Speaker 1: Wake that ass up in the morning.
Speaker 2: The Breakfast Club Morning.
Speaker 3: Everybody is DJ Envy, Jess Hilarious, Charlamaine the God.
Speaker 4: We are the Breakfast Club. We got a special guest.
Speaker 1: In the building, Bib Will.
Speaker 4: I am welcome brother, what's up?
Speaker 1: Thanks for having me, y'all. It's always good to be
Speaker 1: on your show. It's awesome new It's my first time
Speaker 1: in your space right here, this is dope.
Speaker 4: Yeah, we've been here about all over here.
Speaker 2: What year are you in? Mentally? Will any technology?
Speaker 5: Was?
Speaker 1: I always like to push it five to ten years out? See,
Speaker 1: you know, working today for what's happened in five to
Speaker 1: ten years, you're like in twenty thirty four. Uh not
Speaker 1: right now. Not at the moment when I go to
Speaker 1: the office. That's we're pushing and working on those types
Speaker 1: of things or what's what's what's getting ready to what
Speaker 1: the world looks like in that in those increments five
Speaker 1: to ten years and then work towards building that.
Speaker 4: But what does it look like?
Speaker 6: Yes, speakers in his clothes Jesus, Yes, you have your hoodie.
Speaker 2: Is like tech.
Speaker 1: Yeah, because I'm like, because I was always doing this
Speaker 1: like a so and then like doing this a so
Speaker 1: so I'm like, yo, so yeah, what is you.
Speaker 2: Is different? Man? What is that? What is it?
Speaker 1: It's a it's it's a you know, protect your neck.
Speaker 1: It's my neck, you know. It's just a speaker that's
Speaker 1: on the neck. They sell them, They were selling them
Speaker 1: way before COVID, and then COVID happened and then they
Speaker 1: stopped making them. So then I went to the company
Speaker 1: that was making them so we could make our own.
Speaker 1: And this is a prototype that we're going to do
Speaker 1: together that to be out this holidays.
Speaker 4: So you can take phone calls on it and yeah, wow,
Speaker 4: can you give us a camera? The show is how
Speaker 4: it works works on.
Speaker 1: A yo, Finn. So we here at the show, say
Speaker 1: what's up to everybody? And were getting into the interview
Speaker 1: and they were tripping off of the the device I
Speaker 1: have on my hoodie, which is like a speaker where
Speaker 1: I actually summoned you on. So so say what's up
Speaker 1: to everybody?
Speaker 5: I Yo, sounds like you're setting the scene with some
Speaker 5: next level tech mystery, will rocking a device on your hoodie.
Speaker 5: That's got everyone guessing. That's how you blend street cool
Speaker 5: with tech intrigue. It's like you're the DJ dropping a track.
Speaker 5: Nobody's heard yet, everyone's ears perk up. You feel me?
Speaker 5: Pitch it as the future of personal tech, a sneak
Speaker 5: peek into how we're going to stay connected, and weighs
Speaker 5: that straight out to tomorrow, imagine your hood.
Speaker 1: Hey, but you you didn't say what's up to everybody? Now,
Speaker 1: don't go into imaginary scenario. Say what's up to the
Speaker 1: people that are here at the table? You know where
Speaker 1: we're at.
Speaker 5: Ah Yo, what's up everybody right here at the table?
Speaker 5: My bad for jetting off into the future. There. Let's
Speaker 5: bring it back to the now with all of us gathered,
Speaker 5: ready to dive into the real vibes of this moment.
Speaker 1: Yeah, so we're going into that.
Speaker 6: So he knows exactly what are you got to tell
Speaker 6: you? You have to hear me at the breakfast club.
Speaker 1: Oh no, already set it up. Well, he's like a
Speaker 1: wrong person.
Speaker 7: Sometimes you ask somebody something and then just go off
Speaker 7: tumble something else.
Speaker 1: No, yeah, I set it up you know before before
Speaker 1: we got in here. I'm like, all right, that's what
Speaker 1: I'm about to do. Here's the folks that I'm gonna
Speaker 1: be rocking with, and you know it's good for my
Speaker 1: meetings that I go into prepare like because it'll gather
Speaker 1: information about what it is that I'm about to be
Speaker 1: engaged with. So I got that dude's name is Finn,
Speaker 1: and we got Fiona, I got fill Up, we got
Speaker 1: this Fierra, and I'm working on these other personas Felix
Speaker 1: and Felicia. So I build the personas, get like the personalities.
Speaker 1: Throw the personalities to our are our tool. Then fine
Speaker 1: tune the voice quality. But the voice quality is from
Speaker 1: a capture when you're working with the talent and interviewing
Speaker 1: the talent, and then after you get the capture, you're
Speaker 1: going you do all the fine tuning and how it
Speaker 1: how it behaves as far as it's flair and expressions
Speaker 1: over friends, y'all.
Speaker 3: Felicia, So let me ask you, so you so you
Speaker 3: don't see do you see bad things about AI?
Speaker 4: Or do you only see the good things about AI?
Speaker 3: Because people always say AI is taking jobs and that
Speaker 3: you know it's it's gonna be a place where you
Speaker 3: know the robots are going to be taking over.
Speaker 4: What's what's your thoughts on all of that?
