

00:25:38Ay plus Bz.

00:25:43N times minus Q

00:25:48plus N times 1,

00:25:54which is same as common divisor set of

00:26:01M, comma.

00:26:03Yeah, minus Q times N plus N times 1.

00:26:07That's R.

00:26:12This is connection between common divisor set theorem and Euclidean algorithm.

00:26:20Also, the bridge between the two concepts, the bridge to fill the gap between the two concepts,

00:26:29between Euclidean theorem and common divisor set theorem,

00:26:33that bridge is Euclidean division and linear combination, okay?

00:26:38We got it.

00:26:40Okay?

00:26:41Yeah.

00:26:42I'll bring this closer to you, and then we'll take five minutes break, okay?

00:26:45Then I'll start cooking my lunch.

00:26:48I'm hungry.

00:26:50Okay.

00:26:52All right.

00:26:54Five minutes break.

00:26:56Nice.

00:26:57This is neat.

00:26:59Very cool stuff.

00:27:07Okay.

00:27:27Flare reflection.

00:27:30All right.

00:27:33Can you read this?

00:27:39Yeah.

00:27:40If you cannot, yeah, screenshot this and enlarge it, okay?

00:27:49Well, let me bring it closer to you, okay?

00:27:52Now you can read it better, right?

00:27:54Yeah.

00:27:55The other stuff, it is from yesterday, so.

00:28:07Okay.

00:28:08Right.

00:28:09Five minutes.

00:28:11Yeah.

00:28:12I'm hungry.

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00:35:28A valid concept from other web pages.

00:35:31This is good.

00:35:33We've had some good help.

00:35:36I mean, some continuing legal education about AI, they talked about it.

00:35:43Lawyers, actually, we are supposed to use AI.

00:35:46Why?

00:35:47Because it makes our job more efficient.

00:35:49It has to do with competence in the professional rules of conduct.

00:35:55Okay, because like with AI, we can solve some legal problem

00:36:02faster than otherwise, okay?

00:36:05Have I used AI as a lawyer?

00:36:07Yeah, just Google search, Bing search.

00:36:11By default, they do generate some AI, right?

00:36:13Yeah, result.

00:36:14Yeah, I have used it, helpful.

00:36:19But of course, you need to do some double checking,

00:36:21citation and everything,

00:36:22because AI results sometimes are wrong.

00:36:25But it's still helpful, okay?

00:36:27It's not perfect, but it's getting better.

00:36:31Okay, yeah, nice.

00:36:35This is very significant, okay?

00:36:36Dovetailing between something new and something old.

00:36:40Connecting the dots, okay?

00:36:41Nice, this is nice, this is beautiful.

00:36:44Okay?

00:36:47So we have proved like plus part, right?

00:36:50But minus part is same, exact same proof, okay?

00:36:54It's just substituting minus sign instead of plus sign,

00:36:59exact same thing, okay?

00:37:04All right, good.

00:37:07Now, we did good mathematics, right?

00:37:09Now let's hope something else.

00:37:11Okay?

00:37:13Yeah, let's put this behind us.

00:37:15Okay.

00:37:23It's beautiful, yeah, well done, well done.

00:37:28Yeah.

00:37:31Fantastic.

00:37:32That's beautiful, yeah, this is great.

00:37:37What we did was we proved Euclidean theorem with,

00:37:46common divisor set theorem.

00:37:49We proved common divisor set theorem, right?

00:37:52Now Euclidean theorem became a corollary implication,

00:37:56consequence of the common divisor set theorem, okay?

00:38:00I mean, Euclidean theorem,

00:38:01they already proved it some other way,

00:38:04but we proved it on our own methodology.

00:38:10Okay, that's so nice.

00:38:12Yeah.

00:38:15Yeah.

00:38:18Cheers.

00:38:24Beautiful, fantastic.

00:38:29Yeah, I'm unemployed,

00:38:30but I'm doing my job as a mathematician, okay?

00:38:33So, yeah.

00:38:36Unemployed as a lawyer,

00:38:37but doing my job as a mathematician.

00:38:39Good.

00:38:43Yeah.

00:38:45Nice.

00:38:54Yeah.

00:38:58So, yeah, last night we talked about my,

00:39:06undergraduate major,

00:39:09computer science undergraduate days,

00:39:12medicine at Wisconsin University in general.

