Ever pondered the path that leads a mind from the intricacies of organic chemistry to the zenith of cloud computing and AI innovation? Brooks Seahorn, our esteemed guest, takes us on just such a journey, revealing the serendipitous night that redirected his trajectory straight into the tech stratosphere. Our conversation illuminates the essence of passion-fueled transformation, as Brooks shares his ascent from fledgling curiosity to supercomputing prowess, all the while maintaining a flair for turning complex concepts into captivating exchanges. His story is a testament to the unexpected turns that lead to mastery and the delightful intersection of technology and pedagogy.
Strap in for a symphonic discussion where artificial intelligence meets the evocative world of music composition. Brooks and I explore the imminent future where AI serves as a digital muse, offering compositional suggestions with the subtlety of a maestro. We're not just talking about algorithms that mimic styles; we're envisioning AI that spawns streams of music tailored to any genre within the next year. The episode peeks into the secretive advancements in AI music systems and reflects on how this technology could echo the impact of legendary producer-artist collaborations, forever altering the tapestry of musical creation.
The finale of our melodious tour de tech grapples with the authenticity of music in the AI era and the challenges of emulating the human touch—something bands like Dirty Loops epitomize with their flawless technique. We probe the ability of AI to capture the nuances of humor, a domain where human delivery still reigns supreme. Brooks brings his profound insights on AI's current limitations and potential breakthroughs, setting the stage for future episodes where he'll dazzle us with live demonstrations. Join us for a harmonious blend of anecdotes and expert analysis, all wrapped up in the vibrant world of tech innovation.
About Brooks Seahorn:
https://twitter.com/BrooksSeahorn
https://www.linkedin.com/in/brooksseahorn/
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:05):
Welcome to Tech Travels hosted by the seasoned
tech enthusiast and industryexpert, steve Woodard.
With over 25 years ofexperience and a track record of
collaborating with thebrightest minds in technology,
steve is your seasoned guidethrough the ever-evolving world
of innovation.
Join us as we embark on aninsightful journey, exploring
(00:27):
the past, present and future oftech under Steve's expert
guidance.
Speaker 2 (00:32):
Welcome back, fellow travelers, to another exciting
episode of Tech Travels.
Today's expedition is trulythrilling.
We have the privilege ofcharting these digital waters
with Brooks Seahorn, a trueluminary in the field of
innovation.
Now, brooks isn't merely just atechnologist he's an alchemy of
technology, if used with witand fervor.
With his profound knowledge ofcloud computing, his unique
(00:55):
approach to education is notjust merely informative it is in
totally engaging, transformingintricate technical concepts
into riveting tales that reallydo stick with you.
Now, with a diverse odysseythat spans over 25 years,
including crucial time spent asan Air Force contractor and
distinguished qualificationsfrom AWS and Microsoft, brooks'
(01:16):
story isn't just a chronicle ofpersonal growth, but a map for
navigating the tech space.
So fasten your seatbelts,fellow tech travelers, as we
embark on the enlightening questthrough the digital terrain
with none other than BrooksSeahorn.
Brooks, welcome to the show.
Speaker 3 (01:30):
Thanks, man.
And you know, I don't know,you're old enough to remember,
remember the commercial.
I said never let them see yousweat.
Well, after that intro, I'msweating already, yikes.
Speaker 2 (01:41):
So just again, just you know, just you know kind of
tell us about your journey andhow you really kind of got into
technology and you know thewhole thing that you're working
on now around super computingand AI.
Speaker 3 (01:54):
So take us on that journey.
Well, it's a fun journeybecause it started way back in
college when I got a degree mydegree in organic chemistry,
worked for one night as achemist one night and then said
I'm done, I'm never doing thisagain.
And that's when I kind offloated back to this thing I
discovered in college calledtechnology.
I got to help out a little bitusing some pro programming and
(02:16):
stuff like that, just fell inlove with it and so it was a
pretty big bet to make in onenight to go I'm done, I'm
walking away.
But that's exactly what I did.
And then from there it was justa point of learning all this
technology, getting into thespace, getting the tough jobs,
learning how to do this stuff.
You know everybody wants totalk about.
You know, feeling that sense ofI'm just a sort of a fraud.
(02:37):
I don't know how I got the job.
I did that for a long time, man, trying to figure out how to do
this stuff.
But in that space you learn somuch about how things really get
done, past the theory, the hardwork, and just kept working
through it until finally, youknow, just one, two, one job
after another, things that morecomplicated, more difficult,
more experienced, until finallyone day you look around and go,
(02:59):
wow, I can really do this stuff.
So that's how you end up doingthings like this, when you make
rash decisions in one night at12 o'clock in Montgomery Alabama
.
So that's how I got to thespace.
And then it was just a point ofjust falling in love with it.
And I think that and you're thesame, same same as I am, for
some reason the technology wejust fall in love with it, like
(03:19):
we want to know why it's doingwhat it's doing.
It's more complicated it gets.
We want to know more, like youknow, how exactly are things
working on chip and L2 cash?
How exactly is this thingworking with memory and paging
and all that stuff?
And you just fall down to thisthing and you just become more
passionate about it and you loveit.
It's lifelong learning and Iwould say that and I know you,
(03:40):
steve, you're the same way as onthis one.
It's just we got dumb luck.
We found the thing that we loveand we love doing it, and so we
just keep doing it for somecrazy reason.
So that's how I got here.
I just love the technology.
There's no, there's no fancy.
I got my PhD in 19, no, no,nothing like that.
Just falling in love withtechnology, continuing to play
(04:00):
with it, and I would really sayI think there is a really a big,
big sort of sorority andfraternity of people out there.
We all fit into this same spot.
We just love the technology, welearn about it, we get these
you know these opportunities todive in incredible levels of
depth and just put all thatknowledge together.
Speaker 2 (04:20):
You know it's incredible because when, in full
transparency, Brooks and I knoweach other from working at
Amazon Web Services, yourpassion for technology when I
first came to AWS, when theypaired us together and we went
and did road shows right, it wasby far probably one of the most
incredible experiences I had ofhow you take your specific
(04:40):
approach to technology andmaking it engaging, interactive
and just truly just again, I usethe word captivating, but
seeing you work a room withother people, your love for the
technology.
It also leads into your love foreducation and how you want to
kind of inspire and learn andhave other people follow into
(05:00):
this whole learning trajectory.
Right, tell me a little bitabout this ability to captivate
people when you're up theretalking to people training
education, tell me, like, whatis it that gives you this
amazing superpower?
Speaker 3 (05:17):
You mean the ability to violate OSHA at a whim and
get up on a desk and startranting about stuff.
Yeah, I'll be happy to talkabout that.
No, I mean honestly, I've saidit before and this is one of the
things and I would encourageanyone out there listening to
this podcast if you're intotechnology and you love running
your mouth, marry those twothings together because it's so
(05:40):
much fun.
And here's the other side aboutit.
There's no reason whytechnology should be boring.
It shouldn't be boring, itshould be fun, it should be
engaging.
And we as speakers in the space, technologists in the space
talking about these things, Ithink we kind of have a
responsibility to make it alittle more than just high, you
know.
You know I thought about Steve.
(06:01):
I thought specifically aboutwhat was the SNL thing.
Um, the delicious dish, likethe whole podcast, should just
be delicious dish.
You know that kind of thing andpeople do this.
But it's come, there's noreason to do it.
It's exciting, it's fun.
So pour your passion into itand what you'll find is is that,
in fact, you'll enjoy it a lotmore when you do speak about it.
And then for me personally, it's, you know, because I've got the
(06:23):
decades of experience.
I've seen what technology hasgone from and to.
Some of it bad, I will admit,some of it fantastic, though.
And so when you see thesechanges continuing to go forward
and you sort of embrace themand go with them.
It it just wells up inside ofyou as a happiness and a joy
that you want to share witheveryone.
And then I would say and thisis something, steve, you saw
(06:46):
this on display several times,I'm sure, with me Um, it's just
this.
I feel like this responsibilitythat when I'm explaining
something to somebody, I'vereally got to put a lot of heart
behind it to engage them, tomake them want to be part of the
conversation, to want to learnmore, because if you don't, it's
just boring and nobody cares.
