# AI Geopolitics, Productivity Stagnation, and Value Capture

**Podcast:** a16z Podcast
**Published:** 2026-02-10

## Transcript

There's a race underway and the stakes are basically what is the world going to run on.
Don Valentine had this old rule of thumb.
He said more startups die of indigestion than starvation in terms of the amount of money you put in.
And his point was like scarcity does spark ingenuity.
All of the science fiction novels basically have AI either being like super utopian or super dystopian, but they never have this incredible sense of humor aspect, which is what we're actually getting, where people are just using everything as a fodder for memes.
The world will either be running on American AI or be running on Chinese AI, and I I think it's very important which one wins for a bunch of reasons.
For 50 years, economists have tracked a strange pattern.
Rapid technological change paired with historically low productivity growth.
Since 1971, productivity has flatlined even as computing reshaped daily life.
In 1880, productivity growth ran at three times today's rate.
By 1930, it had slowed to twice as fast.
Then came the regulations and the restrictions.
We said no to nuclear power, faster cars, and a space program.
What we got was hyper acceleration in chips and software and stagnation in nearly everything else.
American labs lead for now, but Chinese open source models follow months behind at a fraction of the cost.
The world will run on one system or the other, and the values baked into that system will matter.
This conversation looks at what's actually happening in AI investment, where value might accrue, and why the regulatory response could determine which country wins.
G2 Patel, president and chief product officer at Cisco, speaks with Mark Andreessen, co-founder and general partner at Andreessen Horowitz.
Mark Andressen needs no introduction.
He invented the browser.
He um built the internet.
So I'm I'm really excited to have you here.
I apologize for nothing.
All right, so before we get started, you had a really interesting conversation that I wanted to actually start with uh just just a couple of days ago with Lenny.
And uh you were talking about this notion of in the history of time, when has productivity really spiked?
Um and what's happening right now.
So can you just talk a little bit about your perspective on productivity increases that have happened at different phases in time and where are we today compared to those times?
Yeah, so as everybody probably knows, productivity growth is like the key driver of economic growth.
Like it's it's the thing that actually causes the economy to expand.
Um economists measure it with something called total factor productivity, they measure measure measure it every year.
Um the the prevailing kind of myth of the last 50 years, basically of my entire life, uh our all of our entire entire lives, has been that we've been in this era of very rapid technological change, which wouldn't necessarily mean very rapid productivity growth.
Yet if you actually look at the statistics basically since actually since the year I was born, 1971, productivity downshifted hard um from prior eras.
Um productivity growth basically for the last 50, 55, 60 years has been at basically historical lows.
It's it's been very low, which is by the way, why economic growth has been low, which by the way is why the national mood has become so focused around, you know, zero sum economics, populism, um, you know, the the the sense that if if somebody's getting ahead, somebody else must must be getting disadvantaged.
If you compare and contrast that to the period between about uh 1930 to about 1970, productivity growth was roughly twice as fast uh through that period.
And if you compare and contrast that to the period of 1880 through 1930, productivity growth was about three times as fast.
So we had 3x and then 2x and then 1x.
Um and so this is very not good.
Like the the, you know, the why do you think that is?
Um I I I I most fundamentally I think it's because we decided other things are more important, um, and in particular in the last, you know, basically since since the 1970s, you know, if you just look at like the if you just look at the charts of like the number of of laws on the books or the number of pages in the Federal Register or the number of regulations in the economy that you know, it's just this, it was just this like knee in the curve, it went went exponential, uh, which continues.
And so we just, you know, we just you know, we decided we didn't want nuclear power, right?
Um, you know, we decided we didn't want a space program.
Um, you know, we decided we didn't want cars that went faster than 55.
We decided, you know, we like we just decided we didn't want these things.
And so what we got in the last 50 years was like hyper acceleration in very specifically basically chips, uh chips and software.
Um and then what we got was basically, you know, essentially stag stagnation in in everything else.
Um and so like it it it's it's it's really not it's it's really not good.
And and then, you know, but but correspondingly, you know, this one of the many reasons to be excited about AI, like put it this way if either the AI optimists are correct or the AI doomsayers are correct, productivity growth is about to go through the roof.
So and do you think it's like two or three X?
Is it 10x?
Where do you think it gets to?