00:39:14Yeah.

00:39:15After that, to continue that story,

00:39:18yeah, I went to Cornell University where I was born,

00:39:22where my father got PhD in economics, 1978.

00:39:28So I went back there.

00:39:30Okay.

00:39:31For my own PhD in computational biology,

00:39:33computer science department.

00:39:35Yeah.

00:39:36But I dropped out after two years, okay?

00:39:40Yeah.

00:39:42Why?

00:39:44I realized it's not for me, PhD career, okay?

00:39:47But that two years I learned a lot.

00:39:51So it was good education there.

00:39:56Well,

00:39:58met many good people.

00:40:00It was good.

00:40:06Yeah.

00:40:09Yeah.

00:40:16I did take some classes when I was in Cornell.

00:40:21I did take some undergrad level classes too, okay?

00:40:24Like biochemistry.

00:40:27Okay, yeah.

00:40:31Microbiology class.

00:40:34I actually took those classes for credit and yeah.

00:40:40I got A's.

00:40:43Some other classes I audited,

00:40:46meaning I attended the classes.

00:40:50I did not put audit registration.

00:40:52That means that you don't do homework

00:40:54and you don't take exams.

00:40:56You just attend the classes.

00:40:59I did that on differential equation class in mathematics

00:41:04and also physical chemistry class.

00:41:08Also in biology,

00:41:11senescence class.

00:41:12It's about aging.

00:41:14Okay, yeah.

00:41:19Biology of aging, senescence class.

00:41:23They were good.

00:41:28And some computer science classes,

00:41:30like undergraduate level, I audited.

00:41:33Why?

00:41:34Because as a PhD candidate in computer science,

00:41:38we had to take qualified exams

00:41:41to test the knowledge in undergrad level

00:41:44in artificial intelligence, operating system.

00:41:48System in general,

00:41:51like system meaning like a network,

00:41:53operating system, database, okay?

00:41:58And artificial intelligence and numerical analysis

00:42:00and computer architecture

00:42:05and algorithm and also computer programming languages.

00:42:10Theoretical computer science.

00:42:13I passed all four except one,

00:42:16computer architecture, more hardware-based.

00:42:19That's the only qualified exam that I failed.

00:42:22Okay, yeah.

00:42:23But in my year, first year, PhD,

00:42:28I was the only one who passed four out of five.

00:42:31I was a top student in Cornell, okay?

00:42:35But after two years, I ended up dropping out, okay?

00:42:40So I realized that it wasn't for me.

00:42:42It was just too much studying.

00:42:45I like studying, but I don't wanna study too much, you know?

00:42:48Okay.

00:42:52Five minutes break, book a rest.

00:42:54I'll tell you some more stories, okay?

00:42:56Yeah, sure.

00:42:57Sorry, time?

00:42:57Yeah.

00:42:58Nice.

00:42:59Very cool.

00:43:27Okay.

00:43:57Okay.

00:44:27Okay.

00:44:57Okay.

00:45:27Okay.

00:45:57Okay.

00:46:03And that's it.

00:46:28Okay.

00:46:29Okay.

00:46:30Okay.

00:46:31Okay.

00:46:32Okay.

00:46:33Okay.

00:46:34Okay.

00:46:35Okay.

00:46:36Okay.

00:46:37Okay.

00:46:38Okay.

00:46:39Okay.

00:46:40Okay.

00:46:41Okay.

00:46:42Okay.

00:46:43Okay.

00:46:44Okay.

00:46:45Okay.

00:46:46Okay.

00:46:47Okay.

00:46:48Okay.

00:46:49Okay.

00:46:50Okay.

00:46:51Okay.

00:46:52Okay.

00:46:53Okay.

00:46:54Okay.

00:46:55Okay.

00:46:56Okay.

00:46:57Okay.

00:46:58Okay.

00:46:59Okay.

00:47:00Okay.

00:47:01Okay.

00:47:02Okay.

00:47:03Okay.

00:47:04Okay.

00:47:05Okay.

00:47:06Okay.

00:47:07Okay.

00:47:08Okay.

00:47:09Okay.

00:47:10Okay.

00:47:11Okay.

00:47:12Okay.

00:47:13Okay.

00:47:14Okay.

00:47:15Okay.

00:47:16Okay.

