>> And one topic. I want to get onto that. You mentioned it up and you opened the can of worms on this. So I blame you. His blood flow restriction training you called B F R. And Freeman listening chases the well, the most well versed individuals in this area. I was, I learned from him probably weekly on it, and I get studies from him. I used to be daily. Probably. It will lessen consistent now, because he's probably realizing that I can't read that fast. But I'm gonna chase to talk a little bit about some of protocols that you used be a far and harder you can use it for. Not yet. That's like development for individuals who might just be seeking an alternative way to work out whether the older adults, people who travel on the road and what it does physiologically for not only muscle growth, but the tendon thickness, like you said, and some of the other other >> protocols. Such a cellular swelling protocols. >> Yeah, yeah, I think you know, the one thing I would say about our previous of conversation with incense Thing is, I'm not telling people not to take him out like running around saying that that's the devil and all that. So I make sure that I'm not like one of those zealots about that stuff. It's it's just Hey, do you need it? You know, like this, that thought process is critical. Is this necessary? Not let me just problem cause I'm sore today, right? I think that's the caveat I want people to walk away with is that everything is necessary if it's necessary. And if it's not, is there a better alternative, or is it just part of life? Is that part of being a division one athlete or, you know, somebody who's recreational? E fit is you're going to feel a little sore and tired. Is it necessary to take that pill that made negatively? Thank you. So I think that's one thing I want to say, but kind of moving on to the >> You are not a dealer. I will vouch for it. Yeah. Interesting topic to talk about. And I give you credit for being open minded on both ends. Yes, everyone was concerned. >> Yeah, Yeah, I want to throw that out there. But I think with the Bee Afar stuff, it's I'm so ill. I've learned a lot from the man. Dr Headless Sarah. Hey, Works is Smart tools company, which they're just absolutely revolutionising how available and the education that's associative willful restrictions. So I you know, I I'm gonna kind of pass on that credit and say that, uh, they're really pushing the field forward, and I'm not affiliated with the company. I just think what they're doing is is fantastic work, because local restriction obviously has been around for a long time. It's not new, you know, we're not pretending it's new, but you know, it's really the availability of cuffs for sort of affordable prices has made it seem no refreshed and kind of a new life to it started in the late nineties in Japan, really doing a lot of the early research on it. Ah, lot of people started with tine off with different straps and and, ah, bands that they're just wrapping around their arms and looking for, you know, in a partial occlusion and some cases probably dangerously a full ischemia. But I think you saw it. And most recent years, with some of the owns recovery and the Delphi's, which come in a pretty high price tag and as I mentioned, smart tools has come out. They have much more affordable. I think it's, you know, a tenth of the price. And so now you're able tto. But these types of you know it's tool and everybody's hands. And I think it's is changing the landscape as faras, a modality that has multiple uses. And that's one thing when we talk sports science, we talked technology. You know, everything has a time in place. But when I look and evaluate and vet out technology, or whatever we're going to bring on is as a new resource. I always looked forward to have multiple uses, doesn't have a bang for your buck, and I think the blood flow restriction does. It's versatile. It can be used in rehab. You can be used to build muscle confused for strength. It can be used as, ah, activity potentially ater so you can use it. Potentially increase your subsequent performance with an acute time window. You can use it as a recovery tool, so I think the the utilization of it is still we're learning about it. There's still no definitive. Here's how this happens in this sequence but I think that's what Everything right? The human body. We're learning so much about it. But the science that's there has proven that low load with local restriction, where we're including one hundred percent venous return, but partially including arterial inflow. So there is blood flow going into the muscles and the periphery, but there is no blood flow returning, and so it creates a cooling effect. We're essentially you're gonna limit the availability of oxygen. You're going to decrease the pH and more acidic. You're goingto deplete foster creating stores. You're essentially going to run through the size of principle and use up small of slow twitch fibers and skip essentially rights of fast switch fivers with a low load or even a non loaded exercise. So I think when you talk about somebody who's got limitations, maybe they just had surgery. They can't run. They can't have the impulse of the impact that you would need or you would want to see toe. I kind of developed the most cultures. They come back. Little restriction is a great way because takes a low load exercise and you realise, is that restricted bowling and you get a subsequent fast, which adaptation? So you're you're simulating the big boys, the ones that move us, the ones that make us jump and run faster. Ah, and I think you're seeing time Windows of adaptation that air a sixth of the time Faster, you're getting strength. And I purchased three Adaptation in two weeks, whereas in traditional resistance training it was taking eight to twelve. Um, so And when you talk about, I had an athlete rolled her ankle and I want to make sure that they're not having atrophy is they walk around in a boot. I need to make sure that the muscles around the knees and the hamstrings, the name of the elders, critical drivers and sport aren't just wasting away. So we would have athletes obviously in the rehab sitting, doing protocols to develop muscle but also just sitting the act of just sitting with occlusion passively not doing anything has been shown to cut atrophy by fifty percent. So it's fantastic because it's not invasive. You're not doing anything into him. They're just sitting. So, uh, we don't you know, promote them to play on their phones constantly, but they can sit there and have their phone out and, you know, twenty minutes goes by and they just hopefully of, you know, benefited their return to play and a, you know, a faster, more efficient way than just sitting around. So lots of lots of utility for it. >> Interesting. So for those not familiar bloodflow restriction training the way it works, you gotta cuss. Arms hopefully cast. Not just, uh, elastic band, you tying on. But that's how I started originally from Kat to training out in Japan. So it's a cuff. The attach is approximately on the whim, typically by the shoulder or up along the thigh, and it includes the amount of blood so reduces the amount of blood. Don't