As a lot of you know, I spent four years before coming here working as the executive director of the Unitarian Universalist Partner Church Council. During those years, in the year before, in which I served as a part-time church governance consultant, I did not have a regular pulpit. I was invited every now and then to preach at congregations that had international partnerships, but of course I was pretty limited in what I could talk about. I'd talk about international partnerships. I didn't anticipate missing doing regular sermons, it is kind of a grind, and honestly at first I did not miss the regular preaching. But then I started to, and that's part of why I made a decision to leave the Partner Church Council and become an interim minister for this last chapter of my ministry. Fortunately, given how this year is panned out, it is not the live audience that I missed most about preaching, though that is something I did miss and of course have missed this year. What I missed most actually was the chance to explore topics that feel important and to figure out where I stand on them. As I shared with you previously, Donald Trump descended that golden escalator at the Trump Tower in New York and announced his candidacy for the presidency two days after my last sermon in Appleton.  That campaign and his time in office gave me lots to think and wonder about, but I had no opportunity to process what I was thinking and wondering about in sermons. The other big development during my time without a pulpit was the taking flight of the Black Lives Matter movement and the related struggle in our Unitarian Universalist Association with the ongoing legacy of white supremacy culture. These two things gave me a lot to wonder about during my hiatus from the pulpit and one of the things I wondered about was my previous embrace of a sense of American exceptionalism. I preached that American exceptionalism gospel many times in Appleton. Now my embrace of American exceptionalism was nuanced. I understood that genocide, persecution, and enslavement of blacks and indigenous people were deep consequential flaws in the experiment that is the United States of America. I would acknowledge these flaws in people like Thomas Jefferson, but then lift up the better angels of their nature and how they embodied those better angels in much of the founding documents and philosophy of this country. The problem, I believed, was some bad apples among the founders and early leaders of our country and some folks like Jefferson who had deep flaws. Bottom line though is I believed in the premise that the United States is the most exceptional country in the history of the world. I believed that if you take away these flaws our democracy offers the most enlightened progressive blueprint for a nation. To use language that goes back to the Puritan settlers I embraced the notion of the United States as the bright city on the hill despite the flaws. Well these past five years have deeply challenged my embrace of American exceptionalism and I've wanted to wade into these tricky waters and July 4th being a Sunday this year just was too good of an opportunity to pass up. So the last week's sermon was framed as a farewell I just couldn't resist doing the sermon this morning. So this morning I joined in the tradition of Frederick Douglass and Ralph Waldo Emerson and others in doing a critique of our nation. I believe that critiquing our nation is patriotic. Through the lens of what I've learned these past several years I now believe that we really can't parse out flaws like genocide and slavery and Jim Crow segregation. They are part and parcel what our nation has been and done in the world and I've come to question the idea of American exceptionalism that I embraced for so many years. There are three big problems with American exceptionalism. The first is that this idea of American exceptionalism has fueled some awful actions. As you know because I've mentioned it a lot this year I keep coming back and thinking about American imperialism in the Pacific in the late 1800s and early 1900s. An enterprise embraced by liberals including Unitarians and Universalists. Many of our UU ancestors were motivated by a desire to share what they thought was the best and the brightest mode of governance with which had ever been seen on the face of the earth with countries that had more primitive models of governance. They saw our democracy as the best great hope of the world. Who wouldn't want to have it? They seemed to think. If others didn't seem to want to have it then that's just because they were kind of ignorant and we need to teach them. This led our liberal ancestors, many of them, toward a slippery slope of imposing our American system on others including if necessary by force. And this helped fuel our conquest and annexation of Hawaii, the Philippines and other places in the Pacific. Our face collective embrace of American exceptionalism is why Unitarians and Universalists had an outsized role in that imperialist endeavor. My colleague Reverend Fred Muir found a reproduction of a painting from the Philippines exhibit in the 1904 World's Fair in St. Louis. A painting that perfectly captures this sentiment that animated Unitarian and Universalist imperialists. Before showing it let me share some background on the 1904 World's Fair. It took place six years after the U.S. seized control of the Philippines though President Roosevelt declared the war over and won, mission accomplished in 1902, insurgents still battled U.S. forces in the Philippines as the World's Fair got underway in 1904. The Philippines exhibit was the most popular attraction in the fair. It was estimated that 99 out of 100 people who went to the fair went to that exhibit. The exhibit was called and this is interesting the Philippines Reservation. A thousand Filipinos, many clad and loincloths were part of the exhibit. They were among 10,000 natives imported from developing nations to be part of what the scholar Walter Jensen calls the largest human zoo in world history. Now this painting from the Philippines exhibit captures the liberal idealism that animated the 1904 World's Fair and American imperialism in the Pacific. It's a little hard to see this painting. Here's what's happening.  The American figure is bountiously sharing the riches of our American system. An angel watches approvingly from above signaling that the source of these gifts for the Philippines is divine. This painting depicts how Unitarian and Universalist imperialists framed their work.  The second problem with American exceptionalism or that these last years have exposed is that it's not true. I embrace the belief that our constitution is so strong and perfect as amended that it can survive any and all attacks from within our country. I could not imagine an authoritarian ruler taking control of our nation. I could not fathom large-scale attempts to throw out election results. I believed that our courts and our constitution and the underlying goodwill and commitment to democratic ideals of all people would prevent our nation from falling under the spell of an authoritarian ruler. I know better now. I see how naive I was. And this leads me to the third problem with American exceptionalism. If we believe that our government is impervious to being taken over by an authoritarian, we make takeover by an authoritarian ruler more likely. I was slow to recognize and work against the threat to our democracy because I thought our democracy was stronger than it turns out it is. And I believe that American democracy survived these last years by a very thin margin. Our democracy continues to be sick, a wash and dark money, voter suppression, and deeper efforts to undermine elections. Indeed, I believe that our democracy is in more danger today than it was last November or even on January 6th. One of our two political parties is working very hard to suppress votes, particularly votes that come from black, indigenous, and other people of color. One of our two political parties is working hard to make it easier for state legislatures and Congress to overturn legitimate election results that it doesn't like. In the face of this, thinking that our democracy somehow is impervious to authoritarian assault is dangerous. Our country, like all countries, is susceptible to authoritarian takeover. American exceptionalism is a dangerous view. Now I continue to believe that there is some promise in our nation's heritage and system, as well as deep flaws that reflect the truth that we as Americans are flawed human beings. I believe that the United States, like other countries, is not divinely sanctioned but is and always has been embodied through flawed human beings. The extent to which the United States brings to life the good is in the hands of the American people, we the people. It's always been up to us. Will we be a country where freedom and opportunity exist for all, or will we be a country characterized by bigotry and oppression? Which America are we going to be? We have always had that choice facing us. One of our country's greatest poets, Langston Hughes, wrote a poem called Let America Be America Again in 1955. His visionary, raw, compelling words continue to speak truth. These words are given life anew in this rendition by Abinah Coombson-Davis, the musical director of the Resistance Revival Chorus. And so I will give Langston Hughes and Abinah Coombson-Davis the last word today. America be America again. Let it be the dream it used to be. Let it be the pioneer on the plane seeking a home where he himself is free. America never was America to me. Let America be the dream the dreamers dreamed. Let it be that great strong land of love where never kings connive nor tyrant scheme that any man be crushed by one above. It never was America to me.  