In this episode of The Tony Robbins Podcast, our host Ana is diving into artificial intelligence and machine learning - phrases that are getting tossed around a lot these days - but are shrouded in mystery and misunderstanding.
Helping demystify the hype and break down the pragmatic benefits of AI is Ben Lamm. Ben is the CEO of Hypergiant - a Dallas-based startup that Tony himself invested in! They’re working with big brands and businesses to bring in technology to solve real business problems. For example, Hypergiant recently teamed up with TGI Friday’s to create an AI-powered mixologist, appropriately dubbed Flanagan. Flanagan offers the customers the experience of personalized drink recommendations while simultaneously collecting more data about their preferences. It’s a win-win that enhances customer connection, and ultimately, customer loyalty.
Ana talks with Ben about these types of practical applications of artificial intelligence and machine learning, and we explore other opportunities for businesses to leverage the tech to best meet their customers’ needs. Because most industries are using outdated practices. And as we enter this new era of AI solutions, it’s time to initiate change and encourage your team to start thinking forward.
This is an unofficial transcript meant for reference. Accuracy is not guaranteed.
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Hey guys welcome back to the Tony Robins podcast, I'm any York editorial director for Robins research this week for die.
Into artificial intelligence and machine learning, phrases,
but are getting tossed around a lot these days. But how much are we really understanding?
helping me demystify the hype and break down the pragmatic benefits of ay. I is Ben Lamb Dennis,
the ceo of Hyper giant, a Dallas based start up that Tony himself invested in their working with big
Franz and businesses to bring in technology to solve real business problems. First
hybrid giant recently teamed up with tv I Fridays to create this a high powered mix all just a properly.
Planning in finding an
offers: customers the experience of personalized drink recommendations while simultaneously collecting more data about their preferences. It's a win, win!
because it enhances customer connection and ultimately customer loyalty. I talk with ban about these types of
practical applications of artificial intelligence and machine learning, and we explore,
opportunities for businesses to leverage the Tec to best meet their customers needs because,
most industries are actually using really outdated practices and asked
under this new era of a isolations, it's time to initiate change and encourage your team to start thinking forward, while combating the tunny Robins podcast yeah things were haven't. We
here, of course, so we're really excited to learn about your latest company called hyper giant which Tony Robins isn't investor in its worthy things, he's most passionate about in the coming year. It launched with this goal of bringing the power of a I or artificial until
hence too big brands, but this is a space that people really don't
I know a lot about and I love it if you could just tell us more about the company what it does and how we should think about artificial intelligence, yeah, so big question Watson back their hybrid
giant. You know colleagues started out of this, need where we ve seen Kennedy
rise and fall of artificial intelligence, no relief,
a slight decade, really where people are starting to look at how we use machines and how can we leverage,
an interesting ways where machines can take all of this data and actually start looking for inferences looking for new correlations and actually not just automating processes, but also giving humans better data for them to act.
Make decisions, and so was interesting for us. As we know, we seen Watson, we seen all these kind of big systematic, greater start to go into the space, but you know I I is turned into comes. You know this feeling of like big
data to point out, as I don't have your member remember like no five or seven years ago, where everything was big data,
Everything looks like a big. You know when everyone had a big data, hammer Javary thing: yeah everything was a big data nail in so it cannot started or MIDAS,
where people are like I need I. I have to have a eye, but I dont think they actually knew what that means in when they started.
The search you know thinking about it and they started talking to Phd. They start talking to some of these big
demeanor graders, it really turned into okay. We got to restructure all of our data, we have to ingest all of our data and then we can start to see what inferences we can get
and it just sounded a little magic box. He had sounded a you know. Super hyper sounded super exciting
It's like on one side. You ve got this world where
I'm gonna know people are saying in the news. They know I'm gonna destroy everything you ve got people, I e launder, saying a eyes: the devil. Then you got other people that you nurse.
You know Isla the earth that other we were saying that you I could take people's jobs, and so there's all these emotions about it. But there's this excitement about its content. This, like weird space, where there's incredible acceptance of a about it. People are super excited about kind of what the potential could be.
But there's still just this kind of mass confusion in so I love these all it like an emotional charge because that something at our islands of as everybody knows that your driven by emotion and you people. Ultimately, we think that were rational creatures, but ultimately we buy food.
