Hi, how you doing? This is Rich from Mississippi Live, and it was another crazy day in the markets again another bloodbath Overall in the cannabis sector again Canopy growth got hammered today a roar was down again I mean, we're just seeing blood everywhere on the streets in the cannabis sector but the silver lining In my opinion was that cantrust Out of all the stocks that should have been read today Cantrus was green Not only were they green at one point.  So it's nice to see Suniva have a nice day and Halo labs Nice to see Halo labs having a nice day told you guys Halo labs 9.6 million of revenue just did a deal with Kaleeva. I've been interviewing the CEO and talking to him tons We're talking about like a 30 cent stock in Canada and These guys are in the extraction space. They're in the CBD space. They're working with Kaleeva who's doing a deal with Jay Z No, brainer 9.6 million in revenue 9.6 million in revenue and they're at 30 cents in Canada. I Think it's a no brainer. I think Halo labs is a great company. I think they have huge upside huge potential Like I said, this entire sector is beaten down. I don't think you can really understand why I mean everything goes red and The company who gets their license suspended goes green How do you explain that? I don't think you can explain it. This entire sector is highly manipulated. I Think cantras going up proves it. I mean This company this company gets their license suspended and the stock goes up Cantras has no sales no revenue the Alberta gaming Company returned 1.3 million dollars a product and Cantras stock goes up Halo labs has more revenues than I IPR I IPR was trading at $97 last time I looked and Halo labs is trading at 30 cents and meanwhile they have more revenues than I IPR. I don't think very much in the sector can be explained This sector is crazy. It's absolutely crazy Nothing can really be explained. There's really no real fundamentals to determine where these stocks can go and Yeah, man. It's a it's been crazy, man.  I IPR is at $97 with less revenues than Halo labs, which is at 30 cents How do you explain this? What I can tell you is one of our members on telegram e-dog brought us a pick and I'm gonna break it down for you guys So you guys can learn more about this company because he brought us this pick at 18 cents today hit 22 cents So it has been climbing and he brought a lot of good reasons to our community as to why He thought the stock was undervalued Under-appreciated under exposed the stock has been going up in the cannabis sector tight float Strong management team and board that they're building behind the stock and they're still at 22 cents So I'm gonna do some more research and I'm gonna bring the stock to you guys later I'm literally just driving just did an interview with a cutie ads. Oh my goodness 100 million dollars in revenue dollar 30 stock and I just interviewed the CEO Stay tuned Is your boy rich remit to be live if you're not winning you're not watching we bring your winners and we bring them to you first Yes, the cannabis sector is heavily under attack heavily heavily heavily under attack and We see a lot of red everywhere, but this is a buying opportunity For those that want to win in the cannabis sector in order to win you want to buy low sell high Right now we are seeing the entire sector under attack. It is a great buying opportunity We're seeing 52 week lows across the board the key right now is to do the research spend more time doing research Looking for the best looking for the best looking for undervalued underappreciated under exposed opportunities Buy them at 52 week lows position yourself now and wait for the resurrection Because when the resurrection comes it's going to be epic and Those of you that are patient and that are getting in at these lower levels are going to win big It's true. If you want to win, this is the time to get in man Because we're seeing 52 week lows across the board all over the place We are in a sector right now that is very news driven. It's retail heavy It's short heavy. It's market maker manipulated and it's news driven article comes out saying that Aurora cannabis is Overvalued stock goes down article comes out saying that canopy growth is going to be Building tons of debt and is not going to be making any revenues Stock goes down. We are in a news driven market There are no fundamentals backing anything right now because you got stocks like II PR trading at $97 with less revenue Then halo labs, which is trading at 30 cents Then you've got Aurora cannabis trading lower than a lot of their peers But yet they've got more revenues than everybody else in the sector This sector is crazy The sector is volatile be very very careful when you invest in anything in the cannabis sector Do not invest in anything that we talk about on our show Invest in the company because you've done the research you've done the diligence and you believe that that is a great investment our modus operandi here is to bring you educational and entertaining content So that you can take that information digest it Research those companies and hopefully you can make your own decisions about which companies you want to invest in We are really growing. We're getting out Of just the cannabis sector and we're starting to get into every sector so you're gonna see us interviewing CEOs from every single sector in the world and Our goal is to be able to educate the public about every single major public company Before anybody else on the planet that is our goal and we will achieve that goal Thank you guys for watching if you're not winning you're not watching is your boy rich reverse to be live Bring your winners and we bring them to you first halo labs big day Saniva big day and can't trust Green day to grade it to green days in a row for can't trust who just got their license Suspended apparently now if you want to go green all you got to do is get your license suspended. It's true Obviously, I'm saying that tongue-in-cheek. I'm just kidding anyone that's invested in can't trust congratulations on Them going green even though they just had their license suspended. I hope this continues It's definitely a bullish sign for the sector even though the sector is deep in red It's buying opportunity folks. You heard it from your boy.  I'm a piece


Hannah Ash and now we do indeed bring in Kara Yeruso who I hope brought her dancing shoes to this post-game interview You're gonna show what's your go-to. What's your go-to tic-tac dance? We got to see it Oh, I don't have like a go-to dance, but I like to do like the fast-speed one So I'll put it like slow most and then it looks really fast when you show me something Come on Hey a hundred career points. Congratulations. That's an awesome number. I know you have bigger goals I know that are things that you want to accomplish that are more significant than that But what does that mean to you to reach that milestone? It was super exciting I think what was more exciting about it was I didn't really know what was happening and neither did anyone else So like it was super cool like seeing everybody like cheer for me because it really goes to show that like we really are like a Very close-knit team and everyone cares about each other. That's awesome What coach was talking about obviously, you know, you and I've talked more before about being an all-around player But that that defensive effort that you guys put in the day and you At being such a huge part of that and being you know someone that everybody else taking their cues from how important was it for you To lead the charge that way. I think it was super important Especially like towards the end when they were face guarding I was like in my head I was like I just need to play really good defensively because I knew that obviously I wasn't going to be as big of a factor offensively but We played as a really good as a team today, and I think everybody just had their backs on defense now calling plays Is this something you've ever done before I mean usually we repeat it, but like I don't usually have to actually call it Okay, so talk me through it. What was it like? What was what did you learn from going through something like that? And do you feel like it's something that you can do moving forward? Yeah, definitely I think it's like also as you're playing what feels good what plays are working a lot in the beginning You know, we know the ones that we like to run during practice So I started with those and then as I was kind of out of the play I was just kind of getting a vibe from the other girls and seeing what they wanted to do So did they ever criticize you never say like care what what was what was that that was that was all no That was cool We talked about it obviously disappointing lost Wednesday, but a nice win today What what's the message from you to the young players on this team knowing what's coming up this coming Wednesday in a huge matchup with Messiah I mean I think a big thing that changed from Wednesday to today was everyone played their roles And they played their roles well today, and I think that everyone You know realized that they are a huge part of the team in a different way And today everybody stepped up and did their role well That's what you need moving forward. All right, since you won't give us a tic-tac dance. How about instead go to karaoke song? I like want to be my spice girls You weren't even born then work my older sister loves that song. So like it's just like on repeat Any chance you give us will you give us will you give us any bars at all? Carriers anybody else that you didn't shout out last time you need to shout out this time My sister's Kelly and Chris that couldn't make it today. So shout out you guys and thank you the rest of you for coming Hey, congratulations. Not only on the milestone, but a huge win. We'll see you back here Wednesday. All right Yeah, that's carry a roost. So I'm Glenn Clark. This has been go mustang sports TV


