Comp Lair Live #30 | Guest: Vlad A., Sup / Founder at TECH-VA.com | Tech Corner: Particles Isolation

[Music] hello hello everybody hello i was wondering do i have my mic on i do because now i can see the meter on hello everybody uh welcome to another show as usual it's been a couple of weeks since the last time by the way before i forgot um there might be a chance that after today's session we might have to wait a little bit more than just a couple of weeks but i will let you know anyway on social media as usual but i'm just giving you the heads up all right so you know part of the promise this season was we can have content every week and that's been true so far but um you know um it's summertime and uh there's uh i would like to take some time off basically but um that's not that that's not actually the reason only that reason but that might be the case okay so um i'll let you know as usual but uh yeah let's see how's everyone doing here hello hello everybody so we have the usual suspects with us uh tonight cgi master i believe russia found mistaken correct cgi master correct me if i'm wrong um we have uk with sabine we have rd studios hello rt studios we have workflow in mind that says notified yeah it's been a while isn't it i know that this season it's been more about insights from from the guest i guess rather than notified but i think we need to even that out a bit better so we'll see we'll see um if we can make more of those because i know that it's a it's it's a favorite uh it started i think it started actually with sabine actually uh on the first season the notified thing and then it became something that people always push for yeah i was right cgi master is from russia i believe it's alexa but it's been really quiet it's not uh it doesn't want to disclose who cgi master is uh whether it's he or she i believe it's alex say but i might be wrong here anyway guys welcome to another show and uh we're gonna have a great show as usual you know i always say this obviously uh but let's start with the updates in terms of what happened these couple of weeks of course we have to talk about the usual topic which is the pandemic as as you all know the easing of restrictions across the vaccinated countries continue cases are on the rise again but it seems like these cases are a little bit more controlled in terms of our specializations or severe cases that's obviously due to the vaccination and due to the vaccines themselves um but in any case it seems like we are witnessing at the moment um according to a lot of reports actually that um it seems like the with these new variants things are changing slightly again in terms of like it seems like these variants seem to compromise the immunity that some people have um once they have the they have had the the full vaccine so we are seeing people getting infected um not as i said in the beginning not like severely uh thankfully obviously and let's hope that it continues like that the problem is if they need treatment they will need to go to the hospital and if there's a lot of people uh with that need of course you know staff will will will become like overwhelmed with with the amount of people in the hospitals and because of that probably we well these people will will get compromised in terms of like the treatment that they can get so things are slightly changing it seems um with these new variants um we'll see what happens here uh but because of that as you probably heard also and we've been hearing this for the past maybe i don't know a few months actually i'm talking about like the third dose or the booster dose whatever you want to call it some people call it one thing some people call it another but because of that some countries are already some of them already um giving that a booster i'm thinking about israel if i'm not mistaken i think they're already doing that actively correct me if i'm wrong if any of you have informations regarding that but um dubai administration in the us obviously expected is expected to advise this coffee booster uh shots for most americans so i'm not exactly sure when this will happen as like an unofficial kind of a situation but we've been hearing this for quite a long time now so it seems like it's uh it's actually going forward uh they believe joe i think we talked about this actually last time uh wajo is asking to slow down the booster while we still have like a lot of countries unfortunately without the normal vaccine so why talking about booster if we can't vaccinate the whole can the whole world i would say right because this only works if everybody is vaccinated since we're talking about the pandemic which affects everyone globally at a global scale right so um at the same time of course we can argue yes but if people are getting sick again of course we have to treat them and if there's a vaccination why not if there's like in this booster why not so i'm not gonna get into what's the correct way to go about these things what am i to say right but it seems like this is uh actually happening but it's also weird because i read i think it was today that um there was a study conducted recently and we talked we've been hearing these studies uh you know very often actually and the one that i'm referring today is modernis kovid 19 vaccine protects again delta variant so it seems like these studies you know find that they're actually effective at the same time people are getting sick again or getting infected after getting these shots and of course i'm talking about modern but i read other other studies about other vaccines for example pfizer that it was found out that it seems like it's also very effective but then we have this reality so i'm not exactly sure how these things it's hard to to to understand which one we should hear right um we should hear science obviously but at the same time it's a bit um hard as as as i'm sure everyone can understand which thing should we actually hear right because i think everybody's trying to learn how to deal and and live with this and and of course there's a lot of unknowns still there's a lot of things that was that were discovered at the same time but you know we have like this uh conflicting reality it seems and speaking of which i read this today also probably some of you did too that new zealand uh just entered a new national lockdown over one covet case it seems like it's a delta variant case and because of that they've decided that okay it's time for a new lockdown so it's a bit daunting to i would say to you know think about in during another lockdown i don't think to be honest with you and you've been hearing me saying the opposite you know in the past but i think by now i think it's very hard i will see what happens obviously but i think it's hard to to think ab and to think about another lockdown in europe in europe um we'll see what happens i i hope i'm right this time because nobody would like that obviously but uh you know we're seeing on the other hand we're seeing like this happening on other parts of the world um of course very different continents very different countries very different politics also involved in many different ways but we'll see what happens and also australia continues with its lockdown as far as i'm aware so i think we are now over they are now over one month uh in lockdown um so yeah so all of these things uh it's happening um it's weird right vaccination for the younger generation is also in place and being rolled out in different countries of course at different times as we had uh for you know the the target population or the target uh type of ages but this is now in place and in the uk uh every 16 and 17 year years old uh are to be offered a jab by 23rd of august so we're talking about the week from from now uh i believe yeah a week from now more or less so yeah this will also happen and it's already happening in different countries too and um what else do we have for this week uh on top of everything that is happening regarding the pandemic and all that stuff um we are all aware of what just happened in afghanistan i'm not going to get into politics of the situation because this is obviously not a political show i don't want it to be ever that's not what this is all about but in any case for those of you that were possibly distracted uh these past couple weeks or past couple of days actually because this happened just that recently um and this is also because you know this show as i've mentioned before is also an historic document i think it's um it's important to refer this also uh talking about of course the taliban occupying afghanistan again after 20 years the entire international press is covering the situation extensively and of course for those of you that are interested in knowing more about this i'm sure you have no you will have no trouble in in finding sources obviously but yeah on top of everything this is um this is also happening which takes me to you know i'm sure that uh some of you sometimes by now everybody's tired about the situation kovi and all that stuff but um the reason why i also mentioned what i just mentioned now it's because you know it seems like at least sometimes i feel like this is um this is happening what i'm about to say which is like it seems like the world is under like a really you know severe um changing mode uh because you know a lot of things a lot of them change and it they change very rapidly uh for the past couple of years not even from the pandemic which is obviously what we're talking about here and it's total disruption uh in terms of like personal life and professional lives as we knew it so far of course because of that a lot of good things happen and will happen of course it's also important important to refer the positives not only focusing on negatives but in any case i'm talking about change overall so we have of course the pandemic which is like really big obviously and because of that a lot of other things you know happen too some of them more related with the pandemic than others but in any case it seems like it's all happening at the same time so talking about the pandemic we're talking about this crazy weather that we're all experiencing um these days in many