Good morning, everybody. Welcome you to a second day, first talk on this stage as well. It's quite early. It's still in the middle of the night for some of us, I believe. But yeah, I'm Peter. I'm the hero for today's talk of Camille and Camille is with us. Good morning, Camille. And we, yeah, Camille is giving us a talk about a very interesting idea. We want to play with words. And actually, this is the first Congress of Camille. So it's the first time he's being on stage and at the Congress. So he's enjoying it so far, I hope. Camille is studying mathematics in Poland. And yeah, I think we will let you start with your talk. Actually, it's kind of an interactive session. We have shared or he has shared a document we can use to follow him in his talk. It will be presented, but I think you can enter actually ideas and comments in the document as well. So please be polite. Don't erase anything. Otherwise, we need to shut it down and then stay with the copy read only copy. So Camille, yeah, so have fun. I hand over to you and let's start. Yeah, playing with words. I'm really interested to see what you want to talk about today. Yeah, thank you. Thank you. All right. So a few words about me. I'm considering mathematics before I had one and a half year of long break for optimal places and researching tons of curiosities. Curiosity, since it's one of the reasons I ended up making this talk before I was a visual arts artist working in the industry. And small discriminant. I usually laugh a lot. This is some of some party and encountering and entertaining ideas. So if I will hear some questions for you and I will laugh, this is a compliment. So this is not only about me, but what I do. I do this with in group. So I want to talk about this group a bit. We have five active members. We are from different backgrounds and we playing with words since few months. The main idea of the talk is that I will throw examples of what I mean by playing with words and how how we do this. Then I will sum up and make it like more general. Then because we will generalize the topic, we will be able to speculate about this goal like meta and then I will be waiting for questions. All right. So examples. Here will be a pattern through the whole examples session. First, I will introduce a current word or words or phrases and say what we think it's kind of wrong with them. Then I will say how we propose to fix it and perhaps something more because some examples are like rabbit holes and another one are quick and easy. All right. So let's start. First phrases like to age and to get old. What we think is wrong with it? First thing is that these are at least in my culture, these are charged words kind of negative and they have like basically too many things people can mean when they say to age. So first thing is that they can mean they can mean like age in the biological terms. So this is the fourth one like accumulate cellular and structured damage as an anecdote. This is an ongoing debate in science. What does it mean to age? Here is a link for paper. I hope it will load soon from 2020 which is from December I think which is exploring what is aging in biological terms and authors mention a nice thing here which is quote our mental categories tends to correspond to our linguistic categories. So what is how I read the sentence is that we are used to certain categories that words impose on us and then we expect from reality from our measurements to match this. But actually this is often the case that when we go and try to find what is aging in even aging something that seems to be so fundamental and like natural and normal we find that it's harder to generalize and it's actually a few phenomena going on and different species maybe have different weights on different phenomena and so on. So yeah so to age so one thing when we say to age we can mean that we accumulate cellular damage this is like the general biological meaning of this word but people usually say something different which is like we expect from others to change in the certain way like to behave in an old way like to not exercise a lot or like you know not to learn much like the first year's university is like a university is for people other than like 50, 60, 70 years old kind of new thing as far as I know. So we have many many prescriptions of how how like people above 50, 60 years old should behave so then they agree according to that. So I think it's kind of nice to separate those two phenomena and I can make it clear what we mean. And the first one here is to get unwell as a result of unhealthy lifestyle. So this is kind of between this biological meaning and cultural meaning since like most causes of deaths in the west are due to unhealthy lifestyle like smoking cigarettes and diet. So we actually now currently don't die from mostly from from like accumulation of cellular damage so we don't die specifically from ageing in biological terms per se but from from like what we actually do. Okay so this is this is first example so we basically when we are inside the group of our group with friends we try to avoid using this term and if somebody will use this term we say hey what do you mean and we actually expect from each other to be more precise when we speak about ageing like what do we actually mean. So instead of using shortcuts we using one of those four or more words. Okay so another another another word this work or to work so the thing is with work is that usually when people say work they mean to earn money so volunteering is often not understood as work and we kind of don't like it and like why is this case because historically speaking there was a distinction and and like whole culture shift of understanding of work happened in like 19 to 20 so now we can feel regret that we don't earn money that we don't you know work too much at actually too early because we earn dignity by working and stuff and we say oh let's make it clear like let's speak work to work which is like volunteering raising children learning and so on and so on and labor which is strictly speaking any earning activity so by this we want to be more precise about what we mean by work and also like