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Speaker 1: All right, guys, readings and salutations, Welcome back Episode seven,

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Speaker 1: Lead your podcasts. We're back earn your Lesion podcast. Thank

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Speaker 1: you for your support, your encouraging words. Thank you for

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Speaker 1: riding with us throughout this journey of ours. So, Troy, yeah, man,

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Speaker 1: we gotta we gotta talk about some real issues person.

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Speaker 2: Yeah man, a personal issue for me and for millions

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Speaker 2: of Americans about forty five million of us to be

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Speaker 2: exact student loan that it is a trillion dollar problem

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Speaker 2: in America. I think it is the second not even

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Speaker 2: I think, I know it is the second highest gross

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Speaker 2: of debt in America, only to mortgage debt. And you know,

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Speaker 2: we spoke about the wealth gap and how important having

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Speaker 2: a mortgage is and having homes are. But something is

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Speaker 2: going to be combating that now in the future if

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Speaker 2: something doesn't change, and that's student loan debt. So there

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Speaker 2: are some negative effects that it has long term and

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Speaker 2: short term, and we're going to talk about some ways

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Speaker 2: that we well, not we in the sense, but the

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Speaker 2: government is proposing to change that.

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Speaker 1: Yeah. So something came out recently, right, It's what happened.

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Speaker 2: So we had a report that the Senate is thinking

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Speaker 2: of a way to have employers pay for student loan debt.

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Speaker 2: So right now, they do reimburse people who are going

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Speaker 2: to school, so they reverse you for tuition, and that

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Speaker 2: is pretty standard in some fields of employeing. But having

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Speaker 2: the debt paid is something that will be very new.

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Speaker 2: And what they're saying is that employers can match up

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Speaker 2: to five thousand dollars in student loan debt for their employees.

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Speaker 2: It'll be an incentive for people to take jobs and

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Speaker 2: it will help burden that that that is pretty much

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Speaker 2: crushing people, Like the average person has thirty six thousand.

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Speaker 1: Mean, what exactly you're going to happen?

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Speaker 2: So employers, right like if I want to get a job,

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Speaker 2: Let's say I'm a teacher and I want to get

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Speaker 2: a job at a school, and one of the things

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Speaker 2: I ask the employer or the school district is do

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Speaker 2: you guys reimburse for student loan debt tuition? Right now,

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Speaker 2: that isn't in place, but there are proposals that could

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Speaker 2: do that, and if it passes, they can reimburse up

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Speaker 2: to five thousand, So they're not going to pay your

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Speaker 2: entire payment because I think the average person this is

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Speaker 2: the study showed that the average person spends more on

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Speaker 2: their student loan debt than they do on their monthly groceries,

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Speaker 2: which is like crazy, Like people have to pay more

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Speaker 2: in debt than they are eating, which is like ridiculous.

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Speaker 2: But they'll pay a percentage of it. So even if

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Speaker 2: let's say your student loan payment is seven hundred dollars, right,

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Speaker 2: which is kind of meeting in this day and age,

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Speaker 2: the employer can say we'll pay two hundred dollars of that,

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Speaker 2: and they'll do that as long as you're with the company.

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Speaker 1: So will that be deducted from your salary.

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Speaker 2: No, it's not. It's actually the employee gets a tax benefit.

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Speaker 1: The employer gets a tax benefit to paying off your

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Speaker 1: student loan.

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Speaker 2: Absolutely. It's just like when they do tuition reibursement, Like

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Speaker 2: people don't know that the employers write that off as

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Speaker 2: a tax deduction. Okay, yeah, So like that's a new

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Speaker 2: proposal that could happen. We'll see because if we don't

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Speaker 2: figure something out right, people's lives are being delayed. So

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Speaker 2: like when people come out of college, and it should

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Speaker 2: be a celebratory time, right, we go to school four

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Speaker 2: or five years, we get our bachelor's degree, and in

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Speaker 2: most situations. Now we have to go further and get

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Speaker 2: our master's degree. It's we should be celebrating that. But

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Speaker 2: what they people don't realize is that in six months,

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Speaker 2: government's going to come knocking, right, we need you to

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Speaker 2: start repaying. And the problem is that when people come

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Speaker 2: out of school and they amass so much debt, like

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Speaker 2: if they go to a top line school, it could

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Speaker 2: be two hundred thousand dollars that they owe after they finished,

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Speaker 2: you know, with their school. How are they going to

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Speaker 2: repay that? Because you have to come out of school

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Speaker 2: and then find a job that can support you and

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Speaker 2: then also pay back. So what you see is that

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Speaker 2: a lot of people, a lot of millennials are living

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Speaker 2: at home longer. They're not having the money to save

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Speaker 2: to buy a house. You see more people renting, and

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Speaker 2: you see people's credits being damaged. That's one of the

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Speaker 2: parts that a lot of people don't really understand is

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Speaker 2: that when you defer on those student loan payments, right,

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Speaker 2: they put you into a firma for about six to

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Speaker 2: twelve months at best, and then right after that if

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Speaker 2: you don't pay, it affects your credit. So now let's

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Speaker 2: go further, like if you don't have the credit score. Now,

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Speaker 2: when you try to apply for apartment, one of the

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Speaker 2: things they check is your credit. Some jobs, when you

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Speaker 2: apply they check your credit. When you try to get

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Speaker 2: a home, of course they're going to check your credit.

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Speaker 2: And a lot of people are being completely hampered by

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Speaker 2: it because they can't afford to pay the the debt,

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Speaker 2: and now long term they won't be able to come

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Speaker 2: out from the effects of not being able to pay it.

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Speaker 2: So it's like a domino effect of things that are

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Speaker 2: happening because of this debt.

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Speaker 1: Okay, all right, So actually, if I don't know if

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Speaker 1: people remember, but if you follow my Instagram, I wrote

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Speaker 1: a report about an interesting story in regards to student

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Speaker 1: loan forgiveness a few months ago. So in December, the

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Speaker 1: Department of Education announced it was going to cancel thousands

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Speaker 1: of debts for teachers who had grants turned into loans. Right, so, okay,

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Speaker 1: here's the bad story on it. Teachers that are aspiring

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Speaker 1: teachers were given grants to go to college. Right then.

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Speaker 1: The thing was that you had to work in a

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Speaker 1: low income school district for four years after you were

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Speaker 1: done with college. Right then, if you worked in the

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Speaker 1: school district four years after you were done with college.

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Speaker 1: Then you didn't have to pay the grand back. It

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Speaker 1: was a grant, right. The problem is that it was

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Speaker 1: all kinds of red tape involved, where you had to

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Speaker 1: certify every single year with the Department of Education by

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Speaker 1: sending in I believe like forms, and if you were

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Speaker 1: like one day late on the form, then your grant

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Speaker 1: turned into a loan, and then you had to get

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Speaker 1: the letter I think signed by a principle. But it

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Speaker 1: was during the summertime, so a lot of schools were

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Speaker 1: closed and it was hard to find administrators, and then

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Speaker 1: people moved, and then their addresses wasn't updated properly so

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Speaker 1: that they never actually got the letter in the mail.

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Speaker 1: So what ended up happening is that thousands of inner

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Speaker 1: city teachers had their grants turned into high interest loans.

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Speaker 1: Not only loans, but high interest loans, and overnight they

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Speaker 1: were crippled with tons of debt that they didn't know about.

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Speaker 1: So they might have took a grant, They might had

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Speaker 1: a grant for fifty thousand dollars and they thought that,

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Speaker 1: you know, it was all good, and they find out

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Speaker 1: that now they're fifty thousand dollars of Debt. So a

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Speaker 1: good friend of ours, a friend of the show. She'll

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Speaker 1: be on the show soon, hopefully. Valencia Clay So she's

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Speaker 1: a superstar teacher out of Baltimore. Her name is Valencia Understore,

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Speaker 1: Valencia on Instagram. Everybody probably follows her, everybody knows her.

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Speaker 1: So she's the one that actually told me to write

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Speaker 1: this story because it happened to her personally right where

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Speaker 1: it affected her where I think she was trying to

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Speaker 1: buy a home and she didn't know that her credit

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Speaker 1: was affected and they say, your credit is real low,

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Speaker 1: and she's like, what happened? And then she found out

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Speaker 1: that her grant turned into a loan and she was

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Speaker 1: behind on her loan payments. So that happened to thousands

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Speaker 1: of inner city teachers. It's very unfortunate situation, absolutely, and

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Speaker 1: now I guess it's something that they're trying to rectify

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Speaker 1: by saying that they forgiving a lot of loans because

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Speaker 1: so there are a.

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Speaker 2: Few loan forgiveness programs, like I was a beneficiary of

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Speaker 2: a teacher forgiveness loan.

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Speaker 1: So you were an inner city teacher.

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Speaker 2: Yes, for eight years? Eight years you.

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Speaker 1: Taught in the Bronx.

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Speaker 2: Absolutely right, yep, so part of the loan, and people

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Speaker 2: have to do their research because there are a lot

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Speaker 2: of programs that are being offered to have loan forgiveness

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Speaker 2: depending on what career you're in. So for me, like

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Speaker 2: you said, it was the teacher loan forgiveness and some

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Speaker 2: of the sipulations where you had to work in an

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Speaker 2: inner city school a Title I school for five years

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Speaker 2: and based on what you were teaching, so if it

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Speaker 2: was math or science, you could be granted a certain

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Speaker 2: amount of money, or if it was social studies or English.

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Speaker 2: Here it was a certain amount of money. But I

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Speaker 2: argued like, hey, if I do science right, well what's

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Speaker 2: the different We're all teaching right, So the max you

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Speaker 2: could get with seventeen five hundred. So I was I

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Speaker 2: was granted that, which was great and it helped a lot.