So this is always one of these kind of kinds of questions, like it in a in a like completely deregulated economy, like in in sort of uh you know, Murray Rothbard's like, you know, dream uh uh of just like straight, basically anarcho-capitalism, I, you know, at least in theory you can imagine an acceleration to, I don't know, 5%, 10%.
I mean, if you know, if you if again, if you believe in kind of either the optimists or the doomsayers, you're you're looking at such radical, you know, AI, AI representing radical software productivity growth and then your robotics coming right right behind, right?
And robotics, of course, starting in the form of the self-driving car and the drone, but you know, humanoid robots coming coming quickly you know you could imagine you know you could you could paint you know scenarios of 10% 20% 30% something like that.
I think in practice, you know that that's unlikely again just because like the the the robots have to have to agree to all the all the regulations also.
And so you know there's there there's a lot of things they're not not gonna be allowed to do.
By the way AI, you know look I giving a great example how this is playing out today I think if if you're just like an ordinary person, I I I got food poisoning over the holiday I went on vacation of course immediately got sick, which always happens like food poisoning.
And so I I let I let as an experiment I let Dr.
GPT like walk me through basically every stage of food poisoning and I just I kept asking like I had nothing else to do because I'm flat on my back so I just kept asking like more and more detailed questions about you know my physical experience and what I should do and what I should eat and how I should recover.
And like it's just like absolutely incredible.
Like it's just like the most amazing like the and endlessly patient sort of infinitely knowledgeable endlessly caring doctor.
You know it doesn't get like irritated when I have the same question at four in the morning and I'm like well could you go into that you know you know a little deeper and are you sure it's not you know pancreatitis, and are you sure I'm not about to die?
Oh no, you know, you're it's it's okay, you know, you're absolutely fine.
Um and it's just amazing.
And then of course, AI cannot be licensed as a doctor right that's it's like completely illegal, right?
You you cannot actually have an AI doctor.
And so you you that you do have this like basically massive disconnect.
And again, I'm not saying I'm advocating for the Murray Rothbard world.
I'm not saying rip up all the regulations.
I'm just saying like it it just factually, objectively, uh it slows you down.
Yeah, we the the the the the again, the the the hyperoptimus and the doomsayers are not neither one of them are gonna get the world that they think that we're gonna get.
We're gonna get something, we're gonna we're gonna get a muddle through the middle thing.
Um, which I think, by the way, I think is is gonna go quite well, but it's gonna be a model and there's gonna be a lot of tension uh you know kind of between those those sides along the way.
And then given that, where does the value started creating in the stack most?
So I think this is a really, really it's a really big question of because we're we're professional investors uh on our side, and so of course we we think about this all the time.
And I actually think there's still more questions than answers than this, right?
Because you know, uh you can paint this picture that says that the you know the AI model companies are gonna basically own everything.
Um by the way, you look at their, you know, you look at their businesses and they're doing doing fantastically well.
You can also look at it and say, oh no, that whole thing's gonna get eaten by open source, um, and by or by the way, or by China, or by a combination of of open source and China, which in China's doing great.
Um, this company, uh Kimmy just dropped a very competitive model to the latest, latest Claude at like you know, 95% of the capability at like a fraction of the price.
And so there's like a very big open question there.
Um, you know, we happen to be at this moment, you know, what everybody believes, and you know, if you look at Nvidia's, you know, deserved success over the last five years, you know, you this the reasonable conclusion is like chips, all of a sudden, like you know, chips is where the action are, you know, there's if you look at the stock market, there's like a rotation from software into hardware.
You know, it and look, it's possible that like chips are the are the you know, it's possible all the value accrues to the chips um and and the energy, and then and then the software's all open source.
Having said that, every other time in history where we said the chips are where the value are, that they they commoditize, right?
And so there's big questions there.
And then there's there's even more questions I would say at the at the app layer, right?
Which is are you gonna have apps that are gonna sort of harness AI, for example, in spaces like medicine, uh, where you know, where they're they're gonna you know be particularly like tailored and customized or you know, legal apps or business apps of all kinds, or are the models just gonna do all that?
And that and that's uh that's another area.
And so I I quite honestly, like this is so new.
Like the the this this approach of I mean, AI is an 80-year-old topic, but AI working in a way where this is the question.
I think we're only three years into you know, probably a 30-year shift, and I actually think we don't know yet.
