So, let us then go now to the tutorial. This is the first passage, I want to read it for you. You can see any vapor by the strength of the light diffused by the individual particle. And the more particles you have, the stronger the diffusion. From the strength of the diffusion, you can actually count the number of molecules. I use the word counting not like 1, 2, 3, 4, it is a different type of counting. When I was in the currency office, they used to count the rupees. You know what they did? They did not count the rupees, they counted the bags, they weighed the bags. Each bag was supposed to contain 2000 rupees that had to be taken on trust. And then multiply the number of bags and you get a crore, 10 million of rupees. Like that, you count the molecules of the atmosphere, it is only a sort of estimate. This is passage 1. This is passage 2. The method of approach to the problem of molecular scattering, which is somewhat different from Rayleigh's and which enables the case of liquids to be included, is the theory of fluctuations developed by Einstein and Smolchowski and used by the later especially to elucidate the optical phenomenon observed in the vicinity of the critical state. In this theory, the medium is regarded as undergoing small local variations of density owing to the irregular movements of the molecules and the result of these fluctuations of density is that a certain proportion of the instant light is scattered. Okay? Question. What do you think about the intended audience for passage 1 and passage 2? Yes? Yes. The question is most probably for liquid energy, for engine energy, and for passage 2 I mean... More for the tunnel or article kind of stuff. Article. Okay? Everybody agrees? Yes. Okay. And both are from Sarsiviraman. The first one is a beautiful article. You should go look it up. Why the sky is blue? He's talking to school children in Ahmedabad or some place for the academy meeting. And the second one is from his article about why the sea is blue. So that is published in some Proceedings of Royal Society. Audience, you will change the tone. You will change the words. You will change the way you say things. Okay? You will change the way you use the examples. Okay? In the scientific article, he's not going to write about his experience in the currency counting office. Okay? But with the students, he will say it. And Raman, I found, is one of the best examples of the way he changes when he projects information. There are technical papers about light scattering in diamond. There are articles in the Hindu in those days about diamond. Very different in tone, extremely different in the way they communicate information. You might not realize this, but the two information are basically the same. In fact, Einstein's PhD thesis was on counting the number of molecules using light scattering. And that is what he is describing to the children in the other, this thing. And that is the same thing he is describing here. Okay? So to take such complex information and put it across is a huge effort. And I always found that Raman to be very good at doing this. Okay? Unfortunately, that online resource doesn't exist. RRI used to have all his writing, technical and non-technical. So it used to be such a pressure to read some of them. Previously, it was, I wrote to their librarian, but she hasn't responded yet. Okay? Saying that where is this? Because I wanted to share it with you so that you can go look up. You can use it as examples. But some of it is available. For example, he has nice articles, technical articles about Veena and Mrdangam, Tabla and things like that, which are available for download. You can download and read, which also I like because for this kind of audience. No, Raman effect is from light passage through liquids. But Mrdangam and all, he has done some experiments. So you will put some powder, you will make them vibrate and show what kind of patterns they develop and things like that. Okay? Okay. So it's very clear what the intended audience is and you can also explain why. Okay? So you should always do this as a game. You know? Can I look at some passage and guess how many times do I get it right? Sometimes you don't get it right because the author hasn't done a good job of it. That is also possible. So let's look at this. Okay? Before I do this, I actually want to show you something. This is a paper, very famous paper written by Watson and Crick when they figured out the double helix structure of DNA. There are two things that I want to point out to you about this article. The first thing, this is all very short. In those days, nature was all one page. You know, Romans is one page and this is one page. The first is that if you look at the structure of the paper, for example, if you just read the first lines of each paragraph, we wish to suggest a structure for the salt of deoxyribose nucleic acid. A structure for nucleic acid has already been proposed by Pauling and Corey, right? And then you go down. Another three-strain structure has also been suggested by Fraser. We wish to put forward a radically different structure for the salt of deoxyribose nucleic acid, right? So you can just read the first lines of the paragraphs and they have structured it beautifully so that you can follow what they want to do, what is the background, what is it that they are doing, how they are doing it. This is the nicer part of the Watson-Crick article, but they are also nasty. So one here, for example, this is a single paragraph. This is a very famous sentence in time because, see, they have solved the structure. Now they are claiming that the genetic information is paused on because of this structure. They don't have the details. But if suppose they didn't write this line, somebody else, all they have to say is they have proposed a structure that can do genetic information. So they want to claim priority for thinking of this as the mechanism for genetic information transfer. So this is where they are cunning. They write, it has not escaped our notice that the specific pairing we have postulated immediately suggests a possible copying mechanism for the genetic material, supposedly one of the best understatements in literature. The next line also is something that all of you might do. This is where I said, if you have something else, which is not fitting in the narrative, what do you do? You say that it will be published elsewhere, which is what they are doing. Full details of the structure including the conditions assumed in building it together with a set of coordinates for the atoms will be published elsewhere. Now the last paragraph is the nasty thing that they did. Do you know what they did? Anybody here knows what they did? So there was a researcher called Rosalind Franklin. She was doing experiments and she also pretty much figured out. But Rosalind Franklin is very conscientious. She would not publish unless she does the experiment several times, confirms that it is so. But they were in a hurry to get credit and by one line acknowledgement, they sort of made sure that Rosalind didn't get Nobel Prize. We have also been stimulated by a knowledge of the general nature of the unpublished experimental results and ideas of Mr. M. H. F. Wilkins and Dr. R. E. Franklin. R. E. Franklin is Rosalind Franklin. If I remember correct, I think Wilkins was part of the gang that got Nobel Prize, but Rosalind didn't. But if you go to this nature version, the following article is on experiments and the next article is actually by Rosalind Franklin. This is also a very maybe successful way of communicating science, but I feel that this is not a great way of doing science. The world is a big place. We don't have to crowd out others. I would have respected Crick and Watson, even if Rosalind Franklin also got Nobel Prize with them. So there are lots of articles. You can look at resonance. There are series of articles about Rosalind Franklin. So in the scientific community, it is known that they did it. And they are accused of lots of things. Again, there is a book called Double Helix, extremely well written. Very controversial for some of these things. The way they describe the interactions with Rosalind and the way they try to sort of indicate that she really was not doing great or something like that. But as technical writing, unbeatable writing, here are some people who are not good role models for you in professional ethical sense, but certainly good role models from the point of view of how to write. I mean, look at that. Each paragraph, each sentence. You can just read the topical sentences and you will carry the paper with you. So this is the other exercise I had in mind, so I have done it. So this is the first sentences and these are the tricky sentences. This is the last trick. So this is a kind of paragraph writing style which is sometimes recommended. This is not the only style. There are also places where the last sentence of each paragraph can give you. Sometimes people mix. First sentence, topical sentence will be there for some paragraphs and some others will be the last sentence. So you can do whatever works for you. You need to write a few times and see what sounds better and what conveys your flow of thoughts and what does it in a fashion in which you want it to be conveyed. So we are going to complete this pretty soon. You should have a good dictionary. In fact, you should have several good dictionaries with you and one or two atlas. That is very old style thing. Nowadays with Google nobody wants to look at atlas anymore and sometimes not even dictionary. You know people just look up and there. But I still recommend that you buy a good dictionary. There are lots of things that are there in the dictionary which is still not part of online culture. Now if you are not looking