I studied computer science. I took courses in AI and machine learning. I understand what machine learning is. I don't understand what AI is. So, I don't know, maybe you want to example it? Sure. I think AI will say, I mean, one of the things that I like the most about AI is getting a machine to do things that only people can do. So, I'm a shifting definition. How do you... Choose it. How do you see that? Machine learning is teaching a machine how to perform certain tasks or activities, the way a human would do it, or not as a human, but teaching a machine how to do something, right? And you generally can't teach... You can only... You can write an algorithm, you can write an algorithm that would do one thing, but if you wanted the machine to learn by itself, which is what machine learning implies, you start feeding it data, and then based on the base algorithm, it tries to understand how to use that data to make better decisions. So, what is AI? Because I hear a lot... It's a problem, sir. It's a... Machine learning is only one branch inside the whole area of AI. So, what else? You can say AI is automation. To some extent, it's not wrong. It's just to automate things. That people have been doing since the beginning, but now we're able to make it automated. So, that's in a very broad sense, but AI is... Internet also doing it, right? So, the problem is learning could be that... Wikipedia says it. A machine mimics cognitive functions such as learning and problem solving. So, I guess you're right. It's a very broad area. It covers a lot of things. It could be that more like brute force. Things like AlphaGo or Deep Blue just throw a lot of machines, right? It's more like brute force. It's not really like super intelligent, right? It's just like trying to use the fact that you can write many cycles of machines faster. That's another approach. I think we know the example of what Microsoft did with the bots. The Twitter bot went really badly online. I don't know if you guys read that. They still don't say it's artificial intelligence. It's not well-executed, but it's still... There was some learning. I guess you don't trust the internet to give you input here on learning and problem solving. I've had some experience writing a Twitter bot as well, just as a hobby. The thing about Twitter is that they try to catch bots that pretend not to be bots. So there's a team that finds fake accounts and they delete them. So one of the hobbies I have is to... I don't eat pads, but I keep them to the bots. So I write to governors that try to trick people to think that it's an actual person tweeting. So you can see there's something called intelligence as well. Mimicking intelligence. It goes back to the Turing test. Tend to be human in a conversation. So some technologists don't perform as easily to pretend to mimic a human to pretend because it's just text. Facebook is a bit more difficult because there's so many more mediums of sharing. There's more conversations going on in Facebook as well. So it's going to level me first. Are there any mediums of sharing? I'm just going to say that... One example. The way we use the phrase AI is like there's like all the shop. There's no like governors or the term. So it's difficult to put a box around it because firstly people use it. Salesmen might use it to sell something. And a researcher might recognize over what's in it and what's not in it. And depending on which researcher you go to, they will cut the domain into new ways. I was wondering whether just to put up as like a starting point like creating like concentric circles. And now I'm right in the middle. And context of the set you have AI. And context of the set you have AI. That you might talk about what's in one and not in the other. So I'm not sure about that. Does anyone know how the actual sharing test competition works? No, I have no idea. Well, I don't think it's a competition. It's still going on. It's still every day, every year. There is still a competition. I know the mechanics is... They get a test with people. Correct. With machines. Then you guess, and you guess people as well. You guess which are people. Yeah, so that's the important thing is that you have people who are testing. And on the other side there will be machines and there will be humans. But the interface is the same, right? Yeah. But from year to year they're like, how long do you spend? What type of questions you can ask? This can change. The funny thing about this competition is there are actually two of works. The one team wins. The one, the computer system which wins them. Which fools the most humans. Right? That's the best part. And the human who gets vote at least as a machine. Because there's another possibility, right? You are interacting with a human. But you may be marked as a... You may have to make a decision.  So humans get marked as machines. So there are two words at best. The most human computer and the most human human. Wow. So when you're talking about thoughts, right? At TraderBot. So how do you... Alright, just getting a little more of the next level of that. How do you train the bot to act like they do? What are you doing? Right. So what I did initially was I searched for tweets online. And I threw them to database and I changed around the words to make the tweet look legitimate and not a copy. But later on I found certain language processes online where you can create insult things a lot. So I changed the way the engine works when I created something. So it's just English structure based on certain trends that's happening in Twitter, things like that. So you end up with a bit like a soft bot looking like a teen with a lot of anger issues. I don't know about that. That seems to be... But I don't take input from the internet. So there are different ways to do that I guess. But learning is the... What Microsoft tried to do is probably the impacts of everything you learn. But I guess it didn't execute it properly because it just took input from anyone. I think there was even a 4th century that just attacked the bot about all kinds of strange things. So it depends who you open way to get your data from. So is your bot learning on the go? Currently... Currently no, it's not learning on the go. I'm not letting it just take input from anyone. I'm collecting inputs and putting it in. So where would that, on a spectrum of AI versus machine learning, call like, is it... Because it's not learning, does it imply that it's just like an artificial intelligence? Because it's not learning, so then is that machine learning already being a bit separate? It's fancy I guess. That machine is a bit... Between machine learning and... I wouldn't call it machine learning yet. Maybe just control learning or something. I don't know whether that's the thing. Because essentially you've set its parameters, right? You're saying that... I mean it's very unlike a human where a human is taking input from the outside world, processing it and then trying to change. Whereas this one is very parameterized where you're saying you only can do this and this and there is no other way. It can't act on its... Well it does like on trends for example. So trending terms, one of the people is saying and trying to throw that into a language processor. So that is the part where it gets a bit of learning? A little bit. Does your language processors do anything with measuring emotions? Emotions? No. I do have certain guidelines. I try not to... I prevent the bots from tweeting. Because you'd be surprised how many strange words there are which you don't want the bots to be saying. Do you apply sentiment analysis before you post? Do I apply what? Sentiment analysis or something? I'm looking into trying to do that. Something to... Emotional, trying some emotions. James Penny Baker. He's done some research to pronounce and how it reveals certain emotions. Who's that again? James Penny Baker. James Penny Baker. Does anyone watch this series called Personal Thinkers? Yeah. It's a very interesting series that is run by Jonathan Nolan. Christopher Nolan's brother writes most of the other movies as well. It's essentially an AI system that I don't know, is very classified right now. But it's an artificial intelligence that takes data from all government feeds. And then, based on that, it can move its own location if it feels it's under threat. By that, it means that it could issue commands to people as if it was issued by a woman to move its location. To some extent, that's what the person is saying. It's a learning machine, so it essentially runs a lot of simulations. And based on that, it could tell you what is the more probabilistic positive outcome or negative outcome. I use this big data. It collects all the inputs from all the security cameras. So in that series, they don't explain any of the machines working, but in the initial stages of the machine, there is a part where the machine essentially learns emotions based on its administrators' past events. Has anyone got any experience in how does that kind of stuff work, where you kind of get a machine to understand emotion or empathize, right?  So it kind of sympathizes with them and says, oh, I'm sorry for that, right? And that logic is kind of not present, because... I think humans are really complex creatures, so understanding emotions. Our emotions change even hour to hour sometimes. Yes, it's very... based on the conditions of the events, like the day you can suddenly decide if you hear something badly, so... You might as well be yours, and you should see your friends. Yes, while driving, there's an accident in the next car, and you see the police or the next car, and suddenly you become a man's officer. We don't need any form of biofeedback from a human, so it's really difficult, I guess, from just... maybe facial recognition could come up, I guess. Since sometimes fiction movies are a little bit of a present space, and we try to get an emotional or emotional profile of the person. You could also analyze the text strings, for example, tweets even from someone writing a tweet, and then you could measure some emotion and get some traits. Have you ever... Going back to your... to your algorithm that you wrote, have you ever taken into account the response of your tweets and tried to... Adjust your... Not much time I spent on this weekend, so I'm actually looking at... looking at the emotional aspect of it. Right now, I'm just trying not to get bad to put it down. I have like two plots, about a thousand to two thousand followers each. Are you sure all of them are... Are you sure all of them are plots? People are like experimenting with plots. So there won't be... But they've been online for a few years already. Yeah, so plots following other plots, and then you become just like... I mean, the plots are actually in some of the year, and then you are experimenting with plots.  