Good morning. Good morning, ladies and gentlemen. Are you getting ready? Can you hear me? Good morning. You're very welcome on this second day of our conference and for the second keynote speaker, Professor Sharon O'Brien. I'm not going to spend a lot of time introducing her. I'll just say that we're really pleased to to have her here as a keynote speaker because she really represents a vibrant part of our profession and our academic field. Sharon comes from Dublin and she works at the Dublin City University in the School of Applied Language and Intercultural Studies. She's also director of the Center for Translation and Textual Studies and I think you all know a very good book on research methodologies in translation studies that she has co-authored with Gabriella Saldana. I know that Sharon is also working on a book called Interdisciplinarity in Translation and Interpreting Process Research which is perhaps an even more vibrant research area than the ones that we've heard about so far. So I'm very pleased to give the floor to Sharon. Can everybody hear me? Yes, okay good. So we have a new microphone this morning. I think it's maybe a little bit easier than yesterday to hear. So first of all I'd like to start by thanking the committee who asked me to be one of the keynote speakers at this prestigious conference.  I was asked in the invitation to be a keynote speaker to talk about translation technology because that's an area that I work in quite a lot. But also to touch on the theme of the conference which is moving boundaries. So in the next 40 or 45 minutes this is exactly what I'm going to do I hope. So how many of you recognize the picture on the screen? Few people? Great, a lot actually. So these are dongles which are hardware keys as you know for software programs. So like our USB sticks these days where we stick them into our computers we used to stick the dongles into our computers and it would provide us with the license for the translation memory tool. So this picture represents quite an innovation in translation technology and quite a shift I think in translation process and in the translation profession which I would like to talk about in a few minutes. But first I also want to share with you the fact that these dongles also personally represent a major headache for me because when they were introduced in the beginning I was working in a language service provider and my job was to introduce translation memory tools to highly resistant translators and to document the processes in which these translation memory tools would be used. But also to post by snail mail the dongles around the world to the freelance translators who would use them. So that was quite a headache but it was also a headache when they wouldn't work and I had to troubleshoot why would the dongles not work and even more difficult was getting the dongles back from the resistant freelance translators who didn't want to use them in the beginning. So it's an interesting image but it's an image of positive and negative I think. In what way do these dongles represent a shift in translation technology and in the process of translation? Well first of all in the translation profession with high volume and repetitive translation translators no longer had to use something like Microsoft Word compare feature to compare one old source text against a new source text and cut and paste the translation that they were working on already into the new source text. So the translation memory tool would do that for them. So a slight change in their process. Translators also now had to deal with different kinds of source text to a large extent. So they had the source text, the old source text, the new source text and then they had the match from the translation memory that they also had to look at. So now in terms of process they weren't just translating but they were also doing cross language evaluation and comparison, acceptability decision-making based on what the translation memory tool suggested to them and also editing in the translation process itself. Some people have argued also that the introduction of translation memory tools forced translators to focus more on segments of text rather than text as a whole. So that has had an impact on the process too. In terms of the profession then computer aided translation also has had an impact. You could say that translation became more collaborative as a result of TM tools or perhaps more derivative because translators were now using other translators work on a daily basis. It also meant that translators no longer had to be experts in content management programs like Framemaker, which is quite difficult to master, that they didn't necessarily have to understand SGML or HTML. But on the other hand, they had to become experts in translation memory tools and they had to become experts in handling tags, which is still an issue for many of the translators these days. The price or cost of translation was also affected by the introduction of these tools. So there was a significant downward pressure on the price of translation and at the same time a significant increase in expectations regarding productivity, throughput and also on quality. So it was expected that translations would now be higher quality, at least more consistent thanks to translation memory tools. So they had, I would say, quite a significant impact on on the process and the profession. Now when we talk about translation technology, sometimes people say to me, well, you're only talking about the small translation. So going back to Andrew Chesterman's talk yesterday, what do we include in translation? And translation technology is sometimes seen as only small translation, so not that large concept of translation. But at the same time, we know that many, many translators use these tools and have to engage with them. So it's not an insignificant portion of the translation profession. In fact, in a recent survey by one of the language tool developers and language service providers, where they had almost 3000 responses across 115 countries, 83% reported using productivity software, which is a euphemism for translation memory tools. 68% of these were freelancers. And other surveys that have been carried out on translation technology usage demonstrate that a lot of translators have to engage with this technology. So after the initial introduction of computer aid or translation tools and the shock to the system, we could probably say that the aftershocks have now ceased, and that these are firmly embedded in a large portion of the translation profession. Yet there's a lot of research quite recently even that suggests that translators are not altogether happy with their translation technology. There's also some evidence to suggest that the developers of these tools have actually started to listen to the fact that translators are not always happy about the tools that they have to use. That's something I'd like to come back to a little bit later. But sticking with major shifts in translation technology, I would say that another shift has to do with this concept of data. So with the production of translation memories over a significant period of time, something very valuable was produced for computational linguists. So that is big translation data. Suddenly after years of struggling to some extent with rules based machine translation, translation memory data allowed computational linguists to apply probability formula and statistical machine translation or the data driven paradigm emerged. At first this idea of generating language through numbers was not received very, very warmly, as you can well imagine. But it quickly became clear that statistical machine translation could improve quality over rules based machine translation in general, at least for some of the language pairs, for some domains and for some types of text. So after years of happily ignoring the elephant in the room that was rules based machine translation, machine translation suddenly became something that linguists translators had to pay attention to. I would say that nowadays machine translation is not necessarily the elephant in the room. Many of our professional translators and our translation students see machine translation. It's very visible to them. They know about it. They know how to use it and they interact with it. Potentially machine translation could be seen as just another tool in the translator's toolbox, along with their dictionaries, their online glossaries, translation memories, parallel corpora and the web as a corpus. So machine translation looms large, whether we like it or not. And for some, for all, since it has been introduced in a more usable format, let's say with statistical machine translation, we as educators, researchers and in the profession have tried to differentiate machine translation and the revision of machine translation called post editing from everything else that is translation. So I mean translation from scratch or pure human translation, revision of human translation or revision of translation memory matches are all put into one box over here and machine translation post editing is put into the other box over here because it's argued that that is different from translation and it's different from revision of human translation. But I'd argue that the boundaries are becoming very blurred now between these two things. So let's think about why that might be the case. Machine translation systems are built using human generated translation memory data. The post edited machine translation is now added to the translation memory. Machine translation is integrated now into all of the state of the art computer aided translation tools. Sometimes the translator can choose between a fuzzy translation memory match and the machine translation generated sentence. And sometimes the MT is actually better than the fuzzy match that's available. And your fuzzy matches can even be repaired to become exact matches using sub segment machine