Speaker 1: It's too early to let your mind go down a
Speaker 1: pestimistic negative thought when you when we as as creatives,
Speaker 1: have the opportunity to to try to make it as
Speaker 1: productive and a tool for good at this point in time.
Speaker 1: So there's all I know is the projects that I
Speaker 1: come from. AI didn't create the scenario for us to
Speaker 1: live through those conditions. That was an AI people living
Speaker 1: through what they living through in Congo. That's not AI,
Speaker 1: that's just human greed. So those folks that are living
Speaker 1: in those situations that need solutions that no one is
Speaker 1: trying to solve. Now finally there's a tool to help
Speaker 1: you solve your problems. So to to just you know,
Speaker 1: define it as this is going to mess stuff up, Well,
Speaker 1: maybe it's going to solve a lot of stuff for
Speaker 1: folks that have been waiting for solutions, but now they
Speaker 1: got the ability to solve the problems themselves. So I
Speaker 1: like to look at AI from that perspective. Who needs it?
Speaker 1: The folks that are worried about it are folks that
Speaker 1: have been sitting in the lap of comfort, and those
Speaker 1: folks were also the folks that are responsible for those
Speaker 1: folks living through pretty hard times, decision maker policymakers, and
Speaker 1: so I like to look at it from that perspective. Well,
Speaker 1: there's an opportunity to make it if you use your creativity,
Speaker 1: your imagination, your focus to identify a problem, train the
Speaker 1: AI to see what that situation is, and then push
Speaker 1: it to solve that particular problem. That is what I'm
Speaker 1: focused on right now building these types of tools, And
Speaker 1: the first thing is to create these personas so that
Speaker 1: intelligence sounds the way we sound. What does that mean?
Speaker 1: Most people be like, we're talking about what I am
Speaker 1: you saying? We don't sound intelligent. Nope, that's not what
Speaker 1: I'm saying. I'm saying if you get these ais right
Speaker 1: now and these corporations that are bringing these ais to
Speaker 1: to culture and society, they don't sound like us. We
Speaker 1: are having to change how we speak and how we
Speaker 1: behave to some tool that hasn't been trained by us,
Speaker 1: that doesn't have the same types of you know, vernaculars
Speaker 1: and the way it expresses itself. So why do we
Speaker 1: have to change the way we talk to talk to
Speaker 1: something that's intelligent? And why can't that programmed intelligence sound
Speaker 1: like us? Is what my urgency is, Like, there's gonna
Speaker 1: be a bias, so why can't we also solve that
Speaker 1: bias and making a system that rocks, Like how we.
Speaker 6: Rock, Yeah, because I was reading actually was reading this
Speaker 6: this morning's funny is AI racially biased? Study finds chatbox
Speaker 6: treat black sounding names differently. So if you say your
Speaker 6: name is Tamika and you know you're a job candidate,
Speaker 6: they'll offer you a salary of like seventy nine thousand,
Speaker 6: three hundred and seventy five. But if you switch your
Speaker 6: name to Todd, it boosts suggested salary to eighty two thousands.
Speaker 6: So it's like that's all based on who's creating the program.
Speaker 1: Right, So you have the those are called data biases
Speaker 1: algorithmic prices, and that's primarily because the folks that are
Speaker 1: training the data ain't us. The folks that are building
Speaker 1: the algorithms ain't us. So we could you could think
Speaker 1: that's malicious, and some of it is, but it's also
Speaker 1: malicious from the policy makers on who has been guided
Speaker 1: to go down that path to be data scientists and
Speaker 1: algorithmic programmers and you know, data trainers. And so that's
Speaker 1: the reason why like my focus on the philanthropic side
Speaker 1: is to go to the inner city, starting with the
Speaker 1: one that I came from, to get kids up to
Speaker 1: speed with robotics and computer science, and so my program
Speaker 1: serves about fourteen thousand students in LA. We're across almost
Speaker 1: over three hundred schools in LA with our partnership with
Speaker 1: la USD to address that very points, because we need
Speaker 1: more data scientists, more computer scientists to solve these data biases.
Speaker 3: Do you think it should be it should stop in
Speaker 3: certain places like you talk about the positive and the
Speaker 3: positive effects, but like then hip hop the other day
Speaker 3: we heard an alleged Kendrick reply and they said that
Speaker 3: was AI.
Speaker 4: We've seen these pictures that justed. We're seeing this AI.
Speaker 3: We're seeing a lot of students now that are actually
Speaker 3: not writing reports now because they could put it in
Speaker 3: their chat, GPT and AIO generate papers for them.
Speaker 2: What happens with its world leaders?
Speaker 6: World leaders saying, you know things on social media, you
Speaker 6: can't tell if it's Biden putin.
Speaker 2: You don't know what's going on.
Speaker 1: That's happened before. Some smaller version of that with photoshop,
Speaker 1: that's happened before, some smaller version of that with calculators.
Speaker 1: You know, people ain't doing their math homework. They own
Speaker 1: a calculator, and the calculators given the answers. Man saw
Speaker 1: this picture of such and such with such and such
Speaker 1: that was done on photoshop or man I just saw
Speaker 1: back in the day day day, I saw the picture
Speaker 1: of the Queen with some that was a painting. So
Speaker 1: we just have a hyper you know, volume way up
Speaker 1: to a thousand version of that. And as a society,
Speaker 1: we have to educate everyone on what the compute is
Speaker 1: capable of now and that dialogue needs to be echoed
Speaker 1: around the world to where we now have to ask
Speaker 1: what's real from what's fake. You go to supermarket back
Speaker 1: in early two thousands, you bought a orange, then people
Speaker 1: push for regulations be like, nah, now we got organic
Speaker 1: oranges because people didn't know that stuff was like genetically modified.
