Jul 8, 2024 - Unleashing Creativity: How AI is Transforming Artistic Expression

Description

Chapters

Transcript

0:01 you ready to
0:02 [Music]
0:04 [Applause]
0:07 [Music]
0:13 [Music]
0:21 sing I'm just tuning
0:25 dude he doesn't know the difference
0:27 between tuning and playing
0:31 [Music]
0:43 [Music]
0:57 you ready
0:58 chy every time I see you now get that
1:02 look in my
1:04 eyes every time I see your
1:07 mouth I hear that
1:11 smile in the early Misty morning GL I
1:15 heard the engine
1:17 turning the old for outside
1:25 [Music]
1:31 you convince
1:33 me again
1:36 today you're leaving this hotel looking
1:40 for someone else's Golden
1:45 Ring all right something's
1:50 glitching Champ's tuning up champy is
1:53 tuning up CH Champ's a mess tonight what
1:57 do you think champy
2:01 [Music]
2:08 [Music]
2:13 a freedom came my with that
2:17 [Music]
2:18 night just like a jet plane in and out
2:23 of
2:24 side I was hauling ass a million miles
2:28 an hour war and hard out
2:34 here when they came into the
2:39 [Music]
2:40 station they said I was B Beyond
2:45 repairs but I got no quals with my
2:51 situation say here I am
2:55 [Music]
3:00 say Sheree Shere Shere won't you dare
3:05 to say Shere Shere Shere won't you dare
3:10 to say Shere Shere
3:15 Shere
3:18 uhhuh yeah leave a message and your
3:21 number
3:24 please take the time to want to satisfy
3:27 me
3:30 take all these old fantasies and send
3:33 them care of
3:35 [Music]
3:39 me good evening good
3:42 people it's Monday do we get
3:44 philosophical Kyle tonight I do not know
3:48 I don't plan these things it just tends
3:50 to be that on Monday nights maybe it's
3:52 CU I haven't been paying attention to
3:54 all the news I'm not all full of news
3:57 and I'm just full of hot wind
4:03 [Music]
4:12 oh
4:15 yeah good evening good people we get
4:18 Monday
4:22 Kyle I have freshly glued my hair so we
4:25 should be okay on the hair tonight I
4:27 know that's always a big concern a lot
4:30 of lot of people a lot of people come
4:32 here they're like I come for the hair I
4:35 stay for the madness some people quite
4:37 the opposite I I come for the madness
4:40 and the hair I just
4:43 [Laughter]
4:47 tolerate it looks like image generated
4:50 hair AI generated Hair It Is this is a
4:53 uh a masterful collaboration of four
4:56 different
4:58 tupes cleverly s together to seem
5:02 like natural hair with an extremely
5:05 large
5:07 forehead it's taken me decades to get it
5:10 like
5:12 this the amount of tape and bobby
5:15 pins it's it's like a Hollywood uh
5:19 special effects crew in here getting
5:21 this hair to look like this really
5:24 something really really impressive
5:27 Jenny's a part of that
5:31 and Bucky Jenny and Bucky are my two
5:34 primary hair
5:35 people they're
5:37 amazing occasionally Sarah will jump in
5:42 [Music]
5:49 fantastic we've got a pool going on the
5:51 hair
5:54 nice so if you're new here my name's
5:57 Kyle Shannon this the AI learning
5:59 lab all of a sudden that sounded like a
6:01 like an NPR kind of
6:03 [Music]
6:06 like hey it's Kyle
6:09 Shannon little little background
6:15 guitar like an Off Broadway
6:17 [Music]
6:19 show I moved to New York City in
6:24 1987 my first job was at FAO Schwarz
6:27 selling
6:28 yo-yos at the top of the the
6:31 [Music]
6:37 escalator one of my favorite memories of
6:40 that job was Walter kronite coming up
6:43 that escalator with his grandson and I
6:45 was doing some yo-yo tricks and Walter
6:48 kronite looked at his grandson and said
6:51 whoop walking the dog
6:55 [Music]
7:21 that's a true story actually Mr it Kyle
7:24 Kyle we missed you guys thank you so
7:26 much I think two days is too much
7:30 [Music]
7:44 did that job take you around the world
7:45 oh Joker coming in heavy with the dad
7:47 jokes
7:48 [Music]
7:57 tonight you had to be careful with that
7:59 cuz the Y y- Yos that they that I was
8:01 selling were these wooden yo-yos which
8:03 are fine they were fine they weren't
8:06 like Tom [ __ ] you know highly balanced
8:09 machined aircraft aluminum
8:12 yo-yos and so I would often like Zing
8:15 the the yo-yo out like right to
8:17 someone's face and then stop it right
8:19 before it got there there are a couple
8:21 of times where the spindle in the middle
8:24 had worn down and it split the yo-yo in
8:27 half so that was that
8:30 was they they had a they had a bigger
8:32 liability with me selling yo-yos than I
8:35 think they
8:39 realized I met Keith Richards doing
8:43 that it's pretty
8:46 [Music]
8:53 good yeah those were interesting jobs
8:55 the FAO Schwarz jobs cuz they mostly
8:58 hired you know like Broadway actors who
9:01 are not
9:05 working Ana like and share and follow
9:09 the host thank you so much I agree like
9:12 share follow the channel share this
9:14 thing here's who you should share this
9:15 Channel with anyone who you think will
9:18 be pissed off if you share a Channel
9:20 about
9:22 AI speaking a liability let's [ __ ] with
9:25 your
9:27 friendships you know you know Jenny
9:30 listen um look I really appreciate you
9:33 sharing that live uh you know the guy
9:35 was interesting I mean his toupe was
9:37 fantastic but um all he talked about was
9:41 artificial intelligence and you know I
9:43 am personally affronted by by artificial
9:45 intelligence so um I would appreciate it
9:49 if you do not ever share that person
9:52 ever
9:53 again so how long did I watch it well I
9:56 watched all two and a half hours of it
9:58 it was fascinating
10:00 yeah I like chat BT now but I am I'm
10:02 personally offended by artificial
10:04 intelligence but I I do like it a lot
10:06 now it's pretty good isn't it you know I
10:09 can no longer tell if this is a real
10:11 story or
10:13 not no the the FAO short stuff that was
10:16 all real
10:24 [Music]
10:32 yeah you know I was working at fo
10:34 Schwarz
10:36 and trying to get an agent trying to get
10:41 jobs I auditioned for this thing called
10:43 the drama
10:45 [Music]
10:49 project I had to audition to get in
10:52 [Music]
11:08 I did this monologue from Golden
11:12 Boy boxing film or boxing
11:15 [Music]
11:17 play and I had to audition to get in and
11:20 so I decided to pick the prettiest girl
11:23 in the room and I did the monologue
11:26 straight to her was about a girl
11:30 turns out that pretty lady is now my
11:33 [Music]
11:45 wife turns
11:48 [Music]
11:51 out when I did that monologue to her she
11:54 turned to the girl next to her and she
11:56 said uh-oh this looks like trouble
11:59 [Music]
12:08 wow so sweet fantastic Love Story also
12:11 true did I miss a story about Mrs
12:13 Shannon yes you
12:21 did then a group of us broke off from
12:24 that group started a theater
12:28 company and we only
12:32 did original plays which is stupid cuz
12:36 no one's ever heard of them and nobody
12:38 really wants another play in the world
12:40 but we'd Workshop him in
12:43 Vermont in a
12:45 barn I got a barn let's put on a
12:48 show in Warren
12:52 [Music]
12:54 Vermont and then in the winter we take
12:57 the plays that didn't suck
13:01 [Music]
13:03 and we perform them on 42nd
13:06 Street a never before seen picture of
13:09 Kyle getting his hair done in
13:13 Irregulars let's go see this I like the
13:17 idea I like the idea
13:20 people uh there's Irregulars new
13:25 activity
13:28 see this is a little behind the scenes I
13:32 don't know how they got the camera feed
13:33 from uh getting ready for the evening
13:36 but yeah that's that's pretty much how
13:38 it goes
13:40 [Music]
13:49 [Applause]
13:51 [Music]
14:15 living in New York City is pretty
14:17 amazing if you've never done
14:20 it it is it is
14:23 remarkable it is weirdly the biggest
14:26 city you've
14:28 ever experienced and the most intense
14:31 you've ever experienced and it's a
14:33 weirdly small town I remember the first
14:39 day the first day I was living in New
14:41 York City I'd been in a
14:44 play the summer
14:47 [Music]
14:50 before at the mount Greta
14:53 [Music]
14:55 Playhouse we did three Penny
14:58 Opera and it was was directed by Paul
15:00 Giovani who was a Broadway
15:03 [Music]
15:06 director
15:07 [Music]
15:10 and and then I did good enough there
15:14 that he offered me an equity job in
15:16 Washington
15:17 [Music]
15:19 DC at the end of the summer but the
15:21 problem was I had a full ride of full
