So hello everybody, I'm Eva and even though this is a Python conference I will not be talking too much about Python itself but I would like to tell more like a story behind the research I'm working on and it deals with noted proteins So proteins those tiny things that are in all our bodies the key players that makes our bodies work If I give you an example of hemoglobin that's something you all probably know That's a protein that goes from our lungs to all other parts of our body and carries the oxygen. So it helps us breathe You know that proteins are kind of poison to us and it's honestly pretty fascinating to study them So let's have a look at how protein looks like When the protein is being created it looks like a long string of tiny beads Where the beads the building blocks of the proteins. It's called amino acids And we have 20 different types of them. You can imagine it's like 20 different colors of the beads and from these beads You're making the whole protein As long as the proteins finished it does not stay in this like linear form but it immediately falls into some 3D structure and in this 3D structure it stays for its whole life and The 3D structure is like crucial for the protein because it determines the function of the protein so if you look at the Structures here for example at the orange one it looks maybe a bit like a U shape like a pocket So its function might be that some our molecule comes and sticks to the pocket or the blue thing there It's like a tunnel So it's said somewhere in a cell membrane and it guards which things can slip through in and out of the cell Let's have a look at the folding itself When you have this protein sequence somewhere naturally maybe in a cell It can fold into the 3D structure like immediately in milliseconds but when you're a scientist and you have this amino acid sequence, which is quite easy to get with experiments How long do you think it would take you to get the 3D structure and we can do like Warmup activity where you can do a measurement with your hand. It will be like Hours maybe days months you can show it If you have any guess Yeah, great. Most of you is right. It's maybe somewhere there because if you Know what you're doing if you have some protein you've maybe worked with already it may take you months but usually it's more like years and There's a joke It's pretty bad joke because it says that every protein in a database took a PhD life So it's not that great, right? This difficulty in obtaining the three structures of proteins is very nicely demonstrated in the size of protein databases We have so if you have a look at the unit of database, which is database of all protein Sequences it is something like 300 millions of sequences if you want to work with that You have to class through database so you end up with something like 50 millions of sequences But if we have we want to have a look at the three structures That's like the important thing because you want to know the function of the protein. You're at something like 190 hundreds Thousands records so it's not that much right and this disproportion between getting the protein structure and protein sequence is really nice demonstrated in the size of databases and This poll shows that it will definitely do get better in the future is so Maybe it would be really good for us if we can have some predictions tools that will help us to get the three structure of the protein We can plug in the protein sequence as it'll predict for us the three structure Luckily you have something like that and there's a really nice competition about this it's called casp and it runs every two years and The guys from the competition publish some protein sequences with unknown structure and Basically anybody can join this competition with a models and they try to predict the structure of these protein sequences And then the organizers come they get the real structure and they see who's doing the prediction the best In the past years the lady both looks at like that on the x axis you have all the models that join this competition And on the y axis you have like how well they do in the prediction and And then your 2020 came and there was one tool like completely rolled over all the other tools it was all cut this was called alpha fold and The best thing about this is that this tool was so good that Its precision was almost at the level of what we are able to achieve with our experiments With those costly experiments, which we're running for years. So that's a great thing to have And let's now have a look inside at how alpha-fold looks Not surprisingly, it's a machine learning thing that is trained on all available three protein structures and There's a pretty nice schema, which we can split into like three parts The first part deals with encoding the structures the protein sequences So actually until one thing which is pretty important and interesting both proteins And that is if you have two protein sequences that are kind of similar It's very problem that they are three structure will look very similar So on this example we have hemoglobin protein sequence from human mouse and fish and If you have a look at the human sequence and the fish sequence Maybe only like half of the sequence is the same, but the three structure looks almost the same And it's because the function is the same So if you go back to the schema, that's exactly what's happening in the first part You have your protein sequence in the input and what you're doing is that you're Looking through a database of protein sequences and trying to find something that would be similar to your input sequence And what you hope for is that you can maybe extract from there are some patterns and Get something that might be useful for modeling the three structure Then the input is like a matrix of all pairs of amino acids in the sequence and they potential contacts and Then a logical thing you're looking for some already existing three structure that would help you to model your input protein Then the second part is like in the processing of this input information Maybe it's put it there the word ever former it sounds a bit like a transformer and that's almost what's inside there and The third part is like the modeling itself So what your output is like XY coordinates of each amino acid in the input protein Now if you would like to predict your bright new proteins three structure it's honestly, not so easy because this whole thing is really big it's computationally demanding and One structure may take several hours to compute So people started thinking can we do it some of faster? Maybe like it's great We have this thing that can create a three structure in one hour, but you know We are doing these experiments for years but still it might be something that will do that better and The idea is that we spot what is the slowest part and that was like this database search for some similar proteins What we can do here is that we replace this slow part with some language model Maybe that would capture the idea of the whole protein universe And it would maybe understand the proteins the same way as the database can and it would much faster, right? So Here comes the SM fault, which did exactly this thing it took Basically the same scheme as alpha-fold head, but they replace the slow part of their own language model trained on proteins and Now we can do the prediction in second. So that's great This is a bit longer interaction about proteins how they work these three structures and Now let's shift a bit and let's talk about large language models So what is that? What is life language model? In a simple words, it's type of an AI that is somehow able to understand and generate the text Usually these models are trained on a huge data sets for example all articles from Wikipedia or something like that and They try it in a very specific manner On the input you're giving them a Sentence for example here we have there was a king who had 12 beautiful daughters and in the sentence you Hide one word. So this daughter's word will masked and what you want from your model is to predict you the Distribution of this hidden word. So what this model does is that it predicts a couple of words with some probabilities Where the word daughter scores with the highest probability so that's exactly what you want And what you hope for is that this model can capture somehow the idea of the text of the language However train these types of models is extremely demanding because you have to have a huge data set model itself Is really big so usually only big companies can afford this But when you have this model trained, it's really good and you can use it for some subsequent tasks So for example like classical thing when you have movie reviews and you're classifying them into positive and negative What you can do is that you can take some of the already trained models You basically cut the last layer which was predicting the next word and to replace it with a layer that will be predicting positive and negative and to only fine-tune this small on your specific task and What you hope for is that the model already understands the text So it's easy to just slightly adjust it and it will up to whatever you want Nowadays this fine-tuning has become really easy because we have for example hugging face So for those of you who don't know that it's like a little advertisement. It's a really cool thing It's a let's say platform for the science and machine learning where you can easily share your models and data sets and Fine-tuning has become this simple. It's like whole code for fine-tuning the model In the first lines you just download the model that is already available to hugging face You just load your data set you train