So then we're talking boxing and looking ahead to Jason Quigley's big fight, I'm delighted to say joining us Irish Sun Sports reporter Kevin Byrne, Kevin. Delighted to have you on Highland. Thanks, Oceane. Thanks for inviting me on. It's great to talk. Yeah, you're a man that has a wealth of knowledge of boxing and in particular Irish fighters and Jason Quigley. This has now met you the time Jason met his homecoming fight in Dublin several months ago and he was due to be part of this big summer extravaganza of boxing and Dublin, a big open air event. How come this Berlanga fight happened so quickly after that and plans changed? Do you think, Kevin? Speaking to Jason before that homecoming fight and alongside Andy Lee as well, he knew even though his last fight had gone pretty horribly, his world title fight ended it. It's the stuff of nightmares, I'm sure. Demetrius Andrade broke his jaw on the first round. Quigley was well aware and Andy Lee would have been telling him, Jason, all you need to do is have a comeback here, get back into winning ways.  And so it proved the guy he beat in his homecoming, Gabor Gorbitz, not a big name, not the sort of opponent who's going to move the needle, but just he got quickly back winning. And then the phone started to ring quite clearly. Remember we saw at the Dublin fight, the former Golden Boy Promotions matchmaker, Roberto Diaz was over in Dublin to, you know, he's got a close relationship with Quigley from the time to get her a Golden Boy. And I'm sure he's been working the angles and trying to get Quigley involved in a big fight. And look, it seems to have happened quite easily, doesn't he's got he got back active. He got a win. And suddenly he's got to call to headline a big event over at Madison Square Garden. Yes, you're saying the we were talking we were talking afterwards about this big summer showdown in Dublin and Quigley was going to fight again. But this is a bigger and better offer, I suppose. And the idea of Quigley having a big fight in a big home, a second homecoming fight in Dublin and getting a decent opponent over was probably fanciful. He doesn't have the promotional backing behind him to spend the money on bringing a good opponent over. We saw what happened last time. Gabor Gorbitz was the third or fourth replacement opponent Quigley had and that's what's going to happen when you don't have big money to spend on an opponent. You're not going to get the top guys. And Quigley is certainly in against the top guy in Edgar Berlanga now at Madison Square Garden. Yeah. So what's what can we expect of Berlanga? Obviously we know he's 20 and 16 of his fights came from knockout. But his his recent form hasn't been to what it was earlier in his career. So let's let on the table here. What's the what's the upper or what's the chances rather for Jason Quigley and this one at the weekend, Dave and Kevin? I would say he's he's quite a heavy underdog. He's been probably written off across, you know, boxing, Twittersphere and among the media, certainly in America, because you know, people are people were, should I say, very high on Berlanga for the first couple of years of his career. Like you said, they're rushing 16 knockouts in his first 16 fights and what's more, all of them in the first round. Nobody they nobody has all promoters top ranked seem to match him with could last more than around in Berlanga. A bit of a flat track bully, aggressive Puerto Rican New Yorker came out and blew everybody away until he stopped blowing everybody away. That first came in 2021.  And that was probably a bit of a shock to the system for Berlanga. He tried to get back on track, you know, get his knockout streak back again in the next fight. Kosair is then Steve Rolls, then Angulo, but it was the same thing brought to this. And so his ability to take out fighters at the higher levels, he's fighting that seems to evaporated. And it's probably frustrating him because something flat, flat track bullies don't enjoy is the other guy putting it up to him. Now, that's not to say he hasn't been winning his fights quite clearly. But some of the shine has gone off his name and some of the, and there's a, there has to be a reason behind his promoter's top rank. No longer working with him. Yeah. Well, how does Eddie Herron looking at this fight then? Because he took Berlanga on. Obviously, there's a connection there as well with, with Jason Quigley. What does, what does Herron want out of this fight from the two fighters? Berlanga still has a lot going from in New York, massive Puerto Rican boxing fans, massive number of Puerto Rican boxing fans, kind of like the Irish, but it seems that a Puerto Rican is the Puerto Rican boxing is probably even stronger. They've had a Miguel Cotto over the last two decades to kind of to burnish that there. Like we had John Duddy in the States and in New York as well. But Cotto had, you know, bigger and bigger and better fights, you know, an even more remarkable career, if it can be said, than John Duddy. So the Puerto Rican, the Puerto Rican boxing movement in New York is huge. It needs to be replaced. And maybe Herron sees Berlanga as the guy to do it. Not just that, though. There is not enough great opponents out there for the main man in boxing at the minute, Canelo Alvarez. As we've seen, he's beaten eight British opponents at this stage. You know, every time a British super middleweight or light heavyweight of note emerges, they end up fighting Canelo and they end up losing. He's beating them off from Billy Joe Saunders to most recently, John Ryder. I can name a model. He's gone through so many of his opponents at this stage that they're always looking for someone else. So Herron has seen the top ranker no longer working with Berlanga, snapped them up because it gives them a base in New York, gives them a ticket seller, gives them somebody that he can sell worldwide as an attraction. And if Berlanga can get back to knockout ways, he becomes must watch TV again. But also, he doesn't really need to do too much more to secure himself a Canelo fight for which he would be seen as just as much an underdog as Quigley is against him. However, it's a massive money fight. If he can get rid of Jason Quigley in style and the wording Eddie Hernandez put on it is if he can ice Jason Quigley even more impressively than Demetrius Andra did, which you know, he took him out quite early was in this the second round. So he says if Berlanga can be even more impressive. So it's all set up for Berlanga to go through Quigley for a short cut, first round knockout, that kind of thing. Put some put some heat back in his name and and then maybe one more fight one more win. And then he'll be a viable contender to take on Canelo. Okay. Could the stars align in any sort of way for Quigley in this fight? Do you feel Kevin? I think they could. I think I've always believed in Jason Quigley's ability to win fights.  Like he didn't he did compete as well. And he didn't win at amateur level. And we know some some fighters with a pro style can have that sort of struggle in the amateur ranks. And but also some of this source would mention that he's a flat track bully. And when someone does put it up to him, he falls he goes the distance and and this source also thinks that who has worked with Berlanga now this, you know, this is close close to home for him does this source does believe that if someone can stand up to him, take his punches, someone like Jason Quigley could stop him in the second round of the fight. And but also we have to look at Jason Quigley's amateur pedigree is it's it's extensive. It's 10 years last month since he won the European title. And then followed up that year by becoming the first Irish boxer, the first Irish man to reach a world championships final, you know, so his amateur pedigree, we also know he was a couple of times European underage champion to and he came out of the most competitive middleweight series we've ever had an Ireland as well, you know, beaten to be even to beat Aaron O'Neill to become Irish champion that year in 2013. You know, Olympic captain from the previous year. So we know Quigley has this incredible amateur pedigree.  And he won't be overawed by Berlanga. Also, there's no hope that he's going to be overlooked. Isn't there? Because I think he said himself, he knows her in a set in the upper language for a hundred million dollar super fight with with Canelo and all his role in this drama is to come over and lie down. So he but he's got so much pride and so much ability. And I also believe that Quigley probably hasn't shown his best in the professional ranks. He's in it a long time nine years. He showed he showed everything. He showed the ability to knock out fighters. He showed fortitude. He showed massive resilience. He fought a couple of fights when he got very badly injured and continued. So he's got the heart. He's got a big heart. Obviously, things went badly against Android, you know, broken job, first exchange at a fight, never got to do himself justice in his world title fight. And I don't know him. That will annoy him. Absolutely. He's a cheerful guy. He doesn't really show frustration. But then, you know, when you do, when you do speak to him, you can really understand. He can really take it from him that it pisses him off or annoy. Yeah, sorry. It does annoy him, though, doesn't it? That he never got to show his best because all the dunnigol was behind him. He brought a lot of people that fight and he never got the opportunity. He never got the chance to try and stamp his authority on Android and said it was one way traffic. And that was it. You got to walk away heartbroken. And it was over a year until he was back in the ring and he did have his doubts. He thought about walking away. He says he's back now. And I also wonder what can Andy Lee offer him on this one? Jason is passionate in his defense of Andy Lee as his coach.  