Entrepreneur Kevin Surace: Challenges & Solutions of the AI Revolution

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Episode Transcript

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The following is a paid podcast.iHeartRadio's hosting of this podcast constitutes neither an
endorsement of the products offered or theideas expressed. Servers in the cloud are
just way faster than our human brains. The big dreams cost money. You
love Stephen Singer, I hate StephenSinger. I'm Richard Dearhart and I'm Elizabeth
Gearhart. You just heard some snippetsfrom our show. We had amazing people

(00:23):
on listen for the rest of it. Want to protect your business. The
time is near. You've given itheart, Now get it in gear It's
Passage to Profit With Richard and ElizabethGearhart. I'm Richard Gerhart, founder of
Gearhart Law, a full service intellectualproperty law firm specializing in patents, trademarks,

(00:44):
and copyrights. And I'm Elizabeth Gearhart. Not an attorney, but I
work at Gearhart Law doing the marketing, and I have my own startups.
Welcome the Passage to Profit everyone,the Road to entrepreneurship where we talk with
startups small businesses and discuss the intellectualproperty that helps them flourish. We have
an amazing guest. If I'm reallylooking forward to talking with Kevin Sires,

(01:06):
a Silicon Valley innovator or serial entrepreneur, disruptive, gnote speaker, and Broadway
phil producer. Yeah, but howmany patents? Doesn't that he has a
lot. He has ninety four pattantsworldwide, which mason close to my heart.
And he's also made some startups too, so going from zero valuations to
a billion dollars. So wait tohear his story. And then we have

(01:27):
two amazing presenters. These people arereally cool. So Linda Hollander I met
at Small Business Expo in New York. If you have something that you want
sponsors for about the podcast or ashow, or a nonprofit or something,
she's the woman to talk to.And then we have Stephen Singer. Now
there is a story behind what hedoes. I'm going to let him tell
it when his time comes. Iwas amazed to see that he was going

(01:49):
to be on because I didn't knowthere was a real Stephen Singer until because
of the billboards. I hate StephenSinger absolutely, We're going to find out
why people hate stevens I'm not tellingwhat a wait for him. But before
we get to our distinguished guestsed sitefor IP in the News and this week,
we're going to be talking about Googleand a new policy that's obviously designed

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to encourage people to use AI.And if you've been listening to the show
and following, we talk about artificialintelligence frequently, and most of the disputes
around artificial intelligence are being worked outin the court system, and so they're
trying to decide, well, ifAI makes a creation, can there be
an inventor or can there be anauthor to it? And there's a lot

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of debate about who's going to ownthis content going forward. So Google has
decided that if you use one oftheir tools like Vertex or Duet, those
are two Google AI tools, thatthey will defend you in a lawsuit if
somebody sues you for copyright infringement.So the creators that feel like the AI

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has stolen their creative and used itto make something new have to go up
against Google if they want to filea lawsuit, right, And this is
setting a pretty substantial policy because onesmall player may be willing to sue another
small player, but if Google's goingto defend the AI generator, then that
makes that kind of lawsuit a lotmore expensive and is a real discouragement to

(03:20):
pursuing that kind of lawsuit. Well, there's a lot of conversation around this
topic. Like we were talking toone of the radio personalities and he was
saying, but what if somebody takesmy voice and generates my voice using AI
to promote a product that I don'tbelieve in? What am I going to
do about that? Right? There'sstill a lot of issues to be worked
out. I just think that thispolicy by Google is really interesting, and

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we have with us Kevin sarais andKevin is an Ai Gururu. He talks
on this topic frequently. Kevin,what are your thoughts about this new policy
of Google's. I think this isan important move and I think we're going
to see it by the big toolmakers, if you will. And the
reason is they are putting protections intothese tools that don't allow you to generate

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something that you shouldn't and also generatesomething without attribution for example. And you
know copyright law a lot better thanI do. But we all learn from
the books that we read. Wecould read one hundred novels and then we
go write a novel. Now wecan't write a derivative work, of course,
Well, we can go write anovel right, and that's not illegal
as long as it's ours, Butit was informed by everything we read.

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And I think that you're seeing Googlesay with our image and or text generation,
we put the right guardrails around itto not generate a derivative work and
not generate something that is exactly thesame without attribution. But otherwise you should
be protected because you couldn't possibly knoweverything we trained on right at ie Google,

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and therefore you're going to have totrust that they put the right protections
in so you can't get sued.And lastly, I think you hit the
nail on the head is it's goingto make it hard to sue individual users
of these tools because Google has alot of money in a big legal team.
Well. I think the interesting partthough, is how do you create
a tool that really draws the rightline between something that's original or versus something

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that relies too much on something thatsomebody else has already created. So how
these large language models work? AndI think that's one that we can look
at. A large language model worksby statistically placing one word after another,
it has learned a trillion phrases,give or take, and from those trillion
phrases. It knows how to buildthe English language based on the sentence structure

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of the English language. And thenyour prompt. So if we said today
is Kevin's birthday, it isn't.But if we said that, it would
probably respond happy. Then what wouldcome after happy? While we know birthday
and maybe a third word Kevin,they're the only practical responses, right.
So now if I say I wouldlike a poem about the weather where it's

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raining outside in the style of Shakespeare, well, it kind of knows the
style of Shakespeare, right, It'sread plenty of Shakespeare. It was attributed
is as Shakespeare's, so we'll goahead and write that in that style,
not exactly quoting anything from a bookwithout attribution. So there's been rules put
in place to make sure that itdoesn't exactly do that. And I think

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they've tried to put these rules inplace so that no one's going to call
it a derivative work, right,So you're not going to grab this novel
and just change the names of thepeople and it's exactly the same story.
That's great, And this is thefirst time I've really ever heard how the
AI process works. Steve, whatdo you think about all this. Well,
not only am I not an experton AI, I don't artificial intelligence.

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I don't even know if I haveany real intelligence, so it's a
big problem for me. I'm adope jeweler. I could tell you that
on our previous website, our previousplatform, and our new platform, artificial
intelligence was built in, and Iwas, at least at my level,
I was slightly disappointed, you know, as to what it could do,

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what it couldn't do, it howmuch work, and how which input it
it takes. I think it hadunbelievable potential. And I think the fact
that Google is protecting everyone is obviouslythat's a game changer. I did a
keynote speech at Google a couple monthsago about a different topic, and Google
is one of the most amazing companieson Earth. The things that they're doing.

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I don't think we even have aclue what's going to happen in the
next three months, six months,a year. I think if we talk
a year from now, will bein a whole different world with us.
This AI is just I just don'tknow. I don't have the capacity to
understand everything that it's going to do. My concern with AI, is that
it's just going to make me lazy, right, Because where I used to
write out an introduction for a show, I now just I asked chat shept

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and it writes it for me,and it does a really good job,
right. And if I don't quitelike that one, I'll ask it again,
I'll get a slightly different version.Right. So I wonder overall if
our ability to generate content ourselves isgoing to diminish over time. Well,
one of the things I think wehave to worry about too is just I
know, I think I'm not alonewith this. I don't know any phone

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numbers anymore since I have my iPhone. I used to remember fifty one hundred
phone numbers. So I think thefact that anytime something does it for you
automates it for you when you sayit makes you a little stupider. I
think it a little lazier. Ithink it's true. And that's a concern.
I mean, that's a great question. The question is is do we
really need to know all those phonenumbers if we don't have righting right,

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Well, let me give you anexample that everyone takes for granted. Now,
if that's okay, which is thefollowing back in nineteen eighty five,
Excel spreadsheet showed up. It's probablythe last time anyone did long division by
hand, except to teach our students, maybe teach our kids. And we
don't seem to rue the day thatwe couldn't do long division anymore. I

