I'm Chris Ruzzo and I am a support and operations sort of ish lead for a measurement lab may have corresponded with many of you and Nick team I'm a data journalist intern here over the summer so Nick and I have been working together this summer on a lot of data support requests which many of you have sent to us in the past and so we're going to do a breakout session on working with mLab data we got another slide so what can we make with mLab this is an example we're just really not gonna go any more than that but look we made some maps actually Nick made the maps and they're really awesome and we'd love to build some capacity in your organizations to work with the mLab data and do amazing things with it so that's what our session is about you should come because you might want to learn to use mLab data with basic r-functions jupiter notebooks get started if you're not familiar with what those things are that's fine we're gonna start from the basics and go on up to all the possibilities and then you'll have some ideas please come listen to us talk yes so hello I'm Simone I'm an intern here at mLab and I also work for uni uni is a tool how do I go to the next slide yeah I mean I have serious issues with hardware anything that is hardware I can't really deal with it thank you thank you so okay uni is this project under the Tor project umbrella to measure internet censorship and like in these two slides has just put the basics so one of the things that we do we do many things is try to in a way mock what a real web browser will do for a created test list that depend on the country and try to see if what we got is accessible if not why and if it's accessible if it makes sense what we got or not and based on that we produce research reports and this is for example a very recent research report from Egypt that is quite comprehensive and explains many findings that we we discovered among the many things that we score a very funny one is that there we discovered like that the censorship mechanism in Egypt was serving ads or crypto mining pages for domains that were blocked by the state so this is part of the stuff that we do so this is like in very few sentences what we need us what they will I hope we can do in the session is well I can provide you more background and more information on uni uni is not only a software project there is a lot of human components involved and policy I can talk about that and then I can also talk about another aspect depending on who shows up and what are your interest that is the intersection between what uni does and what M lab does and this is part of the reason why I have what hats and this is basically the fact that if you perform a lot of longitudinal performance measurements from a place then you're able to see when there is throttling because you will observe throttling on the performance measurements and there are cases like calling show the calling Anderson that used to work at M lab showed in the past that you can really see a country throttling all the people and then another possibility is that when there is a country that shuts down an area of the internet you can possibly observe that because like all the clients that were supposed to show up like on the average they disappear so that's my session. Hi everyone thanks for sticking around after lunch. My name is Michael Nakagaki and I'm with the lines for affordable internet a for a as we like to call ourselves. So the right to go online to connect with friends to purchase goods and products to civically engage with your government. These are privileges as you know that we often take for granted because over 50% of the global population still do not have access to the internet. In fact our own research shows that at the current rate of growth we will not achieve universal access until the year 2042 which is two decades beyond the SDG target year of 2020 and the billions of individuals who are left online still are women and the poor from developing countries who are experiencing inequalities and discriminations in the offline space which is reflected online and if not magnified and the number one reason for access inability is affordability in the cost and for that reason a for a I came to being around 2014. We are the world's broadest tech sector alliance and we have over 80 private companies governments and civil society from both developed and developing countries working together to transform policy and regulatory framework to drive down the costs. We believe that driving policy reform is the best way to advance technological breakthroughs around the world and we define affordability through our one for two target which means that for one gigabyte it should not cost more than 2% of national monthly income of a given nation. So as of now we're working in eight countries as you can see and we have helped develop multi stakeholder coalitions in each of these countries where we address local problems with local solutions and in order to do that we also have a robust research team that produces evidence based policy research around how policy frameworks are in place or how they're not implemented and we produce our annual affordability report which you may have heard of. We also produce case studies on infrastructure sharing or taxation broadband strategy plans and we also look at thematic briefings looking at USF reports and so forth. We actually have a report coming out with M lab on quality of services looking at download and upload speeds on mobile phones and low and middle income countries that's coming out this fall. So TBD. So for my breakout session I would love to speak have a discussion with you about how to address this inequality that we are experiencing offline in online space. What can we do to improve internet affordability? How can we close the gap on the digital divide that many women are experiencing which also includes cultural norms and also about how we can collectively produce research that can help policy makers address these issues. Thank you. Okay so Nick and Chris workshop of getting started with M lab data back there. Simone will be over here and Mako will be in the conference room right across the hall and go.


Thank you so much. So before we proceed further, I would say that I really enjoyed this panel that happened before and As we have heard a lot of you know words today, which we have been practicing every day though, which is CDP data technology, etc I think it's great that we also have Advertisers with us to share with us in terms of insights and experience that they hold from a brand's perspective But before we move further forward There was one sentence that echoed the room right which was programmatic gets you cheaper inventory Right, which was a statement long ago But now a fact which stays that and in fact the panel is all about programmatic a game changer So we have come a long way in a very short time and I think that's the power of programmatic which we all will be unleashing today So while we're talking about programmatic beams being such a game changer We know that even digital advertising has been an ever-evolving state and we all are working into it So we know at the pace at which it is moving forward, right? So especially post-pandemic we have seen advertisers and all marketeers They're finding it more and more ways to reach out to their audiences more advanced ways and with digital marketing moving heavily towards programmatic Even brands are changing their strategies and that to a very fast pace, right? So let's just understand like, you know, what are the Advanced strategies that our brands are focusing on that they're developing on and let's open the discussion with our first question for today Which is for mirror notion? For you so at the time of maximizing the most from programmatic advertising strategy We have been hearing a lot on having an omni-channel campaign approach. So what is your take on it? Yeah, thanks for the question.  I don't know if you guys have seen it in the audience Okay, Dune actually is a award-winning Academy award-winning film and it talks about future of the human generation and Actually, if you see the movie it actually goes back to basics, you know So there is a mix of a lot of physical. I mean there are queens There are kings. There are people with magical powers and then there is a lot of digitalization as well so There is there was a lot of discussion which I which I heard about programmatic and and a lot of things but I Firmly believe that the fundamentals of marketing do not change. You know Kotler Has been the king of marketing will be the king of marketing and will continue to be the king of marketing even in the future Now when Kotler wrote Kotler The the book of marketing. I mean there wasn't a lot of digital marketing There was a lot of stuff which he spoke about targeting positioning Which he spoke about identifying your audience as well. I Think those things do not change The basics do not change. I think to a large extent a lot of people in Digital marketing and in programmatic, etc kind of to a large extent give a lot of importance to The entire digital world. It's almost as if everyone is just living a digital world You know, we are we are not living a digital world, right? I mean we are we are having a panel discussion I mean we could have actually had this on zoom or we could have had it on teams You know had it been digital the fact remains that we are having this discussion physically is because we want to meet physically Now those things do not change And will never change even going ahead in the future So if anyone feels that, you know, we're gonna live in a digital world going ahead in the future. I think is It's really mistaken. You know really needs help So omni-channel is something which is obvious And I think an omni-channel experience for the consumer is is absolutely obvious The person cannot live a digital life all his life, you know So you could do a great amount of things in programmatic, you know There are so many trends that are moving towards programmatic with respect to, you know Moving from OH to a digital OH You know with respect to a lot of bots and AI doing a lot of things with respect to programmatic, you know there are things which are with respect to a More personalization to a more relevance kind of for targeting That my friend actually from the mark does and he's got a very strong point of view with respect to personalization versus relevance You know with respect to targeting So there are a lot of things that we do with respect to that but the basics remain that you know The consumer wants to see the ad when he is most Vulnerable to seeing the ad when he wants to see the ad he gets really disturbed When he does not want to see it because he sees it sees it as an intrusion to privacy You know that that's something that programmatic often is to a large extent, you know blamed for you know I often see an ad and I see that okay.   