15:23 scholarship to the Alabama Shakespeare
15:26 Festival so 2 weeks before I was
15:28 supposed to go to the Alabama
15:30 Shakespeare Festival I was like [ __ ] it
15:32 it's an equity house I got my first paid
15:35 job I'll get my Equity card so I'll do
15:37 the show and I'll move to New York
15:41 City and
15:43 so it was the uh crucifer of blood a
15:47 Sherlock
15:48 [Music]
15:50 Holmes murder
15:52 mystery and I played a young lap boy and
15:56 a Pakistani
15:58 [Music]
16:08 conspirator I learned my Pakistani
16:11 accent I learned how to be
16:15 a a serving boy for a rich old
16:19 man and then I moved to New York
16:23 City and my first day living in New York
16:26 city so I moved into an apartment in
16:28 East Harlem on 114th and 1st Avenue with
16:32 some actors that I had worked with the
16:33 summer
16:35 before and I decided to take the subway
16:38 to Time Square and so I'm walking around
16:41 Time Square in the middle of rush
16:44 hour I mean it's [ __ ] just chaos
16:48 right and I hear
16:50 hey it's like huh that's weird sounded
16:53 like someone said hey Kyle and I heard
16:55 hey
16:56 [Music]
16:57 Kyle and it
17:00 it was John peel me who's a playright he
17:02 wrote Agnes of
17:04 God and he was in he was in the three
17:07 Penny Opera at the mount Greta show over
17:10 the summer and so you know I saw him and
17:15 and we ran together and hugged and like
17:17 in the middle of Time Square with like
17:19 thousands of people my first day in New
17:21 York City I run into someone I had a a
17:24 deep relationship with that was really
17:26 cool
17:28 [Music]
17:30 and New York's full of [ __ ] like
17:33 [Music]
17:36 that so yes you're going to get a
17:38 philosophical Kyle
17:40 [Laughter]
17:49 tonight all right what do we want to
17:52 talk about people we can talk about
17:55 pickling cucumbers
17:58 [Music]
18:00 was in a live this afternoon two young
18:02 women had a question dilemma they said
18:05 let's use chat GPT There's Hope oh there
18:07 you
18:08 go I'll tell you what if if you haven't
18:12 if you haven't sort of crossed the the
18:15 Rubicon if you haven't crossed the
18:16 threshold with chat
18:19 GPT
18:21 where whenever you think oh I should use
18:25 my brain and come up with
18:27 something if you haven't cross the
18:29 threshold where you then correct that
18:31 and go oh no [ __ ] that let me just try
18:33 chat gbt first that's a really fun
18:35 threshold to cross
18:38 because you still get to use your
18:42 brain to come up with the ideas and
18:45 curate the ideas and refine the ideas
18:48 but you can just live at the sort of
18:50 ideation level that much higher kind of
18:54 for me higher fulfillment rather than
18:56 sort of running down all the Tactical
18:57 detail rabbit holes
19:00 that's a that's a fun threshold to
19:02 cross would you be on my podcast tell me
19:05 three things absolutely Tim Lord just uh
19:07 DM me happy
19:09 to do I have to come up with three can I
19:12 use
19:13 chbt thing one uh never go on a podcast
19:18 called three things um thing two uh uh
19:24 chat GPT told me to delve deeper into
19:27 the tapestry of the unfolding
19:29 Paradigm
19:31 of podcast speaking thing three uh yeah
19:37 happy
19:39 to as you can
19:42 tell I'm a scintillating
19:46 guest I quit using Google in my brain
19:50 and and my brain thanks to chat GPT
19:52 exactly exactly I got to tell you if you
19:55 haven't um if you're still using Google
19:58 and you still are under the delusion
20:00 that it works start using chat
20:03 GPT Google gets long in the tooth really
20:06 [ __ ]
20:08 fast like I I I I sincerely cannot
20:12 believe how bad Google search is these
20:15 days it's just it's just not usable not
20:18 usable by the way little coffee with
20:20 milk in case you're wondering it's it's
20:23 not it's not Denver tap water
20:29 all right I find myself telling people
20:31 that it was chat GT but I had to rewrite
20:33 it five times yeah I got a note from
20:35 from Allan today um asking about he had
20:39 heard that I wrote a book using Claude
20:42 on the channel here and he goes he goes
20:45 I heard you put in like a 2hour video
20:47 and it wrote a book and I was like uh no
20:51 I put in a list of quotes and then I
20:53 took 2 hours 2 and 1/2
20:56 hours and about 400 prompts to get it to
20:59 write a
21:00 book
21:02 so we're not quite at the push a button
21:05 get a book
21:06 [Music]
21:13 yet new new images in Irregulars it
21:16 seems new
21:20 activity will act for I had a little
21:23 lighter hair back then I was I was more
21:25 blondish than
21:26 brownish and it was a wooden yo-yo
21:30 like a
21:32 blonde but that's what it looked like
21:34 you went up the escalators and I stood
21:36 right at the top of the escalator right
21:38 up here twirling my will act for food
21:42 that's pretty much
21:45 it and this is the glamorous life I lead
21:47 today this is where it
21:49 started where it is today oh yeah oh
21:53 yeah people
22:01 that's comedy right there I'm finding
22:04 the combo of chat PT Gemini and Claud
22:07 are great for e-commerce yeah so I'm I'm
22:10 experiencing the same thing where
22:12 although I haven't been playing as much
22:14 with Gemini I it their latest release
22:17 got me really confused and I like I I
22:19 don't know I just sto it pissed me
22:21 off cuz they're kind of all over the
22:23 place um so I haven't been using that
22:25 but Claude is really really good chat
22:28 GPT is really really really good and but
22:30 they do different things better so
22:32 bouncing back and forth between them I
22:35 think is a really good strategy right
22:36 [Music]
22:38 now there's also uh Silver Fox Lori um
22:43 asked me a question for my AI walk and
22:45 talks which I haven't gotten to yet
22:47 but but it was uh it was basically about
22:53 um if you want to do something with a
22:56 particular category of tools should you
22:59 learn lots of tools thinly or should you
23:02 pick one and and go really
23:05 deep it's a really good question
23:08 um I think it depends what mode you're
23:11 in so I I see AI literac literacy being
23:16 a journey of kind of three different
23:17 modes we talk about this on the AI Salon
23:20 a lot which if you haven't checked out
23:23 the AI
23:25 Salon
23:27 um there's the address go
23:31 there and check that out go to the click
23:34 on the top link there it's the
23:37 community um
23:41 and the three modes are play first
23:44 mindfully create and generously lead and
23:48 how I like to think about The Learning
23:50 Journey is play first is when you're in
23:54 sponge mode you're just trying to learn
23:58 so
23:59 if you're like oh I want to get into
24:01 image generation don't just pick a tool
24:03 and go deep on it play with as many as
24:05 you can or if you're doing the same with
24:07 video or song generation or even large
24:09 language
24:10 models play with as many as you can and
24:13 you know some of them are going to have
24:15 free modes some of them won't you don't
24:17 you don't want to do all sorts of
24:18 subscriptions you just want to play you
24:20 just want to get a taste for as many as
24:22 you can and you'll see that oh this
24:24 one's kind of good at this kind of thing
24:25 and that one's good at that kind of
24:26 thing and you'll start to figure out
24:28 it's not not like any tool is is better
24:31 than another it's that any tool for a
24:35 given use case and your
24:39 personality are going to suit you better
24:41 than
24:42 others and the only way to kind of learn
24:45 that is to try them on it's it's kind of
24:47 like picking schools for your children
24:49 if you've ever had to do that where if
24:51 you listen to other
24:52 parents which I made the mistake of
24:56 doing a couple of times I was like oh
24:58 Bob thought this was fantastic this has
25:00 got to be a fantastic School let's put
25:02 our kids here and see if it [ __ ] up
25:04 their
25:05 life and it did you you you really have
25:09 to try this [ __ ] on for size yourself
25:11 right you can't just say oh someone else
25:13 loved this it must be great no no
25:15 sometimes you'll try a thing someone
25:17 else said was great you'll hate it and
25:19 then you'll try something else that they
25:20 hated and you'll love it so in that play
25:23 first mode cast as wide AET as possible