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mean, we could probably do it, but we don't do it every day.
And so Excel became a tool thatscared financial people. But pretty quickly
accountants found more work to do andthey became the robot overlords of Excel.
But they didn't add up numbers andcolumns and rows anymore. And so no
one looks back at this. OhI wish I could just add columns and

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rows. They go, we don'thave tools to do that for me,
right, I don't know. I'vehad a few moments when I've missed my
log division, but I don't misswalking to Philadelphia. I prefer to drive
right. And now we've got theselarge language models, and that's one part
of AI, one small part.But people are talking about chat, GPT
and open AI and things like that, and these large language models are finally

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a language tool. We've had mathtools for forty years, including the calculator,
before that, and now we havea language tool, and that's going
to make us much smarter about promptingand editing and probably not as strong at
writing from a blank slate. That'strue, and maybe that's okay. Most
of my chat GPT information that Iget is written in good grammar. I

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mean, it's better than what yousee on Instagram yeah, or Facebook.
Yeah. The pros is quite good, way better than ours can be,
Linda, what are your thoughts here? I actually help people write sponsor proposals
and I went to chat GPT andsaid, write me a sponsor proposal,
and it was very underwhelming because ithit some key things that needed to be

(10:09):
said, but it didn't really getinto the psychology of convincing somebody to make
the decision to give you money andunderwrite your business or your event or your
podcast or whatever. So unfortunately it'snot there yet with what I do.
But I think there are a lotof really good uses for AI, And

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as we've been talking about, itputs us in a whole different model because
instead of being in creative mode,we become in editor mode. So if
I'm going to write an article,let's say, and I do chat GPT
then I just edit it, andI think something is lost a little bit
there because I am a high creativeand I love creating things. But I

(10:50):
think it's good for a lot ofthings. And the Google Wow that I
didn't even know that. So we'llsee what happens with Google will stepping up
like that to protect people. Well, it's certainly going to drive AI even
further into our lives. I thinkif people can use it with little fear
of legal recussions, can you well, I would say the conspiracy theorist in

(11:13):
me is a little skeptical still,only because you know, I like the
point that Kevin made about Excel andall these other advances. But I think
my only issue with AI and itsuse is the use of people's likeness,
right, So when it comes tousing people's voices and things to create something
in a space where typically it wouldbe a human I'm also concerned about the
necessity for humans right to do likedaily things and like job creation and job

(11:37):
loss. So there's a lot ofthings that I feel like, great,
this is awesome, great technology,But on the other hand, I'm skeptical
because I don't want it to replacewhat potentially could be opportunities for humans to
function and have livelihood. Well,those are great questions, and I think
with Kevin here will have a chanceto get into more detail on those a

(11:58):
little bit later in the show,but I guess for now I would just
say, you know, AI ishere to stay, whether we like it
or not. It's forcing itself intoour lives and if you're not using it
and you're in the professional sphere,you're probably going to lose out. And
that's just unfortunately the bottom line there. You know it's going to win though

(12:18):
all the lawyers they find the wearingYes. Well, speaking of intellectual property,
if you have an idea or aninvention that you want to protect,
contact us at Gearhart Law. Wework with entrepreneurs worldwide to help them through
the entire process of patenting, trademarking, and copywriting. And if you'd like
to learn more, you can visitus at learn more about Patents dot com

(12:41):
or learn more about Trademarks dot comfor free consultation or downloadable content. So
that said, I think it's timenow to pick up again with Kevin Seras.
He's a Silicon Valley innovator, aserial nor CEO TV personality and edge
you tainer, which is a wordthat we use a lot around here,
right editatement. Kevin has been featuredby BusinessWeek, Time, Fortune, Forbes,

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CNN, ABC, MSNBC, FoxNews, and has keynoted hundreds of
events, from INK five thousand toten to the US Congress. I'm sure
that was quite an event. Hewas also INC Magazine's Entrepreneur of the Year,
a CNBC Top Innovator of the Decade, World Economic Forum, Tech Pioneer,

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and chair of Silicon Valleied Forum.He has a technical background with ninety
four worldwide patents and has built multiplestartups from ground zero to one billion valuation.
So that's really an amazing resume,Kevin, and we're really pleased to
have you here. So happy tobe here. Thank you for having me.
In preparation for the show, Iwent to chat GPT to generate questions

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for this interview. Excellent. Thefirst question is does AI understand dad jokes?
With the correct prompting you can askit, how would it interpret this
as a good joke, a badjoke, a fair joke, something that
people would laugh at. And it'sgoing to give an opinion on that.
Now. Even when I say theword opinion. Of course, I'm anthropomorphizing

(14:09):
the darn thing. It doesn't actuallyhave an opinion. Again, it's a
math model. These large language models, they are math models, and they
are guessing at the probability of oneword coming after the next based on your
prompt and based on what it's learned. And it's learned everything we've ever written,
virtually right, So yes, itwill opine on that. But the
best use of a large language modellike chat GPT is to give you ideas

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that you didn't otherwise have. Thiswould be the case in a legal case.
Even give me some ideas that Imight not have thought of, and
it'll give you twelve of them.You wouldn't use them verbatim. They may
be wrong, they may not becorrect, they may not apply. But
wow, I've got ideas that Ididn't have. It's like this assistant sitting
next to me. Oh. Absolutely. When I asked that question, it
came back with thirty two potential questionsto ask you. And if I had

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sat down and thought about it,I maybe would have come up with so
hey, there's a lot more contentthere now than I would have been able
to generate on my own. Exactly, Well, I did go on your
advance website. And that is theuse of AI that I don't think a
lot of people have talked to everybodyknows not everybody. Most people don't chat

(15:16):
GPT. But what you're doing withAI is kind of quality assurance. Yeah,
software quality assurance finding bugs in software. That's right. So when your
software identifies the bugs, then whathappens do they finish? Summer lay?
Baseline is for a second, andthen I'll answer the question if you don't
mind is people over the last yearthink AI is chat GPT and chat GBT

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is AI. That is one instantiationof work that has been done since the
nineteen forties and nineteen fifties and artificialintelligence. There are literally hundreds of algorithms,
all of which can be applied.Will call applied A applied to a
variety of fields, right, Andin fact, AI in most large businesses
has been highly availed for a decadeor more to analyze big data. So

(16:03):
we've been doing this for a longtime. Facial recognition on Facebook was AI?
Is AI? Right? All ofa sudden, Chat GPT has become
the soup de jure the AI ofthe day. But it's just one version
of a type of AI. It'sjust a very huge neural net built out
a trillion phrases. So to answerthat question, what we do at app

(16:23):
fans and I'm involved in a numberof companies, but app fans is fascinating
because millions of people worldwide try andtest software, and most software is behind
the firewall like your ERP system,meaning it's for your internal use. A
large bank may have ten thousand tofifteen thousand applications, almost all of them
run the bank, and maybe eightof them go to the outside world.