rift connotations because like now we cannot say ah you don't you are so lazy you don't earn money you know this sounds ridiculous but i'm so late you don't work this this is like normal i thought it's much harder to say oh you're so lazy you don't you don't earn money you don't learn or you know organizing community make people happier this is just as weird one of the readings is like part essay from by guy standing this is a person who is into UI and stuff so he obviously likes to uh write about work and what he writes is that for many decades the term in employment was a matter of regret a recognition of low social status typically applied to single woman obliged to take low paid positions serving household headed by the bourgeoisie or aristocracy so this is to underline the the shift in the like we have the same word but the background but the background like what are what are our feelings towards it uh are completely different and he also writes a nice thing down here to our context and this is also the the same like now it's now it's kind of now we earn as citizens we earn dignity by working but because working shifts this definition only to money earning activity we end up that we earning dignity by earning money and this is like ridiculous situation at least for us so he's he's basically the author of this essay advocating that we shouldn't uh like vilified work or not romanticize it so yes we propose to uh yeah i see somebody added uh yes the the physical physical yes of course is a technical term uh labor us we just make this here what do we mean by labor money yes of course we don't want to erase the physical interpretations of of work uh we meant it here in culture this was in the background all right so let's go to another case yes sorry for typos so interesting we propose to ban word interesting so when we are inside our group we don't use the word interesting or at least we try to use this word uh and this is controversial oftenly when people first heard about it but let me explain this so interesting is used in the context when somebody is presenting some idea and you can say it's interesting so we consider this as meaningless because somebody can say if they are interested or not uh so if the person is really interested in what we are presenting to them it's it's obvious it's like saying like this is like people you know are it's you see by their body language that they're actually interested and wants to know more about something you are presenting to them so it's much better to just ask a particular question you know express this enthusiasm just done just mer saying that something's interesting okay another another example to like to have a taste at such a draw so uh actually this is how the thing with playing with words started i read about mer exposure effect so mer exposure effect is uh kind of bias which says that if you saw something before there's a much greater probability that you will like it if you will see it a second time even though you consciously wouldn't remember that you saw before this thing so i thought okay so maybe when people say i like something they actually mean that they are used to this thing at least in certain at least in certain cases so then i was speaking with people and when they say i like i just inside my brain it was automatically like they just i they say i like like i like brazos and in my head i heard i am used to brazos and sometimes this thing used to make much better sense and actually what is does if you replace some occurrence of like to have a taste you will discover that this is much more flexible topic that it's not that you have to like some something and it's closed it's it's under it's when you say i am used to something you you want to underline that what you actually currently like is is the output of the past is a product of the past thus you can try to change it like easier so by changing like to being used to we try to like underline or highlight that that the the future don't have to be the same as as the past what's another thing thank you it can make a comments because this is a definition but appreciated what's what other thing is that about like is that if you see it how the frequency of of like how it's used in a corpus in the body of language is that we are there is a spike in the occurrence of like of course some of it can be can be explained with facebook but you see that the liking is sharply increasing even before facebook and actually the tempo you can see this is very sharp decrease steady decrease and facebook only changed this maybe even more and i also feel because of that the pressure to like and this gives this this take us to another and this is my personal favorite which is meta prefix this is actually a war prefix that we created so what i wanted to say that uh like like is used more like like so often and i feel like obligated to like so many things but what actually i would like to is not to like to like things so this takes us to meta prefix so here we have examples of meta prefix in war in in action so meta prefix is about like self-referentialing words so you can say i like shopping and then i like to like shopping and i like to like to like shopping so with meta prefix you can make this sentence shorter by adding like to like which means hmm or like double like which is like to like shopping so it's it's a bit of a headache at the beginning but then you yes yes somebody yes this is this is this can be done of course so uh what's but i'll explain what i will soon go to why why making is and and like making much more rigid and i like a number here uh is uh is actually might be a good idea as a way to generate more ideas but i will go to that soon anyway so we have this meta prefix which allows us more easy to say like to like shopping and it's a bit of the headache at the beginning but then you start to wonder why it wasn't normal before like consider the case that you are in the kitchen and preparing brassels and dish with brassels and the person sits next to you and you ask them do you like brassels and they answer you know i don't like brassels so like what are you supposed to do with this