And then for his homecoming fight, Lee missed that one as well. He had his television contract with Dazzone in the UK and he had to commentate on a fight that night. And he sent his brother Roger to take care of the corner. Lee is in his corner for this Berlanga fight and Lee will have an awful lot of contacts in New York Box and he lived in New York for a spell journey in his time in the States. He knows the boxing fraternity in New York like the back of his hand and he will know people who know Berlanga intimately. He will have heard rumors, whispers about weaknesses, strategies and stuff. And I know that Andy Lee and Jason Quigley are very close and as well as that, I can't I can't help but think and probably some of this stuff doesn't matter. It's more narrative and it interests me and it might have any effect on the fight whatsoever. But I can't help but think of the similarities of Lee's career and Quigley's career coming into this fight and I see it as a positive. Yeah. Well, hopefully it's going to turn out to be a positive day for Jason Quigley and Andy Lee can help work his magic as well. If Quigley is to pull this off, what sort of fight are you going to expect if it's going to go the way they don't want to go? He's going to have to take some heavy he's going to have to take some heavy shelling early on because Berlanga, like he's been told to do, has to go out and ice him. So he has to take the punishment. He has to take the punishment in the first couple of rounds. He has to spoil. He has to be tricky. He has to have a strong job. He also has to earn Berlanga's respect. He has to catch him at some stage in the first or second round or certainly enough that Berlanga thinks I'm being too reckless here because Berlanga is going to be reckless and he has to catch him coming in with maybe an uppercut or something like that. It's funny to see him stand face to face. Quigley is the guy coming up from middleweight. It's only a second fight at super middleweight or properly, his second proper fight at super middleweight. Berlanga has been there for a lot longer. So you think he's the bigger man but when you saw him at their face to face there at the top of one of the skyscrapers overlooking New York City, Quigley's taller and he's going to have a little bit of a size advantage. That said, Berlanga's a thick, he's a heavy set guy. He's got thick arms and thick trunks. He's going to come at him. Quigley's definitely going to have to absorb some heavy punishment early in the fight. Unfortunately, it was unable to do against Andrade, but we have to look at that shot as a, you know, Quigley's being hit hundreds of times in his boxing career and never got his jaw broken with the first punch of a contest. So we have to hope that that's not the case on this occasion and that his injury is fully healed and he's ready to go. If he can absorb, you know, if he can get through the first four rounds, maybe nick around there and be in the contest by the fifth or the sixth round, like I was mentioning before, you know, I'm thinking about Andy Lee's career and I'm thinking about the similarities. Lee had his first world title back in summer of 2012, this time June during the summer and he went against the Chavez Jr. down in El Paso and like Quigley's world title shot, everything went wrong. You know, it was even accusations of terrible dope testing and everything was against Andy Lee and the fight didn't go his way either and then he had to go on the slow rebuilds, almost like Jason Quigley has done, pick up the pieces and then find that even the interest in his career wasn't the same and he had to self motivate and he had to get himself back to the top and he managed to do so and one of the key venues on his comeback trail was Madison Square Garden when he fought against a guy called John Jackson who was pouring on the pressure and then he pulled out what's going to go down as one of the greatest knockouts in Irish boxing history and he was losing the fight, the pressure was on and Lee pulled out something so Quigley is back to when Andy Lee's greatest triumphs happened. It's a lucky venue for Lee, he also knocked out Carl Daniels at the same venue to set his career alight as well earlier on and he'll be delighted to be back there. Jason will be, I'd say, quite happy to be, quite content to be in New York this week as well and we saw a little bit of the open and trash talk there when Berlanger and Quigley came face to face and he says this is my city and Jason is like, I didn't do geography in school but I didn't need to be told that he's from New York, I'm well aware of it. But I think he's got...  Is there a big knockout in Jason Quigley? Does he have the big punch to won this? Well, that's a tough question and we haven't seen one punch power too lately in Quigley's career either which there was a spell in Andy Lee's career, we did wonder was it there, was it there but you know he did probably have more of a track record of being able to do so and we all, and especially by the time he got to his second world title fight, everybody knew Andy Lee can knock you out with one punch and he kind of did win the world title, he set up to finish with a big right hook. Can Quigley do so? Well, everybody can be knocked out you know and he does have a good knockout ratio and Quigley himself will be the first to admit that his knockout ratio is probably too high because he was fighting against guys who weren't really on his level for the first kind of 8-10 fights of his career and he almost wishes that those were harder fights or his opponents went more round so he could have picked up more experience. That being said, he does have experience of finishing fighters, he has taken out a lot of fighters on his way up in boxing and I think he'd be confident again that he can apply to finish if it does present itself but I think he's going to be prepared for a long hard night, go to distance, win the rounds and like the Quigley, even though he's been a professional for nine years, the Quigley I still think of is the top amateur who can get a decision over just about anyone if he applies himself correctly on the night. The guy who's completely prepared for every style and is super fit, he's a professional you know inside and outside the ring and that's the kind of Quigley I'm looking at to win here. Probably going to have to go to distance and if you can, you're going to have to hurt the guy, you're going to have to earn his respect but if you're both still standing after 10 rounds what you're ideally looking for is him to have dominated the second half of the fight and picked off a couple of rounds in the first half. Okay, well the result doesn't go as way and he avoids the, I suppose, the heavy stuff coming on the early part of the fight Kevin. If he takes this guy the distance or goes the distance and puts in a solid performance even though it would lose the fight, what sort of direction would that mean for his career because if what happened against Andred happens again it's not going to be good for his career but if he's able to go the distance and put in a performance here, obviously defeat doesn't mean it's the be all and end all, there's going to be other opportunities there if he gets the respect of the fighters as opposed to the top men in boxing with a good showing. Exactly, I think it's what can he tell himself afterwards and how is his own desire shaping up, like as we know Jason Quigley got married this year, he's got a light set up outside of boxing, he's got good context in the media, I saw him working on doing a bit of commentary for the zone on the Katie Taylor, Chantel Cameron fight their reasoning doesn't look like they're going to have a rematch and you know, Quigley could have a role there and he's also helping manage fighters as well. So we know that outside of the ring, he looks like he's set up, you know, to be connected with boxing but he can probably do anything he wants as well he's a very smart guy, I've always noticed that about Jason. However, his in ring desire, if he does go to distance, he and he puts on a good show and let's say he loses a close fight, I think he's probably going to be able to tell himself, you know what? I didn't do myself justice in my first world title fight. This was a major event against a New Yorker who's probably going to fight Canelo, it could be a multiple time world champion, we don't know, but if he quickly goes to distance against them, he can say, I'm back, I know the level I'm at, I probably know a couple of mistakes I made in the fight and I could have won the fight, had things gone slightly my way and I'd say he would be able to tell himself, you know what? I can go again, I can win a world title because like, like we say, Lee didn't win a world title at his first attempt, this isn't a world title shot. Took Steve Collins until his third fight, a third world title fight to win a world title and also he would be able to tell himself, I'm still adjusting at super middleweight, I put on a good show for a couple of rounds, I can beat other guys at my weight and you know what, there are other viable fights out there, his contacts with Roberta Diaz, he could probably pull off a fight with Hami Mungia to get another world title shot, I don't think I don't think a close points defeat is disastrous at all, but like if Berlanga has his way, hasn't already finished, it's probably going to be good night. Well listen, we'll see, we'll see what happens and how the fight pans out over the weekend. Listen Kevin, good to talk to you, good to see you and we've got the fingers crossed we're just going to get the weekend, don't we? Absolutely, I think he's got the backing of everybody in Irish boxing for this one, he's a good guy, he's a very popular fella, never messed anyone around and he's always straight down the line, so I think everyone's going to be behind Jason Cookely in his attempt this weekend. Okay, we look forward to it, thanks Kevin. Cheers.


Imagine a universe of minds, each vibrant and unique, yet some navigating the world with different maps. Autism Spectrum Disorder, or ASD, is like one of those maps influencing how individuals experience and interact with the world around them, with rising diagnoses and widespread misinformation unraveling the complexities of ASD can feel overwhelming. In the next 60 seconds, we will embark on a journey to unpack the mysteries of ASD, what factors contribute to ASD, we'll delve into research and understand the potential causes without perpetuating harmful stereotypes. 1. Genes and mutations. Researchers have identified hundreds of genes associated with ASD. These genes, often working in combination, influence brain development and neurotransmitter functions, impacting communication, social interaction, and sensory processing.


UK Prime Minister Rishi Sunak has been fined for not wearing a seat belt. British police issued Prime Minister Rishi Sunak with a fine on Friday evening for riding in a car without a seat belt in a video clip that Sunak's team had published on social media. Sunak's spokesperson had apologised for the previous day for a brief error of judgement after people had noticed and criticised the indiscretion published on Sunak's Instagram account. Messengers caught failing to wear a seat belt when one is available can be fined £100. This can increase to £500 if the case goes to court. Dominic Raab, Deputy Prime Minister said, Mr Sunak was someone with the highest standards of integrity who had made a mistake on the seat belt issue. Dominic Raab said the PM was a human being doing a demanding job and had put his hands straight up and apologised. The Prime Minister was in Lancashire when the video was filmed during a trip across the north of England. Police from the county of Lancashire where Sunak's car was at the time did not name the Prime Minister in their initial announcement, although they gave his age and place of residence. Following the circulation of a video on social media showing an individual failing to wear a seat belt while a passenger in a moving car in Lancashire, we have issued a 42-year-old man from London with a conditional offer of a fixed penalty. Sunak was fined £50, around €57 or $62, one-tenth of the theoretical maximum fee for not wearing a seat belt if taking the case to court. Soon after, Sunak's office said in a statement that the Prime Minister fully accepts this was a mistake and has apologised. He will of course comply with the fixed penalty. The case had prompted criticism from opposition politicians with Labour Deputy Leader Angela Rayner calling Sunak a total liability. But a Conservative MP from Lancashire, Scott Benton said he was sure that Lancashire police's time is better spent investigating serious crime which impacts on my constituents. He called the complaints politically motivated. Sunak was also one of a roughly 50 people, including former Prime Minister Boris Johnson, who received a fixed penalty notice last April for attending a birthday party for Johnson at 10 Downing Street in June 2020, in defiance of the government's own rules on special distancing during the Covid pandemic.