go into the muscle, which then allows these Siri's of physiological effects that chase alluded to. That is a difference between Venus and arterial occlusion and chase in. Regards to that were Some of the specifics are for people who aren't as familiar with blood flow. You rattle off a bunch of stuff regarding blood flow and from the adaptations of it. But people who aren't familiar with it you measure the occlusion through Doppler. I believe Smart tools uses a remote Doppler. They're attached to you on the distal limb and everyone using this, what percentages do use? How do you know what you too much occlusion that to type that not tight enough. And we're the protocols that you use once you have the right conclusion for that limb to increase some of these hypertrophy, some muscle growing activities or, you know, just sitting there play on your phone activities that reduces hypertrophy for your athletes. >> Yeah. So what you're doing is you're actually going to take an external Doppler or something that's gonna allow you to magnify the sound of the pulse, right? So if you take radio pulse, you know, right here you would replace the Doppler on it. You would actually be able to hear the heartbeat as it from service, >> due stew, stew, sh >> and up top. They're wearing the cuff. You're going to slowly start to inflate it. It gets tighter, tighter, tighter. And you will eventually get to a point where that, uh, false will start to fade of >> this dish dish. >> And it comes to a point where it's non existent. And so that's when you know that there's been full arterial occlusion that's there one hundred percent. There is no blood flow into that arm. There's no blood flow out. It is included. And so research has shown that basically anywhere from thirty percent in ninety percent, you're gonna have the same amount of occlusion. So if I was explained that, ah, a little bit more detail is so I'm going to take that one hundred percent occlusion number. So if you've ever done your blood pressure and the typical one of perfect blood pressure's one twenty of Brady and that's the same device we're going to use I mean its's stigmata. I'm anemometer the tough one to say, um and you're going to get a number up there like, let's just say two fifty. Alright, so that's your hundred percent occlusion. What again research has shown is that in thirty percent of two. Fifty all the way up to ninety percent of two. Fifty, that's the sweet spot or including arterial, that actually doesn't improve occlusion as the higher you go. So we stick to fifty percent. So, you know, fifty per cent of two fifty is one twenty five. And, ah, you're goingto have Justus. Much of you did it at ninety percent. And really, the differences is pain perception. Because if you start getting up one hundred percent inclusion and telling somebody to exercise, they're not going to like it. It's not going to feel good. So it's a nice sweet spot of saying, Hey, we have included Arterial but not fully restricted, but we have researched it, Venus. But we can still move and be act on DSO with that what you're really looking to do. There's a thirty fifteen fifteen fifteen protocol that's seen pretty commonly, but ultimately you just need to fatigue the muscles. Ito have a low load exercise that's done for high volume, typically fifteen plus wraps for multiple sets with a minimal respirations. So what we're trying to do is we're trying Teo, allow for blood to be flung, pumped into the muscle. You're goingto actively, you know, contract. Over time, it's going to stimulate fast twitch fibers. You're going to rest for a very short period. More blood flow is going to go to the area. It's gonna keep getting more acidic. It's going to keep activating Mohr fast twitch, and you're going to just repeat that. And so I mean it really, really magnifies the response of typically a weight or resistance that would be almost no impact on you at all. You would have no performance benefit from using a weight that light. So you can really use it as you know, when I was in a rehab setting with an athlete who has very little capability to handle load. Or you could use it as a finisher in your body builder. And you wantto stimulate ah, muscle group that's lagging, and you really want to build it up. Ah, it's the fantastic thing I think about It is it's a minimally damaging activity. And what I mean by that is that you're gonna have a dramatic reduction and creating stores of CK levels. Lt's myoglobin. You're not going to get the same mechanical breakdown that you see what too difficult resistance training when we start talking about internal load and H R V. If you were to substitute and in season lift with the Afar, you're still going to get strengthened and have virtually adaptation without the potential systemic load. That may be a typical resistance training session. Does the now you start talking about minimizing, uh, internal responses? Bye. Still getting annotation, so it's it's pretty, pretty amazing. >> Yeah, that's that's something. So I've seen personally as well. I use smart tools, smart tools. I'm not feeling it with a big fan of whom, because they made it affordable for individuals like you, of myself actually use them. So we're talking about occlusion. We're talking about reducing amount of arterial occlusion, but not with the amount of Venus inclusions here allowing blood to pool. It's an extent you get large amounts of violation. You increase the amount of capital area is in that area, but you're also not breaking down the muscle in the same way that you would otherwise. So we're lifting a heavy load. You have the fibers himself begin to essentially tear apart. Your body has to rebuild these, but now we're increasing hypertrophy, so growing them also, without having to have this break down response in the muscle itself. But that being said, the loads that you're using are also twenty percent of your one rat max. So a very, very light load you're using to fatigue. How does that affect the tendon itself? Because one thing I've noticed personally, this is I'm not I'm not saying you should do this, Okay, this is what I did and maybe stupid or whatever you wanna call it. I had a really bad Tanaka, the issue of my knee where I couldn't play basket. I couldn't go upstairs well, and I didn't be afar. Traditional trailer at tempo work. But when I started doing be fr low level plyometrics when I started inducing some of the shearing forces on the tendon to increase adaptation that area that otherwise might not be there with a >> low load, >> I started Teo see much better results in my knee compared to some of the tempo work. Do you do anything specifically with B a far that might target attendant outside of the traditional thirty wraps, fifteen wraps, fifteen reps. Fifteen reps with >> a low load. >> Yeah, yeah, absolutely. I think you know some of the ice of measures that we talked about when you were working in Stanford and having that Anil Jessica effect. So having the ability to have the mitigation on acute windows of what, fifteen, forty five minutes, but also the college and proliferation. So you're getting an increase in human growth hormone that there's like one hundred seventy