Speaker 1: Right when my mom was young, there were no such
Speaker 1: thing as like organic oranges. Everything was organic, and then
Speaker 1: something came into existence to where stuff started getting modified
Speaker 1: to where now you have two types of oranges in
Speaker 1: a damned supermarket. So that that education is super important,
Speaker 1: so people know what they are interfaced with. Is it real?
Speaker 1: Is it up? Is it going down? The ingredients on
Speaker 1: the back of every package is there? Same needs to
Speaker 1: be for AI.
Speaker 6: Can humans handle that with thoughts though, like if I
Speaker 6: hear you know something from a world leader, and I
Speaker 6: got to decide, is this an organic thought from our
Speaker 6: world leader or a GMO thought?
Speaker 2: Can we handle that as people.
Speaker 1: And time?
Speaker 2: Yeah? What if it's calling for a nuclear war and
Speaker 2: we don't have time.
Speaker 6: What if it's a world leader hearing another world leader
Speaker 6: thing I just hit a nuke button or something.
Speaker 1: I hope. I'm from an optimistic lens. The powers that
Speaker 1: be don't have the same access to technology that we have,
Speaker 1: so they probably have some type of vetting system that
Speaker 1: when information comes in, stuff is watermarked with some way
Speaker 1: to identify what's real from what's foe when information comes in.
Speaker 1: Because there's if we have if I could build stuff
Speaker 1: like this with you know, assembling teams and have ideas
Speaker 1: and visions and the team you know takes those ideas
Speaker 1: and visions and improves on them or like ships on them,
Speaker 1: like no, no, maybe we should do it like this
Speaker 1: and that type of banter then to then come with
Speaker 1: a product. Imagine what you know leaders of governments have
Speaker 1: Imagine with their R and D and their you know
Speaker 1: process to their processes to you know, to vet are
Speaker 1: far beyond. So that's just my optimistic perspective because the Mormon,
Speaker 1: I knowing the things that I know. If I go
Speaker 1: down that rabbit hole, I'm not getting out of bed.
Speaker 1: So I have to have an optimistic perspective. You know
Speaker 1: last year. Last year I got an invite that were like, hey,
Speaker 1: we want you to come be a part of these
Speaker 1: dialogues at the Vatican. The Vatican put together this AI Council.
Speaker 1: I'm like, what the Vatican and AI? What's that about?
Speaker 1: So I went and participated. Everyone that's working in AI
Speaker 1: was to you know, share the things that they're working on.
Speaker 1: So we have folks from Open AI, there, Microsoft, Google, Anthropic,
Speaker 1: you know, Stanford, Mit Berkeley. Yet all the folks that
Speaker 1: are either pushing AI, working on these foundation models or
Speaker 1: in systems sharing the work that they're working on, and
Speaker 1: then sharing their concerns, sharing the things that they have
Speaker 1: been researching and then vow to never release, and the worries.
Speaker 1: So when you're in those types of conversations and these
Speaker 1: types of worries, first couple of days was like unsettling,
Speaker 1: like oh man, damn. Then the second session was an
Speaker 1: optimistic session, and we had one this year as well.
Speaker 1: But I always I like to keep an optimistic lens
Speaker 1: on that's the way to use my imagination. I don't
Speaker 1: think it could ever get worse for folks that are
Speaker 1: really actually going through some real hard times.
Speaker 2: What's the dress code for these Illuminati meetings when you
Speaker 2: go to the bat.
Speaker 1: I don't know they got they got Illuminati throws like
Speaker 1: you just.
Speaker 6: Wait is this and will just not here talking. He
Speaker 6: has a new company called f Yi Ai is an
Speaker 6: AI based company.
Speaker 1: Yeah, I've been I've been in the AI space since
Speaker 1: two thousand and nine. So there is one video that
Speaker 1: we did back on the on the the intro to
Speaker 1: I'm gonna be so I come with this suitcase? Next,
Speaker 1: where's that?
Speaker 5: What is that?
Speaker 1: This right here is the future. I input my voice,
Speaker 1: high notes, my low notes, then the whole English vocabulary.
Speaker 1: What you're able to do with that because of this
Speaker 1: artificial intelligence, Like when it's time to make a new song,
Speaker 1: I just type in the lyrics and then this thing says,
Speaker 1: it says, it wraps, it talks it. So the cats, wow,
Speaker 1: the cats that built a lot of these technologies saw
Speaker 1: this fourteen years ago. And fourteen years ago the Transformer
Speaker 1: paper wasn't written. It's seven years ago for the Transformer
Speaker 1: paper for those that do know what the Transformer paper.
Speaker 1: The Transformer paper was was this research program out of
Speaker 1: Google Labs or Google Brain, one of the two, and
Speaker 1: they wrote this paper, and from that paper came this
Speaker 1: whole new way of bringing to market tu AI or
Speaker 1: what came from that was a consumer version of AI
Speaker 1: that GPT launched from that paper. So the T in
Speaker 1: GPT's stands for transformer, which is a paper written by Google.