(16:45):
It's really fascinating. So of courseyou want to test your e commerce sites
and things, but you've got totest the stuff that runs your company.
And this is a really hard problemto solve. It's and we've been working
at it for twelve years. Introducethe first product about five years ago that
uses AI, and the idea isto generate automation scripts, call it automat
or test automation automatically with virtually nohuman involvement. So you train the AI

(17:08):
what's important in your application, whatare the outcomes, what are you looking
for, and just let it gogenerate thousands and thousands of flows trying to
look for problems, and to dateAI finds way more problems than people writing
test scripts themselves. Are people testing? Now, what's interesting about that is

(17:29):
it can write these tests about onehundred thousand times faster than humans could.
That's a big number and it soundslike a marketing number, but it's a
measurement to actually in the bottom lineis servers in the cloud are just way
faster than our human brains. Right, So we're going to get to a
point where I think in the nextfive to ten years, all software bugs
are really found by AI, andpeople can analyze which ones are the most

(17:51):
important to fix, but they're allgoing to be found by AI. It
would be ridiculous to think that we'restill sitting there writing test scripts in some
kind of code like Selenium and hopingthat it finds bugs for us. Right,
it's going to be ridiculous. Alreadythere is with Copilot, a GitHub
copilot, and also code x fromopen Ai. There are tools now that

(18:12):
are making programmers about fifty to sixtypercent more productive than they were just three
months ago. It's amazing, andthat already completes some of your code now,
even that completion of code that automaticgenerated code isn't perfect, but we're
getting to the point where we willbe able to find the bugs. Then
the next step is find the pieceof software that is causing those bugs,

(18:33):
automatically generate new code that replaces thecode that caused the bugs, and close
the gap. This is fascinating.Now a lot of you will be thinking
what do we do with the people? Well, we start focusing more on
what it is we want our softwareto do and less about making it do
it right. What do we wantit to do? And so some people

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are saying, what happens to allthe programmers? We've got these millions of
people who write code. There willstill be code to write, but you
will be now ten or twenty timesmore productive than you are today, being
able to generate far more features,far faster. And we all want features.
We want them faster, We wantour software to do more, and
we wanted to be bug free.Yeah. Every time I start to feel

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uncomfortable about AI, because a lotof what you're saying, honestly does make
me a little uncomfortable, I alsohear the positive side, and I look
at a database for a business I'mfamiliar with that has all sorts of problems
and inconsistent data, and I'm thinking, well, wow, wouldn't it be
great if you go through there andclean all that up, because it would
be just about impossible for a teamof humans to do that. You look

(19:40):
at the benefits and they're just irresistible, But then there's a price for that,
and the prices. We don't knowwhat the world's going to be like
if we make all of those changes. We can guess, but we don't
really know. We can look athistory and when the wheel came out.
If you were a person who carriedthings on their back and then there was
a wheel, you go, mylife is over. What will the world
possibly be like if everyone has twowheels and then four? It's over?

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Right? And if you were trulyif you were an accountant in nineteen eighty
five and spreadsheet came out, yousaid, I'm going to resist this horrible
thing. It's going to take myjob. There are more accountants employed today
than there were when the spreadsheet cameout, and they've all become spreadsheet experts.
Right, So all of these toolsthat we have put out over the
years have made humans more productive.Thus, the net result of all of

(20:29):
this is that GDP goes up,and yes it's a long there's a long
tail there to make that happen.But the more productive companies are and people
are and countries are, the higherthe GDP and ultimately, you know,
sort of a better living comes outof that. Right. So if you
as a lawyer could handle twice asmany clients as you have, if you
could, and we're not there withAI, but if you could, well

(20:53):
that's pretty good for your law firm. It's probably good for the client,
probably good for everybody. Everybody getsfaster service, you've got more clients.
Life is good. Well, I'mglad to hear somebody saying that more lawyering
is actually a positive thing. Butanyway, we have to take a break.
We'll be right back. Fascinating discussionhere with Temins race passage to propit

(21:14):
with ra Jael is that your heartwill be right back. I'm Richard your
Heart, founder of your Heart Law. We specialize in patents, trademarks and
copyrights. You can find out moreat learn more about trademarks dot com.
We love working with entrepreneurs and helpingtheir businesses grow. And here's our client,
Ricky, to tell it like itis. H I am Ricky Frango,
founder and CEO of Prime six.We manufacture high performing, clean and

(21:37):
sustainable fuels like charcoal and logs.We've been working with your Heart Lost since
the beginning, really and they've helpedus figure out the trademarks, the patents,
everything it has to do with productdevelopment and how to protect our inventions.
And we're extremely grateful for the wonderfulteam that has been supporting our business
since day one. Thank you,Ricky. To learn more about trademarks,

(21:57):
go to learn more about trademarks dotcom and download our free Entrepreneur's Guide to
Trademarks, or book a free consultationwith me to discuss your patent and trademark
needs. That's learn more about trademarksdot com for your free booklet about trademarks
and a free consultation. Now backto Passage to Profit once again, Richard
and Elizabeth Gearhart and our special guesttoday, Kevin Sarrace. This guy will

(22:21):
blow your mind with what he knowsand what he's done, and listening to
him is such a pleasure. Richard, I have handed the conversation, so
now I'm going to throw it toKenya. Can do you have a question
for Kevin. Oh. It wasa great conversation, and I actually came
across the article in Forbes magazine aboutjust some of like the downfalls and the
pitfalls of AI, and one ofthe things that they bring up in the

(22:41):
article is bias and discrimination. Soit says that aisystems can inadvertently perpetuate or
amplify societal biases due to bias,training data, or algorithmic design. And
then there was also an issue withethical dilemmas, right, So instilling moral
and ethical values in a systems,especially in decision making context with significant consequences,

(23:03):
presents a considerable challenge. So Ijust kind of wanted to see what
your take was on all. Great, it's a really great question. So
let me separate AI systems that you'rebuilding within your business, say HR or
whatever, from the large language models, Okay, and we'll just talk about
them really quickly separately. If I'mbuilding AI, and I'll give you a
great example, I'm building AI,a lot of people have to go through

(23:27):
all of your HR data for allof your employees and make a judgment call
on who makes it the top inthe company versus who doesn't. This is
a fascinating thing right, we allwant to study that. Who makes it
to president? Who makes it theVP? Because you might bring in three
thousand people a year, only oneevery five years makes it the vice president.
Why is that what makes them special? Now that data is highly biased.

(23:49):
You didn't mean to make it biased, but it is. And I'll
give you an example. Let's sayat the VP level, you had someone
that graduated, say from my almamater, Rochester, to do technology,
and they interview all candidates or allcandidates in this division. Well, if
a candidate comes in and happens tosay, oh, by the way,
I went to your alma mater,the chance of them getting hired is much

(24:11):
higher than someone who didn't go toalma mater, which is because you already
bond on something. You bond onRochester. It's Rochester inter technology. Did
you have this professor, et cetera, et cetera already And again, not
getting into race or creed or anythingelse. We have a bias, and
so that bias over emphasizes people thatwent to rit not because they're better students.

(24:33):
I think they are, but I'mbiased, but so do the VP.
And by the way, we alldo this without trying to introduce bias.
We introduce bias, and so thosebiases are stuck in the data,
and now you have to figure outhow they got stuck in there, why
is that And the chance of figuringout that that one VP twenty years ago
interviewed and mostly hired people from ritit'd be hard to figure all that out,

(24:56):
right. So that's one area,and you can think of fifteen others.
So that's a challenge now as largelanguage models, they've gone out and
learned from everything we've ever written that'son the web, and that has a
Bell curve of representation. Well thatbell could of itself is biased, so
you could get certain people of certaincountries. The United States would be an
example that put far more, orhave put far more onto certainly the English

(25:19):
Web than any other country for lotsof reasons. It's population and access to
the Internet earlier and GDP and thingslike that. So we are overrepresented,
over represented. And so if younaturally ask even an image generator generate an
image of a beautiful human or beautifulwoman or beautiful man or whatever it is,

(25:41):
it's going to generate right at themiddle of that curve, which is
unfortunately likely, white, likely thin, likely looks like a model because it's
right in the middle of the curve. Doesn't know any better. Now,
if you prompt it differently and saywhat I want is something over here,
it will also of course it hasthe capability to generate that. But if
you don't pre prompt it and you'renot careful, you're getting something down the