different parts of the world whether it's flooding where it's like crazy temperatures and you know you name it you know i'm talking about uh so this global warming thing it seems like it's giving like really um clear signs that this is actually happening this is not a joke i actually read a couple of days ago or maybe a little bit more that the international scientific community is saying okay guys this is guys i mean population you know humankind uh overall this is like we have no wiggle room anymore so we have to do definitely something about this because this is getting a little bit uh daunting and maybe there's no to certain situations there is no coming back unless we start actually doing some things about this global warming and we are witnessing the effects at the moment for sure many different parts we're talking about like canada we talked about this also a few sessions ago canada experiencing like 50 degrees temperatures something crazy like that so it's really crazy at the moment and um also big leaps about talking about still talking about change big leaps that we witnessed um these couple of years since the pandemic hit big leaps in developing develop development i'm sorry about new technologies also in our industry but not only and including also this new space race that uh is like the the latest uh craze right so you know it's unbelievable uh about all of these things these are just examples but they're really big and it's a little bit crazy to think about like all of these big big things that happened in just a couple of years it would be and think of in and think of all i would i would say yeah if it wasn't like if it was like three years ago we're talking about okay you know in this year or within like one and a half years from now we're gonna witness all of these things you know it's it's it's really sometimes you know i i stopped for a moment and thinking and think to myself like is this really happening you know what i mean a lot of good things happen i'm not talking about just the bad things that's what i'm trying to say i'm talking about also positive things obviously and we talked about many of them in this show but in any case it's a lot of them a lot of a lot of things happening in just a short period of time so [Applause] uh for those of you and i know that we have like um been very blessed uh in that like many different countries watching the show not necessarily speaking live because of course it's a global thing the internet obviously so people might not be um might not have the chance to watch this live but uh i know that a lot of people you know as as usual send me messages and stuff like that from all around the world i hope all of you are doing okay i hope all your families are doing fine as well and if you encounter yourselves in a bad situation um think that this will not last forever okay and without a doubt the world is changing quite a lot as i just mentioned now but um things will get better for sure okay we've been too diffic we've been through difficult periods of time in the past and um for sure it's uh it's gonna happen again the fact that we're gonna overcome them as we did in the past two vfx wise for example um we're leaving a very good moment so the hiring spree continues uh which is obviously a very great great great thing and uh so you know regarding this there's no major news actually apart from the fact that this is a continuous good moment and i think it's going to continue that like that for the past for the next i don't know i'm not going to say a number but um it's going to be like that for a while which is great and it's great especially but not only but great uh especially after these difficult periods um for the entire film sector for the entire filmmaking sector right in which of course fx is included so it's not great to see that all of these companies around the world even new ones even you know sometimes hearing their companies that we never heard about um or they were like not really well known but it seems like everybody's hiring at the moment so it's great it's it's a great thing so for those of you that found yourselves either out of work or concerned about what would what you know what would happen which is obviously more than than understandable that people would think like that or you know something along these lines i think now this is definitely a good moment so your time will come for sure okay and i hope the show also helps you guys with with that like finding new solutions new techniques also obviously with the next level program which was like a big effort on my part i have to say but it's great to see that so many people now uh joined and are enjoying it so i thank you all me and monica obviously from the bottom of our hearts we are trying our best to give you the best as well but it's great to uh to hear this feedback from all of you cool speaking of which by the way and now it's time to talk about the technical highlight of the week and in one of the past calls um of the current class there was one person i'm not going to mention the name because i'm not sure if this person wants his name to be disclosed i already gave away right now without without warning uh if he's he or she but anyway i'm talking about vfx cameras database um for those of you that don't know this website this can be handy once in a while like if you're trying to find the characteristics about a certain camera whether it's fume sensor or whatever that might be there's a website called vfxcamdb.com now i'll be putting the you know the the url as usual in the comment section after but in any case you can check that right now because i think it's uh it's a handy thing um when when this person mentioned this assignment yeah maybe i'm going to mention this in the show in the next show because that might be something that people uh might not be aware of and you know it's also a good technical resource i would say cool so let's take a look at all of you guys in here so we have olivia hello olivia olivia was our best guest hello leafy good to see you here as well uh luann says hello pedro i did try the nebulous really love your uh teach tech i believe it's stitch right thank you luwan luan has been um you've been correcting from wrong one but you've been like um with us like in the show from the very very beginning of the first season so it's great to see you that you're still with us you're still putting up with us that's great too that's great to to know and um thank you by the way about the nebulous i did see it just just a little bit before um you know the the live show started i did see your your nebula result keep digging for structures uh and um you know you can take this technique to other fields you know it's it's really up to you but one thing that really really helps in everything that we do i would say but definitely with nebulous because it's something that we don't see every day for sure it's to watch and see a lot of references references always on the side and all these on the side and you'll see that a lot of the things that i i've mentioned last um on the last episode are true so it's very complex there's a very fine detail there's a lot of breakup as well there's a lot of negative spaces in nebulous it's not only about color it's actually a lot of also a lot of uh negative spaces so breakup is really important and there's variations you know i've just showed you guys like a very quick as usual a very quick example it's more about the technique for you to explore you know your own technique you know it's very important and i always say say the same thing your own technique is very important more than just copying someone someone else's technique is very important to you know create your own ways of achieving what you're achieving and let's face it you know we're leaving uh some people say because i've heard this before we're living in an age of refinement not so much invention okay invention as well don't get me wrong but it's a lot of what we do is about refinement and refinement is always also to take away or take in some of the ideas and make it their your own with some differences with some things that are truly yours so yeah great great to know luhan and um thank you once again all right so guys it's now time for the tech corner so take corner this time it's going to be in comparison with what we've been showing so far in the show overall it's going to be a little bit shorter okay so we can have like this mix pro possibly um this season this mix of a little bit longer ones a little bit shorter ones but um it's more it's not about the size right it's more about the i would say the insides of the you know the the information that i'm i'm trying to uh pass to you guys and today it's gonna be one of these guys so a little bit shorter but i think you're gonna like it for those of you that are not so aware of particles we've mentioned particles in the show a few times but not like this this is very specific about what we're going to talk about and i'm talking you'll see obviously but it's about how to isolate specific particles within your simulation to better or to more strategically tweak your entire particle system so we're gonna take a look at that right now and then we're gonna have our guest it's gonna be very very interesting i always say the same thing i know of course but i'm sure you will like it as well okay so enjoy your tech corner and i'll see you in about five six minutes okay see you guys [Music] today we're going to talk about particles more specifically how to control certain particles within our particle system that we're not so happy with and possibly kill them or if you really want to analyze that particle in particular we also can do that for example i have this particle system here it's just you know whatever just to have something going here and let's say that for a certain reason i'm happy with everything but i'm not happy with this particular here so if i want to tackle this particle you know in a system like this or similar it's going to be very difficult for me to know exactly how to control this and how i can isolate this particle to tweak it in a different way or to simply kill it for example