Put a little bit of heart intoit and again it's going to be a
(07:07):
downhill effect.
You're going to enjoy speakingabout it more, they're going to
be enjoying learning about itmore, and it just goes round and
round and round and uh, andthat's everything from let's see
what uh, climbing up on desks,uh, kicking over a chair I
nearly broke my foot because Ihad a person in the audience go.
Ec2s are ephemeral and I likefreaked out at that simple
mention of stuff like that,doing different voices, all
(07:30):
those sorts of things.
But it's always and this is theone thing I let me.
Let me just end this question onthat.
Everybody, if you want to do it, go do it.
It's fantastic.
Make sure you got your techchops together, because nothing
is worse than doing somethingsilly and then being technically
wrong at the same time.
Speaker 2 (07:45):
That's a hard spot to be in.
So, with that said, let's talklike a little.
You mentioned heart, right, andI think that you know I think
AI needs a little bit of someheart right now.
So let's put a little bit oflove into some AI right now.
So again, more and more uhtools, more and more of this
shift towards AI adoption.
You know everyone wants tothink about AI as a tool, not as
(08:06):
a replacement.
You know, share some thoughtson kind of your perspective on
how this is now going to impactuh decision making, creativity
and, most importantly, kind ofhow you start to see this across
different industry sectors andhow it probably are going to
impact jobs.
Speaker 3 (08:20):
You know, let me, let me answer.
Let me actually start withstart with the end, because I
think the end's a very importantpoint, because I've heard a lot
of people say how it's going toimpact jobs.
Am I going to lose my job, etc.
Etc.
I would say, in the short term,you're there's no threat to you
, in most cases, losing your jobto AI.
What you're going to do, though, is possibly lose it to
somebody who knows how to use AI, and that's the problem for
(08:42):
anyone who's not using it.
Um, there's been so many caseswhen you can just switch over to
something like a chat, jim andI whatever system you want to
talk about quickly get an answerto a question, or get a more
sort of lucid way of explainingsomething like hey, chat, can
you make this sound a littlemore reasonable, and then it can
create something for you.
I think it's a great tool inthat space, but that goes back
(09:06):
to the very beginning of whatyou said, the heart of it.
What did you tell the system togenerate for you, and did you
put something truly unique inthere?
Or did you just say hey, I needa great article for LinkedIn
telling me about AI and how itcan help me find a job.
Copy paste, no, no, you didnothing.
You did nothing.
Stop doing that.
(09:26):
Here's a better idea.
Start with that and then startsort of adding your own style to
it, your own words, puttingthings that aren't expected in
there, because that's the thingthat AI really can't do yet.
It really can't.
Don't get me wrong.
It can be kind of creative andit can kind of push you in some
unique directions, and I likethat about it.
(09:47):
But that's how you should useit as a tool, not as a
foundation upon which you arebuilding things.
I think that's where I don'tthink we're there yet.
So, sort of, in short, talkingabout the whole thing use it as
a tool.
Use it as a tool in your job.
My goodness, I, steve, my wifeand I have been talking about
getting a brand new mattress.
(10:07):
Yes, I used AI to help me startmaking this decision.
I know it sounds stupid, butyou can say to it hey, what
would you recommend based on theinformation that you have?
It might give you a directionthat you never thought of or a
brand you didn't think of.
So that's why I say to peopleright now AI it's a tool, use it
as a tool, but then you need tobecome part of that loop.
(10:29):
When you get the answer it'snot a copy paste, it's a copy
out to something else.
Touch it up, put your own style,your own unusual, you know sort
of personality into it, thenmaybe that's what you needed to.
So, right now, use it as a tool.
Use it as a replacement, not asa replacement, use it as a tool
.
I mean like.
One of the things I've beenreally interested in is
(10:50):
particularly the music AI space,since I'm a musician, feeding
in some music to it and saying,hey, give me something unusual,
you know, at this particularpoint in the song and then let
it put something in weird andthen nine times out of 10 is
garbage, get rid of it.
Every once in a while it'll dosomething and I'll be like
that's interesting, I didn'tthink of that and it's not my
(11:12):
style.
It sounds great, but it's notmy style.
But I'll go ahead and embraceit anyway.
That's where the power of thetwo it comes in as a tool, not
as a foundation.
Speaker 2 (11:22):
Use it as a tool?
You mentioned you mentionedthis, and this is something I
haven't explored yet, so I hopethat we can double click on this
is, you know, the ability tohave it work as somewhat of a
somewhat as a kind of a co-pilotwhen you're basically using
something like music?
And I've not had a chance totouch on this.
I've talked about technology,but the music aspect, I'm very
interested to hear more about it.
(11:43):
So, as a musician, what are you, what are you kind of putting
into AI?
Well, what are you expectingfrom it?
And then, what are you gettingback when you say interesting?
Speaker 3 (11:52):
Well, there's two systems I'm working with I can't
name either.
I'm sorry, I'm under NDA rightnow, so, sorry, can't name them,
but they I will say this theywill be releasing in the third
quarter of this year.
They will be releasing, I havebeen told, and here's what you
can do with them.
And this is this is the coolpart, steve you can feed in MP3.
You can feed in actual music,notation music, to the system.
(12:14):
Let it look at it and then youstart prompting it from an AI
tool point of view, saying lookwhat would you say?
You know like, suggest adifferent.
You know like a different, likewhen we get to this fourth
measure right here, I want to dosomething unusual with the
baseline and it'll like come upwith something scale wise.
It makes sense.
In fact, I've even seen a casewhere one of the systems even
(12:38):
made suggestion of a note thatwasn't on scale, which I don't
know if anybody's ever out therehas ever heard.
But it's kind of like youlisten to somebody sing, then
it's like you kind of hear thathalf step down.
It suggested the half step downand I was like that is so smart
, because the best musicianspull crap like that.
They will take that one note.
(12:59):
That doesn't quite make sense.
Then they'll pull it back up.
It's called a pressure release,and so these things are being
built into these systems.
The thing about it, though, Ithink, steve, is this it comes
back to still being a tool.
You've got to write a song thatkind of has got a nice hook,
it's got a nice feel to it, it'sgot a nice beat.
Whatever the case is, let AIlook at it and say, hey, I got
(13:21):
an idea.
You might want to try this, andagain, nine times out of ten
you're like garbage, and so youjust get rid of it.
But every once in a while, itmay make a suggestion that you
really like, and suddenly youwant to add that to the bass
line, to the guitar, to thedrums, whatever the case may be,
and so I think in that space,it's going to come along quite a
bit.
Now I will say this neither oneof these are Amazon products,
because I've had people who'veasked me.
(13:41):
We've tried to figure out is itthe Amazon thing?
It's like nope, no, it's notthat keyboard thing.
Speaker 1 (13:45):
It is not Deep composer.
Speaker 3 (13:47):
Yes, it's not deep composer.
It is not deep composer, it'sliterally this one company.
What they do is they've justbeen feeding music into it,
feeding music into it andfeeding music into it, letting
the model build itself, runningreally large AI jobs on it so we
can start to learn about style.
And that's the other part aboutit too.
Is that I think is reallyfascinating is watching AI learn
(14:08):
about style, understandingblues, delta blues, southwestern
blues, even what we call it.
We call it Portlandia blues.
You know, it's kind of likethat 90s sort of grunge, but
there's a bit of a bluesiness toit, like somebody found a Coke
bottle and started sliding it upand down the guitar, that sort
of thing.
It's learning about thesethings, so you can be very
(14:29):
specific in it, and I think andI'm going to make a prediction
on your show okay, I'm going togo ahead and make a prediction
At least, no more than a yearfrom now, we should be able to.
Can you hear the backgroundnoise?
Speaker 2 (14:41):
Oh yeah.
Speaker 3 (14:42):
Okay, sorry about that.
That's my dog, sam.
He's very excited about AImusic, so you heard me talking
about it.
There will be.
There will come a point, Ithink, honestly, where we can
get, I guess, what I would call,more than anything else,
streams of style when it comesto music.
Speaker 2 (14:59):
That's incredible.
I mean, I want to know moreabout the.
I think if you were to startfeeding in tons and tons and
tons of music across differentgenres, there is definitely no
lack of music that I couldprobably absorb, right, Just
like a natural language model isgoing out basically providing
an index of all the text writtenand it's looking and evaluating
(15:21):
different forms of language andpatterns.