translation. So the two things of post editing and everything else that's done with machine translation have started to really merge together. But getting back to the elephant in the room. Statistical machine translation has encountered a problem. We have techniques like cleaning the translation memory data to make it cleaner, more consistent, tuning the machine translation memory data to make it more specific domains and automatic post editing rules that make machine translation quality better. But at the same time, just as the elephant in this room has hit the ceiling, statistical machine translation, it's argued, has also hit a quality ceiling. And it's very difficult for it to break through that quality ceiling. Especially for morphologically rich languages such as Hungarian or Finnish, for languages for which there is not so much data, so not so much translation memory data to be made use of. And for translation directions that are less common, I want to say. For example, if somebody could correct me on this, from Greek to Japanese. So this would be quite difficult for a machine translation system. So the time is ripe perhaps for a new shift in the machine translation paradigm, which will perhaps have an impact on us in the translation profession. And one suggestion is that neural machine translation or NMT for short will be the new paradigm. So when you think about neural, obviously you think about the brain. And if you think about a neural network, you might visualize something like this. So this is a nice picture potentially of a neural network with lots of connections, synapses and neurons firing, which hopefully yours are at this point in time too. But if a computer scientist talks about a neural network, they're more likely to show you a picture like this. So what they're talking about here are artificial neural networks that are modeled on the biological neural networks that we have in the brain. Now I want to say very clearly I'm not an expert in neural networks and I'm not an expert in neural machine translation. In fact, I would say that there are very few experts yet in neural machine translation, but there are a lot of people vying to become the experts in that area. But what I can tell you is that neural machine translation is based on the concept of deep learning or machine learning, where a computer automatically learns from data. So for machine translation, that means it can create a predictive model of translation for new source material that it has learned from the data that it has already seen. It's basically about establishing links between items or concepts or words, and over time those links either strengthen or become weaker depending on the data that it sees. Now why do we have this shift towards neural machine translation at this point in time? Because as I've already said, statistical machine translation seems to have hit some sort of quality ceiling. The early indications are that neural machine translation produces better quality. Also, while artificial neural networks are not new in computer science, apparently we now have the right processing power to make use of these artificial neural networks. So could neural machine translation be better than statistical machine translation? And why? One of the main differences is that statistical machine translation is largely word or phrase based, and so they're treated as independent units. This means that translation can be accurate in one context, but inaccurate in another context. It also means, and some of you might have seen this, if you've used machine translation based on a statistical model, part of the sentence might be very fluent and the other part of the sentence might be very disfluent. On the other hand, neural machine translation can apparently take lexical preferences from neighboring sentences and neighboring text, and in so doing it can produce more fluent sanding and contextually correct translation, thereby improving the overall text cohesion, which is something that machine translation has been quite bad at so far. Now one of the big issues for neural machine translation is that it requires a lot more computational processing power than statistical machine translation, and as I've said, we apparently have that kind of power these days to start realistically thinking about neural machine translation. But it's still slower at the moment than statistical machine translation. It's very early days for the NMT paradigm, and many people are calling it hype in the same way that they called SMT hype when it was introduced. Current research in the field is looking at if you put neural MT on top of statistical MT, can you bump up the quality? And other research is looking at if you just make the two compete, so look at statistical MT output and neural MT output is neural better than statistical. So whether neural MT will be better, and for which language pairs and directions and contexts and texts is still very much an open question, but one that is being fiercely researched now in the machine translation field, and if it shows that it is going to be better than SMT, you can bet that we're going to be dealing with neural machine translation output. So if neural machine translation actually delivers on its promises, then machine translation will get better. But we don't know to what degree, and therefore we don't know what the implications are for us as translators, as educators of translators, as researchers. Some of the machine translation researchers and developers have suggested that machine translation's biggest impact in the future will be in the production of translated content for domains and languages that would otherwise not be translated. So in other words, those languages and that content for which companies and organizations say they don't have the budget to translate. That means that machine translation won't be taking jobs from translators. It will be focusing on translating content that is otherwise not going to be translated. But even if this is the case, then machine translation will not disappear from the world of professional translation and I think it's likely that it will increase in professional translation too. So the implications are that professional translators will have to deal with machine translation more often, and that our student translators will have to know about machine translation, be able to interact with it, and be able to make decisions on when it's appropriate to use machine translation and when it's not appropriate. So we could worry ourselves with the question, when will translators be replaced by computers? According to the translation scholar Alan Melby from Brigham Young University, this is the wrong question to ask. Rather we should be asking something like when will all specifications for translation result in a recommendation for machine translation only? In other words, when will the situation arise where machine translation is always the appropriate and the best solution? He argues that we shouldn't just train translators in machine translation but we should be training them about translation specifications which many of us would know as the translation brief and about how they should be making decisions regarding what technology is appropriate for which particular brief. In so doing, the students then become educated consultants for decision makers who are making decisions about the appropriate use of translation technology. Of course this question about translators being replaced by computers is really just part of the bigger question about human beings being replaced by computers. The point at which that could happen, the point at which computer intelligence becomes equal to or greater than human intelligence, is known, as some of you probably have read, as the singularity which is described by people like Kurzweil. This discussion about the singularity is very much linked with machine learning so the two go hand in hand. But the machine learning experts and especially those working in natural language processing are telling us that machine learning is a very very difficult paradigm. It's very very complex and at least those working in natural language processing are saying they don't see any sign of the machines becoming more intelligent than the humans with regards to translation anytime soon. So we can maybe breathe for a little while longer. But given the inevitability of some translation translators having to interact with machine translation for at least the foreseeable future and the fact that machine translation is sometimes tedious to correct, an important question I think that we should be asking is how can we make interaction better between the translator and the technology that the translator has to use. So earlier I mentioned that there's been criticism of computer translation tool developers for not taking their end users into account in the development of their tools. Translators report irritation with their translation technology and that irritation is particularly evident for machine translation especially when the translator has to correct the same error over and over again or if the machine translation system delivers complete nonsense that they have to look at and read. But as I mentioned developers are now paying attention to some of these issues and I think that's thanks to some of the research done by people in our field. So they're implementing new features that should make life better for the translators. For example many of you will know autosuggest in the STL status tool but also we now see developments such as interactive machine translation and on the fly learning from post editing in theory so that the post editor doesn't have to correct the same error twice. This is called adaptive machine translation by one of the commercial tool developers. Ironically on that developers web page very recently they describe the benefit of adaptive machine translation as, and I'm quoting, ensuring you avoid making the