Hey guys, welcome to Snowbreak Containment Zone and this is a complete guide on your Neuronix. So before we proceed, if you find this video informative, please do put a like to this video and also consider supporting this channel by subscribing. This really helps my channel a lot. So without any delay, let's proceed to Neuronix here. So let's take a look at our operatives. So we will use live as an example, Neuronix basically is an enhancement of your existing skill. So you can find your skills here. Once you click on your skills, you can also find a mini shortcut here on the right side. So the first on the top is your standard skill. One in the middle is going to be your support skill and the last on the bottom, not the last. The third one on the bottom is going to be your ultimate skill. And the last in the bottom is has no title basically. It's either called your active skill or your passive skill. So take note that there are some buffs for active skill. Presumably I think this is your passive skill or your active skill. Okay, so moving to Neuronix tree. You have six Neuronix tree. You have two pertaining to each skill. So two for this is your standard skill. Two again in the middle for your support skill and two for your ultimate skill down below. Okay, so don't worry, you can unlock all of your Neuronix. It will be unlocked at level 80, but you'll have to be content with what you can unlock right now at the current level that you are. So if you make a mistake in terms of unlocking the current character that you have, let's say for example, there are, for me, there are two types of builds of character. There's your primary character, there is your support character as well. Support is going to be used, it's going to use two skills. So this too, your active or your primary character, primary shooter will be using these skills up here, your standard and your ultimate. So right now life is actually built as a primary character or shooter. Before I chose Frost Wolves, the two clusters here up and one cluster below for Eternal Blizzard. If I want to switch them, if I want to switch her to support, definitely I will go with the middle.  You can transfer the materials you used with life to Akasha, for example. So you cannot do that. So again, a reset is a good opportunity for those who haven't reached level 80. Level 80 will unlock all six. If you haven't reached level 80, if you want to tinker with your skills, then you could do a reset. So that is as simple as that. Okay, so let us go to the trial. So I want to show you guys that there is still a trial here. So if you guys missed the trial for the current limited banner here, she is, this is Kaguya, but we will go to her Neuronix here and we have here six unlocked Neuronix. As you can see, the middle circle here has four of its lights already on and the middle icon has already changed. So indicating that you have unlocked all six. So this is actually proof that we can unlock all six, but definitely happening at level eight. Okay, so going back to the character that we have, so we'll use Yao as an example here for Neuronix. Okay, so Yao here, I'm already up to unlocking her third Neuronic. You can actually, once you open a tree or a cluster, you cannot leave that cluster. You must finish that cluster before you move to the next cluster for Yao. So right now, I am at the second one. As you can see, the buffs here, sorry, each step has different buffs. It's going to be pertaining to an alignment index or it's going to be pertaining to the skill that you are buffing. So Obsidian Core is definitely Yao's passive, not passive Yao support skill. So definitely some of her points in the cluster will be pointing to Obsidian Core. Some of the points will be pointing to the passive or the active skill. So as you can see here, this is pertaining to alignment index. So once that specific point in the cluster is activated, it contributes to the passive or the active skill. So going back to Yao for her Neuronix. So again, as you can see, it's usually a buff to the specific skill and alignment index. So I'm going to open this up because I have the resources at this point. Okay, so I just want to note guys that the last one here, the last one, when the previous one we're using Fiber Axon, the last one you will need a Quantum Cell. This actually I realized applies to your third cluster and I think it applies to third and fourth and fifth and sixth clusters. So be worried that you have an additional resource to get for you to unlock the third cluster up to the sixth cluster. I'm not sure yet if there are additional resources going up but be aware that there are additional resources, not just your Fiber Axon. So let's do this upgrade. So right now Yao is up to three clusters and there we go. Okay, my last tip for you guys, so feel your way in customizing your Neuronix feel, how you play the game in terms of the characters or the heroes or the shooters that you bring. Customize it well but don't worry, you'll have all six eventually. It really depends on how you use the character, how you build your team and eventually how you're going to be moving up as I may say from your current level up to level 80 when you unlock all six Neuronix. So that is the build guide guys. I hope you were able to get something out of this video. So again guys, I would appreciate the support by subscribing and putting a like to this video. Guys, thank you very much for this fort. It has been very overwhelming and I want to bid you a good weekend or a happy weekend. Thank you very much for staying this far. Take care, stay safe, this is The Warden and I'm out of here.


Cool. We're going to start. Okay. So, next up, I'm very happy to introduce two of my friends that are going to be talking about how they tried to use machine learning and maybe worked, maybe. So, Rahul, plus we're calling Chris. Hi, everyone. So, I'm Chris. This is Holden. We did some work on trying to predict PR comments with GitHub, and we're going to be talking about it today. So, if you want to, we put this up earlier, but this is for the stream for folks at home. If you want to go to github.com slash frank the unicorn slash fozdem, it's a repository and you can open up a pull request there with any old open source code you want, and we'll actually iterate on that and process it live today, and we can actually talk about the machine learning we're doing behind the scenes. So, if you want to play along at home, feel free to open up a PR there. So, a little bit about me. I contribute to a lot of open source, primarily Kubernetes and a lot of stuff in the Go community. I've written a book and I just engineer a lot of things, I guess. I don't know. Anyway, I helped Holden here with the Kubernetes bit of things as we started to go down the machine learning path, and I worked for VMware. Cool. I'm Holden. I contribute to other projects, mostly in Scala. I'm an author but of different books, and I work on different projects, and I work for a different company. Thank you, glorious employer for paying my salary. Despite all of this being mountains, I don't climb mountains and also that's not my Twitter handle at the bottom. This is Nova slide template. Yeah. I climb a lot of mountains, and this is my slide template. So, we're going to look at mountains too today. I hope that's okay. Okay. So, this all started four months ago, three months ago. We got together and we were brainstorming ideas for machine learning and Holden had the idea that we might be able to scrape data from GitHub and try to predict the lines of a pull request where people might make a GitHub comment that says like, hey, maybe this isn't the best idea or something like that. The more we thought about it, the more we realized that GitHub stores a lot of information about developer habits. These are things that people commonly do, and then people who are reviewing pull requests all the time, like Holden was Spark. There might be some patterns behind the cognitive behavior there, and we were wondering if we could train a model to represent that. So, we thought maybe we could learn about what normally gets attention from humans in GitHub. Maybe we could use our skills in Kubernetes and Kubeflow and machine learning to build a pipeline to predict where these pull request comments are most likely to show up. Yeah. So, our very high level, super high quality design document, as you can see here, is step one, extract the data, step two, build the model, and step three, serve the model, and then step four, just in case step three resulted in garbage, is to collect explicit and implicit feedback. So, the idea is that you can thumbs up and thumbs down pull request comments, and so the bot will make comments and we can record the interactions. Also, we can do sentiment analysis, and if people start swearing at Frank the Unicorn a bunch, maybe Frank the Unicorn is not the greatest Unicorn. Be very sad. Also, we don't use Kubeflow because I couldn't get my PR to add Spark to Kubeflow integrated in time, but I really wanted to. I have a PR and it'll happen next week. Cool. Okay. So, we started to look at building this thing out. So, the first thing I was tasked with was building some data extraction from BigQuery, and I wrote a program in Go that we can look at later, that runs not only as just like you can run it as a single cron job to export a year's worth of data, but we also have it running in Kubernetes as a Kubernetes operator that will go and audit BigQuery and see if any things changed and automatically update the record behind the scenes if it has. So, we have this resilient ongoing update of data coming out of GitHub, as well as the ability to backport back to 2014, although 2014 wasn't the best year for GitHub data. So, 2015 moving forward as really as far as we got. Then, the BigQuery side of things, this is where Holden really took over. Yeah. So, I utilize my wonderful skills of writing SQL, which I pretend not to have most of the time to avoid writing SQL queries, but I needed some data unfortunately. So, yeah. The SQL query wasn't so bad. The main thing is that GitHub changed their format a bunch of times and the BigQuery table that represents the GitHub data represents it at the format of the time the event occurred rather than the current format.  So, after that exciting joy of writing very imperative style SQL somehow, I started to build the brain for Frank the Unicorn. The brain is built in Scala with Spark. This was a mediocre choice, but informed by the fact that I work on Spark for my day job and I could probably get away calling that work, if anyone asked too closely. This is, it had some good benefits. It allowed us to train our models in parallel and do cool things there, and it also let us do a bunch of data filtering things there too. Once we built the brain, unfortunately, I remembered why I don't build machine learning models in Spark very often, and it's because serving them really sucks. So, sadly, the serving layer is written in Scala and Spark, and we spent the last six hours getting Scala, Spark, and GRPC to all not fight with each other too much. That was just a really great way to spend a Saturday night. Yeah. So, after we had the Scala and Spark side of things set up, we needed a way to plug that in to GitHub, and that's where the Go came out again, and I wrote another Go program, the second one, and we interface with Holden Scala over GRPC.  