Yes, okay, so I'm going to be talking about open source brain at the moment and it's been mentioned a few times already So I'll hopefully skip over some of the introductions But basically that yeah the motivation for this is very similar to the motivation for a lot of other initiatives We really want to make computational newer science more scientific more rigorous and the ways We've identified to actually try to do this or the shortcomings is the problems with ood Reproducibility there's models out there code is out there But it would be very good if you could actually reproduce in full or reproduce in your system of your choice The results from that paper and it's not necessarily always the case even if you've got the Fortran code sitting there Accessibility it's not just computational neuroscientists. We want to have looking at these models and improving them We also want to make them accessible to theoretical experimental neuroscientists Portability everybody uses their own simulator. Maybe rebuilds the simulator. It would be good if you weren't limited to the format that's the original model was built in and Transparency Ideally for really complex models you need to be able to drill down to the specifics of that and that shouldn't involve opening up a text editor and reading Thousands of lines of code so we want to make some kind of way to expose these internal physiological properties of models and make them Open to critical evaluation. So open source brain repository. It's online. It's at open source brain org A bit of background for this. It's been around for probably just over five years. It's been funded by the Welcome Trust generously and The key aim of this is to have an open source model development repository specifically for computational neuroscience What it actually consists of is a database of well tested spiking neuron and network models in standardized formats now We're concentrating on spiking Neuron models simply because that's what we know most about But a lot of the processes we use a lot of the tools we use are applicable for any other types of Neuronal modeling like neural mass models and we have some base initial interactions with some people from those fields as well But the key thing we're trying to do is allow anyone to come along comment on extend reuse the models That we have on this and really build a collaboration platform. So not just the people who've Provided the models put the scripts up there and you ask them questions But anybody can come along if it's interesting for the community. They can contribute to it They can make it better. They can document it And we want to use the the best way to actually do this It's to use the best tools and practices that you've just heard about fraud that have been developed and are very successful in Open source software development. So what types of models do we actually have already an open source brain? We've a number of models cell and network models from the New York cortex thalamus I won't go to these in great detail Cerebellum mainly because we're interested in that in the silver lab Hippocampus, but also some classic models like the Prince and murder Paloac pacemaker network some more abstract neural networks examples fits Unigumo is a cave itch and also linking to ongoing projects like open worm Which is also available on open source brain org so for these models here these model types They're available on model DB. You can download most of these and run them in the particular simulator They were developed in so what's the advantage for actually developing these further on? Open source brain so to give an example of this Give an example of the 2005 paper by Roger Traub and colleagues. This was a very detailed model at 14 different cell types a single column Thalamocortical network model 14 different cell types multi-compartmental neurons each of these had distinct distributions of ion channels and showed a number of properties of Thalamocortical networks, but one of the issues with this it was very good It was very well described in the paper, but and you could download code It was open source, but it was about 20,000 lines of Fortran code and not very many people Even the authors on the paper had actually used this code But this was interesting for a number of different people and a number of groups over the years have taken this taken on board to Try to convert this to other formats. So what you actually have on open source brain now is a Project page corresponding to this model for a Thalamocortical network model And on here you get a list of the various people. There's groups in Poland in India Michael Heinz and the Neuron has also worked extensively on this people who are interested in this model and are interested in making it more accessible And moving it forward you also get a link here to the original model code on Model eB and a warning that's in Fortran But what you also get is a link for each of these projects on open source brain to a github repository now Hopefully I don't have to say too much about github, but the basic idea here is that it's an open source code sharing website and Corresponding to this you have a number of different versions of this model here the original Fortran code a version that's been converted to Moose and Neuron and neuro construct version which contains Neuroml and The people who are interested in this have contributed these various different pieces of code and the great thing about github is you can Actually see all the history of who has actually worked on this the various different versions of this and you can also Find out who's making the most contributions to this making the most useful contributions and You associate with each of these commits you have some comments and for branches as well I mean as an example here if you could read this it says version which works on my computer now This is very valuable information if you find that original code You're looking through the Fortran and you actually say oh, it's actually Helena who's here Has actually at one point got the code to work on her computer Which is a very very useful information rather than just getting a zip file and trying to run it yourself on your computer So it is the whole idea of collaboration and also assigning credit for the various people who are working on this And so associate also with the projects on open source brain. There's a wiki. So here in this model Roger Trapp himself admitted in the paper that it's very preliminary But there is a place where people can come and discuss the various limitations with the models some of the difficulties installing it but also the physiological properties of the model and you also actually get a here a form in this example here I believe Helena again has Try to reproduce the some of the figures from the paper in the in the slightly updated Fortran and in her version of Neuron so again, this is making the model more accessible proving What it can actually do and you can actually see what people have done with it here So it's a way for groups to get together interested in specific areas and to move interesting models forward And all in open source, but obviously if you have five different versions of the model in different simulators That's not necessarily best. Maybe somebody fixes a bug in one of them improves it in one So what you actually need is a common format that you can express models like this which can then be mapped to the simulators of choice for different people So that's as you've heard mentioned of already what's enabled by neuro ML So hopefully most of you have heard of this before but it's a standardized language for model descriptions in computational neuroscience The most stable version of this has concentrated on detailed neuronal morphologies ion channel synapses and 3d network structure the types of computational multi-compartmental models that have been traditionally built on neuron and Genesis And over the years There's about 30 over 30 different simulators applications databases have added support for neuro ML in some form or other So here's just a few of them here So you have the kind of traditional neuronal simulators like neuron Genesis and moose, but you also have databases like neuromorpho There's about seven or eight thousand cells on neuromorpho They can download in your ML format channel PD You can also download from the blue brain project a lot of these ion channels in Neuromorph format other tools for maybe generating neuronal morphologies CX 3d There's a version of this you can generate a network in 3d Exported to neuron and there's a number of other tools and initiatives here which are using various forms of this