so it's actually very easy to do that and from my experience a lot of people are not aware of how to do that so let's take a look at what we have available to us to have this type of control so we have a particle expression and this is all it takes we don't need more than this the thing is we don't know how to highlight that particle what's the idea of this particle you know that particles go by individual ids but i don't know how many particles we have in here we probably have possibly thousands hundreds i don't know but this is actually the one thing that we need to have only so if you put this particle here this particular expression a way that you can instantly see which particle we're talking about within your simulation it's just put the color with the same id number so if i open the particle expression and type id this will make the color of my particles with the same value as my id number it's a little bit hard to see this though with the simulation going on with whatever effects that i have here or whatever forces i have here so the best thing to do is to unplug the particle itself and just look at you know this sprites now if i go here i know that you see i have this set to 68 which means that this color it's actually my id if i don't have this you see that this is just set to one so if i put this id i know that this particle the one this really one that i'm selecting that can be one right on top of this one or right next to this one but the one that i have the pixel that i'm selecting is actually highlighting the particle with the id of 68. so what this means is let's say that this is a particle i'm not happy with and i want to kill it what i want to do is i don't want this to be highlighted the color because i already know it's particle 68 and what i'm going to do is i'm going to go to the channels field and i'm going to say id it's equals to 68 and what i want to do with this id is to set this to none and now that particle is gone so now what this means is once you put your particle as you had before that particle that was the problematic one is not there anymore as you will see so this is with that particle killed and this one is with that particle on there is another one there that you probably want to get rid of so you can always add some particles here directly or you can create another one here to see okay i don't want this particle still which let's see which one is that it's 72 so i'm gonna kill particle 72 as well so instead of 68 i'm going to put 72. no it's gone so if i plug my particle again there now i have my simulation without those two particles so this can be very useful to control your simulation in a better way and you know although there's tools why should you use a tool for something that is so easy like this and you know if you still really want to use a tool now that you know how to do it to your own tool i think it's always a better option now let's see a different thing which is let's say that you now want to analyze what that particle is actually doing instead of healing it you just want to isolate it so instead of doing this equals you're going to say different than 68 so this will basically kill every single one apart from this one so this one is going to be now isolated you see if you want now to in just one line isolate the other one that have the id number 72 you can also do that all you have to do is to put an end statement in dcl and then copy this stuff and then instead of 68 you're going to put 72 and there you go you have this although if you want to do the opposite which is kill these two we have first of all to change this to equals like that you have to change this to or like this so instead of a hand you're gonna have an or and there you go now those particles are gone both of them in just one go so you know very easy to control very easy to look at what are the particles that you're not happy with don't forget to switch off the particle with all the things that you have available to you in terms of the actual particle itself otherwise it's going to be very difficult for you to know what is the particle id because you have the particle with transparencies and stuff like that and whatever treatment you might have in color that can make things very difficult to see but with this stuff unplugged it's very easy to see and to change and to control in these ways that we have seen just now so hopefully now you're gonna be more diligent on controlling your simulation if you happen to use particles in your workflow and how to control certain particles within your simulation that you're not so happy with or you want to analyze exactly what those are doing hope you liked it and see you next time now yeah okay now you can hear me so yeah so that was it as i told you it's uh it was a little bit shorter this time uh but hopefully it was um insightful in uh in what i'm i was trying to convey uh about this idea on how to isolate particles to better you know control your whole simulation or to take away some of these particles that are just affecting your simulation the way that you don't want you know uh of course these messes with expressions a lot of people get put away because it's just the expression now they don't know exactly or necessarily speaking how to deal with them but it's not that difficult i just showed you something very easy um of course it helps and the of course the the the the video today was not about tcl in any in any way specifically but using tcl to something more practical it helps obviously if you know this syntax wise to accomplish different things all right but i just wanted to highlight this um this technical approach to these things because from my experience a lot of people though are not aware of this and uh that was it hope you liked it alright so now it's time for our guest and uh some of you might be aware of who this person is from social media if not personally so we'll see what i'm talking about okay so let's see who's on the other side now [Music] yeah it's vlad hello vlad hello hello hello so i'm gonna try to pronounce your num your your uh last name okay hakstriski correct almost there not bad astriski very close hello vlad so good to see you so um we we actually don't never met each other personally speaking uh probably we are aware of each other i was certainly aware of you um but um i actually from the very beginning of the show i'm talking about season one i wanted to bring you in because uh the the work that you're developing on this new thing that we all uh hear about machine learning and all that stuff is really interesting and i think it's uh it's something that it's definitely changed the game uh we might not be there yet but i think we're going to be uh fairly soon but before we get into all of that do you want to present yourself to the audience i was working in films and visual effects as a as a compositing supervisor as a vfx supervisor in russia and i moved to london at some point and started working for companies like npcs can line frame store uh it was short contracts long contracts different and then we framed store i moved to montreal and worked there as a compositing supervisor and from montreal i moved to vancouver to work for mpc again as a head of compositing and now i'm at scanline and i do some automation work that's right that was very concise uh in the very short period of time talking about like three minutes or something like that you you you beat i think every guest like to tell your entire life in just like three minutes so very good yeah cool and actually before we get into that because um well as i said we we we never met personally speaking but of course i'm aware that you're from russia and uh it was quite interesting to you know understand when i was prepping this interview understand that you you know you had like uh your career developed quite a lot in russia already back then and then you decided to go to london to pursue probably different you know a more specific thing or something different maybe uh but what was the motivation because you were already at that time like a supervisor right now yeah supervisor right life just life like yes i mean sometimes work is driving work drives me to move to montreal or vancouver but uh london was life yeah yeah just personal reasons yeah of course yeah and i think it's very also important and i always say this because um because you know a lot of people that watch these shows and have these people in mind about oh he or she was so lucky because he was in this place or that place i mean you have to make your own luck you know what i mean if you if you're stuck in your own place from the moment you're born until the moment you you die and if you don't risk anything of course no nothing will will happen for you so i think it's very important um oh absolutely it's it's a hard work to find if like when i moved to london i didn't know anyone in industry so i had to improvise it was 2009. and uh what i did is i basically flooded all companies with my cvs i put it my cv by that time it was the letters accepted as well so i sent them a letter i brought a kind of like a package to every reception and i filled up online applications and uh after i did that after like two months i got the contract but i was filming commercial yeah and um kind of tried to survive you know it's it's always hard work even if it sounds easy you need to be prepared for certain moves and actions and uh always one thing that i often say and people that are in the program or people that know me and work with me know that i always say this which is you have to uh you know luck what i say is luck can turn out to be bad luck very quickly if you're not prepared because the training is passing by you know there's the opportunity there so it's the luck part right but if you're not prepared you can go you can't jump in you know you just see like the train going by and then you know it's bad luck yeah exactly oh yeah but it's all it's about life in general like how sure first how short it is actually yeah if you think about it like and if you have plans and how much time do you have to actually realize your ideas and plans or build something what you want exactly yeah