in and that's it Now you might wonder how is this nature language related to proteins. It's a bit different, right? Not really because you can imagine that the protein is somehow language it's pretty easy because each amino acid has its letter code so you can imagine that each amino acid each building block of the Protein is a word and you can then do with the protein the same thing as in normal language You can mask some amino acids and you can train a model that we predict in which amino acid is missing People have already tried it. So we have for example Prodbert model that is trained on like whole database of protein sequences If you spotted the word bird inside this name, yes It relates to the bird architecture in like normal language. It's the same thing, but just trained on proteins and Another example is ESM model, which is something I already mentioned what we're predicting the three structure. It's like the faster tool So When we have this most available for hugging face It has become really easy basically for anybody to play with proteins. So even you can try that pretty easily and Finally we're getting to something. I'm playing with and that's proteins with knots And it sounds a bit weird, but it's pretty fascinating thing and It's built on a whole field mathematical field. That's from like 18th century. It's a not theory and It's just Categorizing different types of knots and trying to distinguish them from each other So on this picture of like different examples of the knots from the simplest one Which is like a knot to three more not which is something you prove a tie on a shoelaceous or somewhere and many many others And maybe here to just explain a terminology the first number here refers to the number of crossings in the knot and The second number is there just to distinguish different types of knot with the same number of crossings How does this work with proteins is basically the same thing But proteins are but not complicated So you maybe don't see at the first look if the protein is not it or not But most of the proteins are unnoted meaning if you pull the protein from both ends it will untie But there exists some noted proteins most of them have this most simple 3 1 not but there exists some other guys like 6 1 not or maybe Even double 3 1 not in bacterias Even though not it proteins were studied for quite some time We're still not 100% sure was the purpose of not so there are some ideas maybe the knot tries to prevent the protein from degradation or For example, we know that the knot creates in some proteins the active site of the protein This is like responsible for the function of our protein. So it's like the very important part of the protein But what we'd really love to know, but we still don't is if there exists any amino acid pattern It would be like responsible for the knotting and that's the place when we came up with our research and Our idea is that we take protein sequences and we will build a model on them Which will try to categorize them if the protein is unnoted or not it and then would try to interpret Somehow normal and see if we can extract from it some patterns of the knotting We want to train Machinery thing you need some data for it, right? So one would say you're very lucky you have this alpha fold tool that will predict you many many protein structures so you can just look through this Database and see if we have some noted structures take them fix and unnoted build a dataset from that Easy task. Okay, it's not that easy because if you do it with this simple approach You will end up with the cities completely biased and the model of was learning like absolutely nothing about the knotting So you have to be a bit smarter It's in every machine learning project the dataset building to us like 80% of the time and When you already think you're finished is like somebody coming Well, we may be forgot about these things. So we have to rebuild database and You have a very beginning. So after like half a year. We finally got something and We ended up with building it almost manually the database because We wanted to be really sure that the proteins we have there are really not it so we manually Manually treated these proteins and took only protein family that was sure with for which existed some already Experiment determined the restructure. It was not it With this approach, we got quite a night dataset, which was had some like 200,000 proteins It was nicely balanced. It was really good for us and I already mentioned that we are now available these protein models so we tried to use one of them prod bird and find tune it on this dataset and Before we actually started the fine-tuning we're curious. How much does the model already know about nothing? It's already shown that these models have some understanding of the protein pictures for for example, if you Get protein embeddings. It's like the inner representation of the model about the protein The model already knows for example From which kingdom the protein comes or for example, which structure it possesses so we tried it for our nothing problem and We saw that the model already has some understanding on the nothing even before it was trained So it was a good thing for us We then took our data set we tried to train the model and we got pretty nice results With the overall curious around 98% It was actually a bit suspicious. We were worried for example that the model might learn only to recognize the biggest protein family so we already also checked this thing, but it looked completely fine So we then approach to the interpretation part when we try to see What the model thinks that might be responsible for nothing but which patterns in the sequence We tried a couple of things, but the best working was our custom technique when we're like patching parts of the sequences and for Each patch we saw how the model prediction would drop So basically if you cover part of the protein sequence how much does the nothing score drop and with this approach you can get the place where the drop is biggest and With this patch you can basically break the knot So you can then aggregate all those patches and see if you can extract some biological meaning from them We tried it for one particle protein family Well, we observed it the model primarily focuses and the end of the not core and We're also able to get some pattern in there. It's just pretty interesting and We observed that this Pattern is closely related with the function of the protein But we would like to continue with this. We tried the interpretation only with one family so it would be good to extend it to some other families and What's a bit like a crazy idea? But what might work someday is that we would like to create our own protein with not like completely artificial design thing you must ask is this somehow useful and Honestly, this is a bit tricky question for us, but I'll try to give you some examples For example, there's a research that says that improper formation of a knot might be somehow related to your visiting and Another thing we know that some not protein families for example spout family It's very important in our body and that the knot is really tightly related to its function And one of the function can be related to bacteria resistance So maybe the understanding of the nothing would help us to develop some new targets for antibacterial drugs and To conclude this talk and just remember proteins are cool especially not the proteins are cool and Research on proteins is something really neat as laughing I would like to thank to my team for this project and Also, thank you for listening So if I understand you at this moment just distinguish if it's knotted or unnoted and nothing More like you don't try to distinguish the knots like what kind of types of nuts not yet But you might want to try that in the future and basically earlier samples if I understand are completely Like most of the samples you were trying are at this moment Artificially made like most of the knotted proteins are predicted yeah, and Are you able to to see like maybe? Sorry later, it's fine How much is the research considering modeling of proteins limited with post-translational Modifications since I guess it's hard to predict them and this influence is destruction the catalytic catalytic activity as well Do you know how far you can get without considering this or are there already options to consider this? Like no idea, but post-translational modification at this stage Okay, are there plans for the future? From my side probably not because I'm not like a lot person But maybe somebody else has this idea Was just a matter of interest. That's what's really interesting presentation Thanks for your talk. You were talking about a solution based on on Bert Part of library Have you tried any any other deep learning based solution? Yeah, we tried other transform based things like this ESM It worked very similarly So we just stick to this one and we also tried to use Simple convolutional network it honestly worked pretty well a bit worse But still real well, so it looks like this nothing problem is somehow quite simple to distinguish and What you also tried to do is to take just the embeddings from the bird and then try Trying some small thing on top of that. It also worked pretty well, but we just stick to this thing Really good talk I was interested in the LMM stuff So you said you would train it on a protein dataset afterwards. Have you tried just dropping in Say a GPT-3 and seeing if it can Dissern the different proteins just as is We all think about it. I think guys would find something like that, but yeah connect to those guys over there Okay Hi, very nice talk and very interesting research Question is regarding the not proteins and the problem of finding which protein is noted and not noted How did you how tech which technique did you use to to distinguish between these two two sets? There's a patent package. It's called topoly It's done by guys from Poland They're doing these regions for quite some time So they already know how these things work and what you do is that you take your 3d structure and to run this tool on that and do the output to you which type of note you have there Okay, but you based on the on the protein sequence and then you move to the 3d presentation by some kind of Dynamics modeling go. How did you get the 3d presentation of the protein by alpha fault? It's predicted. We do not have any questions on the discord If we have any questions in here, we still have time Anymore no, then thank you ever for your great talk and