You know, that's a very different thing. So Personalization to relevance is a very very important topic and and that is something that my friend Yes, he can really talk about, you know, who's from demarc here because he's done a lot of study on that But that is really important because you know targeting the consumer when when he wants to see relevant advertising is very important And not you know when it is personalized to him because he feels like there is an intrusion to privacy So coming back to the subject that you asked Omni-channel is something which is very very obvious so for instance and We've come from a very traditional business like we are from Godrej and boys. We are into the interior business We are into the appliances business So with respect to interior, there are things that we do like for instance We asked the consumer to actually upload the photograph of the of the furniture that he wants to buy and accordingly We'll be able to suggest him, you know, the right kind of furniture that he wants You know, so those are things that we do for instance for appliances If the consumer, you know wants a demonstration We actually give him a video demonstration of what he wants to do So those sort of things are something which are relevant and are going to be continue being relevant With respect to programmatic, I think it is very very important to understand your consumer well And that is only going to come when you are actually fly on the wall and when I'm meaning fly on the wall meaning that the consumer still Kind of moves between the physical world and the digital world He is going to go to the physical store and that is a time when very traditional fly on the wall consumer inciting Understanding the consumer well understanding who's buying it understanding. When is he buying it becomes very very important and therefore Just completely relying on bots or AI for your programmatic is not right I mean you need to understand the consumer well You need to go back to your basics and kind of alter your strategy rather than completely depending upon programmatic I heard a lot with respect to Finding out the ways in which you know, he's he's going to go and surfing history and stuff like that You know Safari has stopped cookies. What are you gonna do gonna do about it? You know and and there are a lot of other people there is an entire movement right on America which talks about you know privacy So in the future what are you gonna do about it? You know it is it is it is not going to be possible to completely rely on bots, right? So finally I had to a large extent believe that an omnichannel experience relying on the old age marketing and Understanding your consumer well altering your digital strategy and programmatic according to you know, what you want is important I'm not denying that programmatic is important I think it is very very important and I again repeat that a lot of people talk about personalization I think relevance is very important and that is a difference between relevance and personalization Because personalization is intrusion Relevance is something where you actually are deceptive to the act and therefore relevance and hyper relevance is much better than hyper personalization and I think I mean yesterday sitting in the in the group here and he can talk a lot more about it because he is knowledgeable about it and we've done a lot of projects with respect to B2B as well as B2C clients and we realized that the age-old Technique about speaking to the salesperson Speaking to the consumer becomes really really important other than you know just relying on your online data Yeah, thank you. I think I spent a lot of time But I thought you know it was important absolutely and I would I'll say I couldn't agree more especially when you say that basic stone change Right fundamentals they remain same and I think that's there the word crops up media modernization But this is not plan a or plan B. This is about where we are and where are we going with evolution? And that's where when you when you made this point, which is very relevant that it's not just about personalization But also about relevancy So when we talk about omni channel and I think that's the base is all about that. Yes digital is evolution is at evolution Programmatic is at a main gameplay, but how programmatic helps us reaching a consumer in a omni channel world Which is not just digital but also offline because consumers have not moved totally towards digital It's still the knee it's still an ecosystem where we are going to physical stores offline stores And hence how programmatic can build and push that gap for us So Nishant I would also want to understand, you know similar perspective from you and when you talk about an omni channel approach Then what is your take on it? How do you see programmatic, you know bringing that solution? Especially when we talk about physical world and digital world both of which them are interconnected for audiences So what I feel is that we need to tap the consumer journey Okay, and then accordingly understand what needs to be shown where Once you do that a very important factor that comes into the this whole Proposition is your CRM activity and where you store the data Okay, and how it is evolving over a period of time and how can you actually identify the right set of an audiences And how do you show them the right kind of a communication? Okay, obviously? searches happens on digital and Then later on the activity the finals and goal of sale mostly happens on the offline medium So it's very important to understand what you show when you show and how you show In in the right proposition in the right frame of mind Looking at his interest goal level and then accordingly targeted. Okay, so that's what I feel is and mostly when there's a Planning happening or so the attic and the martech basically needs to talk to each other Okay, it's not that people are working in isolation and it's completely fall apart You know, so this is my thought on this piece of yes only channel right now going forward I think this is the best way possible that all the market years would be taking out and in spending their monies to ensure that It's not about spending only on one part of it But obviously is the second part of it is also very important and both will continue to grow and evolve together It's not this versus that. This is what I feel right. Thank you Nishant And also I was feel that when we talk about only channel strategy clearly the answer there is that we are seeking efficiency We're seeking outcomes, right? So Nishant again Thank you for the two bits that you shared here Prabhakar this question goes to you So we know that programmatic advertising is at a ever-evolving stage and we know that traditional advertising is still a very big Chunk out there and it has to work in a rallying with each other, right? So when we are talking about driving outcomes, which is highly important and something expected from programmatic as a strategy We would want to know that when it comes to you. What do you see? You know programmatic driving as a business result for your brand Thanks Tim P for the question and thanks exchange for media team for inviting me here See, I'm not very fond of jargons, you know, so pardon me if I use them in absence of plain English Okay, so I mean Mr. Pitavala talked about Kotler. He's absolutely right. I cut my teeth on brand parachute Almost 15 16 years back, you know, then worked in Seattle tires the non-dairy Pay you the now angel one just to give an example. We are acquiring half a million customer on a monthly basis And among the most profitable listed company in our business, you know, what you call fintech with double-inverted commas, okay? So, you know, so so fundamentally, you know, talking about Kotler see we are talking about consumer decision-making process That is as basic as you can get Then the next thing is a customer journey Our customer journey is about touch points about they watching traditional media bait TV Outdoor print radio what not or what they see in digital beat on Google search social media YouTube OTT what not, right? And the third thing is funnel, right? Now when it comes to business outcome, you know And I'm heading both sales and marketing for my organization So for what matters to me is eventually like, you know, what comes out at the bottom of the funnel I mean, can I call them my customer? Can I kind of put some cost matrix to it? Can I put some revenue matrix to it? You know, that's where that's where my, you know game stops in a way, right? What I find very amusing is that even people who talk about programmatic and performance marketing are very much very off, you know Kind of linking them to certain metrics. I mean that amazes me that beats me. I Mean every time I hear that, you know, this implementation will take this many months This, you know, this stabilization will take these many months and all of that fine I mean, that's okay. I mean I I do programmatic for performance marketing I look at it in certain way we have DV 316 place We have been using it for a long time. Then we have brand marketing. I mean we partner with group ms axis, you know And we do programmatic there also Now question which comes in is that Why am I doing programmatic in the first place? You know, what role does it play? I can only answer about, you know, my sector, you know Rather than adding the guests for other sectors, you know, where the customer journey and funnel would have changed See fundamentally people are You know, I mean very curious about financial topics Sometimes they're afraid of stock market So they have queries, you know, they get exposed to the idea of investing in the stock market Maybe they do it on television. Maybe they do it on radio or maybe print But when it comes to the topic as simple as how to open a demand account, what is demand account, you know How do kind of, you know, look for different What is the blue chip stock? What do they do?  I mean it'll be surprised. They also search on MX Takata Or like, you know, other other other search platforms and they used to search in tech talk also, right?  There are so many audiences possible So let me take that burden out of you, you know, rather than you planning channel wise I will take the burden out of you. I understand the audience is this channel I understand, you know, what kind of messaging will work I will take care of the dynamic dynamic creative optimization and all of that and I will do it for you in the background My trouble starts, you know, when You know, I have to choose one platform to another and both are black boxes and none of them are allowing me to kind of, you know You know, I mean, I mean make them accountable for certain metrics, right? So, I mean, that's a long story. I'll cover it during the rest of the panel discussion Fundamentally to my mind I think programmatic is very very important You need to experiment with a platform sometime like just having faith in the team behind it Or sometimes if the partner is allowing you to kind of experiment, they are subsidizing certain cost They're willing to run a pilot with you and all of that I think that's the way you can figure out that, you know How the traditional and programmatic can come together to bring the business outcomes you like I mean, I'm very happy the way we have grown up from a 50,000 account opening per month two years two and half years back to half a million that we are doing now So I believe we have got something right choosing the right channel choosing the right proportion of lower funnel pure performance marketing vis-a-vis programmatic Thanks. Thank you Prabhakar. Thank you. And I would say when you say that apart from programmatic What is a DMAT account? I think that scares many more than any of the programmatic jargons But yes, I really love the fact when you talk about programmatic and performance And I think that is one thing which I hear from almost all advertisers because that