And like a thousand, like... Like a thousand, like... Like a thousand, like... I'm just going to pick up on the point that you mentioned on looking at the words yourself. I think one area is in AI, like, probably in machine learning, you'll use a lot of supplies and super-buyers and in the AI limbo that falls under things like reasoning, things like learning and things like problem solving. These are the words that guys use in AI to kind of equivalent the machine learning to you. But beyond that, there are all these other things which are a bit funny. One is actually knowledge representation. So I think I want to actually mark this as a motion, like, very much. I was quite interested in how the way you represent like a chessboard to a program. What is it? Is it like, you know, 64 columns or like, category variable? Is there something more? So knowledge representation is an interesting one that is kind of within ML maybe not within ML. The one that's within ML and maybe not within ML is perception. And again, when we talk about things like imaging around that, it's powered by machine learning but for a program to know that it's hard. And the same program to also know that I'm near to a wall and the same program to also know that I'm going to do this thing because I'm near to a wall. That perception thing is something that is peace beyond the machine learning project but it's been all in AI. So I guess what I want to say is the knowledge representation of the world is very, very important. And now I'm going to a space that I've not done before around my own excess. When you use natural language processing and all these space represent words you want to see whether this is a happy, is this to the guy happy? Traditionally what you would do is throw in a bunch of dictionaries, these are the words, ecstatically it could be plus five. I'm only happy with plus two and okay, like terrible between things and I'm okay. This is a happy because it's more positive but another way to represent the same data is a word to back sense of that word to back that way where basically every word is represented by a black box of concepts. So if you look at what does the word when in word to back representation you'll find a matrix of like hundreds of numbers which we don't know what it is. And the reason why this is the case is because a man has a gender flavor to it. A man has a person flavor to it and some things all these things are encapsulated is we are representing the word man. So my colleague actually did a demo where we use king minus man equals queen king minus man equals queen. So I think representing data is at the heart of the data we need to make more intelligent things that are possible to make out of this data. And so I think to make a board recognize a motion of recognize meaning, the concept of meaning will really be around the way we use. I think the current record for the most complicated word is word to break. Like if I'm going to take a break, I broke this thing, break credit, give thanks, whatever. I think there's like 70 different meanings to the word to break and it's because of many meanings and characters they want word therapy to represent words in a way that's more complicated than the word. Man was one of the words that I came across on Twitter. He told me that very often man is hot. Old man. Like what? It's very interesting. So each word there's a whole matrix of data and then king minus man. So I think those of you who are interested as a whole one is every word is represented that's a word to break. And the other one is the more difficult one where every sentence is represented where it's like oh man if man thinks oh it's probably not real and you know that kind of thing. So this bit I'm not sure if I'm able to link to it. It's also a menu. From the take away from it is English is probably not the best one to do that in a setting. Is there any kind of what kind of line edge is best for a machine learning? Of course, yeah. Not really. The chess example that you're discussing and the probabilistic values that it gives does the machine remember or is it does it do it? Does it remember all its calculations that it does so that it can lose that in a future scenario? That's one. Second, is it efficient to do that? Definitely yes. One of the things that you do is you make moves within one game. This is what I'll be talking about. We talk about playing games and you make moves. You might move your movement. So after your move it's going to be my move again. I remember what I explored and the possibility space that I explored in my previous move I could build more on top of that rather than clean state every time. Is the probabilistic number changed? The number is 0.6, 0.7, 0.9 So it changes that and it keeps record of that over time. So that's how a single kind of body grows in the sense in the sense of exploring more possibilities as you play longer and longer. It's learning. It's the way I think the humans would learn. Although us as humans for the body it's easier to do it. As humans if you make a move you remember that move whether it worked or not but you would not have a set that you had thought about all these 5 other moves which the next time you play a game and you find a similar scenario you would simulate that one move. The machine says it's actually very simple statistics. It's just counting how many of the future games I might want. That's it. I mean in a very simple way if you just do that it would work pretty well. Just count all the futures I tried out 5% I have won. It's probably not a good place to be. 5% I have lost.  So it's like humans produce map of that. But in your case there was like trillions and trillions of possibilities. How do you integrate all of them? I think I can talk about that. So the idea is to get back to sampling. So we can't do all the trillions of possibilities that we over time will sample the space. Remember how many times we did this. Wouldn't you limit I am just actually really wrong. Wouldn't you limit say if there were 10 minutes to 46 I think right? Yes. If you limit to a certain number and get different machines to run different numbers and then go against each other where all the possibilities are mapped so if they all say if a certain state had 4 possible futures in Ireland you run against each of them and since it's a machine the other side could run the other possibilities in Ireland and then keep a record of all that which could then be collated into a single machine. Is that how it works? They do exactly that. What's why you have a cluster of machines? Because it's randomly random futures Each of the machines could look at a different random future and you aggregate the statistics and you do exactly that. I didn't I learned something. That's what I wanted to learn. That's how much things work. What happens in scenarios where there are defendants how do they resolve this? What do you mean by that? Like say for example there's a scenario where so the variables are not independent right? The variables are dependent where if one variable did something it would affect the other variable or the output of the other variable then something else would change. How do do scientists or researchers start to solve these problems? It's too hard of a mathematical problem or computational problem that it's worth making just guesses of certain things and running with them. There are many ways to paralyze or distribute the computations that we can utilize many machines so I think one of the ways you can do it is just do it at the very top where the very first move we're going to make and that's clearly going to be independent because after the risk is off we try to do it less than inside I guess it's more complicated because you say if I take another move with mine Yes so for example a certain example where say there's the idea of independent variables and variables and there's some curve around it like the idea was that a grandmother has finds a lady has 500 and she gives them every year a chocolate or on New York now she needs to decide out of 10 chocolates she knows from some past data that out of these 10 chocolates every child likes a certain chocolate but then there is a dependency so if the first child takes a red chocolate the second child because his tendency is to take whatever the first child takes he takes a red chocolate so trying to guess what is the best allocation of chocolate that needs to be there there are too many possibilities so what happens in those scenarios like chess is still a confined problem in this case because the dependent variables are changing and it seems very much dependent how do people look at such problems I think that the traditional technique there is always just to look at the part that are independent and try to break it along those lines I mean even look at probability, distribution of the multiple variables such a very complex form because it's going to be, you need a lot of numbers actually represent the distribution of the 10 variables for example each of the combination of 10 variables they have one probability so actually you need a very large even to represent this distribution it's very complicated so what people do is probably these three are dependent and these other three these two groups are not dependent so you can factor two separate distributions which are half the size in some sense and then if you get the joint distribution just multiply because it doesn't depend if it's a multiplication so the problem comes in that you just break it into smaller subgroups that are usually as independent as possible you figure out where are the groups that are independent and leave the dependent ones alone because they are dependent but you can't break it further I think this question is really an idea of a habit so quite long into it but I think I see like two approaches to approach the problem and it depends on who you are so within I guess like some of the size of people there's like almost like two religions one of the people who have gone up through the mathematical modeling and statistical modeling and when they see dependent variables they will use their intuition they will do interviews and try to explicitly account for all these things so you have like 10 variables plus a whole bunch of log variables and you will hand code these things like I will account for all these things that I expected there are schools of thought which I work via the the comm science and now kind of just like you meet the testers with black box I don't care how it works but it works better than it do so hard and so they will just like start that I won't use anything linear I'll use extremely non-linear thing like how I was drawing new network algorithms that would code up its own features and I don't even know what features they're coding up but you can account for dependencies, multiple entities all these things I don't know which ones they're counting for or how but they by choosing the right algorithm and putting in a really how kind of so depends on who you are I've seen both of these things go in parallel and the stats points are actually pretty good but they are understandable like you know yeah I've seen both of these marks and I got semi-accessible you know what I tell you what's going on that guy is like thank you but I don't care and every day you get me through guys like but it's a very classic example from statistics for classification it looks like spam filtering maybe it's an email spam or not and then the early days the base so that example I was trying to like this where I was trying to understand NaE base there actually is to just make a simplified assumption pretend that everything is independent even though they are dependent in reality but they just pretend they're independent and it looks really well actually even though it's not the assumption is wrong but I think we still don't fully understand why that's the case but don't just ignore the problem pretend it doesn't exist then move along and see but it still works out in me sorry we have to go okay we have a lightning dog scenario thanks a lot


