From around the globe, it's theCUBE with digital coverage of VMworld 2020, brought to you by VMware and its ecosystem partners. Hello, and welcome back to theCUBE virtual coverage of VMworld 2020. I'm John Furrier, host of theCUBE. VMworld's not in person this year, it's on the virtual internet. A lot of content, check it out, vmworld.com. A lot of great stuff, online demos, and a lot of great keynotes. Here we've got a great conversation to unpack the NVIDIA, the AI, and all things cloud native with Chris Prasad, who's the SVP and GM of Cloud Platform Business Unit and Manavir Das, head of Enterprise Computing at NVIDIA. Gentlemen, great to see you virtually. Thanks for joining me on the virtual theCUBE for the virtual VMworld 2020. Thank you, John. Pleasure to be here. Quite a world. And I think one of the things that we've been talking about all year since COVID is the acceleration of this virtualized environment with media and everyone working at home remote really puts the pressure on digital transformation. It's been well-discussed and documented.  Chris, what are your announcements today? You got some big news. Could you take a minute to explain the big announcements today? Yeah, John. So today we want to make two major announcements regarding our partnership with NVIDIA. So let's take the first one and talk through it and then we can get to the second announcement later. In the first one, as you well know, NVIDIA is the leader in AI and VMware is the leader in virtualization and cloud. This announcement is about us teaming up to deliver a jointly engineered solution to the market to bring AI to every enterprise. So as you well know, VMware has more than 300,000 customers worldwide and we believe that this solution would enable our customers to transform their data centers or AI applications running on top of their virtualized VMware infrastructure that they already have. And we think this is going to vastly accelerate the adoption of AI and essentially democratize AI in the enterprise. Why AI, why not, Manavir? Obviously we know the GPUs have set the table for many cool things from mining Bitcoin to really providing a great user experience, but AI has been a big driver. Why now, why VMware now? Yeah, and I think it's important to understand this is about AI more than even about GPUs. This is a great moment in a time where AI has finally come to life because the hardware and software has come together to make it possible. And if you just look at industries and different parts of life, how is AI impacting?  This is based on AI. Think about the world we live in today with the importance of healthcare, drug discovery, finding vaccines for something like COVID, that work is dramatically accelerated if you use AI. And what we've been doing at NVIDIA over the years is we started with the hardware technology with the GPU, the parallel processor, if you will, that could really make these algorithms real. And then we've worked very hard on building up the ecosystem. We have two million developers today who work with NVIDIA AI. There's thousands of companies that are using AI today. But then if you think about what Chris said about the number of customers that VMware has, which is in the hundreds of thousands, the opportunity before us really now is how do we democratize this? How do we take this power of AI that makes every customer and every person better and put it in the hands of every enterprise customer? And we need a great vehicle for that and that vehicle is VMware, right? Guys, before we get to the next question, I just want to get your personal take on this because again, we've talked many times, both of you have been on theCUBE on this topic. But now I want to highlight, you mentioned the GPUs, that's hardware. This is software. VMware had hardware partners and still software is driving it. Software is driving everything, whether it's something in space, it's an IoT device or anything at the edge of the network. Software is the value. This has become so obvious. Just share your personal take on this for folks who are now seeing this for the first time. Yeah, I mean, I'll give you my take first. I'm a software guide by background. I learned a few years ago for the first time that an array is a storage device and not a data structure in programming. And that was a shock to my system. Definitely the world is based on algorithms. Algorithms are implemented in software. Great hardware enables those algorithm. Chris, your thoughts. And we're living the future right now. Yeah, I would say, look, I mean, the developers are becoming the center. They are actually driving the transformation in this industry, right? It's all about the application development. It's all about software. The infrastructure itself is becoming software defined. And the reason for that is you want the developers to be able to craft the infrastructure the way they need for the applications to run on top of. So it's all about software, like I said. Software defined. Yeah, I just want to get that quick self-congratulatory high-five amongst ourselves virtually. Congratulations. Exactly. Chris, last time we spoke at VMworld, we were obviously in person, but we talked about Tanzu and vSphere. Okay, you had Project Pacific. Does this expand? Does this announcement expand on that offering? Absolutely. I don't know, John, over the past several years, VMware has been on this journey to define the hybrid cloud infrastructure, right? It essentially is the software stack that we have which will enable our customers to provide a cloud operating model to their developers irrespective of where they want to land their workloads, whether they want to land their workloads on-premise or if they want it to be on top of AWS, Google, Azure, VMware stack is already running across all of it, as you well know. And in addition to that, we have around 4,000, 5,000 service providers who are also running our platform to deliver cloud services to their customers. So as part of that journey, last year, we took the platform and we added one further element to it. Traditionally, our platform has been used by customers for running VMs. Last year, we natively integrated Kubernetes into our platform. This was the big re-architecture of vSphere as we talked about. That was delivered to the market and essentially now customers can use the same platform to run Kubernetes containers and VM workloads. The exact same platform, it is operationally the same, so the same skill sets, tools and processes can be used to run Kubernetes as well as VM applications and the same platform runs, whether you want to run it on-premise or in any of the cloud services we talked about before. So that vastly simplifies the operational complexity that our customers have to deal with and this is the next chapter in that journey by doing the same thing for AI workflow. You guys had great success with these co-engineering joint efforts, VMware and now with NVIDIA, it's interesting, it's going to be very relevant and it's very cool, so it's cool and relevant, so check, check. Ben, if you talk about this, because how do you bring that vision to the enterprises? Yeah, John, I think it's important to understand there is some real deep computer science here between the engineers at VMware and NVIDIA. Just to lay that out, you can think of this as a three layer stack, right? The first thing that you need is clearly you need the hardware that is capable of running these algorithms, that's what the GPU enabled. Then you need a great software stack for AI, all the right algorithms that take advantage of that hardware. This is actually where NVIDIA spends most of its effort today. People may sometimes think of NVIDIA as a GPU company, but we are much more a software company now where we have over the years created a body of work of all of the software that it actually takes to do good AI, but then how do you marry this software stack with the hardware? You need a platform in the middle that supports the applications and consumes the hardware and exposes it properly. And that's where vSphere, as Chris described with either VMs or containers comes into the picture. So the computer science here is to wire all these things up together with the right algorithmics so that you get real acceleration. So as examples of early work that the two teams have done together, we have workloads in healthcare, for example, in cancer detection, where the acceleration we get with this new stack is 30X, right? The workload is running 30 times faster than it was running before this integration just on CPUs. Great performance increase. And again, you guys are hiring a lot of software developers. I can attest to knowing folks in Silicon Valley and around the world. So I know you guys are bringing the software chops to the table on a great product, by the way. So congratulations. Chris, democratization of AI for the enterprise. This is a liberating opportunity because one of the things we've heard from your customers and also from VM, we're mostly from the customer successes is that there's two types of extremes. There's the, I'm going to modernize my business. Certainly COVID's forcing companies, whether they're airlines or whatever, not a lot going on. They have an opportunity to modernize to essentially modern apps that are getting a tailwind from these new digital transformation accelerated. How does AI democratize this? Because you got people and you got technology, right? So share your thoughts on how you see this democratizing. Yeah, that's a very good question. I think if you look at how people are running AI applications today, right? You go to an enterprise, you would see that there is a silo of bare metal servers on the side where the AI stack is run and you have people with specialized skills and different tools and utilities that manage that environment. And that is what is standing in the way of AI taking off in the enterprise, right? It is not the use case. There is