Equality is in the air we breathe. There's never been equality for me nor freedom in this homeland of the free. Say who are you who mumbles in the dark and who are you that draws your veil across the stars. I am the poor white, fooled and pushed apart. I am the negro bearing slavery scars. I am the red man driven from the land.  I am the young man full of strength and hope tangled in that ancient endless chain of profit power gain of grab the land of grab the gold of grab the ways of satisfying need of work the men of take the pay of owning everything for one's own greed. I am the farmer bondsman to the soil. I am the worker sold to the machine. I am the negro serving to you all. I am the people humble hungry mean hungry yet today despite the dream beaten yet today oh pioneers I'm the man who never got ahead the poorest worker barter through the years yet I'm the one who dreamt our basic dream in the old world while still a surf of kings that dreamt a dream so strong so brave so true that even now it's mighty daring sings in every furrow turn in every brick and stone that's made America the land it has become for I'm the one who sailed those early seas in search of what I meant to be my home. I'm the one who left dark Ireland shore and England's grassy lay and Poland's plain and torn from black Africa strand I came to build a homeland of the free the free who said the free not me surely not me the millions on relief today the millions shot down when we strike the millions who have nothing for our pay for all the dreams we've dreamed and all the stars we have millions who have nothing for our pay except the dream that's almost dead today oh let America be America again the dream that never has been yet and yet must be the dream where every man is free the land that's mine the poor man's Indians Negroes me who made America who's sweat and blood whose faith and pain whose hand at the foundry whose plow in the rain must bring back our mighty dream again sure call me any ugly name you choose the steel of freedom does not stain from those who live like leeches on the people's lives we must bring back our land again America oh yes I say it plain America never was America to me and yet I swear this oath America will be out of the rack and ruin of our gangster death the rape and rotten graft of stealth and lies we the people must redeem the land the plants the mines the rivers the mountains the endless plain all all stretch of these great green states and make America again thanks in news


If you have been following the channel for a while now, you know that me having a new bike is quite a big deal And I'm not talking about a new bike just for myself. I'm talking about a bike out of the box For the new ones out there, let me tell you I'm a budget rider since the beginning One of the goals of this channel, for example, is to share tips that can save you some money along the way Therefore, I was looking for a good option for a while now until this pretty good deal came up So for the ones wondering why Bita and why this model? Well, that's why it is a good bike and it was within my budget So now is it good? Is it bad? Or is it just meh? I have no idea, but I want to figure it out One thing you can expect is a fully honest review with all its good and bad things So let's start with some highlights of the 2020 Bita 300RR counter balancer shaft oil injection map switch toolless air filter change ZF sash shock and separate function open cartridge forks E starter without kick starter and XL rims One of the most interesting parts about being able to buy a new bike is a new video. I'm designing for you guys What can we expect from aftermarket bike protections? The goal is simple get a bunch of protection accessories on the bike Throw everything at it from hard and uro and uro cross-country tomorrow cross and Assess the condition of the bike for at least six months. The results will speak for themselves For that I partner up with two reference brands that are known for their quality protection parts Polisport and P-TECH Polisport makes polymer protections and P-TECH makes aluminum protections Polisport will contribute with almost their entire product line from hand guards top fork protection bottom fork protection and front disc guard radiator louvers and shrouds armadillo pipe guard side frame and clutch cover ignition cover swing arm protection and the all-new silencer protection However, polymer protections can have limitations and that's where aluminum protections come in Also, there are some protections that do not exist in the polymer version P-TECH will chip in with their flagship product the engine and pipe guard with linkage protection rear brake disc guard radiator guards and front disc guard Yes, there are a few products that exist in both brands, but it doesn't mean that they are just competitors Being made of a different material or design in a different way means they will provide different kind of protection And will be more suited for different uses So six months from now, I'll analyze the bike's condition, weigh the pros and cons and let the results do the talking In the meantime, you can expect standalone reviews of the products and obviously follow the evolution So make sure to subscribe to find out the ultimate answer


It's by a group called Emerson, Lake and Palmer. I think they're all dead by now. All right, so anyway, with that rather strange introduction, it's four o'clock in the afternoon, so I'm allowed to make strange introductions. So today, while the magician's assistant keeps running back and forth across the stage in front of the fake magician, I would like to finish up what I was presenting yesterday. The part of yesterday that I did show was sort of standard stochastic thermodynamics 101, so to speak. This is some newer material. There's always this weird thing when you give lectures, how much do you present your own stuff rather than trying to go after what you think is truly important, given that you think your own stuff is truly important? And so this is actually my own stuff, but I do think it's truly important, so more strange preamble. But if you remember yesterday, I pointed out, I can't speak with this thing, excuse me, I pointed out yesterday that almost all stochastic thermodynamics today has considered this scenario where you are given a fixed initial distribution and then we want to examine what happens as we change the actual physical process that works on that initial distribution over states. We can add multiple reservoirs, we can do things faster or slower, we can have periodic forcing, all kinds of complicated things you can do, where the total about varying the process were fixed distribution. However, as I tried to emphasize in very, very many situations in the real world, basically everything I would say to do with computation, either if you're building a computer or if you are giving birth to one in the sense of just stating a new biological computer, both of those systems, the process is fixed, the actual individual gates in my computer, they're fixed ahead of time. Same thing with some degree or other, depending on how much you might consider things like phenotypic plasticity. A biological organism, the process that it runs by which it actually transduces free energy in the environment into things like its own computation, that process is also fixed. What's varying greatly there instead is the initial distribution. So it's actually the exact complement of what Stochastic Thermodynamics has worked on almost exclusively. It's the complement that's of most interest. So what can we say then about the dependence of, in particular, entropy production on the initial distribution? I fix a process for the remainder of this lecture. Process is fixed, but we're varying the initial distribution and how does that affect things? So to keep life simple, let's see, is the laser doing better? Oh. Cut off, I don't know why, see how. Yep, it should be this one, acrobat. Actually concerning musical pieces, there's something called before and after science, and I was seriously thinking about playing that at the beginning of the very first lecture, the before science part of it, and then there's another, my next part on that CD, which is the after, and that could be at the end of the course. All kinds of deep symbolism, but in any case. So we've got a, we're varying the initial distribution. We've got a fixed process for simplicity. We're gonna be assuming a single reservoir, and I'm just going to choose units so that KT equals one throughout everything. Recall, I've now made you sick and tired, hopefully, of this formula. This is how the entropy flow, how it is a function of the rate matrices, which can be changing in time, and also the distribution at that moment in time. This is a very weak laser. The thing I want you to notice, this is a linear function of P. So in other words, another way of saying that is it's a linear function of the initial state that you begin with. So for any given initial state, I can calculate what the total entropy flow, the total heat due to starting in that state would be, and the actual total entropy flow under expectation is just the average over that. That's going to be very, very important. So, let's see. And so we can define that way, because of that fact, we can find the heat that would be produced under expectation if we were to start in one particular state, X of T zero. So if we got a distribution over states, it's just going to be the average of this over all X of T zero. And then when we average over all of X, T zero, what we're going to get is our formula for the entropy production is going to be just from before. It's the drop in the entropy of the total system minus the average of this. The