percent times greater after ah workout, which we know. H gh doesn't necessarily build bigger muscles, but it does stimulate collagen growth. So when you're having somebody who is maybe coming back from a ruptured Achilles or another, you know IDA cirrhosis issue, You know, it's a great way to help promote and environment and maybe in a vascular area and the kind of forces, nutrients and a hormonal shift that may promote a more appealing environment. I think you know, we talked about it briefly. The training piece, I think you know, the more that you can start to get people into. I'm not overly dramatic, sport specific person, but I think the more you can get people into activities that are going to be replicated on the field, know whether it's sled pushes and walks or whether it's, you know, having some type of, um, you know, activity. If your picture where you're getting your arm through these range of emotions that are going to be necessary while using the inclusion is actually gonna promote a lot of ongoing benefit. I think toe rehabilitate the area on a functional manner and develop not only the musculature, but also remote the properties around that specific tissue that needs to be healed. So I think there's some really cool things that are just now kind of being played with Just because we can actually die. Elin, the proper collusions. We can actually die. Elin. What we want to see happen with you whether it's, uh, some of the cells, whole protocols that we're doing are these giving preconditions. Bread falls. Where were haven't athletes sit for extended period time passively with their occlusion of set? And then they're gonna reap, refuse. We're in, Allow blood flow back, and we're going to do that repeated intervals prior to activity and see a potential for increased power output. Oxygen. Connectix. The research is pretty amazing with some of the human reconditioning and that they're saying, um, increase time to exhaustion, decrease time trial performances. But they don't really know why. You know, there isn't like a clear mechanisms for performance gains that's been totally identified just yet. There has been stuff where it's shown to attenuate lacked eight levels. So you're obviously no cellular. Respiration is enhanced because you're not getting that amount of hydrogen present in the blood. So you may be potentially more efficient energy user using more, more fat and oxygen, so that's great there. But I think you know, as the research are sketching out, that piece is that's one thing that I'm looking at doing for my research focus for school. Is that potentially a shin piece? If I'm already going to be sitting around before a game, or I'm gonna have time between events like a track and field event are, you know, Cool event. And I know I can sit here passively, not use energy, provide a stimulus to the body that's gonna potentially open up neural pathways or physiological mechanisms to increase contract ability of the muscles. I'm going to, then maybe get that extra tenth of a second. I'm going to throw an extra, you know, a couple feet on the javelin. I'm going to do whatever I need to dio potentially at a higher level. I think that's really as we're pushing towards performance. Why do you take, you know, choose during the game like you want increase performance, you want to run longer, and I think this is going to add one more a little layer to it. That from an investment piece is minimally invasive is minimally changing to their to their schedule. They're not. They don't have to do anything crazy. They feel good. And that's the biggest thing. Is the anecdotal feedback on it is man, I feel great. I feel like I have to I don't have to do a full warm up. I feel like I can just kind of get out there, move around. We still have him do stuff, but they just feel like they've warmed up faster. And I think of that piece is gonna be really cool to see if we can demonstrate some of empirical evidence on it. >> Yeah, that I'm excited to see the research, >> and I know you're working hard on it. >> It's kind of a great stop. Making Brava kind really brings us full circle because you look at be fr it, increases their sit in the area and lacked a production and increases economic nervous system arousal, which has been shown both to increase cognitive abilities. Um, neural plasticity and ability to enhance memory. And so why you're doing this? It's also the only prime main the body for the coming activity. We also prime ing the body is a hole in regards to it's mental capacity and not just the muscular area. And so when you start looking at that, you know, full system, the human body and how we can talk about a little bit here, some dynamical systems where you know the body is really complex. What happens in one area affects another. You can't differentiate between your physical mental side because the physical side of the Afar is now enhancing your mental side. Just like your perception. Ten hands a workout. And so you have feedback up and feedback back down. And that's just a great, you know, highlight You brought up because now it's really inclusive. Were we're so often thinking this isolated manner. Oh, if we've been to this or we run this, this will happen. But we don't think about it in this recursive loop manor where what I did to my muscle, right, our muscle releases these myo times. I go talk to our brain, which then go back and talk to our muscle. And we have the endocrine system working together to orchestrate this all and just the whole idea of be a farm for a game It's not just right the muscles and the scheming Preconditioning, but it's also a fact that you're putting the person in a state That's more conducive. Two performance itself, because so often and this isn't to go on a rant and I apologise. And this is something you buy a top about, right? Avoiding the sympathetic states, All right, we don't want to be sitting there before game doing deep belly breathing because we need to be ready to roll. There's a reason why you get excited in these situations and a really excellent full loop example. How Don't comes together there. >> Yeah, I think one last little piece with that, too, is black. Tate has been shown and exercise of a specific lactate now to have been associated with BDNF, right? So that brain derived neurotrophic factor that exercise stimulates like Miracle Gro for the brain, >> and that if >> you're sitting around watching, you know, lecture for an hour, get up to ten SWATs. Walk around, and all of a sudden you have a renewed focus. And so with that to your point of it's all connected is you have an athlete who essentially is going to get a benefit from that. But we're also, you know, and there they'll never watch this, so I'll say it. I do planting that placebo. My burbage is really, really careful. And hey, just so you know, you wear this attempt ten, fifteen minutes before you do some ISOs, your ankle will feel better. It has an ability to mitigate. Think like him. Planting that sense of this is gonna work because we'll see Bo Effect works. We know it does. So there's a little bit of, you know, mix of art and science and how we imply these technologies and saying they