QuickBooks Online 2022. Populate invoice using a billable item that was created from a purchase order. Get ready because it's go time with QuickBooks Online 2022. Here we are in our Get Great Guitars practice file. We set up with a 30-day free trial holding down control, scrolling up just a bit to get to that 1-2-5% currently in the home page, otherwise known as the Get Things Done page. And the business view as compared to the accounting view. If you wanted to change to the accounting view, it's something you can do. By going to the Cog dropdown up top, switching to the accounting view down below, we will be toggling back and forth between the two views, either by going here or by jumping over to the sample company file currently in the accounting view. Going back on over, we're going to open a few tabs up top to put some reports in. Going to the tab and right-clicking on it, duplicating that tab. Back to the tab to the left, right-clicking again, duplicating again. Back to the tab to the left one more time, right-clicking again, duplicating again. As that's thinking, let's see where the reports are located in the accounting view. And they're located right on the left-hand side of this little thing that says reports. Kind of counterintuitive, but not really. And then over here on the business view, it's a little bit deeper diving, but not too difficult. It's in the business overview section. And then reports, closing up the hand, boogity booger going down to the balance sheet. One of our fav reports, financial statement reports, one of the big two. And we're going to go up top and change that range. 010122 to 123122 and run it. Tab to the right and go down to the business overview again in the reports tab. Closing up the hand, boogity boog. And then going down to the profit and loss, the PNL, the income statement. Changing that range. That range needs to change. We're going from 010122 to 123122 again. Run it one more time. Tab it to the right. And we're going to then go to the business view and reports and close up the hamburger. I'm going to open up the PNL again so we can take a look at the month's activity, comparing and contrasting it to the year to date activity. This being the second month of operations, the second month of data input we are working on. So the beginning date, I'm going to start here at 020122 to 123122 and run it. So we have a bit different of a setup down here, a little less activity on the current month of Feb, although it is filling itself out nicely. And then the profit and loss on the year to date looking something like this. Now let's go on over to the first tab. You'll recall in a prior presentation that we had a purchase order that we linked to a bill and we had a request from a particular customer. So let me recap this epic novel that has been taking place in our great guitars store. Someone came in and they're like, we want these specific guitars and we said that we can order those guitars for you and we made a purchase order then for those guitars and the purchase order was requesting those guitars from our vendor and we populated that customer as we made the purchase order and then we paid for the guitars with a bill and paid for the guitars or we received the guitars and didn't pay for them but entered the bill increasing the accounts payable at that time. Now we have the guitars and we're ready to turn around and make an invoice with them and go into the sales side of things to do so. So let's first kind of track this again.  So on the purchasing side of things we had then the new vendor fender. The new vendor fender you will recall that we made this purchase for. So we made the purchase order for this new vendor because we had someone want it. Let's take a look at that purchase order. So there's the new vendor fender and we entered. We wanted these 20 square guitars because new music stuff ordered them. We put the new music stuff on the purchase order that being the customer even though the vendor fender who's getting the purchase order doesn't care about the customer. That's for internal use so that when we get the guitars we know that we could turn around and make an invoice with it.  So we imagine that we got the guitars from a fender. They had a bill attached to it and we then entered that bill into our system increasing the accounts payable. So let's go into that bill just to see the scenario playing out here. It's all playing out like this. And we're going to say there's the bill and then we made this billable item down below. Something that you have to be careful of when you're talking about inventory items because now we can link this we can turn around and link it to this customer going to the revenue side of things now making an invoice but you got to be careful with this link because sometimes it pulls it over at the cost which is on the bill and the purchase order instead of the sales price. So that's why sometimes you might not want to use this link you might just want to track the customer and then create the invoice from the bill here just using it as a reminder to tell you to turn around and create the invoice but we'll link it across here and we'll make any changes that we might need to you can see that it's linked here to the purchase order. So let's go and close this back out and now let's go up top and hit the hamburger hit the hamburger and then I'm going to say a plus button and we want to say now we're going to turn around to the sales side of things now that we got our squire guitars from the new vendor fender that we're specially ordered for the new customer which is new music stuff so we're going to put in new music stuff and tab and then we get this thing this is paraphrasing QuickBooks is like hey we've got this billable item do you want like us to add that to the invoice and we're saying yeah we do QuickBooks that's really helpful but did you add it at cost or did you add it at the sales price down here and they added it at the cost so that's the problem with the billable item sometimes I'm going to go down there and fix it but before I do let's first tab through this thing and make sure everything is the way it should be is the date I'm going to put it on the 24th the date 224 invoice number so everything is looking good now the way I can see that this is not the correct amount is that I could go down here and say if I've typed in sq squire again I can see then they should be on the books for 244 rate instead of 168 so it pulled over the cost instead of the sales price so what I'd like to do is I'll just change it I'll just say okay I'm going to change this I'm going to keep the link because I want to keep the link I don't want the link to pop up again once I invoice new music stuff again so I'm just going to change this amount to 244 which will change this side the cost side of things should not be impacted so the decrease in the inventory will still work properly and the cost of goods sold will populate properly then I'm just going to close out or trash can this second one which is the fancy delete button the trash can trash it please and then I'm going to change the let's see let's change the sales tax that's what I'm trying to spit out here spit it out and then I'm going to go into the sales tax I want to make it a generic 5% the generic 5% generic 5% why? QuickBooks has to know you just have to know everything right it's my books I'm doing the book these are my books you don't need to ask me questions every time I do something so then we're going to say this is at the 5124 and so there it is so if we were to say what's this going to do well it's an invoice so the accounts receivable is going to go up by the full amount the 5124 then the revenue is going to go up by the 4880 and then the difference is going to go to the sales tax of the 244 that's going to be on a liability account and then we've got inventory it's going to go down by an amount not on here but we saw what the inventory amount was because that was originally pulled in the system knows what it should be due to the item cost of goods so it's going to go up by that amount as well the amount not on the actual invoice the sub ledger will be impacted for the customer of music stuff store as well as for inventory in terms of dollar amount as well as item or number of items save it and close it and let's check it out let's go to the tab to the right to do so checking out the balance sheet to start off with it's going to zoom back in and then we're going to go into running it again and go into the A R A to the R the accounts receivable to see people that owe us money who owes us money music stuff new music stuff whatever that weird name is owes us 5124 that's the full amount including the sales tax going back then to the balance sheet other sides on the income statement going over to the income statement to check it out up top we're in the sale of