goes hand-in-hand when you talk about programmatic What is the performance are we getting? So Nishan similarly on the same lines. Let's talk about it When we talk about outcomes, there's this word performance, right, which has to be there So an industry has evolved way too much for us to understand that performance is also beyond just a lower funnel And it has many meanings and forms around it So we would want to understand from you especially that when you look at performance How do you define that especially with the background that you have on AI and you know? AI can do one this to you if you only have your matrix right around all the funnels that you're planning for What's what's your take on that? It's a nice question and you know over a period of time. We have been just hovering around performances as leads Now it's good that market is these days are moving beyond leads and trying to understand what better Capabilities programmatic can bring to the system. Okay in terms of the reach in terms of the frequency in terms of the cost-benefit analysis In terms of the visits So these are certain funnels that the market is should be look taking into consideration and are taking into consideration Than only the last funnel which is leads Okay, so if you if you actually spend some bit of it more on your top and medium funnel Obviously, I feel that you know your last funnel will accordingly give you the best results Okay, but if you these in today's I see there are a lot many new companies or the fintech companies who come on board It starts with the lower funnel The pyramid cannot be toxic to me, right? You need to do the right things to reap benefits Okay, so you spend on some bit of branding give some bit of time Let users understand what the product is all about and then the whole journey then over a period of time Using programmatic as a proposition You will be able to see that you know your results are far more better effective than just doing a lead generation campaign Okay, the consumers whom you basically acquire doing programmatic Will stay for a longer duration of time rather than using any of the other channels just to drive leads Okay, it could be a fleets or it could be anything else. Okay, so that is what I feel you know When whenever like we go for sales and we we make the client understand that you know being into programmatic ecosystem You need to give some bit of time. Okay a minimum of three to four months for for the platform to gain Certain data points basis, which we can actually then be able to understand create look alike of those audiences and make the reach Far more efficient and better. Okay, and basis that I will be able to drive results post Around three four months down the line, you know, but if it ran says from day one, you know So they have to be a bit more patient if they have to use Performance in programmatic. Otherwise, there are multiple ways to you know drive leads from day one Okay That's what I feel about right. Thank you And I think that's that's a great insight especially when you talk about data Right that you have to look and analyze your data says that you have at your hand but I would also say that when we talk about performance marketing especially today and or programmatic driving performance It cannot be just inventories or just data. It's a it's a whole suite right there, right? So when we talk about even bottom funnel or top funnel, we know that there are many elements Especially creative data technology all has to come together to build that perfect picture for you or even, you know Get you closer to your outcomes. So may I know I would really want to understand from you Especially when you're working in a such a big portfolio, right? For you challenges not just about having one strategy, right? But having customized strategy for each brand that to across the pillars, which is the important and the key So how would you define at looking at, you know driving performance for your brand? Especially when you look at data creative tech all of it together So Dimpi, I want you to ask I wanted to ask you this question How many times have you actually been spooked by the way in which you have got messaging online? Have you been spooked often in would you talk to your friends that? These guys know this thing about me.  So honestly if you're asked ask me this question a decade ago Yes, many times, but yes because I'm into this so I understand how it's outworks, but my friends and family. Yes, they do Yeah, so a lot of people actually get spooked by the way in which Programmatic works right and that actually brings me back to the point with respect to personalization versus relevance So you you spoke about creative it is very very important That the messaging that you are actually giving to the consumer when you are using programmatic is appropriate And it doesn't spoke the consumer like for instance if he's if he's chatted or if he's if he's put on Facebook about something And immediately he gets to get some message saying that you know You you wanted this and you know your it is Memberships, you know so that really spooks the consumer and and it it spooks a lot of people and it says that hey You know what am I doing and these guys have have all my data so it's it's kind of a dichotomy and a lot of people feel that programmatic with respect to AI with respect to a lot of things Is going to be able to work well if you're going to use better AI and stuff like that It's going to work well in the US right now. There is a lot of use of for DOH You know that is digital out of home It's not yet come into India, but it will soon come into India very soon So it is it is very important to use the right kind of data and the right kind of messaging and therefore Creativity becomes very very important And therefore as I said that human intervention becomes very important So it is very important to evaluate your creative on a time-to-time basis with respect to who it is exposed to What is the cohort to which it is exposed to you know You need to identify the cohort and accordingly your your creative needs to change on a regular basis with respect to who is most receptive to it and It should be designed in such a way that you are actually telling a story Like for instance in traditional advertising a lot of people say that you know you need to say a story That connects to the consumer. It is the same in the digital world as well we often forget that and We kind of send the messaging which kind of spooks the consumer and That is not the way in which the advertising needs to be done So as I said that the principles of advertising the principles of creativity, they all remain the same As you do with respect to your offline audience and you make sure that your creative is something that connects with the audience very well You need to do the same with respect to your online audience as well And that is something that is that is very very important is is what I feel yeah So I can clearly see that one message that is coming out very well here Is that no matter what kind of data tech you have at hand? What's important is the decision that you take right? How much relevance can you bring out of it? And I think that makes total sense because especially when you talk about hyper-personalization or connecting with audiences that is it is all about that your consumer has to get an impact with your campaign And that can only come when you think about relevance, which is for them not just for your strategy Yeah, I just wanted to add one more thing with your permission dimpy So right now if you were to look at the 25 years old, you know, they consume at least three sort of media I know at least three, you know, so they would actually go on the OTT platform They would perhaps read The digital newspaper or or they would see the TV So you're even your advertising needs to be consistent across all of these three because they're consuming media the Millenials right now at least consume more than three media right now It is it is different from what it was earlier and therefore the relevance of your communication becomes even more important Right, absolutely. And I think that is where the term comes from which is hyper-personalization That is not about one creative one messaging ten media channels. It's about understanding the mindset your user has I just want to clarify. I don't believe in hyper-personalization. I believe in hyper-relevance Relevance which is hyper-personalization is is a is a term which is to a large extent abused by digital marketeers It is hyper-relevance, which is important hyper-personalization spooks the consumer Yeah, it's hyper-relevance, which becomes more important. That is a trend which is emerging even if you were to look at the latest digital Programmatic advertising in the US people are moving away from hyper-personalization Which used to be the trend earlier to hyper-relevance right now. Yeah, right? I clearly understand it's like audience saying that don't bother me more I saw your ad thrice on three channels. I converted now leave me alone, please Yeah, but great insight But I would also want to understand similar from Prabhakar now Prabhakar when we talk about so mr. Pitavala does not believe in hyper-personalization But I'm sure do you have a little different take on this right and we would and the panel is all about Understanding your expertise your insights your take on it. So what's your take on it when we talk about? Creativity, how do you see creativity? Especially being in a category which is so different from anybody else, right? FinTech remains a challenging category, especially when you talk about terms like DMAT to an audiences We're looking at scale to conversions. So it's not just conversion for you But also educating them at the same time. So how do you look at creativity in this industry? Thank you, I mean just Taking it on after mr. Pitavala On this see for me, you know, I mean advertising if you look at it. No, it's a very very simple I mean I heard the definition somewhere when I was like one decade old in my Profession they say advertising is advert attention My love dhyan Bhatkana, that's advertising Now question is customer says take a dhyan Bhatkanya.   I mean for me.  I mean, that's not personalization for me, right?  I mean everybody wants to but is there something else you want You can talk to me about no, that's that's what I need to see. See, I mean, I'm not very negative on programmatic Let me Say it like this. So performance in programmatic, you know, that's possible. Let's measure it There's a way to measure it Programmatic for brand funnel, even that's a possibility There's a long tail now I mean, I was telling somebody that when I used to review TV planning or large media planning in past It used to be very easy decision Today my team comes with a long tail of OTT platform video publishing platform and whatnot platform and everything will have a 15 lakh 20 lakhs kind of budget But when I edit up, this will be one and a half two crores for a single campaign, you know And then of course, I'm spending a lot on on bigger media as well So my trouble is that in how do I go in depth of all these because I do not understand for many of these thing I'm not even an audience, you know for augmented reality what people are liking in snapchat or, you know Somewhere else. I mean, it's very difficult for me to but yet I have to make a decision Because fundamentally as a sales and marketing head if I'm approving this media plan tomorrow business doesn't happen I cannot go and tell my CEO that, you know, you have to be patient, right? I mean, I will lose my job after two months, right? So fundamentally I have to and I'll just tell my team that, you know, I mean in any campaign In the sense one thing you can make great case studies Win big awards and no disrespect to any award by the way But there are something which really work.  