like, Hey, Logan, just say no, you wear this before that game, your ankle will feel better. You're gonna feel looser, going to hell faster and just letting them roll with that and don't need to tell him anything else. And I think that to your point of it's all connected can then maximise whatever intervention you want to, then increase performance. >> Yeah, and I'll avoid a rant here. I'll keep it short, I promise. But what you hit on? Perfect. Especially since that. Look at some of studies regarding attendance, they'll look at it and see that the timid itself is healthy, yet they feel pain, and they've done lost studies where they're saying an external stimulus. So something like a metre gnome in the background going Ping Ping Ping and you're focused on the stimulus instead of the pain. And you now begin to de associate your knee with pain because the stimulus and regards to the tempo that's going on the background, you're doing it. Why didn't exercise So now? Because you're focused on this external stimulus fall during exercise, you begin to disassociate pain with your, you know, near tendon during that movement and just really shows how coupled the system is and how our brain talks your body body. And if we perceive that we're healthy right? You said, Oh, mixing the heart and the science while you're mixing the science of the science, right? Your you understand that perception is reality is not necessarily. We like to call it art because there's no number to put behind it. Really. It's, you know, the science that our body is deeply into connected and how are neurons from the brain talked to our muscles? Are muscles tough back to our brain are all essentially one and how everything from your nutrition, your perception to your stress from school, you're emotional state, whether you got a text message from someone that made you upset all effects, your internal load off the body itself. And regardless of what external only put and no matter how hard you want to work, if your internal system isn't able to handle the stimulus they're going to put on it in terms of the load you're going to give then what we're doing is it? It's really falling short of what we're actually trying to accomplish because we're essentially using external load to infer what's going on. But there's so many things that go on inside the body outside of external load that we're only using one system to monitor the internal system. We're kind of I was a falling short, but not maybe doing all that we can. >> D'oh Yeah, I mean, I think the you know not to rant myself, but that's one of the biggest mistakes that we as a sissy practitioners make, is the assumption with general adaptation Centrum theory that you're getting people and that they're adapting at the rate into the dose that you think is appropriate that we're making that assumption as to where they're at. So when we say, Oh, they're at home, you know, stasis. And we're going to apply to weeks of ah loading scheme, and then we're gonna unload, and then we're gonna push it higher because they're going to super compensate. I think that is a load of crap. I think that we want that to be the case because we want to feel justified and feel good ofwhat we d'oh. But in many cases, you really have to dial in all the factors associated with overreaching all the factors associated with performance and mix them and have checks and balances to see truly, if somebody is where you think they are and if you got them where they are and if not, what was the reason why was there an energy insufficiency? Was there a Micronesian problem? Was there associated stress damaging the functioning, The A access All those things have you know they come in to play, but we are so rigid and and a lot of our thinking me included Holy, guilty. This we work in four to six week block. So yeah, you know, my own load is gonna be a three week three. Well, maybe your own unload should be a week nine. You know, like, how do you know that they're not ready for Maura. Maura, Amore. Um, you know, so that I think that assumption of not necessarily taking into consideration that connectedness between all these systems Ah, can get us into trouble to make us have false positives. I think I think we really congrats pawn the stuff that's not there >> now, that's that's couldn't be said better because we like to make it simple, because we can understand Simple. And when we make it complex, we realize we don't really understand that much. But the more we appreciate as complex, the more we can appreciate how applying something simple, like we think a load ten push ups really isn't as simple as it may be. And that at times, can cause paralysis by analysis. Where you have so many things >> going on at once and to consider I'm not saying that we just sit there and measure every single subsystem. I know you're not either, >> but the idea that we need to appreciate that and see where can we maybe refer. Teo, Turn, Tio. That isn't just in the lane off. How much weight do we lift? How much low do we give someone But what other factors could be involved and that athletes life. That's not getting the results that we think this external load should be leading. Tio, it's a great check engine light, because now we have this external load. Hey, I expected to be here in three months, and you're not there. That's okay. Who knows whose fault it is? No one's. But the idea is that now we can turn different people because we didn't see the expected results. We can dive a little deeper, and that's allowing us to utilize our resource is whether it's a friend. You know, a doctor. You know, another practitioner, you know, to help arm us with the information to be the best that we can be. >> Yeah, I think that's what the external load comes in, right. You gotta know if they're not meeting expectations or the desired outcomes. No. Are they typically matching people in practice? You know that are similar positional demands. Are they typically being asked to do something that isn't looking normal? That would then we can kind of backtrack and see how they were doing it. What the fuck? Jack is associated with an internal load work, and again, we don't. We don't monitor everything. We don't think it's necessary. We try and find what's appropriate for his team and scenario. But I think again, if you're mindful and you know you're athletes and you know the scenario of what you're trying to put them in, you can then kind of use your your coaching, I to say, Okay, what are the things that I think may be influencing? Yeah, providing Malad a patient, you know, orange, the desired stimulus, you know, desired outcome. Now, what are we doing to them that we should be seeing or think we should be saying. And if I know them, what is essentially a confounding variable to that? >> Yeah, No, that's perfect. You don't assess everything. A because you can't and be known as time. But you assess what's pertinent and you're aware of what's apartment and you act out the check engine light and facilitate where you can now, well said, because I think both ends resettle. Let's be so simple and just do this or let's on Lee do this aspect over here. But when you take in consideration, all of it, you