Want to learn about stocks, cryptocurrencies, NFTs, and the metaverse? Join RichTV.io. Everybody doing today. I'm your host Rich, here on behalf of RichTV Live with our very special guest, the corporate development manager of Neo Battery Materials, Danny, huh? How are you doing today, Danny? Very good, how are you? I'm doing fantastic. Very excited to have you on the show today. And Danny, we're really, really looking forward to learning more about the developments over the last year for Neo Battery Materials. Can you start with a refresher on the company by giving us a brief intro to Neo Battery Materials and the Silicon Anode Market? Yeah, sure. So Neo Battery Materials is a technology developer of low-cost Silicon Anode Materials for electric vehicle lithium-ion batteries. So our Silicon Anodes enable ultra-fast charging, so which cuts down the morbidly long charging time of batteries to date and extends the run time of the battery by increasing the capacity of how much energy the battery can store. And it gives an overall reduction of the battery cost through our proprietary one-step manufacturing process. So we're actively in the process of evaluating and optimizing our Silicon Anode Materials called MBM-SIDE, with multiple large players in the global supply chain, such as battery manufacturers, EV automakers, and chemical material companies. So in 2022, we have completed the construction of our R&D scale-up center, in which we use pilot-scale equipment to manufacture, evaluate, and test our products. And in South Korea, we are planning to construct our commercial plant that will be capable of producing about 240 tons, that is 240,000 kilograms of Anode Materials per year, with a fully extended capacity up to about 2,000 to 5,000 tons per year. So the reason why Silicon has become such a big subject and a hot key word in the battery industry is because on the theoretical level, it stores about nine to 10 times more capacity than graphite, the current material Anode option for today's lithium-ion batteries. So because of this, the industry is expected to grow up to 15 billion USD by 2030. But however, there is a volume expansion problem that Silicon faces during the charging time, and this technical difficulty is quite hard to solve. Although there may be several competitors in the industry, only three globally have been able to commercialize their technology. And because Silicon is a early-stage technology, no dominant competitor or technology exists yet today. So it's safe to say that the Silicon Anode space is a blue ocean industry right now. Exciting. We love that and we love electric vehicles and everything that is affiliated and associated to it. I think one of the main questions a lot of people are wondering is what really differentiates neobattery materials from competitors in the sector. Yeah, so at Neobattery Materials, we not only work through the volume expansion problem that I have just mentioned, but we are actually the first in the industry to offer a unique manufacturing solution that uses the lowest cost Silicon inputs for our Anode materials. So currently in the industry, there are different solutions to solve the volume expansion problems such as nano-silicon, silicon oxides, carbides, or nanowires. However, most of these processes are quite sophisticated, complex, and energy-intensive to make. And when we double this with expensive inputs to manufacture these anodes by intuition, it translates into a scalability problem, which means a lack of scalability. So because not a lot of materials can be produced currently in the industry, the per-unit costs of current silicon nano-app options are high with unattractive selling prices to the downstream, which are the battery manufacturers and the EVO units today. But our company uses a highly scalable one-step nano-coating process, which is a simple and energy-efficient process that we use. So we do away with the current industry conventions, but we use a straightforward process that coats low-cost nano-coating materials onto the silicon. Now, what this does is that it effectively controls the volume expansion problem experienced as a technical difficulty. Along with this, we're the first company in the industry to use and enable a 10 times cheaper silicon input called a metallurgical grade or for short, middle of silicon. So the cost effectiveness and economics have highly attracted the interest of battery manufacturers and EV automakers to our company. And industry experts have given us the approval that this is the correct direction to take for silicon nano-development and commercialization as well. And in terms of performance, because we just use the silicon itself and there's a nano-coated layer on top of that silicon, our silicon provides a 70 to 80% higher initial capacity compared to our competitors. So along with validation from the testing parties that we're currently holding testing with, the equivalent of loading 5% of our materials is the same as loading 10% of our competitors' materials. So this means that a smaller amount of our silicon anodes can give a much larger boost in the runtime of the EV batteries. And in terms of the manufacturer's perspective, they can have more cost savings because they can use less of the materials but realize the same runtime and ultra-factor project characteristics using our silicon. So we're confident to say that our differentiation in both strategy and technology gives us the great upside and one up to performance, economics and the bargaining power relative to the industry today. Danny, can you tell us about some of the corporate developments over the last year and what are some expected milestones for 2023 that shareholders can look forward to? Yeah, absolutely. So to date, we have over 40 NDAs signed that includes large global battery manufacturers, EV automakers and chemical material companies in the industry. So because of the attractiveness of our products, especially the differentiation, we haven't been able to nurture significant relationships with them. We're actively going through sample testing and optimization with these parties and they are returning positive feedback and results. And actually in the last week, we have talked with a battery company that focuses on the fast charging characteristic and we are going to provide samples for them in February for material evaluation. And along with this, with a European-based battery cell manufacturer, you're advancing to a larger format power cell test of our materials after completing a successful point cell test. So as I have briefly mentioned in the beginning, this is largely enabled by the completion of our R&D scale center. In the past, we would have samples being sent to different facilities for the nano-quoting work and the post-task work. But this year, we have prepared all the necessary pilot-scale equipment to manufacture and evaluate our silicon anodes in one place. So this allows for quality control and real-time improvements. And because the work is more efficient for the engineers, our products are being optimized at the fastest rate so far. So we're currently matching the specifications and requirements that these large EV battery players are asking us. And their feedback, again, with our results and development direction have been highly positive. Once certain levels and specifications are met for these manufacturers, in-vectors and the public can expect milestone deals to occur with these players. So these can include joint development agreements, off-paker agreements, collaboration agreements, and also joint ventures. And these joint ventures can extend to funded expansion into the North American and European markets, which the lithium-ion battery sector and the EV sector are rapidly growing. So although a little different by the agreement, the important point to take away is that the collaboration with large players will allow us to access greater infrastructure, capacity and resources, personnel and expertise to advance commercialization to the next day. And we're in discussion with many players in the industry to find an opportunity and we are confident in achieving our next step milestone deal. Fantastic. And can you give us an update on the progress of the commercial plan being constructed in South Korea? Yes. In December, we have submitted the construction permit to the city and we're expecting the approval to come out by the middle to end of January after the due diligence period ends. So once the approval happens, we'll first start with the initial construction work, which includes the site clearance in which the debris is removed and also the basic civil engineering of the plant itself. And concurrently, we'll hold a bid process to select the best contractors for construction. And along with this, our commercial plant engineering team is also in the process of completing the detailed design of the max production lines that will be put into the commercial plant itself. And we are on track to break ground as soon as possible. So we're expecting to complete the full construction by the first half of 2024. And because the commercial plant is situated in such an advantageous