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Speaker 2: But there's another loan forgiveness program which is called the

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Speaker 2: Public Service Loan, and that goes for anybody who works

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Speaker 2: in public service. So if you're a government agent, it's

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Speaker 2: not a double agent government official, you could qualify for

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Speaker 2: this loan if you're part of a five oh one

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Speaker 2: three P program, or if you're obviously a teacher, you

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Speaker 2: still qualified. The problem is that there are a lot

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Speaker 2: of sipulations and some red tape. Like you said, so

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Speaker 2: one of the things is you have to pay. I

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Speaker 2: have one hundred and twenty consecutive payments. You can't miss

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Speaker 2: a payments. So that's like ten years of payments you

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Speaker 2: can't miss. And I thought I qualified for that, like

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Speaker 2: I had paid my loans on time. I applied for

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Speaker 2: this program, the Public Service loan, see the ten years

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Speaker 2: or one hundred and twenty payments consecutive. And what I

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Speaker 2: realized is that after I got no response from the government,

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Speaker 2: it was like, this is weird. And then a report

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Speaker 2: came out. They said that one percent of the forty

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Speaker 2: five thousand people who applied for the public loans service

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Speaker 2: on Public service forgiveness granted it. Yes, one applicants point

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Speaker 2: it's like zero point eight yes, ladies and gentlemen, a

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Speaker 2: government program where one of the applicants, yeah, were accepted. Yeah,

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Speaker 2: because inside of not so. The one hundred and twenty

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Speaker 2: consecutive payments is a thing. But what they don't tell

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Speaker 2: you is like it has to be a specific type

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Speaker 2: of payment pan it can't. It has to be like

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Speaker 2: an income based one or one that they set where

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Speaker 2: the interest is really high and you have to pay

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Speaker 2: like seven hundred dollars a month or probably like my situation,

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Speaker 2: I didn't leave college with a lot of debt.

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Speaker 1: It's all kind of it's college, you know. The interesting

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Speaker 1: thing about is that Google, ibm uh, Facebook, I believe

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Speaker 1: a few other companies recently dropped the college requirement.

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Speaker 2: Right.

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Speaker 3: They're just taking kids right out of high school to

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Speaker 3: be higher, right, So what do we need college?

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Speaker 2: So it's tough, right as an educated like I'm going

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Speaker 2: to say yes that at some point you will need

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Speaker 2: some form of college or right, we can't leave them,

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Speaker 2: or you have to learn a skill, right, And they've

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Speaker 2: been taking that out of schools. Right. They used to

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Speaker 2: have schools where you learn trades and you learn skills

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Speaker 2: and you can carry on that into a profession, which

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Speaker 2: is like kind of what you're saying with Google's doing.

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Speaker 2: It's like, look, if we have kids who have an

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Speaker 2: interest and they are advanced at.

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Speaker 1: If you know how to code, you don't need it.

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Speaker 1: You don't.

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Speaker 2: We're going to go straight and we'll teach you on

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Speaker 2: the job. But you have to know how to code, right,

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Speaker 2: And a lot of schools are offering that now at

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Speaker 2: high school and at the elementary levels. So if they're

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Speaker 2: not going to go to college, then yeah, there are

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Speaker 2: some careers that they can do. And that's one of

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Speaker 2: the things that we talk about in our summer program is, Hey,

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Speaker 2: everybody's not going to go and the way that this

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Speaker 2: is looking is from a court perspective, this may not

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Speaker 2: be the best option for you. So we have to

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Speaker 2: tell them about careers that they can do without a

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Speaker 2: college degree. So some of the things that they can

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Speaker 2: do are law enforcement. They can be a firefighter.

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Speaker 1: I think you need a college degree to be a cop.

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Speaker 2: No, I think you gotta go to academy.

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Speaker 1: Each state is different. Yeah, so New York State, I

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Speaker 1: think you have to have two year degree or two

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Speaker 1: years so with something something not a four year Degreekay.

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Speaker 2: Yeah, So you got firefighters, you have electricians, plumbers, there's.

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Speaker 1: Plenty of HVA.

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Speaker 2: There's plenty of careers that you can do with aut

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Speaker 2: a college degree. Yes you do need training, and yes

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Speaker 2: you do need licensing to do those careers, but you're

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Speaker 2: not going to come out of those trainings with one

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Speaker 2: hundred to two hundred thousand dollarsand death. I had a

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Speaker 2: friend of mine.

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Speaker 4: The other day, his son just got accepted to Ohio

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Speaker 4: State for aviation full ride, and just for curiosity curiosity,

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Speaker 4: I said, how much would that have cost you if

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Speaker 4: he didn't get the full ride?

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Speaker 2: You know number?

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Speaker 1: How much?

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Speaker 2: Three hundred thousand for four years at Ohio State? Three

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Speaker 2: hundred thousand. So imagine the kid who doesn't have the

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Speaker 2: full ride three hundred thousand and you're twenty one years old.

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Speaker 2: What job is going to pay you the type of

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Speaker 2: money that you can reimburse the government.

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Speaker 3: With no job right So it's either you're gonn to

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Speaker 3: pay a student loan or pay your rent at that point,

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Speaker 3: and most times they just stay at home.

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Speaker 2: People stay at home longer, like I said, So you

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Speaker 2: got to choose. It's like, is this the best route,

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Speaker 2: or can we go to schools that are going to

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Speaker 2: cost less or like what New York is doing, you

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Speaker 2: can go to school for free depending on your family's income.

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Speaker 2: And one of the stipulations is that you have to work

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Speaker 2: in the state in that field. So if you wanted

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Speaker 2: to be a teacher again, in New York State they

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Speaker 2: have their SELSIA program, that's what it's called. It's free

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Speaker 2: state schools. The only thing I think, Like every state

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Speaker 2: doesn't have like a SELSIA program, but New York State

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Speaker 2: has adopted it, and that's great. Like if I would

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Speaker 2: have had this CELSIA program, I walk out of school

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Speaker 2: with nothing because I went to school in New York.

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Speaker 2: I've worked only in New York for more than four years,

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Speaker 2: my tuition would have been free. So hopefully some states

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Speaker 2: start adopting policies like that, and if not, man, we're

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Speaker 2: going to have a huge problem on I had. Like

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Speaker 2: I said, right, it's a one point five trillion dollar

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Speaker 2: problem now that only grows because tuition is only grow.

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Speaker 1: Yes, yep, okay, well, and this is something that we

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Speaker 1: need to talk about on the campaign trail and elections

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Speaker 1: coming up, and I would urge everybody really, but especially

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Speaker 1: young people and parents to make that something that you know,

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Speaker 1: you hold your your elective officials accountable for because financial

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Speaker 1: aid and student loans, these things are very important and

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Speaker 1: it's a growing problem and it's only getting worse because

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Speaker 1: the course of education is only going up.

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Speaker 2: And the more you know, the better. Like I speak

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Speaker 2: to parents, and I speak to you know, young teens

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Speaker 2: all the time who have no idea about these things,

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Speaker 2: like we when we have these sessions in the summer

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Speaker 2: and the kids are like, wait, that's how much your

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Speaker 2: gloss Like, yeah, that's what you're walking into. So just

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Speaker 2: be prepared to know that and make sure that you

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Speaker 2: do everything possible, whether it's grants or whether it's scholarships,

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Speaker 2: so that you don't fall into this type of situation,

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Speaker 2: right because thirty six thousand, that's the average. That's a lot. Man.

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Speaker 1: Yeah, it is all right. Well there you have a

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Speaker 1: student loans in a nutshell. Okay, So we talked about

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Speaker 1: student loans and now we're going to talk about business.

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Speaker 1: The world of business and business is a contact sport.

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Speaker 1: I always say it's very competitive, right, So we haven't

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Speaker 1: really had like a head to head competition case study yet.

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Speaker 1: We did look at Rihanna and colleague Jenner's companies, but

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Speaker 1: those we didn't really compare those two companies. But now

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Speaker 1: we're going to do battle to titans, right, clash of

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Speaker 1: two big companies, Uber and Lyft. So Uber and Lyft

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Speaker 1: are both coming on the stock market soon. They are

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Speaker 1: both what's called IPO and you ipo that's when you

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Speaker 1: debut on the stock exchange, and they're very they're probably

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Speaker 1: the two biggest talk of the town when it comes

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Speaker 1: to Wall Street this year. Right, So, Uber and Lyft,

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Speaker 1: we're going to look at them, We're going to kind

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Speaker 1: of compare them, and then I have an interesting story.

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Speaker 1: We both have interesting stories about Uber that probably a

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Speaker 1: lot of people aren't fully aware of. So you want

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Speaker 1: to start this.

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Speaker 2: Off, Yeah, So let's just talk about the two differences

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Speaker 2: of the differences between the two companies. So Uber both

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Speaker 2: are ride sharing companies. Uber the much larger one. They're

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Speaker 2: in fifty eight countries over three hundred cities. Lift smaller,

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Speaker 2: they're in the forty six states in the United States

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Speaker 2: and in Canada. Uber again it's larger, so it has

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Speaker 2: more employees about twenty thousand compared to Lifts forty five hundred.

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Speaker 2: And the valuation is the big difference, the big difference.