allow yourself to be the best you can be in your position that you're in because you're not trying to solve everything. You just try to facilitate where you can. Yeah, perfect for Chase. And I want to hold you up too long, and I really appreciate you being here. I want to wrap it up before finishing up here. I got, I guess, two questions for you. I didn't send them to you ahead of time so that I can if you don't have a quick answer, that's fine. The first one is it's pretty simple. I'm not going. I don't mean Resource is in terms of O go to Pub Med or go to this paper. But are there any individuals out there that you can possibly listen to or find that you have found the very informative and not just in terms of all that's good information, but sometimes change the way you think about how you do your job. >> I'm talking to you right now. It's a lot of my my thoughts and know how I address of, you know, some of the the bio mechanics and physics of what we're doing. You know, it's definitely not an area that I'm strong in, and I think you've done a great job of putting information out there for the public tio toe, you know, be able to digest an easy manner, man, you know, a public resource. You know, this may sound kind of cheesy and maybe a little bit of roast sci fi, but I still re t Nation and Goto like all those you know, you know, Jim Wendler sites and freed all the Westside stuff. And, you know, I think you can't isolate sports science and sail. It's just Dad are, Oh, it's just, you know, pumping out research out of the lab or Oh, it's physiology or urge technology. I think each practitioners gonna have their own flavour and what they like and what they bring to the table. And I think that we need to cater to that. Each person should say, Hey, this is what I'm good at. These are my skills. I want to learn more about tax and if X s o happens to be baseball and throwing and overhead athletes than you're going to find the Mike Ryan holds air crises and really dive into that. And if you want to know about traditional pure ization schemes and force plays, you're gonna look at the stone stuff. You're gonna look at half, you're going to look at people who are early pioneers in it. So I think, you know, I don't have ah, necessarily a one person go follow, but it's more of a question to the question is what do you want to know about? What do you like? What's something that's really really, you know, kind of hits the button for you and then just start Googling stuff start, you know, typing these these keywords in and people will start popping up. And I think that's my development has come has jumped. The greatest, I guess Leaves is when I started diving into these rabbit holes of what I want to learn about right now and just saying for the next two weeks, I'm going all in on, you know, let's see saturation lost muscle from Samo, too. You know, I'm just learn everything I can about my loving and hemoglobin and mad a crit and all that stuff. So it's really more about finding what you want to know at that time and just doing a deep dive and then finding something else, doing a deep that and before you know it, you're times years to that and you have a, you know, a well rounded hopefully, you know, face of knowledge to pull from. >> And my last question for you chase. And this might be a tough one for you to answer the that you are the ghost of social media. Yeah, That the king of the King of trolling my page. You know that you are interested. People are interested in following up on what you're doing. Where can they find more information about yourself? What links or handles either. Twitter, Instagram. Would you advise him to look up into and keep a tab on yourself? >> So the only thing I'm using, as I have on Instagram and at Underscore Chase felt so It's It's simple. It's like toe like to troll you and fight in every now and then. But, ah, that's basically what I got. I got a couple post up there. But maybe maybe if, uh, I get a little help, we'll see how it Ah, how it grows. >> Yeah. I highly advise you guys following him because we continue to push him to post more stuff. I shouldn't be the only one privileged to get his text messages at obscure hours, highlighting some interesting topics I would love for it to be shared publicly. So I'm not being the third party siphoning off his knowledge and posting there. Yeah, well, they could chase. I really appreciate you hanging here and be able to be our first guest again here. The reason why I wanted you on first you quite a bit played a big role in my development and continue, Tio. And we all wish the best for you. Um, it really was great to have you here and thank you. >> All right, man, I appreciate it was a lot of fun. >> All right. Awesome. Well, thank you guys for listening again. My handle here is strong. Sorry. At strong underscore by science. I did that all wrong. It's at strong. Underscored by underscore science. I should know my own handled by now. I use Instagram, I think my Twitter's handles at strong underscore science. Who knows? We'll make a link to it. We'll be sharing this podcast here shortly with different clips as well. For those of you who don't have the attention span to listen to an hour toy mint podcast will die some of this up. So thank you guys for listening. Really appreciate it and take care.

>> Narrator: Live from Midtown Manhattan, it's theCUBE. Covering Big Data New York City 2017. Brought to you by SiliconANGLE Media and its ecosystem sponsors. >> Hello everyone. Welcome back to our CUBE coverage here in New York City, live in Manhattan for theCUBE's coverage of Big Data NYC, our event we've had five years in a row. Eight years covering Big Data, Hadoop World originally in 2010, then it moved to Hadoop Strata Conference, Strata Hadoop, now called Strata Data. In conjunction with that event we have our Big Data NYC event. SiliconANGLE Media's CUBE. I'm John Furrier, your cohost, with Jim Kobielus, analyst at wikibon.com for Big Data. Our next guest is Gus Horn who is the global Big Data analytics and CTO ambassador for NetApp, machine learning, AI, guru, gives talks all around the world. Great to have you, thanks for coming in and spending the time with us. >> Thanks, John, appreciate it. >> So we were talking before the camera came on, you're doing a lot of jet setting really around Evangelize But also educating a lot of folks on the impact of machine learning and AI in particular. Obviously AI we love, we love the hype. It motivates young kids getting into software development, computer science, makes it kind of real for them. But still, a lot more ways to go in terms of what AI really is. And that's good, but what is really going on with AI? Machine learning is where the rubber hits the road. That seems to be the hot air, that's your wheelhouse. Give us the update, where is AI now? Obviously machine learning is super important, it's one of the hot topics here in New York City. >> Well, I think it's super important globally, and it's going to be disruptive. So before we were talking, I said how this is going to be a disruptive technology for all of society. But regardless of that, what machine learning is bringing is a methodology