up dictionary at least once in 2 or 3 days, that means that you are not reading to your potential. You are never too old for not looking up the dictionary. If you are not looking up the dictionary then your reading material is not on par. Your linguistic capability is what you can do. You are not reading at that level. That is what it means. So a good dictionary and usage of it is very very essential. When we were in school they even taught us whatever phonemes how to read and things like that. These days that is not very difficult because online there are places where you can click and hear and you can get the pronunciation. But it is still a good idea to have a good dictionary. Here again people are very particular. Some people like Webster. Some people like Cambridge. Some people like Oxford. What I'm reading is that you know the common thing is to everyone, right? So that's what I'm telling. I mean people have different opinions. I come from Oxford gang so I always have 2-3 Oxford dictionaries with me. But that is not something that is universally recommended by everybody. Some people like Cambridge. Some people like Webster. So Oxford has an academic writing dictionary. Oxford has an advanced learners dictionary. Cambridge also has advanced learners dictionary. And then the full complete English dictionary is there. And I think Oxford the complete dictionary is running into some... Thesaurus is just this thing. The dictionary itself is about 13-14 volumes and costs about 10,000-12,000. That is only for libraries. But personal copy, there is one which is available for 800-900 bucks. Some... Lacks of words. So academic writing there is one. But not for technical communication. But there are dictionaries of metallurgy, for example, dictionaries of chemistry, dictionaries of physics. So there are subject dictionaries. And then there is academic writing dictionary. Common people are Oxford. Oxford, Cambridge. Oxford has an academic dictionary. Academic writing dictionary. Dictionary of academic writing. So you have to subscribe to some good technical journal. If you are teaching technical communication, please subscribe to some technical journal. Resonance is something that I like. Even from my college days I have been reading. It's a very good journal. It's published by Indian Academy of Sciences. The biggest advantage is you don't have to pay. It's available online for free from the Springer side. Academy. Resonance. Journal of Science Education, it's called. It's from the Indian Academy of Sciences. The volumes are available for free. And wired and economists. Sometimes economists has, you know, odd about admitting it. But they have their obituary session. Which is probably the best description in four lines about any field. Somebody who has passed away, who is an architect or somebody who is an economist or somebody who is a chemist, a science biologist. Four or five lines. They will explain what is the person's contribution. And I have never seen anybody else doing it so beautifully. Whether it is in your area or not. So learn later. Which is very important. And there are plotting software called GNU plot, Octave and things like that. And there are statistical analysis software called R. Which is primarily used by biologists. And you should all have a lab notebook. And you should insist that your students have a lab notebook. In which they write everything. What they did, how they did, when they did, why they did. What they expected, what they got. Why they think they got, what they got. And please use a spell checker. Previous days somebody has to edit and look at your listening. Nowadays it is not. But when you are using a spell checker, please be consistent. Sometimes there is an UKF spelling. Sometimes there is an American spelling.  So, but if you are used to writing the British spelling, some of the words will be in British spelling. So you should consistently use and your spell checker format. You should tell which English you are using. And you should be used consistently. And this is something that I recommend. There are lots of online courses about technical writing. Stanford has one by a professor called Sainani. Which I have done. At least part of it I have done, not completely. No MOOC course of mine I completed ever. But there are lots and lots of resources. But because there are lots of resources, again it is very difficult to know which ones are standard. Many of them give wrong advice like this passive voice and don't use I, me and things like that. So some of them you have to be careful. So you should know the veracity of the information. And you should use which ones are standard. But there is also manuals of style. There is Chicago manual style. So there are also manuals of style. But once you get into this business, you will know. There is this book called Strunk and White, Elements of Style, which is universally recommended. But I know of several respected linguists who think that that book is bogus. But they instead recommend the Stephen Pinker's Sense of Style. It's a very good book. Not very costly, few hundred rupees. But it is worth having. And once you are in the business, once you start doing this, pretty soon you will also know what other things. So there is another book, which describes the same incident in 100 different ways. Sense of Style by Stephen Pinker. What I will do is, the books that I have along these lines, I'll make a list. I'll share it with Sundar so that all of you can get it. And it'll also go online. So Strunk and White is what generally people recommend. But there are linguists who take strong objections to Strunk and White. Similarly, I mean, when we were children, we were taught Renan Martin and Fowler and Fowler, modern English usage, whatever. But nowadays, I don't know how popular Fowler is, but I do see some criticism of some of the rules of Fowler. But I think that is simply because Fowler was written long back. Our things have changed. The way we look at English language has changed. So there are differences. But again, I'm not trained in English, so I don't know much. I know only what I used and what I use now. See, what we have been talking about is good technical writing. Where does the good technical writing comes from? It comes from a scientific attitude you should have. What is the scientific attitude? You believe that there is a simpler principle from which you can explain what is happening. Now, if you start from a simpler principle, and if the explanation is available for the existing phenomena, then you are done and you will accept that explanation. If that is not there, you still think that in terms of maybe the same or other simpler explanations, you can explain the observed phenomena. We are not talking about things which are not observable. Science and engineering is empirical. There is no place in it for something which is not empirical. For example, if you tell me that this is a way of doing this, but I am not able to go test it myself, for whatever reason. You might say that that particular material is no longer available. Then it becomes history and anthropology and it's not science. Everything that I say, I should be, and similarly, you can't say with your knowledge, you can't understand this. That's not science. You can say you need to know these, these, these to understand it. If I do that, I should be able to understand. That is the first thing. The second thing is curiosity. You want to know why the sea is blue. Who cares? You can write poetry about the blue of the sky and blue of the sea and go away. But as a scientist, I'm not satisfied with only that. I also want to know why. And not just that, the why should be an explanation in terms of simpler principles. Why can't be something like that is how it was made by God? That explanation is okay in certain contexts. In some contexts, I do believe God made it this way and I'm happy about it. But when I'm luring science, that is not how I would look at it. So curiosity, commitment to follow the truth wherever it takes. Sometimes some of the answers that comes on science is not comfortable for whatever reason. I believe that this is the reason why this experiment is giving this result. And repeated experiment show me that that is not the reason. I should be willing to accept that, yes, I was wrong. Yes, this is the new reason. Sometimes people say why mathematics is too difficult because it is very difficult not to make mistakes. If that is all there to it, it's not a problem. Maybe everywhere people are making mistakes. But in mathematics, it's very difficult not to accept the mistake once it is realized as a mistake. So science is also like that. The difficulty in science is mostly because of the way we approach things. And a good scientific attitude means that whatever result I get with these, I will accept them. However difficult it is for me to accept. And a commitment to communication. Science does not happen. It becomes magic. If I know how to do something, I even know the principle, but I don't tell you. Then that is not science, that is magic. I can always come and show and then everybody will be surprised. But science happens the moment I also start explaining why or how or how you can understand or how you can use the same principle to go beyond and do something else. And the enthusiasm for what you're doing. Science involves lots of drudgery be it experiments, be it coding, be it writing, be it communicating or understanding. You can't do it unless you are really enthusiastic about doing it. And you should also have lots of respect for those who work before you that is shown in terms of giving proper attribution to them. However small they are. No, it's not like it's okay to plagiarize from some smaller person because I know what does that person. It doesn't matter. It might be the student who joined your PhD program yesterday. It might be a well-established scientist whoever it is you are not taking somebody else's work. And if we take, we always give due attribution to them. And we believe that scientific community will do the same to us. That is very important. If you don't have that kind of respect for your fellow human beings who are involved in this process I don't think good communication will happen. And they urge to push the boundaries. Not happy with what it is now. I want to go slightly beyond. And once you start thinking like that then it means that you will understand a lot. You will understand ways of pushing the boundary. And then science automatically happens. And then if you have the flare the communication also happens. So I'm going to stop at this point. And if you have any questions I will take it. But in the meanwhile I wanted to leave you with a thought. We can discuss this is just for me to show you. Is there anybody here who doesn't know what Pythagoras theorem is? So Pythagoras theorem basically tells that if you have a right angle triangle and if this is A, this is B and this is C C squared equal to A squared plus B squared. Yes or no? I mean you can correct me. My Pythagoras theorem is correct. Okay, correct, very good.  