Now coming back to creativity. See creativity for me can happen at scale But for that to happen at scale, you need to really, really understand at least the major personas I mean, you can do then permutation combination of those personas and can talk to millions of, you know, individual Customary that sense but creativity at scale. I mean, that's that's the challenge and there are a lot of examples now, you know, I think Shah Rukh Khan and Cadbury's ad everybody talks about, you know, I mean, that's an amazing thing I mean, you really understood what that SME segment want, you know What Shah Rukh Khan brings to the table and what technology can do So I think and creativity and and almost a decade back people used to talk about old spice, you know Old spice actually, you know made interesting You know kind of, you know campaign and you know, just personalize it together and you know gave a very customized kind of reply So those things are very much a possibility and creativity is where we thrive fundamentally. I mean We are humans, you know, our emotions matter whether even in better words, they matter forget about the real Real place. So, I mean, this is where we need to put a lot of hard work and The fundamentals do not change. You have more better tools now earlier after a steam engine today is a bullet train But they have to take you from point A to point B, you know, I mean, you cannot change that Similarly, when you didn't have a programmatic that that that that time also we were doing business. Now there is a programmatic We have to do business. We have to shy away from the jargons At least the people who are responsible for business at the same time engage Because if there is a better tool and it can bring more value to your competition if they adopted back before you I think then you are doing a net disservice to your business. So have a healthy You know kind of Disrespect or suspicion but engage experiment and conclude. So, I mean, that's how I would look at creativity Personalization relevance in that respect. Thank you. I think I really like the fact when you say that, you know Of course challenge what you have in front of you but still invest into it and do your pilot campaigns do your test campaigns and then take the learnings out and You know great insights coming in when we when we hear about relevancy that it's not just a term hyper personalization Not just about in technology being implemented But how relevant is that for you and your audiences and from you understand that emotions play a vital role? Yes, we don't change we are humans at the end but Nishant also from your perspective I'd like to pick your brains on this too because coming from a very tech background and of course a different experience altogether How do you look at creativity? So, yes It's very important that we we don't ignore creativity in our oral scheme of things. Okay I think Vishal sometime back talked about DCO. Okay, and how can DCO bring value proposition for your overall programmatic campaign? Okay, I still remember around 10 years 15 years back when we used to run campaigns for Sher Khan and And you know on a brand side of it, but at the end of the day requirement was only leads Okay, what can you do? So it's only the creative, you know changing the creatives changing the communication in different ways The end result is the same as leads, right? We were able to achieve that. I'm saying from that perspective Yes, till now in terms of how you communicate in which format you communicate How do you tell your story that also is very important? Okay? It's not about just a vanilla JPEG creative or any of the you know Creative that you send it now video as a and as a tool or as a creative performs much better these days than your normal regular creatives Okay, because you're able to tell the story Okay, so at the end of the day, you will be able to achieve your own Objectives, whatever you want to do it from not from the from the performance side It could be leads from the brand side. It could be your VTR, you know Your engagement your time spent and all of it obviously makes a lot of sense. Okay? From if I talk about brands like Mariko or if I talk about brands like which which are purely Video-centric and heavy on video. They would they would not want to keep the sum and become And then it's what even it's a soap or even it's what an oil or whatever it is But they are they are more bothered about the reach the engagement, you know The story telling that's what they bring to the table Okay, but from the other side of it on the fintech the story changes completely the story is all about performance from day one so Creative plays a role differently in whichever format you want to look at it in whichever way you want to look at it In whichever matrix you want to look at it so yes, obviously creative plays a very important role in the current scheme of things and I feel that nowadays Media planning is is secondary But before that you need to understand if I make this creative. How do I position it to achieve what objective? Media plan will come second first. Let's understand the whole thought process behind Why am I going to make what I what I'm gonna achieve out of this creative that we are gonna make Okay, and then the the whole story starts earlier It used to be the media plan and then the creative element used to come into the picture So I think nowadays it's more to do with the holistic approach And I think it's performing better right it's performing well for and we have seen results as well So that's my right I mean in in Angel one like we put a brand track in place way back in 2019 It's a quarterly brand track and let me tell you that you know Whether you're working on awareness top of the funnel or consideration or purchase intention and even if it's a storytelling And changing the imagery of your brand that can be captured. So for example, you know Angel one Is for youth or Angel one is a hassle-free digital experience or Angel one You know, I mean is cutting edge technology So I want to really so so let me tell you there are tools available and this that goes back to my FMCG learning from companies like Marico You know, so somewhere I have to capture it and and and this another thing I want to tell young marketers in the room that you know Every organization is different and and fundamentally it flows from the CEO of the business because at the end of the day He's accountable for everything. You're just a function.  So fundamentally you have to find out what is the right narrative in your organization? I mean, what kind of correlation can you give on your social media fan base increase or engagement or you know Your middle funnel thing how will you link it up all up and over time if you do it correctly then you will get licensed to experiment you will get Amazing buzzer and you can actually feel very fulfilled as a market year because you'll be working at the cutting edge of What is possible to delight your audience engage them and of course of course at the end of the day make them buy No, so that's that's how I look at it Right, right. Thank you Prabhakar and I would clearly say that I think this is one one opinion Which differentiates really a lot here where we talk about, you know, what really matters most? So we talk about data technology But what we can clearly see here is especially in Ishaan building on your point that When you look at media planning the perspective should not be which channel should I put in but the fact that what is my Communication who is my audience and what is right relevant channel for it for some It could be heavy on YouTube for some it could be heavy on OTT while something for display etc But I think it should flow from your creative communication and then selection picking picking up on channel And I would say that yes This is where we have advertisers playing a bigger role for us because when you're looking at a strategy you look at it from a very 360 degree perspective not just only data and tech and Just to also wrap up our panels discussion. I would really urge you to share or summarize your expertise You're learning especially for everybody then we think from an advertiser perspective when you look at programmatic What do you really suggest for them like top three things that you say, you know focus on this and that's how you should go about it? May I start with you? Thanks So I think going ahead White label software is going to come into being You know because everyone is going to advertise on programmatic and how you're going to be able to differentiate yourself With respect to the others is going to be very important. That's where White label software comes into being you know because everyone uses the same tool everyone You know uses agencies which have the which have the same tool and stuff like that So you're going to land up with the same audiences and you're going to be land up saying different communication and stuff like that But you know white label software helps you to actually diagnose, you know who your right audiences, you know And is going to be able to do sharper targeting And sharper positioning and some sharper messaging also. So I think that is going to be the way ahead. I think There is going to be a big evolution with respect to out of home You know because there is a lot of money that is spent of out of home And and you know a lot of money is wasted because you don't get the relevant audience And therefore digital out of home is something that is going to come into India very soon It has already come into us But it is going to come into India very soon. How marketeers are going to be able to use that is going to be very very important. I think podcast as well as Music is going to be very very important. Those are those are things that are are really Shaping things up in the US. Those are things that will come into India as well, you know, but Relevant targeting is going to be very very important. I already spoke about the difference between personalization versus relevance I think a lot of websites are going to be You know cookie ever so with respect to how do you go about that is going to be very very important with respect to How do you establish a particular footprint or a? Fingerprint is going to be very important. So establishing that fingerprint with respect to going ahead and programmatic advertising is going to be very very crucial those are things which are going to be very very important and Finally, I really do believe that human intervention and programmatic is very important. So when you're doing programmatic advertising Regularly checking whether you are reaching out to the right audience whether the audience is receptive to your messaging As I said, you know, there are multiple medias that the audience is exposed to right now And that is just going to increase going ahead in the future Digital is going to be the way forward people are going to consume more TT more and more people are going to consume CTV more and more So how are you going to be