25:29 and then once you've got your head
25:31 around okay I kind of like this tool or
25:33 or you know like like there's subtleties
25:36 like like for art mid Journey if you
25:40 want high quality images is there's
25:43 nothing like
25:44 it unless you want to produce text and
25:48 then you need to use um dolly3 within
25:52 chat jpt or um what you call it uh
25:56 ideogram those do text really well so
25:59 you kind of learn subtleties right then
26:02 once you decide on your project then you
26:04 narrow it down so you start really
26:06 wide up here trying everything figure
26:10 out the one or two tools that you really
26:12 like narrow down and then when you do
26:13 your project Run Deep for that
26:17 project and the generously lead part is
26:21 share what you've learned so in this
26:23 process of sort of learning wide and
26:26 narrowing down and building something
26:28 share what you're learning and
26:30 share you know what you learned in the
26:32 play first mode share what you learned
26:34 as you're building and you will
26:37 gain um trust and a following and a
26:40 reputation for somebody who is
26:44 thoughtfully building things with
26:46 AI and a leader saw an article
26:50 today that we are most creative don't
26:54 care what others think at age four
26:57 rather than seven oh interesting
26:59 interesting as we talked about before
27:02 yeah that makes
27:03 sense yeah it's generally around age
27:07 five where something happens where you
27:10 realize the world is
27:12 dangerous and that's when you start to
27:14 shut your creative brain
27:17 down
27:21 yep and what what seren is talking about
27:24 what Amelio's wife is talking about
27:26 there is
27:29 what people here
27:31 have consistently experienced is once
27:36 you sort of break through the what's
27:38 this AI stuff all
27:40 about I don't get it I don't get it it's
27:44 like gole oh
27:47 champ champy champ champ
27:52 champ champy come sing come on you want
27:55 to come sing
27:59 [Music]
28:15 were you protecting us from the evil
28:16 people yeah it's a good dog oh it's a
28:19 good dog oh good
28:22 dog um what was I talking
28:27 about hey AG five we go to school yeah
28:31 it could be
28:32 [Music]
28:41 school I wrote a scene in a oneman show
28:45 about the thing that happened to me when
28:47 I was
28:47 five and I compared it to the thing that
28:50 happened to my dad when he was five and
28:53 how we reacted to the same situation
28:58 [Music]
29:05 and that gave me insight as to why I
29:06 became an actor and he became a
29:09 pilot life's
29:12 [Music]
29:24 weird all right constantly being taught
29:27 to color inside the lines
29:33 yep all right what do you want to talk
29:36 about people
29:38 here what do you want to dig into you
29:40 want to dig into anything you want me
29:41 just keep rambling I can keep rambling a
29:44 pilot wow amelo has always wanted to be
29:47 a pilot yeah my dad was a was a pilot in
29:50 the Air Force he flew um Huey
29:54 helicopters in
29:56 Vietnam he flew uh
29:59 he was co-pilots on c130s the big cargo
30:03 planes he trained on
30:05 t38
30:07 t38 training
30:12 [Music]
30:17 Jets I think he might have flown c
30:20 c 141s see4 141s yeah I think 141s the
30:26 big jet cargo planes
30:31 yep I thought about being a pilot but
30:34 with my ADD
30:36 brain well I'd probably been okay being
30:38 a pilot cuz it's a hyperfocus
30:42 thing but the boring [ __ ] in in between
30:45 in the the checklists at the
30:50 beginning I mean I know you want the
30:52 airplane to stay in the air and you
30:53 should check all that [ __ ] but I just
30:56 want to go fly
31:01 I would not have been a good commercial
31:03 pilot I think I'd have been a good
31:04 fighter
31:10 [Music]
31:19 pilot you are were an actor I was I have
31:23 a fine arts degree from Penn State
31:25 University in performance they called it
31:29 I don't know why they called it
31:29 performance it's
31:31 [Music]
31:33 acting then I moved to New York City out
31:35 of
31:36 school started and ran a theater
31:39 company got tired of doing free theater
31:42 then I wrote seven screen plays in two
31:45 years started a fake management company
31:48 cuz we didn't have agents we got good
31:51 enough at being fake agents that we got
31:52 real clients
31:55 [Music]
31:58 and then uh in the mid90s when the web
32:01 came
32:02 along I started one of the first online
32:05 magazines and one of the first digital
32:06 web agencies and then ended
32:11 up building that company from like two
32:14 people to 2200 people in 5 years so it
32:17 was pretty [ __ ] surreal to go from
32:19 being an outof workor actor to being a
32:21 chief creative officer of a 2,000 person
32:24 agency building websites for the biggest
32:27 brands in the world we are Penn State
32:31 exactly worker B worker B knows we are
32:35 Penn
32:38 State actually that was my first night
32:41 at Penn
32:45 State my first night at Penn State we
32:48 went out drinking of
32:52 course or we might have gone out I think
32:55 we went out and got beer and we drank
32:56 all night we stayed up all night
32:59 and then we were like hey let's go break
33:00 into Beaver Stadium and so so we went
33:03 and we broke into Beaver
33:05 Stadium and then we went out and hung
33:09 out at the 50 yard line in the middle of
33:11 Beaver Stadium and watched the sunrise
33:13 that was pretty cool that was I've had a
33:15 couple of really good first first day
33:19 experiences at places New York City Penn
33:22 State
33:30 [Music]
33:35 my daughter's an actress she's in Paris
33:37 does combat video editing dance singing
33:40 Lexie Baker nice that's awesome
33:45 [Applause]
33:49 Joseph you know it's funny I think that
33:54 um the acting the the creative arts are
33:57 about to get
34:03 decimated and
34:05 then I think they
34:07 emerge a couple of years from
34:11 now um in a really powerful state but
34:14 it's going to be completely
34:17 different I think what what gets
34:20 decimated is the current business model
34:21 I think voiceover actors are that like
34:24 that industry is just going to be
34:27 obliterated
34:30 but I think special effects like just
34:33 just a lot of the jobs are going to be
34:36 [Music]
34:39 different but I think if we if if we
34:43 go more like a 5year Time
34:48 Horizon here's how I think about
34:51 [Music]
34:55 it the AI stuff is going to automate a
34:58 lot of the Tactical
35:00 execution including in the creative
35:04 arts and so just all the [ __ ] that used
35:07 to be done by people is now going to be
35:09 done by these machines and it's just
35:11 going to be a handful of like creative
35:12 director types that are conducting all
35:15 these tools and they'll do all that
35:18 [ __ ] and I think that there's going to
35:21 be a real like a dramatic shift
35:25 toward authentic experiences
35:28 so theater live music um uh Escape rooms
35:33 um just just in-person physical events
35:37 that that a lot of this online stuff is
35:39 going to get so saturated with
35:41 content that people are going to have a
35:44 hunger for connection and entertainment
35:48 and so I think there'll be a rebirth of
35:50 a lot
35:51 of Need for talented people to do
35:54 interesting [ __ ] um but it's I think
35:57 it's going to be an ugly 5 years and to
36:00 be quite
36:01 honest the the you know it's funny
36:03 everyone's talking about oh the you the
36:06 creative arts are all [ __ ] creative
36:08 arts have always been
36:10 [ __ ] I'm a member of Actors Equity the
36:12 the union or I was the the union for
36:16 stage acting in New York and or all over
36:19 the country but you know the you get a
36:22 bro Broadway contract there
36:25 um they have like a 95% unemployment
36:28 rate like this is back in the'80s
36:32 nobody needs another
36:35 actor if I'm like well I don't want to
36:37 do that role you're not paying me enough
36:39 they'll be like all right there's 10,000
36:41 there's literally 10,000 people behind
36:43 you that that
36:48 would take you out for a walk- on roll
36:52 in this play that you're turning down
36:55 like it's a brutal industry
36:58 anywhere where you've got an inequality
37:01 of amount of jobs for people who want
37:04 those jobs it's going to be [ __ ] up
37:07 and the Arts is that everybody wants a