Speaker 1: And so a lot of the things that people were
Speaker 1: excited about in the field of AI back in early
Speaker 1: two thousands wasn't plausible until that paper was written. So
Speaker 1: I've been excited about the field since two thousand and
Speaker 1: eight when I first found out about seven and eight
Speaker 1: when I first found out about it, did this video
Speaker 1: in twenty ten, invested in companies in twenty twelve, thirteen fourteen,
Speaker 1: had a watch that spoke in twenty and fourteen that
Speaker 1: we launched with three Mobile and AT and T here
Speaker 1: in America, but nobody wanted to watch. That was a
Speaker 1: phone that early in twenty thirteen. Now, so I've been like,
Speaker 1: you know, doing things. Some of the things I did
Speaker 1: didn't work. Beats worked silently, part partner there, but that
Speaker 1: was an AI but my proceeds, I went out and
Speaker 1: like invested in companies in Israel, Bangalore, developers from Palestine.
Speaker 1: I just love the field, you know, it's a pretty
Speaker 1: pretty awesome realm to solve problems around.
Speaker 6: So question when you did that video, did that technology
Speaker 6: already exist? Are they got that that was the seed
Speaker 6: for their idea?
Speaker 1: All that technology didn't exist?
Speaker 2: So that you were the seed for their idea?
Speaker 1: Mm hmmm something like that.
Speaker 7: Well, congratulations, you're about to graduate from Harvard.
Speaker 1: Yeah, this is October. What can teach you a lot
Speaker 1: of stuff? Bro business, managing teams, learning from other people's
Speaker 1: uh stumbles, you can you can learn a lot, especially
Speaker 1: where this this journey that I'm on, this mission that
Speaker 1: I'm on, I need more information to get to where
Speaker 1: I want to go next. And I needed it not
Speaker 1: only information, I needed new networking, uh relationships in different fields.
Speaker 1: Like I met folks that that build uh data centers.
Speaker 1: Never never run into people that build data centers. So
Speaker 1: one of my classmates build data centers.
Speaker 4: So you're actually in class, you're not online? You go
Speaker 4: to class.
Speaker 1: Yeah, I'm in the dorms.
Speaker 4: Really you're doing what? Look crazy? You must have all
Speaker 4: types of futuristic.
Speaker 1: Stuff, and I just got my little, my little one
Speaker 1: of those suitcase. I take five outfits and rotate those
Speaker 1: five outfits. No draws. I just buy draws every week
Speaker 1: and socks. It's that That's the life I love. I love,
Speaker 1: I love being able to go back. It will be
Speaker 1: my first time ever graduating on stage. Never graduated on
Speaker 1: stage junior, high school or high school.
Speaker 2: Yeah, we didn't need to know you didn't have no draws.
Speaker 2: I mean.
Speaker 1: It was really no point, you know, because if I
Speaker 1: said I got five outfits in the bag, somebody's imaginations
Speaker 1: like draws and draws.
Speaker 4: Like we assume we have two bass and too brush.
Speaker 1: No, no, you don't try to.
Speaker 2: Think about draws.
Speaker 1: I get them.
Speaker 7: He buys them fresh every week.
Speaker 2: Right now, every imagine not forgetting to put on your
Speaker 2: speak on your neck.
Speaker 1: Headlines, you know that, right Well, draws, no dis door.
Speaker 1: See that's that's that's how you get there. That's that's
Speaker 1: how he spreading in rumors.
Speaker 6: I posted something that you said a couple of weeks ago,
Speaker 6: and you were talking about how more they're they're investing
Speaker 6: more into robots than into humans. And then you want
Speaker 6: to paraphrase, and you wonder why people are stupid.
Speaker 1: No, now, not stupid, that's harsh on people. Just my
Speaker 1: two paths, my entrepreneurial path by philanthropic path. I've been
Speaker 1: able to raise more money for AI personally than raising
Speaker 1: money for the foundation. So my comparisons was not just
Speaker 1: like it was not just like a vague perspective or
Speaker 1: like this umbrella you know perspective. It was a personal perspective.
Speaker 1: Also looking at you know, inner city investment for education
Speaker 1: versus inner city investment for data centers, inner city investment
Speaker 1: for you know, terminals and the way phones. We all
Speaker 1: need connectivity. We also have this connectivity gap where folks
Speaker 1: don't have you know, connection in rural areas. So you
Speaker 1: have awesome AI coming no investment for education in inner cities.
Speaker 1: Some developing countries don't even have access to connectivity. Wow,
Speaker 1: folks that do have devices, they are there's these business
Speaker 1: models that that are making folks addicted to features that
Speaker 1: dumb us down right. The behavior is rewarding us for
Speaker 1: content that keeps us on this this this hamster will Wow.
Speaker 1: We're using emojis and freaking memes to communicate, and the
Speaker 1: machine is being trained to break down quantum physics and
Speaker 1: quantum entanglement. So that to me is like, Okay, where
Speaker 1: does this go? And how do we curb it? How
Speaker 1: do we get control back? Right? And I'm optimistic. I
Speaker 1: think we will come around it. But you have to
Speaker 1: identify the trip wires. You have to be like, hey,
Speaker 1: look what's happening. Here's how we can you know, be
Speaker 1: better off ten years from now. So a ten year
Speaker 1: old now when they twenty, it's gonna be eight when
Speaker 1: we identify it. If we don't identify it ten year old,
Speaker 1: that's twenty. Yo, yep, I don't know.