product going into the sale of product items zooming back out zoom zoom and there it is so there so that's for the amount that we charge not including the sales tax down here on the invoice going back up and going back to our report zooming back in zoom and then I'm going to go back to the balance sheet we've got then the sales tax to the account to the sales tax payable which they put in as because we're in California California department of tax and fee administration payable account I won't even go into it don't want to deal with them and then we know that the inventory is going to go down inventory is going to go down by an amount that's not even on the invoice but driven by the item so we know that happens when we make an invoice when we're using a perpetual inventory system is the amount for it so that is good and then I'm so obviously we notice this is the bill that we bought the inventory with and then we sold the inventory here with the invoice and then we're going to go up top and the other side is going to be in the cost of the goods that are sold which is an expense account on the income statement and it's in the cost of goods sold the goods that we sold happen to be a squire or twenty of them or at least that's what we're imagining we sold in this epic guitar shop problem going back now then we can also go to the tab to the right this is the activity thus far in the current month of just February this is what's happened in February if I run it obviously the impact on this invoice was an increase to the sales and cost of goods sold the difference between the two the net impact income we can also take a look at the sub ledgers for inventory and accounts receivable let's do that now by right-clicking on the tab up top let's duplicate it two times repeat or duplicate the process and then give it a little time computers a little slow and but that's okay we like we love it anyway you're doing great computer you're doing great and then I'm going to go into the business overview we're going to go into and close the hamburger and let's scroll down we want the who owes you money and let's go into the customer balance detail customer balance detail and let's change the dates to the future for me at least this is a future date because I'm I'm working in the future O2 let's let's make it 1231 222 and run it and hold down control so who was who did we sell this to music some ridiculous name that someone made up music stuff store I think that was the one is that the one how come this is in there okay yeah I think that's it right but the total adds up to the nineteen eight one one fifty and that matches what's out on the balance sheet or it should and I believe it does nineteen eight one one five zero now we can look at the sub ledger for the inventory breaking out the inventory amounts let's do that that'll be good times we're going to go on over to the balance sheet overview reports I'll type it in in then Tory valuation summary closing up the hamburger and there we have it so we've got the quantities we've got the totals that adds up to the nine six nine eight which should also match what's on the balance sheet the big balance sheet on inventory it doesn't because I'm I'm working in the future I forgot I'm not just in the present here I'm doing stuff way in advance way out there in so in any case there's the six two six six let's go back to the balance sheet six two six six so that looks good now let's go back to the first tab and if I hold control and scroll down a bit we can turn around to the customer area now by going into the get paid and pay area and we can turn around to the customer side of things and the customer side of things closing up the hamburger and our new customer was music stuff store is or new music stuff what in the world who made this stuff up so in any case new music stuff is the one I think so there's our invoice wasn't it I think that's the one we just did so there is that if you were on the other side if you were in the accounting view that would be located in the sales tab and in the customers you can also take a look at it we might just want to sort our invoices by going to the transactions and in the business view we can close open the hamburger that would be in the bookkeeping section and transactions if you were in the accounting view you would be still in the sales area and then you'd be going to the sales transactions so here we're going to go to the transactions and then the sales and then I can look up my invoices so I'm going to hit the drop down on the filter to do so check out the invoices let's look at all the invoices to start off with there they are wonderful wonderful it gives us the items that are open of course on the right hand side we might want to just sort for the open stuff though the open invoices filter in that just give me the ones that are open that we're going to get money on so we can track these people's stuff give them some reminders so there's the open invoices that we have at this point in time okay let's open up our trial balance and just check where we stand looking at the debit leg and the credit leg standing open us to stand upright going then to the business overview reports closing up the handbook typing in trial balance to find the report of that name the report of that name doing the range change 0101222 123122 run it there we are there's our two the left and the right leg holding this company up here it is so if your numbers tie out to these numbers and you're following along that is a good sign if not try changing the date range sometimes it's a range issue on the dates and we'll be doing a transaction detail report at the end of the section which is a great report to diagnose any differences


I do it for fun. What is the best thing that's happened to you and affected you? I'll tell you exactly what that is. You've heard it here first on Cointelegraph. Not that you need any introduction to who this man is when you look at the best explainer videos on the planet, but just for the folks that are new. Just for the folks that don't know. Would you please introduce yourself and tell us what you do? My name is Amir Rosik. I'm a serial entrepreneur. I kind of stumbled on this industry about three years ago. I actually had an underwear company in Hong Kong, our neighbors over here, and I sold my shares for that. And luckily enough, I live in Toronto. We have a really robust blockchain community in Toronto. We have a huge Bitcoin crew over here. We have Hyperledger, and I'm lucky enough to know Vitalik's father, Dimitri, which is my business partner in Block East. And basically my journey started off the exact same questions like, where can I learn more about this stuff? I understand technology. I'm not a developer, but I do understand technology. The most common answer I got is, go to Reddit.  I'm not going to Reddit. I'm not spending hours. I want someone to just tell me, right? Time is the most important thing to me. I want to conserve my time. And so I realized it didn't exist. I'm like, well, I got to create my own. That's where Block East comes from. And then I love video. I love YouTubeing. I've been doing that for four or five years, and I just do it for fun. People think it's my professional thing. I'm like, that's far from it. I do it for fun. There's no business behind it. I think about it, and I'm like, I'll do it, right? You're helping out so many people in your passion.  So I'm like, I started YouTubeing, and it turns out people like that format. What was the most interesting thing that's happened to you since you started your series? Sure. Right? Not monetarily, but deep in your heart, what is the best thing that's happened to you and affected you personally after you started your series? This dates before I started doing blockchain. For me, I'm a big proponent of education. I never went to high school. I got kicked out. I started doing business when I was 15 years old. I'm 32 right now. I've had many. For me is I love the fact that no matter where you are in the world with internet connection and handheld device, you can get education for free. So for me, my biggest love and what illuminates my heart is the fact that people out of their own volition without any authority, without anybody telling them to learn, they will fully learn by themselves. Have you in Vitalik thought about building out a school or an educational platform for cryptocurrency? That's what the BlockGeeks is about. We're the world's largest online community for training developers. We have 3.5 million visitors a month, 6,000 students right now on BlockGeeks. We have three full-time blockchain engineers that are creating curriculum, and we're just moving forward. And how do you plan on scaling that? Expanding, reaching out to more folks? It's completely online, so it's agnostic, meaning we don't just focus on any technology. We'll do Ethereum, Bitcoin, Hyperledger. And no matter where you are in the world, as long as you have an internet connection, you can take our online training. What's the biggest challenge that you've come across with the online? I'll tell you exactly what that is. Number one, finding teachers that can teach. And number two, finding teachers that actually know about this space. So that was mission impossible. We didn't find anybody. So what we found is very, very smart engineers that have the love of teaching, and we trained them blockchain. Because it's all video-based, right? So we have videographers, and they spend every single day making, we make very high-quality courses, study your own pace, right? Bit by bit. So that's the biggest challenge, is finding people who have the capability of teaching. So is there a future in a blockchain-based teaching