I'm sure it's going to be fine. Okay, let's then start, I would say. Let's start with Tabie, you know what we need to do when we start. Everybody smiles. Okay, and I think I will not get interrupted, hopefully, this year on. Yeah, she's asleep. With all my kids bashing through the door, I hope they just stay there. Hello and welcome everyone to a new video from our Azure Stack Hub partner solution video series. My name is Thomas Maurer. I'm a Cloud advocate at Microsoft and I'm joined as always by Tiberio Radu from the Azure Stack Hub engineering team. Hey, how are you today? Hey, Thomas. Hello everyone. I'm doing great and I see you've got the right t-shirt on, so that's awesome. Absolutely. I always try to match the kind of like vibe it's going on. Or it was just top of the laundry, I cannot remember. Okay. So we are having another very interesting partner today we're going to talk to. Who am I going to talk to today? Definitely. Today, we're going to talk with Umbrella. They are a partner that's actually focusing on both providing managed services, as well as a platform that their customers can build solutions on top. So as we went through these series, we've met with both partners that provide platforms, partners that build solutions on top, that provide managed services. So it's a range of partners. Umbrella is providing both the IaaS platform if you want, as well as all the way to actually using App Services and PaaS and that sort of thing. Marcelino will go in more details on these and I'm sure you guys will have a great time. Oh, that's awesome. I'm really looking forward to talk to Marcelino. By the way, so welcome Marcelino. Great to have you on our Azure Stack Hub Solution video series. So, Tippi introduced me a little bit to you and your company, but I obviously want to give you the opportunity to explain a little bit more about yourself and also obviously the company you're working for. Yes. No, thank you very much, Thomas and Tippi. It's an honor and a privilege to meet you guys and to be here. So basically, I'm Marcelino. I work for Umbrella. I'm a Cloud Platform Specialist. I look after our 12-node Stack for Umbrella. Umbrella is a cloud-based company focused on empowering our customers and re-sellers in making the most of Microsoft Cloud to digitally transform New Zealand businesses. So that's in a nutshell what Umbrella is and what we do. That's awesome, especially I like the locations or you're based in New Zealand. That sounds like a lovely place. I would love to visit one day. So, you mentioned that again, you're like a service provider for your customers offering Azure Stack Hub to your clients. Can you explain a little bit more about who your clients are and what you're offering to them in that sense? Yes. So, we have a mixture of clients on Stack ranging from small businesses that have a few computing storage to large businesses. Like one of our clients where they're in the health sector. Look, I can't go too much detail about our value clients, but that's just the range of clients who have the mixture ranging from very small compute to a large enterprise of customers on our platform. It's multi-tenanted. We do have good solutions in place for our clients and we do have managed services that we offer through our portal and it makes it really good for our customers because we have our own portal and from there, they can go and purchase anything they want with Azure Stack and services that we offer for them. Okay. That's awesome. That's quite a lot of things you offer there. So, first of all, you mentioned that you have a multi-tenant Azure Stack. So, meaning that you can offer the same Azure Stack infrastructure to multiple different customers and they can use their own Azure AD tenant, right? Yes. That's correct. So, that is fantastic. Then the other thing is you're not just selling, as far as I understood, you're not just selling the Azure Stack and customers can go through your portal and buy Azure Stack and they get access to the Azure Stack infrastructure. You're also adding some additional value by offering managed services. Now, that's great. Again, I love what our customers and partners are doing with that.  So, yes. We chose Azure Stack because, as you know, New Zealand is a very small country on the map, just a very small country. So, we don't have Azure public and the decision around it was for us to have our own Azure public in Auckland or New Zealand and this is how Azure Stack came about and this is the journey we pursued and we wanted to become the gateway for our clients to use Azure Stack, not only because everything gets kept in a data center and within the country but then also helps him move to the cloud and start moving some of the resources from on-prem to the cloud. So, Azure Stack for them is effectively the cloud but they know it's in New Zealand, you know? So, that was our journey and to make it a hybrid feeling for them so they know that when they get to the cloud this is how it's gonna look and feel and just to give them that kind of experience. Okay, also again, we had a couple of cases where this is absolutely interesting where on one hand you're building this to give customers the choice to have it in the data in New Zealand, right? And having these offering not just the data but also getting like cloud services like consistent cloud services with Azure in New Zealand where they can have IaaS and PaaS services and so on using Azure Stack up and that. And as far as I understood it's also interesting like you help customers also prepare kind of like modernizing their infrastructure on your Azure Stack Hub like so they can when they go to the like they can also go to public Azure as well for some services. So they already prepared for that, right? That's great, yeah. Okay, so now this is absolutely great reasons to use Azure Stack Hub. What would you say is like how are you providing or how are you using platform to provide value additional value to the customers? Yes, the platform features we are using for our customers is the infrastructure as a service for them platform as a service. We have Azure apps as an offering, Azure functions. We also use the foundational storage and key vaults. We're also waiting to trial AKS. We have a client to potential client that wants to use AKS on there. We do also use ARM templates. We've also automated one of our client deployments using ARM templates with Azure Pipelines where we deployed basically the whole compute infrastructure system, you know, the basics, the networking, the compute, the storage, even key vault. And we did that within a few good, should I say minutes to Azure Stack Azure Pipelines. So it's really good knowing that we could automate some of the stuff for our clients. So we have a variety of different features that we can provide for clients. And not to mention, they able to on-sell as well, you know, so they able to sell these services for us as partners, as valued clients going forward. So they potentially can sell Stack for us as well under their own subs. Okay, that is interesting. So there's like, again, I love the story where you get actually these consistent services. Again, like you get IaaS, like Azure IaaS right on Stack and then like serverless with functions and stuff like that. But then you also mentioned the reseller part. So you basically, if I understand that correctly, you basically offer your Azure Stack Hub services to obviously customers, but you can also offer that to partners basically, which then can go out and resell that on the same Stack, right? Yes, that's correct. Yes, basically. And we have our different, you know, quarters that we offer. So we have the way we've distinguished it to, we've got a pay as you go for our normal clients. They can use that for anything that they want to on the service. And then we also have one that we've labeled as cloud reseller pay as you go. So that distinguishes the difference between it too. So we can actually have a look at see exactly what's happening on our infrastructure. No, that's great. I really love what like the way you describe what the offers are with the hybrid consistency, but then also I really love the story with your like reseller part because I think we haven't really, in this series we haven't really talked about that and it's great to see that this is also a possible way. So with that, I know that obviously some of our viewers will have definitely more questions and they will want to find out more about you and your company. So if they wanna find out more, where should they go? Yeah, I mean for our clients, I mean the easiest is just to go to our site, which is www.Ambrella.com and they'll have everything there. They've got the about the contact and to obviously getting in touch with us, through all the relevant links on the site. Okay, that is perfect. Thank you very much, Marcelino. Thank you very much, TB for introducing me to umbrella. Again, we had a very good talk. Make sure you check out their website. We will put the link in the description of this video so you can easily just go down and click on it and you get the link. If you have any questions, feel free to leave a comment and with that I wanna say thank you for everyone for watching and hopefully see you in the next one.