Links, not things ray, and example. Emotion drives action like nothing else and it.
I thought it was happening to you said in an interview that a eyes a drug, that nobody knows what it does, but everybody is trying to get it. Everybody feels that they need it, but nobody knows exactly what to do in terms of how to get there and who to hire and although logistics, so it's like you know, making an emotional decision you I need this, but you have no idea about how exactly into we it's funny. But you say that a new that about you know
its content, but you know we always say that you know pad in great ideas are really import but also passionately cells. The oceans are obviously very passion about space, but we saw this opportunity
and we're like ok, a eyes confusing its nebulous, it's gonna dark. How can we cannot be this? You know guiding light for the fortune, five hundred and then how, in in being that the space is so big. How can we create something? That's you know really, you know impact, but we also know has the opportunity to work or start ups as the opportunities to look at market trends and bill products out and then out, and then also think about how it can serve as some of these
no big fortune. Five hundred and in the end, even smaller companies and get them can have into a I encountered, started demons
If I may, I and II high pay high in really just gonna roll up our sleeves and say: ok, I'm not this magic thing that people through around its actually just a tapestry of technologies and it's a different way of looking at data right. So it's like you know, I mean a butcher. This quote because it's not an, I didn't do this for their some research work ever like a thousand
I'm spin the news it's like every year now, he'll, like humanity like collects more data than ever
before and like the history of all human kind, including the year before, and so with all of that data you know a eyes really just away. They can, if you start to use algorithms,
to use technologies where we can sort of sift through data. Look correlations that you mean
had been there, but you knew the technology wasn't in a place where we could. Actually, you know, find it. No one of my favorite
You know things about me. I want my favorite stories was. This was, I think,
Last year, where NASA announced we found five new planets, but they didn't go out and, like you build out- and you tell us, go over levers new technologies, I think they work with Google and just literally
use deep learning it and machine learning technologies to go through tons of data that they had, that was factually five years old, defined its planet so that they take the decision,
read these planets was there and so were sitting on our answers? We just aren't exactly ere it. So it's a we try to its. We thought when we start a company that you could really
a pragmatic when it comes to air. I, where we could demystify
where we can go in to like a company like
Gee I Fridays or some
air or whoever and say no, you don't have to spend
twenty million dollars and a three year data region
Archery data scrubbing project. Just to get to the point where you know you can now start to experiment like lives.
We'll get. You know predicted data analytics. Let's look at machine learning, let's look it a bite size pieces in like really crawl, walk Rhine, because that's where you gonna start to see true
justification around, you know that our allies of these technologies and then you can start investing more right. So it's like how can we be really smart in and pragmatic and say we don't need a magic. I
what's that, can transform our entire company you're companies finery, you know you poor, you wouldn't be in business. Yes, so like, let's, let's, let's find really interesting places where there's data
or to induce you to leverage alot of this obligation, technology and machine learning to make better in gaining sites, and then let's keep scaling bright, and so so our whole go with was hybrid giant was to really do three things: you'll be the guiding light for services for the fortune. Five hundred and then you know we, we weren't Lookit Ito practice. What we preach rights like let's look at the data that we get when we work with ten willing gas companies.
Ten entertainment companies are ten restaurants and in based on those trends and data that we see. Why don't we then start to build? You know off the shelf tat products it knew we can take, they can solve more macro trends
in the industry in last, is you know we have a venture, are aware in a wild tony
other people invested eyes were also looking at you.
There's a lot of great girls and guys are solving Willie targeted Prob.
Terms any. I n, you know, let's go find those companies, you know, I'm done a bunch of different, comes over the years and doesn't allow different sorrows. Let's actually? U fine, really great
start ups, maybe some investments in them and bring them in a part of the solution and into these companies have been in a kind of helping these big brands. You no inner interact with awesome. I start ups, I love you, you have. This are three pronged attack on, because I think a lot of the frustrations that business owners have is the hire somebody to come in and look at their data. Look at the processes.
And its traditional consulting right. That's the traditional run, salting model, and then they say. Okay, this is your problem. This is your solution.