able to? Do the messaging in a right manner without spooking them is going to be very important, you know So that is something which which I believe are the trends which programmatic advertising is is going to lead us towards so I think a balance between offline as well as online understanding your consumers where As well as sending the right messaging is going to be very important And I think customization which is going to come with white label software. It's the way ahead. Yeah, absolutely And yeah, when you say offline to online, I think DOH is a segment where I mean a partner's lemma They also drive the same. So they're getting the US into wider adoption in India And yes, I can't agree more that when you talk about relevance And moving from offline to online. What really is important is how do you capture all the insights very well and then use it? I would also like to understand, you know same point Nishant from you. What's your take for me? It's all about Transparency, okay, when we talk about programmatic generally people talk about you know as in the previous conversations also discussions that came up Whether it is a bot traffic where the ads would be seen all of it. You know, so there's a lot of negative biased opinion about programmatic advertising as well, you know, but thanks to all the new companies or all these as Mr. Pidavala said that, you know, the softwares and the white label solutions basically Makes the brand spend more on programmatic, okay Making them telling them that here's the cats are running on a safe ecosystem. Okay, it's non-robotic traffic Each and every money spent is is basically where it's supposed to be and there's no leakage. There's no wastage So yes for me, it's more about transparency And using the right kind of a software Right kind of for tools to ensure that we remove or negate wastages as much as possible Right, absolutely Nishant and in fact even the in the previous panel our friend Mr. Nachiket from double verify So even if we he had spoken on this could have shared more So programmatic, I think that's the strength that it brings on the table for us Especially on transparency you can track where ads are running you can see how many impressions Were getting shown to our audiences on what kind of channels is just it's very important to understand that Proper measurement stack has to be put around it and you need to see how your audiences are tapping from one channel to another Which falls into similar line to what Prabhakar had just said before that measurement is very important and is the key Prabhakar, what's what's your take on to this for all of us? Just last summarizing words Yeah, so keep it short. So I think first of all, you know, you modern-day marketing cannot be managed without technology And you know, I mean and this is the right forum to discuss technology I mean because the sheer size of audience the variety we are talking about like I mean, of course for last two years Almost 90% of her new customers are coming from tier 2 tier 3 tier 4 cities I mean talk about language differences talk about sensibilities even creativity for that matter You know, I mean what you show to a Bengali audience show it to Tamilian audience And you'll have a very different kind of reaction and both of them are Indians, okay? And then look at the generation gap, you know below the age of 30 versus above the age of 30 So without technology without measuring you cannot do it second You know at least as a marketing side of mine I have found the custom audience look alike to be a great lifesaver, you know, because it actually, you know I mean helps me Scale of my campaigns much much faster than you know where I can do it Us 12 and third thing is to all market ears, you know, whether you are questioned this or not Please understand that, you know, whether it is a revenue behavior or cost behavior How does it link to link to business just because you know one platform can give you reach and you know a big rich Doesn't mean you need to be there. You really need to understand Will the revenue will be adequate like we joke in my company that we don't want customer with Jandhan account You know, so you want really people, you know who have disposable income and they want to invest in stock market and can wait for longer time So over a period of time if you're a market here and if you measure things now, you'll see a stable pattern And this will help you to kind of take care of your businesses at a stable level Or otherwise like our competition will be like five lakh customer a month and next month below one lakh customer No, that's not how businesses are run. So you have to scale for sure But do it in a stable manner and technology and measurement can help do do that for you I just want to add to the point that Prabhakar said and I Really want to emphasize on that because he made a very relevant point With respect to how India is different from the US, you know, where you know, we copy a lot of programmatic advertising from India is vernacular to a large extent and as he very rightly mentioned The penetration of digital is going stronger and stronger and tired to entire three cities and therefore having your creative In the language in which, you know, the audience connects to you know with respect to vernacular is very very important And we have seen that with respect to advertisers also So last year actually the statistic shows that a lot of advertisers actually went vernacular, you know with with their advertising and and that shows, you know, the The connect that they wanted to make with the consumer So he made a really very relevant point I just wanted to emphasize that how important that is with respect to programmatic advertising also Yeah, absolutely and even that caught my attention too because when you talk about Especially down south for India. It's not just about language, but even with that within that states same state You see a lot many different emotions So your creative concept has to be very much relevant even for that same state You need to talk on same emotions which can connect with them I really loved the discussion. Thank you very much. I'm really honored to be on this panel. Thank you very much Thank you. Ladies and gentlemen


What's going on guys welcome to another video I'm actually out here with my grandpa on Lake Lanier and this is like his first time He's actually been out with me except for when I actually got you know my first little metal boat So we're gonna go out here the fish have been biting really good. So hopefully we can get on some top water fish I want to see if you can hook a few and I got a few rods set up for him and hopefully these fish are gonna Munch I mean there's a little bit of cloud cover. It's not bluebird skies yesterday as bluebird skies and conditions are really rough No wind today. There's not really much wind, but I'm not too concerned about it There's clouds in the sky that fish should bite a little bit better We're gonna go out to our first couple of spots. They're a little bit of top water through a spy bait and hopefully catch some big fish But let's go ahead and get this video started That's my good one you got him keep pressure Keep pressure on him. He might be a big one.  That's a good bait Yeah There you go He's tugging wasn't it look at that.  All right. Here you go. Oh, yeah, he's a good one. He's a good one get him in the net.  Oh, yeah, how about three and a quarter and put him in the live well We'll take a picture at the end.  He came off. That was a that was over five pounds Oh my god, that was over five pounds. I cannot believe he just came off. Oh My god that fish was over five pounds. I He looked like he was dang ten pounds Vinnie. I Cannot believe he just came off that was such a big I cannot believe I lost that one Get the net here. He's right here. He's right here So no that too bad with that Nope Yeah, you one thing that one that hit me over there though, that thing is about three times the size Yeah, ain't a bell Fatty is You two and a half All right guys I actually just picked up a shout out of the water and this is what I have my grandpa throw in this Do-it-spin and look at that You talk about matching the hatch That's insane right there Look at that That's why they're munching on it so hard perfect color and everything you got. Oh, it's a good large mouth It's a good large mouth. That's a good large mouth.  They ain't a spot I Was not expecting to catch a large one.  I only catch a few larges a year. And this is my second one this year There we go. Yeah, look at him. Yeah. Oh, yeah, beautiful. He grabbed that crawl right there He's right up. He was on the side of that pipe caught a few big ones here yesterday See that wind makes a difference right there. That shows it Yeah, throw your bait in there. He might get it. Look Yeah, he's right here. He's coming up He ain't that big but he's good. I mean that one that hit me before him pretty. I'll get him. You keep casting Ain't bad About two about 20 foot where my bait just landed Look, look. Oh, look at him.  Yes a monster Yeah, there's a football. Yeah, it looked like a football I thought it was way bigger than that, but that's a big one All right guys midday update we're uh, we've caught you know, it's probably six or seven It's pretty tough out here But we're what I've just figured out is you know when when there's not too much wind these fish don't bite too good Well, we've been looking around and I finally got to the part by the main lake where there's a lot of wind There's a lot of current coming through and now we're starting to get more bites See when that water's just slaking the wind. It's really hard to get them to bite But that's picked up one that was around three and a half Actually We're all in kind of large mouth.   You see the one behind him. Yeah He ain't bad. Oh my god Look, he's chasing my bait right there.  He's chasing all that bait. Yeah, I was insane Holy fishing right here. All right guys. We're starting to end off the day and get all the fishing libel We're gonna take a few quick pictures, but let me show you the libel real quick some pretty good one Life was great wouldn't have changed a thing. I had it all but with you I had more All right guys, me and my grandpa are about to get off the water right now We just took some pictures with the fish. It was uh, you know, it's really good We caught a lot of fish. He caught a few. He hasn't been fishing him forever. So that was good and You know, it was a pretty tough day But we you know, we adjusted with it and still caught some good fish and that's all that really matters I mean, we still had a good bag. We caught a little over here. I think we caught 10 or 11 fish So worked out pretty good. I lost a few big ones, but that's all right If you guys enjoyed this video and you want to see more videos of my grandpa Please hit the thumbs up button and I'll catch you guys in the next video