In order to really do this Harry Potter giveaway contest right in order to pick the perfect winner I needed to bring in the big guns. Ah My son. Yeah, I just did my own zoom in sound effect Connor that's too much food. All right, so We got my list here of all the entrants there's about 400 and well, I can tell you exactly four There's 444 there's duplicates because you could to get your name put in multiple times depending on how many of the videos You've commented on you want to help me pick this winner Connor? Yeah, yeah, okay We are at random.org. We're gonna paste all the entrance in boom And then all we have to do is randomize Here we are the winner is Miss Amirala. Hi. Well, there you go. That concludes the giveaway contest. I don't what are you doing, bud? Congratulations to the winner whose name I've already forgotten I'm gonna have to look back on this camera footage to find out we will get that Blu-ray or dbd collection sent out to you right Away, I'll I'll hit you up on Twitter or Facebook or something and okay. He screwed around my computer. I gotta go


this you can see what's happening here is just like what we saw pictorially if I'm saying well if this orange is everything up to 80 everything over that point is going to be the blue and everything under the curve blue and orange represents a hundred percent so if I'm using a formula I can use the same formula and just say it's going to be one or a hundred percent minus well first I'll just say this is going to be equal to the same thing I'm going to just do the same thing here and I'm going to say then that this is going to be equal to one one or a hundred percent right minus and then add my norm dot dist norm dot dist so there it is I'm going to select tab to pick it up this is going to be running much the same way I'm going to be picking up my x which is going to be the 80 now notice it's a little bit tricky because this is equal to so the 80 has already been picked up here so if I'm trying to do the inverse I'm going to say that this I can't say it's going to be greater than or equal to so I'm going to say minus then I'll pick like a really low number I'm going to say I'm going to say plus point oh oh oh oh one right so now it's not exactly equal to here and then I'm going to say comma and then the mean is going to be the 74 again and then comma and the standard deviation is the 10 as before and then comma is it cumulative we're going to say it will be cumulative so that's going to be a one and then brackets percentify at home tab number group percentify add some decimals and we get to that 70 30 74 again so if they ask me a question such as what's the likelihood that it's going to be greater than 80 then I can still populate the information up here and now the orange is representing everything less than or equal to and the blue is in essence representing thing everything over and above that amount so that's a a little bit kind of tricky to use this graph we could of course make a different different graphs as well and but sometimes it might be easier to use the same graph so we'll take a look at some different variations to make this graph on the right to deal with these different questions of less than or equal to or greater than and then of course between would be the next question that would often come up now notice if I go up to my formula up top so this is now I didn't make this a dynamic formula so if I go into this now I can make this dynamic let's go into here and say this is going to be equal to I'm going to put the quotes around the text area so this is going to be from here to here I'm going to end the quotes and then I'm going to say and so now I'm going to say and to tie it together and then I'm going to replace this 80 with this actual number up top or that G 10 and then and to tie it together to this last piece of text bracket or quotes and quotes all right so I'm going to say enter and so now we have a dynamic field so if I made this go down to down to 60 for example now you have the 60 over here and you can see it reflected in the graph and you can see it change in our dynamic field so let's bring it back up to 80 and then I'm also going to say this let's say this equals equals this one and then I'm also going to tie it together so I'm going to say and and then I want to tie it together with this one so now and let's see if I can wrap that home tab alignment wrapping the text so now this this column is kind of representing those two things which can help me to basically visualize either of those questions with the orange and the blue is the general idea and I can even adjust my legend over here if I wanted to by going to the the chart group I can go into my data and I can say that this one right here the p of x let's go ahead and edit it and then in the name up top I'm going to change the name to be like this was the blue one I'm going to say this is going to be p is greater than or equal to 80 hopefully I get this right and I don't and then this one I do get it backwards and it's going to be edit and I'll change the name here and say this is going to be the p is less than or equal to 80 and then okay and okay so now I'm going to go back on over and now we have the legend of the blues the amount above the 80 and so so now we can kind of ask both of those questions when you have and you can kind of play with it pictorially okay so then of course you might also get a question of something being between let's do the z score first though so I can do the z in the same way let's just calculate it again so we get an idea of the z again so this is going to be equal to I'm picking up the number we want I'm going to say is x is 80 minus the the middle point closing up the brackets divided by the standard deviation divided by right here I saw the divided by and then standard deviation so there's our formula I'm going to say enter add some decimals home tab number group decimalizing it so there's our point five once again and then again I can do this I can do this same calculation but now with the z score so this is going to be equal to norm dot s dot dist and then enter and so now all I need is the z because the z you'll recall just as we saw is taken into consideration the mean and the standard deviation in that calculation so I just need the z now comma it needs to be cumulative and notice I didn't put the one minus so it's going to be wrong but let me just show you I'm going to say this is going to be true close it up and so if I percentify that I can say oh wait a sec if I put those together that adds up to 100 this is the inverse I got to this I need to say one minus I'm going to double click on it and say this is going to be one minus a hundred percent minus that and then I get that same number now the next question that we get is as you can say that this is going to be P and let's say let's say that that the lower the lower is now going to be let's say 75 in the upper is going to be what we had up here which is just going to be the 80 so now I'm going to say between the lower and the upper is what we want so we might put that in here is by saying P is going to be and you could represent it this way like 75 is less than or equal to the the x which is which is less than or equal to the 80 I kind of like doing this I don't I know this may not be that I tend to think of it as x is going to be is going to be less than less than or equal to


So, we've seen that if n is prime, then every element, 1, 2, 3, up to n minus 1, has an inverse under multiplication mod n, and so these elements form a group under multiplication. We've also seen that the powers of A under multiplication mod n also form a closed set under multiplication. So, let's see where this takes us. In this, we'll follow in the footsteps of Leonard Euler, who in 1755 presented a paper whose English title might be something like theorems about the remainders left by division of powers. It will also be helpful to remember that if n is prime, the multiplicative group of integers mod n has n minus 1 elements. So, suppose n is prime and A is less than n. Let's consider the powers of A mod n, that's A, A squared, A cubed, and so on. Since there's a finite number of remainders mod n, we must eventually have a repetition. A to the power m must be congruent to A to the power n, and we'll assume that m is greater than n. Now if A to the m is congruent to A to the n, then we know their difference is a multiple of n, and let's factor out that A to the power n. Now, since we've assumed that n is prime, it must divide either A to the n or A to the m minus n minus 1. But if it divides A to the n, it must divide A, but it can't because A is less than n. And that means it must divide A to the m minus n minus 1, and so A to the m minus n must be congruent to 1 mod n. And so we know there's sub-k, where A to the power k is congruent to 1 mod n. But remember, if it happens at all, it happens a first time. And so there's a least solution, x, to A to the power x, congruent to 1 mod n. So Euler proceeded as follows. But k be the least power for which A to the power k is congruent to 1 mod n, where again we're assuming that n is prime. And the terms 1, A, A squared, and so on, up to A to the power k minus 1, have to be