The Go also serves as an HTTPS server as well, that the GitHub Event API sends a webhook post request to whenever there's a pull request event. So, if you were to open up a PR, the Go program that's listening on HTTPS will get a big blob of data about your PR, push to it, and then that'll go and open up a connection to Holden Scala side of the fence, and start to iterate and do the back-end processing. If all goes well, that's going to come back to the Go program, and then that Go program is going to go leave a comment on your PR. Yeah. So, that's the high level way of things we're working out. We do have a diagram. So, this is how it all fits together, and I'll walk folks through this. It looks really complicated, but it's really not that bad. So, the BigQuery data comes into the extract operator that runs residually. All of that gets pushed up to Google Cloud Storage as CSV files, and that's an atomic transaction, whatever that goes in. So, whatever is reading from it, I can guarantee that it's a complete dataset. Then we go into the Spark Scala trading bit, and then there's the Scala GRPC server, and then we use the domain fabulous.f, using Kubernetes ingress to serve a public HTTPS endpoint that the GitHub events API pushes to, and all of that kick starts down here by installing Frank the unicorn on a GitHub repo, and then if you open up a pull request, it kicks off the other chain of events that will eventually circle back around back to the pull request at the beginning. Okay. So, I'm going to talk a little bit about the components and what we learned as we were building them. So, as I was building the data extractor, we really wanted it to run in Kubernetes, and we wanted to make sure it could go and check new records. So, I think the big takeaway there was like, we didn't really gain much value as running it as an operator in Kubernetes. It sounded like a good idea at the time because we thought we would be getting meaningful data on the day-to-day basis, but it looks like we probably got a lot more just by backporting over the last couple of years. Furthermore, as we were going through the GitHub data, we realized that it really wasn't clean at all. So, the majority of the Go program just turned into data sanitation and just checking values and making sure that it was all going to fit nicely together. Then, the atomic part of things was important as well, and Go was pretty okay at making this happen, because we could use a new text to make sure that if we were writing a file to a CSV that it wouldn't undo itself before the file was done written. Let's see what's next. Oh, so the Suggestor, this one was fun. So, I got to write an in-memory concurrent queue because we had two main parts of the program happening at the same time. The first one was the HTTPS server, and then concurrently we were running the GRPC client that was talking to Scala and Spark. So, the way that this worked is the HTTPS server would get a post-request to it and stick it in a queue, and then concurrently in the same process, the GRPC client would go and pop-soaking off the top of that queue and then go process it in the background. So, we're seeing this really interesting concurrency double server client pattern that Go allowed us to do, that was exciting. Furthermore, we had the patch view for comments. This was what we learned about the GitHub API. If you want to leave a comment on a PR, it's not as simple as saying leave a comment on line 12. You actually have to go through and calculate, based on the patch view, how many lines down from the previous change, you want to leave a comment. So, there's a little bit of math that we had to do for every one of these. Furthermore, we used Contour for Ingress because we had to serve this whole thing publicly or GitHub wasn't going to send us any events. So, that was exciting to get to use Kubernetes Ingress to solve that problem. Cool. And so, to make this all work, we needed to train a model. Otherwise, it wasn't going to be very useful. So, we trained this with Spark on Kubernetes. There's a whole bunch of different kinds of classification models built into Spark. I tried a bunch of them under the principle of, why not? And for the most part, they all kind of performed similarly poorly. Greeting and poosin trees performed a little better than most of them. And so, that's the one that we just went with. And the first iteration of this, we performed a little better than guessing, but not a lot. That was really depressing. We added some more features and we got more better, but not much more better. And so, this was like a kind of sad start to the project from my point of view where I was like, oh, I have a model, but it's garbage. Okay, right. And if anyone here has run Spark, you know that part of running Spark is collecting out of memory exceptions. They're like Pokemon, except they're like the really crappy Pokemon, because they just show up everywhere. Our favorite Oom that we collected was the container Oom Kill. And this is because it happened often and there were no logs. So, unless you were watching the pod status, you'd just be like, why are my executors disappearing? There's no log messages. And that took me, I mean, that took me several days of trying and then eventually asking Nova. Yeah, and then I got on the phone and fixed it in like half an hour. Yeah, okay, fine. So, and that was good. And then the rest of them were sort of the standard Ooms that we get with Spark. And I'm well aware of, maybe not happy with JVM worker whoops, ah, heaps based out of memory exceptions, but like, that's just my life. That's my jam. The driver out of memory a bunch of times with some of the models during training. And this is because we essentially used the driver as a parameter server during training. And for some of the models, that was just too much memory because it wasn't cleaning up very well. And that was kind of sad because we weren't training on huge stuff. So it was a little depressing, but it's okay. Okay, so we used a bunch of different features. Word2vec was the one I started with because the source tech blog post about ID2vec encodings, I was like, that sounds like a cool encoding, maybe I can do this. And then I did, and then the features, I mean, I'm sure they're good features, but they weren't good for this. But it was our starting point. I also tried TF IDF, which is a standard document retrieval thing, not super useful. And then it started to become things that look more like, suspiciously similar to what a linter might be looking at, just fed in as features to a decision tree. Do, do, do, oops. So lines that are all spaces, the percentage of spaces, what language it's being written. And the last one is the one that I think is interesting was we also looked at the GitHub issues associated with the project. And this one actually turned out to give us one of our bigger performance boosts. If a stack trace ended up touching the lines that were being changed, there's a higher likelihood that that is sort of complex or confusing code that people will want to ask questions about. And so that ended up being a pretty good feature. And there's some ways and ideas on how we can extend it from there. Yeah, so we did some hyper-parameter tuning. And for the most part, more trees approximately better. And then we got diminishing returns just pretty quickly around like 20. The other things we did didn't really make all that much difference. And before anyone gets worried, and you should not be worried that our performance numbers are juiced based on how incredibly bad they are. But I did save a test set before I started doing my hyper-parameter tuning. So it is valid and legit. Okay, so yeah, yeah, this is the slide of sadness. So like a good score here, how would be two orders of magnitude higher? So that was not great. But for the data set that we have, it's like super imbalanced. It turns out that people really, as a percentage basis, do not leave a lot of comments on PRs. And so the random guessing score would be like 0.03. So 0.09 is three times better than just like flipping a coin and being like, cool, looks like a great place to leave a PR. And I think we can do better with more data and we'll talk about that and how you can help us make this model less janky. Yeah, and so this is the list of things in the training area specifically that we wanted to try and improve. One of them is like the classes are super imbalanced and so that was really rough. And so we really want some more data of people interacting with Frank to say whether or not Frank is making good predictions. Flexors and tokenization, we could do much smarter things than what we were doing there. We don't have a lot of context. We look at things on a line by line basis and context matters, so we could do smarter things there. And also I think bringing in more logs, like if a piece of code is really confusing on Stack Overflow and frequently referenced, that's like probably another good sign that would be useful. And we can explore some different models. I don't know, we could use deep learning if we wanted to, but I don't know. We have a link at the bottom if like this is a thing that you care about, those in the back cannot see it, sorry. But the slides will be posted later. We'll tweet them and you can fill out that link and you can submit PRs. Frank will ask you for feedback. Cool, so a little bit about building the GitHub app that we're hoping gets approved, but we'll see how it goes. We had to go through and effectively demonstrate that we did have a working public endpoint that was TLS encrypted and then it actually did something behind the scenes. So that was exciting and kind of fun to go and get to play with GitHub API and actually make it so that we had like an interactive demo for today. And then I think Holden here wanted to shout out. Yeah, if anyone is watching that works at GitHub, please approve Frank the unicorn. Frank dash the dash unicorn. Yes, good point, yeah. It is totally not gonna steal people's credentials, I promise. We are good people. Yeah. Cool, so if you wanna find the source code for any of the programs we wrote, the Scala, the Spark, the Go, the GRPC, that is all in github.com slash Frank the unicorn slash predict PR comments and all of the Kubernetes side of things is there as well. So if you wanna see examples of how to run all of the pipeline in Kubernetes, that's all there and you can try Frank out here and then we can show you the whole system up and running. We have it working right now live and let folks see what they want or if they have questions or whatever, we can do a demo. Demo, demo. Okay, cool. Let's hope the Wi-Fi's still working. Yeah, I think first what do we, do we wanna look at the answers or do we just wanna show folks behind the scenes first? Yeah, let's do the Qt logs. Okay, cool. I'm gonna put this down for a second. I can talk about what you're doing. Okay, cool, yeah. So Nova is gonna bring up the logs for the different components and there's some debugging information that we output about the PRs that are being sent to Frank and also the features and what Frank's predictions were for those features. And I guess Nova really likes aliases because typing is too much work. So yeah, we have three pods. There's the model server, the PR Suggester and there's Ubuntu which was just used to debug it because they weren't talking to each other this morning. You can see we were working on this eight hours ago. I have not slept a lot. Okay, yeah. So the model server is the one which has the more interesting pieces insofar. There is the file name and this is so signal process, someone submitted this and these are the lines that Frank was curious about.  I made a slight mistake in this logging message so we just print out that it's a list which is not useful to anyone but it's a very nice decorative list. I think it really brings the log messages together so I'm not taking it out. Do you wanna show people the features and stuff or do you wanna talk about this? Yeah, go for it, I can see them up. Oh yeah, cool, okay. So, whoa, okay, cool. Whatever, yeah. So you can see some of the feature vectors they're all mostly chopped off just because it's in show mode and the feature vectors are pretty long, right here. Cool. Yeah, and so I think the last one is predictions so this one here is set to one zero and it looks like it really didn't have much going on on that line and so that's a thing, I don't know, whatever. It's some log messages and we could go look at that PR maybe and that'll be more informative. We should probably open one up and watch it go live. Or someone in the audience could open one up and watch it go live, yeah? Yeah. No? Yeah, yeah, thank you, thank you. Okay, so the other side of things that we're gonna split the window here as Francesca opens up a PR for us is we can do our alias again. So I'm lazy. Does the alias actually set you any time if you type it in at the start of each test? Yeah, but now I know that this is like always and I don't think about it. So tailing the logs for the Go program here, as soon as Francesca opens up a PR we should see the Go program. Yeah, you wanna count down and hit Go? Count down. Cool, so yeah, there it goes. So yeah, what happened was GitHub sent us an HTTPS request, you see that over on the right. It says we received, oh thanks, a PR called hellofriends.go and then you can see the scholar and Spark in the back end here processing the request and we're already done, so Frank's already left some comments on your PR here. So let's go look at this. Oh, 28 pull requests. Wow, we have a lot, okay. Man, we have friends. Yeah, so this is always the exciting part is to see what Frank decided to comment on. And this is actually a lot of fun. So it looks like Frank, for whatever reason, thought package main did not look very good. Empty line on line two, line three and line six. So I think this is a representation of, if we have a small sample size, it's gonna find more in there. Yeah, so one of the hacks that I did to make it slightly less garbage is that it more or less pulls the top K worst lines. And so when you submit four lines, it's like, well, of my top five worst lines, these four lines are it. That's not exactly what it's doing, but it's pretty close. And so for small PRs, that optimization was a bad idea. But for some of the bigger PRs, it's a little bit better because otherwise Frank was kind of unpredictable with how many comments Frank was leaving.  