00:47:17Okay.

00:47:18Okay.

00:47:19Okay.

00:47:20Okay.

00:47:21Okay.

00:47:22Okay.

00:47:23Okay.

00:47:24Okay.

00:47:25Okay.

00:47:26Okay.

00:47:27Okay.

00:47:28Okay.

00:47:29Okay.

00:47:30Okay.

00:47:31Okay.

00:47:32Okay.

00:47:33Okay.

00:47:34Okay.

00:47:35Okay.

00:47:36Okay.

00:47:37Okay.

00:47:38Okay.

00:47:39Okay.

00:47:40Okay.

00:47:41Okay.

00:47:42Okay.

00:47:43Okay.

00:47:44Okay.

00:47:45Okay.

00:47:46Okay.

00:47:47Okay.

00:47:48Okay.

00:47:49Okay.

00:47:50Okay.

00:47:51Okay.

00:47:52Okay.

00:47:53Okay.

00:47:54Okay.

00:47:55Okay.

00:47:56Okay.

00:47:57Okay.

00:47:58Okay.

00:47:59Okay.

00:48:00Okay.

00:48:01Okay.

00:48:02Okay.

00:48:03Okay.

00:48:04Okay.

00:48:05Okay.

00:48:06Okay.

00:48:07Okay.

00:48:08Okay.

00:48:09Okay.

00:48:10Okay.

00:48:11Okay.

00:48:12Okay.

00:48:13Okay.

00:48:14Okay.

00:48:15Okay.

00:48:16Okay.

00:48:17Okay.

00:48:18Okay.

00:48:19Okay.

00:48:20Okay.

00:48:21Okay.

00:48:22Okay.

00:48:23Okay.

00:48:24Okay.

00:48:25Okay.

00:48:26Okay.

00:48:27Okay.

00:48:28Okay.

00:48:29Okay.

00:48:30Okay.

00:48:31Okay.

00:48:32Okay.

00:48:33Okay.

00:48:34Okay.

00:48:35Okay.

00:48:36Okay.

00:48:37Okay.

00:48:38Okay.

00:48:39Okay.

00:48:40Okay.

00:48:41Okay.

00:48:42Okay.

00:48:43Okay.

00:48:44Okay.

00:48:45Okay.

00:48:46Okay.

00:48:47Okay.

00:48:48Okay.

00:48:49Okay.

00:48:50Okay.

00:48:51Okay.

00:48:52Okay.

00:48:53Okay.

00:48:54Euclidean theorem.

00:49:11That's not Euclidean theorem.

00:49:12It's more like Euclidean algorithm.

00:49:15Okay.

00:49:22Okay.

00:49:24How did they generalize this?

00:49:27That was generalization, okay?

00:49:39That is like rational real numbers.

00:49:42Well, we only dealt with integers, okay?

00:49:45Yeah.

00:49:47We generalize in terms of integers only, okay?

00:49:51Yeah.

00:49:52But they generalize the rational number, real number,

00:49:59maybe complex numbers, I don't know.

00:50:01Polynomials, Gaussian integers, whatever that is.

00:50:11Because I was wondering if they,

00:50:13if it was discovered,

00:50:15common divisor set theorem is already discovered or not.

00:50:20Okay, so.

00:50:23It doesn't seem to be.

00:50:26Okay, so it's brand new.

00:50:27Okay, good enough.

00:50:29Okay, yeah.

00:50:32The word discovered most likely is brand new.

00:50:35Okay.

00:50:38Because we are very good at it.

00:50:40Cheers.

00:50:41Now back to story time.

00:50:48So my academy advisor in computer science department,

00:50:52yeah, wonderful gentleman, professor, okay.

00:50:55Contextual biology, okay, so.

00:50:58But he's kind of old school, okay, so.

00:51:00Because I wanted to be his student.

00:51:01I wanted him to be my academy advisor.

00:51:04Okay.

00:51:05What is an academy advisor in PhD program?

00:51:08Well, in PhD program,

00:51:10basically you work with a professor.

00:51:13You belong to that professor's group.

00:51:16In a university, professors,

00:51:22we are talking about like,

00:51:24the kind of universities that have graduate,

00:51:26like PhD programs, okay.

00:51:29So in universities, with PhD program,

00:51:35the professors, they have their research group.

00:51:40Okay.