Then they don't actually execute on the solution. Could they don't have the products bill or they will have access to these innovative NASH start ups that are creating technologies that can then you know
He applied to solve that problem. So it's really interested in an ear off, not going the straight up product rout either it's like a blend of of the tea, or rather the three. So when you approach a clients, do you have a particular given that you have these units three incredible day? Three point attack right, but you ve got these three arms that are all helpful to help you solve problems that clients have do you have like a particular process or away that you approach businesses, that's unique like how would you evaluate a potential client and how do you start thinking about what solutions to bring them NOS Greek wash?
you're the reason why we did this kind of three pronged approach has that we don't believe that we have all the answers. Like I mean I don't know if everyone that is a ceo and founder of Ai Company, says that
but we don't have all the answers. Yet there is great people out there. There sobbing different problems. You know we want invent some.
Knowledgeable play leverage other technology. So that's why I kind of had this three prong approach of like you know, if there's, I think, there's different rules for different problems, and so you know when we doing the company this is going to sound super cheesy. I feel
it's true. Is we listen? You just go in and listen. I know one of the big,
you know I've yeah! It's been very polarizing in the industry where some people are like
We absolutely love his stance on us in it.
People are like we absolutely hate his dance on it, but my view is that you so much of a I at least in recent years is technology. First, it's not in business, for
they go in and it's like, I have you know a natural language processing solution into every problem. You have is an actual language processing, and so we tried it in a week.
Really, while we viciously love technology
and we love artificial intelligence and we love all of the facets of of that phrase. We ultimately you know we're here to help businesses right and so
The first part of what we do is really just going to and listen in n. You know, educate, and so it's funny people ask me like was IBM. Your
petted error or you know, is delivered, but our measure could better and I would say our biggest competitors just education in so we go in really try to educate them. Unlike what is the art of the possible like not, although this snake oil
You no magic dna. I start to be seen in movies
and then they would just listen to them like water, the types of things a huge are trying to solve, and then we try to blend those two in. So it's really a combination of like early education in kind of new teaching M that these words,
actually mean things and words actually matter and in listening to what their goals are as business in finding the right ways noted two: can we are solutions and technologies together with you know that the cape eyes and whatever is gonna driving their core business decision of that approach, and I think that's actually something I'd on somebody. Business owners would really appreciate, and I hope that there is now there's server a shift in business communication and instead of going,
to a potential client and having no confirmation by us and thinking. Ok, wall, here's, here's what I have to sell. How am I going to shape their problems that it fits my solution at all?
so going in with this attitude of you know what we used to think was the right way to approach deals, which was confidence right right, absolute confidence. That, in my way,
is the right way and that's that's the old model in knots- and I mean it worked for years right linked, that's didn't the heart of sales right, but this is fascinating because, like I said, I hope that more companies star to adopt this
way of listening and Tony actually has a whole series of hearing
bowed on Meda programmes to an understanding peoples. It do you know, do you have an internal and external frame of reference on? Do you move toward or away something? So it's really getting into neural linguistic
grooming and understanding how people are thinking and
their communicating with you and then figuring
how you know the solution for after this deep listening, ransford deep listening, I'm right how you can then present them with the Vienna the solution to the problem. But you can- and you can't know the solution unless you have deeply listened and not just to
they're saying, but what they're really saying re rounds? I love that approach. I think it's something that sooner extremely essential and again something business owners really appreciate yet, and we cannot, you know we do that from a wrapped in this Brandon
after a few tourism right and so like. If you look at our
Marketing and you look at how we are talking about the space and you look. It cannot even just like you did
meant and yellow colors you like in a week, we had this there's just like you know: retro futures of art style, where you know it's like that, utopian to ensure that we are all promised like flying cars, overboard,
and selfless disabuse. It's like you know, and so we know our whole
is like even down
how're. You know not just solving these problems in in intake
values that were building, but actually even talking about represent yourselves is like, and we want a hope we re
they try to hold ourselves even at the bran level,
this standard of you know we were promised, is awesome world with. Where is it,
and so you know in a in a world where there's mistrust in media and there's a world of you know mister
and data in India is always kind of news coming out.