(26:03):
middle. Because that's what a modeldoes. It doesn't know any better unless
you ask it. So these biasesare built in and it's hard to get
rid of them. Now here's thebigger problem. If you want to talk,
you about the problem. The morewe use these models, for example,
generating content for our blogs and blogposts that are advertising, and the
more that people don't realize that theycan prompt these things to go to the

(26:26):
edges and do some really wonderful things. You could prompt it to generate an
image of rather than just a man. You can say an older man with
gray hair who's a little overweight,blah blah blah. I could do that,
but people don't, so they generate. What happens is they'll start generating
the same thing that'll make the middleof the bell curve. When the model
goes out to learn from the webbigger and bigger and bigger, because it's

(26:47):
now learning from its own generated content, not knowing it generated it or another
model generated it, So it couldend up over emphasizing the middle of that
bell curve and continuing to de emphasizeeyes the breadth of the human experience.
All of our models that we've gotaccess to today, including Bard and Chat,
GPT and LAMA and others, havea huge rules engine at the output,

(27:10):
and I mean millions of rules.So when you say do you love
me, it now has a rulethat says, even though I recognize how
to construct sentences that would reply tothat, because I read all these novels,
I'm not going to do that.I'm going to say I'm a model
that is incapable of love because peopletook it before those rules were in place
to say, oh, this thingis sentient. It knows how to love.

(27:33):
It doesn't know how to love.It just puts sentences together. All
it is right. It's not sentientat all, I can guarantee it.
It's just math. So lots ofrules like how to build a nuclear bomb.
I'm sorry, I'm not able todiscuss that, right, or things
that are we don't think are appropriatefor our society, so we put millions
of rules on the output of thesethings, so you don't always see the
original output. You see that filteredby a set of rules. Who controls

(27:56):
chat, GPT or the AI enginesare the large language engines? Are the
people who set the rules? Yeah, that's right, and who is doing
that now? Actually? Open AIand Google and others have hired people overseas
in all kinds of crazy countries,you know, from Turkey to like Vietnam,
and they've given them a set ofareas that they never want the AI

(28:18):
to be able to respond in,and we hire people over there because they're
a dollar an hour instead of twentyfive dollars an hour. Basically, Now,
it's a hard job because you arelooking at the requests that people are
making and every day you go,we don't want that response to ever be
there. Again, let's put aguardrail in. Go guardrails, Let's put
a guardrail in to not allow youto get that response. So people try

(28:41):
to break these rules all the timeand try to get the thing to jail
break basically, and then their jobis to put it back in jail.
So for open AI, it wasover one thousand people for a year wrote
rules. Over one thousand people fora year, and they were each writing
potentially one hundred rules a day.Think about that, buddy, we're doing
those. Ultimately somebody is controlling this. That is true. That's true.

(29:06):
Right, you're right. You knowyou could choose to use those models.
There are models that are out inthe open source world today that have no
rules. You could write your ownrules. They're just free, and they
will tell you that they love you. You know, we dealt with this.
I built the first AI virtual assistantmodels back in the nineties that ultimately
got licensed and became things like Siriaand General Motors on Star and Alexa and

(29:26):
all of those things. So thecore technology was developed in the late nineties
at a company called General Magic.And her name was Mary actually her literal
name, the person who recorded thevoice. Her name is Mary Mack,
literally Mary Mack. And so missMary Mack would record the voices, and
she recorded thousands and thousands of thousandsof words and phrases and all the things

(29:47):
to have her literally talk to youon your phone. It wasn't one day
before people said, oh Mary I'mso in love with you, will you
marry me? And we had tosay, I don't know if these guys
are stupid or whatever, but howare we going to respond to that?
So we decided to not block that. Instead, we'd respond the way the
human would, which is, oh, I'm already taken or oh I'm not
available. And she had multiple variousrandom responses that would come back, and

(30:14):
we didn't make any bones about it. We just said, we're going to
you want to play that game,we'll play along. We can absolutely create
a large language model that has noguardrails around that and will interact with you
in every way of a relationship,right forget robot right now, just on
the screen, every way of arelationship. And the reason it can do
that is this. Remember these modelswere trained on fact and fiction. If

(30:37):
they've read enough fiction novels, theyclearly can describe and can reply to loving
kinds of things. Right. So, if they're programmed right, and they've
got a large enough data set,again from novels, they could be very
convincing as a partner, and especiallyin a country where there might not be
enough women. There's a lot ofmen, there's not enough women for a

(31:00):
whole bunch of reasons. You couldimagine those guys this is the only you
know, true I hate to saytrue partner because that's not fair, but
you know what I'm saying, rebablythe only true kind of interaction they're likely
to have if the guy wants onewith a woman that's really sick, it
may be. But let me tellyou about the good use of that.
How about older people that are gettingWe're all getting older in this country,

(31:22):
and people are getting to the agewhere we're going to We're getting to a
time where in the next twenty yearswe'll have more people over eighty than we
have under twenty. And of coursethe problem with that is no one to
take care of them. So theyneed companionship. But you just can't even
as their child, you can't bethere twenty four to seven. So a
digital companion, of which there arealready several available, is amazing for these

(31:45):
older people. They feel that theyhave a relationship with this digital companion.
They're not stupid, they know it'sdigital, but at least it's a relationship.
And I'll tell you what, thatdigital companion will listen to your story,
the same one over over and overagain. We have time for one
more question before we wrap up,But where do you see the future of

(32:07):
AI going Regular AI outside of LMSis going to continue to get better at
sorting through our data, fixing ourdata, and giving us real insights into
that data, including pattern recognition ofpattern computers. Another company I work with
up of the Pacific Northwest, andwhat they're doing to look at drugs that
can treat certain kind of cancers andfinding the patterns to match what can have

(32:30):
is just unbelievable. It's unbelievable.So these are huge breakthroughs. The humans
would have never said that molecule reallyI would have tried that, and that's
going to change medicine forever, andthis is very exciting. The second thing
is when you look at large languagemodels five years from now, maybe two
years from now, it's just goingto be a tool that we all use.
Of course, we use Excel formath, we use an LM for

(32:52):
language. It's what we do.If you write blog posts all day,
of course you're going to use anLM to give you the first start of
right that blog post. You'll probablyedit it, you'll probably change it,
but you might have gone from takingtwo days to write a blog post and
edit it and think about it andsleep on it till like twenty minutes.
So we may have made you ten, twenty, forty to fifty times more

(33:13):
productive. And in the end Icall this actually borrowing this from Reid Hoffman,
so I will borrow it from him. Is amplified intelligence. AI amplified
intelligence. What would do we isamplifying your intelligence because in the end,
you're in charge, you own it, You decide what the prompts are,
and you decide what you use fromits outcome. But we're amplifying your intelligence.

(33:34):
We can make you five, ten, twenty times the number of brains
that you had, so instead ofone brain power, you could have twenty
or thirty or fifty brain power.That sounds good to me pretty Darry Devin
serrais Silicon Valley innovator entrepreneur. Thanksso much for joining us. We hope
you'll stick around. Passage profit willbe back right after this. Hi.