distinct. And for reference purposes, we'll call this set A. Now we claim they have to be distinct, but you should prove it. And so suppose A to the power i is congruent to A to the power j, then, well, bad stuff happens. I won't say exactly what that bad stuff is, because you should be able to prove this on your own, and you should do your own homework. However, here's the important thing. There are, at this point, two possibilities. Either we found all possible remainders mod n, and remember, if n is prime, the multiplicative group of integers has n minus 1 elements. So that means k is equal to n minus 1. Or we haven't found all possible remainders mod n. So if we haven't found all remainders, then there's some b that is not an element of A. And so let's consider the products b, bA, bA squared, and so on, and we'll refer to this set as bA. Now to begin with, none of these can be a power of A. Well, we should prove that. Suppose bAi is equal to Aj, then, bad stuff happens. We'll leave that as a homework problem. Additionally, every element in this set must be distinct. And again, suppose one of these, bA to power i, is equal to bA to power j. Then, well again, more bad stuff happens, and we'll leave that as a homework problem. But if we put our two results together, that says if A is the set of powers, and for b not in A, bA is the set of powers multiplied by b, then not only is bA disjoint from A, but it has the same number of elements as A. And so again, either we've found all possible remainders mod n among the two sets, and so 2k is n minus 1, or we haven't found all possible remainders mod n. So if we haven't found all remainders, there's some c not in A and not in bA. So let's consider cA, again, the product of c times each of the powers. And again, they're all distinct. They're all distinct from A because c is not in A, and we have our lemma. And they're distinct from bA because c is not in bA. We can't use our lemma for that, which means we have to prove this statement. Well, let's check it out. Suppose cAi equals bAj. Well, let's see what actually happens here. Because I know that A to the power k is congruent to 1, let's supply those missing factors and multiply both sides by A to the power k minus i. And so that gives me c to A to the k equals bA to the something. And A to the k is congruent to 1. And so that I know that c is congruent to b times A to the something. And so c is in bA. It is b times the power of A, except we assume that it wasn't. And so this is the bad stuff we run into. And so once again, there are two possibilities. We've produced all remainders mod n, and so 3k is equal to n minus 1. Or we haven't found all possible remainders. And we can lather, rinse, repeat. And if we want to summarize our results, we have the following. Suppose n is prime and A is less than n. Let k be the least power, where A to the power k is congruent to 1 mod n. Then what is the following must be true? k is equal to n minus 1, or 2k is n minus 1, or 3k is n minus 1, and so on. And in general, n minus 1 must be a multiple of k. Equivalently, we often state this result as follows. Let n be prime. The least k for which A to the power k is congruent to 1 mod n is a divisor of n minus 1. So how could we use this? Well, suppose we want to solve 2 to the power x congruent to 1 mod 43. Now 43 is a prime number, and so the Euler Fermat theorem applies. And so we know that the least power that makes this congruence true must be a divisor of 43 minus 1, 42. And so our solution has to be one of those divisors, which we can list. And so we can try each one of these in sequence. So we'll find 2 to the second, 2 to the third, 2 to the sixth. Well, we can find that because that's 2 to the third squared. And working mod 43 means never having to work with large numbers. So we can reduce and find 2 to the seventh. Well, that's 2 to the sixth times 2, and so that will be 2 to the 14th. Well, that'll be 2 to the seventh squared, but I don't really want to multiply 42 by itself. So we might notice that 42 is also congruent to negative 1 mod 43. And so 2 to the 14th will be, and that gives us our least solution.


So basically this is a very simple meeting we were told by the state that the vote for the amendment has to happen on one day it can't be split between the town meetings between Monday and Tuesday. So we're doing them the vote for on Stockbridge's town meeting day which is the Tuesday. I've already talked to Julie Smith.  Election day so we really appreciate it. Anybody go by the Rochester town office. Please show your appreciation because it's a big thing. So all I need from you all is we need to do a motion to move the date the warning date from March 1. First yes Amy. Is the location different now. Yes, and it is but in the morning that Dean has prepared it is as Julie told me it's going to be the town office. And it's going to be from 10am till till 7pm at the town office. That is in the warning that Jenny has right now Jenny Jenny has the final warning she actually corrected the time for Stockbridge and then she will print it out as soon as we approve this and and start signing it and then tomorrow morning it'll be a Stockbridge for the Stockbridge people and then get moved over to us. Okay. Just to confirm Ethan the Rochester is at the town office from 10 to 7 and Stockbridge is the town office from 9 to 7. Excellent. I know the Rochester is correct. I assume what you got off the Stockbridge web page is is correct. I'm not sure if Dean is was copied from last time but what I put in there is what the website says so hopefully it's correct. The Rochester party is correct I did look at your version of it and and definitely the Rochester part is correct. So the main thing is the date that's what we have to vote on so and we got a little correction from a charity about doing using so moved and that we do need to repeat we should repeat motions. When they're being moved and then seconded and not when they're seconded but when they're moved so I will entertain a motion to change the date of the special to town meeting warning from March 1st to March 2nd. Could someone. I move that we change the date on the special town meeting vote warning from March 1st to March 2nd. Could we have a second on that please. Jenny seconded. Excellent. All in favor signify by saying aye. Aye. And I heard that I heard everybody good we're all proved so have it Jenny you're you're good to go print it out and I believe it's going to be down at the town offices of Stockbridge tomorrow morning. Well I'm bringing it I'm bringing it to Lindy in the morning I'm not sure what she's doing with it. Okay bring it to Lindy. Probably around. I'll try for like eight. Okay because I'll just I'll just head over to TSA a little bit late and swing by like at 815 then. Okay, and sign it right and sign it then. Because that way that way you don't have to. I don't have to drive to Rochester in the afternoon or when he doesn't have to wait until the afternoon to move it up there. Wendy has a lot of meetings tomorrow so I'm leaving it in the mailbox for her. So if you happen to be late. It could be in the mailbox if it's before Janet gets it. Yeah, like I said I'm going to try to get there right at 815 to give you a chance to deal with kids and all the things that might make you getting there at 805 or 810. But that way, but but I want to get to I need to get to to TSA as soon as I can. Cool. And then is and then it'll be brought up to the Rochester town office for us to sign for the rest of us to sign is that correct. Lindy Lindy said she'll bring it home with her when she brings it home it'll be brought up to. I don't know if it's a town office but I imagine that's not till the end of the day. I can confirm that and get that get information out to you when it'll be moved up. Okay, so we know what to get it. Justine do you think you can get down there in the morning. Right. Yeah, I think I can get there in the in the morning is there a time. Sorry, I'm kind of also trying to all there. Is there a time that I buy that I have to sign by with the time. I say, we're going to wait until you until you get there. And once you're signed because the other two will have done it. So you then it just be about you getting, you know, you getting once you get there then they'll be ready to take it up to Rochester. I mean to get this either posted or provided to start for the book or something. I talked to Jamie and and it's just, it's just a little too tight with the three day weekend. If we make the book for Tuesday morning if they hold off to publish it. I don't know. I don't know if we're going to make it and that's, that's okay with me. We'll post it and it'll still happen and that's fine. It'd be nice to be in the booklet but it's just too tight. I don't know. I think. So, if we can get it signed tomorrow or over the weekend and then by Tuesday we'll have it posted. Any for the business. The Rochester office will they be the one that's scanning it and sending it back to the SU. I will make sure that that is the case. Gotcha. Good. Thank you very much. I will entertain a motion to adjourn. I make a motion to adjourn. I second that motion. Great. All in favor signify by saying aye. Aye. Thank you very much.