key thing is that this is a linear function of P zero. That is not linear, but this one is. Okay, here's going to be the weird thing. In certain respects, when you take, when you look at how it behaves under differentiation, entropy, no, it's not strictly speaking a linear function, but it acts just like a linear function. So actually the directional derivative of this is going to be essentially linear, and you'll see what I mean in a second. Okay, so define this distribution Q zero. That is the initial distribution that results in the minimal EP. So you can, it's not too hard to show that any physical process there's going to be a unique initial distribution unless it's doing a permutation over states, unless it's actually implementing a dynamics which is exactly a deterministic and invertible, any other kind of a process, there's going to be a unique initial distribution such that if you start with that initial distribution, you end up with the minimal total entropy production. Okay, another way to view it is that if you design a bid eraser, you design an AND gate, you design a human being, oops, a human being, all of them you can design, if you happen to know the initial distribution of that particular system that you want to perform a computation, you can in theory design the process to be optimal for that distribution or to flip it around. If you're given the process, the AND gate, the human being, what have you ahead of time, there is going to be one initial distribution over its states, such that it's going to generate the least heat in the form of entry production, okay? So that's this creature. In general, it's also going to have full support. It's not going to be, does some particular edge case. Okay, so given that, notice we're now doing this very, very simple elementary calculus for any other initial distribution, the directional derivative from Q zero, the optimal one in the direction of R zero, if we're evaluating this at the actual, because this is the minimizer, because it turns out that yes, everything is differentiable and so on and so forth, this is going to be zero, no matter what R zero is. That's what it means for Q zero to be minimizing this, is the gradient is going to be zero there. So this is, dot product is always zero, okay? Let's see, is this showing up when people know it isn't? Okay, and the gradient that I'm taking here, this is the gradient over the space probability distributions, question. The whole thing will be zero as well, so just the way you can think of it, yes, yes and yes. Here is if we sort of had it was only in R, if there were only two components, well, see the thing of it is, we actually are restricted to be on the simplex, because probability distributions have to lie on the simplex. So in general, this gradient term right here, that's not going to actually equal zero in all components. But this dot product has to, because it's the minimizer. That dot probably, see this is on the simplex and that's on the simplex. Because we're constrained to be on the simplex, this gradient is not going to be zero in general. This is a gradient over the full space. For example, let's say that you had three possible values of your system. So in this case, the simplex is going to be in R three, it's just going to be a plane. And we are requiring that Q zero has got to be on that plane. But this gradient is over that entire space R three. So that gradient is going to in general not be zero at the point on the plane where it minimizes things. But this directional derivative has to be. You can also do this with like Lagrange multipliers kinds of stuff. But this argument will go through. So this is actually always true for minimal points on any particular kind of a hyperplane or a hyper surface through some higher dimensional space. An embedded manifold. Quick, is that, that's a little bit, I'm not going into the messy details. Yeah, it's due to the fact that you have to be on the unit simplex. That means that in general you're not going to have that gradient be zero. Okay, good question, very good question. In fact, I had to remind myself what the answer to that was several days ago. So there you go. Any other questions? Notice by the way, the implicit arrogance that I say when you ask a question that I asked that means it's a good question. Pretty good, one of the advantages of being a professor. Okay, yes, so here's the, as I was just saying because we're on a simplex, the gradient is not identically zero. Okay, now we recall that, now we're just going to be doing a little bit of algebra. Recall that we just said that the total entropy production is, which we're at the minimum of, that is given by this formula, that's linear in P. So it's very, very easy. What is the gradient of this term with respect to the components of P? It's just going to be a Q of X zero. So the X zero is indexing the actual components of P and the gradient of the expected Q under P is then just going to be that Q of X zero. Simple, here we go. Now let's look at the entropy term. This is where the entropy term is going to act sort of like it was linear. If you just go, how do I move this thing? Sorry, there's junk on my screen that you get to not see and it's kind of hiding things from me. There we go, that's better. Okay, so then when we evaluate the entropy, the gradient of the entropy, P of X, remember this is the change in entropy from P of X zero to P of X one. We're going from time zero to time one. And so when you take that gradient with respect to P at X zero, you're going to get a conditional distribution and basically the first step of your algebra is going to be this. Those terms, the second step of your algebra, you end up with that. Okay, everybody pretty much with me? Let's see, I can do it this way, I guess. Is this working? Come on. Okay, this is not working, so I gotta do it that way. That's not working either. Okay, so anyway, let's now just plug in. Sorry, this stuff is not behaving very nicely. So if we plug in, we know that R zero minus Q zero times this gradient has to equal zero. Here is the entire terms of the gradient. This is a single component of the gradient. So we just plug it in. Q zero times the gradient, is it going to equal this? It's actually itself is going to be the EP at Q zero. And R zero times the gradient, when you go through the math just a little bit, you remember the definition of relative entropy of K L divergence from Gilder's presentation a couple of days ago. This is actually just going to be the difference of the K L divergences between R and Q at time one and time zero, where both in this, to evaluate R one and Q one, you hit both Q zero and R zero with the exact same conditional distribution P of X one given X zero. So P of X one given X zero times Q zero, that gives you Q one.  Okay, so that's how these terms are defined right here. Note that this is completely general. It doesn't depend on the details of the process at all. All details of the process, they're only coming in, this value, sorry, that's a typo, that should be delta sigma of Q zero. All details of the process are coming in for delta sigma of Q zero. In other words, they are saying, what is the least amount of entropy production you could do for any initial distribution?  But aside from that, which is just an additive factor, the actual amount of entropy production for R zero is going to be just this drop in the KL divergences, so the difference between sigma of R zero and sigma of Q zero is just a drop in the KL divergences. That's the amount of extra EP due to the fact that you are not actually using the distribution that is optimal for your process. When I take this computer, right now I'm using it, let's just, and I've got some distribution over inputs to this computer by which I initialize it state, run a computation, initialize it state, run a computation, that's happening many, many times. We can assume that I'm just like an IID process. If this is not the case, but we could imagine, Apple of course wants nothing more than to build their computer specifically for David, so we can imagine that they actually built their computer such that David's distribution resulted in minimal EP for this computer. Then when Professor Marsili uses it, his initial distribution over inputs to this computer is different, and for that fact alone, there's going to be extra entry production when he uses it compared to when I use it. In particular, even if it's thermodynamically reversible for me, the best you can do based upon the second law, the exact same physical device that's thermodynamically reversible, that same physical process that is thermodynamically reversible for one initial distribution will be irreversible, will be generating a non-negative entry production for any other distribution, okay? That has massive consequences for things like designing computer circuits, consequences which nobody has yet figured out, has even started to calculate. Again, another plug if people are looking for PhD projects. Okay, so these are some references for it. Originally, this was some work that I did with a postdoc Artemis Koczynski. There's been recent work by Paul Riekers and Millet-Gew on it. Here, more recently than when we did the original paper, we extended this to quantum thermodynamics, we extended this to differential time processes, we extended it to uncountably infinite spaces and a whole bunch of other mathematical junk. So this is, we refer to this as the mismatch cost. As Maguja noticed yesterday, this has got a very, very interesting connection with information theory, because in information theory, if we have a channel and a coding system for that channel that is optimal for some distribution Q zero, but in fact, you generate signals going down that channel