Below is an excerpt of a conversation that spans 20 pages in writing and 50 minutes in audio. The audio version (which I encourage people to check out) has been embedded in the QR code. Readers can scan it using their camera app.
AYO
Hello Everyone, My name is Ayotomiwa Osunleti. A proud Hunter College student. And today, I have the honor to sit with and to have a discussion with professor Ofer (you're going to correct me on this; I’m going to mispronounce it now; Tcher-noviski?)
Professor Ofer
Cherni-kov-ski.
AYO
I had the fortunate circumstance of being a student of yours a semester ago, and since then I have thought of you as cool, and I've always hoped for an opportunity to speak with you, and so, here we are. And I hope that we have a great discussion.
Professor, seeing you speaking in front of the classroom… and... seeing you move around the stage and engage with the student as you lectured imbued a sense of passion, compassion, and also, you displayed a great show of competence in what you were doing. On this note, I would like to ask, where did your journey start?
Professor Ofer
I guess everything connects to other things early in life. But I did my undergrad in biology, and then I went to study Veterinary medicine, And then, at the same time, decided to become a zoologist, so I did a PHD in zoology. And when I finished both the medical and zoology degree, I was offered a position of a postdoc at Rockefeller university. Which is a few minutes away from here; I spent several years there, I actually got my first professorship there. And then I got an offer from City College to join the faculty and then I did that, that was in 2001. The first time I went to school was 9/11. And I stayed in city college until 2011. And in 2011 I joined Hunter, which was 11 years ago.
AYO
Great. And where are you from?
Professor Ofer
So originally I grew up in Israel, in a small village close to Tel Aviv. And thats’s where I grew up
AYO
Good to know. And the other question I ask is…Well you said you have been a professor for at least 20 years; … Have there been an area in your career you consistently find very pleasurable, and that you find meaning from?
Professor Ofer
Everyday, everyday I come in and do my science and teaching, and I like it
AYO
What would you say is the ultimate aim of a professor?
There isn’t any... You just live your life and do stuff. Being a scientist means that you are a sort of a freelancer. Yo decide what you want to study. Nobody tells you want to study. University hires us to do both research and teaching. I'm assigned to teach courses everys semester and I always teach animal behavior, also for graduate students. For the research everybody decides what they do. From that point of view, your aim is wherever you want to go with your research.
Do you have any Northstar, Is there a particular goal, is there a saying you say to yourself that describes what you are trying to accomplish everyday?
Professor Ofer
Well.. there isn;t any. There are always a few projects I'm interested in. You know science takes a long time. Every paper takes a few years. You publish several papers a year sometimes. But everything takes a very long time. So everything I publish today is an outcome of work I did for three, four or five years. So, it's not that I have to come and say what I will do today, I already have some projects I am committed to. Everyday is another step in trying to understand the problem I am trying to understand.
AYO
You are doing that whilst also teaching
Professor Ofer
The teaching is a relatively small part because, you know. I'm fairly workaholic.
So I work all the time, but I only teach a few hours a week, and I'm very used to doing that. So it comes very natural to me. I don't need to work hard preparing myself anymore.
You can wake me up in the middle of the night and say lecture number seven. And I know what it is. So, it's really the research that takes most of the effort. So therefore research is very hard because by design, you're trying to solve a problem that nobody managed to solve. So, and you never manage to solve it either, but you sometimes manage to make some progress, and not always in the direction that you want.
So research is always very challenging. Yeah,
AYO
On the topic of research. I noticed when I went to your website, I noticed a lot of your research is in regards to songbirds. And I would like to ask a couple of questions on that. One is ; How did you become so fond of them?
Professor Ofer
I like all animals and I didn't have any intention to work on birds at all. In fact, when I did my PhD, I worked on mammals, but then when I came to Rockefeller, you know, the big lab that I joined was a bird song lab. And so, you know, there were just many birds, so I just started looking at them; but I didn't have any interest in sounds or birds in particular; I just was interested in animal behavior, So whatever there is, I study. But once I started working on birds, I found that it's a very cool topic because singing behavior is easy to record…
At that time I figured out that the techniques that they were using at Rockefeller were actually too old and needed to be rethought. And I was pretty good already doing programming, computer programming and data analyses. So at that point, I figured I would spend a little time creating modern approaches and techniques to look at Birdsong and then I'll do other things, but it's so happened that it took forever to do that.