platform that really the end reward is how this student achieves their cryptocurrency education? Have you thought about incorporating a coin or a token of sorts into this educational platform? Not in blockheeks. There's gonna be, for example, we're launching Bounties soon, where students with their knowledge that they learn from courses can earn bounties. And blockheeks will give thousands of dollars away in ether per month. So we're incentivizing students. Plus, we're gonna have a reputation system non-tokenized that'll be attached to your GitHub. And we've worked with ZipRecruiter and big recruiting agencies that with your GitHub code demo, that we guarantee you a job, right? For me, I'm big on e-commerce, I'm big on SaaS, and blockheeks is a SaaS model. We're completely cash flow-neutral within two months and completely profitable within three months, right? So for us, yeah, thank you. Bootstrap, no money raise, sole individual, me, Dimitri, and Vlad, our business partner. So for me, I care about profits in a business. Obviously, business doing good before profits come. People first and profits second. So for me, I see no need to tokenize blockheeks. I see no need to blockchain it. It actually takes away from the benefit of my students. That's not to say other platforms can come around. I think we still have a very long way for something to work like that. The reality of blockchain, it's slow, it's clunky. For example, if you're an ERC-20 token, you can do seven transactions per second. My business can't handle seven transactions per second. I need hundreds of transactions per second. So the reality is that the technology is not capable yet. And we have a couple of years for this reality to actually catch up with us. My next question is, who would you ideally like to work with on your platform to better serve your consumer? On our platform, ideally, we're doing something right now like that. We're actually doing big scholarships. So we're trying to work with the biggest companies in the blockchain space, whether that is L4V, our venture fund, which I'm an advisor for, or whether that is like Cosmos, the side chain, whether that is Blockable, the amazing recruitment agency, or Normative, a massive dev shop that we work in Toronto. But we're launching a huge scholarship for people that can't afford it, even though we try to make it as affordable as possible. It's only $50 a month for all access to our courses, full Q&A support for my teachers. Like we try to make it as affordable. But once again, we're a business, right? So we're launching this amazing scholarship where like you tell us why you can't afford it, tell us what you want to learn and you're in. That is absolutely awesome. When is that launching? Well, I haven't made a public announcement, but Q1, like January, yeah. You've heard it here first on Cointelegraph, but you won't hear it until Q1. That's right. You guys got it first, yeah. Is there anything that you want the world to know right now about cryptocurrency? Bitcoin at 10,000 in December, right? What do you want the world to know about how they should look at cryptocurrency and how they should look at blockchain? I think a great example for this is if we look at history, right? If you look at, there's something called the Gauls law where it states that if we look at a complex ecosystem, like an organism, it never evolved from a complicated organism. It evolved from a single organism, and over time, that single organism became a complex organism. And so when we're looking at like society and we're looking at where do we want to go in the future, most people will be afraid of evolving into a multicellular organism, becoming much more variable and more advanced.  Most people try to understand everything. They try to become an expert in this aspect. I tell people, understand one thing. Understand that Bitcoin, if you could just understand that Bitcoin is a cryptocurrency and a cryptocurrency has these features, that's a huge step forward.  But the bottom line is like anything in life, what is reality? Reality is perception of your thoughts, right? So the story is like, for example, Bitcoin right now just, I think it's like 2,500 last time I checked the Coin Market Cap. That is the story that we told ourselves around the world and that's the story that people are accepting as truth. That doesn't mean how good the technology is. That doesn't mean the use case of the technology. All that states is that people believe that story. Reception is reality. Reception is reality. That's right. Absolutely. How can we construct a way that the underserved, those who don't have access, not even 2G networks, how can we create a social cause pool almost off of your scholarship idea? How can we create that with all of these companies that are involved with blockchain technology? Well, funny you say that. So something that I want to do and I have to figure out the reputation system and we're working on this. We want to build our own LMS is at the end of the day, I'm a fintech company, right? And I know many companies and regardless of the blockchain space is the biggest problem in the tech space is really good developers. And a certification doesn't mean you're a good dev. It means nothing.  I want to see your GitHub portfolio. I want to see how many questions you answer on Stack Exchange. I actually want to see the work that you put in, right? Just show me. Show me your developer. Show me the code. Dude, man. Now you just made my motherfuckers. My pleasure, man. My pleasure.


Hi, my name is Andrea with Foodimentary Adventures in Food, and this week I'm sharing three simple and delicious recipes using Velveeta shells and cheese. And as always, I'll make sure to leave recipe links in the description box. Today we're making Velveeta shells and cheese cheeseburger mac. You are going to need ground beef, your shells and cheese, milk, onion powder, ketchup, mustard, green onions, tomato, and sour cream. All right, so I've already browned my ground beef and to that I'm adding two and a half cups of milk, my mustard. I am adding less mustard than the recipe calls for because my husband is not a huge fan of mustard, my ketchup, and my onion powder. And I am just going to give this a stir and let it come to a boil. Okay, so my mixture is simmering away. I'm just going to add in my pasta, give it a good stir. And then I am going to cover and let this simmer away for about 10 minutes or until that pasta is tender. So my pasta is finished cooking. Now I'm just adding in that package of cheese and the sour cream. And I'm just going to give it a good stir. And next I'm going to mix in the tomato and the green onions. All right, I've got everything all plated up. This recipe is so rich and creamy. It's really good. I did feel like it needed a little bit of saltiness so I added some cooked and crumbled bacon right on top. And I am serving it with some sauteed broccoli. Today we're making Velveeta Nacho Bake. You are going to need Velveeta shells and cheese, cheddar cheese, crushed tortilla chips, taco seasoning, salsa, sour cream, and ground beef. While my ground beef is cooking away, I have prepared my Velveeta shells and cheese according to package directions. So now I'm adding in my sour cream and I'm just going to give it a good stir. And now that my meat is finished cooking, I'm just going to sprinkle in my taco seasoning and water as directed on the package and just let it cook a little bit more. Okay, so my taco meat is finished cooking. I have an eight inch casserole dish here and I am spreading half of that Velveeta shells and cheese mixture on the bottom. And next I'm going to add that taco meat mixture right on top. Now I'm going to sprinkle it with half of the cheese and next I'm going to add the rest of that mac and cheese mixture. Okay, so now I am going to cover the casserole dish with foil. I've got my oven preheated to 400 degrees and I'm going to bake this for 15 minutes. Okay, so I just took the casserole out of the oven. Now I'm just spreading on that salsa, the remaining cheese and the crushed tortilla chips. And I am going to pop this back in the oven for five minutes uncovered. So here is the casserole hot out of the oven.  So here is everything all plated up, a quick and easy casserole. It is so good. And I am serving it with some buttered corn that has a little bit of salt in there and a little bit of parsley on top for color. Today's recipe is super easy. It just calls for two additional ingredients. We are making vegetarian cheddar tomato shells and cheese. So I'm starting off by cooking the pasta according to package directions. Okay, so my pasta is done cooking and I drained it. And I just put it in a skillet instead of that same pot. I just kind of wanted to spread it out a little bit. And now I'm just adding in that package of cheese sauce. Just gonna stir it to combine. Now I'm going to add in my can of diced tomatoes. The recipe says undrained, but I did drain my tomatoes because tomatoes have a lot of water in them. I'm also adding in my cheddar cheese. And I'm going to add in some garlic powder and onion powder, but that is totally optional. And I'm just gonna give it another good stir. So here is dinner all plated up. I am serving mine with a chopped Caesar salad on the side and some garlic bread. Adding those tomatoes to that macaroni and cheese is a great way to sneak in vegetables for those picky eaters. I hope you all enjoyed all of the Velveeta shells and cheese recipes this week. If you did, please make sure to give us a thumbs up that really helps out our channel. And also if you haven't already subscribed, we'd love to have you. Thanks so much for watching and we'll see you all next time.