according to P zero, the expected code length of your words coming out the other side of the channel is now going to be the relative entropy plus the entropy that it would have been if you were actually spot on Q zero. So in other words, this term here, does any one of these, that first relative entropy is in essence, the extra expected length of code words if you are having a coding scheme, a code book that is optimal for a distribution Q zero, but you're actually running it with a distribution P zero. Remember, information theory is all about information transmission. We're not interested in that. We're interested in information transformation as computation. And so, well, it's very clean, very cute and do not yet know actually if there's any deeper significance to this, but then what happens, the exact same kind of a mismatch scenario, you instead of looking at just the D of P given the relative entropy between P and Q, now it's the drop in the relative entropy between P and Q. Okay? Did you say anything about the underlying assumptions on dynamics, for example? Okay, we are gonna talk about finite path formalism tomorrow. And we were discussing just- This holds no matter what. Exactly. That's the point. Yeah, I want you to say it. Yes, exactly. So we are gonna see finite path formalism tomorrow where we are, I mean, until this point in the course, we didn't account for the degrees of freedom of the bath, the heat baths, right? Because we assume that they're just straight forward, like infinite. But while we are driving this, we're not actually, for example, and in the finite path formalism, when we start to actually take into account these degrees of freedom of the bath, we are going to assume that this overall dynamics of this joint system and the bath, they're actually governed by some Hamiltonian. So you have deterministic dynamics, not stochastic dynamics. But even in this formalism, if you take this kind of a derivation, you can still use this kind of a result. So yeah, I just want you to say it. Yeah, okay, that's a good point. So what Gouda's actually referring to several things. There has been a smaller portion of current stochastic thermodynamics. So let's see, step back a second. I mentioned earlier that if you're going to have a Markov process over your system of interest, you need to have an infinite bath that is also got a time scale separation so that you're losing all information about the fast. That the bath is actually, its dynamics is infinitely faster than that of your system of interest so that it does not actually contain, so it's always a Boltzmann distribution. Your bath or bath's plural. And so it contains no information about the previous states of your system of interest. That's what allows you to treat the dynamics of your system of interest as though it were first order Markov process. So that is a continuous time Markov chains. And as I emphasize a couple of days ago, that's everything from ecosystems to gene regulatory networks too, for that matter, financial markets. And for that matter, this is particularly relevant today to geopolitical systems. You can model them as continuous time Markov chains. But there's another body of approaches, another body of work in stochastic thermodynamics where they say, wait a second, what if that's not true? And there are actually many reasons to actually know that that's never strictly speaking true ever in the real world. But in any case, this is an approach where you instead of saying, here's my system of interest and it is coupled to one or more infinite baths. So this is what we've been talking about so far. Infinite bath. And so we actually don't directly see Liouville's equation or anything like that in this particular formalism. I'm just saying there's a CTMC over this. Another approach, no Hamiltonian dynamics, is to say, here's a system of interest and we have one or more baths, but they're all the same kind of size. Actually, let me make this a little bit, make this somehow a little bit more graphic. I'll do better. So here, blue, infinite. It is different. White is all Hamiltonian dynamics. Blue is not. This is finite. And that's finite. So in this alternative approach, what you do is you actually look at the dynamics of this. You assume that this SOI, system of interest and these baths are isolated from the outside world. That's your assumption. This is then Hamiltonian dynamics. Liouville's equation, if you're doing this in terms of phase space and so on, or Schrodinger's equation, if you do the quantum formulation of this, you can do it either way. And so in this particular setup here, a lot of the results that we've been applying, that we've been driving so far, they have analogs in this domain. In this domain, though, the evolution of the SOI in general is not Markovian. The reason being that because this is finite, if you're in one particular state here, it's on particular time, you're going to be having an effect on the bath. The bath is then going to be having an effect back on how you go from XT to XT plus one. This is going to mean that the actual dynamics you're undergoing is going to ultimately, the way it goes is like this, the end result of this process is going to be that X of T plus one depends upon X of T minus one as well as X of T because of what's going on through the finite bath. The finite bath is carrying information about your infinite past. Therefore, the probability distribution of X of T plus one given X of T is not the same as the distribution of X of T plus one given X of T and XT minus one. XT minus one has extra information that's not XT, so it's not a first order Markov process. When you go to finite baths, okay? So that makes some things a lot harder, but here's the trick. Here's the slide that I was presenting before. I should have actually pointed this out. I was saying at this time that the actual dynamics of the system, the details don't matter, but here's the reason they don't matter. Notice that we're just looking at X zero and X one and a conditional distribution of X one given X zero where X zero is the very beginning of the process and X one is the end of the process. What goes on between X zero and X one? It's not just as independent of things like oh, the number of reservoirs you have or anything like that. There's no assumption of Markovian dynamics even anywhere. There's just some arbitrary God given conditional distribution X one given X zero because the entropy flow function is linear, because entropy itself, change in entropy, once you take its derivative is indistinguishable from a linear function, the end result is that we have this form for the mismatch cost even if the intervening dynamics is not Markovian. And so tomorrow Gilger will be presenting some work of this, but then also in terms of using this formula, applying it to these kinds of situations, I'll be presenting stuff on that next week when we're talking about basically using this to model deterministic finite automata to analyze them. Okay, so that was kind of backwards fours. Yes, question. For example, if I have like a hot cup of tea and in the sense that if you have a hot cup of tea, for example, just a hot tub cup cup of tea cup of tea. Yeah. At some point it will thermalize with environment and it will be cold. And there's no way of knowing the initial state of that cup hot cup of tea. So in that sense, we're working in an infinite bath in the sense that it's forgets that hot cup of tea itself is like an infinite bath. But the question is, if I'm now attaching something, so I've got over here a hot cup of tea and over there a cold glass of ice, let's say. So I've got a temperature difference, I can use that to run a heat engine. And at that point, what becomes important is actually, is the working of the internal parts of the heat engine slow compared to the thermal agitation time, the Maxwell's relations. Maxwell's, I guess it was Maxwell, who came up with the distribution over speeds of molecules of functional temperature for the hot tea and the cold ice. The actual system in between has to be much, much slower the way that it's on typical time scales compared to that of these two. Okay, but regarding that in terms of memory of the system. So when that's the case, so it's much more slow, that means that F, in essence, it thermalizes, that cup of tea thermalizes very, very fast. So the time you get to an X of T with that, with any probability is different from this. So we've waited long enough so that this is not going to be almost surely identical. That it's actually had time to change. Once we wait that much time, this is right back to being a hot cup of tea at its Boltzmann distribution again. And so this has no more information about what your previous state of the system is. And notice there's actually a very, very deep philosophical issue here about what probability distributions mean. Because really as a practical engineering issue, that information is still here, but in an extremely fine-grained, complicated distribution. What happens is, loosely speaking, there was an initial distribution of F that was like this. It was perturbed by interacting with XT minus one. And what happened is this actually became something that looked, you know, this is very, very sort of high level. But I think you can get the idea that it's actually, let's say this started like that, and now it's become like this. What we do in physics is essentially approximate, this is really just kind of the same thing, because we are not able to actually discern, or more importantly, we as engineers cannot exploit any of this really fine-grained filigree detail in this particular actual distribution. So for as far as our experimental apparatus is concerned, this is identical to that. It's not that