definitely definitely um you you just mentioned that you actually worked in the in the big in the biggest studios in london and outside london as well and one of the questions that i'm interested in hearing from you is since you already had this career in russia what were the main differences that you found once you get yourself into because you had like you know a couple of months of like knocking on doors and bugging people out and stuff like that once you got in what were the main differences um that you found in comparison with the practices especially about practices that you left in your home country home country in terms of like how you do things how you think about things was like similar just a different country or it was like a completely different experience how was it for you well by that time it was it was absolutely different and though i started uh i started at mpc's mid-level compositor again so i had to do steps back um and that's in it my it is it i mean it depends on what you want if your egg is bigger than reality then you need to deal with your ego right uh after just first day i realized that i'm mid-level compositor and need to learn properly how to do it in a big scale yeah but again it was back 2009 now things changed since that and i think the level is almost everywhere pretty the same but pipelines organizational part and templates and documentation and structure that was the biggest difference by that time between working like back in russia and even though like everyone trying to build their approaches yeah it's just a machine kind of a conveyor system which built in these big companies yeah that's what is the biggest difference the scale isn't it the scale means a lot of different things right so yeah and in the in the end it's just a logistic if you think about like uh what we comp together all these things need to be delivered to us in certain ways sure and if you simplify it it's logistic and it was different yeah yeah i'm also asking this because um and this will be part of uh i would say the core of our conversation today because you have a big passion um you have this in common we have a big passion for tool development processes optimization automation and that's why i was asking if you found major differences on that front because not only in london you you spend some time in london which is like a big school i would say the biggest and then you moved after a while you moved to canada which is where you are at the mall you're in vancouver at the moment so did you find the same differences uh between london and canada regarding all of these things that are your passions uh or or how was it that for you as well uh you're asking about like technology so technologies uh yeah technologies uh tool development optimization all that stuff i'm not sure if you already had that because you mentioned this in in your intro that you already had that kind of thing back in russia right back where you came from originally so that's why i'm asking oh i always i always i always try just to first of all understand what i can simplify or automate uh and uh no that that never gone i mean that's a passion for like of my life life basically uh is to simplify my life yeah and now right and others and others as well because we work in teams right sure you know working with people for me is like i'd say i want as a supervisor ahead i want everyone in my team to know everything i know that means that we can do things faster and more efficient and have our life uh as humans which is a very important life's back we're fighting back right now to get lives and that's what kobe time showed us gave us this moment to actually stop brief and understand yeah for a moment understand like hey uh where am i in all of this fun as you're human i think that's that's so refreshing to hear especially from you know you've been you you had uh positions as a head of 2d as well so you dealt with many different things rather than just being an artist your obvious of course you came from an artist's background now you are more involved in tech uh all of that stuff but and it's really refreshing to hear all of that stuff coming from you know senior roles um part of why i wanted this show to happen was also because of that to demystify this type of behaviors that people think uh or or you know ideas um there are nothing but just uh preconceptions you know what i mean about these type of personalities or these type of roles or these type of journeys because you know we're all the same well we're born the same of course some of us do things differently that's why we achieve also part of the reason why we achieve also different things but it's also about like being a human being and i think there's a that's lacking a lot uh not only now in our industry but in our own industry as well so it's really refreshing to hear that coming from from a personality uh such as yourself so yeah thank you for that and i actually when we were having this this test call a couple of days ago you mentioned exactly what you mentioned now which is automation that's what's going to get our lives back and i found that so interesting do you want to expand on that i totally get that by the way but you want to explain that to the audience yeah absolutely um so basically we are like if you're looking at the moment of time we're right at the moment where automations will join us right and i don't want to join automated process i want automation help us as a human and that's very important how everyone who is involved in creation of this algorithms processes integrating them to softwares how they build them to replace human and to support human it's a two different basically trees branches we can go and it's in our hands uh of everyone basically we've started using it we've started like looking into automations how can you apply those automations to save your time how you can control them and get exact results you want to do and what i'm building at tech dash va is the basically processes which will remove routine and for now for example if i will do a little intro to our tools what we do is so we can do automatic uh king we brought our own mathematics for that and we can extract green and blue screens um automatically with a press of a button you can also do a training so that means that if our our algorithm doesn't understand your material for the for the default approach you can always train it with one shot training and for us speed is very important training on one shot is approximately one minute uh prediction is almost real time speed it's milliseconds we measuring all the statistics so you can rely on our tools and schedule some work with them in the future we also identify markers and just last week our great team of mathematicians went through break breakthrough tracking and we start doing 2d tracking automatically based on markers and some other things we will be releasing some stuff soon hopefully that's great so next week i was about to ask like there's new things uh in the pipeline for you guys but i didn't know if you wanted to disclose that or not but you just did so uh that's great and we also building our tools because i i worked in in big companies i can imagine what kind of pipelines can be and uh i'm generalizing approaches for integration so we we're ready to go like with like installing software in just a few lines of code and we are in nuke and then it's available for our entire facility and just press the button you can run templates we're releasing videos on our youtube channel yeah a vivo explanation of use cases of our technology i'll i'll be bringing more templates and more explanation because there is a lot of actually important things about automation we need to understand i'm integrating not this kind of things i'm integrating different things and controlling but what i know is automation must be under human control otherwise you will get hundred of something instead of hundred of what you want and that's a big difference that's a very i guess i wanted to talk to you about about that as well uh but go ahead go ahead sorry i interrupted your your your thought it's okay uh and so basically we need to be kind of consistent in our quality and that's what we're putting into our tools from the beginning uh we either do king or not do k either identify markets or not there is nothing in between identifying something wrong or super dissimilar so you can at least rely on this and there's a lot of other things needs to be written but apart from just uh fancy pressing button and getting result there is educational process which must happen and that takes time as well um to understand how you can fit it into your into your pipelines that's why also trying to simplify to the templates that's what artists can understand and uh from like amount of results artists can produce producers can actually look at the schedule and understand how fast they can hit some results and yeah for now what what i'm kind of like in videos i'm saying that i call it temp quality but it depends on the depends on the work you do so for example if it's a presentation which like my green screen presentation i obviously did the filmed on using my technologies uh all time so there is a lot of work which you can like corporate videos and other things we do which can be automatically done and it's it's a good thing if our clients are making money using our technology they become richer and that means that they stay our clients and we build tools for them it's a vein we're trying to build so there's a yeah that's kind of uh the ideas and things we built at tech tech va to help us not to dive amount of work and keep control over the systems sure and one important thing as well what we always do for the tools which requires controls is that it's a radius you always can change them right now in nuke if you need to you can manipulate and iterate there is no baked data but for example like when we generate that depth absolutely yes it's just generated that depth for videos which you can use for image segmentation for the focuses and some other things this technology will will build improve in in in some time anyways so all of these things