I have to explain to her what Pythagoras theorem is. Or you want to explain to your daughter who is in elementary school? Or you have a cousin who is in high school? There are many problems, I don't know. There is also this approximation. Sine theta is nearly equal to theta for small theta. So how do you explain that to your grandmother? Sure. Sir, by Brown's rectangle of length. Right, there are many nice ways, yeah, yeah. There are YouTube videos where they will take the things, yeah, yeah. Theometry book in our school then. Very good, very good. Okay, so you can think, I mean this is an exercise that you can think about but this need not be Pythagoras theorem. It could be any concept that you want to communicate but all that I'm trying to say is that you should think of three different types of audience. One is, you know, more or less all the technical stuff is known to them communicate a concept. Another one who doesn't know the technical concept but you can, you know, tell them what the technical concept is and they explain. That is another possibility. The third one is they don't have any technical information. So even the basic technical information has to be translated into plain English and you have to build from that. So it's a good exercise and we will do more of this exercise both online and during the sessions in December. So I also hope that you have noticed what the tutorial sessions are going to be like when you will be at the other end and you may have to engage with your audience and these are the things that I would like you to convey so that they can also do these exercises. We didn't have much time so the exercises I actually rushed through then many of you wanted to say things but I had to cut short. Hopefully during that time there will be more chances for us to interact. So if you have any questions, comments, yes sir. General questions sir. Yeah. First of all, thank you very much for your original ideas on technical writing. And my question is there was a victim called Publish or perish in those days.  Later on patent. What is now, what is the current trend, sir? I want to know about from you as you are in the previous institutions. No, we would like to publish as much as possible. We also would like to get as many patents as possible but somewhere along the line, there is also the question of quality and it is not a question that is just related to science. Again I think of, what is the Markandeyer story? Is there anybody who doesn't know Markandeyer story? Yeah, you can always, the boon is that you will get 100 children who are useless or you will get one child who is great. You're supposed to choose the good child. Sometimes they tend to choose numbers over quality. The moment that happens, I think we are failing in several levels. We are failing the public who are funding us. We are failing the scientific community which is dependent on us. The next generation students are getting trained here. We are failing science overall for this country because if you just get numbers but if they are of no use, what is it that we are going to do with that science? So my personal viewpoint, again this is the personal viewpoint is that research is a very personal activity. Teaching is a common activity. I get paid for teaching. I get my salary because I have been given these courses to teach. In those courses they have put the curriculum. They know what is expected and I run exams. I check if the expectations are met by the students, the ones who meet to pass, the ones who don't fail and repeat. But research is a personal thing and because it is a personal thing, there are no rules. There are only guidelines. So what do I think about publishing lots of papers? I think you should publish lots of papers. Now how many is considered as lot? As many as you can publish without compromising on quality. Now that will be dependent on person, dependent on students, dependent on facilities, dependent on your area. And so we should only check for each person according to these constraints if the person is doing the best or not. But they are also very subjective. There is no objective measure. So because of which I think that's what I was telling impact factor for example. People talk about but some of the great papers that I know don't have that kind of impact factor. That doesn't make it any less great. So if we have that attitude as a scientific community, if we decide that we will look for quality and enhancement of quantity will done along with quality, that is a common community decision to make. That's not one person's decision. If we make that, I think we'll be in better off position. So I would like scientific administrators and managers in this community for example. What are these international rankings? How are they computed? How many of them are relevant for our context? What are the modifications we need to do for our ranking? Can we come up with our own ranking? So the people who have come up with the other ranking, they know what quality they expect and what quantity they expect that quality. We can take it and supplant it here. So yes and we should also not be, because writing is very difficult and writing a good paper and trying to get it through a good journal is difficult. We should not hesitate or be lazy to not do it. To that extent, I agree that we should try to publish, but I don't think there should be any compromise on the quality and the quality is this. Are we pushing the boundaries? Are we asking questions which are of relevance? Are we answering them to the best of our abilities? And are we translating them? It's also Indian Institute of Technology, it's not science. Finally, is it getting translated into something that is measurably improving the quality of life of people? Excuse me, sir. Yeah. So this, my question is regarding the reference. I read in some paper in abstract, they are also mentioning the reference. So is it correct? Generally it is not correct. And second one is what in by H index? Yeah, so generally it is not a good idea to put reference numbers in abstract. If at all you want, you give the full reference in brackets, name, journal, page number, et cetera. And that should be done as sparingly as possible, as much as possible you should avoid. Now H index is, if suppose I have say three papers and all three papers have been cited by others three times or more, then my H index is three. That is one paper might be cited for 100 times. Second paper might be cited for 55 times. But if the third paper is cited only three times, then I have three papers which have been cited three times or more. In other words, H index tells you, not just I publish one great paper, then I don't do anything. So H index is supposed to distinguish this. But the general understanding is that H index is good, not for individual persons. You know, I might publish one great paper, get noble price, then I might not do anything, but I think that is still okay. I'll be much happier if I got the noble price and nothing else for the rest of my life. But what is H index is supposed to measure is you look at the H index of all faculty members in a department and another department. That comparison is valid because overall if everybody is doing better, then the H index will reflect that. That is the hope. But like all things, you know, I said measurement is still subjective in most of science. And that makes it very difficult. You should look at impact, H index, everything, but you should still not be carried away just by numbers. They are finally numbers. You still have to make up your mind about the quality of some work. And that is where you should exercise your scientific expertise. And if everybody does that, I think that'll automatically happen. Hello. Hello, sir. Yeah. Sir, you have given a lot of good ideas about the writing and those things. My question is on your initial part of a presentation. That is you told me you should consistently write. That is write every day at least five sentences. That's true with all. And I guess everybody will agree with me that as we proceed, means when we were students, we used to write something. But as we started our profession, we are a little bit lazy about that. So my question is whether, what are your writing habits, your own writing habits, how you consistently keep yourself motivated to write the things? See, the easiest thing for me to write is my lecture notes. I always write my lecture notes