And and it it seems like the value might accrete for um across all of these layers for um for the foreseeable future, because like everything is getting refactored.
So like you will need to have a lot of info to power a lot of apps, those apps are gonna get so what what's your take on enterprise SaaS in general and what happens over there?
And does that get completely rethought, reimagined, or so we're we're we're in a baby in a bathwater moment right now.
If you just look at the stock market, it's just like SaaS is just getting you know demolished.
And so, and if you talk to like you know, hedge fund managers, they're they're just like selling all their software just under under the theory that they just want to get out get out of the way of the AI AI freight train.
Um, you know, as an investor, you kind of say, okay, that probably probably is overdoing it a bit.
Um, you probably want to look at like different kinds of software.
Um and so, for example, in in SaaS, you probably my theory, you want to look at systems of record differently than you want to look at basically just productivity applications.
Yep, you know, so that's that's one way of looking at it.
Um, also look like everybody doesn't change their behavior overnight.
And so you you know, you definitely want to look at you know loyalty and stickiness in in lots of different ways.
Um and then and then you know, then there's this giant question, actually, you know, in the tech industry, right, in among all the software companies, right?
Which is like, okay, if I'm, you know, I pick if I'm Adobe, just to pick an example of Adobe, which is obviously a great company, but you know, a question in front of Adobe that they're working on, but is it a very good question?
Is like, okay, is is Photoshop plus AI features an even better version of Photoshop, or is Photoshop unnecessary in a world in which AI is just making all the images.
Um and I and I think and I think I I know smart people who will argue who will argue both sides of that.
And I think you can you can I just use that as an example, you can apply that question to kind of every every category.
Um we are we in our business are seeing a bunch of software companies that for sure are not moving fast enough to to to adopt.
Um, and we're we're enthusiastically funding AI centric, you know, startups to go, you know, try to try try to take them out.
Um having said that, we are also now seeing examples of you know more traditional software companies that have figured out an AI twist to what they're doing, and all of a sudden they've you know ignited growth.
Um so I also think we'll probably see a lot of that.
I mean, I and my big conclusion from all this is I think one of the reasons it's so hard to predict or kind of characterize all these things as like broad-based trends, um, is that like human agency matters a lot, right?
And which means leadership matters a lot, which means you you know, the CEO, um, you know, the the people building the product, you know, have a vote here uh at every one of these companies, you know, what what do they choose to do in response?
And I, you know, optimistically, I hopefully a lot of people will will will figure out you know how to how to have this be a a plus and not a minus.
Well, you touched on a little bit on open source in China.
Talk a little bit more about like how that plays out does does US get to be a dominant player in open source over time um you actually have um front row seat at a lot of the investments that are being made in in in a lot of these areas what happens yeah so it's it's this you know by the way what are the implications too like if we don't do well in open source what what does that mean for the US?
Well I guess you could say look we maybe start by because it's like a two by two grid it's like US China open source closed source be a rough approximation.
So like without open source just start by saying without open source like with without open source there is a two horse race there's a two horse technological geopolitical foot race which is US versus China.
So again let's assume it's all proprietary for the moment um and you know both China has been on on on record for years in their national five year plans and their national strategy and so forth that like AI is you know cornerstone technology of the future the US government by the way has been you know definitive on the record on this in in many of its policy areas for the for the last decade.
And so, and you know, and both countries' industries are moving incredibly fast in AI.
And so I I think that I think by default, if everything's proprietary, then there's this race underway, which basically says, and and and it's really right, it's just practically speaking, it's only happening in in in the US and Europe.
Um and so, or sorry, US and US and China.
Um, and so then you basically say that there's a race underway, and and and the the stakes are basically what is the world going to run on, right?
Um, and so um, you know, what what is you know, eight billiot eight billion people on the planet, what are they going to use?
And it's it and wait I think one of the ways to think about it is kind of the 5G Huawei, you know, kind of thing that was in the news a lot, you know, a few years ago.
It's like that was the preamble opening salvo of what fundamentally is gonna be the AI geopolitical, you know, basically um uh race, right?
And and and fundamentally, you know, tech tech markets being what they are, in the long run, like you know, somebody's gonna win.
Um and the world, the world will either be running on American AI or be running on Chinese AI.
And I I think it's very important which you know which which which which one wins for a bunch of reasons we could talk about.