But music is interestingbecause you almost think of it
like it's your sound engineer,it's your producer, Like the
people who would kind of be kindof in that space, right, when
they would hear an artist andthey would say, well, why don't
you try to tweak it like this ormake it sound like this?
And then the artist would say,okay, that sounds great, Okay,
(15:43):
now play it again, right, quickhere, and then play it again
with this.
And the next thing, you knowyou've got, you know like again,
you hear all the stories aroundhow certain artists like Van
Halen or Pink Floyd or you nameany, one of your greats.
Deff Leppard how they were ableto change the style.
You know, rick Rubin with RedHot Chili Peppers was a great
example of well, what do you gotover there?
(16:05):
Well, I've got this notebook,I've got some poems written down
.
Well, why don't you put acouple of those into a lyric and
then see if you can actuallyput a baseline to that?
And the next thing you know,you've got a couple of hits and
they were like well, we didn'teven know about it.
So it sounds like AI is almostkind of becoming that companion
where it's starting to kind ofat least start to work as a way
to help you kind of work on somesort of production, give you
(16:26):
some input, suggestions for newstyles, and give you something
to also, as a creator, to thinkabout.
Creating.
Speaker 3 (16:34):
It's the idea of that sound engineer in a box is what
it comes down to.
Can we, instead of paying, fora studio because, like right now
, studio time runs about.
I think for a 12-hour sessionright now you're gonna pay about
$1,000.
So you know with an engineerstudio I don't know if that even
includes mixing anymore, soabout $1,000,.
Could you put that into a box?
Could you sit there andactually record it, push it to
(16:56):
the box, the box put everythingtogether for you, just like an
engineer would.
Now I think once again we're inthat space we started about in
the beginning of AI as a tool.
It could be a great toolinitially for a sound engineer.
Is it gonna replace a soundengineer?
And not yet.
There's no way to put Rick Rubinin a box.
It isn't gonna happen.
There's no way to put, you know, verdeen, white of Earth, wind
(17:17):
and Fire in a box.
It just isn't gonna happen.
Or, like I think about, youknow, like Jack Strafford of
Wolfpeck, anybody like that, thefolks from Dirty Loops, good
gravy, it's not gonna happen.
But I think what you said isexactly right.
It's that idea of having acopilot sitting next to you that
you can kind of go over and say, hey, what'd you think about
that?
And I think that's fun, becauseto me that becomes the heart of
(17:39):
an AI system where you kind ofgo hey, chewy, what do you want
to listen to?
You're oh, and he sits, he putsit over on Western.
You know it's like well, Ididn't think of that, but great
idea.
Thanks, buddy, as you fly alongthrough space.
Speaker 2 (17:50):
Yeah, it's incredible , I think, about all the
different artists that kind ofcross genres.
Right, they're mixing.
I think a friend of mineintroduced me to something that
was almost kind of like aWestern crossover with rap and
it was almost like so I thoughtit was very interesting and I
think probably that there willbe new genres right Of music
that tend to probably will comeout and will evolve from some
(18:12):
sort of kind of like AI kind ofAI music entity there.
It can, it can kind of help youbuild upon that.
Speaker 3 (18:18):
I mean, I think you could be a one man band at that
point right, Absolutely, I mean,if you can play all the
instruments fairly well and youknow what you're doing, yeah,
you can absolutely do that.
I mean, and the thing is isthat I think in that space and
this is where I get excitedabout it it would allow that
person to be.
And what I mean by that is thisyou've got somebody out there
(18:38):
who's an incredible musician.
They can do incredible work.
However, they don't have themoney, they don't have the
friends, they don't have theother friends who give a care.
They're this one person on anisland.
As I used to say to people, itwas me in technology back in the
early 90s here in CentralAlabama.
I was on an island, y'all.
I really it felt like I was onisland, just reaching out.
Is there anybody out theredoing technology?
(18:58):
So for that person to have theAI system come alongside and say
you know?
Or for them to say, hey, I'vewritten this really neat guitar
bit, what do you think?
And it goes hey, I can add abaseline to that, or I can give
you a backing drum track that Ithink would work with that.
And then you say to it let'smake it a little more bluesier,
a little more up here, let'smake it dance, whatever the case
(19:20):
is, and then put all that stufftogether.
That's where I think AI isgoing to get really, really fun.
Speaker 2 (19:26):
Interesting.
I mentioned the idea to aprevious guest around digital
authenticity and, as a creator,as you're basically creating, is
that you're creating somethingthat's very unique and specific
to your own creative talents.
How do you think about AI inthis space around digital
(19:46):
authenticity being able to say,no, I actually I was able to
create this.
I'm able to then some sort ofcreate some sort of
cryptographic key or an NFT.
What's your ideas arounddigital authenticity in this
space with regards to creators,musicians?
Speaker 3 (20:01):
I think it's going to be incredibly difficult to
figure this one out.
Let me explain why.
I am what they call a muddyplayer.
Okay, like when I play bass,when I play acoustic, I'm very
muddy.
I don't.
I don't have clean technique, Iprefer muddy technique.
It's more, it's very much moreof a Delta bluesy.
You can really hear the stringschiming on the frets and stuff
like that.
I like that.
(20:22):
For me, that makes it easier inthe space because, with AI,
accidentally put garbage in itcould, I guess you could kind of
trick it into it.
If you think about bands likedisclosure, if you listen to
very carefully to songs likeLatch, you can hear pop and hiss
in the background beinginjected by the engineer to give
it a record sound, so you caninject noise and stuff like that
(20:43):
, but you can tell when it'sbeen injected and when
somebody's just classicallydoing it.
The problem I have, though,steve, is when you move into
bands like and there's afantastic band out there called
Dirty Loops.
Most people have never heard ofthem.
They are probably one of thebest bands in the world right
now Technically the best bassplayer, singer, drummer in the
(21:03):
world.
They play almost perfectly.
Their drummer, I think has anatomic clock in his head.
He's so perfectly.
Now, how do you inject artifactsinto that?
Well, they would never injectartifacts.
They're super clean players,which means I think AI would
have an easier time doing that,because it wouldn't have to come
up with the unusual.
It could get that sort of thing.
So when you want to inject thatauthenticity, the only way I see
(21:28):
it happening is going to haveto be in the form of some sort
of metadata, which, again,because it's ones and zeros on a
wire, I can fake that too.
I can add that in and go no,look, there's that digital
signature.
This was truly.
You know, steven the Woodards,I'm going to be your bass player
and Steven the Woodards, sowe've recorded a song, we've put
(21:49):
our key in there, and then,finally, I mean, there are
authenticity mechanisms outthere that are possible to use.
They're actually quite old,simply doing things like MP5
hash sums saying, look, this wastruly me playing this.
You can't recreate it, I can'trecreate it.
It's a unique piece in and ofitself, but as far as being able
to say because I've had thisproblem myself, I played music
(22:11):
before played it back andsomebody said that's you and I'm
like yeah, that's me Like no,I'm like yeah, and so then you
get into that whole space.
You can't prove it unless youpull down the instruments and
start playing it.
So, hey, maybe this is theresurgence of a stadium concerts
.
I think it could be.
Speaker 2 (22:28):
Yeah Well, I mean absolutely, I think.
I think I'm all for it, right,is that you've got?
You've got the resurgence ofconcerts coming back again?
You know it's interesting totalk about music.
I'd love to kind of like to usethe term.
Let me riff on this for asecond right.
Go ahead Laughter, humor andcomedy, you know, are you know
(22:50):
okay?
So I've been finding that it'sbeen very AI has been pretty
mediocre when it comes to kindof these spaces here.
Oh yeah, I don't thinkcomedians, and especially with
comedians and things like that,being able to feel like they're
ever going to get out ofoutspite AI, like AI is going to
tell me a joke better than yeah, I just don't think you know
(23:11):
the thing is with comedy.
Speaker 3 (23:12):
it doesn't make sense .
There was a, there was a greatbit, and I think I forget where.
it was Jerry Seinfeld who saidit but, he was going to go teach
a class on comedy and basicallystarted out saying you're not
funny.
If you're in this class tolearn how to be, you're not
funny.