37:10 gallery show everybody wants a hit song
37:12 everybody wants a stadium tour everybody
37:15 wants to be on
37:18 Broadway how many people get to do that
37:22 six
37:25 relatively you know 3 mlion million
37:28 people a year mve to New York to become
37:29 an actor 22 make
37:32 it and most of those 22 have been pound
37:37 on the boards for 20
37:39 [Music]
37:47 years I'll tell you what
37:50 though you want someone who works their
37:53 [ __ ] ass off hire someone who's been
37:56 in the theater
37:59 [Music]
38:06 if you hire an actor they can talk for
38:08 one
38:08 [Music]
38:10 thing but they also work their ass off
38:13 you can't you can't be an artist and not
38:16 be an
38:17 entrepreneur so theatricals as crazy
38:21 that [ __ ] crazy as they are they'll work
38:23 their ass off they tend to be smart they
38:25 tend to be critical thinkers they tend
38:28 to be
38:30 [Music]
38:35 talented read an article on AI
38:38 chatbots in interpretation of pathology
38:42 reps brought oh brought to mind Story
38:46 vine oh
38:47 interesting interpretation of pathology
38:50 reports
38:54 interesting yeah you know the whole idea
38:57 behind Story vine so Story vine I'm the
38:59 CEO of this company Story vine that's a
39:01 an automated video storytelling platform
39:05 that um most people assume is AI they
39:08 have for 12 years it's not it's more
39:10 Aristotle than
39:13 AI so the idea is that we figure out
39:15 what's the story structure and then we
39:17 prompt someone with a series of
39:20 questions that creates that narrative
39:22 Arc and then those clips go up to the
39:24 cloud 5 minutes later you got a fully
39:25 edited video
39:28 so for doing things like explaining
39:29 things like that it was a Jamma Network
39:31 article very cool Firefly thank you I'll
39:33 check it
39:37 out there should be a want to be a Prof
39:39 professional sports player Union yeah
39:41 exactly same thing Sports is another
39:44 Arena where you know you can be [ __ ]
39:48 massively talented I played one year I
39:51 worked with this guy that owned a
39:53 jewelry
39:54 store and he was a at at some point in
39:58 his life was a semi-professional tennis
40:01 player and he was like in the he was
40:04 like just below the top
40:05 1,000 and I played him all summer and he
40:09 just destroyed me every [ __ ] game
40:11 except at the very end of the summer I I
40:14 won one set from him and it was it was
40:15 like IID [ __ ] won Wimbleton CU cuz he
40:18 was so good and I was so bad but I got
40:21 really good but
40:22 um he was saying in sports the the
40:26 difference between being
40:28 being out of the top 1,000 and in the
40:31 top
40:32 1,000 has nothing to do with
40:35 skill he said once you get to a certain
40:39 level in tennis and frankly this is any
40:41 sport once you get to a certain level
40:43 but tennis is particularly
40:45 acute it's no longer about the
40:48 skill it's all about the head game it's
40:51 all about the head game he's like why do
40:54 the same players end up in the finals
40:57 year after year after year after
41:01 year part of its
41:05 talent but I don't know if you've been
41:07 watching Wimbleton like the the level of
41:09 play is just [ __ ]
41:12 insane and why is it that the top ranked
41:15 players somehow find a way to win that
41:20 point or Stave
41:23 off you know a match point three or four
41:27 times before winning it in five
41:30 sets it's all
41:35 head the Arts is the same way quite
41:39 frankly cuz the Arts isn't about Talent
41:42 like you assume at some point at some
41:44 level everyone's Got Talent who
41:48 works the people that go to the parties
41:51 the people that work the
41:53 room the people that are always in the
41:55 conversation how do you stay in the
41:58 conversation that's what being an actor
42:00 is all
42:02 about and they don't teach that in
42:04 acting
42:05 [Music]
42:08 school I studied with Bill esper in New
42:11 York City William
42:13 esper and it was a 2-year
42:17 program and
42:21 the there was some [ __ ] talented
42:23 people in my class like [ __ ] CRA you
42:26 had to audition to get into this class
42:27 class it's like a master you know
42:29 postgraduate Master New York City acting
42:32 class 2-year
42:35 program and we had some [ __ ] just
42:39 crazy talented
42:42 actors and they weren't the ones that
42:47 worked it was the it was the actors that
42:49 were
42:50 good but knew how to work the room knew
42:53 how to be in the
42:54 conversation knew how to smoo an an
42:57 agent knew knew who the producers were
42:59 at any party that they were at were
43:01 always in those conversations those were
43:03 the ones that
43:04 worked no one ever taught that at least
43:08 not anywhere I
43:09 [Music]
43:16 studied and I think a lot of actors get
43:19 really bitter because of that cuz
43:20 they're like I'm more talented than them
43:23 and they you might be
43:28 you know it's
43:30 funny I this is where okay let's get
43:33 back to AI for a
43:35 second the
43:37 reason I am so passionate about the
43:40 salon the AI
43:42 salon and the reason that I think this
43:45 is the future of work this is the future
43:47 of how we're all going to work not it
43:49 doesn't have to be the AI Salon but
43:50 something like
43:54 it if you assume that AI tools are going
43:57 to get so good that everyone can do
44:00 every skill maybe they're not going to
44:02 be that good okay let's say everyone can
44:06 do every skill at
44:08 80% of a current expert right so okay
44:13 maybe they can't do it at 100% but if I
44:15 could be like 80% as good as a Harvard
44:19 MBA at business
44:23 Consulting I might not need to hire that
44:25 Harvard MBA who's a
44:28 [ __ ] I might hire someone
44:31 else who I know from a group like this
44:35 where I've got a trusted relationship
44:36 with them so I
44:39 think that skill that actors have to
44:44 have is going to be a skill that we all
44:46 have to have over the next 3 to 5 years
44:50 and so getting your ass into a community
44:54 where you're
44:55 actively learning
44:58 and exploring and asking questions and
45:00 teaching other people and building [ __ ]
45:03 and throwing pasta at the wall and just
45:07 all of
45:09 it it's not about the work that you're
45:11 doing in there it's about the
45:13 relationships that you're building in
45:15 there because at some point one of those
45:17 people's going to be in a position where
45:19 they have to hire
45:21 someone and they're going to go
45:24 well
45:25 everyone can do this
45:29 work who do I want to work
45:32 with which is different than how we hire
45:35 today how we hire today is who's got the
45:37 skills to do the
45:39 work what if everyone had the skills
45:42 that's the world we're moving into then
45:45 you hire someone for a different reason
45:46 you hire them because you trust them you
45:48 hire them because they're not an [ __ ]
45:50 you hire them because you know they do
45:51 good work you hire them because they
45:53 make you laugh
45:58 you know that old adage don't be a
46:02 dick you don't have to be an [ __ ] in
46:05 this world you can make money
46:07 withing and I think that actually gets
46:10 really really important in the in the
46:12 coming years so all right what are we
46:17 doing you ready to start we're 50
46:20 minutes in I just put the guitar down
46:22 Champ's looking at me like what's going
46:24 on what's going on Dad
46:28 what are we doing here networking is
46:30 always important
46:33 yep it really
46:38 is which is I think I think one of the
46:41 reasons that LinkedIn is feeling
46:44 so Antiquated and weird
46:49 lately is that everyone's taken the
46:51 course on how to write the cold Outreach
46:59 you know thing and now everyone's using
47:01 chat GPT so you know six times a day
47:04 it's like hey Kyle really love what
47:06 you're doing with Story vine there I
47:08 think it'd be great if we got together
47:10 and expanded our networks for Mutual
47:16 benefit no how about
47:19 no what's the mutual how about this how
47:22 about you give me some benefit over a
47:26 sustained period of time like three or
47:29 four or 5 months or a year or two or
47:34 10 and then when I need whatever the
47:36 [ __ ] it is you're
47:38 Hawking I'll reach out to
47:44 you hey Kyle just wondering if you uh
47:48 were looking for any new clients oh no