information what it scans is that do they like brassels and do do they like to like brassels because if they don't like brassels but don't like to don't like brassels this means that they want to change this liking so if this meta prefix going to to these directions during during conversation is much easier like because it's just like normalizing so this is a term in design affordance just because something is easy to afford you do it more often and it works obviously with negation and this is also the nice question about notation like what's the best notation for it okay so why why should we like what's what we gain by making a number in here so question the meta prefix generated uh can you go further like we like like to like to like if you stop and think about it makes sense but then you hit a ceiling like like to like to like not to like is just like complete garbage so is it because the word itself the phrase itself loses like meaning or is that it's our limited capacity for so it's so for humans it's easy to like to like to like and to like to like to like but it's harder you know you you you hit certain ceiling okay so what other things it generated so it started from liking but then we generalized it to prefix so we can think what are other examples of this meta prefix in use i find example with tolerance nice so it's saying that tolerance requires intolerance of intolerance so in order to have tolerance you have to have intolerance or intolerance uh so i think this sounds less paradoxical with this meta prefix also be used to so are you used to to being used to you know again opening to possibilities like okay you are used to something but maybe your new your addiction is new so you can ask are you used to to being used to um also to believe like do you believe that you believe this is this is this is a then we we thought about this belief and then i found uh reading uh this is a logician the mathematician that he make a whole field of uh doxastic logic and where he wants to categorize type of reason so a normal reasoner is a person who why you're believing p also believe they believe p and there is also an opposite one so by believing p do not believe p and this is a well-known paradox in philosophy so so making this uh making this uh prefix allowed us to like apply this mechanism to the other words um and make it more fun basically and this is the most abstract thus far and we want to go further probably uh can we go to the opposite direction so you see we use numbers here so like to like is to like i like to like to like is free like so we can obviously go like we can increase um we can increase this but can we decrease so what would be to minus one to minus two to minus three like so thus far we think this is garbage but uh we uh we keep an eye maybe some words we would be it would be applyable this kind of trick um thus far we have only one example of this but this requires a bit of introduction so imagine a language which in which uh like means like to like so when people using this language which says like they use like to like and they just don't use this one like only to like um so they could also wonder can we go to the opposite direction and they would discover that they actually can like things as well this one like not only two likes so this is this going to opposite direction and i think a similar things happen already with uh the word see so when i say i see a screen a camera what i mean exactly is that i am aware of seeing it's kind of i'm seeing that i see the camera so to be more specific like i have a model and above of myself which is aware of seeing and now i see this but we have blind spot in the eye so we in a way on the on the low level we see this but our model of ourselves our model is making it smoother so if we agree that that see that we already using seeing in this in this meta prefix way we can go to the opposite direction and say that i don't see that i see a blind spot because the information is there it just being erased before our before it really gets to the model okay so because the meta prefix is my favorite there is a whole big document uh with with it and feel free to go over there and make a comment okay another word come in with us this is example of uh taking back archaic words this is an uh word of a latin root uh and find the beautiful it's uh coming to us means unstructured community in which people are equal and the second meaning is that the first period of community so we encourage use of community task community task again and we do it it's not that like we encourage like actually like who cares like we are already doing this inside our group another one this was a quick one this was before we have examples of erasing words or redefining them and using these definitions but now it's an example that we took back archaic word okay in the world this is comparison and this this this word was invented if i remember correct correctly uh in something like 90s 80s in new york city by some polyamorous uh commune uh they felt that they need the opposite of jealousy so here we have a little diagram maybe like i make it bigger if somebody have a small screen so here is my partner my partner's happiness or success and my partner's happiness or misfortune and here is me axis uh me happy me i'm happy so jealousy is when you are unhappy because your partner is happy uh shun them for that uh i didn't know this word it's it's kind of nice word which is not in english uh i mean it's just borrowed from german uh so it's when you are happy that your friend is unhappy and compassion is when you are happy because your partner is happy this is usually used in the context of polyamory so that your partner has had sex with somebody and you're happy not jealous about this so uh this is next background story we were just sitting on the balcony and thinking like wait a minute what's the opposite of jealousy like can we name it like do we really have to say the opposite of jealousy or inventing a long string of words to to mean the single thing that is like normal to us and so we firstly thinking okay we have to invent new word but then i i searched the web and figured out