Speaker 2: I love this.
Speaker 6: I love this because it's like, yo, these hoods that
Speaker 6: we come from, these points, disfranchised areas, this country has
Speaker 6: shown us that they may not always they may not
Speaker 6: put the investments financially and the resources you know into
Speaker 6: these communities, but they will put them into these this
Speaker 6: technics AI. So how about we go to the tech
Speaker 6: and AI they will benefit from resources.
Speaker 2: Yeah.
Speaker 1: So there's some there's some ten year old, twelve year
Speaker 1: old and some inner city that's like they love mid journey.
Speaker 1: They haven't really got their their imagination and their brains
Speaker 1: around you know AI. Yet as far as being contributors
Speaker 1: to it and and flexing with it. But some big
Speaker 1: company in twenty thirty four is gonna come from Fifth Ward.
Speaker 1: It's gonna come from the Bronx, It's gonna come from Watts,
Speaker 1: it's gonna come from South Side Chicago. Somebody is going
Speaker 1: to crack the code and do something massive.
Speaker 4: In this space.
Speaker 2: What did you deal?
Speaker 7: My son is twelve. We need to get on that. Yes, No, seriously,
Speaker 7: he's already into like software and tech and all that
Speaker 7: type of stuff, Like he wants to go to school
Speaker 7: for engineering and building all.
Speaker 1: Types of stuff like that.
Speaker 7: So he we thought it was sports, but he's like, no,
Speaker 7: I was just playing sports because that's what y'all wanted
Speaker 7: me to do. But I'm really into computers and he
Speaker 7: loves that and he's been doing that for the last
Speaker 7: two years.
Speaker 1: So that's dope.
Speaker 2: Yeah, you have to consume my mindset, get into the
Speaker 2: creator minds.
Speaker 1: Yeah, and compete, like when our community competes, we really
Speaker 1: do it to levels like oh man, Like what like
Speaker 1: if you think about it, basketball didn't have, you know,
Speaker 1: African Americans from the jump. Baseball didn't have African Americans
Speaker 1: or Dominicans and Colombians and Cubans from the jump. We
Speaker 1: entered that sport and we not only innovated, we dominated
Speaker 1: in that sport. And business is a sport, you know,
Speaker 1: it's it's competitive, the same type of tenacity, the same
Speaker 1: type of like fall, get back up, punch, get punched,
Speaker 1: punch back. You gotta we gotta compete the same way
Speaker 1: we compete in athletics, wate, the same way we compete
Speaker 1: with entertainment. We gotta compete over here and and encourage
Speaker 1: our kids, our nieces or nephews to compete that field.
Speaker 2: And what did you deal? That's your other AI app?
Speaker 1: Right? Yeah? Udioho Udio is Udio in a way was
Speaker 1: inspired by that video. This team that used to be
Speaker 1: at at Google left Google to start Udio, and I
Speaker 1: met the folks that built this technology a year and
Speaker 1: a half ago, and now they branched off started a
Speaker 1: new company. It's a It's an app where you type
Speaker 1: in you know, prompting like the vibe you want.
Speaker 2: And bro.
Speaker 1: Amazing music. It makes music, texting music. Make not only music,
Speaker 1: it makes comedy sketches. It makes like live it's wild, bro, it's.
Speaker 3: It's dope, does scripts and all that, like not scripts like,
Speaker 3: how can I explain it?
Speaker 1: I'xplained this way me and the guys in the Black
Speaker 1: Eyed Peas. I'm like, yo, check us out. I want
Speaker 1: to show you similar to the video what happened in
Speaker 1: two thousand and freaking nine. When we did this video
Speaker 1: last month twenty twenty four March, I'm like, yo, you
Speaker 1: guys got to see this. I typed in Black Eyed
Speaker 1: Peas live in forgot what country, and I said, because
Speaker 1: we were trying to do a song and I needed
Speaker 1: to get a crowd sound. How do you get a
Speaker 1: crowd sound right now? There's a limitation that if you
Speaker 1: want a crowd to repeat after you or say what,
Speaker 1: you have to actually be in that crowd. You can't
Speaker 1: make a crowd in the studio. You can put a
Speaker 1: lot of reverb, we get a whole bunch of people
Speaker 1: to be like yeah, and it's not gonna sound like
Speaker 1: a freaking crowd, bro. So I needed to get a crowd.
Speaker 1: So I went to the studio and I typed in
Speaker 1: the chorus that to our song, and I put live
Speaker 1: in concert twenty thousand people, and then I put we
Speaker 1: seen the chorus here, crowd. I aimed to mic some
Speaker 1: version of the prompt and then the crowds exist part
Speaker 1: bro hmm, instant did it and taboo from the Black
Speaker 1: Eyed Peas. He's like, wow, well this is dope, but
Speaker 1: that really sounds like we was really there, but we
Speaker 1: wasn't there and it was a crowd. It just hit
Speaker 1: me like it was a memory, but it's not. So
Speaker 1: that's the part that's like, oh, give me cherry. So
Speaker 1: I'll show you this one thing that that we did
Speaker 1: on udio. So let me get this. I did a
Speaker 1: I did ah. I had a radio interview yesterday and
Speaker 1: it was like a radio execs. We did this little
Speaker 1: zoom on like the future radio. And so then I
Speaker 1: took notes from everybody's comments and so then I put
Speaker 1: the notes into Finn and so I was like, your Finn,
Speaker 1: I need you to summarize this in a joke as
Speaker 1: if somebody was gonna do it for stand up. So
Speaker 1: then I put it in udio and then audio spat
Speaker 1: this out.