Yeah, let's go look at a bigger one and hope it doesn't prove me wrong. Cool. Well, this one's got signal processing module. That sounds like it's probably not five lines unless signal processing has changed substantially. Okay, so, okay, cool. Okay, so Frank really doesn't like blank lines. Which is, it's not the silliest thing for Frank to be upset about because I think there's a lot of situations where especially in Python code, people have extra blank lines. You leave comments and you ask them to take them out. And the problem is that we don't have a per language model. And so Frank is just like, yeah, here's a blank line. And it doesn't have the context of the previous line. So it doesn't know like there have been X blank lines before this. All it knows is that blank lines are a little suspicious and end up having comments on them. So that was a depressing discovery. Okay, so Frank doesn't like how this comment was closed. That's probably a style matter, but this means that on average, probably on across GitHub, people don't like that style. They prefer closing their C-style comments differently. And so that's why Frank is upset. Stars close together. Yeah. Okay. Oh, right. And here's an else, I guess. No curly braces. Yeah, Frank gets upset with elses without curly braces. To be fair, like this happens a lot in the Spark project. We make people use curly braces. And I imagine there are a lot of other projects which also make people use curly braces. And so Frank has just learned this de facto style from the aggregate of GitHub. Okay, Frank doesn't like incrementing size. Well, to be fair, a lot of folks, especially in Kubernetes, like to stay away from the plus plus convention and they actually like to do the literal arithmetic. So there might be some learning there as well. Yeah. So essentially what this shows is that Frank learns a lot of things and most of them might not apply to you. And so I think one of the challenges is perhaps training it across all of GitHub didn't give the greatest results. And it's like there's individual projects that are large enough to have sufficient training data doing a per project model could also be kind of cool. Yeah, okay, Frank is just being, anything in Frank? Okay, cool. Cool. Do you want to pick another Pia? Sure. We've got five minutes. Does anyone have questions? Does anybody want to see anything else? Okay, cool. Oh, there's some great Scala code. Oh yeah, let's look at Scala. Where's that at? Oh yeah, a great piece of Scala code. Okay, so Frank came in and left some comments. That's a good sign. Large disner not rendered by default. Nice. I thought he did, sorry. It's loading, conference Wi-Fi. Okay. Interesting. Class B. I'm always fascinated by like what he chooses to like comment on. Like what do you think he's saying? We have another one here. Oh, I don't think this would be described as idiomatic Scala. Yeah. This looks more like C. Yeah, I don't.  And be like, what are you doing? Oh, interesting. You're getting the same comments on the same line. Oh yeah. This file really messed with Frank. This is a good file. Questions? Yes. So the question is when is this better than static code analysis? So I mean, I think that the set of things that Frank has learned are not all that better than static code analysis. Yeah. It's interesting. And I think you could take the same thing and apply it to a specific project or like a group of projects. And then it could perhaps learn, we've seen that it's able to extract elements of common style and ask for that. And those things might not be easily captured by the static analysis tools. I know that, for example, the Scala static analysis tools are special. And so it probably depends on your language and what the other tooling is that's available there. Also I think the ability to plug in other features like the issue data or like data from mailing lists or data outside of the repository and pipe that back into the repository would offer a little bit more as well. Oh yeah, right. That's a really good point. And this, unfortunately, the demo isn't able to show the one feature that Frank did really well at because we don't have the issues associated with the pull requests that people are making. But that's, in its train test validate, it did much better for finding situations where the code was kind of sketchy based on users' interactions with it and their reported problems, for sure, yeah. Question. You put them at zero one, and it correctly plugged in. So I mean, I put them at zero. Yay, oh my God. So if there's one where it's working, like, yeah. So there is, so while it is like one model per language, there is a feature which represents what language it's written in, and since it's GBTs, like, that's often probably close to a root node. So to some degree, we have per language models, but not really. And I think if we train directly per language models, we would indeed get better results, oh my God. But what was your pull request number? Or pull request 16, yay. Let's look at the one where it worked, maybe, sort of. Is this the right PR? Yeah. Okay. Oh. Do you know where it is? We can just search for Frank. Okay, was this one? Okay, cool. It's very common. That's exciting. That's cool. Cool. I'm glad it worked once, maybe. Yeah, yeah, yeah. Three times better than guessing, but guessing is not very good. How much does it cost monthly? So we're running everything in Kubernetes. We both work for cloud providers, so we're both kind of spoiled. Yeah, everything is free. Yeah. But I mean, realistically, I think the most expensive component here would be getting the spark side of things up and running. Yeah, so the model training part is expensive, relatively speaking. If you wanted to train it for just your project, you could probably do that really cheaply. Or like if there's a family of projects which are similar to the things you care about, for example, like if you trained it on all ASF Java projects, you could probably train that very inexpensively if cost is a concern. And serving it would be like, I don't know, the cost of one node, or maybe two nodes. Yeah. As far as the data processing and the GitHub endpoint, that's almost nothing. It's a very lightweight server with a few hundred lines of code. Question? Sure, yeah. Question is how we represent the code and if it's all represented as a single vector. And yeah, so we use the word to vet embeddings. We do cap the length of the input that we consider on a given line. Normally lines are huge. And if they are, that is in and of itself, another feature, like line length is another thing, which was a strong predictor for PR comments anyways, when things start to get out of the scope where doing that is reasonable. We end up just commenting anyways. And so we have one vector representation. It's not great. I was hoping it would perform a bit better. I think we probably need different lexers in front of it. I think we need per language lexers and then we could probably get better representations. But for now it's okay. No, that means Frank. Oh, so the question is, if I didn't get any comments, does that mean Frank is satisfied with my pull request? And the answer is, it probably means Frank crashed. Which PR? Oh, okay. Oh, I think there's probably... Trixie, Trixie. So no, so this did not drop the database. But it actually, I think it might ignore gitignore files. I should take a look, but I think it ignores pure.files right now. Because I think I just, yeah, I'd have to double check. All right, okay, cool. Are we out of time? Awesome, so thank you. Thank you all for listening. If you do wanna give us feedback by thumbs up or thumbs down on the pull request comments, that would be greatly appreciated and we'll use it to train a less shitty model.


start out by playing a game, because everyone loves games, right? If you don't love games, probably the right time to change rooms.  Good job. All right. Now, if, now keep your hand up, I'm watching, I saw that. If you do not own a smartphone, put your hand down. Did anyone put their hand down? Oh, awesome. You guys rock.  All right. If you do not have a game on your smartphone, put your hand down. Oh, that's definitely an aw.  The rest of you, good job. Well done. All right, you can put your hands down, by the way. I love a good game. What games do you have on your phones, by the way? Any I should be playing? I like Crossy Road. That's kind of cool. What are you playing? Which one? Oh, I haven't heard that one. I'll have to check that one out. What else are you playing? Words with friends. No, I lose at that. I'm not playing that one anymore. What else do you have? I should have known that. I'm in a geeky environment, aren't I? Beautiful. All right, so games are awesome. We all know that. If I actually have to convince you about how good games are and gamification are, maybe I should just start by taking that rock off you and just going, hey, welcome to this millennium. We all know that they're pretty cool, right? And there's a number of ways that you can do it. So for instance, I was given a really cool challenge of we want to run risk management training for our staff. Who doesn't love a bit of risk management training? Yeah. So the compliance manager was super excited about this. He was like, oh, this would be great. Everyone's going to love it. We're going to do some risk management stuff. Here's a policy. Here's the PowerPoint that we would deliver in the workshop. And then once they've read all that, then they can answer some questions. I said, you really don't like the staff, do you? But she was super excited. She's like, no, they're going to love this. And I went, no, they're not.  So I said, well, what about if I made it into a game? And so I challenged myself and I made it into a risk arcade game from like the 90s. So it was kind of like the Donkey Kong kind of era. And she did love it. I loved it until she requested like the 20th amendment to it.  You know, you've got to love a good scorn package, right? Once. It's a bit like, you know, toolboxes. So I diligently made it into Adobe Captivate. It looked terrific, but man, it took a long time. So then I look at H5P and that's super cool. I can do stuff in that if you're interested in that. I just happened to be back up here next tomorrow. And you can do stuff within Moodle as well. Generally I'd try and go, what can I do directly within Moodle? Because I love it. And it's the easiest way to do things. But sometimes it takes a longer period of time to do that. So what I went looking for was how can I actually build a learning game but make it quicker? Because then eventually I'm going to save some money, right? So I went out and I went looking for, and I'm assuming this is the clicker that does stuff. Oh, not that one. And not that one. Ah, big green arrow. All right. So if you need to be convinced of stuff, yeah, games are good. All right, they gave me some stats and I'm like, yeah, that's great. And yeah, no one cares. Let's get to the fun stuff, right? So I found these guys who already made software that would do this stuff, right? And I said, that's awesome. We're a poor tape. What can you do for me? And they said, you know what, we love Moodle as who doesn't. And we love education. So they actually gave us 50% discount. And the good news is they're going to give you 50% discount too. Because I battered my eyelashes at them. And who could say no to this, right? So these guys are going to give you 50% discount if you want to try it. Now, the really cool thing is that there's a trial as well. Like, you can just have a go, right? And if at the end of that you still don't want to do stuff with them, that's cool. But what I found just by playing with it was it inspired me with my Moodle courses, all right? So it gave me some ideas around some of those other gamification elements I could bring into the Moodle courses that I was doing as well. So you can't lose, right? Big green button. Right. So they've got lots of different games that you can play. And what I've got is just a whole bunch of screenshots that I'm going to show you where I'm going to show you some of the ones that I built. And you can scream out questions along the way, happy to take them. Or you can rugby tackle me in the hallway.  All right? I'm kind of allergic to the pedagogy word and all that crap, right? So I go, okay, what do I want someone to do? Let's try this game. But also what type of person is going to be doing this, right? So for instance, what I ended up doing was build some examples. Because people don't get it until they have a go at it, right? So I took each of the games, thought why would someone use this game? And I built some examples so that the teachers at the TAFE could actually go and have a go at the game. And then they would get some ideas of why it would be used. They particularly liked it for maths. That was pretty cool. So it's really good. Learning games are awesome where there's that rote learning.  They can do it a million times. They're not bugging you. Win, win. All right? So if you love arcade games, you're going to love the jump game. So essentially what you do is you want to get the little dude up as high as you can. It has all the tutorials there. You can turn on tutorials or you can turn them off. Depends on your cohort, right? So you can control what it says at the beginning, what it's called. All you have to do, all essentially you're doing is building multiple choice quiz. Okay? So the teacher only needs to have a Word document of here's my questions and here are the answers. And then you just copy and paste that in. But you look like you're really awesome, right? You're like, oh, yes, I built this. Okay? Take full credit. Okay. And then at the end of it, that sense of competition, it already does the leaderboard for you. But you can also turn off the leaderboard as well if you want to. So the option is yours. Trivia game is very similar to that concept. So it's still multiple choice questions.  