and publish them. You know, in the search gate or some online, the thing, some NPTEL, some QTRIP course. So one thing that I always try to write is the lecture notes because that is very helpful for me. Previously I used to maintain a blog, but nowadays I don't do it. But there is lots of writing that I do along with my students, even though I don't write. They have to write every year their annual progress seminar reports. Then we sometimes have to write papers. Sometimes we have to write thesis. And then there are masters and undergrad students in the lab. And we try to make them write and along with the PhD students, I participate in overseeing that writing activity. One thing that we haven't been very successful is in making lots of technical write-ups and reports and sharing them online. We do some amount of it. And that is one of the things that keeps me, you know, involved in writing. But still, overall, I might not write every day five sentences, but over a period of a week, I tend to write at least some five to 10 pages of many different qualities. Sometimes I'm very happy with my writing. Then I go to town sharing with my colleagues, saying, okay, I wrote these notes, if you want to take a look at it. Sometimes I put it up online, saying that anybody can use it. Sometimes it's not of that great quality, so I quietly bury it, move on. Nobody knows that I try writing. What is actually a lecture notes? Lecture notes is I will put the objective, then I will ask a question, which is the motivating question for that class. Then I will describe the concept and I will explain how that question is answered. Then I'll have a few MCQ kind of questions, multiple choice questions, so that the students can test for themselves whether they have understood. And then there is an in-class tutorial, sometimes I make them do in the class, or sometimes there are assignments at the end, and the solutions are posted separate. So this is something that we tried to write. I think if everybody who teaches starts writing this, then it will be really helpful. I found mostly it is helpful for me when I'm writing, then I have to be very careful, I have to think through, and then I have to process the information in one way, so it is very helpful. It's also helpful for the students because then they have something to... To get scientific papers published in standard or reputed journals, it takes around even one year sometimes. In spite of it being reviewed at different stages by great scientists, technologists, and engineers, still we find some papers getting published with so many common errors. So what is your suggestion to make all these papers error-free? Because I've gone through so many papers with very common errors, like cope up with, discuss about, can be able, one another instead of each other. There are so many papers, even I have done a small research on this, still we find very standard journal papers with more common errors. So why don't you suggest to include at least one English faculty as one of the panel members or reviewers? See, the problem is A, people are not interested in the English aspects as long as the technical communication happens. The journals, they are really not too much worried. But actually, sir, in UK papers and US papers, we don't find any errors. But not strictly true. I have found errors. Almost 90% sir, almost 90%. But in most of the reputed journals, including IEEE, Taylor and Francis, Springer, ScienceDirect, there are so many errors. Even I have a print screen evidences. No, I know that there are lots of errors. In spite of getting reviewed at different stages. But as a reviewer, I never look at English and if I have any comments about English, I just write that these are the English things they have to correct. But finally, my aim as a technical person is not about the English. It's about the... So if the English comes in the way of communicating the concept, then the paper gets rejected by me. It is a formal document. We feel very since the errors. But the errors will be there. I mean, how can you avoid it anyway? Because it is a formal document. It is in a very reputed journal. I understand. It can be error free. No, but see, that's what I'm telling you. It's a personal thing. I can't go put rules for everybody. And especially when there are no rules for something. Everybody might have their own opinion. Now, simple grammatical errors, should they be there? I think they should not be there. But then there is a problem because we use only English. For example, if they have allowed me to write in my mother tongue, maybe I'll not write grammatically wrong things. So scientific communication is basically because somebody who is from anywhere, Japan, China, India, Brazil or Egypt, want to communicate a scientific thing. Now, I would like it to be in as much as possible, grammatically correct English. But that is still not the primary aim. The primary aim is the scientific concept. Now, if English comes in the way of that concept explanation, the paper should be rejected. If there are other grammatical errors, they should be corrected. That is why we have editors. We have copy-setters and we have copy editors and all these things. In spite of all the stages, still there are some journals where we have common errors. But errors can always happen.  Let me put it that way. And publication is a major process. I don't think you will have error-free. And the community can find out which are the error-free ones and appreciate them. That is it.


Ball officially at the 13-1st and 10, Titans in the pistol. Three tight ends for the Titans, all to the right. They roll Henry, he's going to throw it. Man is wide open. OK! Touchdown! Titans, jig, a cockwore on the halfback pass. Derrick Henry, who throws it well, makes the play. Henry now eight of 10 passing in his career for 41 yards at five touchdowns.


Hello, and welcome back to the craft box. My name is Brent and today we're in episode 220 of the Wizard of One on Death walkthrough last time if you haven't checked it out already. We finished off Warisburg We defeated Captain Winters and today. We are starting the forlorn tag. You can see Baba Yaga there That's kind of cool. Um, so yeah, let us talk to Mariah I am sorry to tell you but if you were hoping to travel down the Trans Pallarian Highway You should turn back now. The road is dangerous even for the frostbite rangers and farther on it is completely blocked Traversing the forlorn tag is impossible. Come now, Maria. Nothing is impossible for Ivan the Great in this case I suspect it is but perhaps you can help us and together we can make the road safe again Little up yay have taken over the road around the bend pushing travelers around stealing their lunches and everything else a Report just came in that they overturned another wagon I must remain here to keep the camp secure, but you could go and offer assistance Look at that level up. We are now level 107 which is really good. Uh, where are we doing? It's this highway I don't know where we're going. Okay this way That's cool Okay It's about time What must a duchess do to get a little assistance here? I come all the way from will zakistan and this is my welcome And how dare these beastly mammoths treat me this way don't they know who I am I'm impressed and to sketch firstest cousin.   Okay. Um, I'll be back once I've collected these three Luggage's Okay, I am back. We just finished off that My pinguin fur coat had gotten dirty. I don't know what I would do No, perhaps one of you could help my pal in keen bearers carry me to this camp up the road Are you there? I'll ski you look strapping enough. I've been the great does not like being bossed around But he is gentlemen, he will help carry you to camp I must forgot one of my most important accessories My handmaiden chili lily the bullies pushed her into that game.  Oh, but I simply must have her in war risk bug Are you dear? Why this strapping oski escorts me to camp. You see if you can do anything for little lily Okay, then I think this is maybe yeah, that's cool. I'm like and just comes out of nowhere kind of weird just Quests out of nowhere Or that's what it feels like at least but you know, that's fine. It's how this game works. It's fine How much space 100? Oh gosh, we need to clear out the backpack soon. That's for sure J's But let's go dear be careful. You might not want to come in here This bohemath is not very nice. No, not very nice at all Cold in here so very cold. I asked politely, but this bohemath won't let me leave. I wouldn't want that to happen to you Okay, um, why is Ivan with us? I don't know whatever Well, let's do this so death put in some prisms did ice not difficult at all a piece of cake really Uh 14,000 that's not much which is good Go for a blade right off the bat. Hopefully get a couple of them Down that should be good And then we will kind of just sort out couple faints Prism and should be cookie. Hopefully fingers crossed Hopefully um, yeah, especially if we had a shadow, but would be a nice indeed If we can go like that two blades. We've got a faint ready to go Also got an enchant for the next blade that pops up which will be great Okay, hi, okay, that's cool you would wouldn't you Ah What do we got we got this? We will go for a prism right now Just so that he can't life shield In case he does one of those cheeky wood life shieldy things where he does the life in the myth shield Who knows because that would be bad just like that guy did okay? What we will go for a faint and We will go for a blade And maybe another blade and hopes we get a shadow perp We get an enchant would be great for another faint, but we're stunned anyway, that's great. Okay So we probably just pass and then what we have to pass see what we get. What do we