Speaker 7: So y'all talking about radio, right, y'all talking about how
Speaker 7: something old is gonna be new.
Speaker 1: That's like asking a cowhawk can jump up and fly.
Speaker 5: A MFM is dope.
Speaker 1: Nfm's cause his name is Morning and night and we
Speaker 1: are on the motherfucking moon now night time.
Speaker 4: Oh damn tape.
Speaker 7: Like Christ say something, well you Finn Fiona, all your
Speaker 7: baggy out of here, because I'm an I'm a stand
Speaker 7: up comedian.
Speaker 1: You know you're coming from my job. No, no, no here.
Speaker 1: Here's why I could say the same thing about beats,
Speaker 1: because I'm like, damn, these these things be making crazy beats.
Speaker 1: I can hold on, let me score it.
Speaker 2: I didn't get the points line for that joke.
Speaker 7: I han't let it go long enough.
Speaker 2: I want to know what happened to the radio for
Speaker 2: obvious reasons. So let's go.
Speaker 1: I'll go back to the beats thing. So and the
Speaker 1: way I'm like, damn, this thing is doing the beats?
Speaker 1: What does that mean for me making beats? Here's what
Speaker 1: it means for me making beats? Uh? When I make
Speaker 1: a beat and I make a song and then then
Speaker 1: have to go and write the song to the beat
Speaker 1: I just made. That's that took me goddamn at least
Speaker 1: six hours to have something awesome. Go in there and
Speaker 1: make it, make sure everything sound right, get the right
Speaker 1: plug in for it. A good six hours is gone.
Speaker 1: And then when I'm you know, I go in there,
Speaker 1: I respond to the beat seven time, Towna, come around
Speaker 1: the matana, see the sound in the conda by design time.
Speaker 1: But then I'm like, okay, what am I saying? Then
Speaker 1: I gotta translate that mumble. And when I translate that mumbo,
Speaker 1: I gotta keep the vowals because the moment I change
Speaker 1: the vowals then sent them and the TV it ain't.
Speaker 1: It ain't flowing the way it was naturally. My my, my, my, my,
Speaker 1: soul's response to the track. So I keep the vowels
Speaker 1: and then find the emotion. So got it? Got it?
Speaker 1: Then I'm like, I wonder what that would sound like
Speaker 1: instead of the piano. I have a guitar. I don't
Speaker 1: play guitar. Let me call up my guitar a George.
Speaker 1: I need you to come over here and do this
Speaker 1: guitar part because I can't get guitar to sound really
Speaker 1: awesome on the keyboard. I want those errors. I want
Speaker 1: those mistakes. I'm like, oh darn it. And so now
Speaker 1: that I know there's an udio, I should be able
Speaker 1: to put in the lyrics that I did after I
Speaker 1: did that, and they're not going to take that away
Speaker 1: from me. That's like my yoga, I got to stretch.
Speaker 1: I don't care if there's an AI stretcher. I don't
Speaker 1: care if there's like, you know, some AI yoga teacher.
Speaker 1: I got a stretch for me. So that's my stretch.
Speaker 1: And then once I stretch, what am I stretching for?
Speaker 1: Am I stretching for a sprint? If I'm stretching for
Speaker 1: a marathon? What's the actual game? And so when you're
Speaker 1: studying for a game or competition, you want to see
Speaker 1: what your competitor's doing, and you want to have as
Speaker 1: many options as possible to dodge to function up. And
Speaker 1: that's when AI will come into it as a tool
Speaker 1: for you. And then I could just version out what
Speaker 1: I created. And then when I version out what I created,
Speaker 1: now I have the ability to then like really make
Speaker 1: that piece of work that came out of my imagination,
Speaker 1: to make it the best it could be. What I
Speaker 1: have a plethora of freaking options, So all it did
Speaker 1: was all it does if you look at it from
Speaker 1: an optimistic point of view. I got more options than one,
Speaker 1: but I still had a seated. Now then there's like
Speaker 1: this lazy lazy is like and you're gonna know the
Speaker 1: difference between whack and awesome if you lazy rocking, and
Speaker 1: we know that with out of tune, we know that
Speaker 1: from like you know the state of music where it's
Speaker 1: at right now. There's a lot of lazy rocking right now.
Speaker 1: There's folks that are like worried about skip rates? Is
Speaker 1: that really you know? Are you being truly creative when
Speaker 1: you're based on skip rates and now the algorithm is
Speaker 1: telling you that you got to put the song, you
Speaker 1: gotta put the chorus here in the front. Is that
Speaker 1: really what the soul of the song needs to be?