You want to get him as high up as you can answering questions along the way. If you answer the question right, you get an extra life.  You've got three lives. But some people go, I can't, I meant it. So if you've got those people, then this would be a better version to go with the trivia game. But essentially does the same thing. And with either of them, you can set a timer or you can turn the timer off. So if you'd like to create that sense of urgency, I usually give them like 20, 30 seconds to answer the question. Some of the games will also increase their score if they answer it quicker. Depends which game you pick. So there's just some examples of some of the bits. So I will use learning games also to teach teachers about Moodle. For instance. So you've got to win-win. They're playing with some learning games going, oh yeah, I could do that. That's pretty cool. Plus they're learning about Moodle as well. Scenario game. Really cool. Again, you can do this in a authoring package like Adobe Captivate. You can do it. H5P Scenario Tool is pretty cool as well. But I'd have to say for gamification, this is much quicker. All right. Super easy. Again, someone can just come up with a document or a PowerPoint going, this is my storyboard. Essentially it's kind of like having multiple choice, but you're saying if you choose this, this is where you then go and what sort of feedback you want to give them. Again, you can put in instructions and stuff or you can turn that off. So I chose this one for one of the first aid courses. And so they're just going through a little scenario with that. Again, you can base it on time. I felt with first aid, it should have a timer. All right. Create that sense of urgency rather than going, wait, wait, give me a chance. What do I do now? All right. So I did put in a timer. And again, you can see that their score is going to be reflected on how quickly they answer that. And also if they, you can choose whether you just bump them forward, whether they get it right or wrong, or spin them back a step. I mean I make them go back and go bugger that was wrong. Let's try that one. And if they have to go back they can lose points, etc. You've got that control. Again, you can do the leaderboard. I scrubbed out the names a bit because they're some of our teachers and there's more of them than there are of me even though I'm a black belt. Some of them did one. The matching game. Anyone into Bejeweled or any of those or Candy Crush kind of games? Oh, come on. Yeah. So this is kind of similar to that. So all they need to do is do some matching. When they get the matching happening, then they get a question. So again, if you get questions right, you get bonuses, you get power ups, all that kind of stuff. And again at the end you can do, oh, there's just some examples of some of the questions. And you can again put leaderboards and things on the end, give them a chance to do it again. And all of these embed directly within your Moodle course. So you can either have them hosted out on external website, or you can just download them as a scorn package, just drop them straight into Moodle. So all your tracking is in there as well. So the end user doesn't think it's anything other than Moodle, which is really cool. See, I did really well. Did you notice that? Look carefully. Maybe because I made it. Scramble.  But this can certainly be helpful as well. And again, you can base it on if you get this question right, then you get the next question right, your score goes up, et cetera. So you get bonuses. And again, you can do leaderboards, et cetera. Recall is a really groovy one. So essentially what you do is you pop a photo and then you ask some questions about that photo. The quicker someone goes, yep, I've got the photo, I've got it in my mind, and answers some questions, the greater the score. So you can have whatever photos you like, have whatever questions you like. But again, they're trying to answer as many questions correctly as quickly as they possibly can as well. So a really groovy one, I like that one. Sorting it. So let's say, for instance, I took this one for some first aid situations and said, alright, what applies to what? Again, these are just different ways of achieving the same sort of goal. There's no right or wrong on which game you pick. You've not only got to think about what it is that you want someone to learn, but who's learning it. So just some examples. Putting imagery in on any of these games is always awesome. And then you've got all these settings that you can choose. So you're picking which game, you're picking how the game is set up. You've got full control over that. Super easy to use. Even I can use it and I'm a moodler. You can choose your theme. You can choose what things are called, whether it's got annoying music in the background or not. All of that is at your discretion. How much you want to torment your students is at your discretion. Love it. You can add some questions. The only tip I'd really give you there is, number one, don't start out super hard with your questions. Build their confidence. Pretend that you're going to be nice and then gradually get meaner. And also make sure you've got some feedback in there as well, not just good job. It's really easy to just go good job each time, but it's not helpful. It can be translated into other languages. And there are analytics in the system as well. You know, everyone loves analytics at the moment. So yes, you can do that because it's interactive. You can very quickly and easily see how things are going. This is the only part you care about. If you're like, ooh, that looks interesting. All right. So there is a discount code.  As I said, you can just do a free trial and just get inspired of, okay, how could I use H5P for that or a lesson tool or Moodle in general, right? Lots of stuff that you can do. That's where you go. So I'll leave that one up. And do I have time for questions? I do. Awesome. I dare you. No, that's before. Yes. Any other questions? Thanks for the presentation. It was good. I've lost it. Oh, there you are. Hey, how you doing? Is there any way to integrate that with gradebook or the batches? Yes, because it comes in, so it's using a SCORM package tool. So literally, if you downloaded a SCORM and put it in, it's just like putting any other SCORM object into Moodle. So all those activity completion requirements, et cetera, all talk nicely to the gradebook and any other restrictions and completion requirements that you want. Great. Thanks. Oh, there's one over there. Run! Oh, no. Don't run. I've seen who it was. Slow down. Hello. Thank you. My question was regarding the particular content that you're using there. Do you also offer an alternative way for cohorts to get into that content? Because there are certain people as we thought don't like games. We teach a lot of older cohorts and anything I try to do like this, I get told they won't touch it. So do you offer alternate ways to get that material? Yeah. I mean, that's super important. The other thing I'd always challenge is who is telling you that they won't use it. Because I get that a lot, whether they teach or go, no, they won't use that. And that's because they're the person who goes, I don't have any games on my phone. You need to get out the way because there might be some learners, irrespective of age, that might want to use that. So I think it's always beneficial, but yeah, if you can offer alternatives as well, ideal. Thank you very much. You're welcome. Thank you very much, Michelle. We really appreciated that conversation and a round of applause for Michelle. Thank you so much.


Hi, my name is Dr. Nadia Chow. I'm a technology analyst with ID TechX. I'm here with Hannah from CellInc at their booth to talk about the BioX bioprinter. Yes, so I'm going to show a little bit on how the printer works. And what you start with is that you have a mixture of your cells together with a bioink or a bio-material. And then you just place it into the printer, attach the air pressure and then you're done. So with a software, you will choose a 3D structure that you would like to print. For example, if you want to print a small nose, you can have a look at the 3D structure that you want to print and see that you've chosen the right one. You can rotate it and see, yes, this is the one we want to see or print. Then you move forward to the print surface and then you can either choose to print in a regular petri dish or for example a 96-well plate. In this case, we're going to print with a petri dish. The next step is to print a printer setup. So here you will choose which printhead that you want to be enabling. So you have three different printheads and also the print surface or the print bed. For this we can choose to print only with one printhead. We have selling start is the material that we have in the cartridge and then it's preset. So all the setting is in there. We move on to the layers. You can choose to have a hexagonal or a honeycomb structure or for example a regular grid structure. And then you can choose which printhead you want to print what part of the structure that is possible to do here as well. The next step is the overview and here you can see what kind of settings you've entered and also be able to test the flow of the bywing. So if you're printing with a new material, for example, it's possible to see that you have the right pressure for the print. Next step is the calibration and that is done automatically in X and Y direction and the set is now manually, but it will also be automatic in the future. So here you can then choose to set the point zero basically and then you can choose the step size. We have ten millimeters, one millimeter and point one millimeter. So then you want to be as close to the surface as you can without touching it and then you will apply and then you're ready to buy a print. So the process is very easy and the idea with the printer is that anybody should be able to use it. If you haven't worked with 3D printing, it should still be a possibility to use the printer. So then when you're printing like this, you can see that it's going a little bit too fast. So then we can go in and also lower the print speed. So if you want to print it and then you can also adjust the pressure. So if you want to have a little bit higher pressure or a little bit lower pressure, that's definitely possible to do during the printing. So, well, that's pretty. Can you tell us a bit more about selling? Absolutely. We're a quite young company. We started in January 2016 and we were listed on Nasdaq ten months after that and we started with five people, I think, and now we're around 45. So we're growing a lot and we see a great interest, like increase in interest in the quality of our printing. And we have one headquarters in Sweden, in government, and then another one involves in the US, that's our US headquarters. And we just recently actually opened a small office in Kyoto with the plan as well. So we're growing. Yes. Exciting. Yeah. So when you want to print a bigger structure like this, you might want to go a little bit higher in this, the printing density. So this one is 25 percent. For printing a good nose as we're printing here, I would recommend maybe 50 percent to get like a stable structure. If you're building it up to a bigger structure, you need a little bit more density in the structure. But that's basically how it works. So this is just for demonstration or as a support material. So if you're printing a very complex structure, you might need some support and then you can use the sterile version of this material. But we have a lot of different materials and it all depends on what kind of cell type you want to print. So if you want to print liver cells, for example, you want a totally different material than if you're printing cartilage, for example. So it all depends on the material or the cell type that you want to print and also the structure that you wish to print. But we do have a lot of different materials and we have a big team in Sweden working on developing new materials and new viowings basically. What's it for? What could it be for in the future? So the applications range. It's so many different applications. We have people printing small cancer tumors for cancer research or patient specific cancer treatments. We have people wanting to print cartilage for in the future, hopefully to transplant into a human being. Skin tissue. It's a huge field for us. It's both the cosmetic companies that want to try their products on skin tissue but also in the future to be able to print a skin replacement or for someone who has a severe burn damage. You can take the cells from the patient and print their own cells in a perfect shape that they need or that they want for the transplant. So a wide range of applications with a printer and it's growing all the time. New applications every week basically. Just one final question. How has the ID TechEx show helped you? Well, it's the first time we're here and it's a little bit different than the ones that we usually go to but it's always good to know what's out there both for us as a technical like questions about the printer but also to meet new possible customers. You never know where you're going to meet them. And that's been so far so good. Thank you so much for your time. Thank you.