And then when I develop all those methods and start sharing them with other labs; and then everyone starts using my analysis methods. It became a big project… I shared the software to analyze bird songs and their song analysis. I spent a lot of time developing it and letting other people use it; It became a huge project.
Like for the first time you could look at the entire development of the song and record all of it, understanding all the aspects of their learning, in different projects; when do they learn? How sleep affects their learning, how they learn to connect things together, how do they come up with combinatorial abilities?
Then we moved to understanding the song as a culture, you know, how the birds come up with common, local dialects?-- Again,those became very central to us. And as I was doing that, I also became interested in human behavior , trying to understand cultural exchanges and social behavior, and trying to understand cooperation.
And particularly, you know, online; I was interested in what happened in online cultures and how culture and governance are interacting with each other. So these days, my main focus is understanding governance and culture, and online and feedback systems. These kinds of things evolve, as we do things, it's evolving in different directions.
AYO 10:47- Professor Ofer 11:05
At this point in our conversation, I asked the professor how he became skilled enough with software to develop new techniques for recording and explaining his data from his study of songbirds. His response spanned 9 minutes and three pages. For the sake of adhering to the length constrict of the publication, I will exclude this part of our conversation, and will be doing the same for future parts of our conversation moving forward. All these said; these parts below I decide to leave since I deduced they were of great significance
Professor Ofer (An Excerpt from 11:05--20:19)
And I remember I was trying to download it (an application software builder) as a free trial, but, but it was too big. So I couldn't download it.And so I remember that I tried to do it at night when the phone lines were less busy and in the evening I would start to download and then I would wake up in the morning and I noticed that it failed, but I have this kind of feature; that I'm very stubborn.
So, every night before I went to sleep, I clicked the download. And then I don’t know how long, maybe a week or two, but one morning I woke up and it downloaded. And that's what allows me to actually do everything. So, so many times it's those kind of silly things, you know, perseverance, I would say intelligence is overrated.
Anyway, you can always find people that are intelligent and more intelligent and even somebody more intelligent, so they could do things a bit faster. So intelligence really doesn't mean that much. I mean, of course you need a person to be reasonably intelligent. But you don't need to be amazingly intelligent to do good science.That's at least my feeling.
But what you do need is a lot of perseverance and this kind of ability of not giving up…
And so, I would say that perseverance is the most important feature to really do good science and of course also luck, and the ability to recognize whether there is something there and change direction as needed. But not go too much in one direction. and listen to nature. Nature many times talks back; when nature refuses in a certain direction, there are many times a reason you have to go a slightly different way.
The answers are not given to you where you want them. That would be my general theme where all of this is.
The next part of
Insights from all his projects with songbirds. He says the most important
AYO20:33
Alright. Thank you for the answer. There's about two on fire from there. One, one particular. I like to, well, before I go to this idea on online governance and your work with online communities and governance and things of this nature of as a first, like to ask you a question on any insights you gain from, I mean, I think you've mentioned them this idea of perseverance, but any insights you related to your results with.
With your project on songbirds, any like insights that can be transferred into all the insight that you're conscious that you persistently think about, you know, even after years they've came from studying the song birds.
Professor Ofer21:20
Well, I mean it's kind of like see to me the most important insight is not so much a particular result. Because many times you get results and you publish them and sometimes you get it right. Sometimes you get it wrong, but over the year, you know, you accumulate findings and discoveries and every time you make a discoveries, it's exciting and it's always adding something and you never know.
You or the community, but beyond the particular discoveries, I would say that it's always the ability to, and I think I said it in some sense before that the ability to somehow see something that nobody could have seen before and being the first to be able to see. So for example, when you think about the development of.
The song and birds. I mean, what are the development of speech in babies? It's a very elaborate process that takes, you know, weeks and months. And, and it took me a long time in the birds to be able to develop the techniques and the ideas that will allow me to actually see what happened. And so, so it required, you know, things like continuous recording over, over several weeks without stoping.
So that means that you need, you cannot just release everything because you need to figure out when the bird is singing and she has to be automated because our millions, or you will die before you manage to do it by hand. So, so you need to automate all of that. And then, then you need to. If you go out to look at the data to process the data, but once this is all done, I still remember the first bird when I could say, okay, now I can look at the entire process of song development and, and I program, you know, like little movies that shows you what happens in terms of the features of the sounds.