Like I can't explain to you howfunny works.
I remember this comedian namedKlaus Meyers he was.
(23:36):
He was on King of Queens and afew other shows.
He's a German comedian and hestarted his bit with this joke
about and he had this reallythick German accent and he would
say something like you know oneof the greatest problems in my
career.
And keep in mind, you'rehearing this and just you know
this is German sort of.
You know I can't do a Germanaccent, but he's saying it with
this German accent.
And he says people havewondered can somebody who's from
(23:57):
Germany be funny?
And then he kind of paused andhe goes well, let me assure you,
and the place would just comeapart, laughing at this
absolutely insidious voicesaying this how is that funny?
How can I teach AI that that'sfunny?
I don't think you can.
At least I don't know yet ifyou can and I don't know if AI
(24:19):
in the modeling can figure itout.
So I think in that space that'sgoing to be a tough one.
I think we can have a lot ofreally bad AI comedians coming
out who just don't know whatthey're doing and they're going
to bomb and they're going to getbooed off stage because the
quiescence of a lot of thingsthat we do as human beings that
I don't think AI has got yet,springs from the strange place
(24:43):
where things just don't makesense.
Like like, one of the thingsI've always told people is, when
it comes to listening to onlinemusic, they want to make
suggestions turn it off, turn itoff or they will take you down
an avenue where you will neverhear a different song.
You will never hear things likelike there is a there's a.
(25:03):
I can't remember the name of theman.
It was called.
Gunpowder chant was the name ofthe song.
Everybody look it up.
Gunpowder chant starts off witha didgeridoo that goes into an
acoustic guitar, that goes intosome sort of strange music that
doesn't make sense.
I never would have found itlistening to regular AI
generated suggestions.
So I think at the core, we'renot there yet and I don't know
(25:24):
if we have the technology to doit yet where AI can truly do the
unexpected and strange andstart to understand.
And the thing is is it maynever happen.
It may be impossible for AI tofigure out or act like a human
good on us.
That means we just have anotherfun partner in the world that
we can all work with, and that'show I prefer to think of it.
(25:44):
Not as it's not going to beTerminator Y'all that's.
It's smarter than that.
It would never come to thefront door and ask for Sarah
Connor.
Okay, it's just going to make astupid suggestion.
You're going to go, okay and goright along with it.
So in that space, I don't thinkwe're going to get there,
because that quiescence of whatit makes to be a human being,
that strange creative thing, is.
It's not there.
Speaker 2 (26:05):
It's just not there.
So there's no, there's no,there's no Skynet moment yet.
Speaker 3 (26:09):
No, there's no Skynet .
Skynet's never going to befunny.
You know the wamper going allthe way back to war games,
Wamper will never be funny.
Wamper will never make greatmusic, Everybody don't worry
about it.
Speaker 2 (26:20):
That's funny.
You mentioned war games.
It's a good movie with MatthewBroderick right.
Speaker 3 (26:24):
Oh yeah, the wamper.
Speaker 2 (26:25):
Yeah, because he was basically a kid.
He was a kid who wasessentially just tapping into
some sort of DARPA project wherethey were simulating some sort
of war game stuff, right yeahexactly.
Speaker 3 (26:37):
And now that I've been in that space I find it
even funnier, because now I'mlike how did the kid get a dial
up into the zipper?
I mean, you can't do that.
What is this nonsense?
But yeah, that was the wholething.
And for everybody who doesn'tknow what we're talking about,
this is back in the cool daywhere you take literally the old
phone that you would hold upyour head, you put it in the
suction cups so it'd get thegood connection, and then you
(26:59):
had this really awful connectionover to this thing they called
wamper, which was their superintelligence at that time, which
was whatever.
But I think that that, to me, isinteresting because if you go
back and you now look at that,that system had what we think we
have now, that idea of thisthinking thing that can think
things through and go.
You know, there's no point tonuclear war.
(27:22):
There are no winners.
Would you like to play a nicegame of chess?
I think it's how the movieactually ends.
If I remember correctly, it runsthrough every simulation and
then, through its own creativity, goes you can't win this.
I can't figure this out.
I'm walking away, let's go playa game.
So, going all the way back toyour joke thing, that thing that
we keep thinking these machinesare gonna have.
(27:43):
I don't think we're there yetand, to be honest with you, I
think it's gonna take atechnology shift Away from what
we're currently using now.
What that is, I don't know.
It could be moving away fromdigital to analog type chips, so
you get that differentiation.
In fact, there's a greatstartup in Austin, texas,
working on that exact thing,using Analog chips for machine
(28:05):
learning to get that sort ofthat unusual sort of responses
versus digital, which is very,of course, 1-0.
Speaker 2 (28:12):
And no, maybe that's where we start getting funny AI
bots mixing it with old analogchips or sort of mix of old
school and new school technology.
Speaker 3 (28:22):
Yeah, let me hook up my old Fender amp and run it
into my computer via USB forsome little bit of machine
learning.
Speaker 2 (28:29):
Well, I mean, maybe we can, maybe you can also plug
in my old Commodore 64 boyMm-hmm, and then maybe I got a
bit 20 see, and we can, yeah.
So you got a Fender amp, yougot a Commodore 64 and
microphone and a bass guitar.
Speaker 3 (28:43):
And then suddenly from that you actually get
Skynet.
But Skynet at that pointbecomes that thing because of
the unusualness of what youInjected into the system,
because now it's not one andzero, it's kind of and maybe
that's where quantum can help usyou start to get that unusual,
you start to get the personality, you start to get the
unusualness actual comedy, realmusic, a real sort of partner in
(29:06):
work.
Now that's when we could loseour jobs, but I don't know what
we're gonna do if we lose ourjobs.
So I can't go beyond that.
Beyond that's a wall.
I'm sorry, at that point I amnow Paula tradies in the desert
and I can't see beyond the Nexus.
Wow.
Speaker 2 (29:21):
That is incredible.
Speaker 3 (29:22):
Just dropped a dune reference right in the middle of
punch.
Speaker 2 (29:24):
Well, the second movie is gonna be coming up
pretty soon, so maybe we'll seewhat's out.
Speaker 3 (29:27):
This is how.
This is how much.
Speaker 2 (29:29):
I've been living in the basement lately as the fact
that there's a huge movie theyjust came out.
I have absolutely no awarenessthat it actually dropped and
it's in theaters now.
It's in theaters now.
Speaker 3 (29:38):
It's in theaters now.
It's absolutely in theaters now.
And, by the way, a littletrivia for everybody out there
notice there's no computers indune.
If you don't know the backstory, it's AI.
Ai comes along, causes adisaster.
There is literally a culturalrevolution Against AI and now
there's no more what they callthinking computers.
(29:59):
So it's that old story, thatold old story of the machines
are gonna get us.
Speaker 2 (30:05):
They're coming for you?
No, they're not.
Speaker 3 (30:09):
I just need to go outside and mow the lawn.
Speaker 2 (30:11):
There we go, man the Brooks.
This has been an amazingconversation.
I have enjoyed being able toriff with you, especially on the
music idea.
I didn't think we'd go downthis path, but you know what
this is glad we did this hasbeen awesome.
Speaker 3 (30:24):
I'm glad we did because and I would encourage
anybody out there, if you're inthe music, if you just like
music there are systems outthere again, I can't name the
two that I'm using that I'mgetting to copot I wish I could
because they are fantastic.
Look third for third-quarterannouncements from some
companies out there in thisspace Um, and try these tools
and just play with them.
You may find and this issomething that's that somebody,
(30:47):
one of the testers said, sayingit's not that I think my music
is great to the world, but Ireally like.
I really like listening to itbecause it's my music and there
is a something about AI andCreativity coming along beside
you to create your own thing.
It may not be what the worldwants to see, but you'll love
seeing it.
No, love hearing it.
So get involved in these sortsof things, folks.
(31:08):
And again and Steve's beenreally smart about pointing this
out to y'all in the otherpodcast, so hope y'all are
listening to all of them is thisidea of this is a tool.
This is something you should belearning.
Go out there and learn to useit, embrace it.
It's more fun than you think.
Speaker 2 (31:24):
Words of wisdom from from the amazing Brooks E.
Warren Brooks, it has been anabsolute delight to have you on
the podcast today.