they're approximately the same, it's that our fingers are too crude and rough to be able to get them into any of these holes. So essentially, we are up there as far as all of our devices are concerned. So there are these kinds of slippery, subtle things going on. Thank you. Okay. Sorry, this has been a bit of a bounce forward, bounce backward kind of a presentation, but in any case, as I said, that's called mismatch cost. And now let's look at some of its interesting implications. Let's assume for simplicity that the system actually is thermodynamically reversible. In other words, generate zero EP for the initial distribution Q zero. Then what we get when we write it down is the entropy production, the entropy flow, the heat flow out to the heat bath, it's the change in entropy plus the entropy production. In this particular case, if we're at Q zero, that other term is going to be zero, the term that's hanging on on the end. So in this particular case, the actual entropy flow is going to be the difference of the cross-entropies. It's going to be the difference of the relative entropies plus the difference in the entropy of the system. And now let's see what the implications of this will be, for example, for land hours bound. Everybody likes to say KT log two. Well, let's even assume that you've got a process, yesterday there was some discussion about semi-static processes versus more realistic ones in finite time. Let's assume you can do things semi-statically slowly. And let's assume that for a uniform initial distribution over the state of your bit, you actually generate zero EP. So you achieve land hours bound, the total heat flow, the total EF for that initial distribution is in fact KT log two. Well, now let's assume that actually somebody comes along and they start using your bit erasing system with a different distribution that's not uniform. Okay, you would actually expect that's going to almost always be the case. Well, in that case, for example, let's say this other distribution is epsilon one minus epsilon, then as epsilon goes to zero, we get a minimal heat flow. Sorry, this is now a case where we're optimized for epsilon one minus epsilon rather than one half. And so in this case though, if we instead run it with a delta function about one for epsilon going to zero, then we get the mismatch cost term is infinity. So you take a land hour bit eraser that is optimal for one initial distribution and run it with a different one. Actually, it's going to generate an arbitrary amount of heat despite the fact that it's thermodynamically reversible for that one particular state. And here's something where life gets even more funky. Let me first state what the result is and then I'll walk you through why it occurs. And this is part of why thermodynamics of circuits is actually an extremely complicated thing that people know very, very little about. Here's the result. I give you two bit erasers. Let's say this first bit eraser, let's say that's thermodynamically reversible for a distribution, I don't know, two thirds, one third. Okay, so zero EP if that's the initial distribution. Maybe I've designed it to be that way. Maybe I was just lucky, whatever. And over here, let's say there's one that's also thermodynamically reversible for one quarter, three quarter. And we just went through the little calculation that well, if you were to use them with a different initial distribution, now they would generate EP, okay? So we have that, we're comfortable with that. Now let me run these two thermodynamically reversible systems in parallel, like in a digital circuit or for that matter, like in a human brain or anything like this. Let's say that the joint distribution, so we'll call this right here, that's x one, this is x two. We're running these two bit erasers in parallel where we're feeding the parallel bit eraser system inputs generated by some distribution of P of x one comma x two. And let's set it up, choose this distribution so that in fact P of x one is two thirds, one third and P of x two, the marginals is one quarter, three quarters. Okay, can anybody tell me, is this system going to generate EP or not? In general, if there's any statistical coupling between x one and x two, you're gonna generate EP. And in fact, the amount of EP you're gonna generate is given by the mutual information between x one and x two. And it's a, it actually comes from mismatch cost. It's an example of mismatch cost. I'll work that through in a second, but let me first give the intuition. For a system to be thermodynamically reversible means that if you take the initial distribution, run the process forward to get the final distribution, you can then run the process backward to return to the initial distribution. Okay, here, I start with an initial distribution where they're coupled. I run the two bit erasers in parallel. I end up with a pair of delta functions.  That's a bit eraser. It's gonna erase that bit no matter what your initial distribution was. So then when you end up with delta functions, you've lost all information about the original statistical coupling. So if you were to try to run these delta functions backwards, depending on the precise details, what you would probably get, if you run the process forward and then run it backward, you would get the product distribution. You would lose all those statistical correlations. They are being lost when you do these kinds of things in parallel. So two thermodynamically reversible systems, you run them in parallel, they're no longer thermodynamically reversible. This is due to mismatch cost. This means that there's non-zero EP in systems just due to the architecture of how they're arranged in terms of parallel gates rather than doing everything serially all at once, okay? And here is, we can see very easily. By the way, when I asked that question, people really should have just looked over at the slides because I gave the answer there. But anyway, I think that I give it on the next reason. So since the gates are distinct, the thermodynamically reversible joint distribution, I'm assuming that each of those gates there run separately from one another. So the thermodynamically joint distribution is gonna be the product distribution. So we're gonna have the mismatch cost. If we actually run it on a P1, which is not a product distribution, we're gonna have a mismatch cost in the normal way that's going to be non-zero. And if you just work it through, not too much surprise, that's actually gonna be the mutual information, the initial mutual information. Can anybody make a guess as to what happens if I run three bit erasers in parallel? What is the mismatch cost, the unavoidable EP now as a function of the initial distribution? And this is actually, it's a part of information theory that Goudje did not actually present. So this is in a certain sense a trick question. If anybody has come across this concept. So there is a reply from the chat, total correlation. Yes, indeed. The multi-information is also sometimes called. There are many, many ways to try to generalize the concept of mutual information, which is defined in terms of two random variables to more than two random variables. There are many ways to do this. People are still having big fights about it. Still lots of blood in conference rooms after people get together and argue about what's the quote best way to do it. One simple way to do it is as follows. The mutual information between two random variables X and Y is one way to define it is the entropy of the marginals minus the entropy of the joint. When the variables are completely, oops, that's a Y. When the variables are completely independent, this is equal to the sum of S of X and S of Y, so you get zero more generally. It's not hard to prove this is always non-negative, okay? So based upon this, what is a natural idea for how to generalize it to more than two random variables that you think might be going on here? This is what the person on the line said. If I have a set of n random variables, it's going to be the sum of the marginals minus the joints. Now what happens if you start to be doing things that are more complicated than bidder racing? And what happens when you start to actually have circuits that are layered where many things are going on at once and where, depending on the actual values, different things might be happening? And so how should we design a circuit to minimize the EP given all these effects? That should be a topic in many, many computer science departments. Right now, there's nobody on planet Earth who's investigating that. With what exception? Actually with a few exceptions. And there's also some workshops going on. But let me put it this way. There is nothing known about that solution yet. And there's also all kinds of in computer science, there's what's called circuit complexity theory. You may have heard of complexity theory in computer science, which is like NP equals P and things like that. There's a version of it for just circuits in particular. And that is very, very natural to try to extend circuit complexity theory to include not just the normal costs that you consider in computer science but to also consider things like EP. And nobody knows really anything about it. It's very, very difficult problems, very difficult. Okay, so I already gave that intuition. And that's it for my slides. And next is going to be, I guess she's going off to the restroom is Golja. I'm presenting thermodynamic uncertainty relations for the rest of today. Are there any more questions then at this point? Anything from the chat or anything like that? Nothing from the chat. Okay, so anyway, when she gets back, she'll take it over for the rest of this afternoon. Okay. Okay, we take a short break. We can take a break now, yeah.