And you can see, you know, it stopped him from the cloud of songs. So all the sounds form a cloud. And then suddenly they turn like little clusters, almost like, like. So repairing there. And then, then, then you can see those stars moving and then you can see how they connect to each other when the bird is connecting and you can actually see that you can see visually.
And, and I still remember the first time I've seen that, you know, and I was like, wow, this is so amazing. You know? And so, and it's always reminds me of, you know, things that also happen to other scientists. The most famous example is Galileo LA. He, he was very interested in understanding planets, but of course he couldn't.
So he spent many, many years perfecting the lenses and building very, very good telescope. And then I dunno, how many years did he spend on it? But one day he was capable of having really good telescope and looking at this guys and looking at Jupiter's and see moons or on Jupiters. And he was the first person to see that.
So many times it's this kind of like moment that you see something amazing for the first time that nobody I think, but he's got a little looking at the sky and said, oh, wow, look at this. Were on , it's another planet. It's such a huge thing, you know? And, and so I've been, even, you have like smaller things still feels the same, you know, when you have this moment where you're seeing something that.
You know, cylinder thing before people could not before. So you develop an instrument that allow yourself to see like telescope or microscope and every time people did that, it was amazing, right? The first microscope, but with data analysis behavior, it's also like this, you know, you're developing analytical instruments that allow you to see things.
So to me, it's the most important thing, more than the discoveries that follow to see, would you say.
AYO25:17
The behavior, the speech learning behavior of babies, would you say they are similar? Would you say they are similar to the, the learning, the learning behavior of some birds in terms of like speaking? Yeah.
I
Professor Ofer25:36
think that there was a lot of similarities and you're all get capable in babies to do what we can do. I've seen the process continuously, but I hope we will be able to definitely
AYO25:50
thank you for your responses. And I would like to switch to your current research, which is called as far, I went on your website.
It's called experimenting with online governance. Yeah. Well, the first question, and I think you've answered it before is, you know, why a sudden change from a lot of research on some birds and animals to now humans and online mediums
Professor Ofer26:25, there's actually a continuum between those? Right? Because I, again, the interest that I had early on was to understand how one bird learned the song, but then tried to understand how a group of songbirds establish a song culture. So the, the question of culture of course, is common right between our species, but might interesting looking into governance goes a long way into the past. When the, I guess I was always very uncomfortable with the way our society is. I remember as the key variable. And later on, I was worried.
I was wondering what, why w why schools are like that? I mean, Y you're supposed to learn and you're supposed to do what you're told, but you cannot change the school. The school is like a rock is what it is, and it's imposing itself on you, but you cannot change it. If things are annoying, you, you know, you cannot change that.
And so, so this issue of the lack of good feedback and being in, you know, all the imperfections of our society were always annoying for me. And, and, and I was always uncomfortable with the idea of representative democracy, because I never felt represented even if I voted for somebody. And at some point I just didn't vote because I didn't feel any.
Can really represent me in a way that I believe that I'm being represented. It's always seems as those people that are supposed to represent only think about themselves and they pretend to represent me, but it all. And why should anyone represent me? Why can't I have my own voice? And in the early days of the internet, that was all like many other people I was thinking, why don't we use that to kind of like reduce the representation.
Well direct democracy and this dream didn't work. I mean, the internet turned into a nightmare in many ways. And never the less, I mean, you know, the idea that, that we can do, it came to me also from the conviction that the other species can do that and all that these can do it as can do it. There's no leadership in hands.
There's no leadership in bees. They, nobody tells anyone what to do and you have to have perfect harmony. And the communication is completely distributed and not hierarchical. So this idea of hierarchy in society. So there was the fact that we came from apes and monkeys that are very, you know, nasty to each other, as opposed to other creatures that have different mechanisms and sometimes better mechanism creating societies.
So, so does this kind of deep conviction that just around the corner? There's a better way of governing a better society that we could be, we could build. And in fact, if you could do that, we will evolve into it into a different spacious. And so I was always excited about this idea and I was wondering, what can I contribute to move this like one step further?
And my first opportunity to do something about it was actually 21 years. 2001 was a no, sorry. It was 2000 and was less, was 2007, 2008. So that was like 15 years ago. But at that time there was some, I was at city college and we had a lot of problems and, and because of some. And then that happened, the administration was more open for us to make some changes.