get? Okay, Risha don't need that. We do need that one Okay, so we'll pass we'll belay it once more and then hit probably Unless we get a faint and then we'll just faint again because I know two blades will kill the minion This minion is bad Hi, what's the It's a blade. Whoa, you think you're good Okay, we will belay it again then we'll do the best which is either of them We max perp so doesn't really matter. We'll do this one then whatever And we'll hit next With a Lulu and that should hopefully kill What's this tower shield? Okay, good job. Good job. What is this a another blade? Okay, just blading up to the max. Is that a TC blade? That might that must be a TC blade These guys use TC's. It's really weird. It's really weird. It's a good idea But like really weird not used to that yet. Just not used to it We'll hit if we don't kill we will faint and then hit with a deonite at the pops or something I don't know. This should kill though. If it doesn't I'll be disappointed I'll be correct this killing. They're dead. Indeedee Bye Okay block. What a bad help. Okay. How much would have it done? It would have done Oh, it would have been so close to killing if not may not have killed But we killed so it's fun. Hello, Chilly Lily. Oh Goodness that was scary so very scary, but you were so brave. Yes Thank you for defeating that big mean bohemus. We're going to forest burg I hear there are a lot of penguins there. It's exciting. Isn't it? I can't wait. Nope. That reminds me Did you see the duchess? Oh, she went to the rangers camp up the road. That's good. Very good I don't know why but I always seem to wind up getting bullied by someone It's sad. So very sad. I should hurry and catch up with the duchess. She's probably getting impatient So very impatient. I'll see you at the camp. Okay. I don't really like chilly. Lily. She's A bit of a scaredy cat. Oh yes. She is oh yes. She is um I don't know don't really like chilly. Lily. Chilly Lily does not rob me the right way Just don't like her But let's go and talk to the duchess again and we will For yes, we will go and continue on Hopefully getting closer to Baba Yaga Um the closer the better because then we get a new spell in next level or there will be more than next level But we will get a new spell soon. Sometimes soon. Look at all these side quests. Whoa. Hi Rangers tell me there's been some kind of uprising in walrusburg. My cousin's been placed under house arrest Yeah, she is Foolish and to scare I warned her you can't trust these pinguines Can you imagine the humiliation she must be suffering? We certainly can't visit walrusburg now We'll just have to return to alzakistan.  Oh dear. We'd have to pass through urville station again There's something bad there. Very bad indeed. Hold on. Did iven hear correctly? There is trouble at urville station Ivan has Friends there. He does not like to hear them. I'm sure your friends are all right. Ivan. Well, I hope so Maybe it will be like walrusburg. Is it true the penguins have taken over I can hardly believe it Oh, I would very much like to visit but I'd have to leave the duchess. How would I support myself? Oh dear There is one thing I suppose I make good flapjacks. Yes, I sure do. Could I sell flapjacks and walrusburg? Maybe if I had my pan after we crossed the new blogger bridge The tundra trolls in the road demanded a toll so the duchess gave them my flapjack pan She sure did. I guess I'm out of luck. I surely am unless You mean you would go get my flapjack pan. I really dislike chili lily. Can we just drop her from the story already, please?  It's uh I don't like it. Um, anyway, I'll be back once I have defeated and collected these Okay, I am back. We collected that second time not too difficult Um penguins are apparently meant to eat crepes. It was a slight dialogue. I missed it, but that's fine Oh flapjack pan so much. Yes, I sure did and for us to depart We've lost the wagon now. So you'll just have to carry the luggage You'll have to excuse me mistress, but I won't be going back with you. I'm going to stay here in walrusburg. Yes. I surely am Don't be silly. I need you to carry the luggage I wish you the best of luck with that mistress. I certainly do. I hope you have a safe journey very safe All right, wizard. I guess this is goodbye or maybe I'll see you in the city I'd like that like it very much. I'm sorry if I've given your friend Ivan cause to worry Maybe maria has better news. You should speak with her Okay, maria the road is certainly safer Ivan, but the bridge is another matter altogether Believe me. I wish it was not the case You don't understand maria. Ivan and wizard must get through Ivan must visit urville station and wizard must find baba yaga Baba yaga you people are truly mad, aren't you listen If you're determined, you'll just have to deal with deo mo the bridge builder Deo mo and his tantra trolls like to tear down bridges Then they build new ones and charge travelers a toll to get across That's what they've done with the new blago bridge if you want to cross you'll have to get deo mo to raise the bridge Good luck. I can't believe I'm saying this But if you make it across look for my sister zoya, she can point you in the direction of baba yaga's house Okay, let us hit over to The new blago bridge and we will see Um, see these trolls aren't actually too bad. They're Really quite easy. Um Yeah, but you know, that's just how it happens sometimes. Oh gosh. I got the hiccups. That is not good I'm dying. Oh no Um, let's put on the boss deck again Deck out the prisms. I don't know if we need them. I'm not sure, but we'll find out in a bit That's for sure Um, and we will find out who we are facing. Who is it? Here I sit trying to run a legitimate business and everyone gives me trouble. I built this bridge So what if I don't have the old one? No one gets across my bridge today No one if you've got a complaint by all means come a little closer.  That is for sure Um, hello Um, let's see. Okay. All of the lulus that is cute. Um, let's go for a faint to start sounds good I am what is this? Leviathan? Okay, that's cute Remove the dammit with things All the o's All the o's All the o's Leviathan takes me back.  Okay. I don't know if we can use e-freed. I'm just assuming you can. I have cleansers on so it's fine, but um, who knows Who knows? Honestly, who knows? Dimo the bridge builder. Domo. I don't know. I don't know how you say it. Um, let's go for a Death blade. Um, they're just passing. That's cute Okay Death blade Um, another one or a faint Nope, we need another one Hopefully we fight. What am I trying to say? Hopefully we can find some enchants Um, that would be great. Oh, he can e-freed. Okay. That's good to know Look at this. Hello. Just as well. I have cleans whether I can find it. That's another problem Okay, definitely need to get rid of that boy Puh, another blade. Nice. Two blades Uh, if we can go for a one of those nice Might as well get another blade up. Whatever They spam this. They love this This is nice to be shift waters. I don't know. I don't even know what it's called. Shift hammerhead. Maybe. I don't know If I see him I don't know. But they love that shift spell. I think he gives him a clip actually Which I didn't notice before. Oh, of course you would do a minus 45 He's still tired though, which is surprising Honestly surprising Uh, three blades Okay, there's another one if we need it Um, can we get a cleanse? Thank you Um, I think we might go for a hit next Not worried he's going to remove blades Um, he's had a pipsnow, which is great Okay, what are you doing? Meet your probably Nope, okay, minus. Just continue to spam with the smoke screen that makes sense. Okay Ridiculous, honestly. Um We can just cut that. I mean, I'm kind of keen to hit He's only got 12 000 Three blades one. We should be fine. Surely will we fine, right? We should be fine. We can't be free So what's this? What's this? Miss Jeff Grendel What does the Grendel do? Oh, is that the one that gives me like a random um Does that give me a random note? Yep it does. Oh, okay. We're not powering this We are not powering this. There is no way if we power this we're going to be good. Nope. That's a good job Okay Grendel is the one that gives you a random debuff Well, no, we don't have any enchants Yay, this game loves me Let's go for another blade then Might as well Um, hopefully we can find another faint another faint would be great Another faint would be fantastical Pyo! Um I mean, we don't really need it because we've got a lot of blades now four is a good Well, we found another faint Two sheds Okay, can we get some enchants, please? That would be great We're honestly, where are all of our enchants? Like what the hell? They're just hiding Oh, I just like all of these accuracy debuffs Just as well. I have enough accuracy to not fizzle normally Otherwise, I'll be fizzling everything Honestly, this is ridiculous Every round I think I've had an accuracy debuff.  Can we get an enchant? This game honestly Well, we'll just continue to blade I suppose Until we have too many blades and we're dead Uh, hopefully we find an enchant next.  That did so much. I am surprised that did a boat load Okay, we get the Lulu that is enchanted again. Okay, we could have used that a while ago At least we got our cleanse without discarding too much Now I just have to hope that they don't hurt for two rounds like two whole rounds Is kind of ridiculous I don't know if I'm gonna win this If they hurt, I'm dead. Basically how it goes.  Okay Good job good game. We did it. We did it. They're dead. They're dead Okay, here we go We're gonna this is so much over here.  I see how this Just make me crit. That's fine. I see how it is That did so much.  