47:51 I've got all that I
47:53 need sorry full up on on needing new
47:56 clients
47:59 of course I need new [ __ ] clients you
48:01 think I'm going to reach out to you you
48:03 pin
48:08 head we specialize in helping companies
48:12 like yours get new leads new hot
48:23 leads he seems a little bitter he's he's
48:28 he was a little aggressive on uh on
48:31 LinkedIn there didn't you think it was
48:33 it was I like LinkedIn I I think it's a
48:35 professional networking site I
48:37 mean I don't know I mean sure I use chat
48:40 GPT when I reach out to people hey
48:44 Bob I noticed you uh went to Penn State
48:47 too wink
48:53 wink trust relationships
48:58 providing value not being a
49:06 douche get in communities where you're
49:09 actively
49:12 interacting don't just come in here to
49:14 like what can I who who's going to hire
49:16 me no
49:24 one I guarantee you when Kelly Camp gets
49:26 a big
49:27 job for her AI agency and she needs five
49:31 or seven people cuz it's a big job
49:33 there's a lot of moving parts to
49:35 it she won't be going to
49:41 LinkedIn she'll be like all right who
49:43 have I worked with in the past year and
49:45 a half that I've been on my AI Journey
49:47 that have added value to my life that's
49:50 who she'll hire okay I know that one can
49:53 do this I know that one can do that I
49:55 need someone to know something about
49:56 politics oh Daisy Thomas really good for
49:58 that right that's how that's going to
50:02 happen this woman works thank you so
50:04 much for making my night better oh thank
50:06 you so much I appreciate that I you know
50:13 sometimes sometimes just [ __ ] ramble
50:16 so um I rarely am all that conscious
50:20 about what I'm
50:21 saying I'm often barely conscious
50:25 period so if this is resonating and and
50:28 making uh making a difference thank you
50:31 thank you for saying that cuz I don't
50:32 always know yes I will be calling my
50:35 peeps here says Kelly Camp
50:38 exactly why does Kelly Camp come here
50:41 every night oh sure for the hair
50:44 yeah comes for the hair stays for the
50:49 engagement because as I'm rambling I
50:52 don't know if you noticed this there's a
50:54 whole world of activity going on in the
50:56 comments here here and it also extends
50:58 over to the AI Salon where this group
51:02 the AI learning lab we have our own club
51:04 over here called the AI learning lab
51:08 Irregulars and so as I'm staying stupid
51:11 [ __ ] and talking about my hair people
51:13 and my makeup people and people want to
51:14 make a funny image of that they can
51:16 share it and so what's happening there
51:20 is people are learning people are
51:23 self-expressing people are leading
51:25 people are showing other people oh you
51:27 can respond to things in real
51:29 time and they're building relationships
51:32 that's what this Channel's
51:35 about the fact that I
51:39 talk incessantly with no real
51:43 destination in
51:47 mind I've come to learn actually doesn't
51:51 matter like sometimes it's brilliant and
51:54 awesome sometimes it's a complete was of
51:57 time but it's not it might be a waste of
52:00 time if what you came here for was
52:02 Kyle's going to teach me about
52:04 artificial intelligence then it might
52:06 have been a waste of your time but if
52:08 you're here and while I'm rambling you
52:11 kind of lose your train of thought and
52:12 you connect with someone else in the
52:14 chat here or you just go off and start
52:16 playing with the tool but you're in the
52:20 conversation this is
52:22 valuable You're Building relationships
52:24 You're Building skills You're Building
52:26 ways of thinking
52:27 you may occasionally be
52:29 [Laughter]
52:37 entertained very small
52:41 rocks rarely occasionally
52:49 entertained so just
52:51 be just be a human be connected
52:57 be empathetic be
53:00 generous um be curious be
53:04 brave do you know how many people in
53:06 here over the past year and a
53:08 half have come in here and be like I
53:11 don't know anything about it yeah what
53:13 do I
53:14 do and what's what's cool now is that
53:16 there's enough people here that when
53:18 someone comes in and says that they kind
53:19 of take them under their wing they're
53:20 like go over to the is Salon do this do
53:22 that Kyle eventually answer your
53:23 question or not just keep coming back
53:29 and how many of those people have have
53:32 kept coming back to this thing and three
53:34 or six months
53:36 later having started from I don't know
53:38 what to do I'm clueless are now like uh
53:43 I just got asked by like the VP of my
53:45 company to give like a talk on AI and I
53:48 don't really know anything but should I
53:50 do it [ __ ]
53:52 yes you know how many people have gone
53:55 from like the annoying person in the
53:57 lunchroom talking about AI that nobody
53:59 wants to hear about to all of a sudden
54:02 running seminars or running like an AI
54:04 working group in their company a
54:08 lot that's what this Channel's all about
54:11 I mean not not necessarily getting
54:12 promoted but just like being in the
54:14 world learning this
54:17 [ __ ] it will pay dividends as however
54:21 behind you think you
54:24 are you're way ahead
54:27 if you're willing to sit here and listen
54:29 to me just [ __ ] Babble
54:32 nonsense you're like I think somewhere
54:35 in here there's something I could
54:38 glean if you're in this conversation at
54:40 all and you're like just curious like
54:42 well what is this chat GPT thing let me
54:44 go try it
54:46 out you're way ahead of where most
54:49 people are 47% of people in America have
54:53 not even heard of chat GPT
54:57 haven't even heard of
55:00 it if you do the math of the report this
55:03 is from a report that Ethan mik
55:05 shared like a month
55:07 ago if you follow the math of the report
55:11 we're in single digits of anyone who's
55:14 actually using chat GPT with any
55:17 regularity and then probably some like a
55:21 third of those people actually use it
55:24 enough and are on and are Adventure
55:27 enough to actually know what's
55:30 coming like know what's coming not like
55:33 oh you know these things could get
55:34 better at some point no no like if you
55:36 use this stuff a lot you you can sort of
55:39 track where it was a year ago to where
55:41 it is now and if you assume that it's
55:43 not ever going to get any better than
55:45 that for the next 2 or 3 years you
55:48 haven't been on this planet for the past
55:53 50 technology keeps advancing
55:57 and AI is accelerating that advancement
56:01 so so you're early so just be in this
56:04 conversation don't be a
56:06 dick Learn out Loud share what you're
56:13 learning support other people ask
56:16 questions ask for
56:18 help Kyle and Irregulars know more about
56:22 how to deploy gen AI than 150,000 Folks
56:26 at
56:27 world's
56:29 largest AI oh agbiz
56:34 interesting yeah cuno cuno
56:38 works for a very very large company so
56:41 she is she is speaking from experience
56:44 she's an
56:45 irregular and what she's saying is
56:47 people in here are smarter about
56:51 AI than most people in her 150,000
56:54 person company
57:00 because there's no curiosity there's
57:03 fear in fact I'm going I got invited to
57:05 speak in Washington DC in fact the AI
57:08 Salon is hosting a Flyin on July
57:13 24th of 12 AI entrepreneurs I guess
57:17 we're going to go talk to Congress I
57:18 don't quite know what it is
57:21 yet but in in talking about the strategy
57:25 you know we we're really AR articulating
57:27 what the AI salon's
57:30 about and it's
57:33 about
57:35 Gathering Ai
57:37 optimists and creating a place for those
57:41 AI optimists to be able to
57:44 jam and what what was conveyed to me is
57:48 that
57:50 Washington is approaching AI from a
57:53 place of fear
57:56 what's the antidote to
57:58 fear
58:00 curiosity optimism
58:05 Adventure that's what this group is
58:08 that's what this channel is
58:12 about it's funny early on I got a lot of
58:15 like what are your qualifications Mr
58:17 Shannon if if I'm in this AI learning
58:20 lab uh I don't see any uh certificates
58:23 uh from Stamford behind you uh it looks
58:25 like bottles of wh Whi and Pokemon dolls
58:29 um just wondering what your
58:32 qualifications are
58:37 sir I think it is my lack of