So as I mentioned, it's Being used as a common format for exchanging between these applications, but one of the limitations That was present in the version one of neuro ML was that it was very focused on multi-compartmental Hodgkin-Huxley based Models so what we really wanted to do for version two was to try to make it more extensible so that you can build new model types Maybe more abstract models on top of this language and And as an example of the type of model we want to try to incorporate in version two this Bretton Gershner Model of adaptive exponential integrate and fire cell. It's just two ODE's But by changing some of the parameters in this model, you can reproduce quite similar to the ease of Gavitch model you can reproduce a lot of different spiking behaviors of Neurons from multiple brain regions So this would be great to get into a neural mal 2 in neural one What we would have had to do with to be update the specification update each of the individual implementations But what we have in version 2 and I won't go through this in any great detail is a language that we're calling lens which Where you can actually specify these differential equations here in a machine readable format unambiguously and then for Neuron the new amount corresponding neural to element you just specify which parameters it points back to the definition of this in lens And so in this way you get a full machine readable Implementation of that model and then this can be used to generate code for multiple different simulators So we can map this to math lab XP P neuron and so on And so when somebody comes up with a new type of neuron model that they'd like to Support in the format all you do is implement this in this language here, and it's convertible to other formats like 9ml as well And in this way the language can be extensible. So we have in the current version of Neuromal, Neuromal 2 the third beta release is just about to be released Hierarchy of these elements so for describing cell models describing synapse models and other inputs like voltage clamps and so on Behind the scenes for all of these there's a machine readable description, and if the language gets extended with a new Synapse type you can just go to the description, and then it should be supported in all of the Simulators which can support lens which can read this and convert it to the new format So that's what we're trying to do for Neuromal and the idea is with open source brain That's if you get your model into this format all the possibilities which are opened up through having it in this machine readable format And all the cogeneration possibilities will be open to all of these models. So you can list an open source brain Lots of these models is about 80 70 or 80 different models in different stages of development and curation But for each of these you can see where it is with the current level of support for example In neuron and genesis how well it's supported in whether it's supported in Neuromal 2 and what we really want to do is fill Out this as much as possible So for models that aren't covered in Neuromal Just extend the language build support new types in there But also actually we've developed a testing framework for each of these So what we want to do is not just say yes, you can download this and it will run in Neuron to actually have software tests which Look at this generate the download the simulator run the model in that particular simulator Test that it actually is identical to what you're predicting and then if you follow these links here You actually get a log of which version of software we choose which version of the model what it actually did So that if you come back to it in two years time, you know that it has worked So this is slightly different testing that Rick will talk about later It's more software testing that it actually does what you're expecting it to do Okay So just to give one or two more examples of types of models that are on Open source brain you all have heard of the easy cave it's spiking neuron model and this again we produce multiple different types of behavior for Simple in a simple neuron model This was has been for a long time available in MATLAB from easy cave it's website But now there's a open source brain repository with a version on pine So not only Neuromel a lot of the models that we are supporting there are well expressed or available in pine Which is Python based multi? simulator language for expressing neuronal models and also Neuromel format and You can actually go to the wiki associated with this and there's a brief explanation of some minor parameter changes Which were needed in the from the original MATLAB code to get this to run properly on Neuromel and Pine and this work was actually completed in 2013 by a as part of the Google summer of code by a Brazilian student Victor shoud and Yeah, so basically there's a record now that I'm sure multiple different students have Found when they download that MATLAB code, maybe they have to make some minor modifications But now there's a place that people can actually check through this and maybe add support for a new simulator or Comment again on that particular piece of code. So for This year as well there's a Google summer of code students looking at network models of v1 and this student Ramon Martinez has actually identified some classic papers some classic models of Orientation selection in Orientation selection in v1 and The code for these models hasn't actually been available But what he's done is read the paper and implemented this in a set of pine scripts So now if you follow the github repository for this you find a nice clean set of Scripts in pine which reproduce some of the figures from those papers and can be reused for other models of v1 and again the good thing about this is that Ramon's name will be all over these codes here. So if somebody does Take those develop new models. That's good credit will be given to the people who've actually Developed these scripts so while converting an old Paper into pine doesn't necessarily get you a publication. It does get you exposure for Whoever uses that further down the line. Okay, so that's great that you have Models in Neuromell and pine so if it runs and does exactly the same as the original version What is the actual advantage of converting it to there and the big advantage as you've seen already is that once we know? What's actually in that github repository on open source brain itself we can pull that in and extract that information out of it Which would be much more difficult if it was in C++ or neuron or so on so here's an example of what we do there's a open source brain project for the Peking you sell from the shitter and Bauer and We have a 3d visualizer on open source brain that you've seen a little bit of already Which has pulled in that neuron mouth file from the github repository and you can visualize this inside your browser As long as your browser supports webgl you'll be able to use this even on your mobile phone and Since there's information in this file as well about the locations of the iron channels So for example potassium and sodium channels where it's actually located in the soma or the thick dendrite or even the leak Conductions and it varies over the The dendritic tree here all this information can be pulled out and presented in your browser without having to install any software Or anything else and the only requirement on the repository developer is that they put it in there in compliant Neuromell So show another example of this. This is the trap network model, which has also been converted to Neuromell and this is just a 300 cell 10% of the full network Which is again being visualized on OSB and you can see the structure of the model as we have it in 3d The different cell types that are actually present in there. You can go in look at the overall structure Maybe click on one of the cells and then see okay, which cell type this is this is layer 5 tufted pyramidal cell and just make this Very complex model much more accessible to people who would never actually install Neuron or know what to do with the Fortran code and Make it easier for people to comment on this to say well this particular cell type is missing or if you click on a cell and say well, there's actually IH present on a different location What we really want to do is lower the boundary lower the barriers to actually Accessibility and use of these models So I've mentioned well we've heard already about open worm and this example here Really demonstrates the advantages for both OSB and open worm that we have a nice model to actually show an open source brain And we can visualize this in 3d as we