all these use cases which are mission critical that all companies want to do, right? A worldwide that has been the case. It is about the complexity of that is standing in the way. So what we are doing with this is we are saying, hey, that whole solution stack that Manu will talk about is integrated into the VMware virtualized infrastructure, whether it's on-prem or in the cloud. And you can manage that environment with the exact same tools and processes and skills that you traditionally had for running any other application on VMware infrastructure. So you don't need to have anything special to run this. And that's what is going to give us the acceleration that we talked about and essentially live the democratization of AI. That's a great point. I just want to highlight that and call that out because AI is every use case. You could almost say the cube could have AI. And we do actually have a little bit of AI in some of our transcriptions work, but it's not so much just use cases. It's actually not just saying it, you got to do it. So taking down that blocker, the complexity certainly is the key. And that's a great point. I'm going to call that out after. All right, let's move on to the second part of the announcement, Krish. Project Monterey. This is a big deal. And it looks like a, you know, kind of this elusive architectural thing, but it's directionally really strategic for VMware. Could you take a minute to explain this announcement and frame this for us? Absolutely. I think John, you remember Pat got on stage last year at VMworld and said, you know, we are undertaking the biggest free architecture of the vSphere platform in the last 10 years. And he was talking about natively embedding Kubernetes in vSphere, right? Remember Tanzu and Project Pacific. This year, we are announcing Project Monterey. It's a project that is a significant project with several partners in the industry, along with the NVIDIA as one of the key partners. And what we are doing is we are reimagining the share of the data center for the next generation applications. And at the center of it, what we are going to do is re-architect vSphere and ESX so that ESX can normally run on the CPU, but it will also run on the smartNICs. And what this gives us is the for, let's say data center infrastructure type services to be offloaded from running on the CPU onto the smartNIC. So what does this provide the applications? The applications then will perform better. And secondly, it provides an extra layer of security for the next generation applications. Now, we are not going to stop there. We are going to use this architecture and extend it so that we can finally eliminate one of the big silos that exist in the enterprise, which is the bare metal silo, right? Today we have virtualized environments and bare metal. And what this architecture will do is bring those bare metal environments also under ESX management. So ESX will manage environments which are virtualized and environments which are running bare metal OS. And so that's one big breakthrough and simplification further elimination of silo, further elimination of specialized skills to keep it running. And lastly, but most importantly, where we are going with this touches on the question you asked us earlier about software defined and developers being in control. Where we want to go with this is give developers the application developers the ability to really define and create their runtime on the fly dynamically. So think about it, if dynamically they're able to describe how the application should run and the infrastructure essentially kind of attaches compute resources on the fly, whether they are sitting in the same server or somewhere in the network as pools of resources, bring it all together and compose the runtime environment for them. That's going to be huge. And they won't be constrained anymore by the resources that are tied to the physical server that they are running on. And that's the vision of where we are taking it. It is going to be the next big change in the industry in terms of enterprise computing. Sounds like an operating system to me. Yeah, runtime, assembly, orchestration, all these things coming together, exciting stuff. Looking forward to digging in more after VMware. Manavir, how does this connect to NVIDIA and AI? Tie that together for us. Yeah, it's an interesting question because you would think, okay, so NVIDIA is this GPU company or this AI company, but you have to remember that NVIDIA is also a networking company because our friends at Melanox joined us not that long ago. And the interesting thing is that there's a yin and yang here because Chris described the software vision, which is brilliant. And what this does is it imposes a lot on the host CPU of the server to do. And so what we've been doing in parallel is developing hardware, a new kind of Nick, if you will, we call it a DPU or a data processing unit or a smart Nick that is capable of hosting all this stuff. So amusingly, when Chris and I started talking, one of the, we exchanged slides and we basically had the same diagram for our vision of where things go with that software, the infrastructure software being offloaded, data center infrastructure on a chip, if you will, right? And so it's a very natural confluence. We are very excited to be part of this Monterey program with Chris and his team. And we think our DPU, which is called the NVIDIA Bluefield 2 is a pretty good device to empower the work that Chris's team is doing. Guys, it's awesome stuff. And I got to say, you know, been covering VMworld now 11 years with theCUBE and I've known VMworld since it's founding, just the evolution. And just recently, before VMworld, you know, you saw the biggest IPO in the history of Wall Street, Snowflake, an enterprise data cloud company, the number one IPO ever. Enterprise tech is so exciting. This is really awesome. An NVIDIA, obviously well-known, great brand, also a chip company as well and got processors and data and software. Guys, customers are going to be very interested in this. So what should customers do to find out more? Obviously you've got Project Monterey, strategic direction, right? Frame perfectly. You got this announcement. How, if I'm a customer, how do I get involved? How do I learn more? And what's in it for me? Yeah, John, I would say. Yeah, sorry, go ahead, Chris. No, I was just going to say, sorry, but many a way I was just going to say, like a lot of these discussions are going to be happening. There are going to be panel discussions. There are going to be presentations at VMworld. So I would encourage customers to really look at these topics around Project Monterey and also about the AI work we are doing with NVIDIA. And attend those sessions and be active. And we will have ways for them to connect with us in terms of our early access programs and whatnot. And then as Vanuvar was about to say, I think Manuvar, I will give it to you about GTC. Yeah, I think right after that, we have the NVIDIA conference, which is GTC, where we'll also go over this. And I think some of this work is a lot closer to hand than people might imagine. So I would encourage watching all the sessions and learning more about how to get started. Yeah, great stuff. And just for the folks at VMworld.com watching, Cloud City's got 60 solution demos. Go look for the sessions. You got the expert sessions.  And of course, a lot of action on the content. Guys, thanks so much for coming on. Congratulations on the news, big news and NVIDIA on the Bain virtual stage here at VMworld. And of course, here in theCUBE, thanks for coming on, appreciate it. Thank you for having us. Okay, this is theCUBE's coverage of VMworld 2020 virtual. I'm John Furrier, host of theCUBE virtual here in Palo Alto, California for VMworld 2020. Thanks for watching.


Hello, this is Laptop Media, and today, we will show you how to open the Asus ZenBook S13 OLED and what's inside of it. To access this laptop's internals, you need to remove the back rubber feet. Then, undo all 9 Torx head screws you see, and pry the bottom panel with a plastic tool. Please remember, it would be of great help to us if you just hit the like button and subscribe to our channel. That would motivate us to make even more and better videos for you. Here, we find a 67Wh battery pack. It got us through nearly 12 hours of web browsing or 16 hours of video playback. To take it out, unplug the battery from the motherboard, and undo all 8 Philips head screws keeping it in place. This device comes with either 8 or 16GB of LPDDR5 RAM soldered to the motherboard. Unfortunately, an upgrade is not possible. As for the storage, there is one M.2 PCIe X4 slot, which supports Gen4 SSDs. To remove it, locate the two screws that secure its metal cover. The cooling comprises one heat pipe, a side mounted heat sink, and a fan. If you'd like to see more disassembly videos of the latest notebooks we would highly appreciate if you hit the like button and subscribe to the channel.


station that's working for you. You're watching Fox 4 News at 5 a.m. You may never be able to tell a little white lie again. Investigators say they have a new way to tell if you're fibbing and it does not involve a lie detector. It's all in the eyes.  In fact, it's called eye detect. It works by analyzing video of your eyes taken during the course of the test. When a person is in a position they have to lie, the cognitive load is great and to the point where the person then has to make a decision. Do I tell the truth? Do I lie? Do I tell the truth? Do I lie? And they finally make that decision. So they lie at that point. People dilate. Test show eye detect is 85% accurate on its own. But when a traditional polygraph is added, that jumps to 98% accurate. The eye detect test much shorter than a regular polygraph. A woman didn't bother lying when airport security in Australia asked her if she had anything to declare. She handed over a bag with a baby koala inside.