that there is already such a word and there was a community who also was trying to invent new words and using it so we just uh took it uh and this is this was a very nice nice moment in relation kind of and this is a subtle thing now the subtle remark about this because we started to thinking about compassion as the opposite of the jealousy but now we're thinking about the jealousy as the opposite of compassion so by this we like normalize the word comparison uh so this is the compassion this is this thing and then you'll see oh this is the opposite of that and this shield of words reminds me of adding cisgender to vocabulary to normalize transgender so again this is you know you're not that really you know uh because it can be transgender or and there is no word for that so the other the words cisgender and this normalized transgender so this is also to this kind of shifting of weights okay so now a two easy and quick examples so the first one is the phrase latin phrase post hoc ergo propter hock probably i probably misspelled this so we just propose to vulgarize latin and get away with it like before doesn't mean because end of the story don't use latin nobody knows that even academics don't know this language anymore and another one is uh swearing uh i'm just right i'm not sure if i can swear here so i just in uh say that this is a sword in order to this is a phrase to replace being angry towards animals other than human in cities so one of our friend uh one of us spotted that people get angry about animals but come on like the whole context about animals in the cities that we've had in the city but we have to figure out the way to live there so this was traumatizing experience for them and now we are swearing at them like come on so we prefer to say i would prefer if pigeons would add up in other ways is what do you think in a city right so uh this is the end example uh now i would try i will sum up what uh what both examples were about and also generalize what what we were doing what we are doing so from the linguistics perspective we are changing most cultural keywords so we don't change the like primitive words like a group or numbers or place because there is no need for that they they are as basic as possible you probably cannot go and do anything with them and what do we change is the cultural keywords the words that are charged the words that don't only refer to like this with this this was the case with ageing that it's also it's not only a word in biological term but it's very much culturally charged and our attempt to change words stems from from the feeling that many things in culture we just find them ridiculous so and this cultural keywords are just spreading this ridiculousness so we try to change the culture keywords the words we find stickers in the community sharing of mental work so we're making a bubble a nice bubble for ourselves uh so our goal is to provoke thoughts promote like perspective shift of perspective and make us like to to avoid or provide shortcuts because words in like are shortcuts so we are doing this by by redefining words with building blocks words this semantic primitives as they are called in linguistics to denormalize so for example country or like nation this is a one word but if you start like to define this it's starting to be like more and more weird and you see more and more opportunities of how this could be otherwise so now everybody are using like nation and it's like very smooth and you can say such a ridiculous thing very quickly so we are attempting to bond words like this or like change their their meaning they change their definitions and use the definitions instead of the word so you have to say what actually countries and make it makes you it is to make you think about this a bit more yes so we are redefining words using the phrase instead of one word this is an example we have much more examples before but let's go another one natural we try not to use the words natural natural this is a password with the word so uh we propose to say instead of natural that fits in imaginative order originating from the comfort of the post-industrial world uh yeah so instead of natural you just have to say this whole phrase like what does it mean natural it's like no no meaning we we like to hear this word because we are living in the buildings we have technology which protects us from nature that's why it's have good good connotations we are reconsidering basis so for example a first person like we often the use of the first person and thinking about people as individuals instead of as a group in the context like it's also inscribed in language we have grammatical structures to speak about singular singular individual people but we don't have structure the grammatical structure is too easy and quickly speak about somebody inside the group or somebody within a context so one thing we propose is and now there's a new conduction which is on which means in the context of so we can say i con crowd tend to be withdrawn so i con crowd is a singular subject here which means i in the context of the crowd so if and so it's again affordance it's affordance so because we have this connection it's so easy and this this word actually suggests you to use this use this the the mere existence of it suggests you to use this so this makes sentences much more precise and not that longer maybe also trying to ban weasel words so so you can see that some rules are similar to the Wikipedia editing rules okay another thing that we are doing is creating new words in order to match them to what we actually do so this was the case for example with this compression word that we have this feeling a lot but there is no word for this feeling so we're making this word no problem and we promote this word as i'm doing right now so if you can if it's hard to empathize if it's hard for you to empathize with it you can consider archaic word word amnion this is a greek word which means a ball in which the blood of victims was caught like now for most of this this word makes no sense like we don't have to have a word for this because the use of it is like miniscule but but if you're in some