to deal with this influx of IOT data, whether it's autonomous vehicles, active safety in cars, or even looking at predictive analytics for complex manufacturing processes like an automotive assembly line. Can I predict when a welding machine is going to break and can I take care of it during a scheduled maintenance cycle so I don't take the whole line down? Because the impacts are really cascading and dramatic when you have a failure that you couldn't predict. And what we're finding is that Hadoop and the Big Data space is uniquely positioned to help solve these problems, both from quality control and process management and how you can get better uptime, better quality, and then we take it full circle and how can I build an environment to help automotive manufacturers to do test and DEV and retest and retraining and learning of the AI modules and the AI engines that have to exist in these autonomous vehicles. And the only way you can do that is with data, and managing data like a data steward, which is what we do at NetApp. So for us, it's not just about the solution, but the underlying architecture is going to be absolutely critical in setting up the agility you'll need in this environment, and the flexibility you need. Because the other thing that's happening in the space right now is that technology's evolving very quickly. You see this with the DGX from NVIDIA, you see P100 cards from NVIDIA. So I have an architecture that we have in Germany right now where we have multiple NVIDIA cards in our Hadoop cluster that we've architected. But I don't make NVIDIA cards. I don't make servers. I make really good storage. And I have an ecosystem that helps manage where that data is when it needs to be there, and especially when it doesn't need to there so we can get new data. >> Yeah, Gus, we were talking also before camera, the folks watching that you were involved with AI going way back to in your days at MIT, and that's super important. Because a lot of people, the pattern that we're seeing across all the events that we go to, and we'll be at the NetApp event next week, Insight, in Vegas, but the pattern is pretty clear. You have one camp, oh, AI is just the same thing that was going on in the late '70s, '80s, and '90s, but it now has a new dynamic with the cloud. So a lot of people are saying okay, there's been some concepts that have been developed in AI, in computer science, but now with the evolution of hyperconvergence infrastructure, with cloud computing, with now a new architecture, it seems to be turbocharging and accelerating. So I'd like to get your thoughts on why is it so hot now? Obviously machine learning, everyone should be on that, no doubt, but you got the dynamic of the cloud. And NetApp's in the storage business, so that's stores data, I get that. What's the dynamic with the cloud? Because that seems to be the accelerant right now with open source and in with AI. >> Yeah, I think you got to stay focused. The cloud is going to be playing an integral role in everything. And what we do at NetApp as a data steward, and what George Kurian said, our CEO, that data is the currency of today actually, right? It's really fundamentally what drives business value, it's the data. But there's one little slight attribute change that I'd like to add to that, and that it's a perishable commodity. It has a certain value at T-sub zero when you first get it. And especially true when you're trying to do machine learning and you're trying to learn new events and new things, but it rapidly degrades and becomes less valuable. You still need to keep it because it's historical and if we forget historical data, we're doomed to repeat mistakes. So you need to keep it and you have to be a good steward. And that's where we come into play with our technologies. Because we have a portfolio of different kinds of products and management capabilities that move the data where it needs to be, whether you're in the cloud, whether you're near the cloud, like in an Equinox colo, or even on prem. And the key attribute there, and especially in automotive they want to keep the data forever because of liability, because of intellectual property and privacy concerns. >> Hold on, one quick question on that. 'Cause I think you bring up a good point. The perishability's interesting because realtime, we see this now, bashing in realtime is the buzzword in the industry, but you're talking about something that's really important. That the value of the data when you get it fast, in context, is super important. But then the historical piece where you store it also plays into the machine learning dynamics of how deep learning and machine learning has to use the historical perspective. So in a way, it's perishable in the realtime piece in the moment. If you're a self-driving car you want the data in milliseconds 'cause it's important, but then again, the historical data will then come back. Is that kind of where you're getting at with that? >> Yeah, because the way that these systems operate is the paradigm is like deep learning. You want them to learn the way a human learns, right? The only reason we walk on our feet is 'cause we fell down a lot. But we remember falling down, we remember how we got up and could walk. So if you don't have the historical context, you're just always falling down, right? So you have to have that to build up the proper machine learning neural network, the kind of connections you need to do the right things. And then as you get new data and varieties of data, and I'll stick with automotive, because it can almost be thought of as an intractable amount of data. Because most people will keep cars for measured in decades. The quality of the car is incredible now, and they're all just loaded with sensors, right? High definition cameras, radars, GPS tracking. And you want to make sure you get improvements there because you have liability issues coming as well with these same technologies, so. >> Yeah, so we talk about the perishability of the data, that's a given. What is less perishable, it seems to me and Wikibon, is that what you derive from the data, the correlations, the patterns, the predictive models, the meat of machine learning and deep learning, AI in general, is less perishable in the sense that it has a validity over time. What are your thoughts at NetApp about how those data derived assets should be stored, should be managed for backup and recovery and protected? To what extent do those requirements need to be reflected in your storage retention policies if you're an enterprise doing this? >> That's a great question. So I think what we find is that that first landing zone, and everybody talks about that being the cloud. And for me it's a cloudy day, although in New York today it's not. There are lots of clouds and there are lots of other things that come with that data like GDPR and privacy, and what are you allowed to store, what are you allowed to keep? And how do you distinguish one from the other? That's one part. But then you're going to have to ETL it, you're going to have to transform that data. Because like everything, there's a lot of noise. And the noise is really fundamentally not that important. It's