What's shakin'? My name's Cam. Welcome back to another video. If I time this video correctly, if I've done it right, it should look like I have, since the last video, magically grown my mustache back. Yeah, that's right. It's back. Come on.  Anyway, super handsome facial hair aside, I'm stoked to be doing another r slash writing video today. These are super fun to do. You guys might remember the meanest critiques one. That was both hilarious and kind of sad, let's be honest. And today will probably be much of the same because today we are talking about the worst experiences meeting authors. Have you ever met an author? How'd it go? Let me know. Now, I personally, I have met two really famous authors in my life and both were wildly different experiences. Most recently, I hung out with Veronica Roth and her husband for an afternoon. That was about two years ago. It was really fun. Long story short, I was invited to interview Veronica Roth at the Writers Festival where I live. It was her first time in Australia and it was my first time doing an interview, especially for someone so prolific. It was a huge haul. There were hundreds of kids from different schools like primary schools, high schools, that kind of stuff. I was supposed to keep Veronica Roth talking for 14 minutes about her divergent books and specifically how we thought that it engaged younger readers, etc. I must have been sweating like a nun at a strip club because in the green room it was actually Veronica trying to relax me, trying to chill me out. The thing is, I had like 500 pages of questions for her to do during the interview but I was still terrified that I would fly through them way too quick and then I wouldn't know what to do.   Obviously she's done plenty of interviews in her life so she took her time and she was really, to be honest, she was really the one holding the reins on that whole thing. If I'm being honest. But yeah, the interview actually went really, really well except it was meant to be filmed. Of course, me being the lucky person I am, my interview was the one interview that didn't actually end up getting filmed due to technicalities. Hanging out with Veronica and her husband for the afternoon, I just sat there and chatted with them while she was signing books and honestly it was one of the best experiences of my life. What I can say for Veronica is that she is an incredibly down-to-earth woman. The other time I was meeting George R. R. Mutton and I was dressed as a clown. Unfortunately, that is not a joke. I was doing a bit of cosplay at the time. The first and last time I ever did cosplay, I was dressed as the Joker from The Killing Joke like a very iconic comic book. And funny thing, true story, 100% true. I actually managed to give George a bit of a scare.  As I was walking up, he just, you know, pulled across the next thing for him to sign and started signing it for me. Didn't see me until he looked up and then he actually like, he jumped. I get to officially say that I scared the guy who wrote Game of Thrones. So pretty cool. Those are my stories. The only two stories I have of meeting or at least meeting really famous authors. But let's see what Reddit has to say. When I was in high school, I met Essie Hinton, author of The Outsiders. She told us to call her Susie. She was pretty fine and normal during the presentation she was giving. But during the meet and greet, she got a bit awkward. You can tell she's kind of socially introverted. In my teenage enthusiasm, I ran forward and told her that I really loved her book and that her writing inspired me to be an author. She took several steps away from me and just said, Oh, yikes. Not gonna lie. I would probably be thinking the exact same thing if someone came up and told me that my writing inspired them to make a career out of writing. I'd be tremendously flattered, but you know, yikes. Absolutely true story. When I was 21 in 1980, I went into a bar in Sayacaba, New York. The people that I work with told me that John Knowles, the author of one of my favorite books, A Separate Peace, was sitting at the bar. None of my friends actually cared, but I thought it would be cool to approach one of my favorite authors and let him know how much I loved his book. Soon after introducing myself to him, it became apparent that he was interested more in me and specifically having sex with me. I'm not homosexual and I wasn't really interested in having my first homosexual experience with John Knowles. As I was about to walk away, he cut to the chase.  I said no thanks and walked back to my friends. Nevertheless, it was an interesting run-in with one of my favorite authors. God damn.  Remember that time? The author of that book? Oh my God, the replies. He wanted to take you to a separate place. Come on now. I went to see Oscar Wilde, dude just laid there. But seriously, his grave is surrounded by glass that is covered in lipstick and love notes.  I guess you could say that's pretty wild. Okay, oh jesus, the comments on this one as well. The grass is also slick with semen. Desgaustang. My fiancee and I met Andrei Sapkowski, author of the Witcher novels not long ago. He paused midway through the audience questions to go to the toilet, and when my fiancee asked him for a second handshake for a photo he said, once is enough, we're not fucking.  I have heard that Andrei is a bit of an arse, apparently he's a bit salty about the success of the Witcher games because he asked for like a lump payment rather than the royalties, because he thought that the games would fail. How about recently? You know, where he said that the video game is stealing book readers from him?  I know for a fact that his book sales would have exploded since the games and especially since the show. As I approached Amy Tan at a book signing, I decided to smile big and make eye contact. She didn't like that. I got my book signed after a rather hostile glare, felt like a dummy and yet I kind of understood. Tons of fans probably do this, hoping for a tiny connection and it's gotta be annoying.  I can understand how draining it would be to be a celebrity having to interact with so many people one after the other. It genuinely would be tough. I can sympathize with that.  You have a responsibility to show your fans how grateful you are for their support.  I was a kid asking about Goosebumps. Oh well that's… damn it, that's disappointing the hair.  Oh well that might be a good place to leave it. I think. Have you ever met an author? Did it go well? Did they call your partner a whore? Let me know. Or how about this actually, if there was one activity that you could do with any author of your choosing, alive or dead, who would it be and what would you do?  Personally I think it would be pretty cool to like have a beer and play a game of pool with Joe Hill, I think that'd be pretty sick. I have plenty more r slash writing videos in the barrel so if you like this, think about subscribing. Or don't. I'm not your daddy, I'm Lance. Thanks for watching, I do hope you have a nice day, or else, catch ya.


We talk about non-equilibrium dynamics in the 2D easing model using treatments on the drugs. Thanks a lot for the introduction and also thanks for giving me the opportunity to present my work in this conference. So by now we have a pretty clear understanding on how equilibration works in a classical setting. So if we take two liquids and mix them, then we know that after a certain time they will become this kind of homogeneous mass. And we also know or like have an intuition and also the laws to describe this type of dynamics. However, if we now go to the quantum case, as probably many of you know, there are still a lot of open questions in that regard. So for example, if we take such a two-dimensional spin lattice, we split it in two halves and we initialize one half with spin ups, the other half with spin downs, then actually it is not quite clear if the system would thermalize and if so, how it will happen. And so today I want to present my research on this topic and also answer a couple of other questions in such a two-dimensional spin lattice using a numerical technique called tensor networks. So we already got a great introduction to tensor networks last week by Miles, so I will keep it rather short. But then I will go a little bit more in depth on the specifics, namely the architecture that we use is called tree tensor network. Then I will present some benchmarks to hopefully convince you that our method can work in some cases to describe dynamics in two-dimensional systems. And then we will come to the fun part where we will actually look at two very interesting cases. Alright, so last week we already heard that for the sake of tensor networks we can think about tensors as just being very high-dimensional arrays of numbers. And the neat thing is that we can also use this graphical representation where we have the tensor as being a blob and the indices are basically just open legs. And now in this graphical notation tensor multiplication means we just connect two or more of these open legs. And this is a little bit reminiscent of the Einstein notation. And now if you think about it, the wave function for example of a spin one-half system is nothing else than just a collection of complex numbers. Because once we fix the basis we just need one complex number to describe basically the amplitude for each basis vector. And so in this sense we can arrange these complex numbers in this tensor form where we have one huge blob basically and now the number of physical sites we have are the number of open indices. And there we once again encounter the usual problem that the number of parameters grows exponentially with a system size. And a couple of smart people thought about can we do better? So instead of dealing with this one very high-dimensional tensor, we can actually split it up into a product of smaller ones. And it turns out that the number of parameters now goes from this exponential scaling to a polynomial one. Here you can see a graphical notation for a very prominent example which is called matrix product state where we split up this wave function tensor into n tensors and being the number of physical sites in our system. And these tensors are now connected with a bond that has a certain dimension chi. And this bond dimension chi is basically where this exponential complexity is hidden because in order to recover the full wave function we would need to scale the bond dimension once again exponentially with a system size. But the hope would be that by cutting off chi at some finite value we can actually reach a lot of physically interesting states and hopefully work with that. It turns out that chi is actually directly related to a physical quantity namely the entanglement entropy. And so from that one can derive that for representing ground states of one-dimensional local and gap-temal tonions matrix product states are extremely good. This is due to these states having aerial law of entanglement. However what we actually after is not finding ground states and also not one dimension but first of all we want to do time evolution to look at these thermalization processes and time evolution typically leads us towards high entanglement just because as time evolves correlations are being built up in the system. And furthermore in the two-dimensional lattice it is not quite clear what architecture to use because if we take this one-dimensional matrix product state there's no good way to map it onto this two-dimensional structure. And similarly for a different reason PAPS which are the generalization of matrix product states to two-dimensional lattices they are also not that great or there are some issues because of loops present in the architecture. All right so I want to stress that this is a very hard problem and I'm not saying that we have solved dynamics in two-dimensional quantum systems but at least we want to present an architecture that can work under certain circumstances and I will show that now. So the architecture that we use is called Triton's network and the name is I guess self-explanatory because you can see we have this tree structure and this can also be generalized to higher dimensions it can look like this in two dimensions for example and the hope would be that due to this hierarchical structure which actually respects the local nature of interactions in a typical Hamiltonian we can actually push a little bit further towards this higher entanglement regime when doing time evolution. To do time evolution we employ the so-called time-dependent variational principle where the idea is that our wave function lives on this tensor network manifold which is embedded in the full Hilbert space and now after doing one infinitesimal time step we solve the Schrodinger equation. This time step can potentially lead us out of our manifold so we always need to project back onto it using this projector P and this projector P can now be split up in different ways the math for example for Triton's network has been done in this paper here and one realizes that the usual concepts you may be familiar with from matrix product states like environments and orthogonality centers they also generalize to Triton's networks in this case we have bottom environments and top environments as well as