subculture you have the reverse thing so you want to have like quick words to refer to what are you doing so this is very this is a regular thing when you work for example in some specific domain and you work within a group so you are making your own shortcuts your own word but and we are making it also but what's different is that that they are not technical terms but cultural terms so they're not referring to the sometimes they're not referring to the outside like to describe quickly some phenomena or some process but to reflect how do we think and thus they are shareable like i can see i can say to you what's what is a comparison and you will understand it and you can actually like start using it so this is the difference between like making a words within some specific domain which is not like generalizable okay so we finished the part with examples and make a sum up like what linguistic what linguists could say about this what are patterns that can be spotted like what words are we changing in what ways are we changing them uh and now we are slowly going to the uh end which is shifting between wokups i refer to wokups as to the select this this creative vocabulary this this body of new words and styles and phrases so what do i mean by shifting wokups shifting between the wokups so so consider politics and we take a cliche example which is abortion so when one side of the political spectrum hear this word they mean pro-life and another side of the political spectrum hear pro-choice with this word so even though the word this one they are referring to two completely different two completely different words and often me there is no intersection between these words so they are using the same word but speaking of different things and it's kind of similar to what like we have done like we are changing the background sometimes behind the words so you can like what else you could do with vocabulary with language you could try to erase non-s okay this is a very crazy idea but consider this like your friend has a positive on facebook wall or whatever that he that they don't know what to do next and are asking for advice should i go to the neuroscience to make a phd and somebody answers why go to neuroscience it's like go there it's a bullshit go there go to it instead so like this this advice like actually i don't mean anything like you don't have any reasons there is no explanation it's just like a sentence that means nothing it's just like go to the place like this the x is bullshit so you are erasing the norm like x is bullshit go to where i prefer instead so you can imagine that there is a filter that erases here are more examples here in this in this essay you can you can think it as a filter that filters out certain nones and making a patterns there so so the non becomes for example what i like so don't go to it like don't go where i don't like to be you know what i don't sympathize with so the essay is here and it just describes in more detail what i mean here i think the example is exactly the same yes should i get the phd in neuroscience so the input sentence is don't go in this neuroscience something focus on it instead so the the nones here are like meaningless like there is no explanation given there is no you know meaning in this word like in terms of advice having an advice so the output of such a filter without nones would be don't go into and in square brackets insert what the interlocutor plans to do and add something and then focus on what speakers sympathize with instead so this is pretty paradoxical because we erased you know we erased nones or more specifically we put a placeholders for nones and we actually like censor them and now actually we have a sentence which makes much more sense which actually conveys the meaning so this could be also think about some you know playing with words erasing some words and making a generic statements what they actually represent this this can be applied in some cases um another example of this uh is the polite type and this is the initiative in in its infancy it's like the first stage and what's what they did this group uh did is they created what's something with this technique I have found so you can install like most machines most computers uh and this but this font is not only about look this uh this this uh font has find and replace algorithm like very basic find and replace they have like tables with thousands of thousands of words that this font is replacing so if you type with this font ugly you see you are not you are so you see let's again you are this font it's not changing this but when you type ugly the phrase not traditionally beautiful this place and if you try to make like swearing here that we brew or or like stuff like that so so in the future they want to replace the simple find and find and replace algorithm which is like totally damp with a machine learning and apply it as a font uh so you I'm not saying that this is a nice initiative I I have actually I it's interesting theoretically I have no idea would it work and would the outcome would be positive or negative but consider that the whole idea in this in its generality like you have a font which applies certain point of view so and it could work from both from the writer and from the viewer so you could imagine now that you have such a font which is you know make made from particular subculture so if you type in this font you know natural it's it's replace fit in imaginary order originating from the comfort of the post industrial life or you type opposite of jealousy and it's replace it with compression or you know you type to work and it's ask you do you mean to work or to labor you mean work or labor so you this is this is very especially if we go back as I said that we go back to the politics when you could imagine such filters for for you know the ideologies so you can imagine person on the left typing something and on the right person reading with you know right wing new filter and they will see completely two completely different body of text so this is very scary but on the other hand this is kind of think we have currently but it's not formula formalized so as I