I'll move on another day another bridge. So it goes There is lever pull that and it will lower bridge. Then we are on our way comrade. No more delays Okay, let us pull the bridge control Now we cross bridge and look for maria's sister zoya Ivan has met her before zoa knows forlorn tag like back of her paw She will guide you to bobby yoga's house. Ivan must attend to other matters I hope you understand comrade. This was not ivans intent. You heard about trouble in urville station. Yes Ivan has History there if penguins of urville are in danger He must go we will not part ways just yet though. Let us find zoa first Okay All let us head over to zoa then And we will continue on our quest for bobby yoga Which should be good Please Thanks Okay, let's go over the bridge And zoa is right here. Hi You're the first ones i've seen come across that bridge in some time. Does that mean someone taught deo mo a lesson Good glad to hear it Ivan it's been a while. What brings you out here. You have a delivery for the witch In a matter of speaking. Yes My comrade here is wizard from ravenwood and needs your help to find the bobby yoga's house Then this wizard is either very brave or very foolish Baba yoga does not allow visitors Nor is her house easy to find are you aware of the risks you are taking wizard very well then I will help you but don't say I didn't warn you Thank you zoa and now Ivan the great must hurry to urville station. Goodbye for now comrade and good luck The rumors say urville station has fallen on hard times Ivan may be facing as much danger as you my friend Baba yoga's house is hidden deep in the thick boughs many souls have wandered into these woods and never returned The snow treants do not allow trespassers I suspect that is why the witch chose their forest for her home to find baba yaga You must have the snow treants cooperation. You'll have to confront their leader snow beard in the cold clearing Okay, let us go. Nope. That's the way to eval station. Good job this way. Okay Uh, let's go and defeat the leader and then I think we'll end off the episode after that Um, I'm not too sure how we're going on time wise, but that's what I think we'll do Look at this the skybox is so cool Just looks so cool Uh, let's hit on him Right over here So baba yaga's house is just over here. I believe That's her house. It's like over in the back there Um, but yeah, let's hit on in here first Because that's the first matter of duty Need to put more cleansers in I should need to remember to do that Is there really where an old tree ant can go to rest on its roots at the serenity of snow beard? You will suffer for it Okay, so I'm going to skip this battle. Um, just because it is essentially the same as the last ones that we've had And I will be back in just a sec when I'm killing. Okay. I am back. Hopefully killing Nearly forgot to press record. That would have been bad. Um, but we did kill Megan Um, so yeah, that was easy You've proven your metal soft skin. Why do you trouble an old tree ant, so Baba yaga, you wish to visit the witch if you will make me back out in the bars I will show you why that is a problem Okay, um, so we'll talk to him and then end off the episode And next time hopefully we find Baba yaga, that would be great Pretty sure we will be able to because I don't think this area is actually too big. I mean most of the areas are not That big which is great. Um, I find it really funny how like the um The sigil is really far away from where we actually respond. That's kind of funny. Oh, well, where are we going? Where is snow bed? What is in here? Jeez Where does this go? Whoa That's cool That must be a later area. Okay. Let's get a stone block Um, okay, that's really cool that tunnel. That's pretty cool. Uh, let's snow bed. Hi Hi, how are you? Baba yaga lives behind here in the Vale Vale the bowels block your path Long ago, I could have bought them for you But it is now forbidden The Pyromancer to tell me the destroyer will burn down the entire forest if I plot the bowels He has a scorched earth charm A vile thing If you are daring enough to enter the destroyer's sunken tower and recover the charm Then I can park the bowels on your behalf Okay, so next time what we will defeat the Tali the destroyer Um, hopefully meet Baba Yaga, um, which would be great. So, yeah, thank you for watching until you like and subscribe And if you're very subscribed press the little bell so you know exactly when I post another video and remember craft outside the box You


Thank you very much Welcome everybody Well, I understand that you are a bit tired after all the day, but what I try to be the less Charging that I can as she said I'm Edward of Santa Carvalho. I work in a strategy and Well, I I've been over the years designing Lots of AI solutions and now we want to talk about an alternative to a standard complex resolution That's the direct, okay So no As I said, there are lots of complex problems that we want to resolve with AI and many times we go for assistance or corrob all through car autonomous car and we always think on one only algorithm that resolve everything that it's like Rosetta stone of the or cornerstone of the artificial intelligence, but We are going to present today an alternative to this a Colony of two nights gambled more than a single human think about this When you think on a person a person is far more intelligent that any termite or any insect, but What the insect can build it's amazing Why because they collaborate they Well work together to build something that One of the most intelligent beings in the planet can build alone How we how they do that by Dubai and conquer and we can reply this natural behavior But doing the same we have a complex problem, but there is not a single individual there solving all the problem No, they go for it. So problems that are easier because the complex problem requires high computational Power and it's not always Parallel disabled you don't have a parallel approach for every complex problem And also they're kind of difficult to model and prepare the data. That's the reason you need Incredibly good that the scientists to model a complex problem but if you work on the decomposition you are going to have an initial analysis that will be kind of complex, but Easy for any Engineering and the sub problems that are the output of this Analysis process are simple easier problem that can be modeled with Small programs that can resolve that specific sub problem How we do that going by agents what's an agent an agent is an entity that can do Do things in an environment where other processes and other agents exist It's interesting because there is no artificial work in all this definition. Why? because an agent could be anything artificial or natural in the environment anything that is autonomous in the environment is an agent so we have an environment We have requests and what we design as the architecture of this agent as simple agents is Request response as any program in the world, but also they have to be aware of the environment with triggers context for the workflow What that means the environment are going to be sent by sensors and The context will happen a status and the workflow we work with this status how The environment triggered the sensors the sensors make changes on the status And this status is read by the workflow who reacts to it This is also as many other things that we are going to see today Inspired by the natural way that we respond to any process in the environment We sense the environment something. It's changed in levels on Our brain and that triggers some specific response When you have the whole picture you have Domains from a some subtype others titles that all of them are cute By machines and human requests Which are the responses of the same agents? Which means that you can combine any solution that the soup problem Generates and Makes them with the human request in a new queue So you have the whole system that it's working to with environment solving that complex problem And when we say domain a agents we mean a bunch of agents of this type with Horizontal scalability with the able to self clone and to talk with the undernet platform and I want to self kill with no requests Are we safe and as we are talking a vertical Scalability well every agent is able to do there to know if a request Belongs to their domain or not and if not simply rewrote to other agent. We don't like them I don't like this problem. This is not my request not my problem and pass to another one This approach provides true cooperative model and you can have Really cooperation between your agents to solve for real large and complex model and also have all the necessities For a larger scale complex problem solving because you can scale both vertical and horizontal in the way you need and How evolution strategies come here evolution strategies are very no Models that can resolve particular small problems What's the problem with the evolution strategies that? Historical they don't scale well, but let's see a bit of evolution strategies before we decide, okay? When we have evolution strategies, we always have in a rail of individuals to call population each one of these individuals is a Sample of the solution space which means every individual is a solution for your problem your small problem Okay, and these individuals have an array of values which represent their Jeans their chromosomes what they are meant to do and how well they are performed for that specific problem Also, when you go for evolution strategies, we only have two operations crossover which is the traditional Genetic operation when you have two individuals you select parts of the chromosome exchange genes and You get two new individuals that are new performance that could be better or worse than their parents But now you have a bunch of new solutions that can be evaluated to know if you are going to go Well or going bad in the resolution of your simple problem also you have mutation with Increase the entropy of the system by simply doing changes in a specific genes In a probabilistic or a random way, okay, so this is the traditional approach of the evolution strategies You have a bunch of individuals you have a chromosome which means real values and You have crossover and mutation to go over the iteration to get the improvements in the solving of the problem, okay so We we need is to get a better representation a functional representation Look when you go through complex models You always or many people always to go through neural networks and Neural networks are represented by a direct graph like this.  