orthogonality centers a further neat thing is that kind of the most expensive operation in this scheme are matrix-matrix multiplication as well as singular-validary compositions so we profit a lot from using a GPU over a CPU in this case you can see for one TDVP time step we're on the effect of 17 speed up okay are there any questions up to this point because this has been kind of the method support so having introduced the method we will go to the benchmarking part where I will hopefully convince you that our method can work and doing dynamics in two dimensions so we will look at the transfer field ising model you can see here and we will start with an initial state that is fully transversely polarized so we are deep in this power magnetic phase and now we will look at three different quenches our results are the blue lines so the Triton's network results for an 8x8 system and we have some benchmarking results available from your quantum state simulations for a 10x10 lettuce and now in the top row you can see the time evolution of the total magnetization of the system for these three different quenches and as you can see they agree quite well and even for the most difficult case where we quench into the ferromagnetic phase we see okay the bond dimension 128 is not quite enough but by increasing the bond dimension we can improve on our approximation and then reach the benchmarking results we also have access to correlation functions so for example here you can see the light corresponding in the system and we also have access to entanglement properties I wanted to ask whether the bond dimension that you are indicating here is homogenous on the old tree or recent structure yeah basically due to this tree structure these are our physical indices they have dimension 2 so basically this bond has at most dimension 2 but then it basically is multiplicative so if you go to the next bond this would have dimension 4 because this is the whole information you can describe these two spins and so on and basically the place where we cut it off is the bond dimension here okay see thanks okay so this has been the benchmark and now we actually want to look at some interesting physics so we will stick to the transverse field ising model for the rest of the talk in this case I also added another part which is the longitudinal field and another way to think about the transverse field ising model is to write this interaction term by using this operator N which is the domain wall length operator and the idea here is basically if we have such a spin system 2D letters and we have clusters of spins then this operator would really measure the length of the domain wall separating these these spins and in a certain limit namely where the coupling is infinite the transverse field ising Hamiltonian can be reduced to the so-called PXP Hamiltonian and you may be familiar with it from for example quantum anybody's cars the idea here is that we only allow those transitions basically in the Hamiltonian which do not change the length of the domain wall so if you see here the longitudinal field term survives but for this transverse field term which actually flips spins we take only those that do not change the length of the domain wall maybe as an illustrative example if we look at this spin here it has two neighbors that are aligned in the same direction and two neighbors that are aligned in the opposite one so it has locally a domain wall length of 2 but if we flip it basically the orientation of the domain wall changes but the length does not so this is how we go from here to here basically alright and now I want to focus on a very specific initial condition namely we have a 16 by 16 spin lattice and we look at the corner of spins basically which is polarized in the same direction so for example if we take a corner like this we would initialize the spins inside the corner as looking in the positive in the action direction and the rest into the negative form here once again as a reminder the PXP Hamiltonian and it turns out that for these initial conditions the PXP Hamiltonian can be simplified even further namely it can be mapped to a one-dimensional non-interacting fermionic chain and the idea here is that if we have such a red corner configuration then each slope that goes upward can be mapped to a fermion and each slope that goes downward is a vacant site and basically the Hamiltonian that we get from this is given here the transverse field term so the spin flipping term becomes a hopping in the fermionic modes and now the interesting thing is that the longitudinal field now introduces a linear potential for our fermions and maybe you've heard that already if we had a linear potential for non-interacting fermions what we get is Vanja-Stark localization also known as like they're basically our block oscillations alright and now basically this whole thing one can solve it analytically this has been done in this paper here the exact form of this is not important right now but what is important is that we have some analytical predictions and so let's see how these Vanja-Stark localizations manifest themselves numerically so if we have no longitudinal fields basically we have no localization and what will happen is because on the corner will erode the blue line here is the analytical prediction I showed before however the interesting case is when we switch on the longitudinal field and as I said we have Vanja-Stark localization and what will happen is the corner will start to oscillate so we see around here so it starts to deteriorate this is where we reach half period and then from this point on basically the corner is rebuilding itself until we are at this point here so this has been the first example I want to show the second one being basically a different initial condition namely the following where we split up the the letters into two halves and initialize the spins on the left as spins up and on the right as spins down in this case we neglect the longitudinal field the Hamiltonian now I want to showcase two movies basically how the time evolution would look like for two extreme cases in the parameter regime on the left hand side you can see the case where the interaction strength is much much larger than the transverse field and actually because of the same analytical reasons I talked about before this domain wall is very stable it's actually stable in exponential times and this factor G over J on the other hand if we increase the transverse field we see that the letters pretty much almost thermalizes I also want to point out that the time scale here grows logarithmically so it kind of speeds up as time goes on and the question that we were asking ourselves is what happens in between so is there maybe some interesting physics going on there one quantity one can look at in that case is the so-called imbalance which is basically the difference in magnetizations of both halves so we start with a maximally imbalance state which means we have an imbalance of one and if the system thermalizes we will get an imbalance of zero and here you can see now our results for different transverse fields as well as different bond dimensions and one thing that kind of popped out to us is that for these intermediate values of G over J we have very long lift plateaus and a couple of questions that we were asking ourselves are can we describe the height and length of these plateaus for example in terms of this ratio of G over J what happens in the thermodynamic limits and is it maybe possible to derive some effective model to describe this type of dynamics so I won't be able to answer all of these questions today but at least I want to give you a taste on our progress on the last one so the idea is that to describe this type of dynamics we actually can separate it into two parts the first one being that we have this maximally imbalance state and if we now for a second neglect the interaction along the domain wall what will happen is that as time goes on the absolute value of the magnetization of both halves will kind of decrease and this will give us an effect which we call a kind of global reduction in contrast and the second effect is that spins along the domain wall will start to flip and so the domain wall will start to fluctuate and to describe this effect we came up with an effective model where the idea is that on each side in x direction we put a spin n boson and now the y position of the domain wall is described by the z component of the boson and the corresponding Hamiltonian is given by this expression here it's now one dimensional and it also has this very weird looking absolute value interaction furthermore for the results to come we will focus only on this strip around the initial domain wall to get rid of boundary effects and so now this allows us to compare the results for our full two dimensional system with this one dimensional effective model so here you can see now this comparison for different values of the transverse fields as well as different models and as you can see they agree actually quite well so most of the features are there in both models but we can make it even better by now considering this effect I was talking about in the beginning with this global reduction in contrast which we can also simulate from the full model and so if we do that you see that the height and the length of the plateaus agrees now even well with this effective model even better alright so the last point which is yeah it's a fairly new result so what I still wanted to show it here is the question of how information actually spreads in this system so we have this imbalance in the middle this domain wall and in order for the system to thermalize this information that there's an imbalance in the middle it has to spread to the bulk basically of our system and to answer this question we looked at the so-called connected correlation function which is defined here and we basically take one spin along the domain wall this red one and we compute the connected correlation function of this spin with respect to all the other blue ones now we can make a plot like this where on the x-axis we have the sides which are basically these blue squares the red line represents our position of the spin with respect to which we calculate the correlation function and on the y-axis we have the time so this is the log of the connected correlation function and now we see that for two different values in the transverse field this spreading of the correlation actually behaves quite differently so for smaller g in this case minus 0.75 we see that so we go up to times of 100 and the correlation spread only very slowly on the other hand if we increase the transverse field we see that the correlation spreads much much faster and this only goes up to time 10 and if I would plot it up to time 100 you would basically just see yellow and so this kind of gives us a glimpse that something interesting is happening maybe at g-1 and this is something we want to investigate further alright so just to summarize we have this method of tritons and networks and tiny dependent variational principle which we can use to simulate dynamics in two-dimensional quantum systems and especially for these domain wall initial states we can actually reach quite long times which in turn allows us to observe these very long lift plateaus and then we came up with an effective model to describe the dynamics of these plateaus in terms of the global reduction in contrast and kind of fluctuating domain wall and furthermore we looked at the correlation spreading which gave us a hint that there's maybe some kind of transition happening at some intermediate value of in G over J thanks a lot for your attention thank you questions if you feel you don't need the microphone go ahead or why is that thank you very much can you go back to the slides where you were comparing the your results of imbalance from simulation with the one effective 1D model the ok here here in the second like picture it seems like with the comparison it seems like the comparison is actually good in the intermediate regime or at the late time and it's not very good in the initial time so normally I mean that we would normally what expect in tensor network based simulation is like the earlier times are actually better and I don't know like why is it that the comparison is better at late times and not very good at initial times so the way we do this plot is basically so we simulate the full two dimensional system as it's done on the left and then we simulate a second system where we have this initial state and we basically neglect all of the interaction in the middle and so this gives us basically a glimpse on how this global reduction contrast is happening but of course the exact dynamics at very early times may be a little bit different so it's kind of a little bit constructed so it's not supposed to be very accurate at early times because maybe the kind of the dynamics here is a little bit different but then the agreement it's important that it agrees at later times basically Mein you wanted to ask something can you go back to the final slide so no no no the summary one exactly so I'm looking at this long time plateaus when you plot the time axis on a log scale this reminds me a lot of phenomenon known as