Good afternoon to everyone, thank you for the organizer for inviting me to talk in this conference, and I will address a problem which has been partially mentioned in the, in the, in the, in the past talk. Indeed, I will talk about how tensor network need those can be used for benchmarking content simulations. And more specifically, I will talk about the work that we have been doing recently in our group with the same amount and zero and and the question that we are going to address is this one. How efficiently can you simulate high dimensional systems indeed. In the last talk that for one dimensional system we have very, we're very well established solutions but for higher system the question is is more is a for high dimensional system the question is still under under debate. Why do we ask ourselves this question. Well, because recently, for me platforms, many experimental platform for quantum anybody systems, something like ultra cold atoms in optical lattices or chains of, of, of neutral atoms excited to reverse states or, or superconducting qubits for the realization of quantum computer trap and ions. It has been reached a level of control of isolated quantum anybody system and for sizes. Large enough that one ask. What can we do with this system, are we really able close to what Feynman told about the realization of a, of a, of a quantum computer. And indeed, what we exploit in the in these systems characterized by a large in principle number of, of constituents is the fact that they develop quantum correlation that that leads to an, to entanglement which is a purely quantum phenomenon that can help us in simulating this phenomenon in more efficient way that then we can do with the classical system and indeed, for example, we can use that for study punch dynamics of system ground state properties, and in the quantum simulation field for example, this picture is, is from paper is from a study where rapid ions have been using to simulate quantum simulate really in a, in a laboratory, the pair production of electron and positive in the one dimension or QED, or the platform that I mentioned before, are used for the application of, of, of the cubits and, and, and register of, of cubits for the application of contents here with, and the, and the, and the performing of, of, of quantum computation, but luckily, the level that so far is reached by this platform is the so intermediate scale quantum computer this means that there are still many, many errors due to environment imperfection in the realization of the, of the protocols, and at the end of the day we need the classical numerical simulation to benchmark and validate these kinds of experiments and this means that at the end of the day. We, we might think that we have to deal with the exponentially large silver space in which the state of, of the platform that I mentioned before, leaves, but luckily we ask ourselves how much entanglement are we able to encode when we perform our, our classical numerical simulation because the point is here is a, is in this fact that we need so much resource because we need to, to capture all the correlation among the, among the constituent of the, of the systems, but luckily the answer is, is encouraging from the numerical point of view because more than asking ourselves or also. We just need to ask ourselves how much entanglement are we, are we able to encode but we also might ask how much entanglement we actually need to be able to encode because at the end of the day, apart from very peculiar class of the, of the system all the interesting physics in this instance is, is, is contained in a small subset of the, of the full Hilbert space of the, of the quantum anybody system whose properties I will, I will explain new now. Indeed, let us consider that we have a one dimensional model with L size, for example, consider a lattice and the local Hilbert space of it, of the site as a local dimension D which means that the dimension of the space is D to the I. A local Hamiltonian, which we write as a sum of, of local terms indeed, and a large class of decent of systems and under this, under this conditions is characterized by the fact that if we take, if we consider the correlation between the constituents of the lattice, we find that decay very fast in, in, in space, almost exponentially or, or, or power low in some, in some peculiar case. And this means that if we consider two subsystems of our lattice A and B, and we concede and we compute the, the, the, the reduce density matrix for a system in order to compute the entropy, to characterize the entanglement present between these two subsystems. There is a class of law called a real estate in that the, the entanglement between the two partitions, a, a, a, a, and B scales like the size of the boundary between the two subpartitions in a one dimensional system. Good news for us because this means that it is constant in the, in the size of the, of the system as the boundary does not depend on, on L, but instead, and, and this is what will lead to the core of our work. So we deal efficiently with the case of a two dimensional system where indeed, if we consider a sub partition of the system and the complementary one, the boundary between the two, the size of the boundary between the two scales like the side, the linear size of the, of the, just, just one minute I get a chat from Salim Yusuf who says there is no audio in the theoretical presentation. Is it just with you Salim or it's with all the other. Sorry. I didn't get. So is there an audio for all the other students and it's just a problem with with Salim Yusuf or. So it's not a question to me. Okay, so I am sorry for stopping your presentation. Okay, sorry. Can I continue. Okay, okay. So, so at the end of the day, we must find a way to efficiently represent a quantum anybody stays living on a two dimensional, for example, lattice, which is able to, and to, to well capture the area low the system and and an answer is given within the framework of cancer network medus and I will introduce them by talking about matrix product states. The tensor networks allows an efficient compression of, of the, of the, of the information contained in a, in a quantum system, indeed, let us come back to the one dimensional lattice, and let us consider a generic state state psi on the lattice, the coefficients, which, which are needed to represent this, this state can be seen as a rank L tensor, where each of these like as a local dimension, which is the local dimension on each side. And this is a very inefficient way to describe the state. The answers that we can do is this one that instead of having a wonder man, a rank L tensor, we can represent our, our, our state our answer state as a product of local of local where we have introduced an artificial parameter, which is called the bond dimension, which we can tune in order to, to control the amount of information that we are including in the description of our system. So I'm thinking about these M into into way the first is that this is a sort of a, of an interpolation between a mean field description of the state where each site is fully considered as a, as a whole and we are completely neglecting all quantum correlation, and the full description of the quantum on, on, on the other hand, if we take a sub partition of the system and we divide it between the systems a and b, we can see at the bond dimension M as a truncation of the smith of the smith the composition that we will need to describe the, the state psi in terms of the states related to the subsystem a and, and the, now let us recall that the entropy for a one dimensional chain is a constant with the, with the system size and for what I just told the entropy scales like the logarithm of the, of the bond dimension and, and these, and this, and this relation here tells us that for one dimensional system. Our life is more or less easy because we can find an optimal M such as we are, we are able to describe the entropy independently on the, on the, on the sides of the, of the system and thus for example allow us to solve a variational problem for the search of the ground state energy, where we take the, the states psi and PS, it's a, it's dagger, and we send the cheat with the Hamiltonian written in a proper way by the user of, of, of a, of of, of, of local times or itself as they're called matrix product or operators. But now things changes when we ask ourselves for two dimensional system which is the, a good geometry that we might choose first of all, let me say that there are a plethora of proposals, each of them characterized by pros and cons in terms of the quantities that are able to compute within a certain geometry such as the local observable on the entropy and also the computational complexity of, of deriving for, from choosing a geometry or, or another for example that one shows here is a very intuitive one for, for the, for the presentation of, of, of two, of two dimensional system the aspect which stands for project and entangled pair, pair states which on the one hand is good for studying two dimensional system because you can see there are as many legs along a boundary of a given sub partition as the side as the linear sides of the all the system so the entropy is well captured, but on, on the other hand, the complexity, the computational complexity for optimizing such, such, such structure is quite high with respect to the one dimension and another structure that and, and, and it is the one that we are going to focus on is a binary tree tensor network structure. We can see that the main difference between these two, these two structure for example, which is that for example here, we don't have just a single layer of tensors like here, but we have several tensors around in a, in a, in a tree way and in a time that we go a layer above, we are in individuating some sub partitions in the, in the systems connected via these links here, and until we arrive to the top link here which is the only link that connects to half of the, of the, of the system. Our, our self what happens when we want to compute the entropy for this system so in the, in the same way as we have seen for the one dimensional system we find the two sub partition and in order to compute the the entropy. In order to compute them, we need to, to cut, we need to consider the, the, the amount of in, of in, of information encoded in the, in the top most tensor of the, of the chain, but here we have a problem because we have only one tensor with one, with one dimension M that has to contain all the, all the information spread along the sides of the, of the, of the system. So for this reason, even though three tensor network are good because they are computationally efficient, they are good for studying critical systems as they are scaling by and in this shape they are not good for the, for the, for capturing the entropy and capturing the area low in entropy. But here is, is where our, the core of our work is contained and as I will, I am going to introduce you to what we call the augmented three tensor network. So, let, let, let, let consider this is the lattice on a, on a, on a top view, on a top view. This is the tree here I am considering just a layer but consider this as a two dimensional binary tree tensor network. And these orange squares here represent the Hamiltonian of, of our system which are attached each of the, of the local parts on the, on the tree. What we are doing is to insert an additional layer of operators that we call the descent tanglers and we are going to put them between the operators of the Hamiltonian and the tree tensor network state. We are not putting them all over the tree, we are putting them in, in particular position because as we have seen before there are some portion of the, of the, of the two dimensional lattice which are described worse than others in terms of the entropy and for example, look here because here we have the two half of the lattice and all the, all the correlation is contained in just one link. And