00:51:43So professors, who are the members of research group?

00:51:48Well, you're a professor, right?

00:51:49And then you have PhD students, okay.

00:51:56Now let me check on my launch.

00:52:20Okay.

00:52:40Yeah, cooking some chicken wings,

00:52:42like drumettes and flats.

00:52:46So, in a university, like graduate level, okay,

00:52:51you have a research group headed by professor, okay.

00:52:57And under professor, you have PhD students

00:53:02who belong to that group, research group, okay.

00:53:06And also post-doctoral personnel.

00:53:09Post-doctoral personnel, who are post-doctorals,

00:53:16they already have their PhD, okay.

00:53:21It's quite common, okay.

00:53:22So after a person get PhD,

00:53:27many times they apply for post-doctoral position

00:53:34in a university or some research institutions, okay.

00:53:38They're researchers, basically research assistants.

00:53:43They already have PhD, okay.

00:53:45And then after maybe one year

00:53:48post-doctoral research experience,

00:53:52then they get applied for like professor job

00:53:55or researcher job in a university

00:53:58or research institutions or, okay, yeah.

00:54:02Okay.

00:54:06And so professor in a research group,

00:54:12they have to fund them, okay.

00:54:17With PhD students,

00:54:19there are two ways to earn a living as PhD students, okay.

00:54:22First, teaching assistant, TA,

00:54:26in the undergraduate level classes,

00:54:30like to lead a discussion,

00:54:32to score the quiz exams, okay, teaching assistants, okay.

00:54:39To lead like this discussion group and more, okay.

00:54:43And another way to earn a living as a PhD student,

00:54:48research assistant, okay.

00:54:52And that's what I got, RA, okay.

00:54:56To belong to a group led by a professor, okay.

00:55:00Yeah, so research assistant, that's what I got, okay.

00:55:05Which is typically more prestigious than TA

00:55:08because it's no teaching duty, basically, okay, so.

00:55:15As a research assistant, yeah, we do the research

00:55:19and then we publish academic paper with a professor, okay.

00:55:26Yeah, and we get paid, okay.

00:55:31And postdoctoral personnel, they get paid too, okay.

00:55:37So professors, they apply to grants,

00:55:41like research grants from the government typically,

00:55:46government agencies,

00:55:48or some private institutions too sometimes, okay.

00:55:53Now let's take five minutes break, yeah, focalized, okay.

00:55:57Yeah, we'll talk about some academia, graduate level.

00:55:59Sure, sure.

00:56:01Yeah, five minutes break, thank you.

00:56:26Okay.

00:56:56Okay.

00:57:26Okay.

00:57:56Okay.

00:58:26Okay.

00:58:56Okay.

00:59:26Okay.

00:59:48Oh, oh, professors in universities,

00:59:54graduate level, who have like their own research group,

00:59:58they are some of the most capable people in the world,

01:00:02okay, because they have to feed

01:00:07their hungry graduate students,

01:00:09sometimes like master's levels,

01:00:10sometimes undergrad level too, okay.

01:00:12So basically, well, very academic, okay, so.

01:00:17So to feed the hungry like graduate students

01:00:24and postdoctorals, they write grant proposal for a project,

01:00:32okay, if it gets approved,

01:00:34then they get grant for the project

01:00:38to pay for their research assistants, okay.

01:00:42But in my case, I got a fellowship program.

01:00:49What is fellowship?

01:00:49It's a scholarship, okay,

01:00:51so funded partially by private organizations, okay,

01:00:56like foundations, okay, yeah.

01:01:00Yeah, to fund the scientific research, okay,

01:01:05so I got some fellowship.

01:01:07The fellowship program I got

01:01:09was a tri-institutional fellowship, okay.

01:01:12It's a three institutions,

01:01:14like Sloan Kettering Cancer Research Center,

01:01:16which is in Manhattan, New York.

01:01:18Yeah, I've been there, okay, I did some internship there.

01:01:21And Cornell University and Rockefeller University.

01:01:25Rockefeller University, yeah, I had visit their campus too.

01:01:29It's also in Manhattan, New York, okay,

01:01:32a research institution, okay, okay.

01:01:36Yeah, so basically, I got funding from them, okay,

01:01:45so that my professor does not have to pay me, okay.