pre-thermalization is this lifetime then exponential in some quantity, some coupling quantity or is it just power law do you happen to know we've been investigating this question and we so this has been our kind of first assumption on why this is happening but it wasn't very fruitful because so there are some considerations how this pre-thermal plateau should look like and it should be described by a GGE so like a generalized Gibbs ensemble but the conserved quantities that define the GGE they should respect the Z2 symmetry but in this case we start with an initial state that is maximally so it breaks the symmetry and so we think that in this case this is actually not the reason why we observe these pre-thermal plateaus this is the 2D model like for this pre-thermal plateaus it should be described by a GGE remember correctly okay maybe you can chat about it question here so in the case of the coordinates when you look at the dynamics of the corner it seems to me that the next one when you compare the theoretical predictions with the numerical simulations it seems to me that there is a systematic discrepancy are you worried about that I'm worried because I was involved in the theoretical predictions so that's the point so I guess you are referring maybe to this point here yes so I think one of the reasons is that this whole consideration relies on this being the case but of course we are in a numerical setting so we have to set h to its finite value and also this this period here the smaller h the longer the period so we set h to a kind of intermediate value to be able to observe this whole period basically in a finite time and so I think this is where the discrepancies might come in we might look at that I think we haven't tried that yet one last question for me is about the expressivity of the treatments on networking in 2D I have not understood let's say I give you a state with an exact 2D area low for instance a 2D finite depth quantum circuit is there a way to represent it exactly with a finite bond dimension it's not a matter of scaling of area low it's a matter of absolute level my second question was can you extract efficiently with the treatments on network the entanglement entropy it is something which is complex numerically because of some orthogonality relations so also in 2D it should work like you no more questions so let's turn the speaker again and hold the speakers of this station


Innovation is the process of creating and introducing a new solution to a given constraint. At its heart, innovation is a creative process, an inherently disorganized and messy one. Systems thinkers argue that interventions do not always produce orderly, sequential and contained outcomes. Instead, an ongoing process of action, learning, and adaptation is needed to bring about systems change. Central to this process, and indeed you might say the origins of this process, is discontent with what is. Innovation starts with a discontent for what is. If you are happy with the way the world is, you will never change much. You may find two people working on a car assembly line, the one who is quite happy with the job, happy with the way cars are made, their salary, and their place in the world. This person will just go on working the same as before indefinitely. The other, who is discontent, will search for ways to not stay doing what they are doing, and channeling that in a constructive way will lead them to finding a different, faster, or better way of doing things. It is our discontent with some aspect of our world that drives us to conceive of a different, better world. No matter how big or small that discontent is, and how big or small that vision of a better world is, it is what drives innovation and change. Innovation is a creative process. Creative processes do not happen by staying in our comfort zone. New things get created out of tensions, frictions, conflict created by contradictions that are waiting to be resolved, but others shy away from them. It is often said that the capacity of a first-rate intellect is to hold two contradictory ideas at the same time. We have to be able to envision an ideal world, but at the same time be open to the reality in front of us that is typically far from that. Peter Senji articulates this well when he says, the energy of the creative process comes from this gap. How do you generate the gap? Obviously, when you start to articulate a vision, you generate that energy, but just as much when you start to see more clearly the current reality that also generates tension. There are two fundamental ways to generate creative tension. One is by articulating and getting committed to a vision, and the other, it is about getting clearer about what is. So, to put it simply, two sources of creative tension are aspiration and the truth. Somewhat paradoxically, real change is as much about accepting what is as it is about envisioning a different future. To go through the creative process is to hold those two that create the contradictions, to live with them and use them as the fuel to your creativity and eventually create some resolution to them. It is that resolution to the constraint or contradiction that will then work as a generic solution that others can use without having to go through that full process. We have to have a vision of a perfect world and a sense of the real world. We have to hold the ideal and the real without slipping too far into either. Energy is not a thing, it is the potential difference between two things. Without two different things, there is no potential energy, no capacity to do work and in this case, no creative process. The real contradiction and tension that drives this whole process is the difference between the real and the ideal. When those two things are one, then it is game over.  Either way, the creative process is over. It is the journey in between that matters where you are fueled by the difference between the two. The solution may take the form of an institution, a process or technology but what the innovation is is really the product of your resolution of the contradiction you manage to live with and resolve during the process of innovation. Put simply, if you don't feel uncomfortable with yourself about something, you are fundamentally not creating. It is when you put yourself into a space that is uncomfortable for you, when you accept and live with some opinion or perspective that creates dissonance within your accepted paradigm, that is the opportunity for innovation and change. Indeed, we might extrapolate that out to say that it is our collective societal discontent with the world we have created that is the fuel enabling systems change on a macro level. Tension may be the fuel but the actual innovation process requires deep insight, prolonged analysis, systems design and development. As we will discuss in a coming module, if you want to innovate in a system, it is not just necessary that you understand the current form of that system but also understand it in the abstract. Understanding the system in the abstract shows you the full set of possibilities for that system and it is that set of possibilities that creates the space for innovation. By understanding what you are dealing with as a system, you will be able to see what its function is and that provides some rationale as to what is better and what is worse. It is only with insight that we can see beyond what exists to what might exist. Complex systems are counterintuitive. Our first understanding of the system and the problems at hand are typically close to the complete opposite of what is really going on. The people and organizations within the system will have all sorts of agendas that will create all sorts of narratives surrounding the nature of the system and where the problems are coming from. To actually understand what is going on requires deep and prolonged analysis of how the parts interrelate to create the system's behavior. All complex systems have a history that shapes their present and future. It is critical to understand how the system has evolved to its current state and the evolutionary potential that exists within the system now which will enable it to move forward. With systems innovation, we are not creating something new. All complex systems are the product of long evolutionary processes. We never really get to a clean slate to simply build a new one from scratch. All we can do is work with the evolutionary potential within the system. Systems innovation is costly and rare. Systems don't change fundamentally unless they really have to because it is a difficult, costly exercise that the system might not survive. It is part of the basic survival mechanism of a system not to undertake large-scale structural change unless it is absolutely necessary. Of David Snowden's three necessary conditions for innovation, the first two are starvation and pressure. As such, it only happens when a complex system is in a state of transition. In a normal state, you only get incremental innovations. It is only during transitions when the system is in a state of crisis an exponential change that it has the potential to adopt a new way or model of organization. It is only during these phase transitions that there is enough positive feedback to drive exponential change and qualitative changes in structure. System change is about enabling these nonlinear transitions. To do systems innovation is to understand the basic structures of the current system and the potential to evolve to a higher level of organization along some set of trajectories. Complex problems require a prolonged effort by a multiplicity of actors. To coordinate that effect requires the building of a platform that can support a network of actors to coordinate around the given issues. Take for example the issue of obesity. If we were to look at all of the drivers behind obesity, there is no single one. In fact, there are maybe 50 to 100 drivers behind it with probably hundreds of different organizations that are producing and impacting the level of obesity. In a world like that, a command and control centralized organization will not work. One genius sitting in a room is not going to solve the problem. These complex problems require a form of innovation which is fundamentally democratized and distributed but also coordinated and working together over a prolonged period. In short, don't build an organization because most of the people and resources you will need to tackle the issue will be outside of it. Only a tiny fraction of the resources you will need to tackle the issue will be inside of it, and thus you will not be able to do much. To harness those resources outside, you need to instead create a network, a platform as a vehicle for collaboration and coordination.


Look at the broader philosophical point, the Green Party of England and Wales has had to afford two elections with two different sets of proposals of how to fund it. The first one in 2015 was very much focused on wealth taxes and you're taxing the rich in a way that we totally don't in the UK. And multinational companies, I think if we think about that, there's a way of looking at universal basic income as a way of distributing the social capital, the capital that history created that all that that all of our ancestors built structures created wealth in society. Sometimes through colonialism stole wealth, but nonetheless the wealth is here now. And so what we're doing is sharing out the resource that's available to everybody. One of my favorite lines on this is that if you put Bill Gates on a desert island, he wouldn't make a penny. Rich people, rich individuals and companies benefit from all the infrastructure that society's created and what you're doing is sharing that out through the payment of universal basic income. What we did in 2019 was we changed the focus somewhat and this was in some ways a result of the Gilles Jeun, the yellow jacket protesters in France. And we saw with them a great deal of anger that relatively poor people felt they were being made with carbon taxes to pay while France was actually cutting taxes on the wealthy. And so we looked at saying, here's a carbon tax and the money. And that creates a very clear link between what we have to do on the environment with social justice. And so I think that's another useful way of looking at it. But ultimately, of course, the final thing to say is that COVID-19, as we saw with the financial crash, when they want to bail out the banks, when they want to bail out the economy, very large sums of money are found very quickly. They can be found that can be done. Sometimes people say financial basic income is a problem, but I really don't think it's a problem because we know that there is enough wealth and the only question is how we distribute that wealth. I hope that there would be more fairness and justice in funding the corona crisis after math. Right now, many people have lost their jobs and lost their income and don't get that much social security. And at the same time, there is a problem of unequal taxation, for example, in the European Union level. So many of the major corporations, businesses and owners are paying very little taxes. So I think that we must look into these questions of fairness and justice in the tax systems and in what kind of project we fund.