(33:55):
I'm Leasa Asklesi, inventist, founder, CEO and president of Inventing a to
Z. I've been inventing products forover thirty eight years, hundreds of products
later and dozens of patents. Ihelp people develop products and put them on
the market from concept to fruition.I bring them to some of the top
shopping networks in the world, QBC, hsn Evineline and retail stores. Have

(34:20):
you ever said to yourself, someoneshould invent that thing, Well, I
say, why not make it you. If you want to know how to
develop a product from concept to fruitionthe right way, contact me Lisa Askalis,
the Inventress. Go to inventing atozdot com, inventing atz dot com.
Email me Lisa at inventing adz dotcom. Treat yourself to a day

(34:42):
chock full of networking, education,music, shopping and fun. Go to
my website inventing atoz dot com.Passage to Profit continues with Richard and Elizabeth
Gearhart. Find Now for our PowerMove segment. Henry Gibson excited about Power
moved to I'm going to be talkingabout Larry Morrow, who is a serial

(35:04):
entrepreneur. He was recently on myPower Move podcast telling his story about how
he started off by founding Larry MorrowEvents as a promoter, an entertainment business
platform that's featured celebs like Floyd Mayweather, Drake, Rick Ross, Meek Mill
and then he moved into launching LarryMorrow Properties and he's the owner of the
New Orleans based restaurant Morrows and thelegendary Treehouse, So if you're ever in

(35:28):
New Orleans, you want to checkthose places out. He also talked about
his self help book All Bets OnMe, the Risk and Rewards of becoming
an entrepreneur. So you can checkout his full story on my Power Move
podcast. That sounds great. Wherecan people find your Power Move podcast?
Wherever you listen to your podcast,you can watch it on Spotify. So
I always tell people go to Spotifybecause you can actually get a visual.

(35:50):
That's great, Elizabeth. Yes,So I still have Blis Street directory.
It's a video directory of B toB businesses, but I'm taking a little
break from it right now. Ithink with the struggles I'm i, I
kind of have to wait for thetech to catch up a little bit.
And I'm also doing Passage of Profit, which I love. I learned so
much every single time we do this. We have the most amazing people on
I have a podcast with Danielle Woolleycalled The Jersey Podcats what we talk about

(36:13):
Cats, and I have started anew podcast. Well, I'm helping a
ghost with the podcast. Actually it'scalled ghost Stories of the Flip Side.
It's by a ghost named field ababbel Stable and she can communicate with her
niece who can get her on videowith audio. And when she passed over,
she found a bunch of ghosts thatwere really mad because they have ghost

(36:34):
stories told about them and they don'tget to tell their side. So she's
telling the side of the ghosts.It's for children. So feel at babbel
Stable ghost Stories the Flip Side whereshe tells the ghost story and then lets
the ghosts give a rebuttal. Wellthat sounds great. I've heard some of
these and they're really hilarious. Sowhere can we find Fiona right now?
It's on Libson and Apple. Ijust launched it today actually, and it's

(36:58):
on YouTube, ghost Stories the FlipSide and Instagram is at fiona Sapples Stamples.
So we are very excited to haveLinda Hollander here today. I met
her at Small Business Expo in NewYork. She's a sponsor concierge and I'm
going to let her tell everybody whatshe does. Welcome Linda. Great to
be here, Okay, so Iwant to talk to all the entrepreneurs out
there. A lot of people haveall these great ideas for a podcast,

(37:22):
they want to do a show,they want to do a nonprofit charity,
they want to create a business,an event, and you think of this
great idea, but then your secondthought is, uh, oh, how
am I going to get it funded? Because you know, we're all taught
to have big dreams, but thebig dreams cost money, and that's where
sponsors come in. So I helppeople get corporate sponsors to underwrite their show,

(37:45):
their event, their nonprofit, whateverproject they're doing. And I've been
doing it for over twenty years andit's very cool because sponsors give you money
you don't have to pay back.And the reason they give you that is
because, like you, they connecta company with their core consumers and that's

(38:06):
why sponsors can fund you. Whatare your secrets for entrepreneurs who are looking
for sponsorships? A couple of thingsyou want to do as an entrepreneur.
First of all, you want todo what we call the sponsor wish list,
the list of companies that you wouldlike to work with as a sponsor
to have them fund you. Now, the way you do your wish list.

(38:28):
It's all about your demographics. Wealways say your demographics are your destiny
because for you with passage to profit, your demographics. Your audience's entrepreneurs.
What do entrepreneurs buy? They buyoffice supplies, they buy shipping, they
have a bank account, et cetera. And then they also buy consumer goods

(38:50):
in their personal life. So youmake your wish list. That's the first
step. I'm going to give youthree steps. The second step is you
need to create a sponsor proposal andit has to be an industry standard sponsor
proposal. And then the third stepis the funding step. And you know,
I can't tell you exactly how muchyou'll make with sponsors. Most of

(39:10):
our clients get between ten thousand,even up to one hundred thousand from each
sponsor, and there is no limitto the number of sponsors you can have,
so it can be quite lucrative.You could do your five six seven
figure deals. You just combine afew different companies. So that's the basic
process to getting corporate sponsors. Whatare some of your success stories, Linda,

(39:35):
Well, I'll tell you how Igot started, and then maybe I'll
give you a couple of examples.I got started because and you'll love this.
I wanted to do a women's smallbusiness expo because I was in the
poverty trap. I was in anabusive relationship, and I got out of
that situation because I started my ownbusiness, and I started it with my
best friend and we knew nothing aboutbusiness. I was an art major,

(39:58):
she was a cinema major. Butwe grew it to a multimillion dollar enterprise,
and I wanted to show other womenhow to do what I had done.
So, like I said, Ihad this great idea to do a
women's small business expo, but thenI said, uh, oh, how
am I going to fund it.So my very first sponsors before I started
my very first event were Bank ofAmerica, Walmart, and IBN. So

(40:23):
before I even started, I madea profit because I had sponsors underwriting my
events. And then after that Igot Microsoft and Staples and FedEx and you
know all these really really great sponsors. I think this is important for people
to know. I had no experiencewith events and I had no following.

(40:44):
Nobody knew who I was except formy brother in law and my cat.
But a lot of people think,oh, well, when I get this.
Many people on my fan base thenI'll go after sponsors. No,
you sell them on the concept.Do you have to have all your brand
to get everything else set up first? I mean you should because sponsors don't

(41:04):
want to start the train. Theywant to jump onto a moving train.
So they want you to get yourwebsite up, you're branding, They want
you to do the basic things.You need a business account because they want
to write a check to a businessaccount, So you need to get your
basic infrastructure and your brand going,and then you could go after sponsors Tony.
Sponsorships can be a little tricky interms of, you know, measuring

(41:27):
rois. So what do you sayis a good return on investment for someone
who's doing the sponsorship and what aresome of the KPIs that you put into
place for your clients. Well,there are intangibles and tangibles in sponsorship.
So let's talk about those tangibles first. That you asked about the metrics shares
when visits, et cetera. Thoseare the tangibles. Those are the actual

(41:51):
metrics attendees at an event, etcetera. But then there are intangibles like
building goodwill marketing, and this ishow sponsorship changed after the pandemic because cose
marketing became so important. People buyfrom companies who give back to the community,
and that's really you can't really measurethings like that, but it's very,

(42:15):
very big in the world of sponsorship. So sponsors know that there are
certain things, yes, you canmeasure, and you could give them a
report on and show them metrics,but then there are certain things that you
can't like those things though, ofbrand building and cause marketing. Nivin,
do you have a question our commentfor Linda god I think this is really
fascinating because it is different than sayventure capital or seed rounds or that kind

(42:39):
of funding. And I think we'reall used to seeing sponsorships with say nonprofits.
Right, well, we need asponsorship for this program. But you're
saying you're you know, you're doingthis as a for profit. But the
return for these sponsors is views,clicks, et cetera, et cetera,
which is almost on the edge ofa social media star because that's how they

(42:59):
fund themselves. It's here's the hairdryer I'm using today. You would really
love this air dryer, right,so take us through that. How did
you make that work? I madeit work because I started before social media,
and I sold them on the concept. So I went to sponsors,
like my first sponsor was Bank ofAmerica, and I said, hey,
how would you like me to connectyou to the biggest spending block on the

(43:21):
planet, which is women. AndI did so much research on the women's
business market. Found out that womenare starting businesses at twice the rate of
men. But more importantly, Ifound out that women make or influence over
eighty five percent of the purchasing decisionsin America. So that's what you do
when you want to get sponsors.You research your demographic, what they buy,

(43:44):
where they go on the internet,what their lifestyle is. And that's
how you sell sponsors on the conceptof who you can connect them with,
because that's what they're looking for.They're looking for sales, they're looking for
brand loyalty, they're looking for leadgeneration. Can just about any business look
for sponsors. Sponsorship doesn't work foreverybody. It doesn't work for every business.

