Show Notes:
Stories, Dice, and Rocks That Think: How Humans Learned to See the Future--and Shape It:
https://www.amazon.com/dp/B09RMSJ1J1/ref=tsm_1_fb_lk
Transcript:
Peter Crosby:
Welcome to Unpacking the Digital Shelf, where we explore brand manufacturing in the digital age.
Peter Crosby:
Hey everyone, Peter Crosby here from the Digital Shelf Institute. What makes us so darn special from every other species on earth? And what do we do about it? According to author and technologist Byron Reese in his new book, Stories, Dice, and Rocks. It is our ability to imagine the future and recall the past, and by sharing that knowledge at an unprecedented scale, to actually shape our future, including in commerce. Rob and I had a fascinating conversation with a brilliant man who shares his optimistic view of humanity backed up by data. So, Byron, thank you so much for joining us today. I have been just consuming your books and watching your videos, and Rob and I are just so thrilled to be able to talk to you today.
Byron Reese:
Well, thank you. I am looking forward to it as well.
Peter Crosby:
We got introduced to you via your company, ScissorTail.ai, which uses an algorithm you develop for Amazon sellers to aid in the selection of winning products and overall profitability of listings. And we will get to that, but in truth, that work, however cool and useful it really is, as I went through your writings, just the latest expression of your fundamental beliefs in the transformative power of technology. And frankly, at this point, even more refreshingly, a deep belief in human progress. So, I have to ask you, why do you believe in human progress? How are you feeling right now, Byron?
Byron Reese:
It is easy to get discouraged.
Peter Crosby:
Yeah.
Byron Reese:
But I really believe three things pretty strongly. The first is that technology is this thing we created that allows us to multiply what we're able to do, and that's kind of, at its core, what it does. Much of human history has been about us not having enough. There was just never enough of the good stuff. There wasn't enough medicine for everybody, not enough food for everybody, not enough this, not enough education, not enough of all of that, because survival was just a full-time job. And we would still be on that treadmill if we hadn't learned that trick of technology, which multiplies what you're able to do. And while your body consumes a hundred watts of power, that's kind of what you are, then... A long time ago, we harnessed animal power, and then you could get 200 or 300 more watts, or 500, but then we started harnessing fuels.
Byron Reese:
And now if you live in the west, right now, you're kind of in control of 10,000 watts of power. You have you, and then a hundred copies of you all working. So, that's kind of the first thing, is that we now have the capacity at least to do wonderful things that we could not have done in the past. And that's the first one. And then you say, well, we have the capacity. Do we have the will? And that's sort of my second belief, which is, I think people are basically good. I think the vast majority of people would rather build than destroy. I think most people are good. And you can know that because... I sold something on eBay not long ago, and I boxed it very carefully. I put it in a box and in a boxing and box. I triple boxed it. I did everything.
Byron Reese:
I shipped it to the person and then they filed a complaint and said I had not shipped them the item, I had shipped them a box with a brick in it, the box with a brick in it. I didn't send them a box with the brick in it, but they disputed it. And of course I had no way to prove I didn't send them a box with the brick in it, so that was that. But you realized if 2% of people did that, or 3% or 5%, credit cards wouldn't work anymore, and that kind of commerce wouldn't work, this kind of distant commerce. So, it's like, there's really just a few people that are hanging onto the system trying to exploit it, and I think most people are pretty good. So now, we have the technology to do all this stuff. I think we basically are good people.
Byron Reese:
And then I can look across the long market history. You can go back as far as you want, a hundred years ago, 500, 1000, 10,000 hundred thousand, you pick it, and almost without a doubt, anywhere in the world, things are better right now in that place than they were a thousand years ago, or even a hundred years ago, by any measure of progress. And there are a lot of them. There's life expectancy, infant mortality, access to education, individual liberty, status of women, personal, self government, all of those. Things are always getting better. So, that's it. I think we have this trip that multiplies what we're able to do. We're basically good, and we have a 10,000 year track record of always making things get a little better, a little better in the long arc of history. And now, it's easy to get discouraged by the... And I'm not saying it's done. There’s a lot of work to do, but it's like we can do it. We can do it. And that's what I believe in.