Hey everybody, welcome back to magic orthodoxy. My name is David and these are the two best marked decks on the planet All right, so if you've watched my channel for any amount of time, you know that I really like marked decks I like gaff decks. I like magic tricks And so I've done a couple reviews for different marked decks in the past even to the top 10 countdown For some of the best of marked decks since that countdown I've had two other marked decks come across my desk And I've had many of you many of you out there asking me questions about how I think these next two decks compare To the others and let me just say I think that the best two marked decks on the planet And here's why first of all a quick conversation about what would make these the best mark deck why I think they are now They don't you don't have to think they are you don't have to agree with me Okay, this is this is not a perfect world. You don't have to agree with me. We just have to get along Okay, just have to get along so Here's here's my here's my criteria.  Granted, they're not available in blue, but they are available in red I think red is probably the most popular color of a deck of cards now You and I both know that the world is used to a writer back deck that used to the 808s. These are 808s They're not writer backs, but to the layman who doesn't know any different. They're gonna look exactly like it They're not gonna look like any custom gaff.  It says bicycle It says what everyone is familiar with looks like a deck of cards that everyone is familiar with now They're not writer backs, but they are alternatives to the writer back. The reason why they're not writer backs is right now United States playing card company is very protective over their back design is the trademark back design and They just don't allow you to make any sort of modifications to that back design other than just a standard color change And so there are other decks out there that are very similar in style that give the same appearance and would fly Right past somebody with the untrained eye. The first of which is the mandolin back now the mandolin back is just like it sounds It's a person holding a mandolin an angel, right? I'm an angel holding a mandolin and the mandolin shape is kind of roundish on the bottom So it does kind of look like the bicycle tire Everything else looks exactly the same And I think again, it's gonna fly right by someone who's not paying attention The second deck is the maiden back now the two almost are interchangeable if you look at the back again It's an angel. She's standing upright her arms are outspread But again, if you weren't looking for that bicycle the up-person, you know the other guy riding the bike Again, it's gonna fly right by somebody who's just not paying attention All right So you have two different designers out there that have released these two decks in mark deck form And I'm gonna tell you what they are right now All right So your first one is the maiden back now the maiden back are the marked cards and they're exclusively available at Penguin magic calm now one of the reasons why is because well penguin magic releases them and If you purchase through them, then you get the video downloads and really Those video downloads are only available through their checkout system You're gonna get two different videos and both of which cover all the ins and outs of using mark cards And so it's it's an awesome tutorial awesome instruction And the best thing about this is these are nine bucks nine bucks for a single deck of mark cards making these one of the cheapest Mark decks you can buy on the planet Especially since they are so familiar looking so reliable looking at nine bucks a deck This is really your staple deck This is gonna be your workhorse deck that you're gonna have people sign, you know They can autograph it you can do it card you can do card work with them tear them up Who cares, you know for $9 a deck plus if you buy a brick get this if you buy a brick a bricks only $60 that makes these decks five dollars a piece only five dollars a piece That's the best way to go right there.  All right So the second one, which is the mandolin back that is going to be the marksman deck now The marksman deck is through luchter may and vanishing incorporated and you can probably find these from a couple of different Retailers including for an endomestic now this deck is a little bit more. It's thirty five dollars $35 because it comes with almost two hours of video performance and instruction Plus there's a PDF. There's a whole bunch of stuff that Luke has included with this So you're just getting a just a pile of Tutorial information plus you're getting all of Luke's just wonderful routines and some of these routines aren't just absolutely insane Mind-boggling all mentalism. You're gonna learn how to find your current card You're gonna learn how to find the card above it You're gonna know the position of any card in the stack You're also gonna know like when the spectator cuts the cards You're gonna know how many cards are in their hand plus. You're gonna know how many red cards are in their hand Plus you could also do the combined total of all the values that they're holding as well So Luke has just given you just an insurmountable amount of just forward and backward awesome magic tricks You can do with this tons of different ideas like I said thirty five dollars a little bit more expensive Obviously, but Luke and vanishing incorporated have said that replacement decks will soon be available at a more affordable price So be on the lookout for those now as far as cut handling paper stock all at yada yada There's no bells and whistles here.  It's not crushed stock It's not traditional cut anything like that because all of those extras They end up making the decks cost more money and what these two different publishers wanted to do was create a deck of cards that you'd want to use over and over and over again with no fear of Ruining it that you could buy another one to replace it, you know I got two of the marksman decks even though they're 35 bucks I got two just because it was awesome to have that Much power at your fingertips and knowing that I could have one in play and then how would I pocket? You know as a backup So these are made to be your workhorse decks like I said use them sign them tear them There really aren't any better mark decks out there. I'm sorry You can argue in the comment section below, but you're just not gonna convince me easily the two best mark decks on the planet Go out look for them add them to your magic routines today and just you're gonna see just a wow a wow factor Added you're gonna start doing miracles Be on the lookout for both of these highly recommended. Thanks. Bye


Hi everyone, Joe for Jaspy's casebreaks.com coming at you with some hip parade autographed hockey pucks two-box random team break number four at the end We'll re-randomize everybody's names Top ten names will get spots in that that hockey mixer featuring a box of the cup All right, so also if there's no logo on the puck or on the box, it'll go to the team that the players currently active Go to the team they're currently on if they're active or the longest team they played for if they're retired I think that makes sense All right, so big thanks to this group right here for making it happen here are the teams are no Kraken If there's a Kraken puck that's pulled Then we'll randomize it to one person in the break All right, so let's roll it. Let's randomize names and teams two and a five seven times one two three four five six and seven and we'll use a different dice roll for the giveaway part Towards the end of this video two and a five seven times for the teams two three Four all right There's the first half ish of the list right here and the next right there can't really get exactly half There's only 31 teams No trade window as well. Let's just sort by team alphabetically print and rip has a team on there but I Don't think that team exists anymore. Oh No, they turned into this team Okay, so it'll go. Okay. That makes it easy. All right. Here's the final printout right here so it is This player right here, that's Peter Statsney a quibbet Nordic Hall of Famer in 1998 So yeah, that goes to the they've turned into the abs So that'll go to Colorado. That's gonna go to Steve Birch All right, nice one Steve and the next one Let's show Christian squad the abs. All right Hopefully this next player will be a little straightforward more straightforward it is and this puck is gonna be Mark Edward Lasik San Jose sharks Got authenticity on the backs of these as well So there you go, San Jose that'll be for Sean Matic All right, there you go Sean M. Now, let's flip back to the list over here. It's gathered the names Final dice roll Roll it and randomize it three and a five eight times So the whole point of this is obviously not so much the the pocky pucks as it is those mixer spots So top ten after three and a five eight times good luck one two three four five six Seven and eighth and final time three and a five eight times So from 11 through 31 sad times, but I appreciate you trying everybody. Thank you No Steve Birch got him got multiple spots. Hopefully he's still in the top ten There he is see Birch wasn't worried about it.  I'll see you in the hopefully we'll get the other filler done and get the break itself done later tonight Jasper's case breaks.com. Bye. Bye