will come to our life and we need to be able to work with them and have proper structured not only to run them to store material which we actually took care about as well where it plays to in your structure etc we we're working on way smarter kind of like integration but clear and transparent for everyone yeah i think you mentioned like a couple of things that i think is very very important which is not having it baked for me that's a big big big thing that we have to account for and we've been seeing some tools also regarding machine learning these days uh for example you know the the tool of the day regarding the software that we all use copycat right which has big data and i think for me that's uh not only for me for everybody if you can't manipulate and iterate or have it open for you to manipulate in real time you know that the you know defeats a little bit of the purpose of the whole thing anyway but before we get into um more specifics about this uh for for those of you that uh are watching it don't maybe vlad uh spoke a little bit too fast about what this is what this company is all about his company we're talking about tech va automated solutions okay so vlad not only is a compositing supervisor a supervisor in general because we just just mentioned that he had you know different careers back in your in your home country uh but also and people can see on the label anyway but also the founder of this um this company that uh it has like not not even a couple of years does it have like a couple of years maybe maybe just yeah we started in 2019 i presented our prototype on total cows conference in bulgaria so then 2019 that's why we prepared the prototype which we've been building maybe for like a few months yeah and you've been teasing um the community once in a while for the past maybe one year one and a half years right that's when i i was aware of yourself you know what i mean in terms of like okay this this seems a little bit interesting you know so that's that's why uh i invited you on the show to talk about this that this is not it's great to know that it's actually a full-on company it's not just like some tryouts and then interesting things you know what i mean so that's great to to to know that um yeah we've been we've been sorry to intro but i just say that for past this year some apart from just machine learning itself research and like doing a databases and all of this stuff uh we also kind of like working on building up this paradigm of automation and whatever you call it neural compositing whatever but the idea we kind of even formulated it better of how know it's communicating to each other how they can make a decision for human and what priority tools we need to build to to complete the task not to do one thing like not to only identify markers not to only keep all decay but put it together and place the ground in it yeah and make a complete task of for example temp delivery them deliveries are super time consuming in companies and there is never time for that and sometimes there's lots of simple work where i myself say god i wish i have second me and that's what uh that's what we're trying to build you have to implied you organize it there's a smart tools which control it you execute it and you get a result yeah and that's what transformation can be as well yeah it's it's about uh about all of these things that uh vlad is talking about for those of you that uh don't have this experience because the companies that you're working for you don't have temple deliveries or anything like that but that can be very tedious uh for sure and there are some you know intermediate tasks that you have to produce for you know the whole pipeline to run uh as normal talking about fg keys and stuff like that that uh it's very simple we're not looking for perfection or anything like that it's just intermediate tests but that can take a long time um and i just wanna on that point i would like to talk to you about not so much about intermediate tasks but i would like to ask what's your view on autocomp tools because i'm sure you worked with them right well um what's your view on that i'm building kind of one of them and it's not my first approaches first time i started kind of looking at after assemblies like 2014-15 and try to implement them in different different projects in different companies because they are time savers yeah and if your company doesn't have this it's going to be really hard to survive in in the future yeah because more and more companies are using these type of automations and that's how you compete uh efficiently with uh with one another right if you if you're not in the game you're losing right you're on the losing side of the game and by the way our tools are built to be integrated to those sort of systems so cool that's what's on the render farm to work in common lines it's not only gui and uh to run all these processes separately we basically like simple shocks and examples uh on our youtube channel with car where you need to pull decay remove markers it's going to take you 30 minutes anyways like to do all this stuff that run automatically two minutes with the result with the render with the request with everything that's that's actually interesting for producers can be and should be but they really need to understand that machine is not working instead of us no no it's aiding it's aiding the work that we do not uh swapping the work that we do and and that not only for produce i think that's a very important part of the conversation because you know especially younger artists that are on you know they do rototasks and more repetitive tasks in that sense like cleanups and all that stuff that can be very difficult also don't get me wrong as we all know right they kind of feel threatened some of them more than others obviously uh about like what these new technologies will mean for my job right uh and i always say the same thing listen i understand your concern but what this will happen is you'll be more valuable as a human being to do other things that if a machine can do that type of stuff that means that you are free to do other stuff that is more interesting for everybody including yourself in the in the first instance right so there's no reason i don't think for people to be threatened in any way shape or form quite the opposite because this will open a lot of different possibilities you know new things that we know we don't even know in this moment you know what i mean so yeah absolutely like on my like life example like i started from 2d animations and i was quite good we were doing amazing 2d animation commercials and films lots of things been automated and i was just not like sitting and just like collecting some money it wasn't like crazy amount but i was able to have my life that was was was very important but at some point no one really needed to do animation films i had to switch to compositing i had to switch to vfx and do all this work and learn then all other softwares which i didn't know before so don't you don't like especially like who's starting an industry uh i'm i'm not saying that they don't need to worry about anything they just need to be smart they need to be prepared they need to learn that's what i said in siggraph 2018 on foundry panel uh where i said come on people we just need to learn more things every day uh like i learn every discipline around like including effects and lucky i don't have time to do that but i know how to deal with unreal how to render out passes from multiverse like from omnivores for example nvidia and to not passes but renders like and how to deal with all the usd formats because it's actually not interesting it's boring as hell uh because i want to receive a result i want to i know yeah i understand yeah and thus steps for me i want to remove them i want to manipulate images i know what the photorealistic image is so if you think from that point of view like what is your target what are you actually doing what's the end game right what what's removing markers exactly what's really the end game what what are you because you know let's not forget that these tasks not only they need to to be done obviously a lot of people i would say i would risk just to be on the safe side i would say 70 of people don't like to do them okay let's say that 30 percent of people they actually enjoy doing them and that's a great thing because we need these people to actually enjoy what they do but the great majority of people they find these tasks boring in any case it's a way for you to get into the industry and people normally uh they go through that path right maybe when we were starting out that was not the norm because we were doing a little bit of everything like including those but not only right but um yeah um the thing is if since we're talking about the majority if the majority of people can't skip that to actually be more valuable like bringing the human value to the picture rather than just like repetitive tasks i mean it's a win-situ a win-win situation for everybody including as i just said for the person for the actual person or persons that are actually doing the job right in first instance well absolutely just like to to say what about all this rotter prep work uh absolutely horrible and hard work to do i mean honestly for people like who don't like it it's uh it's difficult uh i have lots of respect to these people and also like from business perspective it's quite good business because you don't have creative comments on marker being removed it's either removed or not removed you don't need to paint it to bluer or to whatever so you can basically calculate amount of work and money you can do it's not predictable predictable in that sense right predictable yeah so and some people do love this work and uh some people just run businesses on it and it's great they have workplaces and they do what we need but yes when things are can be done automatically it's time to move on to something new and you absolutely write like i'm dealing with image analysis in different aspects of it like creating different type of data sets and working this is so many interesting information we can find an image which we basically