location in the batteries supply thing out of the South Korea, and South Korea is the second largest battery manufacturing country in the world. And once we start rolling production in 2024, we will be able to capitalize on our growth strategy and we'll be able to convert cash flows very quickly. Great. How much money does the company currently have in the bank? And do you feel that you will need to raise any money this year to accomplish your goals for 2023? Yeah, so last year we received a strategic investment of approximately $3 million Canadian from AMP into NBM Korea, which is our South Korean subsidiary. And our operating activities currently within the scale of center and the commercial plant are being financed by this investment. So currently, obviously we need to prepare for our commercial plant and the initial construction work that will happen after the approval happens. So we're in discussion with South Korean financial institutions to secure strategic financing. And along with the province's officials in which our plant is situated, we'll target a non-dilutive funding opportunities related to clean tech and ED policies initiatives, which are growing in South Korea. And last summer, we had an MOU with Gyeonggi Province in which our commercial plant is located in. And with the province's officials, we have a high likely probability of gaining access to these non-dilutive funding opportunities. And we will let shareholders know through the subsequent press releases. So progressing our corporate activities are very important, but we also prioritize protecting and maximizing our shareholder's value. So as we are in discussion with multiple parties, we aim to secure the strategic investors. For the long-term, they'll provide synergies and enhancement to the capital structure and also business initiatives. So further comments are quite confidential. So the investors in the public can expect us to provide a new update through usually. That's great. And Danny, is there anything else you want viewers that are watching to take away from this interview today? Yeah. So just to summarize and re-emphasize, a neobattery of materials is in the best shape in terms of both technical and corporate advancements today. And our strategy and commercialization plan are clearly defined and we are on track to go to the next stage. So with our already-scaled center up and running with polished-scale equipment and a hard-working engineering team, we are at the fastest rate of manufacturing and optimizing our silicon anodes through real-time improvements in the lab itself. So this factor turnover time for feedback means better product performance and our time to achieve milestone deals with large players of the industry will be much factor going forward. And also with the construction of our commercial plans in South Korea progressing, management and the engineering team are working hard and we hope to deliver good use and milestone deals as soon as possible. That sounds great. And Danny, what is the best way for anyone who is watching to get in touch with the company? Yes. The best way to keep in touch with us will be to email our corporate email, which is info at Neo Battery Materials. But we do hold webinars quite there or not. So if the public and investors can look for other webinar updates, that would be great. Fantastic. We are interviewing today with the Corporate Development Manager of Neo Battery Materials, Danny Hu. I also want to remind everyone that Rich TV Live is strictly for information and education purposes.  In saying that, we believe this is a company that is undervalued, underappreciated and under exposed. Put your attention to the symbol in Canada, NBM. The symbol in America, N-B-M-F-F. And Danny, thank you for joining us today. All right, thank you so much. Always a pleasure. We wish you the best of luck in your future endeavors and we will be watching you very, very closely. And for those of you that are watching, if you're not winning, probably not watching, we bring you the winners. We bring you the news, CO interviews, chart analysis and we bring it to you first. Thank you for watching everybody. And Danny, thank you for joining us again and we'll talk to you guys soon. Have a nice day everybody.


thing why he looks like the black adder when he's lying but that's one of those things that instantly stuck out that he looked like a little child lying to me at that point Chase, what do you got? Chase already went didn't go just quickly imagine that someone's reading a transcript to you and they're talking to another person they say you're at this party, you're sweating all of these people, you're drinking, there's an underage girl walking around in her underwear and you say or you hear the person say no, no, no, there's a problem with that and it's with the sweating and nothing else is denied nothing else is denied so there's no denial it's not answering the question he goes back to focusing on these minutia that are insignificant as if the underage people are not an issue but the sweating is somehow a crime that he needs to defend himself against and then he borrows authority he's borrowing authority from his military career kind of redirecting the story I was in the Falklands war and this lack of sweat ability is called anhydrosis it's usually most of the time it's medication reactions or some kind of genetic inheritance and extremely rare cases to my knowledge in my education this happens mostly in animals that if they are attacked the receptors are receiving too much of adrenaline or epinephrine and they start to downregulate it which is almost never the case from what I've researched, that's all I got she was very specific about that night she described dancing with you and you profusely sweating and that she went on to have bath possibly there's a slight problem with the sweating because I have a peculiar medical condition which is that I don't sweat or I didn't sweat at the time and that was oh is she yes I didn't sweat at the time because I had suffered what I would describe as an overdose of adrenaline in the Falklands war when I was shot at and I simply it was almost impossible for me to sweat and it's only because I have done a number of things in the recent past that I'm starting to be able to do that again so I'm afraid to say that there's a medical condition that says I didn't do it so therefore he froze he froze check it out oh my lord I'm suspicious no he's frozen so we wait on him let's go around and cut back to him so it's his turn alright so let's throw it around the room and we'll all wrap it up and we'll go with Mark chasing Greg Mark what do you got the biggest thing for me is that this is authority behavior baseline so he's as Greg might say on the griddle here this is a real worm on the griddle for him though you might see still some levels of authority compared to how he'd normally be totally outside the baseline that alone means some things going on here outside of the ordinary for him chase yeah this whole video is about a sales pitch and it's not about facts it's not about there's no certainty and there's no denials here that are confident or firm denials and anytime we're watching any video one of the first things I look at is that person's level of control over themselves in that interview that's the first thing I personally look for how in control of themselves are they and we see this is he is wildly out of control because he's wildly separated from his normal behavior Greg? yeah I think Mark he missed his chance to be credible by simply not saying that never happened that's all he had to say and move on to the next topic not try to over explain and you can see even when we are using this interview as a baseline the deviations we see from it when it gets a hot topic you can see the difference you see that chin protection that's pretty universal we talk about but then you see him using a little bit of chat and redirect and lots of other ways to avoid answering the question it surely looks like deception Scott what do you have? it's a great example of a bad attempt at lying because he goes through every cue you can just about nail in deception we're seeing him here and in our regular video I wonder what this is like two hours long we have a version of this go watch that you'll see everything in it some hot spots but it's a great example of someone who's being deceptive and we know he's being deceptive at this point and I think it's just a great example all around for that


Hello and welcome. If you are not here for the true cost of open source you're in the wrong room You need to use the exit go down the hall and find the right presentation Thank you for coming if you are here to listen to me talk about the cost of open source My name is Suzanne Ambele and I am with VMware. I'm our director of open source marketing and strategy at VMware and in in the spirit of Oss love from this morning. I want to shout out some Oss love to a couple of people in the audience mr. Hect from links Foundation research and from the new stack and Geeky girl Don dr. Don Foster over there my colleague at VMware open source love to the both of you. Thank you We get started a little bit about me You can see my Twitter handle there at Rosso vello. That means red bike I used to have a red bike it got stolen, but it didn't change my tag I have been at VMware for 12 years now, and I've been in tech for quite some time Work at a company called tandem computers. Raise your hand if you know anything about that. Hmm. I know how old you are And I also worked at Sun Microsystems anybody Sun Microsystems. How about Java? Yeah, remember Java days? Yeah So I've been around the block once or twice and my career started in broadcast news and public utility making Doing general rate case testimony for Pacific gas and electrics. I've had a very varied career These are some of the things I enjoy in life outdoors outside on my bike I have two Doxons paradox and that's me in the bottom right corner with my favorite gravel racer Sarah stern I have started to race bikes and I have absolutely no business doing that because somebody's got to finish last and That would be me So you can see my Instagram handle down there bikes nappy if you're interested to see what I follow which is bikes beer and dogs Okay With that the agenda today I'm gonna be talking a little bit about kind of our arrival our being open source We're arrival in the big time how we got there what it looks like What are the implications of that and then I'm gonna go into a little bit of a problem I see kind of lurking in some of the data and some of the reports that I've seen published as of late from Variety of sources and they're gonna go