All right, boys. Let's do this. Peace have, good morning. So our fence contractor is coming next week, or is it the week after? To do a site visit. And he's got to measure out the yard. You know, we go to get the survey, make sure that he builds the fence on our property, not on the neighbor's property. But until we get the fence, everybody gets walked on a leash, which is a little bit of an extra hassle in the mornings and evenings and afternoons and every other time. But that's okay. We do what we got to do, right? Come on, boys. Do your thing, man. Pancake for a weasel. Peace. Blueberry pancakes, Diesel, but not for a weasel. How about a shield?  Yeah.  Yeah. Diesel, both you out of the kitchen, both out. Out. Out. Further out. Further out. You too, little buddy. Don't, don't sneak or sneak around me. You know all of you.   Diesel, there's the line there. You need to be on that side of the line. There you go. You stay here. Good boys. Stay away from my pancakes. Is it done yet? Back in Canadian tire looking for mice poison. It's gotta be around here somewhere in season, all they said. That's where I bought the blade for the lawnmower, like the other day. They're all gone now. Good thing I got it when I did. Well, it's all Christmas stuff already. Hmm. Wonder where I would find mice poison. What's this? The lawnmowers, that's not what we're looking for. Do you guys see it? There we go. I think that's what we're looking for. Rat red. We aren't just loose pellets though, right? I want them in like those little baggies. Glue boards, bait stations. Okay. Here we are on an adventure. We brought everybody along today. Even the littles get to explore a bit.  Let's do it. Let's do it. Just stay. Stay. Wait. The little guys down first. Okay. I'll let them all run around. Is this the little guys first time here? Yeah. We weren't gonna let them out here until we had mowed things down a bit at least. Oh, that's right. So we can see them a little better. Well, I got the driveway mowed down at least a little bit. He's a little bit more work, but it's better. What do you think, guys? Pretty nice yard, huh? Makes up for the fact that we don't have much to mowed at the other place. So this is where they'd gotten in last time. So we're putting this trap in here. All right, Hazel, we're gonna get them mice, right? I don't know, I've been reading all your comments. A lot of you are concerned about the mice here and stuff. Should be all right. I mean, we've left it in a field like this in more than one location before and as long as you take preventative measures, it all works out. We're doing everything we can to prevent that. And I mean, if they completely destroy the camper, there is insurance. I don't wanna rely on that, but if it comes to that, then we'll just go that route. We have nowhere else to leave it. And why pay to put it in storage when we have this nice place for it right here? Right? Plus, it's gonna be useful to us here. We don't have to move it all the time. So these are the little mouse catcher poison catchers. It's got poison in the middle there. You see, I like it that it's in a little case like this. Instead of in those like packets, that way the dogs can't get in there. So the mice will go in there, they'll nibble on that and they'll die. Clean this out in the spring. Put that right in the back there. There you go. Dinner, dinner is served. Mickey Mouse. So there is lots of dead fall in here, just like any forest, but much less than the old place. But there's enough of it here that we will have firewood for a while. We'll need to take care of this. Much easier to take care of this than the other stuff too. But the other stuff I'm referring to is that our past land, our old property. I like this one a lot better. So my comment section says, you guys think these may be silver birch. We've looked into it and they're very similar, but these are poplar. 99.9% certain on that. Forest of poplars. There's the boys over there. Hey Chevy, Diesel. Diesel realized he went too far. And Chevy, Chevy's going back. I went too far. Come here guys. Hey Chevy, I'm right here. Come here. Did you wander off too far and get scared? Chevy doesn't go very far on his own. This guy on the other hand, more of a wanderer. He's the one who led you away, wasn't he? Chevy. Oh, he's rolling in that dead frog again. Chevy, his legs just kicking up in the air like crazy. Come here, Chevy. Good boy. Did you have fun? Y'all poked out now? Where's the rest of them? Chevy? Weiner? All the seniors went and sat in the hatch. They refused to come out for another walk. Well, time to go back now. What do you say? Oh, I like it. Thank you so much. You're all right. I like it. I'm a fan of dinner, you might say. She's heavy. Back home. You guys all tired now? Y'all gonna sleep good? Especially you, Mr. Pace, all night. That's what I'm gonna call you now. It's your new name, Pace, all night. Tick, tick, tick, tick.  So mom and dad came over for a visit. For supper. For supper? Yeah. And we got the TV hung up, always getting stuff done. Especially when dad and mom are around. I don't know if it's gonna be so even without mom and dad. I'm kind of impressed we did things on our own. Got a very nice rub. I think it looks pretty good there.  Opens up the room a lot more. And you have that whole surface below it now. Without the TV on it. So, it's pretty good. Somebody's all tuckered out from the day. Ian Alfonzo. No, Ian Alfonzo? Ian, from on Facebook. I'm sorry if I pronounced your last name wrong.  I told Brett about it and she thought that was a great idea. And I think we might go with that. We'll think about it over the night. You know, it's a big decision. Gonna have that land for a long time yet. But instead of calling it the land, we'll call it our spot. So it's just like we can just say, yeah, we're gonna go to our spot tomorrow.  I like it. He said that his parents used to have some land or a place out in Rochester, New York, right? And they used to call it our spot. We like it. I like the sound of it. So I think we're gonna go with it. But we'll let you know in tomorrow's video. Chevy. You're looking at pause. It's bath time. He keeps himself very clean. He smells so good. But you gotta be careful with him. He gets stressed out like in the car on rides, like on the way to our spot, on the way to our spot. He got stressed out in the car. And when he gets stressed out, he releases these pheromones or these oils or whatever from his skin.  So you can always tell when he's kind of stressed out because he starts to smell a little bit. But when he's feeling good, he smells really good. It's almost like having an air freshener beside you. Last night I was sleeping here and he came right up beside me. And he was like right in my face. And it was so good. It was like having an air freshener right beside me. It was great. I love you so much, buddy.  So that's today's video. I think I have a load scheduled now. I have a six drop load in British Columbia. But on Monday is our Thanksgiving here in Canada. So nothing's open on Monday, which means I'll only be able to start delivering in BC on Tuesday. It's about a two day or two and a bit day drive. So if I'm starting on Tuesday, I got to be there Monday night. I really don't have to leave until Saturday night. So what's tomorrow? Friday, we have Friday and Saturday and then we'll be back on the road. Probably that. I don't think I want to push it. I could leave Sunday early morning and just push it really hard and get there. But if anything goes wrong and you're late and it's just added stress. So we'll leave Saturday night probably. So my mom and dad came to visit us today and they both helped us get the TV hung on the wall. One more thing crossed off the list. It's a long list. Anyways, I'm going to call it a night here. I'm going to get ready to go to bed. This guy's already, already there. I'm pretty tired as well. I'll see you guys tomorrow. Thanks for watching.