01:01:49Yeah, my case was kind of exceptional case, okay,

01:01:52so but yeah, but still the professors

01:01:58heading a research group,

01:02:00they are some of the most highly qualified people

01:02:04in the world, okay, so yeah.

01:02:08And they worked really hard, long hours, okay.

01:02:13They're like boss of this like private entities,

01:02:18like startup companies, okay, so yeah.

01:02:24Basically, feeding their employees, okay,

01:02:26bread owner, land maker, when lawyer selling, okay,

01:02:31so okay, yeah, it's like that, okay,

01:02:34so yeah, dedicated professionals, okay, yeah.

01:02:40But also in public sector, okay,

01:02:42I have many friends in public sector too,

01:02:44yeah, dedicated professional there, okay,

01:02:46working long hours, okay, like in Alaska city,

01:02:51yeah, like borough, there's a county level, okay,

01:02:54assembly and people in the borough governmental,

01:02:59the county level basically, okay,

01:03:01yeah, they work long hours, I know, yeah.

01:03:04Because like when I ran for Alaska State Senate

01:03:10back in like, you know, 2020,

01:03:12yeah, I went to like borough meetings,

01:03:14which is open meeting to citizens, okay,

01:03:17so yeah, they work long hours, yeah.

01:03:23Dedicated professionals, okay, yeah.

01:03:32Hard working people, okay, yeah.

01:03:45So my academy advisor, I don't know if he belongs

01:03:48to this group, but he's old school,

01:03:50so hey, before you decide to choose our group,

01:03:55explore, take some other classes of other professors

01:03:59and see if basically, yeah, before you make a decision,

01:04:05explore other area in computational biology

01:04:09and then make your choice.

01:04:12It's good advice, right?

01:04:13Yeah, yeah, absolutely, yeah.

01:04:22And then later on in my,

01:04:24I was there for two years, Cornell, okay,

01:04:27but later on, I proved something in mathematics.

01:04:31They're kind of tangentially related

01:04:33to computational biology, okay.

01:04:35And I presented that, now that I proved it,

01:04:38some small theorem in like, yeah, mathematics,

01:04:42but tangentially related to computational biology, okay.

01:04:45Then I presented the proof to the gentleman professor

01:04:52and then he really was impressed and he really liked it.

01:04:56Okay, so, and then he said,

01:04:58okay, you wanna join us?

01:04:59Yeah, join us, okay, yeah, nice.

01:05:08Yeah, I remember, okay.

01:05:13But I did end up dropping out

01:05:16because it was just too much studying,

01:05:19I could not handle it, okay, so.

01:05:21But they understood, okay.

01:05:25But the thing is this, okay,

01:05:28I learned a lot when I was there,

01:05:31although only for two years, but still, I learned a lot.

01:05:36And later on,

01:05:41well, after that, after Cornell,

01:05:43I went to Los Angeles, California.

01:05:47Then I joined the US Army and then I went to law school

01:05:51and then I came to Alaska 10 years ago.

01:05:55And in Alaska,

01:05:59I got back to science

01:06:04in an independent capacity.

01:06:08And I'm still doing science, like mathematics.

01:06:12And I'm contributing to science

01:06:16as an independent scholar for free.

01:06:22Okay.

01:06:26So like Mr. Dijak said in Bible, New Testament, okay,

01:06:31what you got for free,

01:06:35give it for free, give it back.

01:06:37So it's kind of like that, okay, yeah.

01:06:43So all the investments on me

01:06:45to educate me in all those wonderful schools,

01:06:50now I'm giving back to humanity for free

01:06:55because I got for free education,

01:06:57now I'm giving back to humanity for free.

01:07:00The result of the science that I discovered

01:07:05right here in Humanities School.

01:07:07Okay, yeah.

01:07:08So I'm doing my job.

01:07:11Okay, very cool.

01:07:13Yeah, nice.

01:07:17Yeah, welcome to Humanities School, okay.

01:07:22Time check.

01:07:25It's been more than one hour, okay, so.

01:07:26And my lunch is almost ready,

01:07:28so let's take five minutes break, okay, yeah.

01:07:31Very cool.

01:07:32Let's ventilate the room.

01:07:36Nice.

01:07:54Okay.

01:08:24Okay.

01:08:54Okay.

01:09:24Okay.

01:09:54Okay.

01:09:55Okay.