same MT mistakes again and again. So note how the machine translation mistakes are implicitly attributed to the translator through the pronoun I'm not sure they're even aware that they've written that I thought I might write to them after I mentioned this at the keynote so all of these developments are very interesting but if we have learned one thing from translation process research in the last number of years I would say that we've learned that translators are not computers and we are as human beings creatures of habit but we have individual ways of doing things and we see that a lot in the data that we collect from translators so I'd like to suggest that some of these new developments in translation technology could in theory take this individuality into account and apply it in order to improve translators interaction with their tools so I'd like to spend the last piece of my talk asking how might we do that so a key concept here is adaptation and personalization and these two concepts come together very often in the literature because they're interdependent Garcia Barrios et al say that personalizing is the same as adapting towards a specific user and some personalization researchers define personalization as the process that changes the functionality, interface, information content or distinctiveness of a system to increase its personal relevance to the individual so they emphasize that it's important to treat personalization as a process and not a system feature and they differentiate also between user adaptive automatic personalization in computer software and their preferred user driven adaptable systems where the user is in charge of adapting the system. Now personalization has been around as a concept in computer science since the 1980s and typical areas of application are e-commerce and e-learning which I'll come back to in a few minutes but what I'm talking about here in terms of adaptation and personalization goes beyond what the CAT tool and machine translation developers are currently doing so when they talk about adaptation at the moment they generally mean learning from the post-editing so what edits are done learn from that so that the same errors are not presented again. But first I want to look at what's the motivation for personalization so in the context of e-learning it has been found that individuation of learning materials not only increase motivation but also depth of engagement, how much is learned perceived competence and levels of aspiration so that's a lot of positive stuff there. The question is could we catch some of that and apply it in translation and translation technology to make things more positive for the translator who's interacting with the translation technology. Two of the researchers I already mentioned Ulis Fjerta and Blom claim that there's a link between well-being and personalization and they argue that personalization can lead to better autonomy competence and relatedness so let's have a look at these three concepts for a moment. Autonomy is about freedom and unpressured willingness to engage in an activity and apparently is negatively affected by surveillance, evaluation and deadlines now evaluation and deadlines are two things that translators are very used to and surveillance is really interesting because we now see some of the features in our research tools being implemented in computer aided translation tools for the purpose of logging so keyboard logging etc which could be counted negatively as surveillance. But I want to come back to this later because I want to argue it could also be used positively for the translator. Competence then is seen by the personalization researchers as a psychological need that provides an inherent source of motivation for seeking out and mastering optimal challenges so you can imagine that the imposition of machine translation with this psychological need might be compromised so the important question is how could personalization of translation technology contribute to supporting competence rather than making translators feel that their competence is being drained or attacked and then relatedness is the need to establish close emotional bonds and attachments with other people so as the task becomes more computerized it arguably becomes more dehumanized so this is an issue. So some of you will already have drawn links I think between the really interesting concepts here and the work that's already going on in translation studies in these areas like looking at productivity tracking in cat tools, ergonomics and well-being of the translator in the workplace, translator perception about translation technology. So that's the motivation so let's assume that personalization could be positive for translators. One of the questions is how is that done? So personalization is usually done through user profiling. Now if any of you are tweeting at the moment or if you've been on Facebook or LinkedIn this morning or yesterday or if you bought something from Amazon in the last year you are being profiled as a user whether you know that or whether you like that. So we're all being profiled one way or another in how we use technology and we may not like that but I want to argue that user profiling could be very beneficial for translators and translation technology in e-commerce for example we can profile users by looking at their likes and dislikes, how long they spend reading a page, how many click-throughs from a specific page. So you can already see how a translator who is doing web searching could be profiled for the domains that they're interested in and what resources they trust and what resources they maybe don't trust so much. I talked about the keyboard logging that we have started to use in research but is now making its way into computer-aided translation tools also eye-tracking. These things gather a lot of data which could be used negatively by means of surveillance but could also be used very positively to find out about an individual translator's behavior and their thresholds regarding fuzzy matches regarding quality of machine translation, regarding how often they feel they have to check for a term that comes from the machine translation system whether they trust the empty output or not. Context also plays a very important role in user profiling in general and context is really important for translation too so we could take the context or the specification that we've been given for the translation and tailor our machine translation or translation technology tool to the context so if we have to produce very high quality for example we might turn the machine translation output off if we're in a really big hurry and quality dare I say is not absolutely important then we might turn the machine translation system on so there are various ways in which this could be beneficial to translators. Of course all of this brings up the question of ethics and in user profiling it takes four aspects into consideration content, acquisition, privacy and trust I've dealt already somewhat with content so learning about what the translator is interested in and acquisition using their keyboard logging, eye tracking etc to find out data about them but I haven't dealt yet with privacy and trust these are two very important issues so obviously an individual translator would have to give consent to be user profiled so the technology could be tuned to their benefit the translator would also have to be convinced that allowing their activity to be recorded would in fact lead to a better technological experience for them in the longer term and that it wouldn't necessarily expose any of their weaknesses and that touches on an important thing which is user profiling via the cloud so if we're on the internet and we're doing things obviously there's software there that can gather information about us and this is one of the issues that translators have with online machine translation systems for example that confidential data is being transferred over to the cloud because of these privacy data confidentiality concerns we now see new developments in machine translation such as the Slate desktop which only sits on the individual translator's desktop is not connected to the internet in any way and only uses that translator's data to create a personal machine translation engine for their own purposes so these are interesting developments so I have only one minute left apparently so I want to move on and say let's look forward this is an interesting quote from Robert Dale as technological capabilities move forward the reality horizon or what counts as believable moves forward too so if we go back to when the dongles were introduced our reality was somewhat different from what it is today our reality in the next 10 years will be different again from what it is today so we don't really know what lies ahead but we need to be prepared for it and we need to prepare our students for it according to a 2016 report from an association of German research funders universities have to do more to prepare their students for the effects of digitalization and automation on knowledge based professions and they expect that the demand for academic skills will rise in the next 15 years and that new professions will be created at the boundaries of disciplines and I think this is really really interesting because we need to ask ourselves what are these new professions at the boundaries of the translation discipline I don't have an answer to that question I'm going to throw it out there but I have interesting answers already we see attempts to merge for example technical communication training with translation training which makes sense to me but can we think of other exciting interdisciplinary roles where translation and indeed interpreting competence is essential that will help us to move forward so I hope I haven't depressed you too much with all this talk of machine learning replaced by computers so I want to leave you with a little bit of