into a little bit to talk about some of the maybe the Causes of that we're gonna talk about some behavioral Economics and don't worry. It'll be fun. I promise we're gonna talk about demand and supply or supply and demand We're gonna talk about the free rider and the tragedy of the commons and that is not a Shakespeare play Then we're gonna talk about the consequences that are looming on the horizon because of this situation and what we should be Thinking about and how we should be changing and talk a little bit about the solution and then give you a little bit about an Opportunity for all of you to participate in how to solve the problem and how to start understanding the problem a little more deeply So that's what I'm gonna cover today, and I know I'm between you and lunch So I will try and use short words and finish early Before I begin I do have an econ degree And so I need to make my apologies to Adam Smith John Maynard Keynes and Milton Freeman and all my econ professors Because I am going to be taking liberties and if for all for all of you who may have an econ degree You may go wait, right like okay So I've been some of the rules to apply to the special circumstances that we are here in open source So and that is Adam Smith there in Edinburgh. So One of the econ heroes So as we get started I want to just kind of set the stage and set some definitions that I'm going to be using For this presentation. I define price as the economic value Assigned to an asset expressed in the form of currency and documented in the form of a transaction a purchase order Right a bill an invoice I'm going to define cost as something a little bit different Cost is the combination of the price that you paid plus any indirect investments That you have to expend to put that asset into productive use It's the price you pay and the cost you incur that becomes the total the total number And then value is the benefit that you gain or receive By putting that asset into productive use less any costs Ideally you want that number to be positive because if it's not you're upside down and you should question your motives for actually having that asset in production So keep those definitions in mind So today we know that open source is preferred study after study has said that customers buyers users They now prefer open source It's become kind of the lingua franca of this modern apps in cloud world that we're all in the middle of This study here, which was published by O'Reilly Media called the value of open source in the cloud era And you can look that up you can go get that little book it one of the quotes I pulled out from it was that Companies choosing multi-cloud prefer OSS because it meets their requirements and that 70% of respondents prefer Cloud providers that offer those solutions based on open source. So here's a declared Preference and at VM where I work a lot with our sales teams. They are asking me now What is this open source again my customers asking about it? What is it? How do I talk about it? So I know too from firsthand experience that customers are starting to express this preference and We all know in the application world that open source isn't optional It's a required ingredient of any application. We build today. You can't build modern software without open source Nor would you want to that would be a sort of a silly endeavor to to even try a study by IDC So showed that 72% of all modern apps developed that they they they scanned over that past year include externally sourced components no surprise and That external Components accounted for about 80% of the resulting code. So 20 so only 20 percent of an application is potentially Net new code the rest of it is reused Some of that may be open source some of that may be inner source where you're sharing proprietary code amongst applications But the fact of the matter is only 20 percent may be net new Here's another study picked up sponsor here synopsis This is their 2022 so open source security and risk analysis report And I thought this report was fascinating and I pulled out this one page This one slide that that showed that percentage of scanned code bases containing open source in the following industries From computer hardware and semiconductors. That's that first red box there all the way down to health care in the bottom Corner there, but you'll note that every single number there is above 90 percent So the percentage of those code bases in those industries that had open source is 93% or more and of those code bases 78% of the code was in fact open source That's significant right and this is starting to become you know on the surface and people are paying attention to it So let's sit back and give ourselves a big pat on the back We did it we be in the open source community. We've arrived We now have a seat at the table. We all knew it all along, but now we're being acknowledged as yeah You're here and as I am Brian Bellendorf said on Monday Good enough for the CIA and the Vatican at the same time Right, and I think he got that quote from somewhere else. I didn't write down the full citation But I thought that was a great line To kind of evidence where open source is today we've all earned this place at the grown-up table But we've also earned all the all the benefits and consequences of that confers. We've been proven to be reliable Safe secure mostly, but same with all software trustworthy mostly same with all software No different and for many that are now consumers and and rely on an open source. It's free Or is it? I'm gonna get into that in a minute But in all of this Celebration and all of this data that's after affirming our place in this whole ecosystem There's a small problem lurking and I've started to notice it in a variety of studies and let's take a look at what that's telling us So here's my first foray into econ. This is supply and demand Econ 101 and what I've observed. This is my own personal opinion is an unbalanced situation that's starting to emerge This is a question from the annual Ospo survey run by the to-do group It's also sponsored by the Linux Foundation. This is from last year 2021 data. The question was where's your company or Organization on its open source journey and you can see over the past three years the consuming is quite high But the supply that is the contributing is low And so there's this divide here that's starting to emerge and it seems to be consistent It's not it's not closing in some cases It's widening and you can see some interesting things happening in the data there And I'm really curious to see what happens in 2022 Because you know there was a thing called a pandemic so you know I think that influenced a lot of the numbers that we're seeing especially in this space so But but there is this this difference between what I consume and if I'm willing to contribute Now asking that question a different way The survey also posed how often does your company do the following things? How often do you use open source code for non-commercial or internal reasons? Use open source code for commercial products or contribute code upstream And this is just from last year 2021 so you can see frequently sometimes rarely never don't know The never line is 27% That's a lot. That's an astonishing number of people who say we will never do that have never done that and yet They frequently you know the frequent number is 62% and on that frequent code upstream only 20% So again, there's this big gap between I'm using it. I rely on it. I trust it I have to have it and oh, no, I'm I'm not going to participate Mr. Rostek Yes, yeah that that can be sorted out right So The the question the audience is do do you segregate between companies that don't have developers and can only consume and companies that Have developers but don't choose to participate for whatever reason and yes, you can sort the data by this I'll give you the link to the data you can go in and rummage around and they get how repo it yourself and Kind of sort all tease all that out. This is just kind of high-level pick of The the overall view of what's happening there So so there's a problem going on here And so, you know, it's I'm not trying to assert that for every gap There's a give there should there's not necessarily a one-to-one if I get one thing I'm going to give one thing but there is this this This notion that you should be Invested in open source if you are relying on it and if it is a central part of your code base You should have some Some participation level it shouldn't be rarely or never so what's going on behind the scenes? And this is where I think there's some behavioral economics at play so again economic theory some plausible Things that are happening in the background the first one I think we can all agree is something called the free rider syndrome and in economic theory the free rider syndrome is When something a good right open source is non-excludable open to all When it's available at no cost ie free, there's no currency Transaction, there's no barrier to access or entry. You don't have to show a credential or prove who you are or Interrogate it's just there for you It delivers Value in other words it's something you want it changes. It helps you to achieve a goal and it lacks centralized management or control Now all of those qualities describe an open source ecosystem pretty well a lot of people call the free rider syndrome the NPR challenge National public radio right they raise money. They have their pledge calls You know call now and pledge $10 a month and get a tote bag and There's a lot of free riders in NPR. There's a lot of free riders out in the open source ecosystem the second Thing that I think is happening or is it has actually occurred in some projects is the tragedy of the commons and This is a sort of a self-centered notion in economic theory. This is where individuals with access to a public or common resource Act solely in their self-interest for their own gain They let others do the investment and they just take and they know they're doing it And they're willful and they do that is their strategy right and as that happens and as more and more people adopt that Philosophy around this asset the commons where that asset is swiftly overrun destroyed ruined because Too many people took too much with too little investment back in Now another example of this is a freeway and traffic congestion if everybody decides that driving a car is The right way to go and everybody does it by themselves All of a sudden that freeway no longer works It's too congested. That's the tragedy of the commons You have to start acting not in your self-interest for that common asset to retain any value Now the last thing that I would hypothesize is