those anomalies within the stream of noise that you need to capture. And then use that as your training data, right? So that you learn from it. So there's a lot of processing, I think, that's going to have to happen in the cloud regardless of what cloud, and it has to be kind of ubiquitous in every cloud. And then from there you decide, how am I going to curate the data and move it? And then how am I going to monetize the data? Because that's another part of the equation, and what can I monetize? >> Well that's a question that we hear a lot on theCUBE. On day one we were ripping at some of the concepts that we see, and certainly we talk to enterprise customers. Whether it's a CIO, CVO, chief data officer, chief security officer. There's a huge application development going on in the enterprise right now. You see the opensource booming. This huge security practice is being built up and then it's got this governance with the data. Overlay that with IOT, it's kind of an architectural, I don't want to say reset, but a retrenching for a lot of enterprises. So the question I have for you guys as a critical part of the infrastructure of storage, storage isn't going away, there's no doubt about that, but now the architecture's changing. How are you guys advising your customers? What's your position on when you come into CXO and you give a talk and I said, hey, Gus, the house is on fire, we got so much going on. Bottom line me, what's the architecture? What's best for me, but don't lose the headroom. I need to have some headroom to grow, that's where I see some machine learning, what do I do? >> I think you have to embrace the cloud, and that's one of the key attributes that NetApp brings to the table. We have our core software, our ONTAP software, is in the cloud now. And for us, we want to make sure we make it very easy for our customers to both be in the cloud, be very protected in the cloud with encryption and protection of the data, and also get the scale and all of the benefits of the cloud. But on top of that, we want to make it easy for them to move it wherever they want it to be as well. So for us it's all about the data mobility and the fact that we want to become that data steward, that data engine that helps them drive to where they get the best business value. >> So it's going to be on prem, on cloud. 'Cause I know just for the record, you guys if not the earliest, one of the earliest in with AWS, when it wasn't fashionable. I interviewed you guys on that many years ago. >> And let me ask a related question. What is NetApp's position, or your personal thinking, on what data should be persisted closer to the edge in the new generation of IOT devices? So IOT, edge devices, they do inference, they do actuation and sensing, but they also do persistence. Now should any data be persisted there longterm as part of your overall storage strategy, if you're an enterprise? >> It could be. The question is durability, and what's the impact if for some reason that edge was damaged, destroyed or the data lost. So a lot of times when we start talking about opensource, one of the key attributes we always have to take into account is data durability. And traditionally it's been done through replication. To me that's a very inefficient way to do it, but you have to protect the data. Because it's like if you've got 20 bucks in your wallet, you don't want to lose it, right? You might split it into two 10s, but you still have 20, right? You want that durability and if it has that intrinsic value, you've got to take care of it and be a good steward. So if it's in the edge, it doesn't mean that's the only place it's going to be. It might be in the edge because you need it there. Maybe you need what I call reflexive actions. This is like when a car is well, you have deep learning and machine learning and vision and GPS tracking and all these things there, and how it can stay in the lane and drive, but the sensors themself that are coming from Delphi and Bosch and ZF and all of these companies, they also have to have this capability of being what I call a reflex, right? The reason we can blink and not get a stone in our eye is not because it went to our cerebral cortex. Because it went to the nerve stem and it triggered the blink. >> Yeah, it's cache. And you have to do the same thing in a lot of these environments. So autonomous vehicles is one. It could be using facial recognition for restricting access to a gate. And all the sudden this guy's on a blacklist, and you've stopped the gate. >> Before we get into some of the product questions I have for you, Hadoop in-place analytics, as well as some of the regulations around GDPR, to end the trend segment here is what's your thoughts on decentralization? You see a lot of decentralized apps coming out, you see blockchain getting a lot of traction. Obviously that's a tell sign, certainly in the headroom category of what may be coming down. Not really on the agenda for most enterprises today, but it does kind of indicate that the wave is coming for a lot more decentralization on top of distributed computing and storage. So how do you look at that, as someone who's out on the cutting edge? >> For me it's just yet another industry trend where you have to embrace it. I'm constantly astonished at the people who are trying to push back from things that are coming. To think that they're going to stop the train that's going to run 'em over. And the key is how can we make even those trends better, more reliable, and do the right thing for them? Because if we're the trusted advisor for our customers, regardless of whether or not I'm going to sell a lot of storage to them, I'm going to be the person they're going to trust to give 'em good advice as things change, 'cause that's the one thing that's absolutely coming is change. And oftentimes when you lock yourself into these quote, commodity approaches with a lot of internal storage and a lot of these things, the counterpart to that is that you've also locked yourself in probably for two to four years now, in a technology that you can't be agile with. And this is one of the key attributes for the in-place analytics that we do with our ONTAP product and we also have our E series product that's been around for six plus years in the space, is the defacto performance leader in the space, even. And by decoupling that storage, in some cases very little but it's still connected to the data node, and in other cases where it's shared like an NFS share, that decoupling has enormous benefits from an agility perspective. And that's the key. >> That kind of ties up with the blockchain thing as kind of a tell sign, but you mentioned the in-place analytics. That decoupling gives you a lot more cohesiveness, if you will, in each area. But tying 'em together's critical. How do you guys do that? What's the key feature? Because that's compelling for someone, they want agility. Certainly DevOps' infrastructure code, that's going mainstream, you're seeing that now. That's clearly cloud operation, whatever you want to call it, on prem, off prem. Cloud ops is here. This is a key part of it, what's the unique features of why that works so well? >> Well, some of