comfort perhaps cold comfort again from Robert Dale and thank you all very much for listening It is working it just took a little time so the floor is yours so who would like to ask the first question for Sharon for we are wiped out but statistical machine translation has hit this quality ceiling is that due to the fact that a lot of the data are already generated by computers I think it's probably more due to the fact that the science behind it can't push the quality any further that would be my reasoning why it has hit the quality ceiling that we need new research in natural language processing to push that quality ceiling higher do we see another question please one of the things I was surprised that you didn't mention was the use of voice recognition and translation memory tools to what extent do you think that's blurring the boundary between the traditional work of interpreters and that of translators I didn't include voice but I think that voice is going to be a really important technological input into the tools in general and already we have people asking the question can we post edit with voice in other words can we use voice recognition translation output and instead of textually editing it you either accept it if it's okay or if you want to edit it you re-speak it but in a way that already has the errors corrected so is this blurring the boundaries between interpreting and translation possibly but I don't really count that as interpreting it's some other form of translation it's site translation there's something along those lines but I do think you're right that voice as input will play a very significant role also in the coming years I think there is a burning question for many of us because we're training translators and we're used to thinking of ourselves as language specialists and translators now the profession must be changing it has changed already but it will be changing even more you touched on it when you said that we should probably train our students to be technical communicators as well as translators but do you think that will be an appealing career for young people today I know they're used to computers a lot more than I am but do you think how can we appeal to students will it be intellectually challenging for them will there be status in that kind of job post-editing mainly no that's why I think we need to look ahead into the future very seriously and think about this question of interdisciplinary professions where people are not confined to just you know fixing the output from a machine but have other skill sets that they can draw on they're not just confined to that one thing so I think it's a very difficult question we need to be looking beyond the next three to five years because as we all know in a university things move quite slowly if you want to introduce changes and so on what are those competences and skills that we need to introduce that will continue to draw students and also to give them a meaningful career ahead of them I don't have the answer to that question but as I say maybe other people have suggestions about that because we do need to think about that very quickly I think I'm thrilled because we do do that I mean we saw the future coming but to make people who don't think of technical communication in just those terms that maybe have been described today I've just finished some research looking at the jobs of translators in places where they do combine communication in translation and one of the managers in one of the banks that I looked at said something wonderful she said even though she had this double training she said the most important course she ever took was the terminology course in her translation degree why because the amount of information that's being produced now especially with social media means that no one can find anything anymore there's no standardization for the general public for things that aren't necessarily technical terms so someone who understands the semantics of conceptualizing whatever is being translated or written is a precious person so there's lots of work to be done as long as you look not at the current courses that are being offered but actually the deep intellectual content of those courses thank you for that and I would just add to that one of the challenges of course is for us to express the value of that kind of skill or competence to organizations like banks and other organizations so sometimes when they cut budgets the terminologist is the first person to go they don't see what the value is in terminology or in knowing about terminology as an example what the value of that training is to organizations yes I have a statement or maybe it's also a question and that refers to what we can train our students do in the workplace and I think one of the skills that we need now and that we'll be needing even more in the future maybe to adapt the technologies we already have to new skills because what will stay is the needs of other people with whom we communicate and who will tell us we need this or this from your company and a future employee might be in a position to train tools and to combine tools in order to more efficiently and with more high quality produce these results and maybe also with more speed because we all have a high work density and yes of course I'd like to know what you think about this so your suggestion is I think that we should also train our translators our students to recognize how technologies can be merged for better purposes is that right yeah I mean the traditional translation student is not always embracing technology so I think that would be challenging but it sounds like something that could be interesting for sure thank you very much Sharon this has been very interesting and I'm sure the discussions will go on over coffee and so on but I know that Hele has some messages at least a very important one this is great okay just a few practical messages that I just wish to remind you that for lunch today there is like yesterday we're going to be the same place and there'll be three rooms I just noticed yesterday that sort of people landed in the first room and never got around to the other one so there are three rooms actually that you can spread over tomorrow lunch will be special because it will be you grab a brown bag when you go out of the building and then you just hop on the bus and you get a guided tour okay I also want to remind you that there are actually water coolers on all floors I'm not sure that you noticed that yesterday but there's always even when there's no coffee or lunch or anything there are water coolers and you can always help yourself and take water I wish to remind the poster presenters that there's a change of posters today well that's for all of you and there will be people there during the lunch break to help you put up your put your poster on display and I wish to remind all of you that you must vote for what you think is the best poster okay it's all on the website general meeting later this afternoon remember that voting will take place online so you really do need to bring a mobile device with you when you come for the general meeting it'll be a four o'clock this room please also make sure that you're connected to the internet so that things can run smoothly we may actually be able to vote very very quickly if only your mobile devices work some of you have been asking what does the red dot mean it actually means that you have signed up for the conference dinner tonight so the conference dinner well if you don't have a red dot and you think you should have had a red dot please go and ask them at the welcome desk they can help you with anything I also want to point out that we have a discrepancy in a way because in the printed program you have conference dinner at 7.30 whereas on the web it says 7 and it's sort of in between so we would if you can at all and if we are able to finish the general meeting at 6 as planned we would like to see you at 7 there'll be drinks cocktails down there but if you cannot make it till 7.30 well the first course will only be served at 7.30 so drinks from 7 we would like to see you at 7 but if you're a little bit later it's okay that's it thank you thank you


Students now we are going to study the last experimental design in Kozai experimental designs which is natural experiment. In the study of a natural occurring situation as it is put in the real world, the researcher does not exert any influence over the situation but rather simply observes individuals and circumstances and comparing the current condition to some other condition. So in the natural experiment we do a natural phenomenon and on the basis of that natural phenomenon we see that before that natural phenomenon what was the human behavior and after that natural phenomenon what changed in the human behavior. Like an earthquake, a flood, a heavy rainy season or a natural event, a catastrophe then how people behaved after that event. So for this you do not design a pre-planned study and neither do you design a control group or a treatment group. When the event occurs after that we can see the behavior of people. Like recently last year in Pakistan severe floods came from the northern areas to the central Punjab and Sindh. So there were a lot of predictions and how people were adjusted and how they were impacted so that can be observed only after this event. So natural experiment are actually observational studies which can be taken to assess the outcomes and impacts of policy interventions. So these are purely observational studies in which pre-planned treatment is not given. In fact after the event what response came we can study it. Like I give an example of a study in the US in which day light was seen as a road accident that when you increase the time period of day light then how it reduced the road accidents. So it came to know that when there is day light then there are less road accidents as compared to when there is no day light.