Rob Gonzalez:
So, this is the first podcast that is going to take us back farther than we've ever gone before. Usually, Peter and I are talking about the eCommerce era, which is 27, 28 years old. Every once in a while we get frisky, and we'll talk about the long arc of retail history, which goes about 200 years when the first department store was created. But in 2018, you wrote a book called the fourth age where you talk about the only three times in the history of humanity that technology has had a true step function change in our evolution and development. And in the context of everything that you're saying right now, that humans are generally good, technology has generally made us all better off, you say that there are three major points where technology has really moved the needle, and we might be on the precipice of a fourth. So, at the risk of losing our audience to going back thousands of years, instead of just 27, do you mind walking us through that arc? And what is the fourth age that we are dangerously close to tripping into?
Byron Reese:
All right. So, let me take you back to a time when the Earth's crust had not fully solidified. We're not going quite back that far. We're going to go back a hundred thousand years. So look, all kinds of amazing technology have come along and done these wonderful things, the printing press and electricity and the steam engine, but in terms of ones that were really just, nothing was ever the same again, I think the first one was about a hundred thousand years ago, and that's when we got language. We think we got that technology because of another technology, fire, which allowed us to cook our food, and therefore consume a lot more calories. And we got language. And what you wouldn't guess about language is that the primary purpose of language is not communication. The primary purpose of communication is thought. That's how you think. And we even know this. Helen Keller's got this wonderful quote where she talks about what her life was like before her teacher came.
Byron Reese:
And she said she didn't even realize she was a thing, that she was separate from the universe, that she was an entity, and she didn't really realize there was time. And then once you had language, you can form all that in your head, and that's got to be the big tada moment for us. And I think we got it relatively recently, and that would be the first one, is we got language, because you can't even imagine life today with... Imagine this podcast if we didn't have language, it would be a whole different thing. And then that brings me to... We would just all be grunting at each other.
Peter Crosby:
Exactly. We've done episodes like that, but not this one.
Byron Reese:
The second one is when we went to agriculture. And again, it always, or it's often what comes because of technology, and it isn't really agriculture. People say we settled down to grow wheat, to make bread. There's more evidence suggesting maybe we settled down to make wheat to brew beer. That's not a joke.
Rob Gonzalez:
I definitely buy that. I'm right there.
Byron Reese:
All right. But whatever reason, we got in groups and we had these cities, and that gave us the division of labor. And the division of labor is, of course, about economics only. It says, if you specialize, you specialize, and I specialize, we're all going to be better off. And it's hard to know just how much better off, but it could be a hundred fold or a thousand fold. Imagine if you had to do everything yourself, make your own clothing and make the cloth for your, everything, but we don't have to. So, we kind of got the division of labor, and that created all this wealth. And then the third one was when we got these two technologies at the same time, just a coincidence, but we got writing in the wheel at the same time, and that would be the third age, my reckoning.
Byron Reese:
And those two technologies together gave us the nation state, which really has been the framework that history has acted out through. Because with language... I'm sorry, with writing, you can promulgate laws. With the wheel, you can enforce borders and you can have long distance transport and all these other things. So, I think those are my way of looking at the three big ones. The interesting thing is I do think we're at this fourth one, and I think it really is... We're building machines that do our thinking for us, and we're building machines that substitute for our body, robots and computers. And then you have to say, well, "If something else is thinking and something else is doing, what are we about?" And that's a question we're going to be able to ask and answer ourselves over the next few years.
Rob Gonzalez:
Well, I mean, you answered it almost at the top, which is that we generate a hundred watts of power–
Peter Crosby:
The robots will just plug into a sum collective of us. And I feel like your new book, which is called Stories, Dice and Rocks That Think, and I have to say the subtitle, because it goes to your positive thesis, How Humans Learn to See the Future and Shape It. I feel like you sort of hint at where we might be going based on what we've done. And you examine three leaps in our history that demonstrate what you call a special status to our ability to imagine the future and recall the past, which sets us apart from every other creature on earth. So, besides, once again, proving the enduring power of threes, which is my favorite thing in the world, what is this view that gives you that optimism that we can innovate our way through the biggest challenges we confront. When I think of what we're facing right now, and I know a long arc of history, I think of climate change.
Peter Crosby:
And some believe that we will figure out a way to, I don't know, vacuum stuff out of the atmosphere, whatever the heck it might be. But how do you apply that sort of ability to things of that scale that seem different than what we've been through as a race before, but maybe not? Would love your thoughts.