for this reason we want to place these additional tensor that can enforce the amount of information that we are able to encode here along this, this boundary here. And these, and, and, and in this way we can estimate the amount of additional information that we are providing the description of the, of the system so the, the, these are each single disentanglers is, is related to a couple of sites with the local dimension the, and this means that the amount of, of an, of entanglement with which each disentangler can participate the, the entanglement of this, of the state is, is the squared, and this means that if we have K new disentangler for each layer of the, of the, of the tree we can derive an efficient dimension that we are gaining. I am saying for each layer because you see that here we are, we are helping the encoded on of the information with respect to these links, but at the end of the day, going each layer below we can find the weaker, the weaker points in the, in the, in the lattice and enforce them with the reason thunder, but I will come back to the point of how disentanglers are placed later. Now I would like to sketch you how then the optimization scheme goes because at the end of the day, the usual, what one usually does when, when optimizing when looking for for example the ground state of an Hamiltonian with the, with the three tensor network is, is optimizing the, the variational state with respect to the Hamiltonian and this is, and this procedure is done iteratively. The convergence is, is richer. Now instead we have an, an, an, an additional step because we are not dealing with simply the Hamiltonian of our model, but we are dealing with an efficient and an effective Hamiltonian consisting of the original Hamiltonian plus the disentangler that we have put along, along, along the, along the lattice and I don't, I just mentioned but it is not important that this tensor can, can split and at the end of the day, we cannot obtain an effective Hamiltonian in the, in the same shape of the, of the original one. But the point is that the alternative procedure for the, for the search of the, of the ground state energy and, and the states now is made up two steps the first in which we are, we are, we optimize the content of the disentangler. Tensors and the other where, and so we keep constant the, the three tensor network state and the other instead in which we are update the effective Hamiltonian with the disentanglers and then we are, we are, we optimize the three tensor network state. As I told before, I would like to, to say something about how do we put disentangler along, along the lattice because I sketched as an example that we can, we can place them. It is worth placing them along the weakest boundaries of the, of the lattice but on the contrary placing all the possible disentangler wherever we want is not efficient in indeed the main rule we, we, we are, we attained is this one. We consider two sides that are connected, for example, by, by a local term of interaction, we do not put two different disentanglers attached to the, to the two sides why, why do we do this because from a, from a computational point of view we want the optimization part, the, the, the, the part in which the disentanglers are, are optimized. We want to be run in, in parallel, which means that the optimization of each disentangler must be completely uncorrelated from the optimization of, of the others and this will be impossible if they will share any, any interaction term to be more, more, more specifics I will show in the following the results of, obtained for two, for two models raising and Isabel Gamiltonian and, for example, you see that given this, this idea, for example, we don't, there are no, there are no other, other disentangler are attached in this area, following this, this rule here. And so you see that the disentangler that I mentioned when I introduced them are this one, and then the, the, the procedure with which we decide where to place them is going from the top layer to the bottom one and place as most disentanglers as we can, along the boundary that are, that are individuated from by the three layer, layer by layer. So this one, and then this one, and then these ones, and then, and so on so forth. And the slide went on by itself, and I want to, and I wanted to add that it is possible to extend this procedure of, of course, to, to models where the, the range of, of interaction is, is, is larger as it is the case, for example, for a lattice of, of interacting with the, with the atoms. And indeed, it is just enough to put less, less disentangler. So let's say that as each disentangler brings a contribution to the, to the capturing of the entropy of the, of the system at a certain point for very long range system. This, this approach becomes not, not very effective, but indeed, it helps to improve the precision of the simulation when we reach large size. And indeed, now I want to show you some of the, of the, of the, of the results of our, of our simulation. And I would like to start from the ISIM model in, into, into deep. So here I, on the X axis, there is the bond dimension. And we expect, of course, that by increasing the bond dimension, we approach ourselves to the exact, the description of the state so we expect to obtain more and more precise results. So the error is computed in this, in this way. When we compute the ground state energy for different values of the condimension, we can extrapolate a value that will correspond to the, to am going to infinite. We assume this value to be the, the true value for the ground state energy. And we take the, the, this error here as the difference between the energy at a given bond dimension and the energy at infinite bond dimension as we have estimated. And this is the case for an eight by eight lattice. And we see that both the standard, the three tensor network answers and the augmented three tensor network one more or less go give the same results. But things change a lot when we go to much larger size indeed, when we consider 64 times 64 size, we see that the augmented three tensor network allows to, to provide a more, a much more precise description of the, of the, of the ground state of the, of the model and reach a lower error. The other case that I would like to mention is the Eisenberg model that we have studied the criticality. And from this plot, these, these results here are the, are the state of the arts situation in the, in the, in the field of the of simulating the ground state energy of, of the December model and the, the errors are taken with respect to the, the quantum Monte Carlo results and at least up to, up to here and do and what we see is, is two things that of course, if we see if we look at the the three tensor network approach, we can arrive up to 32 which is a size for which there is no actually neither quantum Monte Carlo. But when we consider the augmented three tensor network we see that in this way, we can improve most of the technique commonly used and for and, and moreover we can reach unprecedented size in the, in the, the, the simulation. Now, I would like to talk to you that on about the, the second, the, the, the other application of our method that you have considered and I would like to, to kind of in, of introduce it a bit. So, as, as we have focused on the, on the, on the read the atoms platform, which, which is a, I, I consider now the one dimensional case for explaining this, we have a chain of linear atoms that are originally trapped in a, in a ray of a, of optical distance between the, these atoms of the, of the order of microns which means that is a very large distance, and this means that the single control of the level for the atoms is a, is a, is a, is actually available. But by means of a properly combined laser beams, we can establish an effective rabbi frequency, which allow us to excite these neutral atoms to highly excited rivers stays which means the principal quantum numbers, or the order of 60, 60, 70. And when the atoms are excited so much, they are able to in, to in, to in, to interact among, among themselves strongly, even if they are at the, at the, at the, at the large distances that I mentioned before. So the ramiltonian is composed by the rabbi part which couples the ground and the excited river part at the tuning, which is able to answer not the, the occupation of the, of the atoms in the, in the, in the river state, and then, and then, then the interaction between the objects in the, in the case of the, of excited isotropic states scales like one over air to the, to the, to the six. And an important feature is, is that these, these interaction here are very, very local, they are, they, they effectively affect the nearest neighbor or next nearest neighbor but no more. So strong that if a couple of atoms is close enough, they are, they are not able to be excited at, at the same way, this kind of platforms is nowadays very, very well studied because in a, in a very recent experiments for example it has been possible to study exotic quantum phase for here we're looking at results for a quantum simulator of 51 atoms trapped in, in a array of optical tweezers, or it is possible to arrange the neutral atoms in very fancy geometry is just a show off of the, of the Parisian group, the group in Paris that realize this experiment just to show how it is possible to realize several possible geometries and at the end of the day but this is very important nowadays, it is also considered to use river atom to realize quantum gates for, for programmable quantum, quantum computers. And that's the reason we thought to simulate to compute the ground state of a two dimensional river atom lattice so the Hamiltonian is the same as before just we are looking at the two dimensional lattice as I told before, the, the range of the, of the interaction is in principle infinite and we need to manually truncate it and we are truncating it up to the fourth nearest neighbor so that this is the largest in, in interaction that we are considering. And we want to check at the phases that that you that we find as we change the distance between the atoms with which means changing the, the interaction, and the tuning delta, while inside the rubby frequency omega is a character constant, which means that for each as a as we change the, the distance between the atoms and their interaction we will observe different phases as we change that blockade radius in terms of the, of the space space of the spacing of the atoms in the lattice, and this is the ground, the phase diagram of the ground state that we observe. First of all, there is more the tuning there is a, what's this called a disordered phase where no localized excitation appears but instead, as we move to larger values of the, the tuning for low values of the, of the interaction we observe as that to a chess board. phase configuration of the, of the atoms, while instead for. For atoms closer, which means higher, higher interaction energy. Also the diagonal, the diagonal positions are forbidden by the blockade radius and we find this Manhattan configuration of localized excitation in order to more quantity. The characterizes these phases we have computed the static structure factor, which allows us to, to distinguish these two phases for the peaks that emerge because we see that the Z two phases characterized by this peak in the pi pi and. Okay here, but in the in the Z four phase where the characterizing peaks