And the idea is to look into the future by way of the past, also, not really the future, but I mean, what can we learn today about what happened yesterday? And I was starting with the inspiration we had at EFI, at the university, where we had Christian Nygård and the Scandinavian approaches as part of our basic development of the EFI, in fact. And the key thing here was his and the Scandinavians approach to system development, which was focused on participatory design and democratic technology development. And there's some traditions back there from working with the unions. It was a project in the 70s with the Christian and actually which led to new working life agreements in Norway, where workers were then, from then onwards, allowed to negotiate the introduction of new technologies. Because at that time, workers and jobs were threatened by new technology. And a typical example is the graphical workers, typographical tools. And a big project in Sweden was linked to making new tools for the graphical workers then. And they developed many methods and approaches for participatory design. And what they actually wanted to develop is what suddenly was there, namely the desktop publishing. So it was not successful because it was overruled by development. Anyway, the hisp and the DHS approach was to adapt the Scandinavian approaches to the context of developing countries. And that was the starting point for the hisp project. And it was more to develop things in the south and empowerment in the south and actually health in the beginning. But health was where this could happen because the health sector is huge. And you have all kinds of use situations and it's very data intensive. So it's actually started in South Africa in that way. Just a couple of words about what is participatory design is on basic principles. Generally, it's about including future users in developing and designing the technical solution. And the idea is the democratic part is then that the future users should have a say in developing the technology. And be part of designing the future working conditions. And to involve users in all parts of the process. That's the key part. And mutual learning is important here in that you learn together while developing things together. And rapid prototyping or prototyping is a very important part of this approach in hisp. Where you can have many different participatory design techniques around developing a real system in real context. And to build working prototypes, that's actually the trademark of the hisp participatory design approach. And that can start with some low hanging fruits and make sure that there are some early results. And thereby learning by doing that's kind of how hisp has accommodated or actually adapted the participatory design approach then. So it started in South Africa when Mandela created, he became president and new South Africa, he was actually part of what was then called Reconstruction and Development Program through being a part. I mean I had a scholarship and worked with a and was actually staying in Cape Town and worked with the University of Cape Town and later also University of Western Cape. And through those contacts we became part of this new Reconstruction and Development Program. And information was seen as key. And the reason why information was key in the new South Africa was that it was a lot of differences and the opposite of equity in all respects between ethnic groups across geographies. And all those differences between racial and ethnic groups that you know and have maybe still remember from what you learned about apartheid. So local use of information was important because that was a way to empower the users, empower those who were kind of oppressed through apartheid. And that should now be empowered through being able to have, let's say, in local governance, that was the idea from the ANC at that time and translated into system development which was about bottom-up design and participatory design. And it was a lot of work, I mean it started in 1994, but the real first version of the database, DHRIS version 1 was tested and implemented around 97 and then in 98 it was a big push in many provinces from there on. And it's developed into national implementation around 2000. So it was a long process and important was that the participants in this process were from the beginning, a lot of people who have been in the anti-apartheid movement. So it was kind of a progressive movement and being part of this RDP as it was called and that was kind of an important part of how the gist of the HISP developed in the beginning. And one thing I became more aware of recently and I wanted to highlight was that the key part of the national health plan for South Africa, I mean the ANC, African National Congress, Mandela's Party's health plan that was to build everything on the foundation of the health districts. The districts were seen as the foundation for decentralized comprehensive primary health care and it should include the district authorities who should then coordinate and manage hospital services, health programs, health centers, community health, etc. And that was then the important part of the changes in South Africa to create these health districts that were created across all these old Bangtustans and homelands that we call these crazy things of the apartheid. And also then of course that's why DHS is called DHS district, but not only district, it's district health system in fact. So this is the background for the naming also and if you look at the visions of how these health districts should transform the health system. You see here just one example from the pilot project, one of the districts in the pilot, in the HISP pilot in the 90s, Atlantis, the typical system was that the data flows were only going out of the districts or no local use of data, it was kind of a very oppressive and depressive system because they were actually disempowered at the district level. In the old South Africa and the idea was then with by creating this district and you should change the data flows and and you should should focus on on say district database and and and district management. This was another old drawing from from the district approach and you see here that the idea was that all this different different programs data from the programs data from community data from from all the clinics, hospitals, all services that should should be integrated through this district approach and what we learned when we when we try to. Look closer at how the district used the HIS here just before the COVID started in Irwanda, Mozambique, etc. We saw we found actually that data was used but they were not really able to do these things of of. Combining data from different sources calculated calculating calculating indicates, etc. And I will come back to that that later I mean the facility profile is one one thing that is not that easy to to carry out in the current situation in the HHS and in the countries and maybe more importantly than that. We don't really have this cross program dashboards and we don't really have good denominator to calculate indicate so that is one of the reasons why I mentioned that it's possible to look into the past in order to learn what we can do now around. This exact this this area, so if we go back to the movement of the history and the details first version move to India and Mozambique mainly from 2000 and. Also other countries in in Africa from them because at the same time we were able to recruit a lot of his purse to a northern program for developing masters in Mozambique, South Africa, Malawi, Tanzania, Ethiopia, and Sri Lanka and a lot of students very enrolled in this this programs and. Once finished with their master they started with the PhD etc to run these master programs and all of these students were engaged in various starting various the tries pilots in in their home countries and in other countries so that's kind of a big, big, big movement, many, many pilots and. And but they were very difficult to to sustain and scale in countries in this pre online period, because of course this this were Microsoft office and standalone system and. Sometime around 2000 and a bit later. 2003 for something was a secret evaluation in South Africa and Mozambique with a I mean the enemies of the tries criticized it for not being treated and not professional etc etc which then led to. To the start of the details to the web based the details to and we actually created the open source master course at iffy in 2004, which then read a foundation for for the development of the details to. For a long time in fact. And at this period and the research and education and working with all these countries were very important part of what he's doing, and we had what we normally call. I mean the three pillars and one is to work and do research on on health information systems that is about integration standards architecture use of information for decision making etc. Then there is free and open source software. That's the DHS to and how to share it and how to include the groups in the countries his groups in the countries to take part in the development to the part take part in the implementation and of course education and research. The basis for for for the work at the university with masters PhDs training and courses etc. And what kind of emerge out of this situation and was that the DHS to actually got funded from ill to something called the sixth framework program in the in the. Around 2006 2009 or around there and we called it the business. And that was a building Europe Africa network in information system. I think it was. It was a requirement to have a fancy acronym and that was fancy enough. And the first DHS to started out with the overall conceptual design of the of the what was then the DHS 1.4 which was an overhaul of previous DHS one versions. And it was actually implemented first on a big scale in San Sebastian. Ola knows everything about it because he stayed there for one year and working in that program project. And when you come to the. DHS to the first pilot in Carolina in January 2006. And it's still I mean the improvement from the DHS. Microsoft standalone was not that significant in that there were no online web based system yet possibilities I mean the internet was not that strong. So the ongoing debate with Colin and the team in South Africa when they claimed that their standalone version was actually better. They were probably very right in that because for every every implementation you had to then implement servers etc in the PCs around in the district. So anyway it was. It was the DHS to it was very best. Although not having good enough internet to benefit from that. And at the same time then. We increased our profile significantly by working with the doubly show and health metric network. Which health metric network HMN was an important part in the development information system in the global south. Starting I think 2007 2006 until 2010 when it's 2010 I think it broke down because they were disagreeing between HMN and the doubly show who should get the money and all that so. But it did some great work during its existence and actually they they initiated and conducted assessment and strategic planning in 50 or more countries in Africa and all over the world. I think it's actually much more than 50 but Johan is the one who is actually knowing everything about that so we need to get the concrete figures from him. And that's an important part because we had our well-known hispish Ola Knut and Johan working with and at this HMN and doubly show. And very important also is that the HMN architecture was very well aligned with the digital to conceptual design so it was very easy when we got the question then in 2007. Whether we could use DHS to pilot this new architecture data warehouse architecture data repository architecture in Sierra Leone and of course we said yes no problem. And this is the HMN architecture which I think