Byron Reese:
So, I wrote this book because my eye doctor asked me a question during an eye exam, frankly. And it was basically, why aren't there any... As I put it in the book, where are the bronze age beavers, where are the iron age iguanas? Where are the three industrial prairie dogs? Why isn't there a whole train of animals that are just behind us a little bit, coming up? Dolphins are supposed to be all smart and everything. And so I was like, why in the world... Everybody likes to say, we are just another animal, but if you look around the world, we look like aliens, the way we live and what we have compared to, say a dolphin. They don't even have... Forget the internet. They don't have telegraphs. They don't have mail. They don't have anything. And so I was like, well, what's different about us? And that's what this book was about.
Byron Reese:
And really, I got it down to, we believe in the existence of two things that don't exist, and they're called the future in the past. Animals don't. I write a lot about this, but animals don't have knowledge of the future, or even episodic memory of the past and remembering specific things what happened last Thursday, and yet we do. And what that does is not only does it allow us to plan and to see the future... And maybe we're just looking 30 seconds into the future. I could go up the back of that mountain and there might be a bear, or I could go this way. You're thinking about the future and you're running scenarios, and you're drawing an experience in the past to figure out what would happen. And that is really our thing. It doesn't even sound like that much, but what it means is that our knowledge accumulates. Every generation, a little more, a little more, a little more, it's stacking up. Whereas every beaver born today is just born into...
Byron Reese:
They're making the same dam that beavers made a thousand years ago, which is the same dam they made 3000 years ago and 5000 years ago. So, I'll skip the other two real quickly. Well, the second one was when we created probability. We learned... Sure, we could imagine the future, but could we predict it? Well, that's when we invented probability. But really, the heart of that book is really about how all throughout human history, we have not had a collective memory. So basically, the story of human history is, somebody learns something and figured something out, and then they die, or they tell somebody else, and then that person dies, or they tell somebody and that person forgets it. Who knows? all these-
Peter Crosby:
That's a dark version of history.
Byron Reese:
The reason it is because all of these things that should have been obvious in the data that we just stumble across through chance and dumb luck. I don't know how long the antidepressant Wellbutrin was prescribed for before some people were like, "Hey, I don't crave cigarettes as much." And then they were like, "Really?" And so they do a test, and then they say, "Oh, this helps people stop smoking. Let's call it Zyban," same exact drug. And so things like that, all of them are in the data, but we lose the data. I mean, we forget it or what have you. You wonder what people have figured out that has been lost. So, in our time. We have these machines that can not only handle a lot of data, but we're putting sensors on them, so they can collect data. And what they're going to be able to do is log everything, every human activity and its outcome, and now that can be frightening in a lot of ways, but just be optimistic for a moment, so that everybody's life experience becomes basically the data that makes everybody else's life better.
Byron Reese:
If I had a hundred years of data of everything people did and how it turned out, I mean, just imagine how that could inform my life going forward, and I like that. So, what we're building is a collective memory as a species, we're using computers to look for patterns in it, we're logging everything. And at some point, some point, everything you do will be logged, every word you say, every breath, you take everything you look at, what happens to your eyes, whether they dilate, everything. I'm going to end up with a skillet that beeps if there's E coli in my food, and I want that. I would want that. I want that. I want a spoon that will tell me if there's anything, but the unanticipated half of it is logging everything you cook, and then everything you eat. And as we do all of that, we're going to build this knowledge base of human experience that will make everybody's life better going forward.
Rob Gonzalez:
It's funny, the timing of you mentioning the forgetfulness of humanity and the potential for this fourth age of AI to get us through this constant forgetting. I've been rereading. The great Carl Sagan's Cosmos recently, slowly a little bit at the time, and I just got through the section where he goes through effectively, a history of astronomy, and there's a big part of it about the Greeks 2,500 years ago, where they have figured out a lot of stuff. And I just pulled up one quote from my Kindle highlights right now. The fundamental idea that the earth is a planet, that we are citizens of the universe, was rejected and forgotten. This idea was first argued by Aristarchus, born on Samos three centuries after Pythagoras, and so on and so forth. So, the sun is the center of the universe. The sun is just one star among other stars.