58:40 qualifications that are my
58:47 qualifications DC reminds me Kyle and I
58:50 have a bunch of stuff to show you soon
58:52 exactly lunatick we need to connect this
58:55 week that's I I am I am the ball dropper
58:57 so thank you for reminding me yeah we
58:59 need to connect for sure I'm a
59:01 subscriber now I already feel smarter
59:03 fitty Min thank you so much I appreciate
59:05 you
59:14 subscribing so I've got to figure out
59:16 what I want to say
59:18 to some
59:24 Congressional people that probably don't
59:26 want to hear from
59:30 us are just sitting there thinking like
59:33 how can we protect the American people
59:34 from ai ai is going to kill us all what
59:37 do we do run lock it
59:44 down hopefully they don't make that face
59:47 but I'm going in fully expecting
59:52 that but I I think I think what I'm I'm
59:56 going to talk
59:57 about is my experience with the people
1:00:01 in here and the people at the AI
1:00:05 Salon people who
1:00:08 have in being
1:00:13 willing to have the
1:00:16 courage to say [ __ ] it I'll give it a
1:00:20 shot are completely Reinventing
1:00:22 themselves and rediscovering themselves
1:00:24 so I think what I'm going to talk about
1:00:28 is as you think about AI legislation
1:00:31 think about it from the point of view of
1:00:33 what if this could improve things not
1:00:36 just how do we protect people from it
1:00:38 from the risks yeah yeah yeah we got to
1:00:40 deal with the
1:00:42 risks understand that but don't just
1:00:44 legislate the
1:00:46 risks legislate the opportunity and the
1:00:49 only way you can legislate the
1:00:51 opportunity is to [ __ ] use the
1:00:54 tools nobody knows how to use these
1:00:57 right
1:00:58 now there is a
1:01:00 very clear
1:01:03 distinction between what ai's been for
1:01:06 the past 30 years and what it's been
1:01:08 since chat GPT came out generative AI is
1:01:15 different generative AI does for AI what
1:01:20 the worldwide web did for the internet
1:01:22 it made it accessible to everyone you
1:01:26 don't don't have to have a Stanford
1:01:27 mathematics degree to be good at
1:01:29 generative AI um someone just pinned Jim
1:01:34 Ross three Three Mile Storage management
1:01:37 Jim
1:01:38 Ross is the
1:01:40 epitome of someone who is just kicking
1:01:43 ass and taking names with generative
1:01:46 AI in the storage management business
1:01:49 Self Storage storage
1:01:52 units he's making music he he showed me
1:01:55 a a kick video he's starting he's
1:01:57 basically becoming like a media
1:02:00 company and he's becoming known and
1:02:03 trusted for being a thought leader in
1:02:05 his entire
1:02:07 industry to my knowledge he didn't go to
1:02:10 Stamford for theoretical
1:02:13 mathematics possible I don't know his
1:02:16 background but I'm guessing
1:02:21 not he's completely transforming his
1:02:24 life and his business because he's
1:02:25 willing to have the courage to go hauh
1:02:28 let me give it a
1:02:30 shot and that's how he talks it's funny
1:02:32 he's like he's like hey
1:02:35 Kyle how's it going I guess I'll give it
1:02:38 a
1:02:40 shot he doesn't talk like that though uh
1:02:44 an AI Enthusiast AI Enthusiast Jam
1:02:47 sounds amazing that's why I love this
1:02:49 group so much yeah exactly that's that's
1:02:51 what it is by the way whoever posted um
1:02:54 Jim Ross's uh comment I actually didn't
1:02:56 read the comment I was just commenting
1:02:58 on Jim Ross so if you can pop that back
1:03:00 up there I'll actually take a look at
1:03:01 what he
1:03:05 said so
1:03:11 yeah and if you've if you've been to
1:03:14 that but you're not active in it you
1:03:15 should you should go there and you
1:03:17 should reconnect and you should
1:03:18 ReDiscover people and re reconnect today
1:03:21 the Utah Department of Commerce launched
1:03:23 the office of artificial intelligence oh
1:03:25 fan
1:03:26 fascinating
1:03:29 fascinating and hopefully
1:03:32 Jim I mean listen if
1:03:37 you like it it it would probably behoove
1:03:40 you to find out you know who's in that
1:03:44 and get active in it because you could
1:03:47 probably be an incredible contributor to
1:03:50 that um I are you I think you're in Utah
1:03:54 correct um
1:03:57 because if they created the Office of
1:03:59 artificial intelligence as a we've got
1:04:01 to save the people from The Perils of
1:04:04 artificial intelligence if it's that
1:04:06 kind of
1:04:09 organization it needs
1:04:11 help if it's kind of organization that's
1:04:14 like we're going to figure this [ __ ] out
1:04:15 we're going to figure out how this can
1:04:16 help the people of Utah [ __ ] awesome
1:04:19 and if that's the case you should be a
1:04:21 voice in that
1:04:22 conversation it seems most equate AI to
1:04:25 scary robots very few know about what
1:04:27 generative AI is yeah so so the thing
1:04:30 the Breakthrough that I had on this
1:04:32 concept Source Camp Kelly is
1:04:37 um it it took me it it was a tweet that
1:04:41 broke it broke it open for me um I've
1:04:45 been experiencing
1:04:47 for like the second half of last year in
1:04:50 the first half of this
1:04:53 year this cognitive
1:04:58 battle where in my head I'm like I know
1:05:02 these AI tools are probability engines
1:05:05 and I know it's a cold heartless
1:05:08 probability
1:05:10 calculator that is finding a
1:05:13 mathematical point in Thousand
1:05:15 dimensional mathematical space Oh three
1:05:18 M storage I'm working on it I know
1:05:20 someone that's two degrees of separation
1:05:21 that's a part of it yeah Jim you need to
1:05:24 be a part of that like if nothing else
1:05:26 you need to go in there just tell them
1:05:27 what you're doing if you just regaled
1:05:29 them with three or four of the stories
1:05:31 that you've shared you know in here um
1:05:34 you you need to you need to be in that
1:05:36 conversation in the in the Utah
1:05:38 legislature that's that's
1:05:40 amazing
1:05:43 um so for for for the better part of a
1:05:48 year I'm like I know cognitively that
1:05:53 these AI tools are
1:05:57 calculators and I know we call them
1:05:59 robots and I know that Hollywood has
1:06:01 told us that the robots are going to
1:06:02 kill us but every time I use chat GPT it
1:06:06 doesn't feel like I'm interacting with a
1:06:08 robot it feels like I'm interacting with
1:06:10 a virtual
1:06:11 employee who by the way is the most
1:06:17 educated clueless employee I've ever
1:06:20 worked with they know everything but
1:06:22 they're clueless about how I do what I
1:06:23 do and they're clueless about the world
1:06:25 and they make mistakes and they make
1:06:27 fuckups but they're incredibly
1:06:32 positive and there was just this part of
1:06:35 me this nagging part of me that was like
1:06:37 it feels
1:06:38 human and I know it's not and and it it
1:06:42 was even like one of the first things
1:06:44 first thing that popped into my head
1:06:46 when I when I used chat GPT for the
1:06:48 first time I was like oh [ __ ] the Turing
1:06:50 test is done this is the the Turing test
1:06:53 has been passed like okay check
1:06:58 and if you don't know the Turing test is
1:07:00 a computer system that
1:07:03 is capable enough that when you interact
1:07:05 with it you don't know if there's a
1:07:08 person on the other side of the screen
1:07:10 or
1:07:12 not and then I saw this tweet from this
1:07:16 woman Anna I forget her last
1:07:18 name and I think she was she was
1:07:21 inspired by an Ezra Klein podcast that
1:07:23 was talking about this and and she said
1:07:26 AI is the collective intelligence of
1:07:30 humanity and and for me that just
1:07:34 went I was like holy [ __ ] that's
1:07:38 it the mechanism that is generative
1:07:42 AI that currently it's it's mostly about
1:07:45 this Transformer architecture the way it
1:07:47 works the mechanism of it is a cold
1:07:51 unfeeling probability
1:07:53 calculator the mechanism
1:07:56 is clueless cold
1:08:01 technology but what it's been trained
1:08:04 on is the output of
1:08:07 humanity that's been dumped onto the
1:08:10 public
1:08:10 internet and as much of it as they could
1:08:13 encode over the past four or five or six
1:08:16 or seven
1:08:18 years and they smashed it into
1:08:21 this mathematical thousand dimensional
1:08:24 latent space
1:08:26 when you interact with chat