Tarzan and the Diamond of Arshere. In the French-African port of Loango, Tarzan and Dono meet the father and sister of the lost archaeologist Brian Gregory, for whom Tarzan is mistaken by Ahtan Tom and his serious woman companion, Magra. Tarzan takes charge of the Gregory expedition, organized to search for young Brian Gregory. Tom, believing Tarzan to have in his possession a map showing the location of the forbidden city of Arshere, manages to bribe Wolf, one of the Gregory guides and hunters, who with the help of Magra, is ordered by Tom to secure the map and deliver it to him. As the scene opens, we find the Gregory party aboard the little river steamer, which will carry them up the Congo to Bunga, where the trek into the jungle is to begin. I'm sorry you're not going with us, I'll miss you. Why, I thought Lieutenant Dono was going. He told me this morning he had arranged his plan so he could go. Yes, uh, buvoyé Tarzan. While Memoirs of Gregory and I were shopping this morning, I cabled Paris for three months' leave and so I am going with you. Well, well, Lieutenant, that's a pleasant surprise. Dono and I will be mighty glad to have... But the lights, the music, the boulevards of Paris, Dono, yesterday you were almost in a hurry to leave Africa. That, mon cher ami, was yesterday. And besides, when I leave for France, it may be a very long time before I see you again. If we allore, if you do not, I'll get, I shall go with you. I am glad, Dono. Miss Gregory is a very charming and lady, isn't she? Oui, ma vieille branque, elle est magnifique. Our equipment and supplies been loaded. All right, Larson, where is Wolf? He's up for it. He just came out. Then as our traps were the last to be loaded, I suppose we'll be leaving soon. No, they are having to cast off now, Monsieur Gregory. Larson, everything is in good order. They would have been aboard sooner, but they had some personal business to take care of. Well, any orders? No, not now. We'll have enough to do when we're on safari. Well, they'll be in my cabin, if you want. Larson and I are working together. Mr. Tarzan. I don't like that man, Dad. Wolf, what's the matter with him? Something about his eyes, I guess. They're too curious. They seem to be probing, searching for something all the time. Did you notice how he emphasized Tarzan's name twice? Up to your old tricks, eh, daughter? Letting your imagination get the better of you? Wolf's all right. He wouldn't be here if he wasn't. How about it, Tarzan? He's all right. Oh, well, maybe I'm wrong. Only he spoke your name as though he doubted its authenticity. I didn't notice. I've never seen him before, and he doesn't know me. Don't get it, Helen. The man's bound to be all right, and Mitchell would not have hired him. When do we get to Bonga, Tarzan? Tomorrow, before noon. If, as Mitchell said, his arrangements have been completed and the bearers are waiting, we'll camp in the jungle tomorrow night. We do not spend the night in Bonga, then, eh? No reason for it. We want to get underway as soon as possible. That's your idea, isn't it, Gregory? Yes, I want to get started on the search for Brian as quickly as I can. You men can sit up and talk as long as you like, but I'm turning in. It's late, and I'm very tired. Good idea, daughter. I think I'll follow your example. Good night, Tarzan. Good night, Gregory. Pardon me, Miss Gregory. Will you step into my cabin one moment, please? Why? Please come in only for a moment. I wish to speak with you about your expedition. Our expedition? Why? Yes, I'll come. What about the expedition? You are going into the Belgian Congo, Argyna, to the region of Tuenbaca? You know of Tuenbaca, the mountain of sunrise? A year ago, I traveled in that region on safari. I was unable to finish my mission there, and I'm returning now. Oh, not alone? Yes. But when I learned from Mr. Mitchell that you are going to the same region, I thought it would be so much better to travel with a large party and in the company of another woman. Oh, of course. It must be rather trying for a woman to undertake such a trip alone. I understand. You'd like to join our party? Oh, I'm so happy that you do understand, and I'm sure I will cause you no inconvenience. I am accustomed to traveling in the jungle. You see, I had intended to organize my own little safari in Bunga, but now... Oh, there's no need for that now. I'll speak to Father and Tarzan. I'm sure it can be a rain. Tarzan? He's taking charge of our expedition, but your name, I'm afraid I didn't catch it. My name is Magra. Magra? Magra, why? Why, Tarzan mentioned that name at dinner last night. Yes? He asked if my brother had ever mentioned any of his letters to us. And did he? No, but... But I doubt that Tarzan seemed to think you knew him. Oh, tell me, Miss Magra, did you know Brian? Yes, I did. He disappeared from the expedition of which we were both members, and he has never been heard of since. That was a year ago, no? Exactly. And that's just why we're going into the Belgian Congo now to look for him. So, you are going to search for Brian Gregory? Yes, and since you knew him, it would be awfully nice having a friend of his with us. I'll go now and speak to Tarzan, and I'll see you in the morning. Good night. Good night, Miss Gregory. Who is it? Who? It's the door. He would have a boom on the board from whom I should take orders. Well, there's only two women here. You must be the one that he meant. And did the other tell you to come to me? He said that you would make yourself known by the word akish. But that is not necessary now. I know that you are the one. So, what about the map? I do not know where it is. But I do. And I've seen it. You have seen it? Yes, just a glimpse. When I went to the hotel this afternoon to get some information from this so-called Tarzan, he was looking at it with the girl under a father. Then Tarzan has it? No, no, the girl. He gave it back to her. Now listen, our job is to get that map. I'll play along with you and help all I can. If you can get it, sing out. Then leave it to Wolf. I think maybe I can handle this job better than you do. You will leave that to my judgment. Remember, you are taking orders from me. All right, all right. Have it your way. Work on the girl. She's got the map. And if you fail, then my way home. Now I'm going. When you want me, give me a sign. When I want your help, I will let you know. Kind of a little spitfire, huh? Well, I like them that way.  And I see that we're going to get on well together. After you know old Helman Wolf, huh? Good night. Hello, Dutchie. Where you been all evening? Oh, just looking around, sweet. Getting acquainted with our party. What's the matter with you? You act nervous, walking up and down. Go to bed like me. Ah, I don't like the smell of things, Larsen. This track we are on, too much secrecy. And this fellow Tarzan, he gets the job I am hired for. Why? He been a good, a fine fellow. Ah, yeah, maybe. But I don't make him a good jungle man. No, sweet. I don't like to set up. I want to know more about where we are going. And why? We know where and why. We go to the upper Congo to look for Mr. Gregory's boy. That's good. Yes, sir. Well, suppose, Larsen, that Gregory's boy is on this boat. On this boat? I don't understand.  Now, suppose young Gregory is here. Suppose he has a treasure map. Suppose I know where that map is. Yes, sir. Suppose I'll let. What next do I suppose? Suppose you and I had that map. Just between us. Now, listen, that paper is important in the port.  And they keep their real purpose undercover. Yes, sure, Dutchie. Well, do you think Ben, their real idea is going up into the Congo? Oh, my God, you blockhead. Shall I draw a picture of it? It must be treasure. Thousands of pounds, maybe hundreds of thousands, and hours for the taking. What do you say? Good treasure, Hunter. And they ain't been going to look for the old man's boy. Hmm, that been interesting, Ulf. Yeah, and here's something else interesting. Tazan is old man Gregory's son. On the stern of the river steamer, Tazan and Dono are listening to Helen Gregory's report of her conversation with Margaret. Well, she claims to have been on safari before and accustomed to jungle travel. And so this young lady now wants to join our party. Oh, a logical reason, I believe, Lieutenant. She must realize that she'll be safer with a large party. Perhaps. Did she say definitely where she is going? Well, she mentioned to Anbarca. But what interests me most is the fact that she knew Brian. Oh, she knows your brother? Yes, and under those circumstances she'll take her with us. I think maybe we should. But Tazan, Margaret with us, the woman who... Yes, Dono. I think it's a good idea to have her with us. She'll be company from Miss Helen. Thank you, Tazan. The fact that you also know her, or at least have met her, as you said last night, makes it more like a family party. And she's very beautiful, Lieutenant. So have heard, Namuselle. Well, good night. I'll see you all at breakfast. Good night, Miss Gregory. So, your friend, Margaret, is aboard. Significant, is it not? And yet, you agree to allow an enemy to join our ranks? I'm not so sure she is my enemy. She tried to help me last night. After enticing you into the trap? That's true, but... Oh, I'd rather have her here with us, where I can watch her. And I'm going to bed. Are you coming? I shall finish my cigarette and follow you. Good night, Tazan. The enemy in our camp, I... Lieutenant Darno. Pardon? Oh, Larson, not in bed yet? No, he got something in my mind. So, what is it? It's at home, Wolfe. Ah, you speak French, huh? You're still a... What about Wolfe? Is there somebody in our party that has a map, a valuable map? A map. Where did you get that? Who told you anything about a map? That fellow Wolfe, he knows all about it. No, I'm not sure. Welcome to the point. Well, I used to, a little while ago, he'd come into our cabin and he'd tell me, Tazan. Hey, Tazan. Wolfe says that he'd been old man, Greg Larson, the fellow we've been looking for. And he tells me about the treasure map Tazan has. Quiet. What was that? By him and he, it'd been a piece of wood. And look, there'd been a piece of...