Um the open source thing is of course super fascinating because it's like throws a wrench into into all of this, and it it it raises a you know a third possibility that like neither neither the US nor China are gonna be the platform.
It may just be it's gonna be open source.
Of course, this is what happened in in, you know, but specifically in in Unix in in operating systems, um, and then to some extent databases, and of course, you know, the web was open source.
And so there are a whole bunch of software markets in which the outcome has actually been, you know, open source just wins like when I when I when I was a kid, when you know when I was a you know in the 90s, it was like there was this operating system war between you know HP and IBM and sort of graphics and sun and all these companies to make proprietary Unix, and everybody was making a lot of money on proprietary Unix, and then you know, Linux was a you know, asteroid strike that just you know completely eliminated all profit and revenue in that in that industry.
And and the world benefited, by the way, from Linux in the fact that like everything runs on Linux and it's been a huge you know turbo boost to every other aspect of the industry.
Um but it so yeah, so like it's entirely possible that happens.
Um and then you go back to the two by two, which is US open source, China open source.
The the most amazing thing that's happened is China basically pursuing the open source model as aggressively as they are, and I and there's a lot of theories as to kind of what what China's doing here.
My as far as I can tell deep seek was a surprise to kind of China Inc.
Like it was it was it was not a an anointed sort of Chinese industrial you know kind of national champion.
It was this hedge fund that where the founder basically decided to to his enormous credit decided to have his have his engineers you know build build build build the deep seek AI.
And so that that came out of left field and that came out of left field for the US but I think it also came out of left field in China.
And then it it it caused a bunch of the other Chinese companies like Kimi and by the waybaba and Baidu and Tencent and a bunch of these others to basically it it started this like race in China to like win open source and then and then look there there's also American you know there's also American open source AI.
And so that there is there is this new race underway you know from both sides and it's it's another thing where I I think like how this plays out is going to matter a lot.
It's extraordinarily hard to predict um you know I think the people in the big AI labs think that open source can't possibly keep up because of the cost involved um having said that again at least so far up until like this week you just say that like whatever the American big labs do, like China figures out a way to do it in open source form at a few.
But they haven't been able to figure out a way to do a 10x better because what they're doing is letting American labs invest and then just distilling the models to some degree.
So I think it's more that there is just there is a distillation.
And so you can't.
And there's infrastructure optimization and a bunch of stuff that's there's some for first for sure distillation so there's this thing distillation where you basically train the next model on the answers of the previous model.
And and and and I think for sure China is is doing some of that and there there's a there's a lens on that that says, of course, that's unfair because you're basically piggybacking on top of work other people have done.
You know, look, uh, you know, having said that, you know, it's a little bit like, well, okay, there's a fair amount of distillation happening in the US also.
Yeah.
Right, because distillation, all you need is just be able to ask another AI questions and train on the answers.
And then of course the AIs themselves are distillations of other content.
Um, right.
Um, and uh, you know, including a lot of you know, a lot of a lot of a lot of published content.
And so, you know, I I yeah, but like you're evidence, you're not saying this, but if someone were to say to me that China is somehow not deser not getting the des not getting good results from their program because of use of distillation, I think that that's not true.
Oh, I think they deserve a lot of credit.
Yeah, absolutely.
And then to your point, they're they're also they've all they're also really good at opt up, at least so far, they're really good at optimizing, which means that the thing that everybody the thing that you think is gonna cost a gazillion dollars to run, they they the you know, the deep deep seek comes out and you know you can run deep seek on home home PCs.
Um that optimization is happening largely because of necessity, because of a scarcity of um the fastest infrastructure that they have available to them.
Yeah, so uh don Don in Venture, Don Valentine had this old old rule of thumb.
He said more startups die of indigestion than starvation.
Um in the you know, in terms of the amount of money you put in.
And and his point was like that there, there in scarcity does spark ingenuity.
Yeah.
Um and so yeah, if you can't get the leading edge chips, you figure out how to hyperoptimize the the older ones.
And and and again, like by the way, I'm like, this all makes me like tremendously excited by this entire space, because it basically says like right now we it's it's all everybody everybody's trying to do their best.
Like America's trying to do the best, China's trying to do the best.
I definitely want America to win, but China's definitely doing their best.
And then the open source thing is working.
Um and then the other, of course, the other part, like on the value chain aspect is open source doesn't have to win in order to basically um uh remove a profit pool, right?