(44:06):
It probably wouldn't work for the neighborhoodgas station or the neighborhood dry cleaner.
You have to have some kind ofinfluence, You have to have some
kind of what we call extended reach. If you have that, you can
get sponsors. Some of the challengesare first of all, doing that proposal,
because the proposal is really important,because that's all sponsors see and that's

(44:29):
how they make their funding decisions.So I read a lot of proposals,
and some of them are created byopen ai and chat gpt, and some
of them are created by Canva,and sponsors are calling me saying what's happening.
When I could tell this is aCanva proposal, I could tell it's
created by chat GPT. So youwant to have the right proposal. That's

(44:50):
a big challenge for people. Andthen another big challenge is really asking for
the right amount of money because askingfor too little and I think Kevin can
really to this because he deals withbig companies big money. Asking for too
little can hurt you in the worldof sponsorship because you're telling sponsors you have
nothing of value and it's not worththeir time. That's very true. I

(45:12):
used to say, it's a loteasier sometimes to get one hundred thousand dollars
than it is a thousand, athousand. It's not even worth my time.
What are you going to introduce meto three people? There's a mindset
there, But I think you haveto work your way into it and have
the guts to go up and say, how about a hundred thousand dollars and
here's what you're going to get forthat one hundred thousand. And I don't
think you could spend your quote unquotead sponsor dollars any better than that.

(45:34):
So, Linda, how do youget to those people that Kevin's talking about,
the decision makers who actually hold thepocketbook strings. You're completely right,
Elizabeth, because your relationship it's notwith a faithless corporation, it's with a
person, it's with a human being. It's with the decision maker. And
that's a big challenge in sponsorship bindingthat decision maker. Because sponsor companies have

(45:57):
thousands of employees, there's usually oneperson that can greenlight a sponsorship deal.
A lot of people go on LinkedInand they say, oh, I'll find
a sponsor on LinkedIn. That becomesan exercise in frustration because a lot of
sponsors don't even put themselves on LinkedIn, or they block content because they don't
want to be slimed. So it'sbest to get a list of the decision

(46:21):
makers. Because I'm telling you thatis going to cut down on your time
and your frustration and really lead youto the right people who can really greenlight
that deal. Now my company hasthe list and at the end maybe you
could tell people how to contact me, but we do have a list of
the decision makers. Well, howdo people find you go to sponsorconcierge dot

(46:42):
com or the better place to gois success with Sponsors dot com. So
just go to success with Sponsors dotcom and you could contact me through that
website. So what does sort ofa typical process look like? Then?
When you're looking for sponsors, Soyou have your sponsorship proposal and you have
your list of preferred potential sponsors,how do then do you follow up and

(47:07):
connect your proposal to your preferred sponsors? You send your proposal. Most sponsors
want you to introduce yourself by emailbecause they don't want to be surprised by
a phone call because they're usually busy. So you get the person and then
you have your first conversation. Thisis really important. On your first conversation
you do not mention sponsor fees becausethey want to see if you're a fit

(47:29):
for their goals and their visions andwhat they want to accomplish. So you'll
have a couple of conversations, you'llcome up with a sponsor fee. Then
you go to contract and you havean agreement that you sign with them because
you're probably going to be working withcompanies that are bigger than you, so
you want to protect your rights inthe deal. Now, after I get

(47:50):
the agreement signed, I start toimplement. So, for instance, if
I tell a sponsor, I'm goingto put their logo on my website,
I do that. I don't waitfor the money to come in. Usually
the money will come in in theform of a physical check, and sometimes
it comes in quickly, and asyou knowing business, sometimes it takes a
while because they're setting you up asa new vendor. Now, after you've

(48:15):
got that sponsor deal in place,the decision is just starting because you have
to keep the relationship going. Youwant to send a sponsor a report at
least quarterly. You want to talkto them when there's something new. And
then there's something called renewals. Therenewal is we suggest a one year contract

(48:36):
with your sponsor, even if you'rea podcaster, and then at the end
of that year they can fund youfor the next year and the next year.
So if you keep in touch withthat sponsor and show them what you're
doing and talk to them about theprogram and be open, you know,
because if they don't like something.I had a bank sponsor and they said,
well, we don't like this thingyou're doing, and I was devastated,

(48:58):
But I said, you know whatif we change that and we have
another conversation. They said yes,and they sponsored me for five years because
we were really open and we didn'tlet what we call residue build up.
Because sometimes they don't like something andthen they just won't renew with you.
You want to get that out inthe open. So it's kind of a
rinse and repeat process. But here'sthe cool thing about sponsors. You don't

(49:19):
have to report back to the sponsorshow you spent their money. You just
have to fulfill your contract. Sowe'll take that example again of putting the
logo on the website. If yousaid you're going to do that, you've
got to do that because they're goingto check up on that. But you
can spend the money in any wayyou want. You could pay yourself,
you could hire a team, youcould put the money in your business et
cetera, because you don't have tosubmit a budget to a sponsor. I

(49:44):
just was curious from an asset perspectiveabout some of the programs that you're building
and what someone can expect. We'reusing digital and traditional because I ask a
lot of people, I say,how are you going to promote what you
do? And they say, oh, social media and the digital platforms.
Sponsors are traditional radio, television,print. It's not dead, and sponsors

(50:06):
love the traditional platforms as well asthe digital platforms. As far as the
media mix. Now people can alsoget media sponsors, and I've gotten media
sponsors to help me get the wordout, and that is really going to
amplify your assets and your effectiveness.With a sponsor, another asset a meet
and greet like I did for Verizon. We did a Verizon relaxation room at

(50:30):
a conference where people came in andthey got chair massages and there was a
monitor that had the Verizon logo andoutside a traditional table with information about Verizon.
But I thought that was a verycreative way to promote Verizon with a
relaxation room. Well, this isact as long as everybody turned off their

(50:50):
cell phones, so we have towrap up once again? How do people
get ahold of you success with sponsorsdot com? And go to success with
sponsors dot com? And I evenhave a free gift for everybody who is
watching and listening to us today becauseI'll give you the number one secret to
getting your sponsors if you go tosuccess with sponsors dot com. That's nice,
that's great. Yes, And nowlast but not lea Steven Singer with

(51:15):
I Hate Stephensinger dot com. Whatis this all about? You're a jeweler.
Why would people hate you? Tella story? Well, you're about
to find out right now. There'skind of an alter ego. We have
Steven Singer Jewelers, which was foundat nineteen eighty forty three years ago,
and we have I Hate Stephen Singer, which is the website and we use
that because it's a little stickier,it's easy people can't spell Jewelers, and

(51:38):
we've had quite a big success withI Hate Stephen Singer. The birth of
it was twenty five years ago.It actually started probably twenty one or twenty
two years ago when it actually launched. We've been running it ever since.
It's been great. So how didyou get that name? Like I said
about a quarter of a century ago, I was waiting on a customer in
our store and it was a youngcouple. This guy just spent on a