Thanks so much for taking thetime and joy to having you on
the show and definitely want tohave you back again to talk more
about your Progression of musicand AI and how it's been and
how it's been for you and whatyou're learning along the way
Interesting and we'll do somedemos next time we will come on
(31:46):
the show and give us a, give usa little bit of a sample.
We will do demos.
Dude Brooks where can we, wherecan we follow you?
Where can we find you?
Speaker 3 (31:53):
I am on LinkedIn, I am on X and those are the main
two places I'm posting.
Anything up right now is Ibegin my new travels into super
computers and some of thebiggest companies in the world
trying to solve the biggestproblems out there.
So check them out.
Speaker 2 (32:07):
Ladies and gentlemen, the amazing Brooks, e Warren
Brooks, thanks so much.
Speaker 1 (32:11):
Thanks.
Welcome to Tech Travels hosted by the seasoned
tech enthusiast and industryexpert, steve Woodard.
With over 25 years ofexperience and a track record of
collaborating with thebrightest minds in technology,
steve is your seasoned guidethrough the ever-evolving world
of innovation.
Join us as we embark on aninsightful journey, exploring
(00:27):
the past, present and future oftech under Steve's expert
guidance.
Speaker 2 (00:32):
Welcome back, fellow travelers, to another exciting
episode of Tech Travels.
Today's expedition is trulythrilling.
We have the privilege ofcharting these digital waters
with Brooks Seahorn, a trueluminary in the field of
innovation.
Now, brooks isn't merely just atechnologist he's an alchemy of
technology, if used with witand fervor.
With his profound knowledge ofcloud computing, his unique
(00:55):
approach to education is notjust merely informative it is in
totally engaging, transformingintricate technical concepts
into riveting tales that reallydo stick with you.
Now, with a diverse odysseythat spans over 25 years,
including crucial time spent asan Air Force contractor and
distinguished qualificationsfrom AWS and Microsoft, brooks'
(01:16):
story isn't just a chronicle ofpersonal growth, but a map for
navigating the tech space.
So fasten your seatbelts,fellow tech travelers, as we
embark on the enlightening questthrough the digital terrain
with none other than BrooksSeahorn.
Brooks, welcome to the show.
Speaker 3 (01:30):
Thanks, man.
And you know, I don't know,you're old enough to remember,
remember the commercial.
I said never let them see yousweat.
Well, after that intro, I'msweating already, yikes.
Speaker 2 (01:41):
So just again, just you know, just you know kind of
tell us about your journey andhow you really kind of got into
technology and you know thewhole thing that you're working
on now around super computingand AI.
Speaker 3 (01:54):
So take us on that journey.
Well, it's a fun journeybecause it started way back in
college when I got a degree mydegree in organic chemistry,
worked for one night as achemist one night and then said
I'm done, I'm never doing thisagain.
And that's when I kind offloated back to this thing I
discovered in college calledtechnology.
I got to help out a little bitusing some pro programming and
(02:16):
stuff like that, just fell inlove with it and so it was a
pretty big bet to make in onenight to go I'm done, I'm
walking away.
But that's exactly what I did.
And then from there it was justa point of learning all this
technology, getting into thespace, getting the tough jobs,
learning how to do this stuff.
You know everybody wants totalk about.
You know, feeling that sense ofI'm just a sort of a fraud.
(02:37):
I don't know how I got the job.
I did that for a long time, man, trying to figure out how to do
this stuff.
But in that space you learn somuch about how things really get
done, past the theory, the hardwork, and just kept working
through it until finally, youknow, just one, two, one job
after another, things that morecomplicated, more difficult,
more experienced, until finallyone day you look around and go,
(02:59):
wow, I can really do this stuff.
So that's how you end up doingthings like this, when you make
rash decisions in one night at12 o'clock in Montgomery Alabama
.
So that's how I got to thespace.
And then it was just a point ofjust falling in love with it.
And I think that and you're thesame, same same as I am, for
some reason the technology wejust fall in love with it, like
(03:19):
we want to know why it's doingwhat it's doing.
It's more complicated it gets.
We want to know more, like youknow, how exactly are things
working on chip and L2 cash?
How exactly is this thingworking with memory and paging
and all that stuff?
And you just fall down to thisthing and you just become more
passionate about it and you loveit.
It's lifelong learning and Iwould say that and I know you,
(03:40):
steve, you're the same way as onthis one.
It's just we got dumb luck.
We found the thing that we loveand we love doing it, and so we
just keep doing it for somecrazy reason.
So that's how I got here.
I just love the technology.
There's no, there's no fancy.
I got my PhD in 19, no, no,nothing like that.
Just falling in love withtechnology, continuing to play
(04:00):
with it, and I would really sayI think there is a really a big,
big sort of sorority andfraternity of people out there.
We all fit into this same spot.
We just love the technology, welearn about it, we get these
you know these opportunities todive in incredible levels of
depth and just put all thatknowledge together.
Speaker 2 (04:20):
You know it's incredible because when, in full
transparency, Brooks and I knoweach other from working at
Amazon Web Services, yourpassion for technology when I
first came to AWS, when theypaired us together and we went
and did road shows right, it wasby far probably one of the most
incredible experiences I had ofhow you take your specific
(04:40):
approach to technology andmaking it engaging, interactive
and just truly just again, I usethe word captivating, but
seeing you work a room withother people, your love for the
technology.
It also leads into your love foreducation and how you want to
kind of inspire and learn andhave other people follow into
(05:00):
this whole learning trajectory.
Right, tell me a little bitabout this ability to captivate
people when you're up theretalking to people training
education, tell me, like, whatis it that gives you this
amazing superpower?
Speaker 3 (05:17):
You mean the ability to violate OSHA at a whim and
get up on a desk and startranting about stuff.
Yeah, I'll be happy to talkabout that.
No, I mean honestly, I've saidit before and this is one of the
things and I would encourageanyone out there listening to
this podcast if you're intotechnology and you love running
your mouth, marry those twothings together because it's so
(05:40):
much fun.
And here's the other side aboutit.
There's no reason whytechnology should be boring.
It shouldn't be boring, itshould be fun, it should be
engaging.
And we as speakers in the space, technologists in the space
talking about these things, Ithink we kind of have a
responsibility to make it alittle more than just high, you
know.
You know I thought about Steve.
(06:01):
I thought specifically aboutwhat was the SNL thing.
Um, the delicious dish, likethe whole podcast, should just
be delicious dish.
You know that kind of thing andpeople do this.
But it's come, there's noreason to do it.
It's exciting, it's fun.
So pour your passion into itand what you'll find is is that,
in fact, you'll enjoy it a lotmore when you do speak about it.
And then for me personally, it's, you know, because I've got the
(06:23):
decades of experience.
I've seen what technology hasgone from and to.
Some of it bad, I will admit,some of it fantastic, though.
And so when you see thesechanges continuing to go forward
and you sort of embrace themand go with them.
It it just wells up inside ofyou as a happiness and a joy
that you want to share witheveryone.
And then I would say and thisis something, steve, you saw
(06:46):
this on display several times,I'm sure, with me Um, it's just
this.
I feel like this responsibilitythat when I'm explaining
something to somebody, I'vereally got to put a lot of heart
behind it to engage them, tomake them want to be part of the
conversation, to want to learnmore, because if you don't, it's
just boring and nobody cares.
Put a little bit of heart intoit and again it's going to be a
(07:07):
downhill effect.
You're going to enjoy speakingabout it more, they're going to
be enjoying learning about itmore, and it just goes round and
round and round and uh, andthat's everything from let's see
what uh, climbing up on desks,uh, kicking over a chair I
nearly broke my foot because Ihad a person in the audience go.
Ec2s are ephemeral and I likefreaked out at that simple
mention of stuff like that,doing different voices, all
(07:30):
those sorts of things.
But it's always and this is theone thing I let me.
Let me just end this question onthat.
Everybody, if you want to do it, go do it.
It's fantastic.
Make sure you got your techchops together, because nothing
is worse than doing somethingsilly and then being technically
wrong at the same time.
Speaker 2 (07:45):
That's a hard spot to be in.
So, with that said, let's talklike a little.
You mentioned heart, right, andI think that you know I think
AI needs a little bit of someheart right now.