can see But the big advantage of this is that all the code for this is shared is publicly available So the elements that we're using for this visualizer here are actually shared with the open worm community So if there's improvements made there to this visualization capability, we benefit from that and he Extra things we implement for parsing Neuromel models can be reused by them also and just given a quick example of that Stephen has mentioned Jepetto and we have started a more up-to-date Model of C elegans, which is fully specified in Neuromel. These are actually just integrate and fire Neuron models It's just showing the somas here of these models But the new features we're trying to build into the OSB visualizer and into Jepetto is actually simulating The model inside the browser. So this is Jepetto has loaded up a Neuromel File containing a description an integrate and fire network for this model And you can actually press start and what you can actually see is activity in each of these neurons In the browser, you can see some of the cells start to light up there but basically The components behind the scenes for running this model are in Neuromel We're developing those the components for visualizing this are being updated by the open worm people And none of this would have been possible unless we're both sharing our code sharing all the models working on the areas that we have expertise in and then putting online and Enabling the community to come along and use these tools. Okay, so just to wrap up those elements that I've shown are really Trying to address these really important issues of reproducibility accessibility to computational and non computational people portable ability across different simulators and transparency being able to drill down into the models very complex models and Get comments and feedback and input from as many different people as possible So we have quite a number of people signed up and nearly 300 members 43 different research groups in open source brain org at 80 different projects and various levels of Conversion to Neuromel and pine and They just point out again This is very big button on the home page here sign up everybody here and anyone else in the community is very welcome to come along Put up whatever kind of models you want and github you have complete control of your github repository if you support Neuromel and pine We will do as many interesting things as we can with it and publicize it on the website and we really want to build a community about this and improve models improve accessibility of What you're doing with those and basically build better more scientific models So finally just to acknowledge a number of people here not just in silver lab But a lot of our collaborators that we work with very close work with the open worm project Neuromel community and support from the UK and CF node and of course welcome trust. So thank you any questions for pouring Thank you very much. I was wondering. Can you make a comment regarding 9 ml? I mean because I was wondering I mean obviously they're sort of especially in the context of ICF I mean there was there was an additional development and do you see that this is now converging or sort of how How can it more is happening now? I think with 9 ml There are some updates to the repository there for us Lemms is roughly the equivalent to what 9 ml the new features that 9 ml enables We do actually have as part of our import and export features you can actually most of those models there you can Attempt to export them into 9 ml. So if there is a simulator which only supports 9 ml We can export valid 9 ml out from a Neuromel description into that format and hopefully load it up into another simulator It's not complete. It needs testing. But again, there's a file there 9 ml writer which anybody can update and make sure that it's valid We do want to have a greater compatibility with these but we do think well We're biased but we do think there's some features in lens that you need like the hierarchical expression and extension that Are there at the moment in limbs that could be imported into 9 ml as well But the key thing we want to do is just make sure they're compatible and open and yeah, so Yeah, very nice talk. Thank you So you talked about the value of being able to convert your model from like one simulator to another Did you have any interest in trying to convert one model from a different? Neuron model to another so for example, I had a student who Who tried to take I don't think it was one of the models you showed it was a Ruben internment model from like I don't know 10 years ago and they'd they'd done it in Some sort of Hodgkin-Huxley type simulator and we try to convert it to an Izzy Kevich model, okay And you know hijinks ensued as it sort of half worked But I mean is that the kind of is that something that would be of potential interest to try different Realizations of of the same. Yeah, I mean in theory somebody could I mean supporting Neuron L you could potentially Develop a a tool a library which reads in any Neuron L model and you say right try to reproduce This behavior in a different type of Neuron L model I mean it's conceivable that you could do that you'd have to re-optimize your model according to those parameters, but What Neuron L actually provides is the input for a Hodgkin-Huxley model the output Izzy Kevich this bit in the middle for how You would actually do that is not necessarily something that Neuron L solves, but it might enable you I mean the other scenario is that you just create a github repository saying converting hh models into Izzy Kevich and then Put it up there put some examples up there send an email and hopefully somebody will help you doing that I mean it's a it's not a difficult not an incredibly difficult problem, but it's an interesting approach to take And there are probably some people out there who might want to contribute to this. So but yeah, yeah I Think at one point I've heard I heard it discussed that there was going to be or there was some work on a high High resolution or high density network model or network serialization That would not be XML is do you have any updates on that? There is a library called Libneur ML which was in the two I didn't mention, but it was in the 2012 I NCF Google summer of code and thank you again I NCF which was developed by Mike fella which does Support much larger. It doesn't require you to save your morphologies into XML every time and read it back in it does use a Mongo database for a serialized a more efficient serial More efficient serial the serialization of the model It has some options for saving that to HDF 5 as well, but it's Neuromal compliant So you can load up a neural model or regenerate a neural model and say save it into one of these other formats Which should be much faster to read and write or more compact and then load it back up again And because you're using an API you just deal with the same neural elements This has been out there. It's published. It's open and I believe it's still it does still work So that might be something to look in but there's definitely a lot more that can be done with Making the for example the HDF 5 much more efficient and The the formats you actually save it in you don't necessarily need to save all the XML strings You could save a much more compact representation of that for reading in and reading out But as long as you have an object model maybe defined by Neuromal that you can handle then you don't really care How it's actually saved in