Welcome back to Scorecats, it's Challenge Shoes A54. Last week we had a human flag challenge which I would say is this week it is Tim's turn to lead on this and it is as head of handstands. We're looking at a frog stand variation all the way up to a handstand and your grades are going to be as follows when Tim demonstrates. What's going to happen guys we're going to go to a frog stand, that's going to be a C grade, we're going to transition into a headstand, B grade, if we can then get into a handstand from there, A grade and for the color to the A star you've got to get all the way back down through the same sequence so it's like a pyramid up and down yeah it's gonna be amazing so I'll give it a go, Jack will talk to the grades, you can see them and then we're going to get this guy have to have a go I'm crying I've got a go I didn't even think of that yes you have because I got obliterated last week by 15 seconds I was like I just said to him off camera so are you alright to demo these because this is hard right okay yeah so C grade frog stand nice B grade puts his head down into a headstand so B grade and then a grade is into a handstand nice and then a star back down to head back down frog and then into his frog nice I'd like to see you hold up frog stand a little bit longer at the end I'm happy with that a star I think yeah give you an A star okay I want a mat for my head yeah let's protect this you remember though when I got that big scar across my head I have previously or a long time ago done into a handstand so I think I could do it I've got a bit of a dicky shoulder so just put that there I've yeah it's been in the locker before are we ready this is gonna this the receivers the weight of it's gonna mess with me as well it's gonna put my balance it's going to put my balance all right so C grade tick all right this is it this is a difficult bit well let the people decide when you give you a B or an L I'm not sure you actually complete yeah I know I can do that maybe another go and another go no so send us we've actually got on Thursday this week we've done a whole video about getting dead strong it's gonna come I can do that how do you get strong so pushing out of that headstand is actually difficult because you get taking down to create momentum movement from us from a part of a dead stop so if you weren't interested in doing that we've got a great video to come out which is gonna help that yep so check out on Thursday this week and we'll put a link in the description below when it's available if you want to subscribe you can click below just down here no no there it is or you can get out that's the free beginner's guide beginner's guide down there guys there's a great content and there we cool a frog stands in there with you starting point yeah and if you want to look at last week's challenge Tuesday number 53 is up there we're gonna go and Jack is gonna have another go because it feels like he's redeeming himself but we won't bore you with that and so we see you next week class dismissed


Hey, how are you doing? I'm good. Okay. There's a partner. He's your home defender. He's my co-presenter, right? Yes. No, I'm good. I'm super excited about what was just delivered the last two days. Amazing how we turned all of this into watch events and now we can't get enough. So let's do this and do a post-it night show. We were supposed to have Anthony also join us and say a few words to start this very special edition of AZ Update. I'm normally behind the scene, but today I am on camera with you. Anthony suddenly dropped to add some technical issues, so we don't know. Maybe he needs help from Patcher, Switch, or Steve, the audio guy. In any case, let's do it when he comes in, he comes in, whatever. As long as he does his next segment. So maybe you had just forgotten to put the jacket on. Maybe not. No, no. So I know you're talking about security. I think Patch and Switch got in again. My laptop completely froze and all these logos of Patch and Switch showed up on the screen and I'm like, what's going on? So I had to reboot and my defender kicked in and cleared it all out, which is awesome. And we're back up and running. So I apologize. We have a nice transition to Defender. There you go. All right. So I'll let you guys take it away. I apologize for interrupting. Okay. So I will be completely serious here that I have not been concentrating or looking at Defender or Microsoft Threat Protection in pretty much anyway, because we've got Oren Thomas on our team, which kind of specializes in the security part to cyber security is actually doing his doctorate in cyber security. So I've kind of left that because there's enough in Azure for all of us to cover. So take me through it. What's Microsoft Threat Protection? What's the value prop and educate me? Of course. So first of all, yes, there is a lot of other tech going on. So I understand. So let's try to summarize this. So at Ignite, we announced our new rebranding. So entering a specific new market, which is a XDR market, we also aligned our products to this. So we have now Microsoft Defender, which is Microsoft's XDR solution. And it is composed of Microsoft 365 Defender, as well as Azure Defender. So those are also two new names. So Microsoft 365 Defender was formerly known as Microsoft Threat Protection, and Azure Defender was formerly the Cloud Workload Protection of Azure Security Center. So those two components now make Microsoft Defender. Is there a chart somewhere that show where old products and why and the new names and so that we don't confuse everyone like I'm confused now? That is OK with you. And then I prepared that. Oh, OK. I didn't know, but that's a great lead-in, almost like we know what we're doing. So let me go and share this guy with you. So can you see this? Yes, we can. Wonderful. So this is kind of the entire Microsoft or Threat Protection by Microsoft. So we have, of course, in the center on all of this is our AI machine learning fused by all the thousands of Microsoft's researchers that we have in our company. And then in order to help customers to be protected as well as prevent attacks in the first place, we have these two solutions. We have Azure Sentinel and we have Microsoft Defender. And I will go again into Microsoft Defender in a bit. But because of the full picture, I want to include Azure Sentinel. Azure Sentinel was announced, I think maybe a year ago or like no earlier this year, I guess, at RSA is our SIEM solution. It helps customers to get all the events and alerts into a single place. And even though this talk is not about Azure Sentinel, just quickly spend a minute and go into the details. So Azure Sentinel is a cloud native SIEM. It's not something that we built before and on-premise and then reported it in the cloud. It was built for such a big scale, like lots of data, any data that you want. Of course, it has then all the machine learning AI to help to immediately get time to value and then also any data that you think. It's like we have a lot of connectors. We even announced many more connectors now here at the Ignite conference. And it helps customers to do hunting and have a single place for Microsoft alerts, but also third party events, firewalls, routers, whatever is there. So and then Microsoft Defender, the XTR solution helps to protect the identities, devices, data, infrastructure, apps and networks and in details, this is what it is. So we have a cross-domain protection. We used to have Microsoft threat protection and Azure Security Center and those are the new names. So if you look at what that is, that is a lot. So we have identities. We have cloud apps. We have data and email and all of this. And I want to go into the old name, new name that you asked for. We have announced also new names for all the individual pieces that are part of Microsoft 365 Defender. So we used to have Azure Advanced Threat Protection. It's now Microsoft Defender for Identity. Microsoft Defender ATP is now Microsoft Defender for Endpoint. And Microsoft, what was it? Office 365 ATP, I think there's a typo in the slide. Office 365 ATP is now Microsoft Defender for Office 365. Okay. So I'm not the only one that's confused. No. And it's still, you know, we just announced it a couple of days ago. It's very hard to really already speak the new name. So if I still say MD ATP, then it's MSDE, like Microsoft Defender for Endpoint. We'll put that into our own user directory and we'll make the switch. Yes, yes. And you will see, I mean, I'm hopping into a demo probably shortly. And you will see that, of course, also in the products themselves, it will take a while to reflect all the name changes. It's easier to do this on a marketing slide than actually in the code of all the individual products. Well, you mean it's not just a search and replace? No. I tried this in our internal Wiki and no, that didn't even work there. So, okay. So did this clarify a little bit about the names? Yes, absolutely. Wonderful. So, and now what is Microsoft 365 Defender, formerly known Microsoft Threat Protection? It's our automated cross-domain security. What that means is, you know, if you look at the Threat landscape today, we have many point solutions. We have something that helps customers to find, I don't know, feature, like protect against phishing or spot user anomalies or endpoint activities. And then they get, because the tools are actually great, so they get more alerts and more signals and the customers are just struggling to put all of these pieces together. So with Microsoft 365 Defender, we actually do exactly that. We correlate events and alerts across those multiple domains and bring them into a nice incident, a nice story to tell customers what exactly happened. We also do automation across those domains. So if I see something suspicious on an endpoint and it was triggered by a user, I can go and clean the user in Microsoft Defender for Identity. So automation also goes and cleans up across those domains. You mentioned one word here that kind of stuck with me. Maybe it's my old ITIL background, but you mentioned incident. So does the system make a distinction between events, problems and incidents? So I think, yeah, so we make the distinction. So I think the tiniest item is an event that we pick up, that we collect from those individual sources. And individual events are being correlated with our tech in the background or on the client and they turn if this is something suspicious, malicious, into an alert. And then alerts are being now correlated amongst each other to then build an incident. And then incident is something that a security persona should probably focus on. Open the incident and within the incident, there's all the individual alerts that belong to this one incident. Oh, perfect. And then if you go and investigate one alert a little bit deeper, you might actually end up going on an endpoint timeline or a user timeline. And then you actually see all the individual events that were around the timeline on the time where the alert was raised. So the system will help the security professionals in any enterprise to be able to follow the breadcrumbs instead of having to hunt all over a series of logs and events in order to just see what's relevant to this incident. Yeah. So why don't we just have a look at that? Perfect. So what you can see here is the list of incidents. And you can see various columns here. And one of the columns says alerts. You can see that how many alerts are active and how many alerts are in there at all. So of course, this is a demo tenant and we turned off automation in multiple