said before now you people from we from two different ideologies see the one word which is abortion and the two persons the thing completely different they have completely different things in in their mind so you could formalize you could try to formalize this and you know make these functions like explicit and now we're going to the end and now you can wrap it even more and say like how discussions would look like if you could if you you know have you would have if you have such a filter like this like would arguing make sense like arguing could be so obvious like I mean arguing this you know low level like low like not like intellectual stimulating discussion about politics like they could be easily my hypothesis is that they could be easily reduced to this kind of font which you know automatically replace ugly to not traditionally beautiful blurs the words that the other the some speakers don't like and so on and so on so maybe then the new kind of debates would emerge which would be you know actually speaking about language so look like in my vocabulary when you say this thing I hear this phrase like this is what I actually hear like what I actually feel when I hear what you're talking about so you could have these things explicit I think this could make discussions easier yeah so maybe another example of so you could also so you could see you know think about like more functions like how to move from one vocabulary to another and where like where are isomorphisms like if they're in what vocabularies you can go to and then back and go and stay with the same place when no information is lost so I think this would be this is that this interests me this like makes like I want I want to see it happening okay so maybe another example because I think it might be a bit confusing so context alex wants to use gender gender neutral pronouns unfortunately they aren't used to them yet moreover they think it would be funny to change some occurrence of like to use to they have read about the mere expo effect recently alex is also a fan of satirical novels input is what they write in the diary so here's the input yesterday sophie was cooking a dinner for everybody she prepared traditional dishes I like them so much they are from my country and the output so the output is what this filter what this kind of font which not only you know changes the words like ugly to not traditionally beautiful but it's much much more advanced goods could display yesterday sophie was cooking dinner for everybody so this is unchanged this is like very neutral like it's hard to you know to change anything there but you could like if you want to they so you see that the vocab the the filter changed she today prepared traditional dishes like this is also like generic you could actually implement the dipolei type is the open source so you could actually try to implement this right away and now it's not and now the funny part so it so the filter change I like them so much they are from my country too I am used to them so much they are from my grandfather so first thing it changed the filter changes like to use to and the second thing is that the filter changed country to grand fallon so as as it was in the context the alex likes satirical novels so they read the card for a good and the grand fallon is a word from a for from courts for a good books and it means grand fallon non group in which meaning is established by a virtue of being in that group probably as a result of the random process so you see that it would be such a tool would be also a could be also using creative ways like somebody that's read court for no good and wants to implement this language to their use so they can just you know go to open the filters that come and org and or g and just download and apply the card for the goods filter and see what some phrases would be changed to if they write like normal stuff all right so this this was the intense part I think that this is the end I have nothing to add so thank you for for stating and waiting for course yeah thank you come here take very much this was interesting and way more complex than expected I think we have a few minutes or seconds to go for a question I think I have a question here from the internet it's linked to your like example it's a little bit like a comment maybe because it would take more time the question is could you explain the widely used word like in in sentences like it's just like your opinion man so it's part of it yeah yeah yeah so yes yes yes yes you're sure so this as far as I understand this means like like as something similar so so obviously we don't like change something similar to the phrase used to this was like implicitly so like sure we don't want to change this we meant only with this sympathy meaning of this word yeah it was more like a discussion point because maybe some more occurrence was like this one used as part of a complete sentence man okay one more question it's a little thing to your polite type example because it looks to be very complex and the question is playing with words in other languages so localizing content is a very complex problem and it is often used completely misleading translations so have you seen other groups like yours playing with words or could your group be starting point to get more information how to avoid these mistakes sorry I it was a bit jacked you can contact me with this mail because I don't know how much time we have but there was something about this yeah it was about your group and if you may be a good starting point for other resources and yes you can join us you can you can you can send me an email and I basically sent you all the links to the group and introduce you to the group so everybody okay can me I think that's that's all for now so I hope you enjoyed your first talk at the congress and you will hopefully have more so next time we see in person in life I think again yeah I hope so thank you very very much thank you very much thank you buddy bye now