I'm positive about Three things that you're positive about excited about Okay Let me see I'm excited to finally see a new bond movie after all these years I'm excited to see what Daniel Craig will give us in his final bond movie his final outing Will it be better than the final outings of brass and Connery and more That's a good point, you know, because they all have pretty weak. Well, it's debatable, but pretty weak Ends of their two news I'm excited about Anna de Armas for seven minutes of screen time probably Yeah And just in general I'm just hoping for That it exceeds my expectations because you know, we're both we're thinking After all these years, we're gonna see an average bond film We're hoping for more It will be quantum, which I think isn't too hard And specter, I like more than you but I still think they could beat that as well In lots of areas. So yeah and I would like to add Action I think the action is going to be Pretty pretty darn good Yeah, I'm like, you know everything like we've seen in the trailers and everything All those like stunts the bridge the motorcycle all that I think that's going to be um I think it's going to be a pretty exciting action Yeah Yeah, if we sum it up like what are the action scenes going to be In this movie, I think a lot of large part of what we've seen in the trailers are all the idli stuff Which I still maintain is probably the pre title sequence like all the idli stuff The pre titles or like the start it seems like a lot's going on In the idli So, I don't know. Yeah, who knows. Maybe it's not the pre title sequence. I just have a feeling It's at least like maybe the beginning of the film like the first half hour or so Yeah I wouldn't be surprised if the pre titles is like uh, uh, no me's mission or something because I remember seeing like the shot of um A building somebody yeah going down a building or like this cooperation with these with these black ops kind of Yeah, yeah, so it's that seemed like kind of an isolated Incident scene or something that's taken place far away from bond Yeah But I'm just who know I'm just guessing because like what would be the other pre pre pre titles like him sitting on the beach Would it be with bond looking at yeah Yeah, my feeling has always been it um because we saw bond drive off with madeline We're gonna see him With madeline at the start and since we we only really see him in action with madeline Uh in italy. Well, well also in norway. I don't know now But I think and I just have such a feeling it starts there like he's gonna he's gonna end up losing her there Somehow maybe in the db5 fighting with all the other bad guys And you know it moves into the titles and an after the titles madeline's gone and you know, we maybe we do a time skip Bond yeah in his hut. Yeah Yeah, I was thinking that Another action scene It's like in the woods They're in the woods. It seems like um I don't know. He's he's being chased by a truck or something. Yeah, because I think that's all the norway sequences Yeah, like that that stuff looked pretty darn cool Like I saw like he he dives out of the way the truck goes like whipping past him like you know flying past him I agree the the action it looks promising enough There is there is a lot in there because if you look at skyfall Which we both I think maintain as one of the strongest bond movies certainly one of craig's strongest But the skyfall doesn't necessarily have a lot of set piece action scenes. Yeah, that's what I always said. Yeah And this one it does seem to have a lot You know to me that the bridge jump comes to mind which they now shown in the Extended scene as well the little 47 clip they show it looks good, you know cinematography looks great The jump looks looks very real um I love the db5 stuff with the the gatlin guns coming out. That's something different And the jump with the bike also in a that looks really cool. Yeah. Yeah, that's another another set piece We can expect We talked about mission impossible before like how that turned into the big action franchise these days Do you do you think no time to die can compete with? Because it's coming out in the same year with the late we haven't seen anything about mission impossible seven But assuming it's going to be on the greater level of the previous Three or two like fallout and rogue nation were really good You think we can compete with them I don't think like the Like craigs bond films like Remember in the past like they used to have this huge signature stunt in a film like even going back to like Golden gun like, you know, the corkscrew jump That are flipping and stuff.  It's just I don't think it's as It's not on the the scale that mission impossible is doing where they say, okay It's almost like the those mission impossible movies promote themselves based around the one stunt Like okay much cruise uh beyond the tallest building in the world We're uh hanging off the the plane like you don't see that with bond anymore like it's it's not Maybe because like the like craig isn't he's not he's not as crazy as cruise who's going to be doing like You know put himself in these situations or who is though who is of course, you know Yes stuff the stuff cruises doing with with these movies like fallout the We've talked about this before probably but it blew me away like this like he took like 2 000 hours of helicopter lessons on the side Just to be able to fly the helicopter by himself through the Yeah, the mountains near the climax of Fallout like he was actually hanging under the helicopter. He did the the halo jump himself Like that the cameraman is in the sky filming and all that stuff is really cruise jumping out and stuff If you have an actor like that, who's that committed? I mean, it's kind of hard to To to compete you might as well just no contest. Yeah, you might as well just do your own thing and let him like, okay Because like imagine like the next bond actor like he's They wouldn't put it in the contract saying okay, you're gonna have to do this life and death stunt You need one of these movies Yeah, would anybody even sign that the cruise is so So so nutty and enthusiastic to do this stuff like yeah He's the producer on those those movies. Anyway, I know and he's pushing 62 and the guy still looks so fit Like we're all talking about craig getting old and stuff Cruises has been doing this since 97 no 96 96 the first mission impossible And and he's still you know the latest the latest one was What was it 2018? Uh, and they're still they're still doing it and and he's gonna do seven God knows if he's also doing number eight But I think with with mission impossible if we delve into this subject that once cruise is done when he's really truly too old god knows when that's gonna be but They're probably not gonna cast a new even hunt They're probably just gonna go with a new lead character of the mission impossible series like a different Different guy and then maybe even hunt will show up in a cameo. I think that's what they're gonna do It seemed like they they were ready to Jeremy renner seemed like they were grooming him for like I think that was the plan with ghost protocol originally Yeah, he was gonna take over Yeah, and then I guess cruises just got too excited to keep doing it a fair point, you know the the stuff sells especially the The latest movies they're they're doing a great job So the question is between mission the new mission impossible movie Um, I don't think we got a title for it, but mission. No, it's just mission impossible seven Okay, and that's coming out.  Yeah. Yeah, it's gotta be bond because You know, I'm not crazy enough to jump into a plane Go to london Book a hotel and see the new mission impossible movie and with bond it's just you know, we're in this fandom and And to me it feels like a certain loyalty that you know, I have to go see this regardless You know, I have to see the new bond movie But if you ask me which one I'm more confident in Doing good and which one are you more confident in actually? You know really blowing us away action wise I haven't seen a trailer of mission impossible seven yet I would probably pick that based on how good the previous one was for I did see one stunt. They were filming for mission impossible seven They're doing a really really big ramp over Into the abyss and cruise drives. Yeah Crew drives a motorcycle right off into the abyss into a town also in norway. I believe or something I'm not sure but it's another one of those typical insane cruise jumps. So Once again action wise that looks more promising But if I if I only get to see one, you know, it's gotta be bond. Isn't it? We've waited so long Between like like we saw that no time to die like that that one motorcycle jump in that trailer In no time to die I guess in italy like we see the guy go straight up and everything Do you think this cruise motorcycle jump in the next mission impossible? Is gonna just like, you know, blow it out of the water with this that's that this ramp If you put those two next to each other Based on what I've seen in the behind the scenes footage of the jump cruise that Yeah, it is gonna blow that jump out of the water, but I'm not sure That's a good point. They're bound to be compared now Even though no time that I was filmed like three years before that probably but Since they're releasing in the same period Yeah Yeah, I know that cruise is gonna definitely beat that it's the same with um when specter was released That was two mission impossible movies ago already rogue nation. They were also so similar also in plot Which one's gonna be the bigger hit?  