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Speaker 2: So you got the valuation for Uber at seventy two

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Speaker 2: to seventy six billion, and then you have Left at

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Speaker 2: about fifteen billion. Now, when their IPO goes on the market,

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Speaker 2: they said that, you know, those numbers are most likely

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Speaker 2: to inflate when we have people invest in. So that's

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Speaker 2: just on the service for those two. They differ again

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Speaker 2: in their future innovations as well, so we have Uber. Obviously,

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Speaker 2: they try to compete with each other, so when one

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Speaker 2: company does something, the other one does the same. So

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Speaker 2: they start out with having cars, but both companies Uber

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Speaker 2: and Lyft have dabbled into the bike and scooter service business.

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Speaker 2: I believe Uber bought the company Jump, which is a

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Speaker 2: bike in scooter service, for about two hundred million, and

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Speaker 2: Lift bought Motivate, which is another bike and scooter service,

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Speaker 2: for about two hundred fifty minutes. So you can see

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Speaker 2: like when one makes a move, the other one is

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Speaker 2: trying to keep up. But then it kind of gets

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Speaker 2: a little difficult for the Lift because obviously they don't

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Speaker 2: have the same amount of employees. So Uber has a

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Speaker 2: huge deal in twenty seventeen. Actually in twenty fourteen, they

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Speaker 2: launched Uber Eats, which is huge, right, it's a delivery

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Speaker 2: service for food. But they get their biggest sponsor in

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Speaker 2: twenty seventeen, which is McDonald's. So McDonald's obviously world were

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Speaker 2: now probably the large franchise in the world. Thanks, yeah,

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Speaker 2: probably right, So they had a large franchise in the world.

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Speaker 2: Uber Eat signs up with them, so Lift says, you know,

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Speaker 2: let's let's try to get our own sponsor, and they

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Speaker 2: signed Taco Bell. Taco Bell, so I've never eaten Taco Bell.

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Speaker 1: I used to eat Taco Bell when I was in Hawaii.

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Speaker 2: Yeah, so they get Taco Bell and they decide to

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Speaker 2: have a campaign with it. So one of the things

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Speaker 2: is like the coldest thing Taco Mode. And I'm not

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Speaker 2: sure if anybody's ever used it, but Taco Mode was

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Speaker 2: only available and Lyft from the hours of nine pm

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Speaker 2: to two am, which is like, I think that's when

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Speaker 2: college students are hungary, is right, So like you call

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Speaker 2: your Lyft and you push Taco Mode and it takes

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Speaker 2: you the lift takes you to the nearest Taco Bell.

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Speaker 2: It is a complete failure. They tried it out. It

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Speaker 2: was a complete failure. They dropped it, and they haven't

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Speaker 2: got another sponsor as far as from the food. Another

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Speaker 2: thing about their future is that they have some some

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Speaker 2: things that Uber doesn't. And Uber has dealt with a

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Speaker 2: lot of scandal lately. So they've been in the news

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Speaker 2: for having the self driving cars that have failed.

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Speaker 1: They had a lawsuit.

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Speaker 2: They had a lawsuit of the car about a lawsuit.

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Speaker 1: So Uber Waymo you ever heard of Waymo Before No,

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Speaker 1: I'm pretty sure nobody has ever heard of Waymore, So

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Speaker 1: we have to give you the backstory on this. Google,

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Speaker 1: I'm pretty sure everybody has heard of Google. Right. Google

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Speaker 1: and Uber have a very complicated relationship. Google was kind

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Speaker 1: of Uber's big brother. It was like a big brother

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Speaker 1: little brother relationship. Right. In twenty thirteen, Google invests two

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Speaker 1: hundred and fifty eight million dollars into Uber, which gives

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Speaker 1: them about six percent of the company, and the CEOs

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Speaker 1: really like each other. They kick it off. Twenty fourteen,

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Speaker 1: the CEO of Google takes a ride with the CEO

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Speaker 1: of Uber and ubers knew they're trying to figure out

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Speaker 1: how to make self driving cars. Right. The relationships sours

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Speaker 1: the next year when Uber finds out that Google is

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Speaker 1: putting money into self driving car technologies by developing a

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Speaker 1: company named Waymo. Waymo is up is Google's self driving

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Speaker 1: car technology company. They have a whole company devoted for

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Speaker 1: self driving cars.

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Speaker 2: It sounds like a pick your brain.

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Speaker 1: Yeah, so Uber feels a way about this. So what

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Speaker 1: Uber does is that they recruit Google's one of their

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Speaker 1: top engineers at Wayne to come to work at Uber.

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Speaker 1: Right and right after he comes they purchased a self

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Speaker 1: driving car company. Forget the name of it, but it

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Speaker 1: makes them five hundred million dollars in revenue. Google sues

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Speaker 1: Uber because they said that the engineer stole twelve thousand

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Speaker 1: files from Waimo to give the Uber right. So now

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Speaker 1: they have a lawsuit where they're going back and forth

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Speaker 1: between if it was inside information that was stolen and

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Speaker 1: it's illegal.

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Speaker 2: To do that.

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Speaker 1: Uber so that they didn't do that. So long story short,

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Speaker 1: they settled a lawsuit, I believe a few weeks ago,

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Speaker 1: and they set up the lawsuit for zero point three

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Speaker 1: four percent of the company. Uber settled it with Google

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Speaker 1: and they gave Wayne Mo what we call thirty four

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Speaker 1: basis points. Thirty four basis points is point three four

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Speaker 1: thirty four percent of one percent of the company of Uber.

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Speaker 1: It doesn't really sound like a lot, but that's roughly

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Speaker 1: equal to two hundred and forty four million dollars. So

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Speaker 1: they settled out of They settled it for two hundred

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Speaker 1: and forty four million dollars. But they're still not admitting

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Speaker 1: that they did anything wrong. So now you have Uber

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Speaker 1: who is at odds with somebody that once was a

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Speaker 1: major investor, was still invested in them and it's a.

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Speaker 2: This episode is brought to you by PNC Bank. A

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434
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Speaker 2: back so you can focus on what matters most ready.

435
00:24:17,960 --> 00:24:21,320
Speaker 5: To see how Square can transform your business, visit Square

436
00:24:21,400 --> 00:24:25,919
Speaker 5: dot com backslash go backslash eyl to learn more that

437
00:24:26,119 --> 00:24:29,840
Speaker 5: Square dot com backslash, go backslash eyl.

438
00:24:30,000 --> 00:24:33,159
Speaker 2: Don't wait, don't hesitate. Let's Square handle the back end

439
00:24:33,400 --> 00:24:35,320
Speaker 2: so you can keep pushing your vision forward.

440
00:24:37,960 --> 00:24:40,679
Speaker 6: Coach, the energy out there felt different. What changed for

441
00:24:40,720 --> 00:24:41,359
Speaker 6: the team today?

442
00:24:41,440 --> 00:24:43,560
Speaker 7: It was a new game day Scratches from the California

443
00:24:43,640 --> 00:24:47,040
Speaker 7: Lottery players everything. Those games sent the team's energy through

444
00:24:47,040 --> 00:24:47,400
Speaker 7: the roof.

445
00:24:47,440 --> 00:24:49,439
Speaker 6: Are you saying it was the off field play that

446
00:24:49,480 --> 00:24:50,800
Speaker 6: made the difference on the field.

447
00:24:50,680 --> 00:24:53,440
Speaker 7: Hey, little play makes your day, and today it made

448
00:24:53,440 --> 00:24:55,879
Speaker 7: the game that's off of now, Coach.

449
00:24:55,720 --> 00:24:58,360
Speaker 6: One more question play than you. Los Angeles Chargers, San

450
00:24:58,359 --> 00:25:01,480
Speaker 6: Francisco forty nine Ers and Angelists. Ram scratchers from the

451
00:25:01,520 --> 00:25:05,040
Speaker 6: California lottery. A little play can make your day peace.

452
00:25:05,080 --> 00:25:07,119
Speaker 6: Play responsibly. Must be eighteen years or older to purchase

453
00:25:07,320 --> 00:25:07,919
Speaker 6: or claim.

454
00:25:07,720 --> 00:25:11,720
Speaker 1: Face for self driving cars. Right, there's a whole different conversation.

455
00:25:11,800 --> 00:25:15,400
Speaker 1: But the self driving car, I don't know about saying, well,

456
00:25:16,720 --> 00:25:20,280
Speaker 1: I'd rather trust a self driving car than a regular driver, right,

457
00:25:20,320 --> 00:25:23,760
Speaker 1: if you think about it, computers are probably more efficient

458
00:25:23,760 --> 00:25:29,520
Speaker 1: than people like, Look how many accidents there are in everything.

459
00:25:29,520 --> 00:25:30,600
Speaker 2: I'm not sure driving a car.

460
00:25:30,680 --> 00:25:33,280
Speaker 1: Okay, if you had it, if you had a computer

461
00:25:33,480 --> 00:25:36,640
Speaker 1: like ib In Watson, do you think that you would

462
00:25:36,720 --> 00:25:39,280
Speaker 1: trust them to do a calculation or would you trust.

463
00:25:39,040 --> 00:25:41,440
Speaker 2: I would trust that that. I would like that.

464
00:25:41,680 --> 00:25:42,440
Speaker 1: It's the same thing I.

465
00:25:42,400 --> 00:25:44,640
Speaker 2: Trust myself more than the computer. It's driving a car.

466
00:25:45,160 --> 00:25:48,720
Speaker 1: Well, the computers don't have distractions. They're not texting, they're

467
00:25:48,720 --> 00:25:52,120
Speaker 1: not looking at what's going on in the road, they're

468
00:25:52,119 --> 00:25:56,800
Speaker 1: not rubbernecking. Some people say it's actually a lot more

469
00:25:56,920 --> 00:26:01,639
Speaker 1: safer to have carless driver list cars.