This tutorial will demonstrate how to write a custom script to export pixie data in the OpenTelemetry format. To do this, we are going to first write a pixel script that exports pixie data in the OpenTelemetry format, then we'll test that pixel script in Pixie's live UI, and finally we'll configure a pixie plugin to run the script periodically at a fixed interval. Everything I'm about to show you is available in a tutorial that I'll link below. You can also find this tutorial on our doc site. For this tutorial, you'll need a cluster with Pixie installed. You can find directions for this in the tutorial. I have a Minicube cluster set up, and I've deployed Pixie to it, and Pixie is in this PL and PX operator namespace. I've also deployed a demo application, the Sockshop demo application, and that's so that we'll have some traffic in the cluster that we can export. I've also deployed an OpenTelemetry collector to this cluster, and that's what we're going to send the pixie data to, and you can also find directions for that in the tutorial. Let's go look at Pixie's live UI. One of Pixie's unique features is that it uses EBPF to drive its data collection. This approach enables Pixie to efficiently collect data in a way that requires no user instrumentation. Immediately after installing Pixie, you'll start to see data that Pixie automatically collects. Here you can see a service map of the HTTP traffic in our cluster, and we can see that the Sockshop front-end service is talking to the catalog orders, user service, and we can also go look at the actual HTTP requests. So if I go up to the script drop-down menu and then do HTTP data, this view shows us all of the HTTP traffic flowing through the cluster that Pixie has traced. Click on any of the rows to see the HTTP request and response. So here we can see that the orders service is talking to the shipping service, and we can see the request body and the response body. So now that we can see this HTTP traffic in Pixie, let's try exporting some HTTP metrics in the OpenTelemetry format. Pixie uses scripts to query its telemetry data. These scripts are written in Pixie's query language. We're going to use the LiveUI Scratchpad to develop a Pixel script to export our Pixie data. So go up to the script drop-down menu, select the Scratchpad. We're going to replace the contents of this Pixel script tab with the script in the tutorial. We will run the script using the Run button here, and you can close the script editor using this button, and we'll go into what this script does in a minute, but let's first validate that this data has been received by our OpenTelemetry collector by checking the OpenTelemetry collector pod logs. My OpenTelemetry collector is just an example collector that outputs the data it receives to the logs. So that's how we'll validate if it's working. Great, and we can see that we have received some metrics here when we ran our data export script. Okay, so let's examine how this script actually works. So I'm going to open up the script editor again with this button, and we're going to take a look at it. So on line one, we're simply importing Pixie's module for querying data, and then on line three, we're populating a data frame with the last 10 seconds of Pixie's HTTP events table, and this table stores all of the HTTP requests and response pairs that Pixie has traced in your cluster. So once we have that data frame, we're going to create columns for pod and service, and so that's just getting the metadata for each HTTP event in that HTTP events table. Then on line nine, we're grouping all of these HTTP events by unique pod and HTTP request path, and then for each pod and request path, we're counting the number of requests to determine throughput, and then hotel metrics also require a timestamp per record. So we're just going to grab the latest value in the window as our representative timestamp. On line 15, we're calculating requests per second by using our throughput value and our 10 second time window that we've grabbed the records for. Down here on line 41, we are calling PX display, and that's simply telling the live UI to display this data frame as a table. I'll comment this up for now. So if we rerun the script, here you can see pod, service, request path, throughput, timestamp, and request per second. So this script so far is just using our normal pixel functions that you've seen before, but lines 17 through 39 will introduce our new methods for exporting data. So to export data, we're going to call PX export with the data frame that we've just created as the first argument and the export target as the second argument. This export target describes which columns to use for the corresponding open telemetry fields. Next, we have the endpoint parameter. And this is describing the endpoint and any connection arguments necessary to talk to an open telemetry collector. The endpoint URL must be an open telemetry gRPC endpoint. And if the open telemetry gRPC endpoint is not secured with SSL, you can set insecure equals true. Optionally, you can also specify the headers passed to the endpoint, as some open telemetry collectors provide providers look for authentication tokens or API keys in the connection context. So next we have the resource parameter. And this parameter defines the entity producing the telemetry data. So this parameter is defined using a dictionary mapping attribute keys to the string columns that populate the attribute values. So the pixel configuration expects service name to be set, but all of their attributes are optional. Keep in mind that when you create new attribute keys, open telemetry has a recommended pattern that you should follow to maintain broad compatibility with open telemetry collectors. So next we have the data parameter. And this parameter allows you to specify a list of metrics or spans that are generated from the data frame. In this example script, we specify a single gauge metric for the request per second column. We also specify an attribute for the metric, which is request path. Each metric and trace type supports a custom attribute field, and metric trace attributes work similarly to resource attributes, but they're scoped only to the specific method. Pixi currently supports a limited set of open telemetry signal types, metric gauge, metric summary, and trace span. We also support a subset of the available fields for each instrument. You can see the full set of features in our API documentation, and if you'd like us to support other fields, please open a GitHub issue. So now that we have a pixel script that exports open telemetry data, let's set up the plugin system to run the script at a regularly scheduled interval. So first we need to make sure that a plugin is enabled. So we'll go to our admin page, and then the plugins tab. And we're going to use the open telemetry plugin, but the script we wrote will work with any of Pixi's long-term data retention plugins. So I'm going to click the toggle to enable the open telemetry plugin. I need to put in my custom export path, which if you're using the demo collector from the tutorial, this path will be in there. And then my demo open telemetry collector does not support TLS, so I'm going to turn that off and save it. So now we've enabled a plugin, and we need to configure which data to export. So to do this, you can follow this link here, or you can go to this data retention icon in the left sidebar. So the open telemetry plugin comes with several preconfigured open telemetry export scripts. I'm going to disable these scripts for now so that we can ensure that the data that the collector is receiving is actually from our custom script. So let's add our custom script. So if you scroll down, or in the custom script section, you can click create a script. And we're exporting HTTP throughput, so I'll put that in the script name. And then I'm going to replace the contents of this pixel script field with the script that we developed. So we need to make a few modifications to this script. First of all, instead of hard coding start time, we're going to replace this with px.plugin start time. And this value can be configured using this summary window field here. We're also going to remove the endpoint parameter since we configured this endpoint when we enabled the open telemetry plugin. And the final thing we're going to do is remove this px display call since that was just used to display the data in the live UI when we were developing our script. If you scroll down, we're going to set the plugin as the open telemetry plugin. Again, this data export script will work with any of our long term data export plugins, but we're going to demo the open telemetry one. Finally, click create. And you can see that our HTTP throughput script is here and enabled and we have a 10 second. It's going to, this plugin will run the script every 10 seconds. So at this point we should be exporting our HTTP throughput metrics to open telemetry and we can validate that by going and looking at our open telemetry collector logs again, since our collector is just simply outputting the data it receives to its logs. So if we run this again, from these logs we can confirm that the open telemetry collector is receiving metrics every 10 seconds. So just to recap, what we've learned is that we can write a pixel script to export pixies auto telemetry data in the open telemetry format. We can configure one of pixies plugins to regularly run this open telemetry export script. And we use the open telemetry plugin, but you can use the script with any of the pixie data retention plugins. If you run into any issues writing pixel scripts, please reach out on our community Slack channel and we'd be happy to help. And if you're interested in contributing to open source, we're seeking contributions for preset open telemetry scripts.