So let's put a little bit oflove into some AI right now.
So again, more and more uhtools, more and more of this
shift towards AI adoption.
You know everyone wants tothink about AI as a tool, not as
(08:06):
a replacement.
You know, share some thoughtson kind of your perspective on
how this is now going to impactuh decision making, creativity
and, most importantly, kind ofhow you start to see this across
different industry sectors andhow it probably are going to
impact jobs.
Speaker 3 (08:20):
You know, let me, let me answer.
Let me actually start withstart with the end, because I
think the end's a very importantpoint, because I've heard a lot
of people say how it's going toimpact jobs.
Am I going to lose my job, etc.
Etc.
I would say, in the short term,you're there's no threat to you
, in most cases, losing your jobto AI.
What you're going to do, though, is possibly lose it to
somebody who knows how to use AI, and that's the problem for
(08:42):
anyone who's not using it.
Um, there's been so many caseswhen you can just switch over to
something like a chat, jim andI whatever system you want to
talk about quickly get an answerto a question, or get a more
sort of lucid way of explainingsomething like hey, chat, can
you make this sound a littlemore reasonable, and then it can
create something for you.
I think it's a great tool inthat space, but that goes back
(09:06):
to the very beginning of whatyou said, the heart of it.
What did you tell the system togenerate for you, and did you
put something truly unique inthere?
Or did you just say hey, I needa great article for LinkedIn
telling me about AI and how itcan help me find a job.
Copy paste, no, no, you didnothing.
You did nothing.
Stop doing that.
(09:26):
Here's a better idea.
Start with that and then startsort of adding your own style to
it, your own words, puttingthings that aren't expected in
there, because that's the thingthat AI really can't do yet.
It really can't.
Don't get me wrong.
It can be kind of creative andit can kind of push you in some
unique directions, and I likethat about it.
(09:47):
But that's how you should useit as a tool, not as a
foundation upon which you arebuilding things.
I think that's where I don'tthink we're there yet.
So, sort of, in short, talkingabout the whole thing use it as
a tool.
Use it as a tool in your job.
My goodness, I, steve, my wifeand I have been talking about
getting a brand new mattress.
(10:07):
Yes, I used AI to help me startmaking this decision.
I know it sounds stupid, butyou can say to it hey, what
would you recommend based on theinformation that you have?
It might give you a directionthat you never thought of or a
brand you didn't think of.
So that's why I say to peopleright now AI it's a tool, use it
as a tool, but then you need tobecome part of that loop.
(10:29):
When you get the answer it'snot a copy paste, it's a copy
out to something else.
Touch it up, put your own style,your own unusual, you know sort
of personality into it, thenmaybe that's what you needed to.
So, right now, use it as a tool.
Use it as a replacement, not asa replacement, use it as a tool
.
I mean like.
One of the things I've beenreally interested in is
(10:50):
particularly the music AI space,since I'm a musician, feeding
in some music to it and saying,hey, give me something unusual,
you know, at this particularpoint in the song and then let
it put something in weird andthen nine times out of 10 is
garbage, get rid of it.
Every once in a while it'll dosomething and I'll be like
that's interesting, I didn'tthink of that and it's not my
(11:12):
style.
It sounds great, but it's notmy style.
But I'll go ahead and embraceit anyway.
That's where the power of thetwo it comes in as a tool, not
as a foundation.
Speaker 2 (11:22):
Use it as a tool?
You mentioned you mentionedthis, and this is something I
haven't explored yet, so I hopethat we can double click on this
is, you know, the ability tohave it work as somewhat of a
somewhat as a kind of a co-pilotwhen you're basically using
something like music?
And I've not had a chance totouch on this.
I've talked about technology,but the music aspect, I'm very
interested to hear more about it.
(11:43):
So, as a musician, what are you, what are you kind of putting
into AI?
Well, what are you expectingfrom it?
And then, what are you gettingback when you say interesting?
Speaker 3 (11:52):
Well, there's two systems I'm working with I can't
name either.
I'm sorry, I'm under NDA rightnow, so, sorry, can't name them,
but they I will say this theywill be releasing in the third
quarter of this year.
They will be releasing, I havebeen told, and here's what you
can do with them.
And this is this is the coolpart, steve you can feed in MP3.
You can feed in actual music,notation music, to the system.
(12:14):
Let it look at it and then youstart prompting it from an AI
tool point of view, saying lookwhat would you say?
You know like, suggest adifferent.
You know like a different, likewhen we get to this fourth
measure right here, I want to dosomething unusual with the
baseline and it'll like come upwith something scale wise.
It makes sense.
In fact, I've even seen a casewhere one of the systems even
(12:38):
made suggestion of a note thatwasn't on scale, which I don't
know if anybody's ever out therehas ever heard.
But it's kind of like youlisten to somebody sing, then
it's like you kind of hear thathalf step down.
It suggested the half step downand I was like that is so smart
, because the best musicianspull crap like that.
They will take that one note.
(12:59):
That doesn't quite make sense.
Then they'll pull it back up.
It's called a pressure release,and so these things are being
built into these systems.
The thing about it, though, Ithink, steve, is this it comes
back to still being a tool.
You've got to write a song thatkind of has got a nice hook,
it's got a nice feel to it, it'sgot a nice beat.
Whatever the case is, let AIlook at it and say, hey, I got
(13:21):
an idea.
You might want to try this, andagain, nine times out of ten
you're like garbage, and so youjust get rid of it.
But every once in a while, itmay make a suggestion that you
really like, and suddenly youwant to add that to the bass
line, to the guitar, to thedrums, whatever the case may be,
and so I think in that space,it's going to come along quite a
bit.
Now I will say this neither oneof these are Amazon products,
because I've had people who'veasked me.
(13:41):
We've tried to figure out is itthe Amazon thing?
It's like nope, no, it's notthat keyboard thing.
Speaker 1 (13:45):
It is not Deep composer.
Speaker 3 (13:47):
Yes, it's not deep composer.
It is not deep composer, it'sliterally this one company.
What they do is they've justbeen feeding music into it,
feeding music into it andfeeding music into it, letting
the model build itself, runningreally large AI jobs on it so we
can start to learn about style.
And that's the other part aboutit too.
Is that I think is reallyfascinating is watching AI learn
(14:08):
about style, understandingblues, delta blues, southwestern
blues, even what we call it.
We call it Portlandia blues.
You know, it's kind of likethat 90s sort of grunge, but
there's a bit of a bluesiness toit, like somebody found a Coke
bottle and started sliding it upand down the guitar, that sort
of thing.
It's learning about thesethings, so you can be very
(14:29):
specific in it, and I think andI'm going to make a prediction
on your show okay, I'm going togo ahead and make a prediction
At least, no more than a yearfrom now, we should be able to.
Can you hear the backgroundnoise?
Speaker 2 (14:41):
Oh yeah.
Speaker 3 (14:42):
Okay, sorry about that.
That's my dog, sam.
He's very excited about AImusic, so you heard me talking
about it.
There will be.
There will come a point, Ithink, honestly, where we can
get, I guess, what I would call,more than anything else,
streams of style when it comesto music.
Speaker 2 (14:59):
That's incredible.
I mean, I want to know moreabout the.
I think if you were to startfeeding in tons and tons and
tons of music across differentgenres, there is definitely no
lack of music that I couldprobably absorb, right, Just
like a natural language model isgoing out basically providing
an index of all the text writtenand it's looking and evaluating
(15:21):
different forms of language andpatterns.
But music is interestingbecause you almost think of it
like it's your sound engineer,it's your producer, Like the
people who would kind of be kindof in that space, right, when
they would hear an artist andthey would say, well, why don't
you try to tweak it like this ormake it sound like this?
And then the artist would say,okay, that sounds great, Okay,
(15:43):
now play it again, right, quickhere, and then play it again
with this.
And the next thing, you knowyou've got, you know like again,
you hear all the stories aroundhow certain artists like Van
Halen or Pink Floyd or you nameany, one of your greats.
Deff Leppard how they were ableto change the style.
You know, rick Rubin with RedHot Chili Peppers was a great
example of well, what do you gotover there?
(16:05):
Well, I've got this notebook,I've got some poems written down
.