You have a function that ideally could represent any problem and solve it When you go with evolution strategies with you have an expression three expression three is a very good way to represent functions that are simple enough and That's the key because we are resolving small simple problems We are not going for the bench or the wall cake. We are going for the best piece And we have the representation of any function with this approach And this is very important because resolving this kind of a structure is far more efficient than the upper one now Which one are the Traditional implementation of this kind of algorithms. We have the traditional that come from the 90s the Genetic algorithm. Okay, it's basing crossover as we've seen before lame demutation is optional as depending of the programmer if they want it or no and Are good for very specific problems like? finding the maximum of the small function with Very small number of parameters and they are very bad at this kind Because when you need to cross over all the population you have a really Performance problem is you can distribute the population and try to cross between different nodes because you are trespassing the problem of the Complexity itself to the network so you don't have any improvement you can scale it would How we can solve this? Well, there are three modern alternatives to this Cmas which means covariance matrix adaptive evolution strategy Which is basing on mutation and only mutation? it's this is very interesting because you discard the crossover and Go through the covariance of demutation to get Very optimum a gradient descent of the problem When you get on sim cmas what you get is a population that Explode basing on the covariance of the power of the of the solutions of the space solution and You concrete where the maximum is and all the population is iterating over that point of this solution space When you have any ease which means natural strategy Natural evolutive strategy you are trying to go For a similar approach, but inspired by natural evolution what you do is to guide all the mutation again And this is very important the main reason because every Approach discard crossover is because all of those Solutions are good scaling a really good scaling so you can put the mutation on Spark cluster or over a tons of low you can have any large parallel back end Which? improved the performance a lot Open a a it's the only one that is really designed it for scaling and It's very recent open AI the described open AI evolution strategies the last year So this is really new solution It's based on cmas, but it's designed for a scaling so you have a problem that could solve Complex problems in a functional way, but simple problems in a computational way so you can go and solve all of them Let's talk about performance because as you can see I was insisting one and over and over and over again about Performance because this is the main point because this amazing technology is discarded several years ago What we have here is a graph or true Executions and you have the iterations needed to get a good a good solution And if you look here at the very start you will see the gradient descent of The simple genetic algorithm, which is the blue line or the open AI Alternatives which you can see that go kind of good under natural a strategy that can go better And you have the best one DCM as As you can see in a very very few iterations You have the best solution rich. This is kind of good because Very few algorithms can do that But let's see also in that time. Okay, this is the performance in time as you can see cmas because Really like a real a regular neural network the iterations are spaced. They are long iterations a long epochs that go improve in and suddenly they explode As you can see the natural strategy Natural evolution strategy go the first to get a very good solution, but far from the best one for Reference the point where all other are stuck. It's about 80 85 percent And the point where he's stuck the cmas is by 99 percent Okay, so they're kind of good finding a very good solution and The problem they are solving here. It's a Thousand variables tracing function. Okay, this is a very complex function that have thousand literally thousands of variables and Thousands of dimensions and have lots and lots and lots of local optimums local maximum and That's the reason the older solution get the stack and even the traditional general genetic algorithm, it's slowly going through is this no look I had a better one but the cmas The reason which is far away from the best solution at the start is because as we talked before They explode on the covariance so gets a lot of very bad options And they do this so they can do a true Explore of the walls space solution. They want to explore all the space solution to know where is the best and Then they come back there So every individual is trying to be the best in the area with the real maximum on our and this is It's incredible to see it But also we have the execution Execution performance is something that many people simply don't talk about everybody is obsessed with training Performance because is where all the money is but Execution performance is the key to know if your model could be used it in real-world or not and how is that because when you have an ES The typical execution time the activation time of your trained model is under the second far under the second Which mean is really usable but when you have for example neural networks in the same architecture you need 20 seconds for activate a neural network and look that the expression tree is even bigger than their neural network, but They takes lots far Far less time to execute and this is because the expression tree is very very efficient in the execution But their neural network need to go through all the nodes several times to get the solution Of course the way We usually go it's adding more and more and more GPUs to reduce that 20 seconds to one or half second but with that Approaches you don't need that any single or any a small resource architecture raspberry P a small A you AWS Instance can execute the model in a very fast way very very fast They don't need any backend to execute to activate So how is this all put in together, okay? It's Very interesting because we see at the start that we are going to solve all this solve this with an Asian architecture Where is the point where our? strategy Sorry evolution is that he comes here Well, of course, it's our workflow our workflow It's going to be trained it with all the requests we have and all the context We have to be able to produce very good responses again for a small small simple problem and then we'll be all combined To get a resolve of the wall problem How is the how does this don't you have the environment and as you know You have sensors that trigger changes in the status level and the CMA. Yes, it's reading This status is reading risk request to activate but also You can have a very good thing here You remember the execution times. They are very very small Training of an S or training of CMA S. It's in the order of seconds Not minutes nor hours seconds on a standard architecture those times where Were executed over in a standard i7 CPU? so What we can do here that is Far more difficult with other approaches. You can have retraining Continuous retraining and you can have this absolutely automated because you are fairly sure that the Retraining it's not going to take long. It's not going to take lots of resources and Even more important being parallelized. This can be executed in a back-end with Will be even in the same machine as the CMA s it's executing. So you have a very small Algorithm with needs very few RAM very few CPU that can be retrained it very frequent That even is not necessary or a strong back-end for retraining But it's absolutely parallelizable. So you can do it and that's the fantastic solution about this You can decide if you can you want to go over a spar with strong back-end lots of nodes for retraining or you can go with a small architecture like raspberry P and train only what you need and That's the real point that is killer with this technology that you can do all of this and decide exactly what you want Let's see a practical scenario of this, okay Of course, this isn't oversimplified Solution, but let's take a smart rocker mass broker a smart rocker is the solution Everyone want to solve because if you solve it you are going to get rich very quickly and be very very happy the rest of your life So what's the first thing we need to do we need to do to a splitting soup problems? We have the relevant facts with the news about the different stocks that we are Monitoring we have third-party recommendation and this is very important because if everybody is Recommending to buy some kind of stock It's likely to go up or go down and you need to know that and also the historical data, of course Which shows you a minimum maximum on trendings What we do now is to model those soup problems with here is here to solve