going on is a little bit of the paradox of price and That's what happens when something has a price of free It has it automatically infers no value back to that individual because you haven't had to extract an economic cost From your your situation so you haven't had to make a trade-off So every month you have a budget and you can buy this or that and if you buy this expensive thing You can't buy those other three things. You've had to make a trade-off. There's a consequence to your choice now If something is free, there's no consequence to that choice. There's no budgetary impact. It becomes invisible Because it doesn't have a resource commitment assigned to it There's no line item in the budget. There's no purchase order or bill or invoice associated with your consumption So the result is the consumer of that good tends to treat that good with a little bit of willful disregard and Analogy I have for this situation is a water meter Okay, California is in the middle of an epic drought Hundreds of years. It's never been this bad. I grew up in town of Sacramento called Sacramento And Sacramento were by to the confluence of two rivers the Sacramento River and the American River and growing up We use water as much as we wanted whenever we wanted. Why? no water meter No charge. No one was counting so it didn't matter and Even today there are no water meters in Sacramento It doesn't matter and so of course water consumption Isn't being managed in Sacramento in the middle of a drought So again, if you put a price tag on it if you meter it and all of a sudden you're aware of it You start to understand your consumption of it and you you're better at managing it Now the last thing on the bottom of the slide is not an economic theory, but I'll just call it ignorance is bliss Now all those economic theories above assume For knowledge, I know I'm a free rider I know I'm part of the tragedy of the commons and I know this thing I'm using and has no price I know the last one ignorance is bliss is I don't know and I don't want to find out That is also I think happening quite a bit So a lot of this thought was inspired by a blog I read a couple years ago by Dries Who view the old tart somebody helped me with the last name? I know I butchered it This is written in September 19th 2019 it was called balancing makers and takers to scale and sustain open source and this is an Extraordinary piece very thoughtful writing. He's not an economist by training, but there was a lot of clues into this and It is a long blog Set aside a half an hour or more to sit down and really go through this and read this Really interesting this one poll quote. I really like which is the difference between makers and takers is not always a hundred percent clear Makers as a rule of thumb makers directly invest in growing both their business and the open source project Well as takers are focused solely on growing their business and let others take care of the open source That is the classic free rider. So there's makers and takers and not everybody can be a Maker Stephen Ross doubt some people cannot for whatever reason but most can Be a maker most can figure out some way to invest back So the result of all this free rider tragedy of the commons Ignorance is bliss and the the paradox of price is this great Illustration nobody says it better. I don't think there's a presentation without this right like there you go You have this one little stick in the middle Everybody's relying on it and that and and we're okay with that. Well, we shouldn't be we shouldn't be okay and What happens when we do that when we have this one little spike here and I'm gonna talk a little bit about the risks Involved in that and this is a hat tip to Don Foster This is a lot of the next slides are from inspiration from her blogs her writing and her Presentation that she's given at open source summits in the past and if you want to read more by dr. Don Foster You can see her blog link down there She's done a whole series on risk and open source and how to identify it and how to mitigate it and some of these thoughts are from that Some risks to consider our project ownership if you look if you're using open source Do you know real who really owns that or controls that project? Is it an individual benevolent dictator for life or solo pilot or? Is it company-owned controlled or is it foundation-led and community managed each of those poses different levels of risk that you may or may Not be comfortable with and may or may not have accounted for as a potential cost First projects that don't have a lot of adopters that should raise some alarms in your head The more adopters the better it lowers the risk because there's more people Contributing to it that you can look to two more types of risk or security Right lower risk projects have documented processes So you know what happens how people collaboratively make decisions how things get posted and we're mediated and then a Risk is also involved if you're too distant from that open source project and unaware and connected to it Technical debt starts to mount very very quickly and technical debt is one of the most expensive debts You can carry on your books largely because you don't know it's there and I have a sea turtle picture there because Finally, you know, it's only fun being underwater if you're a sea turtle Other than that it's not a whole lot of fun to have all that technical debt around your neck and then ignorance is bliss Recall that studies show that up to 80% of a code base could be open source and If you don't know is my code base 80% 60% 20% If you just don't even know how much is open source and you don't know what open source there is That's kind of an 80% gap an 80% blind spot and the thing that you're building and shipping and That should make you very very nervous So again going back to price and cost and value and revisiting those definitions Price is that dollar amount you exchange To get that asset value is the benefit that you get from using that asset and Cost is the combination of the price that you pay and any indirect investments You have to make to get that productive use and I will assert that cost is where surprises are likely to happen to change your value line from a positive to a negative Right and all of those risks that we talked about before are actually cost in disguise So risk is cost in disguise it's a future cost of Unknown magnitude That must be paid maybe tomorrow Maybe the next day Maybe in two months Maybe every single day for every single thing that you're building But the point is you don't know if you don't know what you're using and you don't know its state This is a huge problem for you And I think this is where I see this supply and demand gap growing where people are adopting open source and embracing it as you know kind of the the superpower For their code, but at the same time these same companies aren't willing to contribute and Some of these same companies that are enthusiastically embracing open source are also enthusiastically prohibiting their employees From participating and so there is some cognitive dissonance happening there We need to start thinking about and understand why a company would say no way never But at the same time say I will consume nothing but open source, right? There is some dissonance happening there that kind of need to look in the mirror at so how can ospo's help resolve this difference and I think ospo's and You know ospo like groups within companies or even individuals can really help to lean into this and identify this problem To management you've got an 80% blind spot. Let's start talking about it Let's start having some uncomfortable Conversations maybe in certain circles about what you need to change and how you need to change So the first thing I think an ospo or an ospo like individual They can start having some guided discussions or conversations with their leaders which is all about open source what What are you using? Where are you using it? Do you have an inventory? Are you compliant with licenses? So this is a compliance starting point and that's often the place where ospo's start Are you compliant with the licenses? Do you know even know what you have? The ingredient list the S bomb right The ospo can then take that conversation to the next level which is asking that question of why Why that open source and not something else? Did you get here? Here being the consumption of that open source by accident You just don't know why is your open source consumption strategy ad hoc in the moment built of accident and incident For 80% of your code base Or did you arrive here by design with purposeful documented choices and ospo can help with that conversation and Help lay out what those checklist items might be to make smarter Informed choices and to document them so that the next person down the road will go ah, ah, ha You're using these things and here's why you chose to use things and why you chose to use those versions When that's documented now, you know now you can act on it when it's not documented. Where do you go? They can take the next step and say okay, you have these things you've decided to use them How close are to source are you how how much of a snowflake do you really have? What is your technical debt on that piece of code and how would you get to current is? That even possible at this point right so they can help you have those Technical discussions to figure out how to get yourself into better said and Then for that product and that open source component is it strategic? how do you know and If it is strategic What sort of commitments are you making to protect that investment? at VMware Dawn's group maintains a list of Strategically identified open source projects at VMware participates in and we keep our eye on that list because those open source projects are very important to us and To our customers and so we monitor those and we invest in those more heavily than we would others But we've made a decision. Yes, that one is strategic and here's why and We check in on that and we make sure that that project is healthy and thriving and has what it needs Whether it's something that VMware has originated or it's a third-party project that we're participating in but we keep our eye on that with intent Because it is strategic and we're making commitments to it The next thing an Ospo can do is help you check your contribution culture What is the environment that you've established for your employees? Are you a prohibit just say no? Are you with an ignore culture which is don't ask don't tell I just don't want to know Are you a tolerate culture that says? Well, if you must we'll make an exception just for you Or are you a culture that