Okay so the first question we wanted to do or we were asked is let's figure out what the complete Lewis structure showing all atoms, valence, electrons, and all formal charges for the following species. So the first one sodium fluorohydride that we're looking at. So sodium, what is it? Always. It's just that positive and so it's going to be just the cationic portion. The structural portion of this molecule is the BH4 or the borohydride portion. So the sodium ion is just going to be a spectator ion. So it's going to be just the counter ion to the thing that we're looking at. So what do we know about boron? Right? Yeah so normally it will want to have three, right? But since we have a sodium plus on there, what must BH4 have on minus charge? Okay so it looks like this BH4 minus. Okay so if you're building things like how I taught you how to build things, putting all your valence electrons first, so Lewis structure wise we wanted to say well boron has three valence, right? How many does hydrogen have? One. Okay if I give hydrogen another electron, the way we've been doing it, can it make a bond? What do you need to make a bond? A half filled orbital. Remember guys we talked about half filled orbitals, okay? So here we can, so this, what is this negative charge cell? Gaining another electron, right? So boron here can gain another electron. So we've got that sort of situation and you don't have to do all this if you can do it on your own without drawing all those valence electrons, okay? So it says that we've got a negative charge. Where is that negative charge going to be located on the boron? Should we do the formal charge calculation? Are you guys pretty good with looking at them now? So that's what it's going to look like. So that's the Lewis structure showing all atoms. So if you wanted to, can I erase this portion of it? If you wanted to talk about Lewis structure, you can do something like that just to emphasize the close proximity between the two ions, okay? Showing all atoms, all valence electrons, there, we didn't have them all there. All formal charges for the bonds we see. So that's it? Yep. What's the molecular geometry around the boron? Tetrahedral. What's the ideal bonding? 1 and 9 and a half. Yeah. What would be the hybridization? Sv3. Sv3? Very good. Does that make sense? Is that what you, ladies, put? Yep. I'd say that's what I put. I actually want 3rc. Okay, well we'll do that one next. Any other questions on this one?  Yeah, you can't put brackets around it. You got to put the formal charge on the actual atom. You have to.


What's up everybody? Welcome back to my channel! Hi, how are ya? Whether or not you consider yourself a fan of Jeffree Star, you probably know that he's made quite the empire for himself and his next level famous. Along his journey, he's definitely stepped on a lot of toes though and doesn't hold back his opinions, that's for sure. Which beauty influencer had the biggest drop in followers in one day last year? I'm so sorry. Lorely? That is correct. Jeffree is 33 at the time of this video and has 14.6 million followers on Instagram. Not to mention his audience on YouTube is massive with 16.3 million loyal subscribers who love to watch his every move. He's an internet celebrity, beauty guru and makeup artist, model, entrepreneur and even a singer. If you were big into my space like I was back in the day you would know by 2006, Jeffree was the most followed person on that platform and you'd also likely remember some of his weird songs. Have any of you guys heard his song Ice Cream or am I old for knowing that one? Jeffree is probably best known for his cosmetic line, Jeffree Star Cosmetics and his makeup reviews, looks and videos. I'm just gonna put some on my chin, I know this might be a little weird to everyone but hi, maybe a UFO will just land right on my chin later. Basically anything to do with makeup but in his reviews he can definitely be ruthless too. They announced it in July, there was so much hype, makeup ads came out, product reveals, packaging and then it was like pre-order. And the whole world was kind of like hello. And aside from all of his success in this department, Jeffree is also infamous for getting into some feuds. In most cases these feuds had something to do with makeup and some of them were pretty intense. Let me just remind you one thing, I was her friend for 10 years, you've never met her so do I know the real tea? Of course I do. I'll be getting into them in a little while because today we're gonna tell you all about Jeffree Star's celebrity scraps here for you on Famous Entertainment. What's going on guys I'm Kara and today we're doing something a little different. As always you gotta make sure you're subscribed and ring that bell to be notified when we post videos so you never miss out. If you guys like this idea and wanna see some other lists let me know which in the comments down below. We also have some celebrity exes lists like the Ace Family on this channel which we'll link after. Now let's get into this video. If you're wondering why I'm dressed like this it's almost Halloween at the time of this recording. And if you wanna pick up some costumes for yourself or perhaps some other fun stuff for you and your significant other be sure to check out our sponsor Adam and Eve. Starting with another famous beauty YouTuber Nikki Tutorials. Hey guys I'm here today to show you the power of makeup. Nikki is a Dutch makeup artist and beauty vlogger who gained popularity in 2015 on YouTube most notably for her video showing the power of makeup. She was also BFFs with Jeffree at one point. We need to stop somewhere later because guess what I don't have any setting spray did you bring yours? Oh sh** it's still in Amsterdam. Apparently back in 2017 the two ended their friendship over some unfair collaboration contract Nikki had with makeup brand Too Faced. It was said they cut ties on a press trip to Necker Island with Benefit Cosmetics. This is when Nikki and Jeffree unfollowed each other on Insta and didn't even take photos together on this whole trip. Some even say they had a full out screaming match on the boat. Fast forward to 2018 and there was some more beef following the release of a controversial product release from Tarte Cosmetics. The brand's new foundation line only offered three shades for women of color out of 14 which was obviously pretty rude. Nikki did a review on the line and fans got mad when she didn't address this fact at all. The comments led to Nikki taking the video down and apologizing on Twitter. But as usual, Jeffree had something to say. I think that it's very important that when you do have a huge platform like Nikki with over 8 million subscribers you do have a choice to really talk about something and bring it full forward because yes girl they may have had your shade but half your audience didn't have their shade. And also added my problem with that you've been on YouTube for 8 years. You know you have a voice girl. And also you live your life online. You saw the shade range. You didn't really acknowledge it. I mean he definitely has a point. These days there are rumors that Jeffree and Nikki are cool again but I'm not totally sure. Next up Huda Katan, another beauty YouTuber, makeup artist and founder of the cosmetic line Huda Beauty. This time Jeffree accused Huda of stealing the concept of her easy bake setting powder from the indie brand Beauty Bakery in his Brands That Hate Me video. Now I'm all for people being inspired by other brands but when you literally steal the exact concept and photoshoot from an indie brand how do you sleep at night? That's the real tea.  I gotta say I side with Jeffree on this. He even tweeted Tell Huda Beauty to f off and use products from someone with a soul. And if you care, Jeffree also posted their convo in the DMs. Safe to say these two won't be working together any time in the near future. Next up we have Kat Von D. Probably the most well known Jeffree feud is the one he had with Kat Von D. These two were actually friends for a decade and Kat even helped him start his makeup career. Kat was best known for being a reality TV star and tattoo artist on the show LA Ink and she also has her own makeup line at Sephora which came out in 2008. The beef between these besties apparently started in 2016 when Kat exposed Jeffree for not paying graphic designer B.J. Betz for the work he did for him. Kat then announced on Insta she won't be associated with Jeffree anymore and released a video exposing him. Just because I called you out on social media about being a bully doesn't mean that you can post a tweet that says hey you know Kat Von D has never supported me in my makeup line when honestly Jeffree if it wasn't for me you wouldn't be where you are now. I mean as far as your makeup line goes. It's a long story but if you've seen Kat's video you would know she had plenty of reasons why she couldn't be friends with Jeffree anymore including the way he allegedly copies ideas his drug use, racism and his bullying towards others. Jeffree stated about the feud even though we were friends for 10 years you never know you're going to literally wake up one morning and have your best friend backstab you in front of the entire world. He also posted a video explaining his side of the story and showing text convos that Kat apparently forgot to include. So I am going to show our text conversation on camera because I just think it's fair and I really think that that's a huge chunk of a story that is missing. After I asked her to film she goes silent. I do not hear or speak to her until a few days ago. I could go on and on explaining the feud between Jeffree and Kat but I think you get the idea. Who said where you guys on in this one? Let me know in the comments. This next Jeffree drama was with a whole group of beauty influencers. Laura Lee, Manny MUA, Nikita Dragon and Gabriel Zamora. I'm not entirely clear on how this one started in the first place but I know Jeffree was super close with Laura and Manny once upon a time. Jeffree sat down with Shane Dawson in his documentary and explained with my ex friends people still don't really know what went on. Why do I feel like they need to know? Because there's so many versions of things that never happened out there. Apparently these ex friends he refers to include Laura and Manny. He also threw shade at the beauty community in his tweets. Even when a fan asked Jeffree if tweets referred to Laura he said You know nothing about her personally. Her soul is pure evil. Ouch.  That was captioned Which is bitter because without him we're doing better. A clear jab at Jeffree.  