Well, why don't you put acouple of those into a lyric and
then see if you can actuallyput a baseline to that?
And the next thing you know,you've got a couple of hits and
they were like well, we didn'teven know about it.
So it sounds like AI is almostkind of becoming that companion
where it's starting to kind ofat least start to work as a way
to help you kind of work on somesort of production, give you
(16:26):
some input, suggestions for newstyles, and give you something
to also, as a creator, to thinkabout.
Creating.
Speaker 3 (16:34):
It's the idea of that sound engineer in a box is what
it comes down to.
Can we, instead of paying, fora studio because, like right now
, studio time runs about.
I think for a 12-hour sessionright now you're gonna pay about
$1,000.
So you know with an engineerstudio I don't know if that even
includes mixing anymore, soabout $1,000,.
Could you put that into a box?
Could you sit there andactually record it, push it to
(16:56):
the box, the box put everythingtogether for you, just like an
engineer would.
Now I think once again we're inthat space we started about in
the beginning of AI as a tool.
It could be a great toolinitially for a sound engineer.
Is it gonna replace a soundengineer?
And not yet.
There's no way to put Rick Rubinin a box.
It isn't gonna happen.
There's no way to put, you know, verdeen, white of Earth, wind
(17:17):
and Fire in a box.
It just isn't gonna happen.
Or, like I think about, youknow, like Jack Strafford of
Wolfpeck, anybody like that, thefolks from Dirty Loops, good
gravy, it's not gonna happen.
But I think what you said isexactly right.
It's that idea of having acopilot sitting next to you that
you can kind of go over and say, hey, what'd you think about
that?
And I think that's fun, becauseto me that becomes the heart of
(17:39):
an AI system where you kind ofgo hey, chewy, what do you want
to listen to?
You're oh, and he sits, he putsit over on Western.
You know it's like well, Ididn't think of that, but great
idea.
Thanks, buddy, as you fly alongthrough space.
Speaker 2 (17:50):
Yeah, it's incredible , I think, about all the
different artists that kind ofcross genres.
Right, they're mixing.
I think a friend of mineintroduced me to something that
was almost kind of like aWestern crossover with rap and
it was almost like so I thoughtit was very interesting and I
think probably that there willbe new genres right Of music
that tend to probably will comeout and will evolve from some
(18:12):
sort of kind of like AI kind ofAI music entity there.
It can, it can kind of help youbuild upon that.
Speaker 3 (18:18):
I mean, I think you could be a one man band at that
point right, Absolutely, I mean,if you can play all the
instruments fairly well and youknow what you're doing, yeah,
you can absolutely do that.
I mean, and the thing is isthat I think in that space and
this is where I get excitedabout it it would allow that
person to be.
And what I mean by that is thisyou've got somebody out there
(18:38):
who's an incredible musician.
They can do incredible work.
However, they don't have themoney, they don't have the
friends, they don't have theother friends who give a care.
They're this one person on anisland.
As I used to say to people, itwas me in technology back in the
early 90s here in CentralAlabama.
I was on an island, y'all.
I really it felt like I was onisland, just reaching out.
Is there anybody out theredoing technology?
(18:58):
So for that person to have theAI system come alongside and say
you know?
Or for them to say, hey, I'vewritten this really neat guitar
bit, what do you think?
And it goes hey, I can add abaseline to that, or I can give
you a backing drum track that Ithink would work with that.
And then you say to it let'smake it a little more bluesier,
a little more up here, let'smake it dance, whatever the case
(19:20):
is, and then put all that stufftogether.
That's where I think AI isgoing to get really, really fun.
Speaker 2 (19:26):
Interesting.
I mentioned the idea to aprevious guest around digital
authenticity and, as a creator,as you're basically creating, is
that you're creating somethingthat's very unique and specific
to your own creative talents.
How do you think about AI inthis space around digital
(19:46):
authenticity being able to say,no, I actually I was able to
create this.
I'm able to then some sort ofcreate some sort of
cryptographic key or an NFT.
What's your ideas arounddigital authenticity in this
space with regards to creators,musicians?
Speaker 3 (20:01):
I think it's going to be incredibly difficult to
figure this one out.
Let me explain why.
I am what they call a muddyplayer.
Okay, like when I play bass,when I play acoustic, I'm very
muddy.
I don't.
I don't have clean technique, Iprefer muddy technique.
It's more, it's very much moreof a Delta bluesy.
You can really hear the stringschiming on the frets and stuff
like that.
I like that.
(20:22):
For me, that makes it easier inthe space because, with AI,
accidentally put garbage in itcould, I guess you could kind of
trick it into it.
If you think about bands likedisclosure, if you listen to
very carefully to songs likeLatch, you can hear pop and hiss
in the background beinginjected by the engineer to give
it a record sound, so you caninject noise and stuff like that
(20:43):
, but you can tell when it'sbeen injected and when
somebody's just classicallydoing it.
The problem I have, though,steve, is when you move into
bands like and there's afantastic band out there called
Dirty Loops.
Most people have never heard ofthem.
They are probably one of thebest bands in the world right
now Technically the best bassplayer, singer, drummer in the
(21:03):
world.
They play almost perfectly.
Their drummer, I think has anatomic clock in his head.
He's so perfectly.
Now, how do you inject artifactsinto that?
Well, they would never injectartifacts.
They're super clean players,which means I think AI would
have an easier time doing that,because it wouldn't have to come
up with the unusual.
It could get that sort of thing.
So when you want to inject thatauthenticity, the only way I see
(21:28):
it happening is going to haveto be in the form of some sort
of metadata, which, again,because it's ones and zeros on a
wire, I can fake that too.
I can add that in and go no,look, there's that digital
signature.
This was truly.
You know, steven the Woodards,I'm going to be your bass player
and Steven the Woodards, sowe've recorded a song, we've put
(21:49):
our key in there, and then,finally, I mean, there are
authenticity mechanisms outthere that are possible to use.
They're actually quite old,simply doing things like MP5
hash sums saying, look, this wastruly me playing this.
You can't recreate it, I can'trecreate it.
It's a unique piece in and ofitself, but as far as being able
to say because I've had thisproblem myself, I played music
(22:11):
before played it back andsomebody said that's you and I'm
like yeah, that's me Like no,I'm like yeah, and so then you
get into that whole space.
You can't prove it unless youpull down the instruments and
start playing it.
So, hey, maybe this is theresurgence of a stadium concerts
.
I think it could be.
Speaker 2 (22:28):
Yeah Well, I mean absolutely, I think.
I think I'm all for it, right,is that you've got?
You've got the resurgence ofconcerts coming back again?
You know it's interesting totalk about music.
I'd love to kind of like to usethe term.
Let me riff on this for asecond right.
Go ahead Laughter, humor andcomedy, you know, are you know
(22:50):
okay?
So I've been finding that it'sbeen very AI has been pretty
mediocre when it comes to kindof these spaces here.
Oh yeah, I don't thinkcomedians, and especially with
comedians and things like that,being able to feel like they're
ever going to get out ofoutspite AI, like AI is going to
tell me a joke better than yeah, I just don't think you know
(23:11):
the thing is with comedy.
Speaker 3 (23:12):
it doesn't make sense .
There was a, there was a greatbit, and I think I forget where.
it was Jerry Seinfeld who saidit but, he was going to go teach
a class on comedy and basicallystarted out saying you're not
funny.
If you're in this class tolearn how to be, you're not
funny.
Like I can't explain to you howfunny works.
I remember this comedian namedKlaus Meyers he was.
(23:36):
He was on King of Queens and afew other shows.
He's a German comedian and hestarted his bit with this joke
about and he had this reallythick German accent and he would
say something like you know oneof the greatest problems in my
career.
And keep in mind, you'rehearing this and just you know
this is German sort of.
You know I can't do a Germanaccent, but he's saying it with
this German accent.
And he says people havewondered can somebody who's from
(23:57):
Germany be funny?
And then he kind of paused andhe goes well, let me assure you,
and the place would just comeapart, laughing at this
absolutely insidious voicesaying this how is that funny?
How can I teach AI that that'sfunny?
I don't think you can.
At least I don't know yet ifyou can and I don't know if AI
(24:19):
in the modeling can figure itout.
So I think in that space that'sgoing to be a tough one.