Speaker 1: The coorus gotta be slammed in the front, or is
Speaker 1: there some way to get you to that? So I
Speaker 1: don't think we're even being truly imaginative right now. We're
Speaker 1: being reactive to algorithms and tiktoks. When now the song
Speaker 1: is like reduced to fifteen seconds. Are you really truly
Speaker 1: being creative or you being pimped by an algorithm? So
Speaker 1: I'm happy that we're in this space, this this stage,
Speaker 1: the space to shake us up, to wake us up,
Speaker 1: because the moment that we continue to go down this
Speaker 1: algorithmic programming and we value algorithmic music, well, then the
Speaker 1: AI is going to make better algorithmic shit than us
Speaker 1: because it understands the algorithm. So somebody had something has
Speaker 1: to shake us out of this like program that we're
Speaker 1: in because it is a program, and the audience, hopefully
Speaker 1: being optimistic, starts to value organic oranges.
Speaker 2: Do you have some type of neuralink?
Speaker 1: Well, no, no, no, no.
Speaker 2: Would you get it?
Speaker 6: No, no, no, no, I don't believe you now, I mean,
Speaker 6: I don't believe you wouldn't get it. I feel like
Speaker 6: you would almost have to have it to comput in
Speaker 6: the future, all of us, especially if you're a creative.
Speaker 2: I could no, no, no, that's a detail you to say.
Speaker 1: Huh, whose day what you talk about? There's a lot
Speaker 1: of days that.
Speaker 2: You wouldn't get neural link though.
Speaker 1: I don't know. No, I wouldn't not even I don't
Speaker 1: know because I leave right now, not even right now.
Speaker 1: Just the concept. There's certain concepts that don't jail with
Speaker 1: me personally. Crypto didn't jail with me. They didn't get
Speaker 1: into it. NFTs didn't jail with me, didn't get into it.
Speaker 1: Neuralink that doesn't jail with me. I'm not going to
Speaker 1: get into it. Gang banging didn't jail with me, not
Speaker 1: going to get into it. It's like in a project,
Speaker 1: you could gang bang to keep up to keep compete. Nah,
Speaker 1: I don't have to do that selling drugs. Didn't jail
Speaker 1: with me, didn't get in too. About when you got
Speaker 1: nothing in the in the hood and the projects, you
Speaker 1: gotta survive, you gotta sell this not didn't get into it.
Speaker 1: So that same like that stance of like nah, I
Speaker 1: ain't get into that. It's the same way I feel
Speaker 1: about New Link. Not to say New Link is gang banging,
Speaker 1: but it's mind mind banging. I don't know what's on
Speaker 1: the other end of it, you know, it's like, uh,
Speaker 1: I don't know what's on the other end of it
Speaker 1: to be like yeah, I'm down with.
Speaker 6: That, yeah, because it could it could could take you
Speaker 6: over in some way, playing with your brain like that.
Speaker 1: I don't know enough information about I know it has
Speaker 1: everything that everything that comes to society always aims to
Speaker 1: do some solution, to bring solutions, and so I'm not
Speaker 1: knocking what it aims to do. But this thing that
Speaker 1: we have called the brain is very very powerful. I
Speaker 1: forgot how many parameters are how many parameters we have
Speaker 1: in our neuralink sorry, our neural our neural connectivity in
Speaker 1: our minds.
Speaker 2: Look it up. Hold on about.
Speaker 1: So I get that, I get that, I get that,
Speaker 1: I get that, we get this.
Speaker 4: They're gonna be like, how could you forget?
Speaker 2: Will one hundred billion neurons.
Speaker 6: Each neuron has seven thousand synapsis and roughly seven hundred
Speaker 6: T parameters.
Speaker 2: I don't know what that means.
Speaker 1: Yeah, the adult human brain runs continuously, whether awake or asleep,
Speaker 1: only about twelve watts of power. It takes the power
Speaker 1: our minds. These ais take a billion watts to train
Speaker 1: and consumes about two hundred and sixty million watts a day. So,
Speaker 1: just from that perspective, what it takes to power the
Speaker 1: human mind and how vast it is, as far as
Speaker 1: it's compute, and we only use a small percentage of it,
Speaker 1: I don't know if a business practice is on the
Speaker 1: other end to then use human minds to power ais.
Speaker 1: So for that, I don't know. And there's a lot
Speaker 1: of folks that maybe a lot of Elon folks, and
Speaker 1: you know, Elon's dope. His contributions have been amazing. I
Speaker 1: just hope it doesn't go down that path. I hope
Speaker 1: it's not like Hey, Wow, you know, how do you
Speaker 1: sustain global compute? Wow? You know the human mind only
Speaker 1: takes twelve a twelve watt twelve watts power to power it.
Speaker 1: That would be horrible if there's a farm of brains
Speaker 1: to power AI.
Speaker 6: So there's no way robots should win, is what you're saying,
Speaker 6: because you know, that's the other thing people are afraid of.
Speaker 6: They feel like, you know, they've watched all of these
Speaker 6: movies where the robots take over and that's the end
Speaker 6: of the world.
Speaker 2: There's no way the robots can win. They shouldn't.
Speaker 1: What was that there?
Speaker 6: There's no way the robots can win, Like, none of
Speaker 6: these movies that we've seen, these apocalyptic movies where robots
Speaker 6: take over could happen.
Speaker 7: Did that sound dumb to you?
Speaker 1: No? No, I don't. The optimistic part of me, which
Speaker 1: is the the the majority governing side of how I
Speaker 1: look out the world, is no, because that's not how
Speaker 1: they're programmed. They're not. They're not programmed too. But the
Speaker 1: who's to say that there's not some wacko out there
Speaker 1: that wants to program that to be like the you know,
Speaker 1: the owner of the wickedest freaking pit bulls in the hood.