don't have time yeah yeah yeah and or maybe we don't have a pin holes to look at something super specific and get some gain some knowledge from it new things right sure move on to new effects new way of storytelling and new kind of visual effects and yeah leave leave all these things after what can be done automatically to the machines that's what i'm saying yeah in our slogan leave routine to machines that's what we're offering yeah i saw that too yeah that's exactly right yeah but listen also as um you know from the supervision point of view what we do and uh this is if you can't consider if you guys want to consider this a tip go ahead um it's not meant to be a tip it is what it is but you know part of the the way that you get noticed in order for you to get into supervision roles whether it's like all leadership roles it's called it like this whether it's leading or being a supervisor is exactly to think about systems like this think about optimization because you're not thinking only about your task your shot you're talking about you know a more broad picture it's about the big picture it's about a team it's about the company it's about the show not about this shot or that shot that is in in your play yeah that has to be done as well but the way that you also get notice is try to find solutions that are rip that you can replicate semi-automatically or fully automatically to other people you know i mean it's a win-win situation for everybody and that's how you get noticed how you do that well learning python i would say it's uh it's a big plus uh as i said many many times when i was starting with python the documentation out there was almost inexistent to in terms of the api and all that stuff for what we were doing these days is quite different so take advantage of that and the fact that we are leaving this pandemic and probably fund yourself out of a job that's unfortunately obviously but you can take that also as an opportunity to learn all of these things that once the industry is back which is the moment right now now you can offer more that you could before you know what i mean so all of these things i think it's very important and the way that you get notice is to think about it's of course it's not the only way it's one of the ways think about the more broad picture more like high level kind of uh like an eagle-eye kind of a view rather than just like your little shot your little task you know can be very important for the whole show i'm not i'm not saying the opposite but you know this is a business it's not about just that so if you can help the business thrive of course people will thank you and probably will think about you in a different way well absolutely absolutely i also want to add to that is it is very important to put put attention to standardization and normalization normalization for data whatever utility passes you receive whatever your lighting is doing how you're building up scenes and layout if it's normalized you can process lots of shots simultaneously if it's not it's a nightmare uh second thing but like also important is a standardization naming conventions for templates for all of this structure of reviews uh dailies how the comments are coming back in what format and what structure it sounds a little bit robotic but thus things actually in my opinion need to be standardized and under control so we don't spend time on those kind of broken communication misunderstanding misinterpretation of of feedback as well as like if that is consistent as i said you can just process lots of things yeah and naming conventions oh that's that's that's very amount yeah i'm talking about naming conventions all the time that make your life easier your creativity is not how long you actually building up the script it's not even a template it's the result yeah probably all right that's what we see uh and what is inside as simple as possible yeah and as automatic as possible in my opinion couldn't agree more couldn't agree more and people that know me and know the show for now we're talking about like already the second season i've been saying this you know for so long that it's great to to have i guess saying basically the same things in a different way because talking about different person obviously so that's great but uh tell me how in terms of like this data science more specifically how did that journey started for you because uh as i said also in the show uh there was a time in which addition from vfx to data science i didn't uh and now we have all these new tools that are based on data science which is like a very broad topic anyway so how was that for you that journey um oh that was interesting basically my first test was on i think it was 2015-15 i don't remember i was i was looking into deep dream and my friend who is my partner in development as well he uh he sent me a few things uh for my mock uh we set up docker and we set up some stuff and it stopped doing some whatever hallucinations on this deep dream with crazy dogs and eyes i looked at that out here okay so uh i won't actually get a character from it and that was probably the beginning so i took the footage i filmed i filmed the footage in in the mountains here and uh run it through deep dream it did some hallucinations i extracted something what looks like a character and content back to that and like okay that's interesting that's crazy it was looking really strange uh but what else can i do with this and i start reading uh on conferences before hobbit i was going to russia every year once or two times uh to to the ucg event it's a russian conference and there's a lot of topics there about machine learning and all these things and i started looking uh into that and in some pictures work i receive a a book which was from uh i think sam petersburg technical university and about machine learning and that science i started reading it and like okay so we can connect things out of connecting things take one technology another one put it together yeah something doesn't work change it but i don't not saying i don't care about technologies they are important but what kind of technology to use it doesn't matter when you're building a prototype and i started building prototypes and then it was just like going deeper and deeper into the research and reading reading githubs reading everything and but i in in our development i i spend most of my time on like front end python and what tools we built and what do we need to receive as a result uh i write first prototypes and then we think about data uh how we're gonna build these data sets and what they need to have there's i had to write a lot of automations to deal with data science yeah even to create automated tools there's a way more automations behind otherwise i wouldn't be able to sure sure yeah i think that's clear actually and i find i invite everyone um to watch uh the the the company's youtube channel in which there's a not a lot of videos but the ones that are there maybe you're talking about seven or eight of them right and then it's a few of them but they're really interesting in that sense and uh one thing that um it's clear or it was clear for me was the fact that this is not one node and then you just click and it does everything for you now you have to integrate this into already a system this is just like that boring test of that system that you don't want to do because the machine can do for you you know what i mean so that doesn't swap again that doesn't swap or that that that doesn't take away the human factor it just enhance enhances it by just uh automate well you know this this let's call it boarding tasks you know what i mean because they're repeat the repetitive that's only because of that that i'm calling it boring right well yeah the whole paradigm is to automate compositing i mean yes to automate compositing uh because they will just provide us results what we create is in our hands of templates in our hands of the final target and goal uh well i can't wait to start experimenting with our tracking uh system because we might be able to connect it to unreal as well we'll see it it really depends on resources um we can go because there's so many there's so many avenues that you can take these things isn't it it's like unbelievable you start here and then you have like you know god knows how many branches that you can do yes well i honestly this is interesting that's kind of reminded me of one thing which is i think very interesting for the future if you look at all this machine learning and image analysis mostly it's built by programmers who deal with images as as a references of data sets whatever parts we compositors actually know what the photorealistic results are our brain working super well with pattern recognition with different kind of uh analysis and expertise saying that doesn't look organic in this area we have this knowledge which i believe will help us in the future i mean in general humanity to build more accurate data sets for something something important something where details are important and we know what to look at as well yeah i mean science like in terms of medical side of things of course that's very important when you look at a an image of whatever and this is quite one of the the most common examples when people are trying to explain what data science is or what machine learning can learning can do for for us as human kind you know you know the medical part is always one of the things that people are really you know they can relate to that right uh because you know if you have these days just for people to to understand what i'm saying these days when you look at an exam a medical exam it takes the expertise of the doctor to look at the exam and to interpret that exam right okay this doesn't look good or this looks weird or we should look more into this this or that but that's just one person per one patient right uh at a time if you have machines you know trained with with the very big data sets to do that analysis in seconds for thousands of of patients you can see the benefit right i think everyone can can understand that and this is always one of the most common examples that uh you know when you found