expects and encourages open source participation? Participation and you know, I'll say a little snide remark here Be careful what you wish for because it could end up being one of your okay ours I don't know if anybody has any okay ours going down, but So so there's a whole spectrum and it may not be evenly applied across a large organization There may be some organizations that may be on the prohibit end and others that may be on the expect and and Encourage and but again an open source program office can help establish a more positive Contribution culture one that's based more than based on more than just compliance. They can help guide you and give you tips and and best practices on how to engage in an open source project what type of Contributions right all of these things can help your your employees act with more Confidence and competence as they step into an open source community that may be brand new to them You know a lot of people said lurking and stalking is the place to start I'll use the word spectate. It's great to go to a project and spectate first Just listen and learn and watch and understand and then as you get more comfortable with it Then you can step in ever so Gently as much as you want to start to engage. I'll give you some tips on that in just a second The to-do group has an immense immense treasure trove of information for those of you Who are curious how to start what to do there are Our call it guides galore on the to-do group site how to create a program Measuring your program tools for managing your program how to use open source code wisely community participation The list goes on and on and on it's all documented. It's all great content. You can see the guide there For a lot of people reading isn't the best way to get through something so they also have training modules So they've taken that content and made training modules out of it again You can get that content for free on github. You can go down you can download each of the modules and you can read through it yourself But for many that's not incentive enough So sign up for a class and then there's seven modules and you're expected to finish each one and take a quiz Sometimes that is the great motivator to get through some content. So there's a several module program. It's formal It's on the Linux foundation. There is a cost involved So if you don't want to pay again cost price value Go to github and you can read it on your own But you may not be a learner that learns by reading you need to listen and see so again take advantage of all these resources if you don't have an open source program office today and Realize that you might need one because of some of the situations I discussed earlier and Less formally than that Here's some other tips if you are a consumer or user of open source in every single one of you is in this room step one Identify the open source that you deem essential or strategic to you yourself personally to your your project to your team to your department to your company and Then go to the source There's there a contributors guide. Is there a governance doc if there aren't read it? Study what's happening, you know be a spectator in that project understand what's going on understand where it's at where you're at What's the difference between the two and then maybe maybe on a big dare introduce yourself say hello To the maintainer say Thank you. I'm using your software to do x let them know sometimes that can be Just such payback for anybody who's worked so hard on a project to have someone say please Thank you, and then step three. How can I help? What do you need? I'm using this. It's giving me great benefit How can I repay that how can I help you? Now for those of you That are on the other side of the fence you're a project maintainer or leader. I asked three things of you one Update your contributors guide and governance doc or if you don't have one make one Doesn't need to be elaborate doesn't need to be fancy There are plenty of templates out there for you to choose from Cnc half see the CNCF has plenty of templates that you can look at and borrow from I would also say code of conduct Also very important for your project. So people understand how does this project work? How do I go from spectate to contribute? Make it easy Make it friendly ensure that you've got communication channels set up that you have regular calls that you have Frequently asked questions things that help someone feel comfortable at home. I call it hospitality Project hospitality make it a welcoming place and then step three be explicit Ask for help Here's my list of good first issues here are the things that I'm wrestling with here is my road map Here's what I hope to achieve. Would you like to help? Sometimes that explicit ask for help gives that person that over there that is a spectator The the courage to say I know something about that I wonder if I could help and now all of a sudden you have that two-way Exchange and then you're starting to bridge that gap between the demand for open source and the supply of people Actually contributing to it and you start to bring these two more into equilibrium another favorite economic term so as you engage and as you raise awareness of the consumption and use and the essential nature of open source in your In your personal life in your company in your department in your business you start to increase contribution You start to define the investment levels that you need put a line on them in your budget open source What are you going to assign to that? Are you going to sign resources? How much? Is it resources in relation to the amount that this that you are relying on this? Is there an imbalance there that you might need to fix? And as you do this your benefits will rise because as you get more engaged in the open source You rely on you get closer to source you get closer to that influence and impact You the that flywheel of innovation starts to spin so much faster And your costs aka your risks will start to fall As you get more engaged. So there's a win-win there and it's good for everyone. It's good for you It's good for the community. It's good for the project. So it's something you should really take a second look at so in closing What is the true cost of open source software? and like any good economist I'm going to say it depends It depends on a lot of things Where are you out on your journey? How close are you to source? What is that open source project? How are you using it?  You don't know But pay your dues Ignorance is not bliss It's going to bite you Many people that endured the log for shell log for j Situation were like do we have it? I don't know. How do we know? I don't know how we know That was a really big sort of pivotal moment for a lot of people and so ignorance isn't bliss It's actually quite frightening And then I would encourage you to operate with intent not accident have a strategy have a plan know the why Behind the open source that you are using I like this quote that came from joe betta joe betta is now a free agent He is on his own after working at bmware for the past four years But he said open source is a growing force for any company that deals with software and today that's every company And smart organizations turn open source from the source of stress i.e I don't know ignorance is bliss state To a competitive advantage where they understand what they're using they're investing it They're delivering more value back to that open source community and they're also reaping the rewards of that So be a smart organization And then last but not least i'm going to encourage all of you to take a look at the new research study That was released today. Hillary cardy carter talked about that this morning. This is the 2022 ospo survey This survey is in field now You can go to that link down there. You can read the press release You can get the little button that says take survey now I encourage you all to take that survey the richer the data set the better the outcomes the better the insights that We gain every year from understanding how each of you View open source how each of you are using an open source program office or something like it or not, right? It helps us understand where we are on this maturity what progress we have in front of us And then there's another study coming up hasn't been announced yet, but it's uh, dr. Henry Chesboro He's a faculty director at um, you see berkeley school of business. Um, he's an economist Uh, he's going to be doing a survey called the under understanding the economic value of open source and that is coming soon I've seen a draft of that survey. I know that he's working on that I expect to see that out in the coming quarter. So if you see that come your way Please I encourage you to also take that as we start to understand the real numbers behind the open source that we're using today and with that I went pretty quickly I want to thank you all for your attention and coming and if you have any questions I'll do my best to answer it. I can no longer draw the kanesian cross though. So please don't ask me to Thank you any questions sir I'm sorry. Can you say that again? Can you use can you identify any of the strategies or metrics you use to identify the The open source projects that are important to vmware Let's see don just left. Um, so don uses She's part of the chaos project. She uses beturgia. She uses auger. Um, we have our own Sort of criteria that we have internally about different types of technology like You know kubernetes obviously important to us We're obviously going to keep an eye on that and other sub projects But she does have metrics that she tracks and we do pull that data every quarter knowing that the data is Good but incomplete so it's it's directional It it's it's you know, what I've learned that capturing data in this area The closer you get to the data the less reliable it becomes because there's a lot missing right So you kind of have to step back and go directionally. It's looking like this So she uses a variety of tools But if you have some specific questions on the scripts that she she uses and how she does it I encourage you to read out reach out to geeky girl dawn Mr. Hect How do you um How do you see level of innovation that's coming from open source? Okay, so the question in the audience. I'll continue just a second is um, how do you capture And and quantify the value of innovation and the value of innovation from open source. I get that correctly Um, it is a conversation VMware's open source program office reports to our VP of research and innovation So innovation is near and dear to his heart and it's not a foreign conversation It can be a hard conversation for Some who are not