Let's look at the most or one of the most intelligent machine the human us and If you look at one of the important factor of development of human is communication Really early on we communicate or happiness or surprise Or even our sadness We do it through our gesture and this is a core aspect or really important aspect of a Child and her mother Communication becomes important from the beginning and over all of her life We develop this communication skills to the point of today being able to have this wonderful event Like the world economic forum where we communicate ideas Emotions and this is done through three main Modalities the first one and this is the rule of three V the first one is the verbal when we communicate are deciding on specific words and They're really important. They're meaning is important But every word can have a really subtle change to it even a word like okay if I say Okay Okay Okay, there I change and the subtlety of human communication is so powerful and Makes our communication so efficient that makes these meetings possible And so when when we want to think about a you intelligent machine We have to go in the verbal in the vocal and you're probably expecting the next V the visual So a lot of what we do is to my gestures to my facial expression Through the proxemics to my posture all of these three V's are essential to human communication So how are we communicating with computers with keyboard and mouse? We are also these days having much and we have newer technology like touchscreen and VR And we're getting closer But it's much further than what is human communication. So when we think about these Intrusion machine human communication being able to understand and communicate with human in a natural way becomes important And this is true for embodied Intelligent machine like a robot a virtual human, but it is also true for non embodied Intelligent machine your cell phone your computers that may not have a phase that may not have a direct embodiment But this is also really important So for all of these case one of the core component is what's called? multimodal AI multimodal AI is this capability of computers intelligent machine to understand the subtlety of human communication And what's exciting now is that we and I would say we the community scientific community in general the community Have found really interesting new technology to address this challenge One of the big one is we were able to go from a really shallow interpretation of human communication To a much deeper understanding going from understanding only the facial landmark Motion of eyebrows or simply the motion of of a mouth to a level where we also understand the Appearance of a face and the subtlety in the appearance to the point where we can in fact study all 48 muscle of the face and from this being able to infer the Perceive expression or emotion and I say perceive in this case because what really someone feel is also still a challenge But we're getting closer to a deeper interpretation a second aspect is that Computer but with all this power we have in these computer We can go from a micro to a multi-level Interpretation of human communication where we understand at the first level Something simple as a gaze That's the first level of looking at the dynamic of human communication But as I said the communication is a lot more than that We should look at the multimodal how a person is behaving and how all these What the 3v the verbal the visual the vocal? But I'm not just talking to myself I'm talking to you and so a lot of it is also when computers now these days are looking at Communication as an interpersonal dynamic to people talking together a patient Patient with their doctors So that's what one of the key aspect and this is going now these days to the next level of group and social Dynamic and looking at different cultural norms So this is a really important aspect of this new technology is that we're looking at at multiple level and the last one The last piece the ingredient was that we are able to have a lot more information Freely available and so we can go from small data to big data Where a lot of example of people communicating and not just Laboratory but in really different scenarios different culture and different individual the last piece is that the Algorithms are getting a lot smarter and we can handle a lot more of this data So multimodal AI is one of the key component I believe of intelligent machine and that's also what allows us to think of what do we want these? Intelligent machine to be or to do right now. There are a lot of command like I Command my Siri or command my cell phone to do something, but I believe that computers are a lot more about Colleagues and co-workers so I believe and that's in fact We already see some example of that that these technology will help for example a doctor To be able to help during diagnosis or assessment of mental health disorder and be able to look at the subtlety of Communication and be able to give this feedback to the doctor. There's a big change in how Education is happening in fact people are learning remotely But we know that remote interaction is really challenging when you compare to face to face interaction and Technology can help us for that and this is true for business interaction Also, we are lucky today to be all together But what if we have to interact remotely? So let me give you an example of a first step toward these intelligent machine and let me introduce Ellie In fact, Ellie is part of the SimSense a project and Ellie is there to help doctors during their assessments of Mental health. She is not a doctor. She is not a virtual Doctor, she is an assistant. She's an interviewer. She's gathering information and when we're looking at depression or distress in general This is a challenging thing for any clinician to successfully diagnose And so what if we could do what exists in other part of medicine? Example a doctor has the intuition about a disease They will do a blood sample a blood test and then look at the details for mental health We have now the possibility of doing an interaction sample How did that person change over time? So maybe we can reduce the treatment and change the medication So let me introduce Ellie with an interaction and showing how she can interact in real time and perceive the verbal The visual and the vocal. I'm Ellie. Thanks for coming in today I was created to talk to people in a safe and secure environment I'm not a therapist, but I'm here to learn about people and would love to learn about you I'll ask a few questions to get us started And please feel free to tell me anything your answers are totally confidential. Are you okay with this? Yes So How are you doing today? I'm doing well That's good Where are you from originally? I'm from Los Angeles Oh, I'm from Ellie myself When was the last time you felt really happy? um But I try to stay happy. Um, I'd rather be happy Uh, my kids keep me going What advice would you have given yourself 10 or 20 years ago? um to uh to not believe uh To to not be so gullible to not be so gullible So this is a short example. In fact, we had more than 150 people interacting with some sensei And this is just over a period of a few weeks And what was interesting is the interaction was supposed to be only 15 minutes People enjoyed talking with her. She talked for 30 or 40 minutes In fact, if you look at how much sadness or real behavior they show There's more sadness when they're interacting with a fully entomatic Intention machine than when they think that there's a human behind pressing the button And what is really interesting is because of all this data We can start looking at differences for example differences between man and woman for depression or for anxiety So these tools are one example and as you can imagine, there's a lot more of these example going on for both uh healthcare For education and business where intelligent machine can help as a co-worker And as a colleague. Thank you very much for your attention