Rob Gonzalez:
The stars are kind of just the sun, but they're really far away. The earth is round. All of these things were things that there was a particular society that knew all of them to be true, and then it took us 2000 years almost before we had Copernicus and Kepler and the folks that kind of reinvented the ancient thinking. So, some of this stuff is just remembering the data, but some of it also, in AI, one thing that's kind of interesting is it helps us see patterns that are really, really hard to zoom out and see, like the smoking cessation, Wellbutrin, for example, right? And so I want to bring this to ScissorTail for a second, and how this applies to Amazon and ScissorTail and people that are creating product strategies. What's kind of interesting about the internet is it enables the long tail and almost anything.
Rob Gonzalez:
When Chris Anderson wrote the book, The Long Tail, he had the stat that was like 50% of iTunes store downloads were at the long tail. And yet the median number of downloads for a song in the long tail was zero. I, but it's still in volumes, 50% of the mass. If you look at a grocery store or Walmart or whatever, there's only so much shelf space. It's only covering the fat head of products, the very popular products. Whereas in theory, 50% of all product purchases in the economy should happen on the long tail, if it follows the same power law that almost every other product category, but that means thousands and thousands and tens of thousands or possibly millions of product ideas, all of which can make some money. And how do you even find these things? How do you identify them? So, walk us through exactly what ScissorTail is doing in that space with Amazon for product creation. I just love this as an example of everything that you're talking about,
Byron Reese:
No, well, thank you. So, ScissorTail... I got interested in the idea of how products get made, and how do people figure out what people want, and how do they make it? And I read that the majority, I think 72% of all Amazon sales are still somebody doing a search clicking on a non-sponsored link and buying that product. I mean, it's really a kind of basic thing, but how do you know what to make? And as I got into it, I realized most people looked at demand signals. They said, "What are people searching for?" But that's only half of it, right? Because I think there's 5,000 garlic presses on Amazon right now. And so would you make another garlic press? Well, the answer to the question is, well, I would make one if I could ring on page one of the search results, but otherwise I wouldn't. And so I started working on that problem.
Byron Reese:
And so we tried to figure out what are things that people could make that had essentially no competition, or weak and poor competition. And if that would kind of draw the market towards making things that had kind of a latent desire that built in that people wanted, but it didn't just jump out at you. And so we had to figure out a lot of ways to, we basically made a way to score listings and figure out searches for which... The products that came up are very poor or insufficient, or they don't match the query, and so they look like these areas where you can build products. And I think we identify 50, 55,000 products we think you could make and fill on Amazon and rank on the first page of search results without spending any money on ads, and that was what we did. It's taken two years. I raised venture money to do it, and took two years to build it. And it's ready. We've proven it out internally, and we have some external proof points, and that's what we did.
Rob Gonzalez:
So, it's basically, you're looking at to, I mean, to your point, there's search behavior, that's obvious, I don't know, bookmark or garlic press or whatever, where it's a known category of thing, but then there's kind of a remove of that, which might be left handed garlic press. I don't know. I'm not a lefty, but-
Byron Reese:
Exactly.
Rob Gonzalez:
Yeah. So, is it that type of use case that you're looking for? It's like the lefthanded garlic press? Literally, nobody's making them, if you make a left handed garlic press and that's the product title, you're going to be the number one search result, and you're competing with nobody, and there's enough volume there for you to make money. Is that the idea?
Byron Reese:
Almost. That's almost it, because what we did is we started that. I mean, because you can just start off by saying, "What are searches people do where none of the products come up, have the words in it of the search?" You could just start with that. But it is a little slim, because then you say, "Well, what if there's one person who makes garlic press?" And all the words are misspelled in it. Oh, no. No, they say there's two people, and the second one doesn't have any photographs, or maybe there's three, or four, or five or whatever that have these quality markers that say, this is not killing it. They're not killing it with this lefthanded garlic press. That's when we try... Because you see, there's 20 spots that are you... Well, 10 spots anyway, you're competing on. And if you can just get one or two of them, if you can just get one, you're in good shape.
Byron Reese:
So, very close to what you said, but we just put a lot of energy into scoring and all the other things come up and say, "Wow, all these lefthanded garlic presses are terrible. If you make a good one, then you'll rank on search results."
