this week, the psychology of the trump bump in the markets. a robot makes coffee faster and cheaper than any starbucks barista. we'll meet the robot's creator and talk about the future of jobs. and how to manage silicon valley when "old" is 20. this week on "press:here." good morning, everyone, i'm scott mcgrew. my first guest either invented

something clever that will make you smile, or he doomed starbucks baristas. it's possible he did both. cafe x is a robotic barista, making coffee right now in san francisco. this is more than just a fancy vending machine. you use your phone or tablet to order a custom cup of coffee, ready as you walk up. the brains behind cafe x joins us. henry, you were one of the peter thiel kids. you dropped out of college to come up with this idea. >> yes, i was waiting on line at a cafe and decided to drop out to work on it. it's important because productivity in food service is not very high. >> peter pays people, how does that work, he encouraged you to drop out of school, right? >> so i did actually drop out of

college before receiving the thiel fellowship. obviously having that makes things easier. >> tell me, when you were looking at the roboticness of a barista, it occurred to you this something a robot could do. >> a lot of what baristas do is robotic, doing the same thing over and over again, spending a lot of time moving cups around. we use a robot arm to do that. we partner with local specialty coffee roasters to use their coffee and have them set our recipes. >> how long did it take to go from an idea to a working prototype to deploying it? >> we built the first prototype in less than a year. but it takes time to refine everything and make sure it works well. typically the technology we use

is not something you put in public for hundreds of people to use every day, so there was a lot of work we had to do to optimize everything and make sure it's safe and user friendly. >> do you think robots are faster, more efficient than normal human baristas? >> definitely faster. it's more efficient. the most important thing, though, by using a robot to do low productivity, highly repetitive tasks, we allow the staff onsite to do more important things like interacti interacting with customers. >> you were insistent, yes, we're replacing a human being in one job but we're creating a job, it's essentially a greeter, an overall ambiance sort of thing. >> yes. we call the person a product specialist. a good coffee experience is one where you get to try the different coffees. someone is there to educate you

about coffee, answer any questions. kind of like the experience you would have at a nice restaurant. all of our product specialists are really well-trained to answer those questions. >> you can order by mobile ahead of time, so you get there, and it's hot. what if you have different people ordering at the same time, how will you organize who gets their coffee first? >> when the coffee is ready, it waits in the machine for you to arrive. it waits for six months. if you don't show up, we'll throw it away and make you a new one. when a lot of people order, this is one of the things we're working on, basically is taking all of that data, looking at how long it takes us to make each drink, what kind of ingredients we use. even the location of the customer, you know, using their phone. we're applying some machine learning to really optimize that. so in the longer term what you'll see is, even when a lot of people order, we'll still be able to give the right drink to the right customer as they show up. >> walk us through the economics. what is the startup cost that

you face with your kiosk versus like a typical starbucks? how many people are you employing versus a typical starbucks? how many people can you serve versus a typical starbucks? >> sure. on sites we employ less people than a typical starbucks. however, to build the equipment, we have a lot of engineers, it's a product that's manufactured. so there's still a lot of people behind the company needed to create this product. in terms of setting up a location or store, a cafe is not like a manufactured product. you don't really have economies of scale. whereas with the robotic cafe, this is something we'll mass produce over the next few years. the economics will be significantly better. >> there is a cheaper coffee as well. did you intentionally make it cheaper or are you offering it for cheaper because you're not paying the robot medical benefits? >> that's one of the reasons we can offer it for a lower cost and still be a good business.