We really want to get a hold hyper giant to the standard of. How can we really help businesses kind of
I sure, in kind of this kind of you know. Fourth, industrial revolution of intelligence, and so
You know we really loved kind, retro future ism style, and it's not just at you know,
yours on a business card or on a website, but it cannot goes to Canada, Cultural Psychiatry like what we're trying to achieve here
here you know, add hyper giant and really make sure that, like new companies know that it's not just as selling a service or solution or product, it's really us. You know
it is our dog food and we are eating it in Vienna. We want to hold ourselves to the standard of dont. Get lost in the high like theirs. Is awesome world like let's go leverage these technologies to build it? Yet
I, the first Cassio I hyper giant raises the astronomical meaning of it, but I didn't actually
get the word hype has the art of your name, and I love the awfulness that you put into the brand, and I think that sending out a lot of ceo business owners and people who are just starting businesses need to think deeply about its, not just about what you're delivering its. Also about
the psyche and the cultural mindset at the time of your audience and
I like Nina retrofitted resonance fastening right because we aren't we,
promised this amazing world, and yet the first thing that happens, that sort of reminds us that it's not
utopian society that was promised to us. Like a self driving cars.
You know, killing somebody on the street were ah was another sort of way.
Get moment- are faced by grace her without knowing exactly. I don't like the elephant in the room that everybody is talking about right now and there is
statistic that I ran across. That was ninety one percent of executive decision makers anticipate significant barriers,
to adoption of ay? I is that something that
I mean it's almost sounds like on a business level. There is a lot more hesitant,
turn around and there is on consumer level that consumers like yes, yes, gas, like let's move into the future. But what is the hesitation on
on the side of businesses. Why? I think it? I think it is a little bit of you knew, I think, you're right, but I think that
the reason for it. You know- and this is just gonna, my speculation is- we went through a kind of dislike back Iain modernization that occurred with IRAN
as a mobile, so everybody did mobile app. You know everyone can
fast enough IRAN was selling or what I was saying that space for a while. But you know what is interesting is that companies dangerous had to go build a mobile out. They don't have to do is go find a company to do at the outset. It completely rethink UK. What's in the imo lasted the mobile app has to do something so tiny back in services. We gotta worry about security, so there's this entire. You know in what the rise of mobile their assistant,
the internet of things, there's entire kind of legacy. You know I've gotta redo all of our backing api eyes so that external services can talk to write into that was painfully
his mobile- went really really fast into a view now with technologies like I did all of this promise, and then you start
in some of the new initial leaders in the big insulting firms out there. There were talk
about a. I know, a lot of him look like big data, no projects in that kind of game,
Did my? I assume it kind of gave a lot of companies can a harbor of like ok, I've gotta go spend
You know twenty million dollars in three years to see what happens right, and so I think that a little bit
Canada mysticism in
the confusion in this base, coupled with some these big price.
Bags early on by couple in Dublin,
your companies has caused people being like. Ok, really excited about it. We needed are boards asking for more investors are asking for. The press is talking about it
I don't wanna be subject to a massive bill
in three years, then come out and say: ok generally, do anything and so on.
I actually I'm actually really happy that there's that scepticism, because it really gives us opportunity come in with this different approach.
And in its really resonating with businesses, and so I think that you know that, while the scepticism is definitely there, ah, I think it actually give enough for us. We look it as a really great opportunity, as customers are actually
and learn from the lessons of big data. Wondered oh and learn from. There can be no entire api
modern relation in the rise of mobile in some of those scars are still little fresh mean that wasn't at long ago. So I think up freezer. Like you know,
ah, actually trying to learn and be educated on these technologies, which is awesome, and, I think, to you, know, there's a lot of over promising and under delivering and in some cases tea. They were trying to tackle projects that were just enormous, and I think we would I'm interested in hearing about, and I think our audiences,
Well, as you don't answer them to re Jaeger, here entire strategy to fit the solutions that offers there are small things that you can do. I gotta go back to the root of testing enery so, for instance, Tony Robins we have a messenger bought, so you can go round faced with messenger and you want to know what the next event is or you want to get updates from the spot cast her from the bog. You can get those automatic updates and that's a relatively minor technology. That's just it just compliments or business. It grows righteousness in smaller
is it expands your engagement in small way, as it has in the end the potential to make massive impact in the future, but a dozen you know you don't have to change anything at European Year currently doing in order to fit that in what are some of the things that you guys have done or are doing with clients that you can speak about. That are examples of a small things that you can do yes or I'll use the tv
Friday's. Ah, you know eggs views, retardant, apology, it's it's giving great reviews,
people think it sexy and it is but but I'll take born, I say about the data would actually desert, like. Oh that's, actually, the sexy partner, a mix all just below Tv Fridays, which I think everyone
knows from the nineties and before right. This, like awesome, restaurant, that's gonna like in a one of America's restaurants, one of their caught one of their main one of their main executive Sharif is says. You know
I have to say that were actually like a fifty year old start up and were reinventing ourselves and we're
Only restaurant that owns the day of the week, and so they see that this is kind of like interesting,
some kind of modernization it's going on at this brand, and so when we went,
sort of talking in the them about artificial intelligence because they were religious excited about it, but no kind of like I mentioned earlier with it. You know healthy scepticism there what's actually possible in like how could a really help us. You know DR value to our customers.