(52:00):
ten thousand dollars on an engagement ring. And there was another customer sitting right
next to a gentleman sitting by himself. The young couple. She's said,
I love Steven Singer, I lovethe store, I love my ring,
I love the whole experience. Imean, this girl's been waiting her whole
life for an engagement ring, andshe is over the move. Meanwhile,
this guy spend ten thousand dollars.I didn't do anything. All I did

(52:22):
was make the ring. And theguy that's sitting right next to it looks
with a deadpant look and turns aroundand looks like he goes, you love
Stephen Singer. I hate Steven Singer. You want to know why? And
the girl thinks, ouh, thisguy must be a complaint, must be
a nut. I don't want toget involved with. She goes, No,
that's all right, she goes,let me tell you why. Twenty
years ago, I got my wifea ring from Steven Singer, and I
had two grown children, one incollege, one just started college. And

(52:45):
we had everything paid for, everythingmapped out. We're ready for the next
stage of our life. I getthis ring from Steven Singer. My wife
thanks me that night, and nowI have another kid and it's his fault.
Wow, I think about a badattitude. That's horrible. I mean,
he said it in jest, andit's funny because the kid, the
I hates the original I Hate StephenSinger baby only found out when she was

(53:07):
like seventeen or eighteen that she wasthe I Hate Stephen Singer kid. And
the story is absolutely true. Andwhat happened was we were talking about it,
you know, a few days later, said that was really really funny,
so we should make that into acommercial, and I said, you
know what, We're going to doit. So we made it to a
commercial. We made radio spots,we made billboard, we did everything we're
going to do, and nobody wouldrun it. We went to the radio

(53:27):
station, which we'd already been on, by the way for twenty years,
and they said, this is thedumbest idea we've ever heard. We're not
going to run it. You're notgoing to do it. You're going to
go out of business. We're justnot going to participate in it, so
it took me almost two years toget them to do it. We had
this sign of a legal document whichyou'll appreciate, that was like two or
three inches stick that I was goingto hold them harmless, that I'm doing

(53:50):
this on my own accord, thatthey've informed me that it's a bad idea,
that the professional opinion was the worstdumbest thing ever, don't ever do
it. And we did that withthe billboard company, we had to do
with the radio stations, and wedid it with everybody. So what we
did in the middle of the night, we got these fake stickers that looked
like graffiti, and we graffeited ourwhole building and says I hate Stephen Singer

(54:10):
all over the building. We changedour voicemail to say I hate Stephen Singer.
We changed our website to look likesomebody had hijacked it, and it
said I hate Steven Singer all overit like graffiti and looked like it was
all like somebody destroyed it. Andwe put only one billboard on Interstate ninety
five in Philadelphia, so it lookedlike there was a really angry customer,
angry person that put it up.It worked I've seen the billboards many times

(54:35):
and I always thought it was likea jumped to fiance or something. Well,
that's what everybody's thought individually. Itwas either I was cheating with my
wife, I was a drug dealer, I had an angry girlfriend, I
broke up with somebody, you know. They everybody had all these different theories.
And as a matter of fact,the day we launched it, we
had I don't know, maybe fouror five hundred calls and people say,
listen, I don't know what youguys did, but I love you.

(54:58):
I still go there. I don'tknow what, but I'm still going to
come there. So everybody hated theidea. Everybody in my industry groups hated
everybody in my store, my family. I was on an island. Nobody
wanted to do. I said,you'll see what I see. Everybody goes
left, We're going to go right. Everybody sells love, We're going to
sell hate. I said, We'regoing to stand out, and nobody would
do it. A year later,we won a Billboard of the Year,

(55:20):
we won two Addies for advertising,and the CBS asked me to speak at
their national Sales convention in New Yorkto say what a brilliant idea. This
was so the year before I wasan idiot. The year later, I
was a genius. We've rode thatever since and it's been great. It's
been a wonderful, wonderful thing.And people every time I go. So
I've had, you know, theGovernor of Pennsylvania. I've had the Mayor
of Philadelphia at different events. I'vehad different celebrities and different people. They'll

(55:45):
see us at an event or somethingand they'll just blurt out, I hate
Steven Singer just because they think it'sfun, and it becomes very stincid.
You don't have to lube with that. It's fine with me. Listen.
I take it as a compliment everyeverywhere we go and everywhere we do it
so it makes us stand out andit's different. What it has evolved into
is that all my competition hates mebecause we have a single the love Guarantee,

(56:05):
which we guarantee the diamond, thering and the relationship. So even
if you just break up, we'lltake it back. There's nobody else in
the United States that does or not, Nobody that I'm aware of that doesn't
let me put it that way.So we go opposite with everything that we
do, and it's worked very wellfor us Kenya. You know, you're
like the shop jock of advertising,right, And a lot of people say
that because we are the oldest continuousadvertiser on Howard Stern. Yeah, we've

(56:30):
been with him since nineteen eighty sixor seven, whenever he came to Philadelphia.
When he first came to Philadelphia,he couldn't buy a sponsor. He
couldn't get like McDonald's or Coke orPepsier, nobody that would have any kind
of they stayed. He was likea pariat So not only were we one
of the first sponsors that go onthere. I said to him, listen,
I don't care what you say aboutit's just mention our name once in

(56:52):
a while. You know, youcan say whatever you want. These are
the ads that stick out and thefunny things that sometimes he sings our ad.
We do everything in marketing and advertising. One of the things is like
nobody is tired in my opinion,Wendy's wears the beef or Nike just do
it or Coke is the real thing. The advertisers get tired of it,
or the advertising agency gets tired ofit, and they want to generate new

(57:14):
copy of new business. But customersand the clients and the people out in
the public aren't tired of it,so they change it just for the sake
of change sake a matter of fact, people like the consistency. People didn't
like new coke. They liked oldcoke, the original coke. So we
keep the I Hate Steven Singer.People love it. I mean we have
Christmas learnerments to say, I wehave shirts, we have all kinds of
paraphernalien things that we give out topeople. And I have people that come

(57:36):
like from all over the somebody comein from Washington, from Baldwine, people
from la that come in just tocome in and get a picture, or
they want and I hate Steven sickand they didn't want to buy anything.
They just want to get something thatsays I hate Steven Singer on it.
So everything we do stays under theI Hate Steven Singer umbrella, and then
is underneath that, So we keepthat focus on there, and then anything
else we do is underneath that.Eye hate to like, why do other

(57:58):
jewelers hate me? Well, maybethere is the reason that type of thing.
There was something in the show notesthat I thought was hilarious that you
said about lab created diamonds. Whatwas that? Nothing says I love you
less than a lab grown diamond.It's a fake. Lab grown diamonds are
you know, they're like Frankenstein's They'remade in a machine in the laboratory.
They are not the same as natural, real earth born diamonds. They are

(58:21):
very similar, and they're the closestthing to natural earthborn diamonds, but they're
not the same. And anything thatyou can mass produce, as much as
you want to picture it as oceanfront real estate, God's not making anymore.
That's why ocean front real estate isso expensive. Diamonds, real natural
diamonds are a sign of affection,a show of commitment, part of the
marriage contract, and they're enduring,and they have intrinsic value decades, decades,

(58:44):
hundreds of years, and you cangive all kinds of examples to that.
Lab grown diamonds are like the plagueof our industry. They've gone down
ninety five percent value in the lastfive years. Are jewelers required to disclose
whether it's natural or one hundred percentfirst off? FTC the Federal Trade Commission
of the United States says, theonly thing you can call diamond is a

(59:06):
natural earthborn diamond that came from theground, from a river, better from
the money. Anything else has tohave the simulant name. The prefix in
fundament has to say simulant, manmade, lab growth or whatever. It
must disclose right up front, andit has to be in front of the
word diamond. The only thing you'reallowed to legally call a diamond is a
diamond that came from the earth.Do you also design jewelry for people?