in the, in the zero pi and pi zero positions. Further, further study of the, of the phases that we have, that will observe can be fine, for example, by looking at the staggered magnetization in which we see these, these staircase behavior corresponding to the disordered, the two phases. And we can characterize the type of quantum phase transitions by looking at the second derivative of the, of the energy with respect to the tuning sorry. I am considering the behavior along with this, this line here, sorry. So we see that there are two phase transition of the, of the second order, and in order to proceed to place the transition points, we have performed a finite size, size escape provided the errors from comparison between this estimation, and yes, and the estimation obtained from the computation of the derivative. And the very nice fact is that after that we put on online this, this work, the experiment has been done really in a, in a, in a, at the Harvard laboratories and they have, they have been able to study the phase diagram of 16 times 16. And they have, and they have observed this phase here that they have called the checkerboard, this one here, and the striated ones, which is this here, here in the, in the phase diagram, and, and they, and they, and they combine with those that were that you have predicted in our, in our, in our, in our calculations, but instead we didn't, we didn't reach the interactions in large enough to observe this other phase here. So now I can, I can conclude and I hope that I convinced you that tensor network can allow, allow to tackle problems which otherwise cannot be easily handled, that in particular we have focused on three tensor network and augmented three tensor network for studying high dimensional problems. And the, the open questions that remain from this work is the fact that while for three tensor network, it is easy, the computation of the, of the entropy. This is not the same for the augmented three tensor network, we know that the state describe better the, the, the entropy of the, of the system but it is not computationally efficient so far they call the actual computation of the, of the entropy. And the next step that we want to talk is the, is the, is the include the possibility to compute dynamics in our, in our system, and I have concluded and I would like to thank you for your attention and I will be happy to answer your question. Thank you. Thank you for a very nice and clear talk questions. So, I will start. So, could you please explain again why for a long range system the augmented tree are having more, more unentangling measures makes it worse. So I come back to this slide here. So, as I said before, we need to place the disentanglers inside in such a way that there are no two different disentanglers on couple of sites connected by interaction terms. So this means that for example, here for nearest neighbor interaction, we can have, they are eight disentanglers while inside, due to the fact that here, the interaction range is within this blue area, I can put less of them. And at the end of the day, the amount of improvement that I can induce in my, in the description of my, of my state is less. This is the, this is the, the point, but it is not that they, they don't work simply they, the efficiency of this, the, of this technique. It depends on the, on the balance between putting as much as disentanglers as you, as you can. This is the. Okay, makes sense.  You talk about the range of the interaction but does it really also, I mean, would it be the same situation if you have a longer range of hopping in a system somehow. You are saying if instead of having diagonal long range in interaction, I would have had a long, a long range hopping. Yes. Yes. Yes. In any way, yes. Yes. Yes, it is the same. When I say long range term I mean whatever kind of in, of interaction there. Yes. Thank you. If I can I wanted to ask you something, let's say a more technical aspect. When you perform the contraction of all your indices of your tensor network in order to compute things.  No, you have to, you have, okay, there are two. Okay, let's see. Okay, so it is, it is a standard that that when you want to, to optimize a three times or not working on a or an MPI setting of the day, you truncate up to the maximum one dimension value that you have fixed. In particular, here, in, in, in principle, we might also want, we might also consider to enlarge also the, the, the size of, of this link here when we split the, the here, for example, we, we do not increase it at all. So the, the size of, of this link here when we truncate them is fixed at the beginning that it does not depend on the, on the maximum one dimension that we, that we consider if we didn't do this. Okay, we will end up in a, in an exponentially large one dimension and so the, all the efficiency of the simulation will be lost. Okay, thank you. Maybe if I may. Yes. So, did you try to compare this method with several different other techniques and see from a, okay. We are, we are, we, we started from, we started from three times or networks as, as the complex as the computational complexities of the different geometries is, is known, for example, the computational complexity of treating with the is the, is the bond dimension to the time, while instead the complexity of three times or network is the, is m to the four, and this is one of the, of the most efficient geometries for, for three times or network, apart the limitation of the, of the full feeling of a real understanding of why we started from three times or network and the, and the, and applied the, these entangles to them. Okay, but so you didn't like pick one example, and have the, the several methods running or compare with the late literature and compare with the literature. Yes, it is what. Yes, it is this, this, this plot here, for example. Okay, okay. These are the non results. Yes, of course. Actually, let me, let me add that this, this simulation even if we ran them on standard the cluster, which means one, one node and so on and so on. The 32 by 32 C, you know, nations take times of the order of, of months so computing all the ground state and so on. So it is not feasible to take all the, all the, then you have to, you need to have an, an optimized code for all the techniques. Yeah, no, but okay, okay, yes. Sorry, I need to raise my hand like this because I don't have the button. I don't know why. About this plot. Do you, this is the anti ferromagnetic isopropane model. I see. Yes. Do you have to impose any kind of sign structure on your on your tensor network. No, because I find them. Thank you for saying that because the fact that tensor network are not affected by the same problem is a, is a great, great advantage of, of using this, this is this kind of technique. You will see it, you will see it in tomorrow in the, in the talk of, to set the money reports. Well, I would say it's actually more than that because variation Monte Carlo done with the EPS for instance that you mentioned here, also is not affected by the same problem, but results are significantly in the sense that you can simulate fermions or frustrated that you will not have any problems, but results are significantly improved. If you actually specify in your answers which is something that you can do any PS, for instance, the structure of the signs of your problem if you know it already as in the case of the Heisenberg model. We can implement symmetry is and yes there is a, I didn't go into into these details but then the simulation can be improved also on easy easy is improved already also on this, on this level. Okay, so there is a possibility to actually superimpose a strong assigned structure from somewhere else and then have the, the, the program opted the code optimize other aspects of the thing because that is something that is routinely done in variation on Monte Carlo when possible. It does improve the results a lot, for instance, the numbers of EPS that you show here I think are done without this thing if you actually apply it to the number that the precision should increase a lot. Thank you. Thank you for the comment I don't, I don't know that the details for all the. There are a lot of techniques. Now I just wanted to know if this was something that could be done for the for the augmented tree dancing networks. Thank you. I have one question. Yes. Hi Simone. I want to ask you are showing comparative results between the ATT and other methods. I think it would be also interesting if if you have any comments. It would be interesting to compare different choices of positioning of the dissent timers you also talked about this for. We have, we have. Yes, I didn't, I didn't go into. I understand from this, from these graphs, there are various choices, very different choices that you can make of where you put them. And some of them will be better than others and one question is if there is, if there is an optimal way or somehow how would you guess. Thank you. Thank you. Yes, thank you for the answer because it is something that that we have to stress in, in, in, in, in adjusting the paper so there are some, some, some strict criteria that that are the following the one of the of the interaction that I said, and then the other is the fact that we want to privilege the to put dissent tanglers on the, on the, along the boundaries of the top most layers of the, of the tree so if I, if I go here you see that the top most link is cutting this, this bipartisan here, then these, then these, these, these, then for each link, there is, there is the, these two couples of this, these two times or divide the respectively, the parts a and b into, into two other subsystems and so on so forth. So, at each layer, we have a boundary, we have a set of boundaries of, of, among all the bipartitions that are, that are individuated by the tree structure and our, our criteria is to place the dissent tanglers wherever possible, starting the boundaries related to the top most links, and then going down so for example, if I, if I now go back here, you see that for example, if you imagine that, that now we place the tree on, on this lot is there are boundaries here, and there are sub boundaries here, and then here, but instead of putting the dissent tanglers on these lines here first because they are, they look at small subsystems which are better described within the usual one dimension that we have at our disposal. For example, we, we prefer to, to announce the, the, the information content of the links that connect the larger, the larger by partitions, then, overall, given these rules that I just told you there are, there is some ambiguous, ambiguous, ambiguous, for example, this dissent tangler here might have put here, and so all, all the others might change accordingly, but the results are not, are not significantly affected by these small changes in the, in the zone. Yes. Thank you. Any questions or comments. So if not, let's thank the speaker again, and this concludes the session for today. Okay, so I think we can go I wanted to personally thank also on behalf of the air I'm pretty sure all the speakers and the people that were involved in the discussion today we had lots of interesting physics going around lots of questions and no threats, which is always a nice thing. And I, we will see you tomorrow morning the first talk is at 10. So it's a bit later than usual. And, and that's all. So have a good rest of the day and see you tomorrow.