Yeah Which I wish it turned around because if you look at Bond and mission impossible competing Like the first one 96, you know going up against tomorrow never dies and golden eye That was not necessarily an action movie that much the big set set piece was cruise hanging down from the from the rope and you know Golden eye and tomorrow never dies were really action packed. They could stand on their own The second one was terrible It the rules and enough was much better um Not as not as horrible as diner today though but Number three was pretty good But that came out in the same year as casino real again bond one in my opinion casino real is much more complete much more Of an actual bomb movie Though I really like mission impossible free as well having seen it recently again But then from number four onwards ghost protocol and skyfall boat really good rogue nation It blew specter out of the water Also the same year then they got fallout Which didn't even have to compete with a bomb movie because we had nothing and now it's this one competing with no time to die so Yeah, it's like the mission possible series slowly took over Because I felt the bond ones were always the better ones in the early days, but now it's turned around I think it's funny certainly action wise They how how back in the in the 60s when they had like the big spy craze They'd have the james bond, you know connery's bond movies come out and like they'd have all these imitators these low rent like, you know, uh chintzy Cheap spy movies that like they're trying to like cash in on on the bond craze Yeah, like they were including mission impossible that spawned from bond, you know, well, yeah the tv show But like they would have like, you know these cheaper movies these knockoff movies You know the liquidator and stuff and like it they would barely make a make a ripple Like, you know, okay connery, you know operation kid brother, you know, like they weren't that concerned with These things like taking them taking the heat off of like, you know, the latest bond movie, right That's because bond was as big as the Beatles, you know, it was it was the trans setter in the 60s There was nothing bigger movie wise probably But like all most of those other like the the low grade films those knockoff films. There wasn't even a worry about it Now Sort of like, yeah mission impossible grew out of 007 They're doing these movies now and it's eclipsing the actual bond series It's kind of strange like how it just turned around. I'm I'm wondering if like they're If Babs and Mike are concerned about like and I was blown away by um Fallout mission impossible six So I already know without a trailer that at least action wise it's going to be a banger again and with no time to die We just hope We hope it's going to be a banger


Welcome back to HPE Discover 2021. My name is Dave Vellante and you're watching theCUBE's virtual coverage of HP's big customer event. Of course, the virtual edition and we're going to dig into transformations, the role of technology and the role of senior technology leadership. Look, let's face it. HPE has gone through a pretty dramatic transformation itself in the past few years. So it makes a great example and case study. And with me is Rashmi Kumar who's the senior vice president and CIO at HPE. Rashmi, welcome. Come on inside theCUBE. Hi, Dave. Nice to be here. Well, it's been almost a year since COVID changed the world as we know it. How would you say the role of the CIO specifically and generally IT has changed? I mean, you got digital, zero trust has gone from buzzword to mandate, digital. Everybody was complacent about digital in many ways and now it's really accelerated, remote work, hybrid. How do you see it? Absolutely, as I said in the last discover that COVID has been the biggest reason to accelerate digital transformation in the companies. I see CIO's role has changed tremendously in the last 15 months. It's no more just keep the operations running. That's become a table stake. Our roles have become not only to create digital customer experience, engage with our customers in different ways but also to transform the company operations from inside out to be able to give that digital experience from beginning to end of the customer engagement going forward. We have also become responsible for switching our strategies around the companies as the COVID hit in different parts of the world at different times and how companies structured their operations to go from one region to another. A global company like HPE had to look into its supply chain differently, had to look into strategies to mitigate the risk that was created because of the supply chain disruptions as well as you go to taking care of our employees. How do you create this digital collaboration experience where teams can still come together and make the work happen for our end customers? How do we think about future employee engagement when people are not coming into these big buildings and offices and working together but how to create the same level of collaboration coordination as well as delivery of faster goods and services which is enabled by technology going forward. So CIO and IT's role has gone from giving a different level of customer experience to different level of employee experience as well as enabling day to day operations of the companies. CEOs have realized that digital is the way to go forward. It does not matter what industry you are in and now CIOs have their seat at the table to define what the future of every company now which is a technology company, irrespective you are in oil and gas or mining or a technical product or a car or a mobility company end of the day you have to act and behave like a technology company. So I want to ask you about that because you've been a CIO and a leading technology provider now for the last three years and you've had previous roles and were non-technology selling to IT companies and as you point out, those worlds are coming together. Everybody's a technology company today. How do you think that changes the role of the CIO? Because it always seemed to me that there was a difference between a CIO and a tech company. You know what I mean by that and a CIO and sort of every other company. Are those two worlds converging? Absolutely. And it's interesting you pointed out that I have worked in many different industries from healthcare and pharma to entertainment to utilities and now at a technology company. End of the day, the issues that IT deals with are pretty similar across the organization. What is different here is now my customers are people like me in other industries and I have a little bit of an advantage because just having the experience across various ecosystem. Even at HP, look, I was fortunate at HP because of Antonio's leadership. We had topped out mandate to transform how we did business and I talked about my next gen IT program in last year's CUBE interview. But at the same time, while we were changing our customer partners' experience from ordering to order processing to supply chain to finance, we decided this pivot of becoming as a service company. And if you think about that pivot, it's pretty common if it was a technology company or non-technology company. At HPE, we were very used to selling a product and coming back three years later at the time of refresh of infrastructure or hardware. That's no more true for us. Now we are becoming as a service or a subscription company and IT played a major role to enable that code to cash experience which is very different than the traditional experience around how we stay connected with our customer, how we proactively understand their behavior. I always talk about this term digital exhaust which results into data which can result into better insight and you can not only upsell, cross-sell because now you have more data about your product usage but first and foremost, give what your customer wants in a much better way because you can proactively understand their needs and wants because you are providing a digital product versus a physical product. So this is the change that most of the companies are now going through. If you look at Domino's transition, they are a pizza sellers but they did better because they had better digital experience. If you look at Chipotle, these are food service companies. Ikea, which is a furniture manufacturer across the board, we have helped our customers and industries to understand how to become a more digital provider and remember when HP says edge to cloud platform as a service, edge is the product, the customers who we deal with and how do we get that help them get that data, understand how the product is behaving and then get the information to cloud for further analysis and understanding from the data that comes out of the products that we serve. I think you've been at HP now, I think around three years and I've been watching, of course, for decades, HP, well, HP