the unique features we have, so if we look at your portfolio products, so I'll stick with the ONTAP product. One of the key things we have there is the ability to have incredible speed with our AFF product, but we can also Dedoop it, we can clone it, and snapshot it, snapshotting it into, for example, NPS or NetApp Private Storage, which is in Equinox. And now all the sudden I can now choose to go to Amazon, or I can go to Azure, I can go to Google, I can go to SoftLayer. It gives me options as a customer to use whoever has got the best computational engine. Versus I'm stuck there. I can now do what's right for my business. And I also have a DR strategy that's quite elegant. But there's one really unique attribute too, and that's the cloning. So a lot of my big customers have 1000 plus node traditional Hadoop clusters, but it's nearly impossible for them to set up a test DEV environment with production data without having an enormous cost. But if I put it in my ONTAP, I can clone that. I can make hundreds of clones very efficiently. >> That gets the cost of ownership down, but more importantly gets the speed to getting Sandboxes up and running. >> And the Sandboxes are using true production data so that you don't have to worry about oh, I didn't have it in my test set, and now I have a bug. >> A lot of guys are losing budget because they just can't prove it and they can't get it working, it's too clunky. All right, cool, I want to get one more thing in before we run out of time. The role of machine learning we talked about, that's super important. Algorithms are going to be here, it's going to be a big part of it, but as you look at that policy, where the foundational policy governance thing is huge. So you're seeing GDPR, I want to get your comments on the impact of GDPR. But in addition to GDPR, there's going to be another Equifax coming, they're out there, right? It's inevitable. So as someone who's got code out there, writing algorithms, using machine learning, I don't want to rewrite my code based upon some new policy that might come in tomorrow. So GDPR is one we're seeing that you guys are heavily involved in. But there might be another policy I might want to change, but I don't want to rewrite my software. How should a CXO think about that dynamic? Not rewriting code if a new governance policy comes in, and then the GDPR's obvious. >> I don't think you can be so rigid to say that you don't want to rewrite code, but you want to build on what you have. So how can I expand what I already have as a product, let's say, to accommodate these changes? Because again, it's one of those trains. You're not going to stop it. So GDPR, again, it's one of these disruptive regulations that's coming out of EMEA. But what we forget is that it has far reaching implications even in the United States. Because of their ability to reach into basically the company's pocket and fine them for violations. >> So what's the impact of the Big Data system on GDPR? >> It can potentially be huge. The key attribute there is you have to start when you're building your data lakes, when you're building these things, you always have to make sure that you're taking into account anonymizing personal identifying information or obfuscating it in some way, but it's like with everything, you're only as strong as your weakest link. And this is again where NetApp plays a really powerful role because in our storage products, we actually can encrypt the data at rest, at wire speed. So it's part of that chain. So you have to make sure that all of the parts are doing that because if you have data at rest in a drive, let's say, that's inside your server, it doesn't take a lot to beat the heck out of it and find the data that's in there if it's not encrypted. >> Let me ask you a quick question before we wrap up. So how does NetApp incorporate ML or AI into these kinds of protections that you offer to customers? >> Well for us it's, again, we're only as successful as our customers are, and what NetApp does as a company, we'll just call us the data stewards, that's part of the puzzle, but we have to build a team to be successful. So when I travel around the world, the only reason a customer is successful is because they did it with a team. Nobody does it on an island, nobody does it by themself, although a lot of times they think they can. So it's not just us, it's our server vendors that work with us, it's the other layers that go on top of it, companies like Zaloni or BlueData and BlueTalon, people we've partnered with that are providing solutions to help drive this for our customers. >> Gus, great to have you on theCUBE. Looking forward to next week. I know you're super busy at NetApp InSight. I know you got like five major talks you're doing but if we can get some time I think you'd be great. My final question, a personal one. We were talking that you're a search and rescue in Tahoe in case there's an avalanche, a lost skier. A lot of enterprises feel lost right now. So you kind of come in a lot and the avalanche is coming, the waves or whatever are coming, so you probably seen situations. You don't need to name names, but talk about what should someone do if they're lost? You come in, you can do a lot of consulting. What's the best advice you could give someone? A lot of CXOs and CEOs, their heads are spinning right now. There's so much on the table, so much to do, they got to prioritize. >> It's a great question. And here's the one thing is don't try to boil the ocean. You got to be hyper-focused. If you're not seeing a return on investment within 90 days of setting up your data lake, something's going wrong. Either the scope of what you're trying to do is too large, or you haven't identified the use case that will give you an immediate ROI. There should be no hesitation to going down this path, but you got to do it in a manner where you're tackling the biggest problems that have the best hit value for you. Whether it's ETLing goes into your plan of record systems, your enterprise data warehouses, you got to get started, but you want to make sure you have measurable, tangible success within 90 days. And if you don't, you have to reset and say okay, why is that not happening? Am I reinventing the wheel because my consultant said I have to write all this SCOOP and Flume code and get the data in? Or maybe I should have chosen another company to be a partner that's done this 1000 times. And it's not a science experiment. We got to move away from science experiment to solving business problems. >> Well science experiments and boiling of the ocean is don't try to overreach, build a foundational building block. >> The successful guys are the ones who are very disciplined and they want to see results. >> Some call it baby steps, some call it building blocks, but ultimately the foundation right now is critical. >> Gus: Yeah. >> All right, Gus, thanks for coming on theCUBE. Great day, great to chat with you. Great conversation about machine learning impact to organizations. theCUBE bringing you the data here live in Manhattan. I'm John Furrier, Jim Kobielus with Wikibon. More after this short break. We'll be right back. (digital music) (synthesizer music)