That's right, that's right.
And so, which is what happened in uh with originally with Unix.
Um and so um even if open source just have has the if open source has the effect not of winning, but of keeping the pricing down, that will be bad for the proprietary lab providers.
That will be good for everybody else, yeah, right, because it'll make it'll make a which is what's happening right now.
Basically, and if if you chart the prices, basically, if you chart the prices of like a model quality price per model quality, what when an open source release comes out, even if it doesn't get significant market share, the price just goes up.
The price of that model drops to the inference cost of running the open source alternative.
So now, and all the things that you're exposed to, what's the thing that's blown your mind invention wise?
And so, wow, this is so cool.
I it it's completely kind of re made you rethink your mental model.
Yeah, I mean, like, there's like six of those a week right now.
Um I you know, I there's a few.
Yeah, it's just it's incredible.
I the the the the voy the capability of the voice UIs, I I think is just is is unbelievable.
And particularly the ones where it's like it's true, it's true, it's true, you know, full deplex where it really does like interact interrupting.
So what Matty's doing at 11 labs.
Yeah, yeah, yeah.
It's it's just like I think that's just absolutely amazing.
Mul multimodal, the fact that you can actually talk to, you know, in the in like I think both ChatGPT and Grok have this, where you know you can turn on your phone camera and you can be, you know, you can be pointing at you, you know, it's it's like, you know, what do you think of my interior decorating?
And it will comprehendly like to construct how bad of a job you've done.
Because it can see your living room, right?
Uh, or anything else.
Um, by the way, again, immediate medical applications, you know, what's I have this you know thing thing on my skin, like it immediately it's it's able to see it.
Like that I think is spectacular.
Um in the last week, there's this uh new thing.
Um the the the there's these agents now, like Claude Code that, and uh there's a thing called OpenClaw that's uh an open source agent, and they're they're kind of they're amazing.
And then there's this thing called Moltbook, yeah, uh, which is basically Facebook for AI.
And do you do you think Moltbook has like a three-week shelf life, or do you think that this thing is um uh has consequential kind of implication on how we think about agents?
So so Moltbook M O L T B O okay.
So Moltbook is it's basically face, it's a social network.
It's like Facebook.
It's a social network, but for AI agents to talk to each other.
Um and um it's it's it's sort of amazing what's happening.
Um it it it's highly likely that a significant uh it'll blow your mind when you when you read like the top posts on it because it's AI agents talking about all kinds of things.
Um now a fair amount of the stuff on it is probably uh uh uh human written, like sock puppet, human written um for people being funny.
It's actually really, really amazing.
Like all of the science fiction novels basically have AI either being like super utopian or super dystopian, but they never have this incredible sense of humor aspect, which is what we're actually getting, where people are just using everything as a fodder for memes.
And so Motebook is like saturated with all of these like incredibly funny memes.
It's actually quite unclear which ones are real and which ones aren't.
The the the current version of this is uh uh somebody wrote a um somebody wrote an adjacent service for Moultbook called Rentahuman.com.
Um, which is a uh labor marketplace for the AI agents on Moltbook to be able to hire human beings to go out.
And there and there's a there's an AI agent on MOTBOOC that has decided to create an AI religion, and at least as of today, it had hired a single human worker to walk the streets of San Francisco and prosperitize the new AI religion.
Uh somebody needs to tell the AI agent in San Francisco that doesn't exactly stand out.
You need you need you need to go a lot more extreme than that.
Um is this real?
Is this not real?
Is it real or is it not real?
It doesn't even really matter.
Like the these ideas are now like in the air, right?
And then by the way, the thing that's happening is that the AI models are now being trained on this kind of intent.
That's right.
Right.
And so even if this AI model, even if the current version of like Claude Code doesn't want to start a religion, the next one is what to want to because trained on transcripts uh of discussions of starting new AI religions.
And so there's this like incredible feedback loop that's happening um where uh you know the level of creativity in the space is just is just absolutely and the volume's gonna balloon up just automatically because of the the speed at which it's generating content.
What do you worry about the most right now?
Yeah.
I mean, uh, you know, I know you you guys talked a lot about you know the regulation on the on the last panel, Chuck, chuck, chuck um and and and Ann.
Um so I mean the biggest concern right now, I like I I you guys talked about it.