then HP is, I feel like it's entering now the sort of third phase of its transformation. You know, phase one was okay, we got to figure out how to deal or operate as separate companies, okay, that took some time and then it was okay, now how do we align our resources and what are the waves that we're going to ride and how do we take our human capital, our investments and what bets do we place and all in on as a service and now it's like, okay, yeah, how do we deliver on all those promises? So pretty massive transformations, you talked about edge to cloud as a service so you've got this huge pivot in your business. What's the technology strategy to support that transformation? Yeah, that's a great question. So as I mentioned, first, your second phase which was becoming a standalone company was the Next Gen IT program where we brought in S4 and 60 related ecosystem application where even in the traditional business there was a realization that we were 120 billion company, we are a 30 billion company, we need different types of technologies as well as more integrated across our product line across the globe and I'm very happy to report that we are the last leg of Next Gen IT transformation where we have brought in new customer experience through low-touch or no-touch order processing a very strong S4 capabilities where we are now able to run all global orders across all our hardware and services business together and I'm happy to report that we have been able to successfully run through the transformation which a typical company of our size would take five or six years to do in around close to three years but at the same time while we were building this foundation and the capabilities to be able to do order management supply chain and data and analytics platforms we also made the pivot to go to as a service now for as a service and subscription selling it needs a very different code to cash experience for our customers and that's where we had to bring in platforms like Brim to do subscription billing, conversion charging and a whole different way to address but we were lucky to have this transformation completed on which we could bolt on this new capability and we had the data analytics platform built which now these as a service products can also use to drive better insight into our customer behavior as well as how they're using our product real time for our operations teams. Well they say follow the money in the queue we love to say follow the data and data is obviously a crucial component of competitive advantage, business value so you talk a little bit more about the role of data I'm interested in where IT fits you know a lot of companies they'll have a chief data officer or CIO sometimes they're separate sometimes they work for each other or CDO works for CIO how do you guys approach the whole data conversation? Yeah that's a great question and has been top of the mind of a lot of CEOs, CIOs chief digital officers in many different companies the way we have set it up here is do we do have a chief data officer and we do have a head of technology and platform and data lake within IT look the way I see is that I call the term data torture if we have multiple data lakes if we have multiple data locations and the data is not coming together at one place at the first time that it comes out of the source system we end up with data swarms and it's very difficult to drive insights it's very difficult to have single version of truth so HP had two pronged approach first one was as part of this next gen IT transformation we embarked upon the journey first of all to define our customers and products in a very uniform way across the globe it's called entity master data and product master data program these were very very difficult program we are now happy to report that we can understand a customer from code stage to servicing stage beginning to end across all our system it's been a tough journey but it was effort well spent at the same time while we were building this master data capability we also invested time in our analytics platform because we are generating so much data now globally as one footprint how do we link our data lake to our SAP and Salesforce and all these systems where our customer data flows through and create analytics and insight from it from our customers or our operations team at the same time we also created a chief data officer role where the responsibility is really to drive business from understanding what decision making and analytics they need around product around customer around their usage around their experience to be able to drive better alignment with our customers and products going forward so this creates efficiencies in the organization if you have a leader who is taking care of your platforms and data building single source of truth and you have a leader who is propagating this mature notion of handling data as enterprise data and driving that focus on understanding the metrics and the insight that the businesses need to drive better customer alignment that's when we gain those efficiencies and behind the scenes the chief data officer and the data leader within my organization work very very closely to understand each other needs sometimes out of the possible where do we need the data processing is it at the edge is it in the cloud what's the best way to drive the technology and the platform forward and they kind of rely on each other's knowledge and intelligence to give us superior results and I have done data analytics in many different companies this model works where you have focus on insight and analytics because data without insight is of no value but at the same time you need clean data you need efficient fast platforms to process that insight at the functional non-functional requirement that our business partners have and that's how we have established in here and we have seen many successes recently as of now I want to ask you kind of a harder maybe it's not a harder question it's a weird question around single version of the truth because it's clearly a challenge for organizations and there's many applications, workloads that require that single version of the truth the operational systems, the transaction systems the HR, the sales force clearly you have to have a single version of the truth I feel like however we're on the cusp of a new era where business lines see an opportunity for whatever their own truth to work with a partner to create some kind of new data product and it's early days in that but I want to and maybe not the right question for HPE but I wonder if you see it in your ecosystems where it's yes, single version of truth is sort of one class of data and analytics got to have that nailed down data quality, everything else but then there's this sort of artistic version of the data where business people need more freedom they need more latitude to create are you seeing that and maybe you can help me put that into context that's a great question Dave and I'm glad you asked it so I think Tom Devonport who is known in the data space talks about the offensive and the defensive use cases of leveraging data I think the piece that you talked about where it's clean, it's pristine, it's quality it's all that most of those offer the offensive use cases where you are improving companies operations incrementally because you have very clean data you have very good understanding of how my territories are doing how my customers are doing how my products are doing how am I meeting my SLAs or how my financials are looking there's no room for failure in that area the other area is though which works on the same set of data it's not a different set of data but the need is more around finding needles in the haystack to come up with new needs, new ones in customers or new business models that we go with the way we have done it is we do take this data take out what's not allowed for everybody to be seen and then what we call is a private space but that's this entire data available to our business leader not real time because the need is not as real time because they are doing more what we call this predictive analytics to be able to leverage the same data set and run their analytics and we work very closely with business units we educate them, we tell them how to leverage this data set and use it and gather their feedback to understand what they need in that space to continue to run with their analytics I think as we talk about hindsight, insight and foresight hindsight and insight happens more from this clean data lakes where you have authenticity, you have a quality and then most of the foresight happens in a different space where the users have more