information about data science in general or machine learning more particularly to what you can do to us humans people can understand this quite well so you can transpose this type of example to whatever you do in life you know what i mean so if you can automate all of those things you can if you can analyze more way more in a way more that no human could could possibly do that leaves us humans to do what humans can do instead you know what i mean so i think that's so important and for me it's very clear actually well yeah and you know like also like dealing with with that sense we need to understand responsibility so if you're building a medical grade a military great technologies it's a one it's a one thing when machine learning is getting integrated in something where it's making decisions if human guilty or not and the system relying on that that's scary that's scary yes that's scary um there is there is a lots of basically as well like dealing with all this automations i see a lot of bad ways bad ways applying machine learning for sure that that's what is like can be lab just on the human aspect like well what is your moral principles are they allowing you to do that or you just don't care uh yeah it will be in front of someone at some point um it's up to them probably uh speaking of which that there was one time not that not that long ago um elon musk which uses a lot of these things in whatever he does uh machine learning you know in many different ways obviously cars space whatever you name it right um it was actually defending that we should have a commission that regulates machine learning technologies exactly because of those reasons that you're talking about and it you know you would say or you could think like oh this type of people or this guy surely uh is on the winning side so he doesn't want anything to be controlling it doesn't want any anything any commission or whatever to control you know the things that he can explore with that type of technology but it's actually the opposite because you know you know if you pass a certain threshold you you lose control a bit you know what i mean and that's why he seems like really concerned generally concerned about like we need to have like some sort of you know commission or i think he mentioned commission to to actually regulate you know this type of stuff in the same ways that we have commissions to regulate other things you know i mean whether it's energy or whatever that we do these days you know equi is very strongly of defending regulation for machine learning and yeah i think we can understand it it is it is it is very important it is very important to uh to do something to do something regulated or at least maybe having a hub where like hey guys it looks like we found something dangerous and scary um i might sound like from sci-fi movies but like imagine if uh if you were watching images with kittens but you're experiencing absolutely different feelings and emotions something different been planted and bring some cognitive dissonance to to to what you see that's scary as hell yeah uh and looking at what actually uh research is trying to do with with the ways like with waves like sounds and uh bringing into the focus and all these things that bringing us to the not if not mass control things for the for the video but similar to that there's a lot of things about humans research recently and like depression uh you can be sick with depression from other humans because of the uh of the waves uh of the yeah so that's already research is uh proving that so if you can find that if you can generate a wave so jesus christ like i even don't want to know what kind of world it's been yeah yeah it's it's scary and uh for sure i understand the need of uh regulating this these technologies in the same way that we have with others so this is no different actually we can argue that if we have in others surely we need on this one for sure right so yeah it's it's one of those things we will see what likely in early luckily we're in early days but uh about like using machine learning and visual effects uh like going back to industry i want to say that we need to not maybe now but at some point just figure out it will be a question okay so we using machine learning generalizing knowledge to whom this knowledge belongs to that's a more philosophical question isn't it that's uh that takes us to very very good questions yeah but uh again there's no blame should happen we just need to figure out figure out the uh the smart way kind of understanding what is generalized knowledge what is your personal expertise put it into that generalized knowledge and it's not a question of today or next three years or whatever but after that on a big scale it will be kind of noticeable yeah uh and we discussed with some some some other companies who's working in blockchain for example smart contracts and all these things connecting all these things together but that's uh not like even my my area uh of expertise it needs to be global thing we need to sit together and discuss this ways one of the discussions regarding that um that type of issues is for example when you train the model and you train this model in a certain location uh in a certain machine whether it's local or not local can be in the cloud or whatever you know there's obviously concerns that we take we have to take into consideration about like the intellectual property that training does that belong to the company that hired you does that belong to the company that designed the model to whom that you know that it's one of those things that a lot of people don't think about and but this is definitely one thing that uh you know people of course people that are in the business of course they think about these things and they have things in place policies in place for that for sure but you know this is one of the things that most of us don't think that much uh because we just push a button and the result is there but let's not forget the fact that you're taking an image that has a certain copyright to something to be trained outside your work station no we we we uh we offer like for companies we offer enterprise solution which is uh allowing like work inside yeah i'm not talking you know what i mean yeah but there is a way generally i mean yeah but there is a way so like for example we're not transferring images either we we preparing some some some array uh and uh just enough to analyze uh and give a correct result because we don't want to deal with it uh and it's a standards indicate the standards and uh we we care about this uh in in this in this way so for those of you that don't know exactly what i'm talking about me and fled we're talking about about this ip possibly infringement because of data science there's actually i believe it's on foundry's website there's a section there only regarding machine learning in which um there's at some point these type of discussions going on as well and what's what are the current practices regarding these issues that we just mentioned uh right now so i think it's a good read for those of you that like to know a little bit more about this i think it's a good read for for for you to continue your education in this technology that without a doubt it's going to be you know the future it's some at the moment already some things as for example what flat is doing with tech va some things more applicable in more specific things but it's definitely the beginning it's just the beginning and uh one of the things that i would like to ask you about also vlad is what are your thoughts about you know foundry obviously just released the copycat right which is you know a tool again in the beginnings in the beginnings of this whole machine learning applied to what we do but for me the biggest downside is the fact that it's baked you know so if you if you can't open the result for you to further tweak it you're just like relying on luck like okay i'm gonna train this model for 12 hours or 20 hours or whatever you know that might be depending on the task and the length and all that stuff you know you pray for the best but if things you know don't go exactly as planned which is probably the norm if the data set is not big enough you know what i mean you are gonna you're gonna do you're gonna have to train again you know i mean and hope again for the same result so i think it's very important for these tools to be open in the way that you can iterate them manually if you need to if you don't need to you know it's good for everybody right but uh but that's that's not probably what's gonna happen most of the time so i would like to to hear your thoughts about that because you just mentioned that in the beginning of your presentation about um the company your company yeah sure well that's why we built everything we what we want to control uh we don't do bike data because it's a cake and i can't do anything with this cake if i need to change something that's a good way to put it yeah exactly yeah it's a baked cake yeah um well there is a certain things uh as a for example like guns and style transfers right uh like what this copycat is is like that similar thing uh it's the how this algorithm been built and what it can produce and i think i think it will evolve to something different and when it will allow us to make hallucinations in real time on gpu audio optimization which that's a hallucinations right of neural network um and even even though for example i'm building experimental tool okay i'll i'll talk about it it's an open source i just took one of the guns and clip i to text recognition and you can type and it will start doing some hallucinations for you it's not a tool which we can use at the moment but i brought hell lots of controls basically everything that i can control from requests uh to manipulate that and it's there is a possibilities uh i'll i can't show you now but i understand i'll send you better like the way how we can compare approaches uh and for example in my approach is like you can run a sequence and you can hallucinate on every frame of the sequence any amount of hallucinations uh and compare them them and just see what results you can get