Hi, this is Saig from SD Microelectronics. In this video, I'm going to show you how to generate dead time in between complementary PDLVM signals using SDM32's advanced timer peripheral. The objective for this video is to generate dead time between complementary PDLVM signal to minimize the risk of two complementary transistors in bridge topologies from shorting and causing damage to the circuit. Just a side note, for accessing all the materials discussed in this video, please visit the link in the description. For this hands-on, you will need a Nucleo H745, a micro USB cable for connecting the board to the host, and a oscilloscope for measuring the output PDLVM signal with the inserted dead time. For my setup, I will be using a 200 MHz dual channel mixed oscilloscope. Why do we need dead time insertion? When operating multiple switches, for example those in the H-bridge configuration, we want to operate switches inversely, such that the top switch is on and the bottom switch is off, like the one shown in the right figure. However, due to delays in switching, there is a chance that top and bottom switches can both stay on at the same time, momentarily, which causes a shoot-through and ultimately destroys your H-bridge circuit. I'm going to briefly discuss a low-level setup of dead time configuration, although in the laboratory, we wouldn't be needing to worry about all of these details. Dead time insertion is enabled by setting both the CCXE and CCXNE bits of the capture-compare-enable register, timer 1 being in our case. If the break circuit is present, then you also need to enable the MOE bit in the timer break and dead time register. You can read more about the break function in the reference manual section using the break function. Output pulse will not be generated for dead time delays being longer than the OXC or the OCXN output pulse width. You can read more about the dead time insertion setup by referring to the section complementary output and dead time insertion. For this hands-on, we'll choose an arbitrary value of 10 microseconds between the output PWM and the negative PWM output signal. We'll be inserting a pause of dead time, which just means during the 10 microseconds both outputs are not inserted. Timer 1 will be selected for this application because we need the complementary output. This table can be found in the datasheet. Now we're going to start the hands-on exercise. Using STM32Q IDE, create a new STM32 project and select NUCLEO H745 board for this exercise. File, new, STM32 project. Type in STM32 H745. We're going to select this board here, click next. We're going to give it a name of dead time insertion PWM underscore demo. Click finish. Go to clock configuration. For the clock, we're going to work with a value of 64 megahertz. This value is chosen arbitrarily. Go to pinout and configuration. Go to timers. Select one of the advanced timers. We'll go with timer 1 because it can output complementary PWM signal. For runtime context, set it to cortex M7. We're going to load our project on the cortex M7 core. We're going to choose complementary output. So change channel 1 to PWM generation. Channel 1, channel 1N. PWM generation, channel 1, channel 1N. We want to create an output PWM signal of one kilohertz. Again, arbitrary chosen here. Let us use a prescalar of 64 to reduce our clock to one megahertz. Since the prescalar counts from zero, we'll enter 64 minus one for the prescalar. Counter mode up. County period. In order to get the PWM output one kilohertz, we need to have the timer counter reset every 1000 count because dividing one megahertz with 1000 gives us one kilohertz. Go to break and dead time management output configuration. Set dead time to 232. We input 232 ticks for generating 10 microseconds of dead time. Calculations will be shown in latest lights.  For pulse, enter 500. Choosing pulse of 500 would give us 50% recycle because 500 divided by 1000 gives us 0.5. Note that pen PA7 is connected to timer 1, channel 1N and pen PE9 is connected to timer 1, channel 1. After finishing your IOC file configuration, click device configuration tool and code generation. For the last step, you need to enable complimentary PWM generation using the HAL API for the regular channel and the HAL API for the negated channel. In the link provided in the description, you'll come across as a folder called complimentary PWM dead time insertion. Extract it here. Open the text file code to be added and copy these two lines into your main code in the Cortex M7 core project. Add these two lines here. Say a brief overview of the HAL API is used over here. The first HAL API highlighted here starts the PWM for the normal channel, timer 1, timer channel 1. The second HAL API here starts the PWM for the negated channel, timer 1. Before running our Cortex M7 project, we need to upload the Cortex M4 project image into our board. Else, our project on the Cortex M7 core will get stuck inside a loop. So click on the Cortex M4 project, click on build, build finish, and click on run. Click OK. So now our Cortex M4 image is uploaded into our board, so we're ready to upload our Cortex M7 project next. Compile the project and ensure there are no errors or warnings. Zero errors, zero warnings. Now debug and flash your image into the nuclear board. Click Resume. Now the code is executing on the nuclear board. Connect your oscilloscope to pins PA7 and PE9. Then you should observe a complimentary output signal. Zooming in using the scope, you should observe a 10-microsecond dead time between channel 1 and channel 2 of your scope. Details about the calculations can be found on the PDF slide posted in the link. As well, you can reference the dead time generator set up in the reference panel. Connecting channel 1 of our scope to pin PA7 and channel 2 to PE9, we observe the fallen figure. You should see something similar. It's hard to see the dead time inserted into our signal, so we'll zoom in. When you zoom in, you should observe the figure shown. Using the cursor feature of your oscilloscope, you will measure the dead time to be approximately 10 microseconds. Relevant application notes, as well as reference manual and datasheet, can be found in the following links. We hope you found this video helpful. Thank you very much for watching.


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