470
00:26:03,680 --> 00:26:05,919
Speaker 2: I'm just yeah, I couldn't do it. I just personally

471
00:26:05,920 --> 00:26:08,320
Speaker 2: couldn't do it. It's happening, Yeah, I know it's happening.

472
00:26:08,359 --> 00:26:10,720
Speaker 1: And it's a race. It's a race who can do

473
00:26:10,760 --> 00:26:12,119
Speaker 1: it first. Yes, it's a race to who can do

474
00:26:12,160 --> 00:26:14,680
Speaker 1: it first. Elon Musk is involved with Tesla.

475
00:26:15,040 --> 00:26:19,000
Speaker 2: Uber is involved, but they've also like so Tesla himself

476
00:26:19,040 --> 00:26:21,399
Speaker 2: has had again so not scandal, but they've had some

477
00:26:21,440 --> 00:26:24,440
Speaker 2: controversy with some of their cars malfunctioning some of their

478
00:26:24,480 --> 00:26:25,280
Speaker 2: self driving.

479
00:26:25,160 --> 00:26:28,280
Speaker 1: Of course, but how many cars malfunction regularly?

480
00:26:28,359 --> 00:26:30,120
Speaker 2: Yeah, I mean people getting there's always going.

481
00:26:30,080 --> 00:26:32,160
Speaker 1: To be one card. It's not like it's never gonna

482
00:26:32,160 --> 00:26:33,159
Speaker 1: be one hundred percent.

483
00:26:32,920 --> 00:26:35,399
Speaker 2: Perfect, right, you know, people getting accidents every day exactly,

484
00:26:35,600 --> 00:26:38,840
Speaker 2: just true, exactly, And like you said, like there's gonna

485
00:26:38,840 --> 00:26:41,920
Speaker 2: be less distractions. Obviously there won't be if there's self driving,

486
00:26:41,920 --> 00:26:44,879
Speaker 2: there's not going to be any alcohol related accidents. So

487
00:26:45,160 --> 00:26:46,760
Speaker 2: like you said, but I don't know, I just feel

488
00:26:46,800 --> 00:26:50,680
Speaker 2: like the trust in myself over a computer, I would

489
00:26:50,840 --> 00:26:52,160
Speaker 2: I'd have to learn how to do that.

490
00:26:52,720 --> 00:26:56,000
Speaker 1: Well, we'll see. But it's interesting because now way Mo

491
00:26:56,320 --> 00:27:00,160
Speaker 1: is at a disadvantage because they're behind in the technol

492
00:27:00,600 --> 00:27:03,880
Speaker 1: Because now Uber people don't even people don't know that

493
00:27:04,280 --> 00:27:07,880
Speaker 1: Uber invests so much money and they're already planning their

494
00:27:07,920 --> 00:27:10,200
Speaker 1: next phase. It's one thing I do like about Uber.

495
00:27:11,240 --> 00:27:14,119
Speaker 1: They are constantly reinventing themselves, right, So they're rides sharing

496
00:27:14,200 --> 00:27:16,760
Speaker 1: company now, but they know that that space is crowded

497
00:27:17,080 --> 00:27:19,200
Speaker 1: and there's a lot of competition, and then there's problems,

498
00:27:19,200 --> 00:27:22,040
Speaker 1: political problems, stuff like that. So now they're already trying

499
00:27:22,040 --> 00:27:22,960
Speaker 1: to reinvent themselves.

500
00:27:23,119 --> 00:27:25,840
Speaker 2: The Uber eats, they got the food, the food delivery.

501
00:27:25,600 --> 00:27:29,680
Speaker 1: Your delivery. Now they have they have drones, food delivery drones.

502
00:27:29,720 --> 00:27:32,399
Speaker 2: And then they're investing in flying, so like they're thinking

503
00:27:32,440 --> 00:27:34,480
Speaker 2: already like down the line, like we're going to have

504
00:27:34,760 --> 00:27:38,040
Speaker 2: taxis that fly flying taxis.

505
00:27:38,200 --> 00:27:44,119
Speaker 1: Yes, that's flying taxi. No, it's yes, flying taxis. And

506
00:27:44,760 --> 00:27:48,479
Speaker 1: this that's what I'm saying. It's so crazy because Wayne Moo,

507
00:27:49,119 --> 00:27:52,399
Speaker 1: nobody's heard of weaymo before. Google has a billion dollar

508
00:27:52,520 --> 00:27:58,320
Speaker 1: company that nobody's heard of that is currently working on

509
00:27:58,440 --> 00:28:01,080
Speaker 1: ways to change the way that we travel.

510
00:28:02,560 --> 00:28:03,680
Speaker 2: That's pretty that's pretty crazy.

511
00:28:03,720 --> 00:28:04,320
Speaker 1: It's interesting.

512
00:28:04,680 --> 00:28:06,720
Speaker 2: So a part of the thing you said it like

513
00:28:06,760 --> 00:28:10,080
Speaker 2: politically like things are changing too, And what's happening here

514
00:28:10,119 --> 00:28:15,000
Speaker 2: in New York with Lyft and Uber is that they

515
00:28:15,080 --> 00:28:18,400
Speaker 2: have changed the way that New York City travel looks. Right,

516
00:28:18,520 --> 00:28:21,240
Speaker 2: we us It used to be yellow cabs that flooded

517
00:28:21,240 --> 00:28:25,200
Speaker 2: the city and now it's Uber and Lyft, and the

518
00:28:25,240 --> 00:28:28,840
Speaker 2: Taxi and Limousine Commission said, wait, they're taking away our business, right,

519
00:28:28,880 --> 00:28:31,119
Speaker 2: we have one fourth of the inventory that they have. Right,

520
00:28:31,160 --> 00:28:35,359
Speaker 2: people take their everyday cars and turn them into taxi services.

521
00:28:35,680 --> 00:28:37,479
Speaker 2: So what they said was like, we're going to file

522
00:28:37,520 --> 00:28:39,640
Speaker 2: a report and we're going to get to the bombs

523
00:28:39,720 --> 00:28:42,400
Speaker 2: because we're losing drivers at an alarming rate. And what

524
00:28:42,440 --> 00:28:44,400
Speaker 2: they did. What they found out was that the average

525
00:28:44,480 --> 00:28:46,800
Speaker 2: Uber and Lyft drivers they were making like fourteen dollars

526
00:28:46,840 --> 00:28:49,760
Speaker 2: an hour, which in New York City is not the

527
00:28:49,840 --> 00:28:50,600
Speaker 2: minimum wage.

528
00:28:50,960 --> 00:28:53,400
Speaker 1: The minimum wage is fifty fifteen dollars.

529
00:28:53,400 --> 00:28:56,240
Speaker 2: So when they found that out, they were like Uber said, hey,

530
00:28:56,520 --> 00:28:59,080
Speaker 2: we don't have to abide by the minimum wage because

531
00:28:59,720 --> 00:29:03,920
Speaker 2: these employees. We don't have employees. We have independent contractors.

532
00:29:03,400 --> 00:29:06,040
Speaker 1: Ten ninety nine independent contract.

533
00:29:05,720 --> 00:29:08,320
Speaker 2: Right, So when they have an independent contractor, they don't

534
00:29:08,360 --> 00:29:10,400
Speaker 2: have to by workplace laws like they don't have to

535
00:29:10,400 --> 00:29:12,920
Speaker 2: abide by minimum wage and they don't have to buy

536
00:29:13,120 --> 00:29:16,080
Speaker 2: over time and safe and healthy laws like you're an

537
00:29:16,080 --> 00:29:20,280
Speaker 2: independent contractor, right, So that that changes the way that

538
00:29:20,320 --> 00:29:23,720
Speaker 2: they look at the people who are working for them.

539
00:29:24,120 --> 00:29:27,880
Speaker 2: So from that New York City obviously won the case.

540
00:29:28,160 --> 00:29:30,600
Speaker 2: Mayor built a Vosia was part of that. Now the

541
00:29:30,640 --> 00:29:33,160
Speaker 2: minimum wage it has to be fifteen dollars for Uber

542
00:29:33,200 --> 00:29:35,800
Speaker 2: and Lyft drivers. But on top of it, and to

543
00:29:35,960 --> 00:29:39,560
Speaker 2: combat the overflux of these cars, like they're trying to

544
00:29:39,680 --> 00:29:43,840
Speaker 2: charge like tolls now to go into Lower Manhattan, they're saying, look,

545
00:29:43,840 --> 00:29:46,200
Speaker 2: we're doing a pause, so for twelve months to start,

546
00:29:46,240 --> 00:29:48,240
Speaker 2: I think in the summer this year, in twenty eighteen.

547
00:29:48,480 --> 00:29:51,080
Speaker 2: For twelve months, they're not allowed to have any new

548
00:29:51,120 --> 00:29:55,160
Speaker 2: licensed vehicles patrolling the streets of New York City. So,

549
00:29:55,200 --> 00:29:57,480
Speaker 2: like in Manhattan, that might sound good, but if you

550
00:29:57,560 --> 00:29:59,960
Speaker 2: live in the outer boroughs, like you might rely on

551
00:30:00,280 --> 00:30:02,680
Speaker 2: those services and you can't have any more right now.

552
00:30:03,320 --> 00:30:07,720
Speaker 1: Yes, yes, Well it's like I always say, you can't

553
00:30:07,720 --> 00:30:10,720
Speaker 1: stop energy. I don't think that that's a fight that

554
00:30:10,760 --> 00:30:16,440
Speaker 1: the city is going to win because Uber their groundbreaking.

555
00:30:16,880 --> 00:30:17,800
Speaker 2: They're not going anywhere.