but it's guessing in the future those algorithms need to have need to change and it will be different type of algorithms um i'm pretty sure uh i don't want to say many things of what we understand kind of thinking because it can help to kind of step on a path and now it's a fight exactly yeah of course a fight yeah no totally get it yeah some things will be possible but for now like big algorithms all these big data sets are possible like uh to be created by big corporations open source open source community uh that is kind of the stopper for more experiments uh on algorithms themselves uh because quite a lot of papers it's just a variation of that paper this paper and that thing and we just put some transformers or something else there and we like as it's lots of jokes in uh machine data science communities machine learning about like oh yeah we spent 10 million dollars on that and we do it by 0.1 percent more accurate exactly that's the fight isn't it but that's the first time we're at this time where a lot of things needs to be researched that's why like i see the big companies they do big steps like okay just broader picture yeah okay we can look into this area of uh data analysis great we can do this we can do that as uh i'm considering me as a small company who's developing machine learning but based tools we're using some of this knowledge which they're sharing with us and we can put lots of things in our way and that's what one someone will do something new new approach new combination of algorithms and maybe we'll get something what you want but it really depends on the task so maybe first it's really figuring out what we need to do and maybe we don't need generalized tools for that maybe we just need a few different tools a few different approaches to to build what we want and rely on it yeah sure it's never one thing it always will be combination of yeah of approaches yeah and that's and that's actually how different companies uh will win it's uh because that's basically what we have at the moment you take this idea of that idea you combine them together you join other things that you have from your past that can be even unrelated with those two you know what i mean but that's how you know new things are born uh these days because a lot of things that's i forget of that a lot of these things are already invented so the time now is to you know refine as i just mentioned in the intro of this episode refine what we have in a different way like it's mixing and matching combine different things combine things that are not even related with each other to come up with the true unique thing you know what i mean based on things that already exist that that's the fight yeah for sure oh yeah absolutely it's always evolving like if you stuck to if it's a company which stuck to one algorithm um it's the end of the company there's no point doing it [Laughter] there you go guys um we are over one hour way over one hour actually guys if you have any questions uh people are super quiet by the way today uh they're they're like listening to us like uh like i'm i wanna i wanna believe that they're so quiet because they're really interested in what uh you were saying vlad uh they might be shy also they might be shy also but guys if you have if you have questions please type them down so we can read them yeah you're about to say of automation it is a hard topic i'm trying to find the correct words to explain explain that as well because sometimes like oh you can do that automatically wow okay why would i need that uh that's well listen we already we already looked at many different examples of why you want to do that you know what i mean there's there's a plenty of reasons why everybody would like to have that in their lives you know what i mean of course listen i'm not gonna take away the fact also and i think this is also important to to talk about which is every time that there's like this big disruption in technology of course the world is gonna become better in medium term of course you know on the short term that can mean also some disruption for some people right so that's why i think it's also important to adapt to learn new things to embrace these things so you can also be a part of that new change if you don't want to learn if you don't want if you want to stay exactly the same way that you are 20 years from now 10 years from now 40 years you if you don't want to do anything while the world is changing and you don't change of course you're going to suffer you know i mean so i think it's also very important to not look at these technologies because we have many many different uh examples throughout history human history in which things evolved you know what i mean now we have cars there was a time in which cars were not existent you know i mean planes you know you name it you know what i mean dishwashers you know all of these things that can mean like great things for us as humans right but you have to adapt uh to these things and of course evolution technology-wise is never linear is exponential and of course you know older people will have a more hard time to adapt in comparison with younger people but in any case um and we've seen this in many different examples in in history you know we have to adapt our lives to these things and not to be concerned all the time without doing anything about it you know what i mean so i'm not taking away the fact that you know it's going to be all bells and whistles like it's going to be all fine for everybody from day one of course there will be some casualties if you want to put it things like this but i think all in all it's going to benefit everyone you know what i mean so um it's important also i would say to have this in mind without forgetting also that there are people that you know there are in countries in which technology is not as accessible as as we have it in our lives for example but you know we have to do what you can you have to do what you can and you'll see that if you do what you can but really do it you know the road will open for you slowly but steady oh absolutely you're like starting from from python for example lots of people afraid learning python yeah listen listen guys just so if you just type import nuke and type print hello put your name and press enter you're not launching rocket okay you uh doing a simple loops a lot of automations in vfx and routine can be fixed with a few loops and couple of conditions and your life even with that will become easier a hundred times yeah on some tasks for sure that you don't you're not launching rockets i mean if you're in a studio environment just please be careful but if you're doing it on your own machine and you're not impacting infrastructure no one's going to be harmed and you can fight as much as you can as much as you want and be creative there is also no uh one way to write in python it's a lot of different ways you can write approaches and it will tell you if it doesn't understand what you've wrote and now ai came in uh and helping call coding with you but you need to know what you're doing i mean always in films and everything what is your goal what is your target i think we can't top that so i think we're going to leave that here vlad with those with those words i just want to say something which is um next week you you can have a talk with foundry right about va right so for those of you that would like to attend this will be on august 26th is it is it yes so august 26th so if you'd like to attend you can go to tech va linkedin page the invite is there like the page in which you can register yourself is there you can also go to foundry's website for sure and i'll be putting uh the link also in the description of this video later on so you have all all the possibilities for you to attend if you if you wish to uh this is going to be again august 26th so next week okay it's going to be yes wednesday if i'm wednesday or thursday right thursday it's thursday yes so it's a week from tomorrow uh and it's gonna be interesting because a lot of things uh we already touched uh today uh probably vlad i'm just guessing i don't know because vlad didn't disclose anything special for me regarding what what they're gonna talk about but i'm sure they're gonna talk about more specifics so if you'd like to attend uh these are the ways that you can do that there's no questions from the public people are like really really interested in in the conversation as a conversation uh maybe they're scared about asking questions i hope you there's no there's no stupid questions there's no stupid questions i mean there are some but there is no stupid questions about things you don't know it's fine to not know something exactly exactly that's all is what i say to people as well so but since there's none uh i hope you have more uh more luck next next week with foundry okay vlad but thank you so much for coming in uh it was great i would be here for another hour for sure uh but we don't want to bore people so uh we get the link we gotta leave it here and um yeah see you soon i guess nice to meet you by the way yes and uh great show though amazing you're doing great work ex like explaining people what's going on it's it's needed for for all of us cool thank you so much vlad uh please stay on we're gonna see each other guys in a couple of weeks maybe a little bit more as i said in the beginning uh but i'll keep you posted uh in any case i'll see you next time all right glad thank you once again and bye bye everyone let's stay on because we're gonna have like our final set yeah all right bye guys see ya [Music]

Channel: Comp Lair

Views: 442

Keywords: comp lair, the next level, particles nuke, nuke particles, nuke particles tutorial, nuke expression, nuke expressions 101, nuke tips and tricks, vfx, live show, advanced compositing, advanced nuke, nuke tutorial, nuke advanced tutorial, 2d supervisor, compositing, nuke particles expressions, nuke, maths, foundry, hugo's desk, vfx guru, marvel, dneg, ilmvfx, framestore, cinesite, milk vfx, mpc film, pixomondo, trixter film, Rodeo FX, Digital Domain, rxpvfx, VFX Geek, Vfx geek

Id: uxS6wAEEnFU

Length: 90min 34sec (5434 seconds)

Published: Thu Aug 19 2021