>> because starbucks is four bucks, you're about two something, right? >> typically we're about a dollar less. we have single origin coffees that cost a dollar more than the standard ones. you can select from the app different coffee beans. >> it's a little like -- i mean, kids love it. when i saw it, my first suggestion was, you need to start serving hot chocolate because kids -- are you serving hot chocolate? >> we're working on that. >> people just are mesmerized by the thing moving back and forth and picking up the cups, et cetera. >> yeah, well, i think with a good food or drink experience, it's supposed to be a good experience, so having a robot there, you know, in addition to the efficiency gains, is also quite exciting, it's fun to watch. we did add a new item called really good milk on the menu. >> okay, good, a kid thing. >> yes. >> how do you respond to some of the reactions that you're getting, some of the less positive reactions about, you

know, this is displacing jobs, or, you know, i actually enjoy going to my cafe and talking to my barista or having that human interaction with my barista, i enjoy being in a cafe with other people rather than getting served by a glorified vending machine? >> our goal is not to replace cafes. cafe x will create the best possible experience for people trying to get good quality coffee to go. if you're looking for somewhere to sit down, have a meeting, a cafe is still a great place for that. for the tip uypical use case, w you just need coffee, you want good coffee, train station, airports, high traffic areas, office buildings, i think cafe x is the best possible experience for that. >> you got some interest out of facebook and google, some others, that they want these things. because they're cool, right? have you landed these in high tech buildings? >> so we're working on installing these in several

offices. there isn't one we're ready to announce yet. >> okay. i'm speculating facebook and google because they have cool things in them. will you offer the coffee and then charge the high tech company for the existence of it? because generally speaking, they don't charge their employees for products. >> yeah. so for our model, enterprise model, they can buy the machine, and we'll do technical support. or they can pay us a monthly fee. >> my last question, you were a student and were able to land money. how did you get the finance, as a young student, to create robots? >> i think the biggest thing that investors are looking for is the ability of the founder to execute or to build things and put it out into market. so that's kind of what my focus is. that's what i really try to do well. >> you knew what you were doing. >> a lot of learning and figuring it out, yeah.

>> okay. because i have one final last question, last-last question. what did you mess up? what does the robot do poorly, where you said, "come on, robot"? >> when we first had prototypes we had concerns about spilling and potential safety things. we made it really slow, and it was ridiculous, watching this slow robot. so now it's pretty fast. >> can the robot clean up after itself? >> we're working on it. cleaning mode. >> that may be the killer app. henry hu, cafe x is in san francisco, anywhere else? >> a few more locations in san francisco over the next few months. >> thank you, henry. up next, the dangers of old age when old age is about 20. "press:here" continues.

>> the permanent loss of thousands of gigabytes of sensitive or precious data. >> we found all the files that had been encrypted and we just deleted them. i went straight to the bar i cu barricuda backup. it was resolved in under an hour.

welcome back to "press:here." my next guest has the most peculiar resume. he has done something no one in silicon valley has done. he has worked at the same company for more than 20 years. we hardly know what to make about that. murray rode works for an old company by silicon valley standards. old age creates a unique challenge for these companies. established companies suffer from what's known as the innovator's dilemma. by doing exactly what the america wants, by being successful, old companies run the risk of failing to innovate, to take risks. now, we know this company is successful, it counts t-mobile and jetblue among its customers. thanks for joining us. you're kind of fighting two fronts here when it comes to competition. you've got the young startups that everybody needs to worry about. you've also got the saps and

oracles that you're competing against as well. >> that's true. on the one hand, you can say it's a bit of a two-front war, competitively. on the other hand, we get the advantages of being small enough to where an individual can make a big difference. that's appealing particularly to young engineers. and we're big enough that we don't have the inherent risks of a startup. we have momentum. we have that flywheel of an existing business that gives us the ability to invest. we have a lot of interesting customers that we're very deeply embedded in their businesses. that's interesting, again, for the employees that we're trying to attract. >> one of those companies you just cut a deal with, mercedes, and the f- te1 team, formula on racing, will we key tibco on the cars there, running around? what is the driving analytics of racing have to do with tibco? >> tibco's business is all about

connecting data, particularly realtime data, and helping our customers make sense of that. often with realtime analytics. if you think about that, that's a lot of what goes into managing an effective racing team or effective racing car. so yes, we're a sponsor, the tibco brand shows up, gets a lot of excitement from people outside and inside the company. it's also about us working with them for them to get the benefit of that analytical technology. >> what's an example of going into a pit stop or something, what's going on with tibco to actually play a part, how do we understand that? >> i'll give you kind of a broader example that advertise into this. i think a big part of what we're doing these days has to do with iot, internet of things, and particularly industrial applications around that. think of another customer of ours that runs big wind turbines, they collect a lot of data about wind turbines. being able to analyze those data