556
00:30:17,800 --> 00:30:21,880
Speaker 1: It's groundbreaking, it's a groundbreaking idea, and it's disruptive, it's disruptive,

557
00:30:22,040 --> 00:30:27,000
Speaker 1: and it's changed changed everything. So I think that their

558
00:30:27,040 --> 00:30:30,200
Speaker 1: biggest competition will come from other companies like Lyft and

559
00:30:30,360 --> 00:30:34,320
Speaker 1: other new companies that spawn up, which is I'm pretty

560
00:30:34,320 --> 00:30:36,360
Speaker 1: sure they are aware of that, and which is why

561
00:30:36,400 --> 00:30:40,400
Speaker 1: they are constantly reinventing themselves and adding new facets to

562
00:30:40,440 --> 00:30:44,040
Speaker 1: their company. Neither Lift or Google It. Neither Lift or

563
00:30:44,160 --> 00:30:48,280
Speaker 1: Uber is profitable, by the way, But it'll be interesting

564
00:30:48,280 --> 00:30:49,880
Speaker 1: to see how you know, when the IPO I think

565
00:30:49,920 --> 00:30:54,680
Speaker 1: that you know, obviously Lift is that disadvantage their smaller company.

566
00:30:54,920 --> 00:30:58,440
Speaker 1: They have less, like you said, drivers, they have less revenue,

567
00:30:58,480 --> 00:31:03,720
Speaker 1: they have less everything globally than newer But at one point,

568
00:31:03,880 --> 00:31:07,160
Speaker 1: you know, my Space was bigger than Facebook. True, at

569
00:31:07,160 --> 00:31:10,280
Speaker 1: one point Blockbuster was bigger than Netflix.

570
00:31:10,520 --> 00:31:12,080
Speaker 2: Never never discount the underdogs.

571
00:31:13,240 --> 00:31:15,120
Speaker 1: Just because somebody's number one right now does not mean

572
00:31:15,120 --> 00:31:18,840
Speaker 1: that they're going to be number one forether. So it'll

573
00:31:18,960 --> 00:31:22,360
Speaker 1: you know, be entertaining to watch to see how did

574
00:31:22,400 --> 00:31:24,600
Speaker 1: some play, how did some folds, Whether you know, they

575
00:31:24,640 --> 00:31:28,160
Speaker 1: get brought by a company, whether they take each other over,

576
00:31:28,320 --> 00:31:32,320
Speaker 1: whether they both succeed, who knows, but everybody.

577
00:31:31,840 --> 00:31:33,080
Speaker 2: It might be a third party that comes in.

578
00:31:33,080 --> 00:31:35,000
Speaker 1: Who knows, it might be a whole completely different new

579
00:31:35,040 --> 00:31:37,280
Speaker 1: company that comes in. So all right, well, we will

580
00:31:37,320 --> 00:31:40,760
Speaker 1: follow it. We will look to see what happens and

581
00:31:40,800 --> 00:31:42,520
Speaker 1: when the I p os we definitely will have a

582
00:31:42,520 --> 00:31:55,200
Speaker 1: follow up on both of them.

583
00:31:55,280 --> 00:31:57,440
Speaker 2: All right, ladies and gentlemen, it is now storytime.

584
00:31:58,320 --> 00:32:01,960
Speaker 8: Here's a little story that must be Listen up, gangsters

585
00:32:02,000 --> 00:32:03,920
Speaker 8: and honeys, with your head done the best story.

586
00:32:04,000 --> 00:32:06,600
Speaker 2: Tell us stuff now, right, pray downs gray us.

587
00:32:07,040 --> 00:32:14,040
Speaker 1: Okay, So, boys and girls, today's story. This episode's story

588
00:32:14,520 --> 00:32:16,800
Speaker 1: will be on Airbnb.

589
00:32:17,520 --> 00:32:20,560
Speaker 2: Airbnb Airbnb. Man. Amazing story.

590
00:32:20,880 --> 00:32:25,200
Speaker 1: Phenomenal, phenomenal story. So I'll started off in two thousand

591
00:32:25,200 --> 00:32:34,360
Speaker 1: and seven, right, Joe gad Drabbi Gebbia and Brian Sheesky.

592
00:32:35,160 --> 00:32:37,640
Speaker 1: They were both twenty seven at the time, right, and

593
00:32:37,680 --> 00:32:40,440
Speaker 1: they lived in San Francisco. If anybody's not familiar, San Francisco,

594
00:32:40,480 --> 00:32:44,680
Speaker 1: I believe is the most expensive place to live in America,

595
00:32:45,000 --> 00:32:48,600
Speaker 1: highest real estate. I'm pretty sure. I'm pretty sure. No,

596
00:32:48,640 --> 00:32:51,080
Speaker 1: I think it's more explored than that. Yeah, I'm pretty

597
00:32:51,120 --> 00:32:56,240
Speaker 1: sure it is. So they were struggling to pay rent, right,

598
00:32:56,320 --> 00:32:59,840
Speaker 1: you know, twenty seven year olds stretch out of college, struggling.

599
00:33:00,080 --> 00:33:03,080
Speaker 1: So they live together. They have like a two bedroom apartment.

600
00:33:03,120 --> 00:33:06,800
Speaker 1: I as soon and it was a big conference coming

601
00:33:06,880 --> 00:33:08,360
Speaker 1: up in the City of Design conference.

602
00:33:08,640 --> 00:33:11,440
Speaker 2: So they both come from the Rhode Island School of Design.

603
00:33:11,880 --> 00:33:14,760
Speaker 2: So there was a design conference coming and they were

604
00:33:14,760 --> 00:33:15,680
Speaker 2: playing on attendance.

605
00:33:15,760 --> 00:33:19,680
Speaker 1: Yeah, so all the hotels in the city were booked.

606
00:33:20,320 --> 00:33:22,680
Speaker 1: Because if anybody familiar with San Francisco, San Franciscoco is

607
00:33:22,720 --> 00:33:24,240
Speaker 1: a very small city. That's why our real estate is

608
00:33:24,240 --> 00:33:27,040
Speaker 1: so expensive in San Francisco because it's very small. Obviously

609
00:33:27,120 --> 00:33:29,600
Speaker 1: you have to look on valley nearby and tech industry.

610
00:33:29,800 --> 00:33:32,800
Speaker 1: So it's a couple of different things that makes Simrancisco

611
00:33:32,840 --> 00:33:36,280
Speaker 1: so expensive. It's very small, and you're surrounded by the

612
00:33:36,280 --> 00:33:41,480
Speaker 1: tech industry, which billionaires all around, so land is very scarce.

613
00:33:42,280 --> 00:33:45,600
Speaker 1: So all the hotels in the city were booked, right,

614
00:33:45,840 --> 00:33:50,280
Speaker 1: So they have the bright idea to rent out their

615
00:33:50,360 --> 00:33:53,120
Speaker 1: living room for people that are looking for hotels. They

616
00:33:53,120 --> 00:33:54,840
Speaker 1: know people are coming into the city and that they're

617
00:33:54,840 --> 00:33:56,000
Speaker 1: not going to have anywhere to stay.

618
00:33:56,040 --> 00:33:58,480
Speaker 2: Yeah. I think Joe sends an email to Brian like, hey,

619
00:33:58,760 --> 00:34:00,840
Speaker 2: I have this idea, and he shows it that a

620
00:34:00,920 --> 00:34:03,680
Speaker 2: lot of his press commas is I have this idea. Yeah,

621
00:34:03,720 --> 00:34:05,440
Speaker 2: you know what, there's no more city, there's no more

622
00:34:05,440 --> 00:34:08,440
Speaker 2: hotels in the city, there's no more rooms. We got something.

623
00:34:08,480 --> 00:34:12,000
Speaker 1: So they want to put three airbeds in their living

624
00:34:12,040 --> 00:34:16,600
Speaker 1: room on the floor and they are gonna cook their

625
00:34:16,920 --> 00:34:17,800
Speaker 1: guest breakfast.

626
00:34:18,000 --> 00:34:19,960
Speaker 2: Right, so we're gonna rent the space. We have some

627
00:34:20,000 --> 00:34:23,239
Speaker 2: space in the living room, three air mattresses. Not only

628
00:34:23,280 --> 00:34:25,640
Speaker 2: we're gonna let people rent that, but like you said,

629
00:34:25,640 --> 00:34:27,439
Speaker 2: we're gonna make breakfast for them.

630
00:34:27,440 --> 00:34:30,600
Speaker 1: So the next day they launched a website. The website

631
00:34:30,680 --> 00:34:35,719
Speaker 1: is called air Bed and Breakfast dot com because they

632
00:34:35,760 --> 00:34:38,719
Speaker 1: give you an airbed and breakfast, because they're gonna make

633
00:34:38,760 --> 00:34:43,799
Speaker 1: you breakfast airbed and breakfast, hence the name Airbnb, but

634
00:34:43,920 --> 00:34:46,319
Speaker 1: at first it was called airbed and Breakfast dot com, right,

635
00:34:47,040 --> 00:34:52,960
Speaker 1: So from there they a few weeks later they actually

636
00:34:53,000 --> 00:34:56,399
Speaker 1: get three people to come and I think they charged

637
00:34:56,440 --> 00:35:01,840
Speaker 1: them eighty dollars a night person. Yeah right, and it

638
00:35:01,880 --> 00:35:05,600
Speaker 1: worked out for them. And then next year is when

639
00:35:05,640 --> 00:35:08,400
Speaker 1: they really take off because now they have an idea,

640
00:35:08,440 --> 00:35:10,440
Speaker 1: they have a business model, we have a website.