Hello, everyone. This is Alice Gao. In the previous video, I talked about a little bit of history on deep learning. Then I talked about the motivation for using a neural network rather than using some other machine learning models. Then I finally talked about the structure of a neural. In this video, we are going to look at a computational and mathematical model of a neural. Artificial neural network actually uses a very simple mathematical and computational model of a neural. This model was first proposed by McCulloch and Pitts in 1943. This tells you that this is not a new idea. It's been around for a few decades already. This is a very simplified model. If you learn a little bit more of neuroscience, or for example, if you take a more specialized class on neural networks, then you will know that an actual neuron works much more complex in a much more complex way than this. So there's many simplifications. But essentially, this model says that a neuron is a linear classifier. To think of a very simple example, if we have some data in a two-dimensional space, we have some maybe positive examples and negative examples, things like this. So if you try to use a neuron to classify these data, then what are you trying to do? You are trying to actually fit a line which you can use to classify these data into two classes, for example. But of course, our data, whenever we use neural networks, the data is probably not two-dimensional. We probably have much higher dimensional and much more complex data. So being a linear classifier for the neuron, I have to describe it in one sentence. It means that the neuron is going to decide whether to fire or not. And this depends on a linear combination of its inputs. So we calculate a linear combination of its inputs. So you can see in this picture right here, this summation here is saying, we are calculating a linear combination of its inputs. And if this sum exceeds some threshold, then the neuron is going to decide to fire. And also that depends on, sometimes you can adjust how much it fires, the strength of the output signal as well. Let's look at this model in more detail. So here is again our model of the neuron. And we have a few input signals coming from other neurons. So these are denoting the input signals from other neurons. In general, we'll denote it by a sub i. So coming from neuron i. And our current neuron is called the neuron j, a sub j. So we have these input signals and between the connection of this neuron and another neuron, which is sending the input signal, the connection has a weight. So for example, going from ai to aj, the connection has the weight wij. And then the current neuron is going to compute a weighted sum of its input signals. So this weighted sum is taking each input multiplied by the weight and then take the summation of all of it. So after calculating this weighted sum, where the neuron j is going to apply an activation function called g to this weighted sum to figure out the output signal. So depending on what the activation function is, the output signal may be different. So applying the activation function. Something you might have noticed here, something maybe interesting, maybe odd, is that we have this input a sub zero, which is always set to one. This is sometimes called a dummy input or a bias input. And then we also have weight between this input and our current neuron, between our connections, which is called w sub zero j. And this is called the bias weight. So why do we need this extra bias or dummy input? Some of you may know this already. So thinking back to the previous slide, the neuron is a linear classifier. We are trying to use it to represent a linear function. In a two dimensional space, it's a line. In a higher dimensional space, it's a hyperplane. In order to be able to represent all possible linear functions, we need to have the possibility of having a constant term. With a linear function, you could have, for each input, you can multiply by some weight. So that's the coefficient for that input. But you might possibly have a constant term. So how do we have this constant term? This bias input allows us to be able to have a constant term in the linear function that we're trying to represent. So in the simple model of a neuron, the activation function is a pretty important component. Let's look at this component more and think about what are some desirable properties we want this activation function to have, and then given those, what are some suitable activation functions that we can use? So how should we choose our activation function for our neural network? Let's look at three desirable properties that we probably want our activation function to have. The first property is that the activation function should be nonlinear. The reason behind this, well, we are trying to use our artificial neural network to model complex relationships and complex relationships are often nonlinear. Linear function is a really simple function and most complex things in the world are nonlinear. So how do we get the neural network to ultimately represent nonlinear function? Let's imagine that we choose a linear activation function. Then what's the consequence of that? Well, we have a bunch of neurons say in a particular layer and each neuron computes a linear combination of its inputs and then we'll feed that linear combination the weighted sum into a linear activation function. And then we'll take those output signals and then maybe feed them into more neurons. This is how a neural network is going to look like.  And no matter how complex our neural network is, no matter how we stack multiple linear functions together, we're going to end up with a linear function. That's how linear functions work. So if we don't have a nonlinear component in a neural network, we are never going to end up with a nonlinear function overall. So that's why we want to choose nonlinear activation functions. So once we do that, a neural network with multiple layers of neurons, we are essentially interleaving linear and nonlinear functions. We have linear functions as the part where we're computing the weighted sums, then we'll feed these weighted sums into a nonlinear activation function and then we'll maybe feed those into other neurons, which is again one layer of linear function and another layer of nonlinear functions. The second desirable property is kind of obvious, but we should still state it. We should choose the activation function in a way such that it mimics the behavior of real neurons. So how should the activation function mimic the behavior of actual neurons? Well, neurons are going to take the input signals, do some computation and feed it into the activation function. And typically, in a very simplified way, we can understand the behavior of neurons as if the weighted sum of the input signals is large enough, then the neuron is going to fire or it typically sends a high output signal. Otherwise, if the weighted sum of the input signal is not large enough, then the neuron does not fire or it sends a low output signal. So typically, we want the activation function to almost look like a step function, where we have some sort of threshold and then given this threshold, the neuron either fires or not. As you will see later, a lot of activation functions are similar to a step function, but they're not exactly the same as a step function. So it doesn't mean that if we want the activation function to mimic the real behavior of a neuron, it doesn't mean we always have to choose something that looks exactly like a step function. We want to mimic the behavior, but it could be that there's no hard threshold. Maybe for every possible weighted sum of the input signals, we will fire an output signal of some amount. It doesn't have to be 0 or 1. The third desirable property says that the activation function should be differentiable almost everywhere. The reason for this comes from the perspective of learning. We are going to train or learn neural network using optimization algorithms such as gradient descent, and many such optimization algorithms require the function to be differentiable, because we need to calculate the gradient, which is basically the derivative, and use the derivative to decide on which direction we want to change the parameter values to do the optimization. There may be other desirable properties that we want the activation functions to have also. Now, given these desirable properties, let's look at a few examples of activation functions. The first activation function that we're going to discuss is not surprisingly the step function. I already sort of implicitly mentioned this when I talked about the behavior should mimic the real behavior of a neuron. I've plotted the step function right here so you can see what are some properties of the step function. First of all, it's very simple to use, very simple to understand, and it does in a very simplified way mimics the real behavior of a neuron. But one critical problem with the step function is that it's not differentiable. It has this continuous point at x equals 0. So we cannot use it for applying gradient descent. So basically, if we use this activation function, we won't be able to learn weights for a neural network using gradient descent. Honestly, the step function is not used in practice. But in lectures, I'm going to use it quite often because it's simple to use, it's easy to calculate, and it's useful to explain some concepts. Next, let's look at the sigmoid function. The sigmoid function is a really popular choice for the activation function for quite a while. But at some point, people discover some serious problem with the sigmoid function so they started using other activation functions. We'll discuss the problem in a moment. So in this plot, I've drawn two versions of the sigmoid function curve, and the flatter curve, the one in red, uses a relatively small value of k, and