If so, then we started talking to him in. You know bliss in really listening to him in trying to
you're saying you know what are their goals in there and you know what was great about Fridays,
They know who they are. They know
what they were. They know who they want to be in this kind of hissing entire kind of modern relation, not just from a technology perspective but also from liking in store perspective. There
we do not the restaurants a lot of the charge veto
just going away, and it's kind of you know they still want to be kind of that neighborhood happy hour about absent in your social. With your friends write the place they want you to come into the bar and also have a great suit the bars kind of central to
why you know that their vision is from the past and for the future, and so they told us new that their goal was. How do we get people? You know in the restaurant, in the bar, with theirs
and how do we better served in? How do we know more about them so that we can better serve them? Not any new creepy facebook way
but he knew it, but in that, but in a railway like how can I know better Sergei their names exactly and meet them where they are? And so we came up with this concept called project Flanagan
which is really in a I'm ecology. So then, obviously, when we announced that the press is like a dynamic
I'll, just it's amazing, it's a bartender from with an irish name. We just gotta, namely from cocktail that may you're too young to know what our whole our whole thing was like a well if we're gonna focus in the bar and we want to have
beside consumers, you ve got a new app. You ve got loyalty, you ve got all these different things. Why don't we try to start to understand kind of you know what our peoples Flavour palace right, like water
buying a different regions. What are you is a wealthy member? You know by prostrate perspective, what are you drinking so we can really do two things for
user, initially number one. We can recommend great drink sea. Based on what I mean,
the season is what other people are doing. You know you time a day, your specific paper profile. We can start to recommend.
Three that maybe didn't know or try. It can also mean a week. We invested a lot of different data from Dj Fridays. No data sets in there can be no executive bartenders and we train this system so that we can actually
made the system can actually make drinks. Now it will all be amazing, imperfect, probably not, but we can actually make like. You know the been lamb cocktail right and then I can take that and say this is a cocktail
that you know, maybe it's in a partner or maybe it's partly
margarita and may be a hint of mohira or something like that, and I'm like oh, this came together very well based,
and can have you know the rules set so gave the this system in the data in the system and then my particular kind of ordering history and flavour paladin inhabit the way I've train the system. Personally, I could come up with a drink that you know maybe awesome. I can share with my friends in the Hague tried to Bin Laden cocktail here it is in you could go in in.
And had an experience that new custom drink and then maybe there could be some magic drink. Then you may know that D Jeffreys actually discovers out this. That's awesome for the user, but then also for forty Jai Fridays
They can say, you know not leaves, are one awesome drink that comes out of this, that we can put our menu or name
after you know a customer, but, interestingly enough we can start to say
while in the summer in Texas, eighty percent of our population are drinking bitter drinks, a winning dead like we need a string,
you no more new sweet cocktails and other types of cocktails and refreshing dreams to the forefront in. I think some people get able that's. You know, you know
you should just know that, but unless you actually look at the data you're, just in you're, just gonna, guessing right in
in making a lot of assumptions, and so they can actually start to look at a macro level. You know and then look at all these different correlations to better service or customer in you, as a customer can. Having
really individual experience right, and so the more you spend time. You know what this is
some more knows you the more he recommend and then over time. I think, there's probably opportunities to take that to the food category and other things. I was making drinks
much easier than a precept menu but be theirs. There's a lotta implications from that in so while it sounds like sexy of, like oh in an artificial intelligence mix, all just yogi, it's really
just about looking data and making, it is really almost like a humanist nation for the customer, forty Jeff Fridays, which I think for Europe? Where are they data points? Coming from saying on businesses struggle with like input like how did they get the data, given you mentioned order history, but has anything else
yes right now. It's so we we still not. We believe that, and I think all's I training day that you know it and I think this work we cannot get into this world, as you know it,
do not always like his people like well armed gaiters, not goodwill is it. You know you can also click new data. If you have been a thousand restaurants deacons our clothing, you do you always have to use legacy right in so it's a combination.