Why are Kirby spinoffs always so good? With the release of Kirby's Dream Buffet, 2022 is shaping up to be a bumper year for Hal Laboratory's iconic pink mascot. Widely described as full guys but with cake, this new multiplayer title sees Kirby crashing through colourful levels in ball mode, similar to his Rainbow Paintbrush adventure on the Wii U. The developers at Hal Laboratory have a long history of filling Kirby spinoff titles with wild and unexpected ideas, so why do these developers always put so much work into making games outside of the core series so varied and interesting? According to Hal's chief creator, Shinya Kumazaki, the spinoff games aren't mere side projects to keep developers busy and squeeze a little more money from a popular brand. These games are a crucial part of the Kirby creative process. He said, The core titles have an important role as the core of the series, but leave a separate role for the more unrestrained spinoff Kirby titles that are full of surprises you'd never expect to see in a Kirby game. And then these slightly more unusual spinoff Kirby games drive anticipation for the core Kirby games, which helps us get enthusiastic about developing a title that meets those expectations. The series keeps getting bigger as we fill those roles and make it more diverse. In addition to keeping Kirby on everyone's minds, these spinoffs are also an opportunity for training and experimentation. Kumazaki said, With each passing year, the development of Kirby games gets larger in scale and more complicated. Completing smaller games like these is a good experience that gives the younger staff members at Hal Laboratory an opportunity to take up a more active role. Kirby's Blow Out Blast was originally a mini game that came about because we wanted to try out 3D action. A younger director worked hard to develop both that title and Team Kirby Clash Deluxe. This constant training up of younger staff brings in fresh ideas and helps prevent creative burnout. It means that developers at Hal are always excited for the next project because it won't be like anything they've tried before. In an interview with Famitsu, lead programmer Katsuyoshi Sumitomo said, I really want the next thing we create to be called the pinnacle of Kirby games. I'm positive the Kirby series can become even more fun. Design director Ricky Furman agreed, saying, For me personally, I'd really like to make a non-action Kirby spinoff game. We're going to have a wide variety of Kirby coming out in the future. According to Kumazaki, through assigning Kirby developers to work on various side projects, it makes the entire team stronger. They each learn skills that help produce even better games through collaboration. He said, The team is a culmination of the best aspects of the Kirby franchise. Kumazaki believes that good ideas don't come from the top. Instead, collaboration between people with different ideas with all levels of experience within development teams is what makes Kirby shine. He said, I may have made the initial proposal and was responsible for the overall direction of these titles, but the ideas and feedback, the technology and the style, all come together from a variety of people to complete a single Kirby title. So, if you've ever wondered how Kirby developers managed to create so many weird and wonderful games starring everyone's favourite pink puffball, the answer is simple, because they love doing it. The moral of the story then is that creativity can thrive when we all have fun together.


Greetings and welcome to Behind the Curtain. Here on Behind the Curtain we're going to look at the world of community theater. I'm your host, Susan Harrington. Today we are being joined by John Pease. John is a director, an actor, and a set designer. Welcome John. Thank you for having me. Well, I'm so excited for you being here. I want to not ignore the other things that you do, but primarily today, for this visit at least, talk about your set designing. So in your, in theater, what is your interpretation of the role of the set designer? The set designer, his role is to create the playground that the actor wants to play on and also what the director has in mind in his vision. I take that and then I translate that by reading the script. I look at it. I come up with ideas and I pass it before the director. I want to make sure that he is happy with the design and he can use it to stage his show, how he sees it. Great. Did you say this in college? No. I don't know. I've just been mostly an artist myself. I always liked colors. I always liked design. I've always liked that aspect. I like all aspects of theater, acting, directing, you know, and design. And it is very relaxing for me to do that and people are like, what do you mean? I just, isn't that like, you know, hectic or whatever? Yeah, it can be, but it's also very rewarding to me. So your process, which I think you've already explained, once you've been assigned the show is to make it what the director is looking at. How does, or how will or how could, how the actors play into that? Well, I also want to make sure, you know, they're comfortable with the space, too. You know, I found it odd when I first started doing sets that sometimes the directors were just like, oh, do what you want. Do what you want. And I'm like, yeah, yeah. And then, you know, when you do that and then later on, you know, I don't like it. That's why I was asking you before. You know, but with actors, it's really mainly, I want the director to be happy. And then from there, I take it. And then the actors usually adapt to their environment that they're on.  But the directors, you know, sometimes you need to really push them for their point of view. And you also need to know certain things.  Is there something funky that needs to be on the set? You know, like a knight in armor that moves or something. All things like that you need to take into effect because you need to incorporate that into your design. So it's extremely important that you read the script. Because you have to adapt it.  But that's not the exact same space that you have where you're working. So you need to work with your director and say like, you know, this aspect of this won't work here. We can't just set it up. You know, you can get lucky sometimes with single set. You know, just like, oh, this is the living room of the house. And that's it. But if you have multiple locations, you've got to really figure that out. Like when you did T for, what was it? Not T for two. No, key. T for two. That was just, well, no, it wasn't more than one set. But when you did the odd couple, that was just one set. Yeah. Okay. So that was, now, okay. So you had- Yeah, key for two was a single unit set. Oh, okay. I thought- It had the bedroom and then the living room. Okay. Yeah. So you designed the set. You had to think about the director, what he or she is looking for. Yeah, his vision. And then the actor. But what about the sound people and the lighting? Well, you work together. At least, you know, I would. You know, I, you know, you're talking as set design, but as a director, I have my hand in all of those things. So in order for the set to work perfectly, we all need to work as a team. It's a collaboration. It's not a dictatorship. You know, and you need to like, so this is what I'm thinking of doing this for the set. Will that work? Can you light that area? And do colors, and do you also have to keep in mind what colors to or not to use? Yeah. Like, you know, a lot of people say green is a horrible color to use. But you can use it if you use it properly, you know, because green absorbs more of the light and it has a tendency to make it look dark. But if done correctly, it looks beautiful. Okay. I know that, obviously, that you direct and you act, but do you have a favorite kind of a set to design? That's hard. I do like to do, and I haven't had the chance since I've been up here, but to do like mysteries or like thrillers. One of my favorite sets I ever got to do was on Long Island when I lived on Long Island, and we did Frankenstein. And I got to do this set. I told the director, I said, this is what I want to do. And we did the sets in all sepia tones, browns and burgundies, deep colors. And when we did that, we made sure when we worked with the customer that the costumes didn't have those colors in them and that when they came on the set, they would pop and their colors would be vivid against the backdrop. And when we did that too, when we did the laboratory where the monster was, the effects of, what do they call those, where the lightning goes between, was phenomenal. And that was one of my favorite sets. It really was. It was just, I would love to do that up here again. Okay, so what are some of your favorite shows? And I think that might be different than what kind of sets you'd like to design. But that you have done up here and you've done many. Because I know the first thing I ever saw you in was Don't Dress for Dinner at AFD. And then another was Last Night at Ballyhoo at QP. So are you talking about as a performer at what I've done?  