was extremely productive for for the DHS to roll out and scaling across the globe because it's it's it's very similar to to the conceptual design of the DHS to take data from different different sources. And you put it into a repository and you produce graphs and dashboards and all that and we produce this drawing then to show them that actually this was more realistic version of their own architecture. So I think that's that was a very, very important step forward and you can say that at this point in time. The standing of DHS 2 was quite significant. I mean I mentioned that we had people like Knut and Ola and Johan working in Geneva and was part of this and for actually some time and I think that this has been very important in the success of the DHS 2. And when HMN closed into having to close down then they declared the DHS 2 in Sierra Leone as a big success. Mainly maybe because they were not so many successes they had to brag about so they declared it anyway as success and when HMN closed down then immediately after that around 2010 11 or something. It was 50 at least 50 countries that were working and they had had their assessment and they were working on strategic plans largely based on this HMN architecture. And I think that that's also a very, very important part that for example what I will come back to later is that Kenya was one of the countries that has made their strategic plan and suddenly the old HMN etc disappeared and that was part of the reason why they came to the DHS 2. But at that time also we had a very close collaboration with other global health informatics actors like OpenMRAs, IRAs and others. We had in 2010 also interoperability workshop in Accra and where all these partners were, WHO, OpenMRAs, IRAs and others. And that was then the start of our collaboration with VAHO and Tomeka and basically based on the fact that he said that if Sierra Leone can implement DHS 2 then. Any country in West Africa can do that because if you remember back then at the time we implemented the DHS 2 in Sierra Leone. It was not long after the civil war and all this blood diamond stuff. So it was not a very conducive, generally speaking environment for system development. Anyway, so my reason for mentioning these different global issues and actors is if we go back to say look at the standing of the DHS 2. We can call it discursive strengths, discursive formation influence at this point in time at the start of what would be the big scaling up. We can say that the standing of the DHS 2 was in the global health informatics crowd. It was very high. They were working and having hackathons and interoperability workshops etc together in the country health authorities and the Ministry of Health. It was not that high but it was increasing and interestingly the donor community was very low. It was no donors funded the DHS 2 or his for anything like that at that time. This EU, this framework program, which was not linked to it was research and it was not linked to the donor community at all. So I think that is interesting. We can look at how we sit now. I think maybe the global health informatics crowd. Our standing there is considerably lower now than it was then but in the donor community, very high. So it might be interesting to see how these different measures of discursive strengths or standing is developing through time and maybe there are 400 for what will come later. So my reason for mentioning is it might be very important to work to strengthen our standing or discursive strengths in the global health informatics crowd, which is a lot of fighting there now. Of course, at this time, we're talking here that was the aggregate data where so we didn't fight over the same turf. So I think maybe that is why the fighting is a bit harder now where the tracker and all that. So anyway, that's another discussion. Interesting things happened at the time of the implementation in Kenya, which everybody have heard about. But what happened was that cables around Africa finally came and we were actually, for the Kenya project, we got an invitation from Kenya, from Danida in the end of 2010. Then we went Lars and I and Ola also to Kenya and we worked with the Minister of Health in Kenya. But still, it was not yet the vision of having an online DHIS2. So when we started to set up the DHIS2 in Kenya and we wanted to actually test the internet, the idea was to have standalone implementation across the country. We went to a neighboring small town and tested it in the hospital and we were testing the internet and launched the DHIS2 and it worked fine. But suddenly we saw that it was a power cut and after the power cut it didn't come up again and we just realized that it was not possible to implement online. And we were just on the way out when it was actually a Japanese volunteer that was with us and he said, why don't you use this? And he put up what turned out to be what he called a dongle and that was connection to the mobile internet and we plugged it in in a laptop and fired it up and it worked perfectly. And then first they realized that it was possible to do this online implementation in Kenya and in Africa and what had happened was that they had pulled the cable from Mombasa up to Nairobi just immediately before our test here. Over the next month the people were testing the internet all over Kenya and it turned out to be very fine and then the DHIS2 was implemented in Kenya and that was actually what triggered a lot of work. And it was a lot of work actually the whole with Lars and the whole team moved literally to Kenya and followed up 24-7 over quite some time over the whole 2011 to get the implementation right because Danila was pulling out so they really wanted to finish everything over the first year. And that was what happened and also had the first DHIS2 Academy in Mombasa and that helped scaling to other countries like Uganda, Uganda, Tanzania, etc. So important in this scaling was that the work with West Africa, that's wow and the ESC, that's been very important in enabling the implementation all over West Africa and all over East Africa for example working with ESC. They said, but Burundu hasn't implemented DHIS, we will help you to implement DHIS. And in East Africa, Tomé is Portuguese speaking, he has been irritated for a long time over the only country in West Africa not using the DHIS2, that's a cap word. And finally he managed to get it implemented also in cap word from a couple years back. So this regional approach has been extremely important in scaling of the DHIS2. And this is just a map showing the different regional HISP in West Africa, South Africa, East Africa, India and in Vietnam and Sri Lanka. So the regional approach has been important. And I just wanted to show this kind of development in Africa, maybe people are not fully aware. I said that when we came to 2010, we had a very strong standing in the HMN and people were making the strategic plan all over Africa etc. But at the same time, we had a mobile explosion with the subscribers in Africa, you see here, increasing 2008, 9, 10. And then we have the bandwidth in Africa, also increasing around 2010, 2011. And of course then we have the implementations of DHIS2 which is kind of directly correlating with the bandwidth. But without the strong standing and the HMN and the fact that all countries were making their plans on the one hand. And on the other hand that we have been struggling with the DHIS2 in the most difficult context in Africa like Sierra Leone and also in India for already many years. All this made it possible to hit the ground running as one might say. And to fully use the opportunity by the new internet revolution. And just a little comment on the principles we developed a couple of years back to put it that way. I think it's very, very recent. And I wanted to mention it now that free and open source software and training and education material is a very, very important part of the DHIS2 community principle. I think it might be important to highlight that now that we get all these other software applications and systems and what you have all calling themselves global goods. I think it's important to highlight that we are actually not only global goods, we are free and open source. So that's one thing and then now I'm probably community etc. But another thing which I will come back to now is that important is the developmental approach to capacity building and research and to engage users, his groups and others in action research. And then I turn to current challenges because we have a new project in his pen that is to work on improving data use, assess what might be improved, what is wrong and what can be better. And we started out before this COVID thing and had an assessment in Mozambique, around Tanzania, Kenya and also in Laos and Indonesia. But particularly East Africa showed that the DHIS data was used but DHIS2 dashboards and visuals were not used. Why? Because it was of many things but denominated data were always problematic to get for the facilities and what we can call last mile features, they are not there. I mean what makes it possible to really use the dashboards. So the new project is to revitalize the participatory design and what we can call the district data use by follow up countries and support countries and also to see how we can engage countries in action research. And to collaborate and support app development where roadmap is too slow and not precise enough and to help countries to build apps, that's the idea with this. Because if you look at the general picture of the development of participatory design in DHIS2 is that you have local use and participatory design in the country and then your feedback via the roadmap etc. Your new requirement is coming in the next release etc. What we have seen is that this is too slow to really help action research and participatory design when you are stumbling in something concrete and that's where this custom app development comes in which we will try to work on and support countries in doing. And we also have a design lab at EFI with students etc. that we will try to involve in that. Just a few examples from our assessment. This is just an example of what is used at the district level in Mozambique in our district we visited. And they were all in all their kind of dashboards and displays they used Excel they took data from the DHIS2 copied downloaded. And put it into Excel and why why not dashboards why why why can't we use that directly in DHIS2 because denominated data and target data is not in the DHIS2 because it's kind of contested.  Same in Rwanda they have routine monthly data use and evaluation meetings in districts hospitals health facilities every month they are meeting and they are discussing data. How is DHIS2 what can be improved that was our question data from DHIS2 is everywhere but DHIS2 dashboards and analytics are not really being used. Again the problem is denominator and target data for the facilities is a recurrent problem and reason here is not politics but facilities have their own data or target data and they are kind of crossing numerator areas etc. So it's always a bit complicated that's a typical last mile thing to make sure to have this and obviously we should make it easier for locals to operate with alternative denominated data. And we have a group what so group working in Rwanda now and discussing features a lot of the requirements is about adding text and reports and calculating indicators etc. We see that custom apps are possible to develop on many of these issues but many of these things cannot really be made a feature in the DHIS2. This is one example where it's not so easy to make a generic feature in DHIS typical example of a last mile problem where what they want they want to mix colors and texts in a table. So that's the challenge then to maybe make and also to make reports etc. So that's one of the challenges we will work on with the design labs and to support countries to develop custom apps.