01:09:56Okay.

01:09:57Okay.

01:09:58Okay.

01:09:59Okay.

01:10:00Okay.

01:10:01Okay.

01:10:02Okay.

01:10:03Okay.

01:10:04Okay.

01:10:05Okay.

01:10:06Okay.

01:10:07Okay.

01:10:08Okay.

01:10:09Okay.

01:10:10Okay.

01:10:11Okay.

01:10:12Okay.

01:10:13Okay.

01:10:14Okay.

01:10:15Okay.

01:10:16Okay.

01:10:17Okay.

01:10:18Okay.

01:10:19Okay.

01:10:20Okay.

01:10:21Okay.

01:10:22Okay.

01:10:23Okay.

01:10:24Okay.

01:10:25Okay.

01:10:26Okay.

01:10:27Okay.

01:10:28Okay.

01:10:29Okay.

01:10:30Okay.

01:10:31Okay.

01:10:32Okay.

01:10:33Okay.

01:10:34Okay.

01:10:35Okay.

01:10:36Okay.

01:10:37Okay.

01:10:38Okay.

01:10:39Okay.

01:10:40Okay.

01:10:41Okay.

01:10:42Okay.

01:10:43Okay.

01:10:44Okay.

01:10:45Okay.

01:10:46Okay.

01:10:47Okay.

01:10:48Okay.

01:10:49Okay.

01:10:50Okay.

01:10:51Okay.

01:10:52Okay.

01:10:53Okay.

01:10:54Okay.

01:10:55Okay.

01:10:56Okay.

01:10:57Okay.

01:10:58Okay.

01:10:59Okay.

01:11:00Okay.

01:11:01Okay.

01:11:02Okay.

01:11:03Okay.

01:11:04Okay.

01:11:05Okay.

01:11:06Okay.

01:11:07Okay.

01:11:08Okay.

01:11:09Okay.

01:11:10Okay.

01:11:11Okay.

01:11:12Okay.

01:11:13Okay.

01:11:14Okay.

01:11:15Okay.

01:11:16Okay.

01:11:17Okay.

01:11:18Okay.

01:11:19Okay.

01:11:20Okay.

01:11:21Okay.

01:11:22Okay.

01:11:23Okay.

01:11:24Okay.

01:11:25Okay.

01:11:26Okay.

01:11:27Okay.

01:11:28Okay.

01:11:29Okay.

01:11:30Okay.

01:11:31Okay.

01:11:32Okay.

01:11:33Okay.

01:11:34Okay.

01:11:35Okay.

01:11:36Okay.

01:11:37Okay.

01:11:38Okay.

01:11:39Okay.

01:11:40Okay.

01:11:41Okay.

01:11:42Okay.

01:11:43Okay.

01:11:44Okay.

01:11:45Okay.

01:11:46Okay.

01:11:47Okay.

01:11:48Okay.

01:11:49Okay.

01:11:50Okay.

01:11:51Okay.

01:11:52Okay.

01:11:53Okay.

01:11:54Okay.

01:11:55Okay.

01:11:56Okay.

01:11:57Okay.

01:11:58Okay.

01:11:59Okay.

01:12:00Okay.

01:12:01Okay.

01:12:02Okay.

01:12:03Okay.

01:12:04Okay.

01:12:05Okay.

01:12:06Okay.

01:12:07Okay.

01:12:08Okay.

01:12:09Okay.

01:12:10Okay.

01:12:11Okay.

01:12:12Okay.

01:12:13Okay.

01:12:14Okay.

01:12:15Okay.

01:12:16Okay.

01:12:17Okay.

01:12:18Okay.

01:12:19Okay.

01:12:20Okay.

01:12:21Okay.

01:12:22Okay.

01:12:23Okay.

01:12:24Okay.

01:12:25Okay.

01:12:26Okay.

01:12:27Okay.

01:12:28Okay.

01:12:29Okay.

01:12:30Okay.

01:12:31Okay.

01:12:32Okay.

01:12:33Okay.

01:12:34Okay.

01:12:35Okay.

01:12:36Okay.

01:12:37Okay.

01:12:38Okay.

01:12:39Okay.

01:12:40Okay.

01:12:41Okay.

01:12:42Okay.

01:12:43Okay.

01:12:44Okay.

01:12:45Okay.