Welcome back to the Hacking Career Village. We're just so excited that we've had so many great presentations these two days. I really want to thank all of our speakers for taking the time to pre-record these discussions and then being available in Discord to be able to answer your 101 questions. Today, we have a good friend from the Twitter sphere, Roy, who is going to talk a little bit about the key ingredients for job interviews, which are very important these days because once you get through all of the search and you finally get that interview, you want to make sure you're on top of your game for that. So Roy, take it away. Great, thank you. Thank you very much, Kathleen, and actually the Career Hacking Village. This is, I think, the first time this year. So first off, thanks to Kathleen and the entire team for having this opportunity as well. And also just wanted to thank everyone for tuning in today. So yeah, first off, going to kind of talk about the key ingredients for job interviews, whether virtual or face-to-face. The first thing that I always like to do in all of my presentations is that I don't accept responsibility for any of the liable for any of the actions or if I have any inaccurate information as well. And of course, the presentation doesn't represent any of the organizations that I have worked for. And of course, this is not, this is absolutely not a one-size-fits-all at all. And again, it depends. It's very contingent on the individual, individuals as well. So first off, yeah, who am I? Healthcare, professional, et cetera. Yeah, basically, taught at Brandeis University for over 10 years, created the program there. And yeah, I really enjoy data forensics, instant response, healthcare security, application security, and IoT, Internet of Things. Obviously, the picture that you see on the right bottom is actually not my picture. There is a great website based on machine learning and artificial intelligence that actually creates different images of people based on different things as well. And it's not a real person at all. So you can actually go to that link to get more information. So the agenda for today is actually I thought that these were the steps in regards to preparing for the job interview or being more successful at it. Number one, we're going to talk about the preparation stage. Number two, about looking great because you always have to look good. Doesn't matter if it's virtual or a face-to-face presentation. Resume review, we'll talk about that too. And really exuding confidence. More confidence, the better as well. And also talk about some note-taking strategies as well. And also asking back, not only do you keep answering questions, you should also ask a lot of questions too. We'll talk about that too. And I actually added one more thing too. And the other one was trying again. We'll talk more about that and really address any specific questions as well. So first off, during the preparation stage, you think about when you're on engagements or a project or actually, let's say you're doing some kind of lead teaming, red teaming, penetration test, et cetera, you want to really do a reconnaissance on the opportunity or the job offer. Remember that it's not a one-size-fits-all. Things that are advertised in the job description are sometimes not always the things that you are the candidates or the individual is going to do. So you want to prepare as much as possible. So like what I like to say is kind of doing your reconnaissance on the opportunity, talking to people inside the company or if you know anyone in your social networking profiles, et cetera, or your conferences, talk to people that may know people in the company. Because chances are you'll get a much more in-depth overview of the company and the opportunity that you are applying for. Also at the same time for those of you who are virtual, just like as we are having physical face-to-face conversations during the interview, et cetera, for those of you that are virtual, especially during these times, you want to ensure that you test all your equipment, lighting, et cetera, and do that ahead of time too. And also at the same time, preparing yourself not only on the specific technical questions and non-technical requirements, I like to call this like doing your homework. Think about, think outside the box and also try to look at the different non-technical skills like the communication skills, teams building skills, additional leadership skills as well. If you don't have the experience, you can substitute it by relevant coursework. For those of you in school, et cetera, or part-time, and some other opportunities like taking a class online, for example, et cetera. Remember that presenting to different audiences is a very key ingredient, not only presenting to technical people, but also presenting to non-technical people as well. And also in addition to doing your reconnaissance on the opportunity or opportunities, performing your own risk assessment on the opportunity, job offer, et cetera, requirements, and giving it a grade. Because just like as we're doing risk assessments, because every security, et cetera, is all about risk assessment, even though there's so many different areas in it, give it a grade. Maybe you have kind of like a spreadsheet that talks about the kind of the different things, location, culture, environments, interviewing with the different people that are there, external factors, for example, and other things, unknowns as well, things like that. Next is always about looking great. I can't stress this enough, but always trying to look good. Present yourself in a way that even if the requirement says that's stress casually, you always probably want to show up in something that you're comfortable in, a business casual suit. It all depends as well. Even if it's virtual or face-to-face, remember, especially during these times when there are a lot of these virtual interviews now, you also want to be prepared for that in terms of looking your best, looking at the lighting, looking at your camera, looking at your sound as well. And practice makes perfect. So the more you do it, the more you get better at it as well. Next is also talking about kind of like the resume review. And I like to say that the resume review can be in different parts. It can be kind of the first step is really tailoring your resume even before applying for the job application or the job opportunity, for example. Tailoring your resume so that it actually shows what you've accomplished. I always like to say that honesty is the best policy. If you don't know something, you can always say that it's something that you want to learn and also that maybe there are some additional courses or open source projects and software that actually you can contribute to. It shows a lot of passion. It also at the same time, you know, I also like to say is that the resume gets you into the door, but the interview, interviews are where the interviewers and the organization gets to know you. And it's a great thing too. And what I also like to say is, again, as an individual that also reviews a lot of resumes when building the team, etc., you want to do something that people haven't done before. Obviously, you want to follow all of the resume guidelines. For example, the number of pages, etc., based on your experience as well, but also at the same time, thinking outside the box, trying to do something that's different. So, for example, when let's say you apply for, give your example, let's say you apply for an engineering job. Obviously, there are going to be a lot of engineering requirements and technical skills and verbal and communication skills as well. As someone that looks at resumes, I would say a lot too as well. And looking to build a team, I would also stress that adding different things that can have you stand out from another individual. Because when you think about it, the organizations are always looking at potential candidates, what are some things that can make you stand out? For example, number one, maybe you may not have as much experience, but it's a great opportunity. It looks like it's a great opportunity. The first thing that you can do is participate in either conferences or volunteering or other projects, especially specifically open source projects that you can contribute to. It shows a lot of passion as well. And of course, motivation. Another thing that you can do is also including taking courses. Especially, I love the stress a lot of these edX courses. So many opportunities now, especially now during the pandemic that are free, they can take as well something that you're learning to build your skill set, basically. And remember that as IT professionals or if basically you're professionals, and just like every other industry or profession, we're always developing our skills. And one of the main ingredients that I look for, maybe in my opinion, is what stands out? Thinking outside the box. A lot of people are going to answer a question this way or have the resume this way. So take a look at the job description and try to do your own assessment in terms of what you can do and what you cannot do. And again, adding different things that where it shows more passionate and motivation as well to do the job, etc. Next, I want to talk about really exuding covenants. Obviously, it really depends if you're introverts or extroverts, but with preparation comes making sure that you understand the roles and responsibilities of the job, not only the job, but the company. What's the organization's business mission, for example? Let's say for a healthcare company, maybe it's all about patients. So for example, when you're doing your job or when you're part of the team doing your job, obviously, you don't want to be like a no team to everything. It also has to support the business. And so look at the business mission as well and educating yourself about not only the job details itself, but learning additional skillset, etc. as well to apply on your job. And also preparing your questions to ask different people. This comes with confidence and experience too, especially as you are doing more interviews depending on the job opportunities and now