Long story short I don't think there was a winner in this feud considering fans exposed racist tweets from both Gabriel and Laura. It all just sounds like a huge mess to me. I want to talk to you guys in this video. It's been so fun. Moving on to Jeffree's beef with Kylie Jenner. This wasn't the only lady in the Kardashian Jenner clan he had a feud with and I'll tell you who the other one is right after this but I bet you already know. For $360 I am very curious why this is, I call it vegan leather it's like a plastic faux leather it's obviously not real and this does feel very cheap so I'm going to start the review off by saying this feels like it's from the Dollar Tree just being f***ing 100% Jeffree is known for throwing shade at Kylie's brand Kylie Cosmetics pretty often whether in his product review vids or on Twitter. Back in 2016 when Kylie released her lip glosses there were angry customers over what looked like a faulty applicator and of course Jeffree had something to say. Looking at past tweets you can see how Jeffree went off but Kylie didn't let all of this get to her and she stood by the fact that she has the same passion for makeup as him. Later on Jeffree also came at her accusing her of copying his packaging at one point. He said, I gotta know one thing with all that effing money she's made why did Kylie Cosmetics use the same packaging as my liquid lipsticks that have been out since 2014 invest and make something different maybe. The second Kardashian-Jenner sister that seemed to be on Jeffree's hit list was none other than Kim K but I don't think he came for her half as bad as he did for Kylie. This happened a couple of years back when Kim posted swatches for her KKW powder contouring kit. Of course Jeffree went on Twitter to say um Kim what is going on with those new swatches looks like chalk. Girl them powders like sound dry on her snap like they just like looked a little chalky. So of course my tweet went a little crazy everywhere and everyone started talking about it even more and then it turned into a circus. Kim ended up posting on Snapchat to defend him against her fans coming after him. Because of his remarks I'm learning like from the best like from Mario like how to swatch properly so guys like and I see you being so petty bringing up things in his past so let him live like I welcome honest you know comments about my products and because of it I'm swatching better now. Anyways the internet got a bit out of control over this drama but I personally don't think it was a big deal. Jeffree still ended up doing his honest and fair review of Kim's KKW contour and highlight kit. Last up on our list is Jeffree's feud with James Charles being another super famous beauty YouTuber James seems to find himself in hot water quite a bit. I'm sure you're all familiar with the huge James vs. Tati Westbrook scandal that happened earlier this year and at the time Jeffree added to the drama and came at James. Even though the two appear to be friends and they filmed a bunch of videos together Jeffree backed up Tati's claims that James inappropriately targeted and harassed straight men. He tweeted There is a reason that Nathan banned James Charles from ever coming over to our home again. There's a reason why I haven't seen him since Glam Life Guru's birthday in February. He is a danger to society. Everything Tati said is 100% true. Then Jeffree's merchandise production company dropped James' label sister's apparel as a client. After all of this Jeffree ended up apologizing about how he was towards James and said his accusations were based on rumors. Well then. So Jeffree's list of famous feuds is definitely longer we know he's also gotten into it with founders of big makeup brands such as Too Faced and Lime Crime. But you get the idea and I definitely don't think this will be the last of Jeffree's feuds especially as long as he keeps reviewing makeup. After looking at that long list of who Jeffree's come out in the past what do you guys think? Whose side are you on? I think Jeffree's one of a kind and just doesn't hold back his thoughts. Maybe sometimes he should have a little more chill but I think his fans appreciate his honest and sometimes harsh makeup reviews. I guess we'll just have to see what's next for Jeffree or what drama. If you guys like these videos let me know what other lists you'd want to see. Make sure you're subscribed and follow me on Instagram if you want to chat more. And thanks to Adam and Eve for sponsoring this it helps us bring you guys more videos. I'll see you guys next time. Bye.


This exciting book is called Fun in the Mud. The author is Anna Prokofs. And the one who drew the pictures is the illustrator, Dave Clegg. I will read through the story and we have different activities for you. All of you children and teachers will work together on activities related to the story. We have a list ready to go. Three big words you need to know. Snout.  Squeal. This means a loud, high-pitched sound from your throat. Strutting. This means a walk that is done with confidence. Here we have the farm. Over here we have the barn. The pig is laying down. And over there we see the goat standing. On the fence, you can see the rooster. The sun is rising on the farm. Time for rooster to sound the alarm. Get ready for a big surprise. Pig squeal. I'm going in the mud today. Pig races to the squishy mud. He splashes in with a great big thud. Yahoo! Pig says the mud's all... Then goat trots over to join the swine. Goat says with glee, I found someone to play with me. Pig looks at goat and shakes his snout. The mud's all mine. Pig says, stay out goat says sadly. That's not fair. He knows that friends should always share. Let's take turns goat says. It's fun. There's lots of mud for everyone. Just then rooster comes strutting through. He wants to play in the mud too. Go away. Pig says the mud's all mine.  Rooster tells the swine. Goat says the mud will fit us three. We'll all have fun. Don't you agree? Pig thinks. He shouts. Mud party can begin. Splashing and laughing. The three farm friends play in the mud. Until the day ends. I have a big question for you. Did the pig have a lot of fun playing around in the mud when he shared with the goat and rooster? Tell me why.


Good day fellow investors. I decided to start an investing stock market vlog. Most of my content is researched and then I share my research. However, there are lots of questions which I can answer off the bat. I don't need to make research, I don't need to prepare and those answers I would like to answer in a vlog. I think it will be very valuable especially for beginning investors because investing is more about the mindset. We can all find all the data possible today with internet, with everything. So we have everybody has the data. Now it's important how you analyze the data and what do you get out of that data. And in this video I want to answer such questions. How do I research stocks? What do I think about such a stretch of this on that? What's just my perception without going deep into the research and analyzing the supply demand side of stuff and so. Especially if you have off the bat questions please put them in the comments and I'll be happy to reply. Today I want to start by answering one question that comes often. Where do I find the stocks that I recommend? How do I go about finding those stocks? And that's pretty easy so let me share it with you. If you type in company list NASDAQ you get to this page. You have all the companies listed off on NASDAQ NYSA MX sorted by letter, by region, by industry so whatever you want. So if an industry is cheap oh let's check that industry and then you can check the company. What I usually do I go by letter so I check everything. So I have I download the data I put it in an excel shield I grade it I give comments and then here and there I find interesting companies that I researched deeper. Recently researched the letter T and then I found three house that I recommended in a video a few days ago. In the letter T I found another interesting stock and this will show you how I go about researching those stocks. So something interesting I saw Trivago I know it's a growth stock internet online booking very interesting company it IPO'd last year it spiked to above 20 and now it's below the IPO price so that's interesting. What happened there were downgrades Morgan Stanley downgrades Trivago on increasing headwinds. What has happened the management lower growth from 50% to 40% that's terrible should deserve to go bankrupt apart from the jokes shares are down so again interesting because I'm happy with 40% growth I don't doesn't have to be 50% for me as always I'm not trust the management I want to see what are the trends I look at Google trends I look at the research okay Trivago is growing alongside booking the same as the market Expedia however is declining that's interesting then I further researched the company what's doing the company how is the business how do they make money what's the business model and I find something that puts me off in this case 46% of Trivago's revenue come from Expedia 43% from price line the owner of booking so it's a growth company yes but it depends on two customers and they will try to do everything to avoid going through Trivago they want to have direct access to customers in order to lower their costs and increase their profits so that's something that puts me off tells me okay too risky for me too complicated it's not an investment it's a bet and I don't like betting because betting implies high risk high reward situations so perhaps Trivago is a company for you if you like betting but not for me so to conclude I simply research everything out there I go stock by stock so that's the way that I learn about the market now I learn about Trivago I learn about other stocks when I repeat the research process usually two times per year I research everything or it's a country I don't know a year two years ago I research all the stocks in Poland Italy Spain so it's so that's practically what I do I go through lists check the companies until I found something interesting and if I find five six investments per year that are interesting I'm a happy champ for now I have five stocks in my portfolio I'm very very happy owning them and that's it if I find the next stock probably something will happen like it happened to you buy and then I'll have money to buy the next stock or I'll wait for it to become a bargain the more I do research the more I know the better I understand the market Buffett used to say that he needs five minutes to analyze a business I'm not yet at five minutes but perhaps in 10 20 years I'll be at five minutes to know whether something is a good investment or not I'm looking forward to your comments let me know if this vlog idea is something you find value I think it's also valuable for me because it will allow me to systematize my mindset my thinking it's not just about research data and stocks it's about our mindset and our approach to investing by sharing it with you I will systemize what I think which will help also my investing and my investment returns thank you for watching click like and I'll see you in the next video