cases just that we actually have something to see and to look at and not everything is clean. So what you also can see is there is, for instance, multiple alerts and from multiple entities. And this is what I was talking about. We have devices, we have users, we have mailboxes. And if I actually click on one of those incidents, you can see a nice summary. Let me actually make this a little smaller so that we can see something. So the summary gives you a great overview of, first of all, what are all the individual mitre attack tactics that have been used in this specific incident? You can see the timeline. You can see the scope. It immediately tells you how big this incident is for your organization, how many devices, how many users, and how many mailboxes are part of this incident. And then you can go through the individual tabs that show you all the individual alerts and all the devices, and I will go over this in a moment. So but also because some of our customers, they might have only one solution that is part of the Microsoft 365 Defender solution, let's say they have Microsoft Defender for Office 365. We also invite those customers to come over to use the security.microsoft.com security center because they get all this extra value as well. So they also have incidents now. Even if they only contain Office alerts, it's still something that they don't have in there, let's call it Old World. And sometimes you might have an incident that is only if you have, let's say, a fishing campaign, a good one, meaning the attacker is really good. You have hundreds of alerts just because of one email. You have them all in one incident and you see the scope right away and you're not flooded with figuring out whether the other alerts all in my tools. Yeah, because we keep telling the users if you don't trust the source of the email, don't click you did not win a Best Buy or an Amazon card that just doesn't happen in email. But it's interesting to click on it anyways. I need to tell you a little quick side story here. So in order to onboard the devices to the service, you can of course do this with management tools like Microsoft Endpoint Manager, System Center Config Manager, but there's also a script that you can just double click for local, for smaller, usually POC environments. And a CISO once in one of my EBCs was saying like, oh, that's cool. So I will just send this via email to all of my employees and we are onboarded within five minutes because everybody is clicking on everything that they're getting. That was funny. It's not funny when they get hacked though, but I know, I know. So okay, back to this view. So we have all these individual alerts, like list of alerts we have even here, you can see that there's two alerts that are again grouped. So we really help to narrate the story and make it as easy as possible to understand all the devices, user mailboxes, and I want to move over to investigations. So investigations is another feature of Microsoft 365 Defender, which helps as I mentioned before to clean up the devices or the users or the mailboxes with any kind of malicious activity or evidence that's there. Of course, user meaning reset the password or turn on multi-factor authentication, these kinds of things or devices, it's malware or some changes that one made in the registry. And automation comes in two flavors. It's semi-automated, which usually most of the customers start semi-automated to see how everything works and we investigate the incident and we provide a remediation package and then the security operator has to approve before the remediation is being done. Okay, so there is a human gate there to prove. Exactly, yes. And then there's also the fully automated which is it's done entirely automated. And of course, we give enough freedom and customization so you can put your endpoints in the group fully automated, but then you might have some servers that you put in the semi-automated or user groups and so on. So there is flexibility that then fits any organization's needs. Yeah, oh, so that's kind of cool. Yes, and we see more and more customers actually going into the fully automated because they don't want to wait for a human to first have to approve if you have some shit happening there on your end. Well, if the alert comes up, if the incident comes up, let's say on Friday night at 10 o'clock and you don't want to have to wait till Monday morning in order to address it. You just want it cleaned and the user accounts locked and changed. Exactly, and there is also a it's called the action center where we lock all the activities that have been done by the automation and you can go and reward something that you think wasn't the appropriate step to do. So everything that was found is in the evidence tab. You can see all the entity types, what was suspicious, what has been remediated, what is left and so on. All this one thing in an incident. One question about the evidence. Does it actually keep like a copy of the email that had the malware in it? Or does it just keep a link to it? How does that work? No, it's always in quarantine and everything can be reviewed by a real human in the end. And this is actually the usually when we talk about automation, I wanted to bring this in and now that I mentioned humans. So automation is not just, oh, there is something suspicious. Let's isolate the machine. This is really mimicking the ideal steps that a security analyst would do in order to remediate this or investigate and then remediate the threat. There is a lot of intelligence and every time we get an answer, we might have a new question. So for instance, oh, how did this file get here? And it's like, oh, it was downloaded from this IP address. So who else access this IP address? Is this IP address associated with an activity group? What and so on. There's tons of questions that we keep asking until we really clean this out. Okay, so there is really the wealth of the security center and the AI that collects all that information in our cybersecurity groups that all that knowledge is kind of rolled into that tool. Yes, yes.  So another thing that I would like to show is advanced hunting. This is also a unique new capability for Microsoft Defender for Office 365 users going to this portal as well as for Microsoft Defender for Identity. Microsoft Defender for Endpoint users, they already had advanced hunting before. So but now if they use Microsoft 365 Defender portal, they can hunt across all those individual domains. So advanced hunting is a KQL query language. It's rich. You can now specify queries for instance, hey, show me all devices that have some vulnerabilities not fixed and a user with admin rights has been logged in. So this is huge. This is rich. So I'm combining the user information with the device information to do my hunting. So you can see all the individual schemers. We have apps and identities. We have the email data, events, attachment info, delivery events, devices, threatened vulnerability data. And then because, you know, it's all about community, we have a GitHub repository where people upload their great queries that they think would be beneficial for other users. And I want to ask everyone who's watching and listening. So if you want to contribute, please do. The community is only as good as their members are. And then you can also, of course, save those queries and share them only with your team. So I am going to do a suggested MTP one, which is here, a log on after a malicious email was received. So see again, I'm combining endpoint log ins with something that happened in an email. This is amazing, like hunting across those domains. And then I can run this query and wait and see that there is, I think there's one event that comes back in a moment. That is really cool because I remember back in my days, we're having to go through hunting all of those logs, you would find something and then you'd have to start over because you're looking at the second part of that equation or like the user, oh, we got this, but who's accessed it? And then, but now you can do this all in one query. All in one query. And the beauty about these queries is also that you can now actually save them. That's what we already did, but also create a detection rule. So, okay, and in this case, some of the properties are missing. But what is a detection rule? A detection rule is turning my own threat intel or my own query into alerts or like detections, custom IOCs, custom indicator of compromise. So I can say next time, every time someone logs on after a malicious email was received, I want to have an alert. I don't want to go and hunt again manually with the query. I want to have an alert raised into my system. So this is amazing. So it grows with you as you discover things and as you set things up, that knowledge stays within the system and then it'll start telling you without you having to ask for the info. That's great. Yes. So we looked at incidents. We looked at automation. We are self-healing. We looked at advanced hunting. One thing that I think is also very unique to Microsoft is we not only help show you the incidents and give you automation. We also help you contain threats by integrating with Microsoft Endpoint Manager or Azure Active Directory when it comes to conditional access. You probably know this technology already for a little while, but if there is something malicious with a user suspicious, if there is something suspicious happening on an endpoint, we raise an alert. Right. And now the alert has a severity and the severity will also tell how risky this device is. And if the device has a high risk, you can say this device is not compliant anymore and this device cannot access corporate resources until the threat is gone. And because the alert was raised, the risk level was high, we do the automation, we clean the alert, we close the alert, then the risk level is set to low again and the user can access. So it should work in, I don't know, let's say 10 minutes, 15 minutes, that there was something suspicious. The user was, the threat was contained. The user could still be productive, not access corporate resources. The threat was remediated and then the user can keep working even with corporate data again. This is amazing. This is wonderful. I'm thinking, man, I wish I had another hour, but we have Anthony and his panel that are going to be joining in a minute or so. People want more information, where do they go? So I would say, let's go to aka.ms-ms365D, which is the product website and you will find additional resources over there. And then of course, follow me on Twitter at Heike Ritter. And there's always some new stuff that I'm sharing via my Twitter account. That's the two things. This is wonderful. And I'm so glad that we invited you again to cover this, because really, when I looked at your 15 minutes during Ignite, it gave me the, like, I want to know more about this. And now you've given me enough to understand what I don't know. You were just saying you want more time. I want more time, but now I'm going to take that time and actually go and try it out on my own and look at it in my test description and see what I can see whether or not I'm vulnerable. Okay. Do this. Let me know. I probably am, because it's the test subscription. All right. Well, thank you so much, Heike, for spending the time with us. And I hope you have a great post Ignite. Hopefully an uneventful move to your new house. And thank you. Thanks for having me again. It was great to see you and Anthony. Thanks everyone for doing this. Thanks. Cheers. Thanks, Heike, for joining us.