there are a lot of job opportunities. Prepare your questions, ask different questions to different people. Don't only answer those questions, but as you're doing your homework, getting more information about the company, for example, in the first stage, reconnaissance stage, getting to know people that are in the organization. Maybe there might not be like a direct link, but you can get some questions, etc. I'm going to talk about more of the questions that you should ask as well. And also really, when asking the questions, you want to ask open-ended questions so that it makes just like the interviewer or interviewers, most of the time it's going to be interviewers, they're going to ask you open-ended questions because the interviewers don't want to have to see or don't want to hear like a yes or no answer. They want you to kind of like a scenario-based question chiming in, how you think, how you apply, how you fix this problem. How do you negotiate when you have conflicts as well? So as a job applicants or applicants, you also want to ask these open-ended questions too, to have the organization open up and give you more information, not a yes or no, because it will give you a lot of information in terms of, is this the right opportunity for you or what you're trying to do or pursue, for example, because remember that just because the job description says something doesn't mean that it's going to be 100% what you will be doing, for example. And I'm not going to get into the specific job titles, etc., but there's been a lot of things where there's a lot of misrepresentation around job titles, etc., but that's going to be another talk. But just really when you're building your confidence and again it comes with preparation, etc., and thinking outside the box, you can have all your pre-canned open-ended questions to ask the interviewers, for example. So one of the things that I do, for example, when preparing for the interview, is I do my reconnaissance about the company, but usually what happens is that when the interviewer is scheduled, for example, human resources or the people, culture team, etc., they send a list of all the people that are going to be interviewing you. So one of the things that I like to do just like is actually go to do a reconnaissance and actually see what job the potential interviewers will do, because when HR, Human Resources, sends you that list, it actually shows the individual and actually the person's title as well. You can kind of do your reconnaissance to see how long the individual or interviewers have been in the company, for example, if it's advertised in there. Also, you can see kind of like some of the projects as well as you are kind of like creating these questions too. So again, it's all about when you do your homework, you have more confidence to ask these questions, but without doing your homework, you won't be able to ask the questions. So that's what my challenge to everyone is basically to ask those questions, do your homework so that you can ask those questions so that you can see if this opportunity or requisition is the right one for you. Next, we'll be talking about note-taking. So first off, I really like, I think now, based on the electronic era, etc., you can bring your gadgets, etc., as well, but make sure that, you know, again, maybe it's on vibrates so it doesn't impact your interviews, etc. I still like the traditional notebook or extra piece of paper regarding the questions that you want to ask each individual. So what I usually do during the interviews is, of course, as the applicants, I bring an empty sheet of paper in the front and also in the back. I actually have all of these open-ended challenge questions, open-ended questions for the interviewers as well. And because I cover it up because, number one, you know, it's really like a matter of choice as well, but that way the interviewers don't see that as well. But then, because your blank page will be about taking your notes, really following up for what things you want to ask the interviewer or maybe it's a follow-up in terms of what the interviewer said as well. The reason that I take notes is just so that we remember, we remember what happened, the gist as well.  It's not he said, she said, etc., so that it's all captured in your notes as well. But I also like to say that, again, note taken is a great, great thing because sometimes during the, actually many times during the interviews, etc., there's going to be times where you interview with so many people, typically now for the, you know, depending on how big or how big the companies are or also how noble they are, typically for any information security position and depending on what role you are going to be taking in the organization, typically you're going to be interviewed by at least one to three people or the more senior the position, seniority the position, the more people as well. For example, some of these I've actually, I remember this many years ago, but don't quote me on this, but many years ago, probably when I was actually interviewing for like a security analyst, security engineer position, I actually interviewed for a healthcare hospital position. I interviewed for at least about five people and it took most of the whole day, for example, so just prepare for that. And again, your note taking will come in really handy because this will also not only help you in determining if this is the right fit or the right role and to follow up with any questions that you have or any questions that the interviewers have for you, where you might not know the answer, for example, it also helps into generating after every job interview, for example. Usually it depends, so there's no specific guidance on it, but send like a thank you email, for example, and the note taking will really help because then you know what you talk to each interviewer or interviewers about and you can actually put some of this information in terms of your thank you notes, blah, blah, blah, I'll give you an example. Thank you very much, Erin, Rob, Chris, Mike, Lian for the interview today. I really appreciated the time that you took and then you can kind of say Lian talked about this blah, blah, blah, so it kind of serves you also as like a summary as well to kind of help you close the deal on the interview. Now, I also wanted to add, I added this because, well actually I, the next one was the one I added, but asking back, don't just have, don't just basically answer questions as well. It has, it's kind of like a give and take, so because remember that the interviewers or the interviewer is trying to ascertain if you're the right individual or the right fit for the team, so don't just ask the questions, you want to kind of give and take in terms of having the interviewers ask you questions, but remember in the preparation stage as you're creating, already created these questions based on who you're going to be interviewing with, you want to ask them questions too because this is your best time to make sure that this is the right opportunity for you. Is it really true? Is the job description really, really, really match what is in the job description for example? Is it the right culture? Is it the right environment? Is it the right team? Is it the right people? Is it the right mission? Is this something that you really believe in for example? And like I'm not going to read it, but at the end like getting to really know the real company, obviously I'm going to say again this is just my opinion, but the job description sometimes is probably most, sometimes just a copy from somewhere else as well, and sometimes the job description is not what you actually sign up for, and again this is not a one-size-fits-all, but it depends on the company as well. Now some of these example questions, we're going to talk about that. I don't have everything here, but remember where I mentioned about asking open any questions? So the one thing is that some of these questions can be, you want to find out is this too good to be true? Some of these open questions could be, how long was the security team been in place, for example? Was there Information Security Manager? Why he or she? Was that the company? Did they leave? What was the reason? Et cetera. These are some additional questions that you can ask, and again you can tell your questions on how much information you want as well. So for example, why did some of these questions might be, why did the entire security team all leave? Is this a new security team? Is the security manager who you will be reporting to, for example, or IT manager, why did he or she leave, for example? Other questions might be, again remember it's all open-ended. How long has people specifically been there? It doesn't only have to be about your specific team as well, especially think about, remember that you're doing your reconnaissance, doing your homework, doing your preparation, looking great as well, but making sure, one of the things you can do is, especially your open-ended questions is asking not only who do you report to, but also ask about your manager or your security leadership team who they report to as well. So you can ask, let's say sometimes just to give you an example, the security manager probably reports to, let's say a CISO, or let's say the CISO or every security manager reports to a CISO, you probably want to find out who the CISO reports to. Is it the CIO? Is it the privacy officer? Is the CEO, etc.? It really depends. It's not a one-size-fits-all. That way you can actually tell their question and say, hey, you won't ask it like that, but hey, how come the CIO was only here for this amount of time? Has there been some transition? Has there been some kind of reorganization as well? So remember that it's asking back. It's not only asking questions, but you also want to find, this is your best opportunity to find, if this is the right opportunity for you. And it's something that resonates with you as well. Next is really, this is something that I added as well, because I was just thinking of things of, okay, what happens if you do all this and you still don't succeed? And don't worry, because this is always, it's kind of like a, think of it as