into agents You have an agent for mood that can extract from relevant for a relevant facts the mood about a stock and you can with the same Algorithm and the same instance you can scale sub cloning so You can have lots of agents Looking for the relevant facts and reacting and producing a value for every a stock that you want to monitor Also, you are going to model an agent that make influence Which means what is everybody else saying about these stocks and this is very important But also it's a simple problem. It's not very difficult to get the influence. This is many times This is a toy a sample toy problem that you have in many tutorials That you have lots of opinions and you have to categorize them. Well, this is it Small agent that simply categorize a recommendation to know if a stock it's a and good mood It's a bad good mood or if the people are recommending to sell or to buy and the last one again simple a Simple agent and this is very interesting because Getting maximums and minimums is the specialty of evolution strategy So you have the best algorithm for doing the trend of the historical data here It's the best one you can have and the less Resource consumer so it's fantastic because you now have your Very complex problem, which is very very difficult to model because you have relevant facts It's an instructor a data you have third-party recommendation, which is a structured but comes from many different different Approaches and you have the historical data, which is the structure of data and You don't try to solve on a one shot now You go for the small problems and as I say this is oversimplified the real smart rocker We have lots more problems lots of more agents, but that's a sample you have these and This is the point to go you have the smart rocker Just split the problems and you model the agents and train that I'm going for retraining because Other thing that you have here is it's very easy to retrain frequently when you have Continuous data like it's this example. Okay so Evolution strategies are a very good solution for optimization problems and They are very useful in multi agent implementations Okay, and they can solve complex problem if you go for a previous analysis phase that the split every Problem in simple problems that can be solved in a multi agent environment The training times are very few very small compared with all the other model solution that you have available today and Even very few for all the power they offer to you and And these allows are I said and I will say again and again You can retrain you can real-time retrain your models and this is very very good You can do that with any model you think it's only a few models that can do that and here you have a Model that can't represent any function You want for any volume of data that can scale and that can be retrained it Continuously continuously as killer is fantastic So if you have multi agent system based on CMAS or other ES you want but Important that will be a scalable and within modern approaches You can massive Parallelize across three units cluster. You can invoke tons of flow or you can invoke a spark clusters and get Retraining and retraining and important but you have multi agent You only have to retrain one of them because all the the others are clones and you can spread The new model the new values of the best solution across all the new all the clone instances of the agent so You will have lots of solutions and you will have everything you need and I Think I've been a bit too quick so Thanks for coming and this is the time when if you have any questions, and I hope you have lots of them you can go through it. Oh that's a Difficult to compare because you need to compare the wall system and the multi agent system many times Don't go for wall training when you train a RMM you are training for resolve the complex problem the wall problem and when you go to train this CMAS this small agents you are going to train only a small part of the problem So your wings have to be a better time in the CMAS But that doesn't mean that it's a better global training time but if you Try to scale and get a similar Circumstances on my experience. I still think that the CMAS approach. It's more flexible and also Faster that the standard training of our RNN and There is another point very important here when you are training a CMAS you are not Conditioned by the back end you are trying in a neural network often you are going to decide to go through Keras and go with TensorFlow and always on a GPU or a cloud of GPUs You are stuck with the architecture of the back end, but here you don't you can train on MPI with the local Computer because you have a good GPU or you can go with TensorFlow because you want to explore all the tensors and all the Or you can go with a spark or never you can go with any computing cluster You can think because you just have to model it and you have training it and Model expression trees is kind of easy because it's one of the simple binary trees that you can model Well, I I tried to I Try to solve the same multi-classification problem standard classification problem with you have some patterns and Some categories and you want to know if your pattern belongs to one or another category and In my experience what we have is similar It's difficult to say similar because as I said before I I trained it The bulletin strategy using a spark back end and I trained the neural network using TensorFlow with the GPU but The training times are similar But the execution time the activation time are far far far away So I said Using TensorFlow over CPU for solving a similar problem small problem, of course The training time was similar, but the execution time the activation time of the neural network goes through 20 seconds instead of the 160 mile seconds of the expression tree and both problems were achieving similar loss after a training but the activation time was what is killer for me here and Think about this I Don't say that you don't have to use neural network What I saying is that you can use another things about a part of neural networks You have to think on your problem first and you will have to go for the best solution and this one is a very good solution especially when execution time The activation time not the training the activation time. It's a really important factor for you Thanks to you Hi Thank you for the look I have two questions The first one is have you used this approach to solve real-world problems or just this is kind of experiment Well, I personally use it When I was doing the comparison from NLP problems with our classification problems when you are trying to generate text and well, as I said the The training was similar that is not a fair comparison because we are using completely different back-end from training but The the execution is killer. So yes, I try to it to help a problem real-world problems and As I say, it's very good for some kind of problem specific So for classification and optimization problems is very very good. Okay, and second one is what kind of representations Are you using only expression trees or yeah, I focus mainly on expression trees here Because I think Offers the best option for the execution time. Of course you can use and many people using it For training neural networks, and then your representation is the neural network itself then you can go for a improvement on the training fairly good improvement, but There are two constraints that you have to have in mind if you are going to use as a pollutive strategies for training for not yet for training for by propagation instead of a propagation using Evolutive strategies you have to think that Evolution strategies like to decide the shape of your network. They like a lot. It's very it's far better when you let the Evolution decide which is the better architecture inside the network and this is a Consideration because many people with using neural networks say this is my problem I go for an LSTM or I go for a convolution error network and They are a stack to this architecture and that's your best option is to go with a tons of flow standard training with GPUs and Which is usual for this kind of problems because if you really want to use evolution strategies are the guide For the training of a neural network you have to let the Evolution study to decide the inside architecture of the neural network Okay. Thank you. Thank you There is another question back there Thank you for the talk Thank you for comment a bit about CMAES, right? Yeah, and as far as I know this method works for Optimizing real value data, but it seems like you're using that to create these Expression trees. Yes. So how does how does that work out? Well, as you see the expression tree represent real Data as you say and if you want to go for classification problems and not for optimization problems, of course, you have to do a trick every other tricks can be done and you can you have to decide between several options to deal with the Declassification, okay The most usual it's to go not for only one expression tree But for an array of expression tree representing each one every category of declassification So what you are doing is representing what after is going to be your one hot encoding of the solution and What you are training every expression tree is for the site with is the best probability for those category So you go training all those Expression trees which are very fast for training very fast for execution that can be parallelized even for the execution can be Parallelized when you have this approach and the result is a value between 0 and 1 Which is the probability to be in this category with you have multi category classifier classifier Okay, we can talk later. I'll do it. Okay Thank you everyone for coming