641
00:35:10,520 --> 00:35:12,400
Speaker 2: Before they get to the next year, like they're broke.

642
00:35:12,920 --> 00:35:15,080
Speaker 2: Oh that it broke, so like that conference came in

643
00:35:15,120 --> 00:35:17,520
Speaker 2: the left and they still can't pay the rent. So

644
00:35:17,600 --> 00:35:20,280
Speaker 2: what they did is they took out as many credit

645
00:35:20,320 --> 00:35:22,680
Speaker 2: cards as they could. I think he tells a story

646
00:35:22,680 --> 00:35:24,600
Speaker 2: where he has well he remember he used to have

647
00:35:24,600 --> 00:35:26,719
Speaker 2: trading cards and you slip them in. He had a

648
00:35:26,719 --> 00:35:28,719
Speaker 2: trading card book, but it was just credit cards. And

649
00:35:28,800 --> 00:35:31,960
Speaker 2: I think they accumulated like fifteen thousand dollars in credit

650
00:35:31,960 --> 00:35:34,719
Speaker 2: card debt each just to they couldn't take out any

651
00:35:34,760 --> 00:35:36,239
Speaker 2: more cash advances on their credit card.

652
00:35:36,520 --> 00:35:40,959
Speaker 1: Cash advances powerful tool, very dangerous tools.

653
00:35:43,160 --> 00:35:44,120
Speaker 2: We have some stories on them.

654
00:35:44,160 --> 00:35:49,000
Speaker 1: Yes, that's a different story. Okay. So next year, two

655
00:35:49,000 --> 00:35:53,799
Speaker 1: thousand and eight, there's a senator that is the talk

656
00:35:53,880 --> 00:35:58,560
Speaker 1: of politics. His name is Barack Obama, right, so it

657
00:35:58,640 --> 00:36:03,480
Speaker 1: is he's running for president the first time, obviously, and

658
00:36:03,520 --> 00:36:07,799
Speaker 1: there's the Democratic National Convention, which is held in Denver, Colorado.

659
00:36:09,239 --> 00:36:12,800
Speaker 1: So they gear up for the Democratic National Convention.

660
00:36:12,880 --> 00:36:14,120
Speaker 2: Yeah, they got another idea.

661
00:36:13,840 --> 00:36:16,600
Speaker 1: They can today saying, okay, this is a perfect I

662
00:36:16,640 --> 00:36:19,480
Speaker 1: think eighty thousand people were going to come into Denver

663
00:36:20,239 --> 00:36:22,759
Speaker 1: and there's not gonna be enough hotels, very similar to

664
00:36:22,800 --> 00:36:25,399
Speaker 1: what they did in San Francisco, but now they want

665
00:36:25,400 --> 00:36:27,920
Speaker 1: to scale it. So they want to recruit other people

666
00:36:28,080 --> 00:36:31,480
Speaker 1: to rent their apartments, re rent their homes, and then

667
00:36:31,520 --> 00:36:33,719
Speaker 1: they get a portion of that and they'll broker it

668
00:36:33,800 --> 00:36:34,200
Speaker 1: for them.

669
00:36:34,239 --> 00:36:36,040
Speaker 2: And yeah, the idea was like we're going to find

670
00:36:36,080 --> 00:36:39,160
Speaker 2: Obama supporters in Denver to open up their homes for

671
00:36:39,200 --> 00:36:40,200
Speaker 2: other Obama supporters.

672
00:36:40,280 --> 00:36:42,000
Speaker 1: Think you had eight hundred listings they were able to

673
00:36:42,000 --> 00:36:44,439
Speaker 1: find it. Yeah, eight hundred homes and it was great.

674
00:36:44,480 --> 00:36:46,920
Speaker 1: They made some money, they made it. They made a

675
00:36:46,960 --> 00:36:47,800
Speaker 1: little bit of money.

676
00:36:47,680 --> 00:36:50,759
Speaker 2: Yeah, some money. Yeah, not enough, not enough. Yeah. So

677
00:36:51,000 --> 00:36:53,839
Speaker 2: they still even after the convention, they're still broke.

678
00:36:53,960 --> 00:36:56,680
Speaker 1: No, no, before the convention is over, before the convention

679
00:36:56,760 --> 00:36:59,520
Speaker 1: is over. Leading up to it, they have eight hundred

680
00:36:59,760 --> 00:37:02,480
Speaker 1: homes and apartments that they were able to get people

681
00:37:02,520 --> 00:37:05,000
Speaker 1: to rent, but they still didn't really make any money, right,

682
00:37:05,040 --> 00:37:07,400
Speaker 1: I don't know why. I guess it just wasn't profitable

683
00:37:07,480 --> 00:37:11,240
Speaker 1: for whatever reasons. So now they go to the convention

684
00:37:11,520 --> 00:37:15,560
Speaker 1: and they have the bright idea as a marketing tool,

685
00:37:15,560 --> 00:37:16,960
Speaker 1: and they didn't really do this to make money. They

686
00:37:16,960 --> 00:37:20,280
Speaker 1: did this as a marketing tool to make cereal limited

687
00:37:20,320 --> 00:37:22,920
Speaker 1: boxes of cereal. They have the Obama os and the

688
00:37:23,200 --> 00:37:24,840
Speaker 1: Captain McCain cereal.

689
00:37:25,160 --> 00:37:27,799
Speaker 2: So the it ties into what they do, Right, we're

690
00:37:27,800 --> 00:37:30,560
Speaker 2: going to give you the room, and how are we

691
00:37:30,600 --> 00:37:32,440
Speaker 2: going to make breakfast now for you? Because the original

692
00:37:32,480 --> 00:37:34,400
Speaker 2: thing is like you'll get the room and we'll provide

693
00:37:34,400 --> 00:37:35,000
Speaker 2: breakfast but.

694
00:37:34,920 --> 00:37:36,319
Speaker 1: This was more of a pr store.

695
00:37:36,360 --> 00:37:38,600
Speaker 2: Yeah. No, but so he says it in some of

696
00:37:38,640 --> 00:37:41,920
Speaker 2: his speeches. He's like, look, we had to figure out

697
00:37:41,920 --> 00:37:43,719
Speaker 2: how we're going to scale breakfast, So are we going

698
00:37:43,840 --> 00:37:46,680
Speaker 2: to put eggs and ship it to people? No, We're

699
00:37:46,680 --> 00:37:48,719
Speaker 2: going to make cereal. So what they did, like I

700
00:37:48,719 --> 00:37:53,600
Speaker 2: think Joe Gobia does, is he goes to like the

701
00:37:53,719 --> 00:37:56,400
Speaker 2: cheapest places he can find cereal. So he goes to

702
00:37:56,440 --> 00:37:59,160
Speaker 2: like dollar stores and buy cereal, and they press up

703
00:37:59,640 --> 00:38:02,000
Speaker 2: these pictures. They go to an architect like, hey, we

704
00:38:02,040 --> 00:38:04,400
Speaker 2: need you to draw this picture. So they have Obama

705
00:38:04,719 --> 00:38:07,160
Speaker 2: and they have McCain on the cereal box and they

706
00:38:07,160 --> 00:38:08,200
Speaker 2: make it limited.

707
00:38:07,960 --> 00:38:09,319
Speaker 1: Edition, limited edition.

708
00:38:09,480 --> 00:38:11,360
Speaker 2: Yeah, and each box has like the numbers, so if

709
00:38:11,400 --> 00:38:13,839
Speaker 2: you bought one, you know that you have four out

710
00:38:13,920 --> 00:38:15,880
Speaker 2: of five hundred. Because I think they only did one

711
00:38:15,880 --> 00:38:17,840
Speaker 2: thousand buses. I think it was eight hundred one thousand

712
00:38:17,880 --> 00:38:20,359
Speaker 2: boxes each. Each candidate got five hundred boxes, so they

713
00:38:20,360 --> 00:38:23,319
Speaker 2: put like like four out of two hundred or five

714
00:38:23,360 --> 00:38:26,240
Speaker 2: out of two hundred, so everybody had a limited number

715
00:38:26,320 --> 00:38:30,120
Speaker 2: on their box. Okay, the brilliant thing is that we

716
00:38:30,200 --> 00:38:32,799
Speaker 2: know boxes of cereal of course, like four dollars at

717
00:38:32,840 --> 00:38:35,920
Speaker 2: the most sometimes a little bit more of super size.

718
00:38:36,680 --> 00:38:37,879
Speaker 2: They charged four dollars for the.

719
00:38:37,840 --> 00:38:41,399
Speaker 1: Box and they made thirty thousand dollars, So they made

720
00:38:41,400 --> 00:38:46,640
Speaker 1: thirty thousand dollars off cereal and that was enough to

721
00:38:46,760 --> 00:38:52,920
Speaker 1: propel them next year going forward where they finally got

722
00:38:52,920 --> 00:38:55,000
Speaker 1: the business off the ground, off and running, and then

723
00:38:55,040 --> 00:38:58,080
Speaker 1: they were able to get substantial amount of money from

724
00:38:58,080 --> 00:39:02,280
Speaker 1: an angel investor, some seed money, some seed money. Then

725
00:39:02,760 --> 00:39:08,719
Speaker 1: in twenty eleven they get even more money from Ashton

726
00:39:08,840 --> 00:39:14,400
Speaker 1: Kusher legend. People don't He's made.

727
00:39:14,239 --> 00:39:15,120
Speaker 2: Some brilliant moves.

728
00:39:15,280 --> 00:39:16,560
Speaker 1: People don't even remember him.

729
00:39:17,560 --> 00:39:18,040
Speaker 2: Was it Pumped?