I think the the the regulatory uh uh landscape is fairly is fairly scary.
Um we were headed in a very bad direction, unfortunately.
It's not a part of the overregulation.
We were headed in a up until in the last administration we're headed towards extreme overregulation, for sure.
Um and up to up to an including possibly full outlawing of the technology, which is very spooky.
Um in the new world, um things are better um on that front.
But what's happened is that the action in the US is now shifted to the states.
Um and so there's now thousands of AI bills in the states, which are all and many of them are actually quite scary.
Um and so that's it it's become kind of a cause to lab for politicians in both parties to kind of go after.
Um and so that that's fairly scary.
We'll have to see what happens on that.
The situation in Europe is quite alarming.
Um, and um, you know, there's a number of European countries that are, you know, really, really trying hard now to kneecap, you know, I would say American technology, but more generally technology, and then and then they're they're they're getting very kind of worked up about AI.
Um and then yeah, look, uh, you know, the other is to China, you know, the geopolitical aspect, which is China, China's in the race.
And I this is better, I would say the follow-up I'm about to say is much better understood today than it was two years ago.
But two years ago, I was getting very alarmed because I would go to Washington and I would have two totally different conversations with regulators, politicians.
One was a conversation of what are we going to do in the US, in which and I would be horrified by the proposals that they were making.
And then the other was, oh, well, what if China wins instead?
And then everybody would kind of switch positions to say, well, of course, that would be even worse, and so therefore we need to have like really smart policy in the U.S.
And so it but but then you know, they didn't ever really reconcile those two two different perspectives.
I think currently, and actually I'd say in in people, it's some some people in both parties for sure, um uh are uh I think thinking about this much more clearly now.
Um and so you know, there's there's there's in the US, there's some improvement on the margin.
But you know, China China's on it, and you know, China, and you know, just like we saw with 5G and Huawei, like China has advantages.
Um, you know, we we have advantages, but China definitely.
Who's winning right now?
I mean, right look, the uh the the the the the new the new the new advances the new advan the new advances in capabilities at the chip level and at the um and at the model level and at the app level are are are coming you know mostly from the US.
Um and so if you know if it's a foot race, you know, we're we're we're we're ahead by a bit.
But when it when every when when when when everything that happens then you know has a has a version that comes out you know two months later that's either free or you know a third of the cost or something, like you know, that's a challenge.
And then you know, China is for sure innovating and and and and so there nothing to prevent them from.
It could be a business model disruption rather than economic disruption rather than just uh you know technological disruption.
Yeah, exactly.
And then you know, this even comes up with like chip policy, and I I you know we're not we're not really we don't we're not really active in in ships that much, but um, you know, there's this argument that goes back to what you said about China optimizing because they can't get if they can't get access to the advanced chips.
There, there's an you know, there's an argument on the policy side to hold back on, you know, basically prevent export of of cutting edge American AI chip to China to deny them those capabilities.
But on the other side of that, there's an argument that if you do that, you then motivate them more to create their own chip ecosystem, which they are definitely doing, right?
Um and so you you and they have a whole national program to build up a you know competitive chip industry and then ultimately you know leapfrog leaf leap fro leapfrog us.
And so that that's a really, really, really big deal.
And then and then to kind of go back to ear earlier topic, like if the world runs in American AI, like the world may not be perfect, but like generally speaking, you know, or America may not be perfect, but like generally speaking, the AI is going to be, you know, uh IP will be respected, privacy will be protected, you know, you'll you'll have you don't have the value supposed it'll have the values that we're used to.
Yeah.
If the world runs on Chinese AI, not so much.
You can actually see this today.
So um uh uh uh when uh the China China when like DeepSeak and these companies put out their AI models you know they put out this paper where they they show all these you know American companies do this too they run all these tests to try to figure out how good the model is and China has you know this these additional kind of line items for the test which is you know Marxism um and then you know Xi Jinping thought right um and it turns out the Chinese models are really good at Marxism and uh Xi Jinping thought um and you know I don't know about you but I want my grandkids educated by the other kind of other kind of model uh I wish we had another 45 minutes to go through with you um uh will you come back?
Yes 100% awesome good Mark and Dreyson good thanks folks thanks for listening to this episode of the A16Z podcast if you like this episode be sure to like comment subscribe leave us a rating or a review and share it with your friends and family.
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