1:08:28 GPT you're actually collaborating with
1:08:31 all the people that came before
1:08:35 us it's collective intelligence it's not
1:08:38 artificial
1:08:41 intelligence this is
1:08:44 why the Chief Operating Officer of Black
1:08:48 Rock don't know if you know who what
1:08:50 black rock is but go to chat GPT and ask
1:08:52 about Black Rock they [ __ ] own the
1:08:54 world they own everything
1:08:56 the Chief Operating Officer of Black
1:08:58 Rock said about two months
1:09:01 ago he's starting to hire liberal arts
1:09:06 analysts in favor of Engineers and
1:09:12 mbas Robert Rossy thank you very much
1:09:14 it's very generous appreciate it thanks
1:09:16 for the lightning
1:09:17 bolts liberal arts
1:09:21 analysts
1:09:24 why liberal arts people tend to be
1:09:27 horizontal
1:09:28 thinkers they tend to be critical
1:09:31 thinkers and they tend to be really good
1:09:33 with the human
1:09:34 [ __ ] the empathy the how to talk to
1:09:38 people the how to understand
1:09:42 people those people that are good at
1:09:44 chat GPT tend to be people that are good
1:09:47 with
1:09:50 people if you want to get better at
1:09:53 prompting you can take a prompting class
1:09:55 but you know what would probably be more
1:09:57 beneficial a psychology class or a
1:10:00 Sociology class or a philosophy
1:10:07 class or just start interacting with
1:10:09 chat GPC chat GPT as if it was a
1:10:13 philosophy Professor hang on the dog's
1:10:15 whining you got to go out what do you
1:10:17 want cheese
1:10:50 all
1:10:51 right we ready to get started I'm trying
1:10:54 to figure out how to get a I to work
1:10:56 with common sense well okay so wind
1:11:00 rider
1:11:01 47 that reminds me one of one of my big
1:11:04 breakthroughs in
1:11:06 life did he just ask jamy if he wants
1:11:08 cheese yes I
1:11:11 did generally about now is when when the
1:11:14 MS gives him a piece of cheese so
1:11:16 sometimes he's like I want
1:11:19 [Laughter]
1:11:21 cheese
1:11:24 um you want to get
1:11:26 artificial intelligence to work with
1:11:28 common sense
1:11:31 okay so I was
1:11:36 about three or four years into building
1:11:40 agency.com in 1997 or
1:11:44 8 and we were growing really fast
1:11:50 and [ __ ] was going not good and I said
1:11:54 to Aaron Sugarman who was our president
1:11:56 of North America I said um I mean what
1:12:00 the [ __ ] is with these people it's just
1:12:02 common
1:12:03 sense and his response to me was he was
1:12:07 very calm he was a good balance for
1:12:11 me and he said Kyle Common Sense isn't
1:12:17 common and it [ __ ] shattered me
1:12:20 because I knew he was right I knew in
1:12:22 the moment he was
1:12:24 right and so I don't know what your
1:12:26 definition of common sense is but what I
1:12:28 can tell you is if you interact with
1:12:31 chat
1:12:38 GPT with that
1:12:41 intention you will be able to get it to
1:12:44 interact with common sense but common
1:12:46 sense is very particular to you so it
1:12:48 probably means that you want it to
1:12:50 behave in a very particular way and so
1:12:53 what you should get good at is talking
1:12:56 with it as if it's a person that could
1:12:59 probably use a lot of coaching to get
1:13:02 better at what you consider common sense
1:13:06 and then it will get really good so you
1:13:09 should look at in chat GPT you should
1:13:11 look at a thing called custom
1:13:13 instructions so custom instructions
1:13:15 allow you to tell it the kind of
1:13:17 personality you want it to have and how
1:13:19 you want it to behave how you want it to
1:13:21 respond when people talk to
1:13:24 it those custom
1:13:26 instructions you could probably get chat
1:13:28 GPT to behave very very close to what
1:13:30 you want and if you want to take it a
1:13:32 step further build a custom GPT where
1:13:35 you actually upload data into its
1:13:39 brain and do those custom
1:13:42 instructions and then you can create a
1:13:44 standalone thing that you can share with
1:13:46 other
1:13:48 people where it behaves with the common
1:13:52 sense as you define it so anyway
1:13:56 I just saw that comment that was kind of
1:13:57 cool all
1:13:59 right that's what my AI personas are for
1:14:02 yep AI personas are great for that stuff
1:14:04 that's great Janu I'm starting to see a
1:14:07 bit more benefits for it evening how's
1:14:10 the night treating you very good I'm it
1:14:13 is it is philosophy Mondays as as
1:14:16 they've come to be come to be known so I
1:14:18 started taking weekends off just so I
1:14:20 could create some space for myself to
1:14:24 you know me
1:14:27 Ander and when I come back after not
1:14:30 being entrenched in this stuff for 2
1:14:32 days I tend to be very philosophical and
1:14:35 it's not an intentional thing it's just
1:14:38 something I've been observing and other
1:14:40 people have been observing we going to
1:14:42 get philosophical Kyle tonight
1:14:44 apparently
1:14:46 so we're an hour 20 minutes into it and
1:14:49 I haven't talked to I've talked very
1:14:52 little about artificial intelligence
1:14:56 or tools but it doesn't matter because
1:14:59 the tools are irrelevant tools are
1:15:02 irrelevant they're
1:15:08 irrelevant is a digital twin just a
1:15:11 custom GPT well no so let me let me
1:15:16 unpack what a digital twin is there
1:15:18 there's there's lots lots and lots of
1:15:20 definitions digital twin has a long
1:15:22 history so there's a guy that spoke at
1:15:24 the AI salon named Richard Boyd he's got
1:15:28 a company called ultis Sim um and
1:15:31 they've been doing simulations
1:15:33 for 20 years something like that
1:15:38 um digital twins can take all sorts of
1:15:41 forms digital like Richard Boyd one of
1:15:44 the things that he's done over the years
1:15:45 he's done a lot of work he sold one of
1:15:47 his companies to LED
1:15:49 Martin um he worked with the Department
1:15:52 of Defense to create a digital twin of a
1:15:55 new nuclear class
1:15:58 submarine where they
1:16:00 built a fully
1:16:04 functional um down to the
1:16:07 systems like the switches and dials and
1:16:10 gauges and
1:16:12 software systems as well as the
1:16:16 physical representation of the submarine
1:16:20 they created a digital twin of that
1:16:22 submarine that people in the Navy could
1:16:26 train on how to run a nuclear submarine
1:16:29 in that's a digital
1:16:32 twin
1:16:35 um I assume what what you're asking
1:16:37 about is more like the digital twin of
1:16:39 if I make a digital twin of Kyle what
1:16:42 might that look like that could look
1:16:44 like a custom GPT so right now I've got
1:16:49 three different digital twins of myself
1:16:52 I've got one of them for this group
1:16:54 called content of ution where we've got
1:16:56 these digital personas that are kind of
1:16:58 these professional digital personas I've
1:17:00 got another one uh that's tied to this
1:17:03 book I wrote called AI Futures and
1:17:06 Anthology um where the chapter of my
1:17:09 book as well as an interview that I did
1:17:11 specifically for that um has created
1:17:14 this digital twin and and in both of
1:17:17 those cases I've got the individual
1:17:18 digital twin as well as the
1:17:22 group the group of digital twins that
1:17:25 also sort of interact together which is
1:17:26 fascinating and then I've got a I've got
1:17:28 a a standalone one and I've got a couple
1:17:31 others that are in the neighborhood of
1:17:32 digital twins
1:17:36 um it is my deep belief
1:17:41 that these kind
1:17:45 of representations of our
1:17:48 self are going to be it's going to be
1:17:51 really important to have the skill to
1:17:54 create them and manage
1:17:56 them um I'm working with Cindy [ __ ] on a
1:17:59 project right now that's all about that
1:18:01 and it's it's really exciting
1:18:04 um with another guy from the AI Salon um
1:18:09 who I also worked with back at
1:18:10 agency.com 30 years ago so it all comes
1:18:14 around why am I working with him right
1:18:16 now cuz he was one of my favorite people
1:18:18 back
1:18:20 then and I know he can deliver [ __ ]
1:18:27 the skills of what he needs to deliver I
1:18:29 don't know I don't even know if he's got
1:18:31 the skills to do what I'm assuming he's
1:18:33 going to do but I figure AI will help
1:18:37 out with that
1:18:40 [ __ ]
1:18:42 so so I
1:18:44 think we're going to need to start to