And it's more of a black box type. But at AFD there's a proscenium stage with a thrust. And so I just didn't know, do you prefer working with designing sets that do or don't have thrust? Or would you prefer a black box or? It doesn't matter for me where, what theater outlay, layout has. If I like the play, and that's another thing, you have got to like the show that you're doing. Because if you don't, it's going to show. Because when you like something, you pay attention to the detail, you pay attention to it working properly. Just all those aspects of it, of design and dressing and everything. And you want it to look, when you're into it, you're on the team and you're participating at 100%. And that's really fun. But also too, I like it when I have a difficult space. Arlington is a difficult space. People are like, oh no, it's a proscenium. It's not wide, it's deep. And that's hard because you have your sight lines.  And I had a great set designer for me when I did the odd couple there. And him and I worked and we made a Manhattan apartment in there. Oh, I thought you designed that set. I designed it with Chip, Chip Sheeranen. Him and I worked on it together. I told him, this is what I kind of think. Can I do that? He was more familiar with the space than I was because he had built sets in there before. But he helped me. It was my design in his. And it came out really good. I wanted to move in. But yeah, it was really, really nice. That was a challenge. It was fun. So what were some of your favorites? I may have asked this, but maybe asking it differently. Some of the shows that you have designed sets for, what were some of your favorites? Not that, you know, whether it was a good show or not. You mentioned one before, key for two. I was the director, but I was also working this set with Donna. And that was one of the few shows that you could look at the back of the script and look at that design and put it in the space. And it worked. And, you know, one of the big things we have is doors in small spaces like that. So we got to use our imagination. We used a pocket door instead of a regular opening and closing door. We had it slide. It saved room. We eliminated one door.   But key for two was one of my favorite ones because it looked so good. And by the time I was done and, you know, we try things. And we had Donna Corbett was helping me and she was the main lead on the set build with Hugh on that. And we ended up trying to use wallpaper and we put it up and were like, mm, didn't work. So when we're thinking and I came up with the idea, I'm like, wait a minute. Let's get keep the wallpaper because it's got a great design, but let's put a sheer over it. And so we took shears, cheap $2 shears that you could get from building 19, which is gone now. And we took it and we stapled it all across the back wall of the bedroom and it looked like a French bedroom by the time we were done with it. It looked really nice and that was fun. Well, I was going to say your pre-show music, this kind of sounds silly, but your pre-show music and your intermission music that was great on that piece and I think that it helped kind of get people into the mood of it and stay there, which enhanced I think the set. Oh, thank you. Thank you. I picked that music. I know you sent me a copy of it. And I jokingly said, can I have a copy of that? And you said, yeah, sure. And you sent it to me. Oh, wow. It's wonderful. Now have you replicated? I think you did key for two somewhere else. Did you? Okay. Yeah. But and that was tricky because that was Winchester, right? Yes. And then they're gone. Yeah. But this and their set was that in the church rectory and it was that sense. Did you take that off the stage and put it on the floor? No. I'm trying to remember. No, it was all up on the procedure. Okay. It's small, but it worked. We did it. Yeah. Do you like repeating shows designed? I do. I do. I like that. Like I've done that also with a musical comedy murders of 1940. Oh, okay. You know, and it's always different. It's never the same thing. It can't be, you know, but the set when we did the set for musical comedy murders of 1940, which I had given Katie some pictures of. You can see when we did it, it was done in two dimension cause QP space is so small. You couldn't have a full bookcase. So we took it and we painted. And like, you know, in that show, it was a lot of fun. That show too. That's another one of my favorites that we did because they were able to make the bookcase slide or open to reveal a doorway or this hidden tunnel or whatever. It was a lot of fun. And but it was done in two dimension. And when you look at it, it looks like a real bookcase. But you know, but you can tell it's painted, but still it worked really, really well. Wow. And then I did it up at Concord. I was going to ask you. And he, wow. Alan Bentley. Alan Bentley. Yeah. We bow to Alan Bentley. He's a phenomenal set builder. Yeah. And he did that. He did the upper portion of the set like a Tiffany lamp. It was gorgeous, gorgeous set. Gorgeous. Wow. Yeah. It's fun. Because I was going to ask if you've ever done anything at Concord. You know, women, they have that huge set. Yeah. Stage, I mean. That huge stage. There's a lot to. Well, thank God it was big because it worked. Yeah. Because there's, in the show, there's three hidden passageways. Wow. And it was like, oh my Lord. I mean, I've seen some amazing sets there, but I was just wondering, you know, but they've got all that space. Do you find it more challenging or less challenging? Well, it worked really well for musical murders. Okay. Because it was a cast of ten people and a large set. You know, but if you have a show that's smaller and supposed to be intimate, me personally, I would, sorry, I hope I didn't touch the mic.  Yeah. And to help that, maybe even bring it forward. Yeah. You know, it depends. You know, but that's, again, that's where you work with the design team, with the director, and you help them. Sometimes you have a huge input as a set designer. It can really change the vision that the director had. Lately I've been asked to do this, and so I'm wondering, have you ever worked with a dramaturge? No. Okay. Do you think it would be more helpful or more invasive to work with a dramaturge? No. I think it's, a dramaturge, I think, can help you with, especially with period pieces. I was going to, yeah. And, but even, you know, even now, certain things, you know, like, that they didn't have that style back then, and that doesn't look right. And, you know, when you have a, you're doing a 1940s plane, we have a 1980s couch, and it, you know, doesn't work. I went to see a show with a friend because our co-worker's nephew was in it. And we're sitting there, and she starts rumbling and grumbling, and I said, what's the matter with you? She goes, they didn't have those kind of tuxedos back there. And I said, what? Now I wouldn't know, but she's a costumer. She was a costumer, and she says, you didn't have tuxedos with stripes down the legs. I went, okay. And then she said, that woman's gown is too far off the ground. It should have been this. It should have been that. See, there's those things that I think, you know, our folks know, and the general public doesn't. So then again, we look for certain things, and we're very particular, and it's important to us to be right on the money. Well, you know, I've never worked with a dramaturg, but I will tell you, I research my period and everything. And it's great that if I had somebody to co-work with that or, you know, assist me with that, that would be awesome. I would love to work with somebody like that.  