like a date, I guess. If the date doesn't go, it all depends. So when you're doing this, even if you do all the, these are, again, these are not a one-size-fits-all, but as you're doing this, obviously these different strategies and tactics will help you as the individual job applicants become more successful. But remember that it doesn't always work. And again, especially these different companies, please don't despair, try again. Even things that, let's say it's a company that you're really interested in, or organization, or et cetera, or it's a great opportunity, the best, don't worry. And again, I think I won't quote it, but there's been many security professionals and engineers where their first choice isn't always the choice that it was set out to be as well. So take this as like a grain of salt, but again, learn from what you've done, lessons learned, et cetera. You know, more interviews also gives more experience and confidence. And also remember, and again, it also depends on the organization as well. Some organizations, based on how you interview, you will get kind of like a very, you know, could be like a big summary sometimes, but some of the organizations if you ask nicely as well, especially with your thank you notice as well, you can also get some feedback on what were some of the feedbacks, things that were a pro that worked really well, and things that did not work very well as well, based on the different interviewers as well. And again, at first you don't, just like that other song, right, I think it was from Aliyah, I believe, at first you don't succeed, try again as well. But take this as a, you know, take this as a learning experience and know that you won't always be successful. I've known people at, when they actually applied to Google, some of these really, you know, really great organizations as well, or brand name recognition, they didn't get in. And then of course, they didn't, they tried three times, you didn't get in. But, you know, after either through a merger position, for example, they actually ended up being at the same company, et cetera. So I also want to say here is that don't burn your bridges as well. Again, obviously treat people as you would like to be treated as well. And again, companies may not give you all the feedback that you may want to hear as well. But again, remember from those open-ended questions, et cetera, too. And usually, remember what I mentioned about like making a risk assessment on the interview or the company, before you actually interview with the company, you can also have like make a grade and a risk assessment in terms of the grade around how your interview went with this interviewer, for example. Would you work well with him or her or the team, for example, would you not work well as well? So you can kind of get a good example. You know, again, it's probably only just from your own perspective. You probably want their own, their perspective as well. But it gives you a good overview and a good remembering, remembrance of what happened during the interview as well. Now, just kind of like putting it all together. Remember that. And again, this is not a one size fits all at all. Really, and again, these probably can be done in different different steps as well. It's not like step one, two, or three. But I really believe that, you know, preparing, having the preparation, having the preparation is key.   Preparation comes with preparation. Comes all the additional confidence that you have, asking the different questions that you have for them as well, and also kind of reciprocating to see if it's the right fit for you as well. Number two, really talks about looking great and just looking your best as well, wearing some kind of business casual, even though there's some other minimum requirement, just looking your best. Doesn't matter if it's virtual or face to face as well. And number three, talking about the resume review process. This is probably beforehand and then of course, afterhand as well, because one of the things that I actually didn't mention. And so I have the paper with your note taking. You have the blank paper. You also have the open-ended questions that you have for the interviewers. But also under that, you also have your resume as well. Maybe you can have additional. Most of the time, the organization will always have the resume. But this is something that you can pull out so that you can reference as well. I've also known some other candidates where, especially when they're going for like different positions or like a higher up position, et cetera, or a position that's just out of their league, for example. Again, remember, it's about thinking outside the box, doing something different. Most people are going to bring the resume, et cetera. What can you do to bring? What can you do to do something different? A lot of people now, they actually bring in like different presentations actually, tailored to what they can do. Let's say like, if you're doing like applying for a chief of emergency security officer position, et cetera. What makes you stand down that other people aren't doing? For example, that could be the difference. Let's say a security analyst position, for example, or someone more junior, et cetera. It doesn't have to be that. It's just showing the initiative, showing that you're passionate, showing that you really want to be part of this team and environment and company and organization.  Maybe one of the things that you can do is actually show some of the presentations that you've done in like a very high level as well. Remember, you can remove all of the company names that you work for before as well for privacy purposes, et cetera. Again, it shows the initiative as well. That's some additional things you can do. Of course, COVID-19 is just really as you do more of your homework, as you prepare for it. Again, what I like to say is that don't just wing it as well. Don't just wing it because that never works for anything. In terms of interviews, et cetera, tests, et cetera. I'm going to say that by doing all of these different recommendations, you will have more confidence as well. You can also look at additional things that you might have additional questions about. Remember that your open-ended questions are just going to be just some pre-canned questions so that you remember that you asked the interviewers about. Maybe when you go to the interview, for example, you see something in the queue. Again, it's not just about pre-caning and then doing your open-ended questions. When you're also interviewing, you're going to see the physical location, et cetera, physical location, physical security as well, and you can also ask open-ended questions around that, too. For example, where I'd be working in this area, what floor, et cetera, where does the IT work, where do the other teams work at, et cetera. People will be working remotely and other things, too. Next is the fifth one is about note-taking. Again, I'm not going to stress that, but just remembering what you talked about, what you're going to say, your open-ended questions, anything else that you want to follow up on from the interviewers to the interviewing for yourself. Also, it serves as a great thank-you sum-up note-taking based on what you mentioned and talked to the interviewers. Next one is asking back. I won't stress that, but really just, again, give and take, not only answering questions, but what you see during the interview, what you see during the phone, what you see during talking to different people, you can ask those open-ended questions. And last but not least, obviously, with all these strategies and recommendations, everyone won't be successful, or probably using these different strategies won't be successful. So keep trying. Again, I think the main thing here is just really trying again and know that even if it didn't work out, there's always going to be a better or more challenging opportunity as well. And things happen for a reason as well. And things may not be meant to be, for example, things like that. And other than that, just wanted to specifically get any questions. I'm on Twitter, WR0. If you have any questions specifically, you can also email me at website or at gmail.com. And also, all of these presentations will also be shared on my GitHub account as well. So thank you very much for your time today. Thank you. Roy, really great step-by-step laying out what people need to do for, excuse me, to what people need to do preparing for their interviews. It's really great. I think that everyone really needs to have that kind of checklist that you just laid out, mainly because we get very nervous and get anxious about preparing for interviews or doing the interviews. So having a really great checklist like this is very helpful. I really liked your suggestion. We tend to work a lot off of our electronic devices, but actually having the notepad when you're in the interview to take down notes, I think that causes us to slow down a little bit because many times when we're in an interview, we're nervous. And having something that slows us down is really great. I also think it's really great, one of the points you brought up about being sure that you bring into the interview the resume that you submitted for the job, so that you can talk from that resume. We've talked in other sessions about making sure you have resumes that are customized to those specific jobs that you're applying for, but it's also helpful to make sure that you've brought the resume with you that you submitted to that job. So really great points. I know we're going to have some questions in our Discord channel. Thank you so much for being part of the Career Hacking Village. Take care, Roy. We'll see you around on Twitter. Yeah, thank you so much. And I look forward to your presentation as well, Kathleen. Thanks. Take care. Bye-bye. Take care. Have a good one. Take care. Bye.


towel scrunch exercise. For this exercise what you're going to do is keep your heel flat on the floor, you're going to use your big toe all the way down to the small toe to scrunch up the towel and pull it underneath your foot. We're going to perform this for ten repetitions two to three times per day.