and recognize patterns in the performance of the wind turbines enables them to do proactive things with maintenance, so it reduces their maintenance costs. it also enables them to take a lot of that modelling and help customers decide where it's best to place a wind turbine to model weather and be able to put that in the context of designing the most effective wind turbine farm. so similar with something realtime like a race car, looking at performance of the various components of the car, modelling that over a number of raises, is where you can also start to apply things like machine learning and ai techniques to predict behaviors. >> you were talking about young employees. everybody is competing for the same talent. if a young engineer is thinking about google and she's looking at some sort of disruptive startup, there's so many in san francisco that say they're going to change the world. how do you convince her that, no, tibco, which again, doing exciting things with formula one racing cars, but is a mid-sized,

20-year-old company, this is the place that you want to be, not google, not that disruptive startup creating new ways of toasting bread? >> oh, it's easy. it's no problem. part of the point is that we've actually changed the world for a lot of our customers. so there are very good examples in banking, in telecommunications, retail. i mean, a whole variety of industries. so we can point to that as a very real way in which we're making a difference. i think in some ways, you know, the kinds of things google is doing, for example, is very different from what we do. you know, where we engage with customers on a whole variety of solutions that touch that customer's customer, whether it's a retailer in creating a more engaging digital experience, a bank in creating, you know, a high speed trading platform for that bank, telco, and kind of the volumes of data and the complexity of the

scenarios we're solving in many cases are appealing to hard-core engineers. >> tibco went private in late 2014. how has that affected your ability to manage and grow the business? and how has that affected your ability to attract and retain talent? >> it changes things a little bit. two very positive things, one, we have what i think is a very progressive private equity sponsor in vista equity partners. and they believe in the growth story of tibco. the second thing that it's enabled us to do, not being a public company with all the same sort of exposures of a public company, we can make some longer term bets. we can think a little bit more long term about what we're investing in, which products really matter, build for the future. that's very much what we've been doing over the last years. >> and of course there is the chance you might go public again. if i'm a young engineer, i'm

joining a pre-ipo company. >> that's exactly right, the best of both worlds, big enough for momentum and security but small enough to be innovative. >> as you're placing those long term bets, what do you see as the opportunities for tibco going forward? >> i think three big areas we talk a lot about today, i mentioned iot. in essence it's very central to what we do. it's about a lot of data and how do you process a lot of data in realtime to take advantage of it. and then on the other side, what we do with analytics, and merging that with the ai technology that's becoming much more prevalent today, so our ability to combine ai and analytics so companies can take advantage of connected data is a really big opportunity. and the last big thing that you hear a lot about these days is block chain. and block chain in many respects involves integration, involves

connecting systems to the block chain. and we have a lot to offer. >> i want to squeeze in one last question. you've seen president trump trying to adjust h1-b visas. i assume you participate in h1-b. >> we do. >> what effect do you think that will have on your company? >> it could be a challenge. it's certainly but that's important to us. i'm a product of an h1-b visa. >> really? where are you from? >> i'm from canada. >> okay. >> i'm very empathetic to it. h1-b really helps us in terms of accessing a global pool of resources. you know, there's great talent in the u.s. but there's great talent around the globe. >> murray rode, the ceo of tibco, thank you for being here. >> thank you. next, why flowers are better than money and what that can teach us about the stock market, when "press:here" continues.

welcome back to "press:here." all of my viewers are of course above average. but it turns out average people are pretty smart too. mayor stanton says the average american is rational and "normal smart," in his words, smart enough to figure out the stock market better than professional investors. i can't say i disagree. although paging through his book, the mayor likes charts and graphs maybe more than most people do. he is maybe the world's top expert on economics. you've been on the show many times before, a friend of the program. psychology is what people do sometimes irrationally, isn't it? >> no, economics is a study of what people do when it comes to economic decisions. >> for their best interests.