They existed. Yeah, and were used in this way. And what I think about is when we moved to Upstate New York when I was little, I think they had, they were stuck in the 1950s. And every house we moved in had this pink and like aqua colors from the 50s that were in, almost every house we were in. And so, you know, when you're doing shows, when they think of 50s, I think of that.  And if you have a set with a color that wasn't really popular, it doesn't look authentic. The other thing too is when we did fences at folks, and they make this comment about things, everybody in the cast, almost everybody in the cast was much younger than this period. And we had to explain to this one girl what a hot comb was.  She went, they used to do what? You know, she couldn't believe it, but it helped to explain so that she could understand even though it didn't happen on stage. So that's why I was wondering if, do you primarily as a set designer, and maybe as a director, just look at the furniture and what would be on the set and the props, and maybe the set dressing, or do you also investigate or investigate things that were happening during the period? Well, yeah. I mean, if, historically, if you're doing a piece in that period, will the news affect what was going on back then? Will that news from then affect that period? Or whatever, that's a different side, but like politics in one way, you know, it affects the class that they were in. You know, low class, upper class, middle class, you know, that affects your design of what you would pick. You know, you're not going to put some really expensive piece of furniture in somebody's house. You know, an example for me would be if you were doing Brighton Beach Memoirs, and how she always polishes the table, you know, that would be something that was handed down and heirloom, and you know, that would be an important piece of furniture. And especially, doesn't she talk about it in the play? Yeah, she talks about it in the play. You know, that is something, too. And that's another reason why you need to read the script. Yeah. You know, in certain things. I know, when we did at festival with Footlight Club, we did Raising in the Sun, and we had the, this is what we used to do. I saw that. The old adjudication form, where they each came out individually. And each adjudicated to a person who said, well, you know, a colored family wouldn't have, because that's back to the reference, they were referred to as colored, not negroes or blacks, or African-Americans, a colored family would not have pots and pans that were that shiny, that looked that new. And each of them said that, and my co-producer was going, like, keep talking about the pots and pans. And I said, yeah, but listen to what he's not saying. And she was like, oh, he's talking about the pots and pans. Well, first off, they each caught that.  But, and I said, think about it. And they even made a suggestion, okay, you aren't necessarily going to find old pots and pans. So someone said, take some Vaseline and hit them with some Vaseline, and the light hits them differently. And they look older. Well, even hairspray, too. Yeah. You have spray, as long as it doesn't damage the thing. Yeah. The surface.  But when I build the set, I'm thinking about where the pieces would go and what they would look like and what they should, you know, like, oh, if the TV is supposed to be 1950s, where is it going to be? Because it's smaller or bigger. You know, it's all sorts of different things like that.  There's a lot to think about in that. Yeah. Because what I was going to say too is, is granted, you know, and I'm saying, I'm using the word just for a reason. You're just the set designer.  Is, do you feel some, and there's some way that you can, you should or maybe should not interject your suggestions? Like you were saying, because of something, you know, they didn't have those kinds of things, or as Judy would say when it came to costumes. They didn't have stripes down their tuxedo legs, you know. Oh, when I'm doing that, I have a hard time not being vocal about it. Right, you John.  No, maybe not all of them, but some people will notice. And when that happens, when something like that happens, when you see something and you think about that for that moment, it takes you out of the moment of the play. Yeah. It takes you out because you're creating an illusion. Yes. You want that illusion to be perpetuated. And, you know, attention to detail like that really, really is really important because not everybody will notice. Exactly. I mean, for us and our family, where we have our shows adjudicated, we had the Footlight Club took, all my sons took it off the stage and down on the floor. And I knew one of the adjudicators who was coming was Jennifer Lavin Howard.  And I happened to look down at my lead female and I said, wait a minute, she had on the same style shoot, but they were different. They were the exact same color. The heel and everything was the same. I don't let people know when we have a adjudicator coming. I had her down in the costume when we were tearing through the boxes. I said, you either find the left one to that or the right one to the other. It doesn't matter. I go, yeah, it does because I knew Jennifer would have seen it, but someone else might have. And so that's why, you know, that's why I was asking. I just look crazy on the woman for a few minutes. Like it is. And like I said, it's really important, you know, because when that happens, it takes the person out of the moment. Yeah.  It does. If you know something that I don't know and you see it, please tell me. Yeah. Please tell me. Yeah. Yeah. It just, it's not a dictatorship. It's a collaboration. Yes. Okay. Well, then I'm going to ask you one last question. You sure? You always have another question. I know. I'm such a fibba. Well, this is my last question. Oh, yeah. What advice would you give someone who wants to become a set designer? And I'm saying, I know we've discussed a number of things, but how would you let's say consolidate it or give it synopsis to, you know, Joe Schmo or Jane Schmo wants to become a set designer and you would tell them. If, you know, if they were going to do it like in community theater for the first time, you know, go and check out your space that you're going to be doing it in. Look at it. Look at the measurements. See, you know, like the advantages or disadvantages of the space, just like in Arlington. Everybody's like, oh, it's deep. That affects your sight lines. Look at stuff like that. QP is like a diamond. You know, there's advantages and disadvantages to that. And also, if you were going to do a piece, research the furniture and all the things that go windows, doors, in that time period. And now this day and age, it's so much easier than it was when I was younger. You know, the Internet is loaded with stuff to show you.  And then also, if you're going to do that, you know you're spaced, do your research and read your script because people talk about where they're living in it.  Great. Okay. I think that's really, really important. Thank you for joining us, joining me here behind the curtain. I'm Susan Harrington and my guest, our guest was the fabulous John Pease. Thank you, John. You're welcome. I really appreciate it. Oh, I'm glad. On the first episode of Behind the Curtain.