(59:28):
In our facility? We have ourown shop, our own designer, We
do our own cad a computer ateddesign, We do our own wax making
for everything, and we make allkinds of custom jewelry. And we've done
a lot of really cool things fora lot of celebrities and sports teams and
rock stars and all kinds of thingsthat I'm very very proud of, and
different things, different logos and differentpieces of jewelry for them, and it's

(59:51):
been great. And whether you're justcoming in for a two thousand dollars engaging
and you have a custom idea youwant to do, we will create it
for you. It doesn't cost anymore to make a custom the ring and
again, as far as I know, we're the only ones in the country
that will exchange return. You say, you know what, now, I
see it not hitting the mark.I want to do something else. We'll
take it back, We'll change Whywould anybody hate that? Where we located.

(01:00:12):
Our showroom is at the other cornerof As and Walnut in Center City,
Philadelphia, about a block away fromIndependence Hall and the Liberty Bell.
We have fulfillments all over the countrywhere we ship because you know, we
ship twenty four to seven all overthe country. The thing that sets us
apart, one of the things iswe're real jewelers in terms of we touch
and feel everything ourselves. We don'thave a drop center or call center in
India. Everybody that you talk toor it works in our building or has

(01:00:37):
worked in our building. I Kstephensingerdot Com, Passage to Profit, The
Road to Entrepreneurship with Richard Wilsoneth Gearheart, Ken You Gibson. Our special guest
today Bevin Sarrace, and we willbe right back. I'm Richard Gearhart,
founder of Your Heart Law. Wespecialize in patents, trademarks and copyrights.
You can find out more at learnMore about patents dot com. We love

(01:00:57):
working with entrepreneurs and here's our clientwho tells it like it is. I'm
Peter Olison. We recently were electedas one of the best inventions of Time
Magazine for Funny twenty two. Throughthis journey, we've been relying on get
out Law to guide us in theright steps to build a right portfolio of
patent trademarks to support our lands ofour new products. It has been a

(01:01:19):
great experience working with get at Lawas they had the deep knowledge into the
market both in North America and overseas, so we make the right choices at
the right time. Thank you,Peter. To learn more about patents,
go to learn more about patents dotcom and download our free entrepreneurs Guide to
Patents, or book a free consultationwith me. That's learn more about patents
dot com. It's Passage to Profit. Now it's time for Noah's retrospective.

(01:01:45):
Noah Fleischman is our producer here atPassage to Profit, and he just has
a way of putting his best memoriesin perspective. When I was a kid,
I used to love the holidays,but my favorite times of the year
were actually two nights twice a year. Was that we would take the clock
off the wall and readjust it byhand daylight savings time and back. Wow.

(01:02:06):
I thought that was fascinating. Itwas like being at the Hall of
Science. My first question was weall have to do this? What if
somebody forgets? Next question, how'sit working out for you? I don't
think daylight savings time is a badthing, really, we just need more
options. Let's say I want totake fifteen minutes, hold onto it this
year, and then save the otherforty five and acru it into the next
year. If I do that thefollowing year and the year after that,

(01:02:29):
and maybe even add some time ontothat, well, by six seven years
later, I've added practically a yearon in my life. Think of what
that'll do for healthcare premiums unbelievable.You know, when technology, science and
all the other advancements come together tomake this thing happen properly, we're gonna
have a world that is absolutely justlike this one, only more aggravating and

(01:02:51):
complicated now more. With Richard andElizabeth Passage to Profit, what an amazing
show. I learned a lot abouta lot, lot of different things.
I learned about Steven Singer and Ilearned about artificial intelligence, and I learned
about sponsorships, all very important anduseful things. Absolutely, So now it's
time for the question. I amgoing to start with Kevin Siras and his

(01:03:15):
website is Kevinsias dot com. That'sKevin s u r Ace dot com.
Kevin, what do you wish AIcould do for you? I wish AI
would come in, cook and clean. It's very sick. I hear no
disagreement from the Banel, right,No, I we anticipated this answer.

(01:03:36):
So AI is just unbelievable the thingsthat they're doing. I don't think we
even have a clue what's going tohappen in the next three months, six
months, a year. I thinkif we talk a year from now will
be in a whole different world withus Linda Hollander bonsor Concierges dot Thop.
What do you wish a I coulddo for you? Well, as you

(01:03:57):
know, I'm a big cat lover, animal lover. I wish they would
come and clean out the litter box. That's one of the things I don't
love about having a cat, sothat would be great. Yes, I
agree, so Stephen Singer with Ihate Stephensinger dot com Diamondman, what do
you wish a I could do foryou? Well? I have two.

(01:04:18):
One. I heard Kevin articulate somethingwonderful what the AI does for older people
in terms of listening to their storiesover and over again. So if I
could just get that to follow mywife around and stop telling me the same
stories over again and do that forme with my wife, that would be
excellent because he yells at me ifI listen or I don't listen, so
that would be terrific. I knowwho's gonna hate Steven Singer tonight. I'm

(01:04:42):
gonna blame it old Kevin. I'mgonna say this genius that I was on
this podcast with that came up withit wasn't me. But I'm really really
looking forward to what it does inmedical advancements. That it can read every
medical paper all over the world andknow everything at all times, no matter
how great your doctor or your teamor your hospital is. That they can
have this wealth of knowledge and exponentiallychange medicine and medical diagnosis and things like

(01:05:04):
that. That's why I think isone of the giant PALESTRAA. I agree,
Kenya Gibson. Our media may thenwell, Stephen stole my joke.
So I was going to say,hope it helps reprogram my husband. Well,
why don't we introduce your husband tobuy wife and they can talk to
each other. I guess for me, you know, I'm in a similar
vein in terms of like just itsability to maybe create a better, more

(01:05:26):
well society overall, you know.I mean, obviously there's a lot of
advances in the wellness space that Iwould like to see around, like fitness
and nutrition and people like being ableto just live better. So if it
can create some advancements in that space, I would be happy to see that.
Richard Garvart, your part law andtrademark copyrighted term. I. You
know, there are so many opportunitiesfor AI and so many things that I'd

(01:05:49):
like to see automated. But thething that I dislike the most is brushing
way tea and so if I couldfind I guess that's more of a robot
than AI. But if there werean automatic toothbrusher out there, I would
be really happy for that. Well, that's a good one. So for
me, and what about you,I have to go with Kevin Cook.

(01:06:10):
You well, LISTI being say anew husband. I feel like I lucked
out there, No Bunny Gil replaceyou Richard. Well, that's probably true.
So anyway, that's it for uson this episode. Before we go,
I'd like to thank the Passage toProfit team, Noah Fleischman, our
producer, Alisia Morrissey, our programdirector. Our podcast can be found tomorrow

(01:06:30):
anywhere you find your podcasts. Justlook for the Passage to Profit Show and
you can find us on Instagram andthreads at Passage to Profit Show and Twitter,
or if you're even more up todate, x at Passage to Profit
and on our YouTube channel. Lisealso join us on our new Facebook group
search for Passage to Profit Show ListenerCommunity, a new community space for our

(01:06:54):
listeners and guests where you can postquestions that you would like answered on the
show and interact with a Passage toProfit team. And remember, while the
information on this program is believed tobe correct, never take a legal step
without checking with your legal professional first. Gearheart Law is here for your patent,
trademark and copyright needs. You canfind us at gearheartlaw dot com and

(01:07:15):
contact us for free consultation. Takecare, everybody, Thanks for listening,
and we'll be back next week.The proceeding was a paid podcast. iHeartRadio's
hosting of this podcast constitutes neither anendorsement of the products offered or the ideas expressed.