And, and I was nominated to be a tool to kind of like have a leadership in in solving everyday issues that we had that a lot of issues that the lab had, you know, we couldn't get anything done. It was management. Declared his physical plant services, whether it was power Fenty or lamp or waterflood, or he couldn't get it fixed and everything was going, oh, the system is bad.
So since I got this opportunity, I, I, I, and again, I just said, you know, the, all right, what I wanted is to that was before the cell phone, but the idea was why don't people be able to click every time they see something wrong just to click on their phone that was before phones, but, but at, let's go to your computer.
On something and say, that's wrong, that's wrong. And then everyone can see, you know, so everyone could see that the toilets are dirty, that everyone can see if there is a flaw in your lab. Everyone can see that. Right. So to have, so actually wrote a little web application, this as a volunteer and and since the college, at that point was in tubal lands.
I told them, look, let me do that. And let me allow people, no representation, get rid of the facilitator. We get rid of everything. Just let people directly to report problems. And then you guys can see that, you know, everyone can see it so everyone can see the problem and I can okay. Do that. So I did that and and we gave it to everyone was just practically was, I didn't want to open it to the internet.
So it was kind of like only for the building. And so we did that and and people just reported problems like these. But what I didn't tell the facilities is that a week after somebody report a facility, a problem, you got an email from our system saying, was it fixed? And then. Say yes or no, even the rating.
And then I published those ratings on top of each topic on the same pages. And of course, ratings are very low because nothing was fixed. So so I remember the Dean came to me and told me to turn it off. And I said, no, I'm not going to get off. But then, but then what happened is that actually the people from the physical plants services, th th they, they started.
Does that turn it off. It's actually good. We just go back to the problem. The problem will improve. So, so the Dean lost and then we kept it going and and at some point the Dean left and I became a deputy Dean for a little bit just to solve that problem. So for two years, I was kind of like doing that mistreated.
Mostly on this and that allowed me to develop a feedback system directly with people and get experience with that. And we actually wrote a paper about it, about how to get an that. And there were several little things that helped. For example, if you just show people just the satisfaction, like one star, two stars, five stars, then it's not really useful because, okay, it's good or it's not good.
But instead of that, what I did, I showed the trends show graph is strengths. So people could see if service is improving or it's getting worse in the last week or two or three. And that was the people in the services. They liked it because even though they were not doing good, they were doing better every week.
So, so they were kind of influenced by this system. And every time they did the loop, And the good seeds. So the graph in the websites show that the trend is positive, that, that, that, that the services are moving and people that use the service also wait a second. So, so good, but it's getting better. So let's keep sending information.
So I generated a feedback system that I thought was, was useful, and I realized that you have to think about social feedback. In a dynamic way. And so then after republish it, I, I said, okay, let me set it in other places too. And because our system was really good and they still use it, still use this system.
But nobody lets me do it. No, nobody lets me do that because everyone's else fantastic. But you know, what's, what's, what's NIMBY like, no, not in my backyard, you know, do do it somewhere else. I don't want to get exposed. So softer failing. So she didn't know you fail to do something. What do you do. So, so then we kind of like move, say, okay, you know what?
Let's actually have a game where people have simulated services and then, and then do all this feedback and governance within that game. So again, I learned how to program games. So again, you just learn a skill. So I spent, you know, several hours a day over a year learning it. And and then I start using it and that's where I am right now, because it's kind of like big games that people are playing and they collect coins, which is giving the money and then they have to write fairies from island to island.
But those fairies sometimes are slow, you know, and then they lose time, they lose money. So then they have to decide how to improve the fairies. So, so I just generated a game which has similar. We had in city college, right. That you have to get feedback on the service and then you can do governance of that.
So, so you see how things go, right? If you you've got an opportunity, you go somewhere and then you keep going that way. Wow.
AYO35:59
Well, it is a lot to break down from there that, and w I think the first question I would like to ask is based on what you just said is, were you able to, were you able to make some progress, which your, with this, like, We have administration administration, you know, just direct we've got, I'm working in a facility and there's a problem.
I just direct, I just go to my
Professor Ofer36:23
computer. So I'll give you one example. Yes. So for example, you always kind of like start doing it and then you can see where the problems are. You never know where the problems are, but when you start doing it, suddenly you say, wait a second. So the first thing that we noticed when we were actually running the game and getting people just to report, you know, if they had a good farrier or.