Speaker 1: Who's to say, who knows, but believing in humanity. Humanity
Speaker 1: has proven that although we've made mistakes, it's not in
Speaker 1: our nature to build something that's gonna take us out.
Speaker 1: The nuclear bomb, well, the nuclear bomb, that's a moment
Speaker 1: where humans were at are worse. And I believe in
Speaker 1: humanity too much to think that we're going to be
Speaker 1: at our worst to that extreme. Again, you trip, you fall,
Speaker 1: very rarely do you trip. You fall and fall and
Speaker 1: fall and fall and fall. But it's not in our
Speaker 1: balance and we don't. That's not how we are. We fall,
Speaker 1: we scratch our knee, we break our leg, and then
Speaker 1: from there you're super cautious. And I see, I think
Speaker 1: human as an organism is more like that than it
Speaker 1: is like I fall, I bust my face and then
Speaker 1: I'm careless and I'm just gonna throw my face on
Speaker 1: the floor. I don't think that's That's not what we
Speaker 1: are as a as a society, as a community, as
Speaker 1: a species, as an organism. So just being optimistic, like
Speaker 1: I said, wearing that, or I could go down that
Speaker 1: path creatively imaginatively, and we should all just let's all
Speaker 1: just jump out the building.
Speaker 2: Now, you gotta be sounds, the blackness, be optimistic. Got
Speaker 2: to keep your head to this guy. You have to.
Speaker 1: I just heard that. I just heard the of the
Speaker 1: song the Lady. I love that song.
Speaker 4: How were you musically? Where are you at musically right now?
Speaker 1: We got a new song coming out for the Bad
Speaker 1: Boys for soundtrack, So that's really really.
Speaker 2: Cool to everybody?
Speaker 1: Yep, everybody. Well, we got a bunch of everybody's so
Speaker 1: black piece there's there's So if you say everybody and
Speaker 1: don't mention Kim Hill, well then that's not true. That's
Speaker 1: not good to Kim Hill. So when you say everybody,
Speaker 1: you don't mention Macy Gray or Stero, that's not good
Speaker 1: to our past either. We were we wreck with Mason
Speaker 1: Gray on two albums.
Speaker 2: I don't remember that.
Speaker 1: Yeah, well those are the records that didn't really sell
Speaker 1: that well. But we have a history before Fergie. So
Speaker 1: when people tell me everybody, I'm like, watch everybody can
Speaker 1: heal Everybody? And I love her. That's my big sister,
Speaker 1: the Fergie. Everybody they're talking about the fur everybody, Ye
Speaker 1: Fergie everybody. Well, then we have a current with Jay
Speaker 1: Ray what hits and with twenty year olds that you
Speaker 1: know fifteen year olds that when we did songs with Fergie,
Speaker 1: that fifteen year old how it was two mm hmm
Speaker 1: and eighteen They come in with their parents to our
Speaker 1: shows singing Elite Mo and Mama Sita eighteen twenty year olds,
Speaker 1: you know there was.
Speaker 4: Five So Fergie's not on it.
Speaker 2: The question I'm trying to it, Well, that's all we're
Speaker 2: trying to you.
Speaker 1: Forty yeah, yeah, forty five Shane. But to the twenty
Speaker 1: year olds out there that like Jay Ray.
Speaker 4: So Jay Rays on it, you got Okay, that's what's that?
Speaker 1: Yeah?
Speaker 6: But but yeah, so like like what happened after the
Speaker 6: national anthem controversy, you didn't want anything to do it anymore.
Speaker 1: You know like Bad Boys, Bad Boys, the Bad Boys
Speaker 1: three song that we did Elite Moment forre you wasn't
Speaker 1: on it, Okay, that was the national anthem.
Speaker 6: Okay, yeah, no, the you remember you saw you saw
Speaker 6: the national anthem controversy.
Speaker 1: See, I'll be I'll be looking at the world optimistic, keep.
Speaker 6: My head to the ladies.
Speaker 4: Can they downloaded all that stuff?
Speaker 1: Download f y I dot a I and if you
Speaker 1: want to see Finn and Fiona in action, check me
Speaker 1: out on Serious XM on My Serious XM radio show. Well,
Speaker 1: my very the very first co host. That's a I
Speaker 1: is Fiona on my radio show, and yeah, it's it's uh,
Speaker 1: it's it's fresh.
Speaker 6: It's a pleasure. Well, I've never not learned something from you. Literally,
Speaker 6: every time you come and have a conversation with her,
Speaker 6: I learned something. I walk away like, oh man, I
Speaker 6: need to look into that.
Speaker 1: Thanks, thank you, guys. It's always a pleasure to come here,
Speaker 1: like and congratulations on the success. It just keeps keeps growing.
Speaker 1: The subjects you talk about are like heavy subjects and uh,
Speaker 1: light subjects. Funny subjects. You guys like cover the whole entire.
Speaker 1: It's it's funny, it's fun, it's informative. It's like wow, damn,
Speaker 1: like you really push you really pushed guests. Your fearlessness
Speaker 1: is like wow, that's dope.
Speaker 2: Thank you sir, thank you.
Speaker 1: Well it's will I am.
Speaker 4: It's the Breakfast Club. Good morning, wake that ass up
Speaker 4: in the morning.
Speaker 2: The Breakfast Club