>> of course. but their best interests are not necessarily money. the best interests really is what is the money for. and so to the extent that money is for financial security, that is what matters. if it is for the children, it is for bebequests, it is for chart. you can't just stop at i want to make money. >> there's an emotional component. >> it's more than that. think about going to the movies. have you noticed that movies are fiction? you're paying real money for fiction. why? because it makes you feel good. that really is why kids, have you noticed, they cost a lot of money. >> i have noticed. i have one in santa claire. they cost a lot of money. paying your salary. >> oh, well, don't put me on the spot. [ laughter ] >> so what is a normal people, a normal person?

is it somebody that's not an expert in the markets? >> no. normal people are people like me and like you. they are people who are neither computer-like rational, getting everything right, robotic. neither are they bum building irrationals, bumping into trees and doing everything wrong. so normal people are people who are genuinely knowledgeable but sometimes ignorant, they're generally smart but sometimes are stupid. if you ever caught yourself saying, that was stupid, don't do it again, well, that is a mark of a normal person. and i'm trying to understand what it is that people actually do, what normal people actually do in their own economics and finance, and perhaps how we can help them do better. >> so if somebody reads your book, a normal person reads your book, what should they expect to get out of it? >> what they expect to get out

of it is a picture of themselves, they'll see themselves in the mirror. and they're going to say, i know this person, that person is me. and then they're going to see the kinds of mistakes, for example, that they are making. and perhaps be able to them stop themselves and ask, wait a minute, should i do that, or should i not? >> so, mair, this is less about go for the 30-year fixed mortgage, and more about every day psychology and how it affects your decisions on what to do with your money. >> that is part of it. it really is more about life than just about money. and of course, money is part of it. but, you know, again, if we're talking about family, we're talking about your wishes to be socially responsible, your wishes to donate money to charity, to send kids to

college, this all involves making choices. and we do make good choices most of the time. but sometimes we fumble. and sometimes we fumble when it comes to investing. >> putting good money after bad, that sort of thing. >> that is one example, yeah. people think, for example, that that it's easy to beat the markets, why don't i pick this stock or that stock because i read something in "the wall street journal." the question they should ask themselves is, who is the idiot on the other side of the trade? >> you taught me that years ago, when you are selling a stock, there's some other guy who things it's worth buying, or if you're buying, some other guy things it's worth selling, one of them is wrong. >> one of them is the idiot. [ laughter ] >> when you're looking at financial decisions that normal people make, what are the biggest mistakes that people make, what are some of the problems that people need to recognize? >> think, for example, about issues that we talk about in

terms of framing, okay? when people think about investing, they think about it as the equivalent of playing tennis against a practice wall. they've heard this is a good stock so let me rush there. but it's not. trading is like playing tennis against an opponent on the other side of the trade. >> i have to interrupt because i promised the viewers the flower analogy. i've got $10. i can buy a flower for my wife or give her $10. $10 is more useful than a flower. but there's an emotional component to it. >> that is right. it doesn't take much to know that you're better off giving her a rose than $10, precisely. because while i rose has no utilitarian benefit, she cannot eat it or drink it, a rose says i love you, you're a thoughtful man, you'll do well to marry me. >> is that a good example or one of the better examples of the

psychology of finance? >> it is. because it says people hear not just about utilitarian benefits, can i eat or drink it, they hear also about the expressive and emotional benefits. >> mair stanton, the authori of "finance and normal people," we'll be back in just a minute.

that's our show. our thanks to our guests. i'm scott mcgrew. thank you for making us part of your sunday morning. o: hello and welcome

to "comunidad del valle." i'm damian trujillo and today we have a special treat for you. we have the best mariachi in the world, mariachi vargas de tecalitlán on your "comunidad del valle." male announcer: nbc bay area presents, "comunidad del valle" with damian trujillo. damian: i'm celebrating 18 years of hosting this show, ♪ celebrating 18 years of hosting this show, "comunidad del valle," on kntv, and what a better way to celebrate than with the best mariachi in the world. thank you all for being here. whenever you play in this venue, it always sells out. why do you think people want to come to see you here? >> well, i think the people have