All of the fairies are good. Some and I programmed them. So I know I make some of them slow. Some of them delayed and people have no reason to, to, to, to, to lie. I mean, they are playing a game. And so in the world, it's much more complex, but people are lying and cheating, but here it's long. So, so I said, well, in these guys, you know, that the ratings that people give should be fairly accurate.
Right. But it's not, it's not accurate. And then I was wondering, why is it so bad? And then I noticed that it's not, that people are not accurate people, not accurate, but everyone has their own, their way of writing. Some people are generous. Wow. So they give a lot of five star, four star and some other people that are grumpy.
So they usually give two star three, but everyone is not curating their own way. But when you put them together, But accurate. So I was wondering, you know, what can we do to make it better? And, and remember that in the class I taught you about costly signaling and about the amounts that having the idea that communication have had to add a cost because the cost is really allowing you to distinguish between those watering, the tools, but also the cost put an effort, which also makes it more reliable.
So I decided to apartment, we use. Signaling for feedback. So so we did, instead of people giving one star or five stars, what I was doing, I built a virtual slider that had the friction. So when people wanted to report, they start in the center like 50. And then if you want to go to go up 200 or go down to zero, but as they move the slider, it resists so that they have to remove it, then it doesn't move fast.
And the more you approach the edges, the slower it moves. So, so. You have to kind of like, wait a little bit and just doing this, we got much better results. So suddenly just replacing the stars with a slider only three seconds. It only takes me seconds to move it. And that's enough. You already can learn much faster.
So, so we can get the three times faster learning in a group like that, that just doing this. So
AYO38:54
by using the slider, you're allowing people to put some more efforts
Professor Ofer38:58
into, they want to, if they want to. So they can just go this way and enough, or go all the little
AYO39:03
more. Right. So, you know, you know, you know, they mean, they mean those edges when they do go.
Yeah.
Professor Ofer39:09
Actually maybe because the push for another second or two, and so that's called bright people now, the grumpy people and eh, you know, less grumpy and the people that are more generous or less generous because you could say, oh, I'll give you five star, but 50 to wait, three seconds, maybe four star. So, so it's kind of interesting that very, very small, low level.
I can change what happened in the group level. The individual doesn't feel it, that much move a little bit this way, but when you combine the data together and you're thinking about the wisdom of the crowd, yes. Then you can actually have stronger effect by little manipulations and individual level.
AYO39:49
Do you know what you, what are you trying to understand by this research?
But you're using gov by understanding governance in all our communities. Is there a particular like you, are you trying to understand something or you just ages like paying attention to what is going on as a result of the things you are changing in the research? Or are you just trying to get to a point.
Professor Ofer40:12
Well, there's always the next target, but the next target is always a local target and it's a many times less to do with what you encountered. For example, if you tried to be the system with feedback where people report, and it's not reliable, the neighbor problem, you have to understand why it's not reliable.
How do I make it reliable? And then you say, let's use a theory of costly signaling to see if I can make it more reliable. Then on the higher level, then you have all those issues of what happened. We'll have to make collective decisions and our different rules. What happened when you combine those rules?
Can you actually learn each rule alone? How it affect people and then understand what happened when you combine them or not, maybe we'll combine them, you get something different. So, so all those kinds of questions are kind of practical, but also a theoretical important, because you want to know what level you can.
Knowing in advance. What happened when you add more things to governance or maybe you just have to experiment and then how to explain it. But in general, the goal of the third, my goal in general is to allow people to get rid of representatives as much as possible. I don't think that we cannot continue.
We've got to completely get rid of representation, but well, maybe in the future, but, but right now you cannot immediately get rid of. It's there. And, you know, we don't know about, but if you want eventually to have less of it, or maybe none of it, and maybe thinking about the city without the mayor results, anyone running gates, you know, is it going to work?
Probably not. Right. But then if you have people do it in a distributed way, maybe you can get it to work to some extent. So my, the feeling is that ideally what I want is a city without the manual. I did we get to that, but you cannot get to that thing once that you'll just start by having more and more distributed systems learning small scale, how to have this, because what is distributed governance is this system means that it's like bees bees, right?
Every bit does it things, but the communicate and some of the communication ends up to something good. So it's not, nobody's making a decision. The decision is happening collectively, and we know that other creatures. But do we want to do that? Do you think humans want to, well, what people want to do is their problem, but what I can do is telling you that something that you thought you couldn't do, you can, then you put aside if you want that.