New, their menus in historical ordering data within four years ago, consumer were using range,
where's learning, so you know when it recommends a drink. It then ask you the system ass. You did you like the drink kid you score the drink. What did you not less about? Why did you love about it? Because, while we can take all this data on mix all
details, data about you, know historical ordering and make recommendations based on you know what people have historically ordered with this food cyber. What not? We still use a person to return to reinforce that right
like we can't like magically know why you lie.
You know you like. I, like me, no whiskey, drink
it is suggest like, even if, even if all the data, most people from a grouping perspective, that in did once perspective that most people
What are these types of things that you did once went? Burma's we can make some owes inferences. We also need use, a human did say yeah. This was great or know that wasn't great, so that weaken you do continually not how the data set for the whole, but also for you as an individual, and I think, a big pain point for businesses is. How do we get more data about our customers? They know full well that how important it is to really understand your client, try and use that
permission in order to better serve them, but one of the problems, as you know there are we want more and more in our Sierra. We want you no more robust data sources and the whole deal and that they cannot surveys and ways that they can gather data through. You know multiple sources and its bit overwhelming to be honest by what the missing piece it sounds leg is you can get that data as hung as you have the make it clear that these clients going to benefit from it and right with you, you know you're using it to serve them on front end right. Ok, this is gonna creed, deeper, personalization customization, for you
then there can be ten times more likely to offer that because they get an immediate benefit, they get that gratification. There are just saying: hey we're gonna gather data so that you can get you know we can. You can go
to date, we have several yeah exactly exactly going ahead. I gotta go to get here and I think people get, and I think, like history
Lee companies like all anymore. Did I guess we knew more days. Our customers. Do you or do you need the right data? What do you need more
you need? You need to know that, like their part of the soccer club, you really need to know that an orgy of your tv Hebrides do you need to know what they like or do you need to know
when they want to eat like what's are eating out? You needed a different.
And I think, there's time I've been to your point: dislike organic, like more data
You know, I'm in this world that organic living with Facebook,
like Jane and everything else, people in our country. You know nervous
about their data and they should be right? And so you to your point, which I think you said it perfectly- you know, there's gotta, be that giving get like. I want to build trust as good as it customer of tea Jeff.
It is with Fridays and the only way I'm gonna do. That is, if I know that the things I give them I get out of it in the end, I respect that relationship and I respect the dated and giving them the collecting data for the sake of collecting data is just wearin, creepy
and so on on asthma, and so I think that you ve got a really build that trust in you gotta make sure that no you're asking for things that make sense could like if an app where're, you know,
Software or a brand asked me for data them when they were known it like that
Naturally, we like it's weird, I dont, for I don't it's just that I'm in space, and so you ve got him and make sure that you can have it had that artists and authenticity entrusting me based on Canada, give gets model that you talked about. So that's a great example.
The main thing everybody can relate to. Are there any other, and these don't have to be clear as it exists today, but when you guys think about the possibilities, what are some other examples from other industries like
I don't know, medical services are real estate or I used the I'm just thinking about the industries that that our audiences is in and in Athens,
the size and scale to of different types of businesses, because our audience is not necessarily from fortune five hundred companies, but rather business owners?
who are you there just starting up or maybe- and this is what I love- what you said about teach I Fridays being such an eye- conic brand, but that is continuing to modernize, because a lot of people who attend in a specific way, Tony Robins is business event. They have, they have sort of legacy businesses.