Rob Gonzalez:
Got it. Well actually, that's actually really interesting, because I don't think anyone knows exactly how many products are on Amazon, 600, 700 million or whatever. So, you're basically looking at product categories where there's a bunch of loser products as well. So, it's not just the search behavior. It's the search behavior ideally combined with existing purchases. So, it's like somebody else has already done the hard work of proving the market, even if they're doing it with a craft product, and you could just swoop in there and be a good product in a crap product category. And I would imagine that most of these categories are small enough. That product and gamble is going to look at them and say, that's like a 10 million, 10 million product category. I don't care. So, I'd assume that a lot of them look like that, but 10 million in sales is a lot of money to a lot of people though.
Byron Reese:
Right. I mean, I have a threshold for that 5,000. If you say that 55,000 products, in terms of revenue, there's about a hundred thousand a year. That's where we cut it off and said, "Well, anything below that, we're not even going to... Then we're really dealing with a lot of data, but that's exactly right. We made a 10 point kind of score that would score all the listings. We kind of assume that a new listing from a competent seller will be about seven. And so what you want are just a bunch of products that come up that are twos and threes, and threes and fours, and ones and twos and fives, and then you're like, "I'll kill it in there." And we've been able to prove it out... I was certainly worried about doing this business, because the learning cycle is very long, right? It could suggest you should make a left-handed garlic press. I'm not going to get data back on that for almost a year by the time we make it and get it in there.
Byron Reese:
And so I'm like, oh my gosh, if these algorithms need constant updating and tweaking, I'll never be able to do it. But luckily, the data is so kind of compelling that we were able to do it in just, I think two passes.
Rob Gonzalez:
So, the 55,000th thousand product, if you produced, it would make pretty reliably a 100k in gross sales. So, you could take the 10 worst products in that 55,000 product list and have a seven figure business?
Byron Reese:
That's exactly right.
Rob Gonzalez:
Yeah, that's awesome.
Peter Crosby:
And with no and with no ad dollars, is what I heard you say, Byron.
Byron Reese:
And that's the important thing, right? Because otherwise you can... And by the way, it counts that. It basically says if a left handed garlic press brings up searches that are sponsored, those slots are not available for you to win in. So, even if it's 10 terrible listings, but they're all sponsored, you can't beat them. So, it had to be that. Those are basically unavailable spots for you to compete in. But if we just said, "Oh, if you're willing to whatever you want, then..." So we had to do just organic search.
Peter Crosby:
So Byron, our listeners are a lot of the people you might think as you're sitting in the optometrist chair. Was that what it was?
Byron Reese:
Basically, yes.
Peter Crosby:
And as you're sitting in that chair and you're thinking about, well, how do products get made? What is the next great idea or next worthy idea or possible idea? A lot of our folks that do this are fighting in the eCommerce world, the commerce world, bringing products to market every day. How is it that... If someone was... You're at a bar or restaurant and you're on a trip and eating alone, and so someone saddles up next to you and you start talking about this, and you find out that it's a a head of eCommerce or product person at a brand manufacturer, how would you say here's some things you can go home, with or without my algorithm, and light up the board kind of with a way to find those ideas or be innovative in this state.
Byron Reese:
Now, that, I think there's a lot of good things you can do. I mean, we're in a world where we have an enormous amount of data, right? And I guess there's two two things. So, the first would be to find data that other people are ignoring, and use that to inform your choices. I noticed that a lot of Amazon sellers seemed to migrate to the same vendors and the same data vendors, but it's a big world full of a lot of data. I think of Greenspan. Do you remember him? Chairman of the Fed – He watched two indicators. One of them was how many cardboard boxes were being made and how many wooden pallets were being made. And the theory was that when those numbers heat up, the economy's going to heat up in six months, because in order to ramp everything up, you have to have boxes, put it all in in pallets to do it.
Byron Reese:
And so he watched those. He looked at data that other people ignored. I could give more examples about the fax machine and how the companies that developed it didn't monetize it because I think they were looking at the wrong data and all of that. So, I would say, be really creative about the kinds of data sources you get, and think outside. I don't want to say outside the box. It's so trite. But try to think of really-
Peter Crosby:
Outside the pallet.
Byron Reese:
Thank you. Things that you can glean learnings from that are going to be so far off everybody else's radar that it's really like your private data. And that would be the first one. And then I would say the second thing is, I knew somebody who made TVs, and they used to do these focus groups. It was a hard business because it's largely commoditized, right? Everybody's 45 inch TV. And they would go around and they would ask people, "What problems do you have with your computer, with your TV?"