So you can have a, so we can have like societies that will go for a representative. Awesome. That would go for dictatorships and some that will go for distributed systems and then let's see who does better, you know? But, but that's an option, everything. I mean, what do you mean the option? I mean, we cannot, you, you could not presenting an option.
Look, all you can do is develop technologies that make things possible once it's possible, then people may use it. Not exactly the way you saw. All the way you saw. But I want to make certain things possible right now. Distributed governance is not possible. It's possible, very rarely, but I believe that, but there are many people that are trying to look at.
There is a Nobel prize winner in a, in a political scientist, Eleanor, a. Eleanor Alstrom, Elinor Ostrom who won the Nobel prize for governing the commons. So for developing techniques, for people to do distributed governance. And that was a while ago. I mean, she died in 20 11, 20 12 or something like that.
So she already died like more than 10 years ago. And she got the Nobel prize, I think in 2009 or something that was before the big days of the internet. But. You already thought about it. Didn't got a lot of recognition to that. So she took it some level and people are trying to use our metal to some extent, but I don't think that it took off yet.
You know, like the idea of distributed this also all the people that do cryptocurrency, they also try to do this the governance, but I don't know to what level they are going in a good direction or not, but they're trying. And of course there are many distributed governance happening in many organizations.
We compete. It's a very good example of distributed governance and the thing about Wikipedia. So huge project, and they keep things working in a distributed way. So, so there are all these success stories, but I think that something is missing to get us take it to the next level. So to me, well, to me, the next level, to be able to actually run societies like that, what a village like that, then if you can own a village like that, can you run a little town?
Like. Can you run a city like that? Can you run a country like that? Those are big steps, but but I think that, that the science is not there. That's the problem that we need to move the science in that direction. I was surprised by how little attention it gets in the scientific community. So what, when I'm doing those things right now, I feel that there is a very, very small community that is interested.
I think that everyone should to do with it. Cause that's, to me like the most important problem, how do you. You know, society that is more open and more distributed, but it's not a big branch at all in science. It's a very small company, so I joined it.
So
that's fine.
AYO46:11
So the invention. It's a written method for improved accuracy of customer evaluations and cost savings
Professor Ofer46:21
society or the rating,
AYO46:24
the rating system. Is this something else? Or I, we talked about it before. Well,
Professor Ofer46:29
I'm not sure which one you're talking about. The costly signaling, the rating system. No
AYO46:34
customer evaluations.
And cost-savings your
Professor Ofer46:37
invention. Oh yeah, yeah, yeah. That's a little patent application. Yeah. So that's all it to do with and the costly signaling. Yeah.
AYO46:50
And you do come up with this with the invention.
Professor Ofer46:54
Well, the invention just happened.
AYO46:57
It's affluent as a result of
Professor Ofer47:00
dealing with the problems getting bad quality ratings.
AYO47:04
Right. So, because she's not right now, you're in, you're in business territory.
Professor Ofer47:08
Wow. That's really, I mean we just decided to, to ever play. So that people don't just steal it. Maybe there, there's kind of like some efforts to try to convince some organization to use it. So, so it has a business aspect to that, but I, myself, not that.
At all, but since I'm at coin vent or find it online, it's not something I'm really spending time.
AYO47:42
So this, your, this research with governance and online communities, we, it's a, it's a big, it's a small step into your bigger goal or a goal. You think everybody should think about which. Self-governing and I've in less representative democracy.
Yeah.
Professor Ofer48:02
I think governance something happened by the way.
AYO48:14
Two to three minutes. So stuck with him.
Professor Ofer48:19
Yeah. I mean, again, as I said, I mean, the idea of open governance is not new and many people are doing it, but the idea of having more distributed, less representative is something that there's not enough research about feel that there has to be more
AYO48:37
possibility.
Professor Ofer48:38
Yeah. Topics like that.
AYO48:42
And. It'd be the end of our conversation.
Anything you would like to tell the listener, your codes, or, I mean, I think you've mentioned in lots from the beginning of our conversation about persistence and just the ability to notice, you know, to not give up in everything one does. And is there anything you would, I like to add to that?
Thank you for speaking with me today. Thank you for taking the time to, you know, to have this discussion with me. It's been a pleasure. Thank you.