They want to bring into you know the future and are not a hundred percent sure how to do that, because they're still at that medium sized or not enormous. Yet so how did they begin to think about how I could benefit their business like what are some sort of creative ideas that when you know- and you guys rest and just talk about what the possibilities are, what or something
that you guys have come up with your eye. So I regret it in. I don't have a company or a person in, but one or two eggs, we're not talking about yet publicly, but we, I read aloud timber,
that came to me a couple months ago and I thought we were just catch him for lunch and
never his rich. I love this guy. I love it. You see actually know what did the space he's he's interrelated
no there and he's in one of the biggest real estate and investment funds. But did you know it's like a lot of these big rosy things it? Nobody knows like no one heard up
he and he was like. Is there a way that we can use machine learning in
nay, I related technologies without impress it even started with that question that way, how do you know it
I think I want to do this or I've heard of this, but I can't is even possible. Can we
can we understand my correlations that we,
and what are we know of like market trends in rates like historically,
Can we just that data
and know what our exposure risk is near. The market tanks by this present our interest rate,
changes because right now is like we don't know what our exposure
in Louisiana like so like you like? If we have one of our Linda Partners, call us and they say: what's our exposure on this
under properties that we own in arm in Louisiana is? Are we call analysed and we cannot go figure it out for them, but he's like that's not in real time or even near Alcides like it takes a couple days
now like wait, you're telling me that you guys in other railway companies, have you no hundreds
millions hours or a million dollars or a billion dollars for Gaza, whatever scaled, still the same but you're actually
standing here, you actually like, there's not anyway, that people post
that data together and doing correlations against it in making recommendations like sister
are dynamic, know is, if we don't even like we'd, be can't you know spreadsheets all to each other, and I was like
Are you serious like this? This is amazing because it is a huge opportunity in so that's an example of like united I'd. I think that a lot of Sunday, real states
your words great and we all use it. You know it is sometimes a lagging industry. Life assure its sea. We
regardless of whether you're buying some
houses are. You doing you know internet
national, you know casino type, development, whatever scale you know, they're still using really antiquated old systems and a lot of it.
This common manual labor, where you're like you taking in,
your data in brain and spreadsheets, an email him around than one mess up spreadsheet could drop everything right.
There is just a lot going on, but a lot of that kind of the automated right, and so what I love about the launch. It wasn't that we have as mass
a solution that were to go can work on the other, but it was just a back that this guy, that's not in technology. That is, you know in
you know it's one of the partners are real estate. Investment fine said: is it possible right, and so I think those the core
genes, that new small, medium and large cap companies, all across scale need to understand is like you is start asking, is it possible and then
doing the research in being educated, because
It's amazing that you know someone. It was from this mean a super
antiquated, auto industry called me and said I was doing research on this, and I can I think, it's possible what I just want to know right into it said kind of curiosity around these technologies that could lead to us, partnering or or them partner with someone else or whoever to build dislike massively. France form
the thing for the entire industry right and push the entire into before it in, and I think that's what's you monsieur brought interesting kind of about the space of a kind of like what the ripple of Ex could be. You know from like just one person saying: is this possible yet now which what role
He in at that at that firm, so he's he's a managers. I mean he's, not mine
main guy, like the whole thing legacy. Eric he's in the UK was researching solemnly.
You guys are doing. I don't fully understand it, but this is what I am you know gleaned from you.