730
00:39:18,160 --> 00:39:19,680
Speaker 1: Was that the show punk?

731
00:39:20,120 --> 00:39:22,319
Speaker 2: I think that's what that the seventies show?

732
00:39:22,360 --> 00:39:26,440
Speaker 1: First, the seventy show Punked. He had this movie called

733
00:39:26,440 --> 00:39:27,320
Speaker 1: The Butterfly Effect.

734
00:39:27,400 --> 00:39:29,400
Speaker 3: I was just yeah, that was That was a decent movie.

735
00:39:29,680 --> 00:39:32,840
Speaker 3: And then he married the Jimmy Moore. Right, he was

736
00:39:32,880 --> 00:39:33,840
Speaker 3: married to Demi.

737
00:39:33,560 --> 00:39:35,239
Speaker 2: Moore and now he's married to Melakunis.

738
00:39:36,000 --> 00:39:40,560
Speaker 1: Okay, Ashton Cusher. Not to get off topic here, but

739
00:39:41,760 --> 00:39:47,160
Speaker 1: the guys a genius RIGHTOD movies, he's angel investor, He's

740
00:39:47,160 --> 00:39:50,600
Speaker 1: a Hollywood A list celebrity who, at the peak of

741
00:39:50,600 --> 00:39:53,880
Speaker 1: his career decides to switch his focus and become an

742
00:39:53,880 --> 00:39:56,799
Speaker 1: investor in tech companies. Some of the companies that he

743
00:39:56,880 --> 00:40:03,080
Speaker 1: invested in early Spotify, Airbnb, Uber, Twitter, and now Ripple

744
00:40:04,120 --> 00:40:08,880
Speaker 1: Yes cryptocurrency. Ripple So Aston Kusha comes in twenty eleven,

745
00:40:08,920 --> 00:40:13,800
Speaker 1: gives them money.

746
00:40:11,600 --> 00:40:12,280
Speaker 2: And then.

747
00:40:13,680 --> 00:40:17,640
Speaker 1: They skyrocket skyrocket, right.

748
00:40:17,719 --> 00:40:20,080
Speaker 2: It gives them money to hire more staffing. They go

749
00:40:20,280 --> 00:40:25,160
Speaker 2: staffing the United States to now Europe. Officers become global Global.

750
00:40:26,920 --> 00:40:30,440
Speaker 1: Their current valuation is thirty eight billion dollars.

751
00:40:32,239 --> 00:40:37,520
Speaker 2: Wow, yeah, I think so. They're both founders. It's three

752
00:40:37,560 --> 00:40:43,359
Speaker 2: act founders. They're each worth four billion dollars four billion.

753
00:40:43,360 --> 00:40:44,879
Speaker 2: They're under forty years old.

754
00:40:45,760 --> 00:40:48,360
Speaker 1: Ye, thirty eight billion dollar valuation. The reason why I

755
00:40:48,400 --> 00:40:53,839
Speaker 1: like this story is because it highlights if you are

756
00:40:53,960 --> 00:40:56,840
Speaker 1: an entrepreneur, you have to do whatever you have to do.

757
00:40:56,840 --> 00:41:00,200
Speaker 1: You have to hustle at all courts. Right. So they're

758
00:41:00,200 --> 00:41:04,080
Speaker 1: starting an idea to put air mattresses in their living

759
00:41:04,120 --> 00:41:05,440
Speaker 1: room and they make people breakfast.

760
00:41:05,640 --> 00:41:08,560
Speaker 2: Nobody believed in them, like they took this to Silicon

761
00:41:08,640 --> 00:41:10,279
Speaker 2: Valley and had twenty investors.

762
00:41:10,400 --> 00:41:13,600
Speaker 1: No, it's laughable if you take if you think about it, right,

763
00:41:13,960 --> 00:41:15,960
Speaker 1: you're putting three air mattresses in your living room and

764
00:41:15,960 --> 00:41:17,880
Speaker 1: you're gonna make people breakfast, and you're gonna name the

765
00:41:17,920 --> 00:41:20,680
Speaker 1: company airbed and Breakfast.

766
00:41:21,239 --> 00:41:23,719
Speaker 2: They said. They laughed at they. That's not a joe.

767
00:41:23,760 --> 00:41:25,359
Speaker 2: They laughed at them, and they said, this is never

768
00:41:25,400 --> 00:41:28,760
Speaker 2: gonna work. They had twenty investors. Ten of them didn't

769
00:41:28,760 --> 00:41:31,120
Speaker 2: respond to their emails, five of them met with them,

770
00:41:31,520 --> 00:41:34,279
Speaker 2: and the other five sat down and had a ten

771
00:41:34,400 --> 00:41:37,200
Speaker 2: minute conversation. All of them said no, none of them

772
00:41:37,200 --> 00:41:37,680
Speaker 2: believed in.

773
00:41:37,640 --> 00:41:41,480
Speaker 1: It, and then right nobody believed in it. And then

774
00:41:42,280 --> 00:41:45,880
Speaker 1: when all else fails, they realize that they have to

775
00:41:45,960 --> 00:41:47,920
Speaker 1: go to plan B and they sell cereal.

776
00:41:48,120 --> 00:41:50,560
Speaker 2: And that's what gets the money from the seat investors.

777
00:41:50,560 --> 00:41:53,880
Speaker 2: They're like, if you can sell cereal to people at

778
00:41:53,920 --> 00:41:56,520
Speaker 2: four hours a box, you must be on something.

779
00:41:56,600 --> 00:41:58,920
Speaker 1: If one hustle isn't working, you gotta switch.

780
00:41:58,719 --> 00:42:01,799
Speaker 2: It, right. He said that his mom would call him like, wait,

781
00:42:01,960 --> 00:42:05,640
Speaker 2: I thought you guys were a chain of like hotel services.

782
00:42:05,640 --> 00:42:07,680
Speaker 2: Like you're selling cereal, nount here a food company.

783
00:42:07,400 --> 00:42:09,440
Speaker 3: You know, So whatever we have to do to get

784
00:42:09,480 --> 00:42:11,600
Speaker 3: this money, whatever by any means necessary.

785
00:42:11,680 --> 00:42:14,480
Speaker 2: Yeah, But it didn't. Like I said, it didn't work

786
00:42:14,480 --> 00:42:16,799
Speaker 2: at first, and they had to go to the drawing

787
00:42:16,840 --> 00:42:20,000
Speaker 2: board and one of the things they said they met

788
00:42:20,040 --> 00:42:21,600
Speaker 2: an investor and he was like, go meet your people,

789
00:42:22,200 --> 00:42:24,360
Speaker 2: And what that really meant was like, why isn't it working?

790
00:42:24,600 --> 00:42:27,319
Speaker 2: And they found out that when they went to some

791
00:42:27,400 --> 00:42:30,040
Speaker 2: of the places that they were listing, they realized that

792
00:42:30,040 --> 00:42:32,880
Speaker 2: the people weren't taking great pictures. It wasn't displaying the

793
00:42:32,920 --> 00:42:35,120
Speaker 2: homes like they should. So they said they went to

794
00:42:35,160 --> 00:42:38,000
Speaker 2: New York and they went to Manhattan and Brooklyn and

795
00:42:38,080 --> 00:42:41,120
Speaker 2: they went to each listing and said, look, here's the

796
00:42:41,160 --> 00:42:43,040
Speaker 2: camera I want you to use when you take these pictures.

797
00:42:43,080 --> 00:42:45,920
Speaker 1: And from that moment, and it's important too, because you know,

798
00:42:45,960 --> 00:42:47,879
Speaker 1: when we say all right, we give you guys these

799
00:42:47,920 --> 00:42:52,200
Speaker 1: case studies. So when you go to business school, Harvard, yeah, whatever,

800
00:42:52,360 --> 00:42:55,359
Speaker 1: top business school, boarding, they go through case studies, right,

801
00:42:55,560 --> 00:42:59,799
Speaker 1: and it's entertaining stories, but it's more so it's education. Right.

802
00:43:00,040 --> 00:43:01,960
Speaker 1: We're not just giving you these case studies just to

803
00:43:02,239 --> 00:43:05,080
Speaker 1: entertain you. Hopefully you can learn something from it and

804
00:43:05,160 --> 00:43:07,560
Speaker 1: implement it in your business, whether you sell t shirts,

805
00:43:07,880 --> 00:43:11,000
Speaker 1: whether you're a barber, whatever, you can learn from other

806
00:43:11,040 --> 00:43:14,880
Speaker 1: people's success stories and figure out a way how you

807
00:43:14,960 --> 00:43:18,080
Speaker 1: can copy what they have done. Right, there's nothing wrong

808
00:43:18,120 --> 00:43:22,000
Speaker 1: with it okay what they have done or inspire you

809
00:43:22,120 --> 00:43:25,120
Speaker 1: or gain some type of insight. So I just want

810
00:43:25,160 --> 00:43:26,600
Speaker 1: to leave that because you know, we give a lot

811
00:43:26,600 --> 00:43:30,759
Speaker 1: of these stories and they are entertaining, but it's not

812
00:43:30,920 --> 00:43:34,680
Speaker 1: just a bedtime story. It's for actual action, like to

813
00:43:34,719 --> 00:43:38,680
Speaker 1: take action, to leave some inspiration. So hopefully that story,

814
00:43:38,719 --> 00:43:41,080
Speaker 1: to me at very least is a very inspirational story

815
00:43:41,120 --> 00:43:43,840
Speaker 1: for a few different reasons. But I just feel that

816
00:43:44,920 --> 00:43:47,799
Speaker 1: stories like that really, you know, give you the push

817
00:43:47,880 --> 00:43:50,720
Speaker 1: to keep going because it's not going to be easy

818
00:43:50,840 --> 00:43:52,279
Speaker 1: in any type of business that you do.