Byron Reese:
And people would say, "I don't have any problem with my TV. I love my TV." And then they would say, "Do you ever lose your remote control?" And they're like, "I lose my remote control all the time then." So, what they've done is they are putting 10 cents worth of electronics and this TV to put a button on it that when you press it makes the remote control start playing music. Now, they solved a problem that nobody was expecting them to solve. Nobody said, "It's my TV's fault I lost my remote." And so there are all of these ways that we can now build things to solve problems that nobody would even ever imagine. And this is a bad example, because I'm just making it up off the thing, but I've always wondered why... No, that's not even a good example. Nevermind. I'll leave it at that. Solve problems that nobody expects you to solve. I want the one with whatever.
Peter Crosby:
And I feel like what you're talking about is solving for experience, thinking of the totality of an experience around a product, or that's at least part of what you're talking about.
Byron Reese:
I think that's even better than how I said it, I will point out. Yes, that's exactly right.
Peter Crosby:
Which I think is, in the future that we are headed towards, and even now, experience is so much of what people are paying for, and that requires really understanding your customer. And then as you just pointed out, not necessarily what they would tell you, but what they feel or what enrages them, asking those things around.
Byron Reese:
And another thing, this is not easy stuff, honestly. It's really hard to come up with things that people would like and make them awesome and do them right, there's so many steps, and yet the difficulty of the task, I think, always seems to be, contrary to a lot of business books that seem to suggest that you can be successful in business if you just remember these five simple rules, these nine simple rules about how you should, just basic business axioms. And if you just stick to those, you're going to be okay.
Byron Reese:
And I don't believe that anymore. And what's terrible about it is, when you fail, as I do, and I'm sure most people do, you feel like twice it was supposed to be easy. It was supposed to be really easy to do. But what I realized along the way is that business advice almost always has an opposite that's supposedly equally true. People tell you, "Look before you leap." That seems like good advice, but they also tell you, "He who hesitates is lost." Well, that's exactly the opposite piece of advice. Or, a bird in the hand is worth two in the bush, but nothing ventured, nothing gained, right? They're exact opposites. If some company changes with the times and they go out of business, people are like, "Yeah, they didn't stick to knitting. They should have stuck to the knitting."
Byron Reese:
And then if they stick to the knitting and they go out of business, they're like, "They should have changed with the times. They should have changed..." And what I kind of realized is that business is not about learning a few little rules. It's knowing when to apply the rules that you know, and that's a much harder thing to do. So, I would just be... I think just an upfront admission that while we try to steal things down so that busy people can absorb them, I never want to forget that this is really, really hard, what we're all trying to do, and very difficult.
Rob Gonzalez:
This is the Ben Horowitz's book's title, The Hard Thing About Hard Things.
Byron Reese:
Oh.
Rob Gonzalez:
I mean, it's meant to try to convey what you're getting at, which is, there is no easy way when you're building something new. And I think a lot of people want to believe... In America, you want to believe there's an easy button to all kinds of problems. You want to believe there's an easy button to losing weight. You want to believe there's an easy button to starting a business. That's why you got all these meme investors and crypto and speculators, and there's an easy way out. At the end of the day, there's not an easy way out. There's a lot of different hard ways and you have to find one. So, yeah, strong agreement from me.
Peter Crosby:
Well, Byron, thank you so much. I mean, as we think about these creators, who are our listeners, and are in this position of... Actually, they probably chose eCommerce, or eCommerce chose them and digital chose them because they want to do the hard things, because that's fun and frustrating and building. And so I just can't... Well, I guess I can recommend your new book enough. I feel like if you're kind of looking for sparks that might give you a chance in those quiet moments to make a leap, I think Stories, Dice and Rocks That Think is something that you should pick up, and we'll have the link to it in our show notes. And Byron, we really appreciate bringing your brain and your heart and your optimism to the podcast. It's been a joy.
Byron Reese:
Thank you so much for having me. I would love to come back.
Peter Crosby:
Thanks again to Byron for sharing his viewpoints with us. The link to his new book is in the show notes, or search Byron Reese, on Amazon. And assuming he eats his own AI dog food, it should come right up there on top of listings. Become a member at digitalshelfinstitute.org for all the latest coming out from the DSI. And thanks for being part of our community.