Doing some research on what's possible and here's how we look at data and he's like, and then you kind of walk me through the process is like you know how they understand their exposure risk in certain areas,
and ass. It gets all her work you can either do you, like it literally told me, is vital to say there is he literally told me
that is like I googled macros input, brolly spreadsheets together and then I created a powerpoint, those just dashboard, and they are like we had to what this
the CEO George on, but you are the smartest person here as I would that that its awesome for you
you gotta be pushing forward, but he was like that. Wasn't that hard and
it was so amazing to this industry right in so behind him. He just any midway in the company in just said, you know, is this possible and even our meeting with her leadership team and talking about come
what is possible and in its great it all started with you pave the way we're doing
it seems like a lot of work and machines could probably help take some barb late and make it better. I mean, I think you just hit upon something really key at four. Take an early for medium sized businesses is, it is not the ceos responsibility
to sort of facilitate or enable these sort of change initiatives right like it is not
all on you as a business owner to do that
and we actually have in Romania has a whole thing around on how to encourage employers to innovate, so how to build a culture of positive change, and I think one of the most important things is look at your look at your leadership team. Look at your managers give them a sense of ownership, not just over the day to day right. So, ok, here's what you need to hear their output for they re like this is head down execution in execution mode. It's really important to give your leadership team the
just like the the space to to innovate, but also serve like the emotional encouragement, like hey each of you as an ownership, seed, marketing, accounting and let you know I really there's innovation with an eye to the people
often look at eighty as the space from which you know all technology ideas need to come, and that's just not the case, because
as a manager over your particular department in your employees. You know what your pain points. Are
every time you hit send and there's you know these ex these spreadsheets attached to an email, little bell should be going off in your head and you should be thinking there has to be a better way, and that comes from you write it did. It is not come from anybody above or below you comes from you. You need to take ownership over innovation. Absorbent know your thousands are right leg, you know, I I sometimes
say it like a I that arise, not magic. It should work. It's just math, like his letters, were in either it matter much. What we will do that I do but its role,
his work right in, and I actually think that humans are magic greatly. People have this. I view that a in these technologies,
what a humans, like I don't know,
I actually think human ingenuity is magic, and I think that you know their. I actually think there's nothing more human then artificial,
is because we are creating amazing technologies to push all kinds of industries Board like my friend could literally change the entire related industry with his idea in, and he is not in the eighteenth group. He is litter argues like that, I'm in the finance group- and I just thought
This is his art. What we're doing right- and you know it's one of those things that I
We think that you knew humans are magic,
and human ingenuity, magic and we'd now you know, could have reached this political.
Where we were starting to building technologies. Second drive: you know, intelligent behaviour in imports is to give back to humans to make things better, and you know,
really can can come from anywhere. You know within the organisation so Ventnor.
Then wonderful. I am. I wanted Sesar to end with a question. I know we ve been talking about the
future this entire time? But
do you see a going? Not just this year, not his justino immediate,
applications? But how do you see
evolving over the next three five?
even ten years like what, where do you think we're going to end up with us? That's a great it's a great question. It's a hard question right! You! They think that there is a lot of future. Is out there, I think a lot of people are selling ten.
Yours out today, so I'm a little careful and how I answer it, because you know, I think the biggest thing that that I think can happen with a sigh is trust.
It's like right now with a lot of the system that were developing work closely, not just in implementing the you know, it's not just about the white, but it's the. Why into were actually doing a lot of stuff with a customer
for when the machine makes a recommendation or makes a temperance. We actually give them, is quite right proofs and in your
which, like were the worst things ever where he had like, is accused the answer, but yet approved by all the sceptre Letty showing were actually servicing,
you, the businesses, how it came to these conclusions and why it is
it is what the weights are with the decision factors are in so because I think that transparency builds trust in so for me,
I think in the next five years. You know I would love her. You know the vast majority of businesses, ranging from a sober
pride or to a fortune wine to implement some
version of a related technologies. What its verdict, data and legs or know? How can you you implement nestlings processing and your call and your commissioners or whatever, and how can we actually just start, and so I would love in the next five years for a cut two things happen.
Every company starts in the air and were too I would love for companies to actually be educated on what these words actually means. They dont make bad decision
and, in the end it better our. Why? Because that's just look at the whole industry back so with that education will come trust in so if they start in a experiment and they get educated in the trust. The system with that. I think that in ten years from now
that we can have. We can be looking at a very, very different future, where you know there's a lot of time. This day to day come guesswork, that's been occurring,
there'll be handled by machines in humans are gonna, be had more time just go. Do nothing continue to push the entire planet for which, which I think we are.
So you ve made me very motion, often see her. It is extremely it's an extremely exciting space and there is a lot of missing.
Permission out there and a lot of money in it's good to take missteps cause like you said we learn from not, but it's really really fascinating just to hear about. We know where we're going with us. So thank you run the Van Lamb from Hyper giants and you can go to their sight, hyper giant dot com to find out what you know more about their products and services
and thank you so much by that was great. Yet things were army on the twenty weapons passed his directed and has to buy Tony Robins anymore
is our editorial director, an occasional host, our executive, pretty-
there is carry some Jimmy carve a home and aid
we'll do that today. Our digital editors, special thanks to me
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Transcript generated on 2020-04-04.