819
00:43:52,400 --> 00:43:54,840
Speaker 2: Two thousand and seven, nobody believes in them. Two thousand

820
00:43:54,840 --> 00:43:59,440
Speaker 2: and sixteen, they become the official sponsor of the Summer Olympics.

821
00:44:00,080 --> 00:44:03,080
Speaker 2: Like this brand that nobody believed in. So like that,

822
00:44:03,080 --> 00:44:03,600
Speaker 2: that's to.

823
00:44:03,560 --> 00:44:06,160
Speaker 3: Tell you, like, just be persistent from thirty believing itself

824
00:44:06,200 --> 00:44:10,640
Speaker 3: from broke to thirty thousand cereos to thirty eight billion

825
00:44:10,840 --> 00:44:13,520
Speaker 3: valuation in ten years.

826
00:44:13,840 --> 00:44:17,240
Speaker 2: And anybody can do that. Yes, anybody can be a host.

827
00:44:17,400 --> 00:44:21,160
Speaker 2: So it's like if you have space, like anybody, it's.

828
00:44:21,920 --> 00:44:25,239
Speaker 1: It's disruptive idea. They disrupted the hotel industry, which was

829
00:44:25,280 --> 00:44:27,640
Speaker 1: the same for one hundred years, so if you want

830
00:44:27,680 --> 00:44:30,759
Speaker 1: to find the next big thing, see what hasn't been

831
00:44:30,920 --> 00:44:34,080
Speaker 1: changed in the last hundred years and find a way

832
00:44:34,120 --> 00:44:34,839
Speaker 1: to disrupt that.

833
00:44:34,920 --> 00:44:37,640
Speaker 2: And look across, look across, like the people around you

834
00:44:37,719 --> 00:44:38,719
Speaker 2: might be able to help you.

835
00:44:38,800 --> 00:44:40,680
Speaker 1: Yep, right, that's another lesson.

836
00:44:40,680 --> 00:44:43,319
Speaker 2: He reached out to his friend who's from the same

837
00:44:43,360 --> 00:44:45,960
Speaker 2: design school. He reached out to another friend that was

838
00:44:45,960 --> 00:44:47,960
Speaker 2: a web developer. That's how they got the site up.

839
00:44:48,280 --> 00:44:51,400
Speaker 2: And then the person who gives them to seed money

840
00:44:51,640 --> 00:44:54,480
Speaker 2: actually came from came from the Rhode Island School Design.

841
00:44:54,680 --> 00:44:56,279
Speaker 2: He was like, wait, let me at least have a

842
00:44:56,320 --> 00:44:58,480
Speaker 2: meeting with these guys since they came from our school.

843
00:44:58,960 --> 00:45:02,920
Speaker 2: And that's how it starts. Man Reach Across, Man Reach across.

844
00:45:03,160 --> 00:45:08,600
Speaker 1: Okay, well, before we leave, we have some exciting news.

845
00:45:08,680 --> 00:45:12,760
Speaker 2: Yeah, so we are again on YouTube, which we announced

846
00:45:12,840 --> 00:45:16,719
Speaker 2: on the last episode, but now we have our merch

847
00:45:16,840 --> 00:45:20,240
Speaker 2: up on earnier Leisure dot com, so we have some

848
00:45:20,239 --> 00:45:23,360
Speaker 2: some some cool ideas that are up there, so you know,

849
00:45:23,360 --> 00:45:26,560
Speaker 2: feel free to support. We also have our Patreon app

850
00:45:27,120 --> 00:45:30,120
Speaker 2: which is going to be provided some exclusive and behind

851
00:45:30,120 --> 00:45:33,080
Speaker 2: the scenes content and also some other features that we

852
00:45:33,160 --> 00:45:36,680
Speaker 2: thought that would help people. By requests pretty much people

853
00:45:36,680 --> 00:45:39,239
Speaker 2: have been asking some things, and yeah, we thought we

854
00:45:39,280 --> 00:45:42,280
Speaker 2: felt like Patreon would be a good avenue to address

855
00:45:42,280 --> 00:45:42,960
Speaker 2: some of those topics.

856
00:45:43,040 --> 00:45:45,120
Speaker 1: Patreon is something that we're definitely excited about, something that

857
00:45:45,120 --> 00:45:47,160
Speaker 1: we've been working on. So, you know, we give a

858
00:45:47,160 --> 00:45:51,960
Speaker 1: lot of free game for you long time my Instagram page.

859
00:45:52,440 --> 00:45:56,279
Speaker 1: Two years we do. We do the podcast, so a

860
00:45:56,320 --> 00:45:58,400
Speaker 1: lot of time people have even more questions or they

861
00:45:58,400 --> 00:46:02,520
Speaker 1: want like kind of like mentorship, pick business coaching, or

862
00:46:02,560 --> 00:46:05,000
Speaker 1: pick my brain or just even stuff with the podcast.

863
00:46:05,040 --> 00:46:08,360
Speaker 1: We talked probably about an hour after the podcast is

864
00:46:08,360 --> 00:46:11,200
Speaker 1: over with, were just going to end depth stuff so

865
00:46:11,360 --> 00:46:12,880
Speaker 1: you guys be able to see it when you're going in.

866
00:46:13,040 --> 00:46:16,920
Speaker 1: But that's all the extra bonus features and all of

867
00:46:16,960 --> 00:46:21,480
Speaker 1: that stuff will be laid out in our Patreon. All

868
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Speaker 1: of the links will be on our website and uh yeah,

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00:46:25,440 --> 00:46:28,840
Speaker 1: YouTube the merch the merchant Dope too. I'm not just

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00:46:28,880 --> 00:46:31,440
Speaker 1: saying that because I'm involved with it. It's actually very

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00:46:31,480 --> 00:46:33,960
Speaker 1: creative and you know what, it gives a good message

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00:46:33,960 --> 00:46:37,880
Speaker 1: for financial literacy, and it gives good you know, inspirational

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00:46:37,960 --> 00:46:40,680
Speaker 1: quotes and things of that nature. So I think that that.

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00:46:40,800 --> 00:46:42,239
Speaker 2: Especially in our cultures, like that's one of the things

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00:46:42,280 --> 00:46:43,920
Speaker 2: we notice is that people will look at what you're

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00:46:43,960 --> 00:46:45,880
Speaker 2: wearing for So if they're gonna look, we might as

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00:46:45,920 --> 00:46:46,160
Speaker 2: well have.

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00:46:46,160 --> 00:46:48,759
Speaker 1: A message and say something exactly so you know, that's

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00:46:48,800 --> 00:46:51,200
Speaker 1: what we're doing. We're just pushing positivity. Thank you guys

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00:46:51,200 --> 00:46:53,040
Speaker 1: for supporting us. Thank you guys for rocking on us.

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00:46:53,120 --> 00:46:59,840
Speaker 1: Don't forget to subscribe to our YouTube channel and also

882
00:47:00,000 --> 00:47:05,480
Speaker 1: turn on our notifications. Also for Instagram as well. Also

883
00:47:05,760 --> 00:47:09,040
Speaker 1: for iTunes, subscribe. I know you guys are listening to iTunes.

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00:47:09,560 --> 00:47:11,440
Speaker 1: We're not just on iTunes. That's another thing to people.

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00:47:11,520 --> 00:47:15,840
Speaker 1: We're on Spotify, We're on Google Podcasts, We're on Podbeam,

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00:47:16,320 --> 00:47:20,800
Speaker 1: We're on Anchor, We're on I watch.

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00:47:20,640 --> 00:47:22,879
Speaker 2: You everywhere you listed all the time.

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Speaker 1: So all right, guys, we will see you next week. Peace.

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Speaker 8: An illegal alien from Guatemala charged with raping a child

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00:47:57,239 --> 00:48:01,040
Speaker 8: in Massachusetts. An MS thirteen gang member from Al Salvador

891
00:48:01,320 --> 00:48:05,440
Speaker 8: accused of murdering a Texas man of Venezuelan charged with

892
00:48:05,520 --> 00:48:09,400
Speaker 8: filming and selling child pornography in Michigan. These are just

893
00:48:09,520 --> 00:48:13,280
Speaker 8: some of the heinous migrant criminals caught because of President

894
00:48:13,280 --> 00:48:16,839
Speaker 8: Donald J. Trump's leadership. I'm Christy nom the United States

895
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Speaker 8: Secretary of Homeland Security. Under President Trump, attempted illegal border

896
00:48:21,719 --> 00:48:25,279
Speaker 8: crossings are at the lowest levels ever recorded, and over

897
00:48:25,320 --> 00:48:28,560
Speaker 8: one hundred thousand illegal aliens have been arrested. If you

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00:48:28,640 --> 00:48:32,480
Speaker 8: are here illegally, your next you will be fine nearly

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00:48:32,560 --> 00:48:36,600
Speaker 8: one thousand dollars a day, imprisoned, and deported. You will

900
00:48:36,600 --> 00:48:40,279
Speaker 8: never return. But if you register using our CBP home

901
00:48:40,320 --> 00:48:43,680
Speaker 8: app and leave now, you could be allowed to return legally.

902
00:48:44,040 --> 00:48:48,800
Speaker 8: Do what's right. Leave now. Under President Trump, America's laws,

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00:48:48,960 --> 00:48:51,400
Speaker 8: border and families will be protected.

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Speaker 2: Sponsored by the United States Department of Homeland Security,