accustomed to open source to say well, wait a minute You just invented this great thing and you're giving it away for free Tell me again how that works, but this is all about, you know, that that flywheeled innovation and sharing that that That initial spark so that things can grow that much faster What you do as an individual software company is you provide that differentiated value on top of that core That's how you have to have that discussion. It's a tricky one It's one that has to happen again and again and again before they get it. It takes a while Mr. Bork Suzanne great Session today congrats. Uh, just a friendly suggestion on that one slide. You talked about the spectrum of Yeah, you know ignore a taller rate And then you led to okay ours, I believe There's one additional stage if you want to really get radical and optimistic is incentivize And it would be great to get more organizations to actually not just Expect it but go the extra mile and recognize it in a meaningful way And it's one of the fights I've had in my travels because there's Plenty of examples of companies that incent patent creation intellectual property And Hold it up on a ivory tower and applaud it and at the same time they're consuming the holy out of open source and They barely put a toe in the incentivize pool Here here Incenting that rewarding that Acknowledging open source contributions. I think is critical inside a large company I know that google does that regularly they have quarterly awards and acknowledgement They published publicly on who who Who has contributed? We are still on that journey at vmware, right? Um, and and all of that does take time as people Understand that they really are standing on the shoulders of giants. Mr. Rostat Question. Yes. Um, I'm on the technical the lengths foundation technical advisory board or aka the tab We are working on a Rating system for companies on how well how well they support maintainers open source maintainers wonderful And that should be published. Hopefully soon Um, I don't want to say anything right now, but we're right now working on something We're going to probably go to a few companies that are open source Make sure that you know, they don't say hey, wait, we're not rated in this like red hat So like they know but uh, yeah, I expect that to come out and we're hoping that that could could help incentivize uh, as the Companies to reward maintainers a little better. Who doesn't want to get a good good great, right? It's the technical advisory board lengths foundation technical advisory board We're coming up with like a rating system that we're going to say these are the Qualifications of that puts you on a thing. It's going to be kind of a general stand like a System. Yeah, that basically says this is where each company is listed in their support for maintaining maintainers of open source projects We have a long ways to go to say. Thank you to maintainers Um, you know, we saw that slide in the in the keynote today that showed what there were some 100 projects with only 15 people the census to report is just Astonishing it how few people are maintaining such critical projects and how we need to really change Change the balance on that and really change this this this imbalance between the two All right. I think I am at time. I don't see my my time lady Holding up a red. Yes. Here comes the red sign right now Stop it says so with that I will stop and say wish you all a good afternoon And thank you for coming. I really appreciate your time


There's a practicality to the world of Blade Runner. Every element that adds style to the world of the film first serves a tangible purpose. These lights, for example, are for air traffic control. Take just about any scene in the movie, and every detail will add up to something greater. Blade Runner fits into the genre of realistic science fiction. In his commentary track, Ridley Scott stated that the two biggest films that had an impact on Blade Runner are Star Wars in 2001, A Space Odyssey. The former is essentially a fantasy film that was set in space, in the latter an ultra-realistic prediction of the future. If Star Wars is described as what if in 2001 is described as what will, then Blade Runner can be described as what could, or what would happen if people were to be able to recreate life. And the film's answer to that is the end of humanity. The film establishes this very early on. It's just about five minutes into the movie before we see a human, and it's this unnamed Blade Runner testing Leon's humanity. There will be more on this a bit later, but the ultimate irony of this scene is that the human shows no emotion, whereas the replicant does. When we enter the streets below we're presented with a number of reasons why humanity seems to have dried up. One of the most apparent is the lack of communication. Throughout the film characters struggle to understand what others are saying. What? I said throughout the film characters struggle to understand what others are saying. What? Forget it. In addition, the languages spoken on the streets are a jumbled mess of English, Cantonese, Spanish, Japanese, German, French, and Hungarian. There is no uniformity, no great connector, instead just people isolating themselves from one another. Moreover, people are looking to leave Earth for off-world colonies, further distancing themselves from one another. In the off-world colonies, the chance to begin again in a golden land of opportunity and adventure. But the biggest cause of this lack of humanity comes from the replicants, or at least the creation of these replicants. From their conception they are told that they aren't human. They're created with an inferiority complex before they are enslaved. As we are told in the opening credits, the replicants are equal to or superior to their human creators, and the humans enslave them, devaluing their own existence. The film is over one-third of the way finished before we see our first decent and human act. J.F. Sebastian invites Pris up to his house. J.F. is one of the few characters with humanity in the world. He really cares for others and shows compassion, this compassion which ultimately leads to his demise. However, it isn't a total loss because his compassion sets in motion a series of events that becomes a central focus of the film, characters gaining humanity. It starts with Roy Batty accepting his dwindling amount of time left alive. From his creation, Roy was given perfect intelligence and health, but as Tyrell tells him, that comes at a cost of a shorter lifespan. The light that burns twice as bright burns half as long. Before he came to Earth, he clearly put no value on human life. They slaughtered 23 people and jumped a shuttle. As we are told, Roy and the other replicants massacred the passengers aboard a cruiser, and once they reached Earth, their reign of death and destruction continues. All of this killing was for one very ironic purpose, to extend their own lifespan. However, upon being told that this is an impossibility, Roy, the last remaining offworld replicant, has an existential meltdown. He has hours of life left, everybody who he has ever been close with is being retired, and Deckard is quickly closing in on him, trying to end his life as well. During their confrontation, Roy finds out that he is superior to Deckard in every way, and looks to beat him both physically and then mentally. He begins by breaking his fingers, essentially stripping Deckard of his power before moving on to show the flaws and morality that drive Deckard and the other Blade Runners. They are attacking and killing the weak, social outcasts who are unarmed. Deckard is a character who clearly has a conscious, so during this confrontation, Roy succeeds in stripping him to nothing. Despite this, when Roy has the chance to let Deckard die, he chooses to save him. You could read this scene as a visual representation of enlightenment, of Roy pulling Deckard up to his level to show him that there can be good in the swirl, and that life has value. Just because he was created instead of being born, he still understands the importance of existence. All of this killing served no purpose, and killing someone else would achieve nothing at all. This is then reaffirmed with his final monologue, a beautiful soliloquy praising the value of human life. Reaffirming that even when society tries to strip down everything right in this world, one simple act of goodness can have a drastic impact. And just like Roy was inspired by J.F. Sebastian's Goodwill, Deckard is too influenced by someone who he once believed to be subhuman. Throughout the entire film, Deckard struggles trying to find any purpose in existing. He has been beaten down by the inhuman world and just exists. And everything from his attitude to his drinking habits to his attire, Deckard is clearly influenced from the film noir era detectives. And like film noir era detectives, he is unwillingly forced into the story, and his ultimate goal to movie is to find a way out. He wants to leave this world and to exist somewhere that he can be happy. Whenever people get close to him, he turns them away, even if he ultimately cares for them. He has been conditioned to view the world as evil. He dreams of purity, of being more than human, as we see in the unicorn sequence. But he doesn't achieve that until he comes face to face with humanity through trying to hunt the replicants. From the first scene with a replicant to the last one, replicants show more humanity than anybody else. In the opening scene with Leon and the Blade Runner, Leon is joking around and trying to connect with the Blade Runner, who just stares at him. Following killings or retirements, the replicants are the only ones who show true emotion. Replicants are truly human. They are the representation of what people should be. They're not good, they're not bad. Instead, they exist somewhere between the two in a contradictory state. Selfish while also caring, individualistic while also group-oriented. This is the journey of Deckard. After Roy saves him, he too finds the beauty in humanity and begins to truly appreciate it. He chooses to start a new life with Rachel, who is the one person in the movie who truly makes him happy. Hey everyone, I hope you enjoyed. Blade Runner might be my favorite movie of all time. It's definitely up there. I'm glad that I could finally discuss it over here. I'd love for the discussion to continue, so be sure to drop a comment to get your thoughts out there. If you haven't seen it yet, be sure to check out my last video, where we compare to Silence and Apocalypse now. If you're not subscribed yet, hit that subscribe button. Thanks for watching, and I'll see you next week.