I think we can have a lot ofreally bad AI comedians coming
out who just don't know whatthey're doing and they're going
to bomb and they're going to getbooed off stage because the
quiescence of a lot of thingsthat we do as human beings that
I don't think AI has got yet,springs from the strange place
(24:43):
where things just don't makesense.
Like like, one of the thingsI've always told people is, when
it comes to listening to onlinemusic, they want to make
suggestions turn it off, turn itoff or they will take you down
an avenue where you will neverhear a different song.
You will never hear things likelike there is a there's a.
(25:03):
I can't remember the name of theman.
It was called.
Gunpowder chant was the name ofthe song.
Everybody look it up.
Gunpowder chant starts off witha didgeridoo that goes into an
acoustic guitar, that goes intosome sort of strange music that
doesn't make sense.
I never would have found itlistening to regular AI
generated suggestions.
So I think at the core, we'renot there yet and I don't know
(25:24):
if we have the technology to doit yet where AI can truly do the
unexpected and strange andstart to understand.
And the thing is is it maynever happen.
It may be impossible for AI tofigure out or act like a human
good on us.
That means we just have anotherfun partner in the world that
we can all work with, and that'show I prefer to think of it.
(25:44):
Not as it's not going to beTerminator Y'all that's.
It's smarter than that.
It would never come to thefront door and ask for Sarah
Connor.
Okay, it's just going to make astupid suggestion.
You're going to go, okay and goright along with it.
So in that space, I don't thinkwe're going to get there,
because that quiescence of whatit makes to be a human being,
that strange creative thing, is.
It's not there.
Speaker 2 (26:05):
It's just not there.
So there's no, there's no,there's no Skynet moment yet.
Speaker 3 (26:09):
No, there's no Skynet .
Skynet's never going to befunny.
You know the wamper going allthe way back to war games,
Wamper will never be funny.
Wamper will never make greatmusic, Everybody don't worry
about it.
Speaker 2 (26:20):
That's funny.
You mentioned war games.
It's a good movie with MatthewBroderick right.
Speaker 3 (26:24):
Oh yeah, the wamper.
Speaker 2 (26:25):
Yeah, because he was basically a kid.
He was a kid who wasessentially just tapping into
some sort of DARPA project wherethey were simulating some sort
of war game stuff, right yeahexactly.
Speaker 3 (26:37):
And now that I've been in that space I find it
even funnier, because now I'mlike how did the kid get a dial
up into the zipper?
I mean, you can't do that.
What is this nonsense?
But yeah, that was the wholething.
And for everybody who doesn'tknow what we're talking about,
this is back in the cool daywhere you take literally the old
phone that you would hold upyour head, you put it in the
suction cups so it'd get thegood connection, and then you
(26:59):
had this really awful connectionover to this thing they called
wamper, which was their superintelligence at that time, which
was whatever.
But I think that that, to me, isinteresting because if you go
back and you now look at that,that system had what we think we
have now, that idea of thisthinking thing that can think
things through and go.
You know, there's no point tonuclear war.
(27:22):
There are no winners.
Would you like to play a nicegame of chess?
I think it's how the movieactually ends.
If I remember correctly, it runsthrough every simulation and
then, through its own creativity, goes you can't win this.
I can't figure this out.
I'm walking away, let's go playa game.
So, going all the way back toyour joke thing, that thing that
we keep thinking these machinesare gonna have.
(27:43):
I don't think we're there yetand, to be honest with you, I
think it's gonna take atechnology shift Away from what
we're currently using now.
What that is, I don't know.
It could be moving away fromdigital to analog type chips, so
you get that differentiation.
In fact, there's a greatstartup in Austin, texas,
working on that exact thing,using Analog chips for machine
(28:05):
learning to get that sort ofthat unusual sort of responses
versus digital, which is very,of course, 1-0.
Speaker 2 (28:12):
And no, maybe that's where we start getting funny AI
bots mixing it with old analogchips or sort of mix of old
school and new school technology.
Speaker 3 (28:22):
Yeah, let me hook up my old Fender amp and run it
into my computer via USB forsome little bit of machine
learning.
Speaker 2 (28:29):
Well, I mean, maybe we can, maybe you can also plug
in my old Commodore 64 boyMm-hmm, and then maybe I got a
bit 20 see, and we can, yeah.
So you got a Fender amp, yougot a Commodore 64 and
microphone and a bass guitar.
Speaker 3 (28:43):
And then suddenly from that you actually get
Skynet.
But Skynet at that pointbecomes that thing because of
the unusualness of what youInjected into the system,
because now it's not one andzero, it's kind of and maybe
that's where quantum can help usyou start to get that unusual,
you start to get the personality, you start to get the
unusualness actual comedy, realmusic, a real sort of partner in
(29:06):
work.
Now that's when we could loseour jobs, but I don't know what
we're gonna do if we lose ourjobs.
So I can't go beyond that.
Beyond that's a wall.
I'm sorry, at that point I amnow Paula tradies in the desert
and I can't see beyond the Nexus.
Wow.
Speaker 2 (29:21):
That is incredible.
Speaker 3 (29:22):
Just dropped a dune reference right in the middle of
punch.
Speaker 2 (29:24):
Well, the second movie is gonna be coming up
pretty soon, so maybe we'll seewhat's out.
Speaker 3 (29:27):
This is how.
This is how much.
Speaker 2 (29:29):
I've been living in the basement lately as the fact
that there's a huge movie theyjust came out.
I have absolutely no awarenessthat it actually dropped and
it's in theaters now.
It's in theaters now.
Speaker 3 (29:38):
It's in theaters now.
It's absolutely in theaters now.
And, by the way, a littletrivia for everybody out there
notice there's no computers indune.
If you don't know the backstory, it's AI.
Ai comes along, causes adisaster.
There is literally a culturalrevolution Against AI and now
there's no more what they callthinking computers.
(29:59):
So it's that old story, thatold old story of the machines
are gonna get us.
Speaker 2 (30:05):
They're coming for you?
No, they're not.
Speaker 3 (30:09):
I just need to go outside and mow the lawn.
Speaker 2 (30:11):
There we go, man the Brooks.
This has been an amazingconversation.
I have enjoyed being able toriff with you, especially on the
music idea.
I didn't think we'd go downthis path, but you know what
this is glad we did this hasbeen awesome.
Speaker 3 (30:24):
I'm glad we did because and I would encourage
anybody out there, if you're inthe music, if you just like
music there are systems outthere again, I can't name the
two that I'm using that I'mgetting to copot I wish I could
because they are fantastic.
Look third for third-quarterannouncements from some
companies out there in thisspace Um, and try these tools
and just play with them.
You may find and this issomething that's that somebody,
(30:47):
one of the testers said, sayingit's not that I think my music
is great to the world, but Ireally like.
I really like listening to itbecause it's my music and there
is a something about AI andCreativity coming along beside
you to create your own thing.
It may not be what the worldwants to see, but you'll love
seeing it.
No, love hearing it.
So get involved in these sortsof things, folks.
(31:08):
And again and Steve's beenreally smart about pointing this
out to y'all in the otherpodcast, so hope y'all are
listening to all of them is thisidea of this is a tool.
This is something you should belearning.
Go out there and learn to useit, embrace it.
It's more fun than you think.
Speaker 2 (31:24):
Words of wisdom from from the amazing Brooks E.
Warren Brooks, it has been anabsolute delight to have you on
the podcast today.
Thanks so much for taking thetime and joy to having you on
the show and definitely want tohave you back again to talk more
about your Progression of musicand AI and how it's been and
how it's been for you and whatyou're learning along the way
Interesting and we'll do somedemos next time we will come on
(31:46):
the show and give us a, give usa little bit of a sample.
We will do demos.
Dude Brooks where can we, wherecan we follow you?
Where can we find you?
Speaker 3 (31:53):
I am on LinkedIn, I am on X and those are the main
two places I'm posting.
Anything up right now is Ibegin my new travels into super
computers and some of thebiggest companies in the world
trying to solve the biggestproblems out there.
So check them out.
Speaker 2 (32:07):
Ladies and gentlemen, the amazing Brooks, e Warren
Brooks, thanks so much.
Speaker 1 (32:11):
Thanks.
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