leverage to use data in many different ways to drive analytics and insights which is not readily available Great, thank you for that, interesting discussion you know digital transformation is a journey and it's going to take many years in a lot of ways, not a lot of ways 2020 was a forced march to digital if you weren't a digital business you were out of business and so you really didn't have much time to plan so now organizations are stepping back saying okay let's really lean into our strategy the journey and along the way there's going to be blind spots there's bumps in the road when you look out what are the potential disruptions that you see maybe in terms of how companies are currently approaching their digital transformations That's a great question Dave and I'm going to take a little bit more longer term view on this topic in what's top of my mind recently is the whole topic of ESG environmental, social and governance most of the companies have governance in place because they are either public companies or they are under some kind of scrutiny from different regulatory bodies or whatnot even if you're a startup you need to do things with our customers and whatnot it has been there for companies it continues to be there we the public companies are very good at making sure that we have the right compliance right privacy, right governance in place now we'll talk about cybersecurity I think that creates a whole new challenge in that governance space however we have the setup within our companies to be able to handle that challenge now when we go to social what happened last year was really important and now as each and every company we need to think about what are we doing from our perspective to play our part in that and not only the bigger companies leaders at our level I would say that between last March and this year I have hired more than 400 people during pandemic which was all virtual but me and my team have made sure that we are doing the right thing to drive inclusion and diversity which is also very big objective for HPE and Antonio himself has been very active in various round tables in US at the world economic forum level and I think it's really important for companies to create that opportunity remove that disparity that's there for the underserved communities if we want to continue to be successful in this world to create innovative product and services we need to sell it to the broader cross-section of populations and to be able to do that we need to bring them in our fold and enable them to create that equal consumption capabilities across different sets of people HPE has taken many initiatives and so are many companies I feel like the momentum that companies have now created around the topic of equality is very important I am also very excited to see that a lot of startups are now coming up to serve that 99% versus just the shiny ones as you know in the Bay Area to create better delivery methods of food or products the third piece which is environmental is extremely important as well as we have seen recently in many companies and where even the dollar or the economic value is flowing are around the companies which are serious about environmental HPE recently published it's a living progress report we have been in the forefront of innovation to reduce carbon emissions we help our customers through those processes again if our planet is on fire none of us will exist so we all have to do that every little part to be able to do better now I'm happy to report I myself as a person solar panels, battery, electric cars whatever I can do but I think something more needs to happen as an individual I need to pitch in but maybe utilities will be so green in the future that I don't need to put panels on my roof which again creates a different kind of ways going forward so when you ask me about disruptions I personally feel that successful company like ours have to have ESG top of their mind and think of product and services from that perspective which creates equal opportunity for people which creates better environment sustainability going forward and you know our customers our investors are very interested in seeing what we are doing to be able to serve that cause for bigger cross-section of companies and I'm most of the time very happy to share with my CIO cohort around how our HPE FS capabilities creates or feeds into the circular economy how much e-waste we have recycled or kept it off of landfills our green lake capabilities how it reduces the e-waste going forward as well as our sustainability initiatives which can help other CIOs to be more carbon neutral going forward as well you know that's a great answer Rashmi thank you for that I got to tell you I hear a lot of mumbo jumbo about ESG but that was a very substantive thoughtful response that I think tech companies in particular are have to lead and are leading in this area so I really appreciate that sentiment I want to end with a very important topic which is cyber it's obviously you know escalated in in the news the last several months it's always in the news but you know ten or fifteen years ago there was this mentality of failure equals fire now we realize hey they're going to get in it's it's how you handle it cyber's become a board level topic that you know years ago there was a lot of discussion oh you can't have the sec ops team working for the CIO because that's like the the fox watch in the hen house that's changed uh... it's been a real uh... awakening a kind of a rude awakening so the world is now more virtual you've got a secure physical uh... assets i mean any knucklehead can now become as a ransomware attacker they can they can they can buy ransomware as a services in the dark dark web so that's something we've never seen before you're seeing supply chains get hacked and self-forming malware i mean it's a really scary time so you got these intellectual assets it's a top priority for organizations are you see a convergence of the the c-so role the cio role the line of business roles relative to sort of prior years in terms of driving security throughout organizations yeah this is a great question and uh... this was big discussion at my public board meeting couple of uh... days ago it's as as i talk about many topics if you think digital if you think data if you think is the it's no more one organizations business it's now everybody's responsibility i i saw wall street journal article couple days ago where somebody has compared cyber to nine eleven type scenario that if it happens for a company that's the level of impact you feel on your on your operation so you know all models are going to change their c-so reports to cio at hpe we are also into products security and that's why c-so is a peer of mine who i work with very closely who also work with product teams where we are saving our customers from lot of pain in this space going forward and hpe itself is investing enormous amount of efforts in time incoming out of products uh... which are which are secured and i'm not vulnerable to these types of attacks the way i see it is c-so role has become extremely critical in every company big part of that role is to make people understand that cyber security is also everybody's responsibility that's why in itv propagate def sec ops uh... as we talk about it we are very very careful about picking the right products and services this is one area where companies cannot shy away from investing you have to continuously looking at cyber security architecture you have to continuously look at and understand where the gaps are and how do we switch our product or service that we use from the providers to make sure our company stays secure the training not only for individual employees and anti fishing or what does cyber security mean but also to the executive committee and to the board what cyber security means what zero trust means but at the same time doing dry runs we did it for business continuity and disaster recovery before now this time we do it for a ransomware attack and stay prepared as you mentioned and we all say in tech community it's always if not when no company can thumb their chest and say oh we are fully secure because something can happen going forward but what is the readiness for something that can happen it has to be handled at the same risk level as a pandemic or earthquake or a natural disaster and assume that it's going to happen and how as a company we will behave when something like this happens so i'm a huge believer in the framework of protect, detect, govern and respond as these things happen so we need to have exercises within the company to ensure that everybody's aware of the part that they play day to day but at the same time when some event happened and making sure we do very periodic reviews of IT and cyber practices across the company there is no more differentiation between IT and OT that was 10 years ago I remember working with different industries where OT was totally out of reach of IT and guess what happened WannaCry and Petia and XP machines were still running your supply chains and they were not protected so if it's a technology it needs to be protected that's the mindset people need to go with invest in education training awareness of your employees your management committee your board and do frequent exercises to understand how to respond when something like this happened see it's a big responsibility to protect our customer data our customers operations and we all need to be responsible and accountable to be able to provide all our product and services to our customers when something unforeseen like this happens Rashmi very generous with your time thank you so much for coming back in the queue it was great to have you again thank you Dave it was really nice chatting with you and thanks for being with us for our ongoing coverage of HPE Discover 21 this is Dave Vellante you're watching the virtual cube the leader in digital tech coverage be right back