01:12:46Okay.

01:12:47Okay.

01:12:48Okay.

01:12:49Okay.

01:12:50Okay.

01:12:51Okay.

01:12:52Okay.

01:13:23you

01:13:53you

01:14:23you

01:14:34okay

01:14:43yes so i really appreciate university professors i mean the

01:14:50busy busy because my professors typically they teach some classes right

01:14:55and also on top of that if they have their own research group they do

01:15:00research and then uh after the research project is done and then they write

01:15:06down the research paper and publish it

01:15:12that's a lot of work okay so

01:15:16me uh yeah i do mathematics and i do yeah right here right but the way i do

01:15:26mathematics kind of fun okay well back in the days i used to drink alcohol when

01:15:31i do mathematics right here okay like uh even earlier this year okay some earlier

01:15:38episode of humanology series

01:15:42earlier this year that was may right yeah right here when i was doing

01:15:47mathematics with whiteboard and pen i was doing like vodka right i don't do

01:15:53that anymore okay i do mathematics without alcohol okay but i used to okay

01:16:00but still i do mathematics here human series in the using whiteboard in front

01:16:06of the laptop camera solo zoom show software upload to daily motion right i

01:16:13mean there's nobody here but still i'm interacting with the future audience

01:16:18like you thank you for being here okay so and um so still somewhat interactive

01:16:24although there's i'm alone in this room okay yeah imagine the audience

01:16:30basically okay future audience and uh whiteboard and then uh after i

01:16:39accumulated enough results then it becomes publication volume yeah then i

01:16:47write them down in microsoft word and then publish it in like either fixer.org

01:16:53or ssrm.com okay online for free okay yeah

01:17:00so teaching yeah i teach as i learn real time i share with you with the world

01:17:09as i discover something in the whiteboard okay i i sometimes think about

01:17:16it in my bed or doing cigarette break but as i as soon as i discover those

01:17:22things i share with you you know right here okay humanizers right yeah but after

01:17:29accumulation of enough material if it becomes a publication volume and after

01:17:36the particular project is done then i write it down and then publish it online

01:17:44microsoft word convert it to pdf okay yeah yeah cheers

01:17:54last one i published yeah the the fractional algebra sure yeah uh let's

01:18:02take um what

01:18:08it's three minutes break and let's check it out together yeah fractional algebra

01:18:13sure three minutes brother thank you okay my lunches have already

01:18:38you

01:18:41you

01:18:59you

01:19:07you

01:19:37you

01:19:56you

01:20:08you

01:20:18so think about it like in a way i'm kind of like uh living my life kind of like

01:20:26professor where i do research i do the teaching studying sure sure well you're

01:20:34okay yeah there's no time pressure and there's no uh need for like grant

01:20:46because mathematics look it does not cost any money whiteboard pen uh yeah i mean

01:20:56whiteboard is like about 30 to 50 dollars per whiteboard but they're reusable pens

01:21:03they do run out but uh very slowly okay and internet yeah great research tool

01:21:12yeah i pay the internet bill that's about it okay i don't need research funding

01:21:19okay and there's no time pressure i still study mathematics and also teach at the

01:21:28same time in very relaxed informal fashion and uh it's working very well right yeah

01:21:40yeah good part there's no money involved so there's no time pressure yeah two

01:21:46things okay uh money not involved it has to do with time pressure because if i get

01:21:53i mean research grant setting you have to some due date

01:21:59there's some pressure time pressure there okay but i don't have that

01:22:03okay but driven by uh intellectual curiosity and also entertainment intellectual

01:22:12entertainment yeah it's fun that's why i do it mathematics okay so in the way i'm

01:22:22very blessed yeah how many people do mathematics just because for the love of it love of it

01:22:30okay i do some people do too yeah

01:22:40yeah i am very blessed okay yeah i did not come to alaska in order to study mathematics

01:22:48it just happened that way okay uh i came to alaska for this great nature freedom

01:22:56freedom plenty of spaces okay so

01:23:03okay

01:23:07yeah

01:23:11nice

01:23:12nice

01:23:16okay my lunch is ready so i will see you tonight okay yeah thank you fantastic yeah

01:23:27yeah see you tonight martial arts education career development exercise continuing education

01:23:33career development and uh yeah be the leaders okay yeah my future leaders yeah thank you

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