the black curve, the steeper curve, uses a relatively larger value of k. So what are some properties of the sigmoid function? One property as you can probably see intuitively is that the sigmoid function sort of approximates the step function. That's one of the original reasons why people wanted to use it as the activation function. Because if we cannot use the step function directly, then we should use something to approximate it. And for this general version of the sigmoid function, you can change the value of k, and as k increases, the sigmoid function becomes steeper and becomes closer to the step function. So it's a better and better approximation of the step function as k increases. Another property of the sigmoid function is that it gives us clear and bounded predictions. So as the value of x becomes very large or very small, the value of g of x is very close to zero or one. And often when we have a classification problem, we want the prediction to be bounded within this range. At most one, at least zero. This will make our computation much easier. The sigmoid function is also differentiable. So this allows us to use gradient descent to learn the weights of the neural network if we use this as the activation function. So far, the sigmoid function probably looks like a pretty good choice. Next, let's talk about some problems with this function. So one problem with the sigmoid function is that it causes the problem called vanishing gradient. So if you look at this function, if the value of x is very large or very small, the value of g of x changes very little. The curve is quite flat. So in those regions, the value of g of x responds very little to the changes in x. What does that mean? That means the gradient, which is basically the derivative of the function is going to be very small. Because of this, the network in those cases, when the value of x is very large or very small, the network either does not learn further anymore or it learns very, very slowly. Because the gradient is very small, the gradient tells us how much we can update the weights in each step. And if those updates are very small, then the network changes very little. So this is one of the classic problems with sigmoid function called the vanishing gradient problem. And this motivated people to look for other activation functions that don't have this problem. Finally, compared to the step function, sigmoid function is pretty computationally expensive to calculate. As I will discuss later, we will learn the back propagation algorithm and also from many stories and news articles, you must know that it takes a long time usually to train your network. So often we are going to prefer activation function that's easier to calculate than one that's expensive to calculate. Next, let's talk about two versions of the rectified linear unit. So first of all, the classic version, I've plotted the classic rectified linear unit here for you. A couple of properties of this function. First of all, it's computationally efficient. Just by looking at the expression, you can see that it's pretty easy to calculate the result of this function. So being computationally efficient means that when we use it to learn a neural network, the network converges pretty quickly. So that's a really nice property of the function. Also, this function, of course, is nonlinear and it is differentiable. So these are the good properties of a relu. But recall that one critical problem with the sigmoid function was the vanishing gradient problem. So does relu fix this problem? Well, it seems to fix it on the positive side. When x has a positive value, this function will always have a constant derivative. So it sort of fixes that on the positive side. But on the negative side, we still have a similar problem. This problem is also called the dying relu problem. So when the input, when the value of x either approaches zero or are negative, you can see that the gradient, the derivative becomes zero and the network cannot learn. So we fixed the problem partially but not completely. Finally, we have another version of the rectified linear unit called the leaky relu. So the main difference between this and the classic version is that on the negative side, when x is negative, we have a line which has a small positive slope. So it's not a complete horizontal line. So leaky relu has the exact same nice properties as the classic rectified linear unit. But it fixes the dying relu problem in the negative area. So even if now x is negative, the derivative is still not zero. So it allows us to keep learning for negative input values. That's everything I want to say in this video. Let me summarize. After watching this video, you should be able to do the following. Describe the simple mathematical model of a neuron and explain why a neuron is a linear classifier. Describe some desirable properties of a neuron. Give four examples of activation functions and then compare and contrast the properties of these activation functions. Thank you for watching. I will see you in the next video. Bye for now.


All right you guys in this video I'm gonna show you how I did this piece It's the junior of this mammoth of a piece this one's 48 by 48 this one I think is 2024 But I sped up through it because it took me a number of days So I'm just gonna tell you real quick what you're gonna see in the video First I did the gray wash background Like by Spursing water and letting it drip and things like that then I went in and picked the areas that I wanted to have this red Added and I just kept layering deeper and deeper every time let that set next day. I added this gold leaf with a special adhesive I'll link all the Materials I used in the comment box below and then I went over it with gold leaf I can't decide yet if I want to resin her to finish. I think I will but Stay tuned till the end of the video to see how I finished off this piece Before I post her for sale. All right you guys Jeff took all of our camera mounts out to the mural that he's working on today. So I'm doing the best I can with I Can't even explain the rig to you guys So I'm going to finally finish Bertha. I'm gonna try a couple new things. Maybe I don't know Depends on if I'm brave enough We'll see so I'm using in biotech's light on this piece for no other reason than I like how it works After this cup is big enough I'm not sure how much resin this will take. I'm not doing that much like artwork with it. I'm just Giving it a good coat So We'll see if I have enough resin Okay, I've been toying with the idea of adding some glitter, but I don't know if this is like too Not really gold. I think it'll probably be fine So here we go. Now since I knew I was gonna be adding Resin to it. I prepped the canvas just like I would if I was just prepping for a regular pour So that it doesn't dip so much in the middle I usually try to make sure that The interior has a good healthy even coat before I push the resin to the sides That way as a little falls off as possible Sometimes you'll end up with a piece of gold that just wants to stick up If you like maneuver it enough it'll either come up or go ahead and lay down That way you can avoid doing a second coat Because that takes time It's not a fun time Then you have to sand it and heat it and alcohol it And if it can be done in one coat I'm all for it Alcohol I know what is this? Resin's expensive. I need to find a resin sponsor. That's what I need to do One day baby steps All right, now that everything's covered. I'm at the point where I have to decide if I want to Add sparkle or not and typically I'm sparkle kind of person. So we're gonna get that a shot Have you all ever tried to put wet gloves back on? Don't recommend. It's like putting on a wet swimsuit Only with resin not fun times I didn't I had this much fluffed over so we're gonna add It into the mix and adding clear resin over where I have glitter and all of the pigment powder That's just gonna push around What I already have so it's gonna make little designs Which I will show you guys when we're done with the whole piece. Yeah, be careful when you use mica powders I don't know if this is a mica powder or just a Pigment powder It says non-toxic. I don't know What are labels but be careful because It's not good in your lungs if it is mica Y'all can't really see it right now, but you will in a minute Filting it just a little bit while I add this heat so that it can generate more movement because gravity I Had y'all rigged up there with this thing on this bar I think that's where we're at right now So this is a small version of this. I didn't put the gray in the background like I did in this one and I haven't covered it in resin yet when I do I haven't decided if I'm gonna do the glitter thing Or leave it just clear but Like on the surface you can't really see much about that pigment powder that we Like dust it over it, but on the sides you can't let me get a light I'll show you more about how she turned out after she sets