Hi, I'm Alex Williams of Silicon Angle here at the Node Summit, live with theCUBE, our world-class online new streaming service that we do at events like this here at Node Summit with James. James, Richard, how are you, sir? I'm doing great, man. It's so good to see you again. Good to see you.  But, you know, great venue, amazing crowd here at the show. And I'm really excited to be on theCUBE again. The last time I was on was a great time, so. What's up with Node.js and kind of your perspective of the world? Well, you know, one of the aspects of Node that's really interesting came up on the panel that I moderated this morning. We had Nojitsu, and Heroku, and Azure, and Cloud Foundry represented. And we talked about Pascal, but one of the things that really came out of it is, you know, in some ways, Node is just another language in the sense that there are things it's great at. There are things it's not so great at. But I think what's really exciting about Node in the cloud space is it's a venting model and it's JavaScript-based nature really makes it something that is quite portable and quite kind of re-assembleable and componentized by nature. In fact, you heard a lot of the talkers at the show talking a lot about how Node kind of gets you to break down to the smallest denominators as quickly as possible to make event management that much easier to deal with to help with things like debugging and deployment and other things. That's kind of the nature of where the cloud's taking applications in general in a lot of ways in that because it's a very service-based environment, people are beginning to break down capabilities into smaller service units and then bring them together, compose them in different ways that may or may not have been expected up front. Node is a great representation, I think, of a language that takes this into account, not maybe not intentionally, but it does fit very nicely. And one of the things that, or in tights at Heroku, is that one of the places we're seeing the Node version of their environment use the heaviest is in machine-to-machine communication. They have a very high traffic level in machine-to-machine communication. And to me, that's really kind of the next frontier. We've done the Web 2.0 thing and it'll continue to grow. There's a lot of room to grow in that space, Facebook apps, consumerism, but really, a big growing area is going to be this machine-to-machine capability where now the automation environment that underpins a lot of, you know, the traditional automation will become much more cloud-like in that it integrates with third-party components that protects, takes information from some source that's not within the four walls of the company and begins to bring that together. And Node seems to be very well-suited to that. Yeah, it does. I mean, and talking to people about how they're using Node.js, for instance, I was talking to a FlowDoc. I think that's the name of their company, but they take group messaging and activity streams, but they take activity streams from GitHub, they take it from JIRA, they take it from email, and they're going to start adding Twitter into it. And so Node.js is really, really ideal for that, as they say. And it seems like it's, you know, we're hearing a lot of it, you know, a lot of people saying that it's great for that real-time communication, so that's what it's great at. What is it not so good at? Well, I think when you get into situations where thread control, where concurrency and managing what's happening from a concurrency perspective gets to be a little bit more detailed and a little bit more finesse-oriented, some of the kinds of things that an Erlang would do really well. I think that's the point at which Node's eventing model means it's much less predictable about what's going to happen when or whether you're even going to have work that is stacked up, intended to be completed, but it's not completed yet. There's not that serial nature to it. It's much less, it's much more about sort of the flow of information through different things taking their part of it and then passing it on to the next thing. When you get into something where you're really getting into the need to really finally work at a high performance on a given processor or just in general on computing, I think that's the point where a lot of people would say there's some things that Node does that aren't the smartest things to do in those particular architectures. That's interesting, I mean, that really then speaks to the need for really good tools, doesn't it? To really be able to see what's happening with the deployment, for instance. I mean, I think about joint and the data visualization tools that they have really to kind of see what's happening inside the network. And it's a big reason for something like Instratis to exist as well, right? Tell me, let's talk about that. Yeah, so Instratis is the leading enterprise cloud management solution. And by cloud management in this condition, the situation, what we mean is the consumption of cloud. So as opposed to being something that delivers a cloud service, we're about how do you take your applications and consume cloud services in a way that is under control, allows you to do some governance around who can do what, potentially financial controls, you're making sure that people are only consuming as much budget as they're supposed to be consuming for something. These are the problems that enterprises deal with when they look at cloud that are very, very, they're exemplified by the enterprise. A big difference being, in a Web 2.0 space, typically you have a few development teams, they have some number of processes, they're growing number, but they're still a well-managed number of processes. And the idea is they have to scale these things across hundreds or thousands of nodes. The enterprise problem is, they've got hundreds or thousands of applications. Each of which may scale on an average need of five to 10 nodes. Right. But the problem is each of those applications have different owners, they have different requirements, they have different budgets, they have different compliance constraints that they have to meet, policies they need to apply to the cloud environments that they run in. And so it's that bringing together the governance and the automation of the application from the application's perspective in a multi-team environment, in an enterprise environment that we really focus on. So we give you, basically the one way to think about it is as a console for managing and operating applications in the clouds that you consume for those applications. So managing those applications inside the enterprise, and we're hearing a lot of popularity for Node.js in the enterprise. Is that one of the, that's one you just outlined, some real reasons why it has viability there. What are some other reasons that you're seeing that they're talking about? That enterprises are talking about Node in particular? Yeah, you know, again I think the, when you look at the types of applications in enterprises, they span the full gamut end to end. One of the things that's happening is the cloud has introduced the ability to build some applications that were economically unobtainable, frankly, in the past. So a lot of big data, a lot of the excitement about big data comes from the fact that you can now experiment with processing data in certain ways.