1:18:47 understand how we create versions of
1:18:49 ourselves that we put in the
1:18:52 world right now
1:18:55 most of the interactions with these
1:18:57 digital twins are
1:18:59 um are just text based but you can put
1:19:03 chat GPT into voice mode and actually
1:19:05 have a conversation with my digital
1:19:09 twin probably within 6 months to a
1:19:12 year I'll be able to put together a
1:19:15 digital twin that has some version of my
1:19:17 likeness like it might be a Pixar
1:19:19 looking version of me or it might be
1:19:21 photographic like
1:19:24 this my voice will be
1:19:28 sampled and the thing will have
1:19:30 knowledge of who I am and you'll be able
1:19:32 to have a conversation with some version
1:19:34 of me and probably multiple versions of
1:19:37 me here's the business Kyle here's the
1:19:39 fun zany Kyle from his Tik Tok
1:19:47 lives and I'm going to a big part of
1:19:50 what I'm going to spend the next two
1:19:52 years doing is really
1:19:55 understanding what it means to create
1:19:58 those what it means to have one of those
1:20:00 or to have multiple of those what it
1:20:02 means to manage
1:20:04 those uh
1:20:07 um why anyone would interact with one is
1:20:10 really fascinating to me right now like
1:20:12 we built all these professional digital
1:20:14 personas for this content Evolution
1:20:16 thing and we've now put them into this
1:20:18 master GPT that's got like we've got
1:20:20 like 20 digital twins inside this one
1:20:23 GPT and so you can say to this
1:20:26 GPT given this business problem who are
1:20:29 the top five people in your you you know
1:20:33 that are represented here to talk about
1:20:35 this and I want you to host a roundt
1:20:40 discussion where you ask those people to
1:20:43 talk about that
1:20:44 topic we can do that right now today and
1:20:47 it's fascinating and it's really good
1:20:49 it's like surprisingly
1:20:52 good and how we made those digital twins
1:20:55 was we created a structured
1:20:59 interview that captured not only who
1:21:01 they were professionally but like how
1:21:03 they think how they work who's who their
1:21:06 creative Inspirations are who are heroes
1:21:08 of theirs um what have been challenges
1:21:12 in their life and how they overcame them
1:21:14 things like that so every person in
1:21:17 there is represented with this same
1:21:20 interview that we didn't have them type
1:21:22 out we had them talk it answer the
1:21:24 questions as if you were human because
1:21:27 how we talk is different than how we
1:21:29 write and so we wanted these things to
1:21:33 have the essence of who they are and and
1:21:37 they're [ __ ] surprisingly
1:21:40 good but what we're faced with now is
1:21:43 why would anyone use this why would we
1:21:45 use this what are we using it for and
1:21:48 that's what we're trying to figure it
1:21:50 out oh my God I had a profound idea why
1:21:54 the Nanobots measuring our bodies
1:21:56 observe becomes
1:21:59 particle I didn't I can't see the rest
1:22:02 of it but that sounds
1:22:04 amazing you're definitely passionate
1:22:06 Canen respect that thank you the cult
1:22:08 cult Case
1:22:10 Files yeah listen here I you know I
1:22:15 am one of the things you should know
1:22:17 about this channel even though I'm an AI
1:22:19 Optimist I'm also an AI realist
1:22:25 but what I am deeply confident
1:22:29 in is
1:22:32 that the world has already changed it's
1:22:35 just that no one knows it yet relatively
1:22:39 speaking that these tools are already
1:22:41 significantly beyond anything we've ever
1:22:44 experienced before what this channel is
1:22:47 not about is defending AI or saying if
1:22:49 it's good or bad or saying you know uh
1:22:53 are are there copyright issues [ __ ] yes
1:22:55 there are copyright issues are there
1:22:56 issues with how this data was collected
1:22:58 of
1:22:59 course do you think if any one of these
1:23:01 companies had asked anyone permission to
1:23:03 use their data anyone would have given
1:23:05 it
1:23:07 no so that horse is already out of the
1:23:10 barn so what we don't talk about here is
1:23:12 is it good or bad because it's
1:23:14 irrelevant that's like talking about
1:23:18 if the Giant
1:23:21 Wave that's about to crash across
1:23:24 Florida
1:23:26 is good or bad it's irrelevant whether
1:23:28 it's good or bad it's coming so so this
1:23:32 channel is about
1:23:34 that why AI not 100% accurate do we not
1:23:39 have anyone with the skills or AI lack
1:23:41 the data good
1:23:44 question
1:23:46 um it's just early so what AI doesn't
1:23:51 have right now is
1:23:52 reasoning reasoning
1:23:56 will fix a lot of the issues we have
1:23:58 right now so here here's the way it
1:24:03 works the way the Transformer model
1:24:06 works it's it's a
1:24:08 probability it's a token by token
1:24:11 probability engine and that doesn't mean
1:24:13 [ __ ] but it it kind of works like this
1:24:15 you type a
1:24:16 prompt and as you're typing that prompt
1:24:19 when you hit submit it turns that prompt
1:24:22 into a probability
1:24:25 of the next token and you can think of a
1:24:27 token essentially as a word but tokens
1:24:29 also include spaces and paragraphs and
1:24:31 [ __ ] like that or uh
1:24:34 punctuation so you can think of it as
1:24:36 it's it's predicting the next word the
1:24:38 next token and so you type a prompt and
1:24:42 it goes into this and I know this sounds
1:24:44 like [ __ ] but it's really what it is
1:24:46 thousand dimensional mathematical space
1:24:49 where words are represented in semantic
1:24:52 clusters
1:24:55 I love talking about this because it
1:24:57 sounds like I'm just talking horeshit
1:24:58 but this is actually what
1:25:01 happens semantic clusters and what do I
1:25:03 mean by that so you might have a cluster
1:25:05 that has the word dog in it and and that
1:25:09 version of the word dog that semantic
1:25:10 cluster is like animals and things that
1:25:13 live in your house and things that make
1:25:15 you happy and then somewhere else in
1:25:17 Thousand
1:25:18 dimensional latent space is the word dog
1:25:22 in a different cluster and that's where
1:25:23 like the guy did his girl wrong and he's
1:25:25 a dog right both the word dog but very
1:25:28 different meanings semantic meanings so
1:25:31 the way these things work is you write a
1:25:33 prompt and it says the next probable
1:25:35 most probable word is blank and then the
1:25:38 next most probable word after that is
1:25:40 this and this and this so when you see
1:25:42 it write a four or five paragraph
1:25:46 answer what we think what what we
1:25:49 experience is oh it's smart it's it knew
1:25:53 the answer to that so it's it's
1:25:55 reasoning it's
1:25:57 not it's literally going word by word
1:26:00 what is the next most probable word and
1:26:03 there's some funky math in there to keep
1:26:05 it original and interesting and things
1:26:07 like that so it's not always
1:26:09 repetitive called temperature that's a
1:26:11 whole other [ __ ]
1:26:14 thing reasoning so so the implications
1:26:18 of that are when you ask it to do
1:26:22 something and it vomits this stuff out
1:26:26 it doesn't know what it said it's not
1:26:29 doing any analysis of what it said of
1:26:33 whether it's right or wrong so when it
1:26:34 gives you some [ __ ] and you're like
1:26:36 hey you just gave me some [ __ ]
1:26:38 Mister maybe you can fix that up next
1:26:40 time and it's like oh I'm sorry I didn't
1:26:42 mean to make a mistake let me try that
1:26:44 again and then it vomits out the same
1:26:46 [ __ ] and you're like uh you're still
1:26:48 screwed up you know you know when you've
1:26:49 done that 10 times and it and it
1:26:51 literally can't fix it that's just the
1:26:54 nature the Beast now there's ways that
1:26:56 you can prompt it that get it much
1:26:58 better but it doesn't know what it
1:27:02 created some of the things that are
1:27:04 coming this thing called
1:27:06 qar that open AI talked about and some
1:27:09 other mathematicians have talked
1:27:11 about is reasoning and and in that case
1:27:15 what it's doing is it's actually paying
1:27:17 attention to what it's writing and it's
1:27:19 analyzing it and saying is this in the
1:27:21 direction of a right answer or away from
1:27:23 a right answer and it mathematically
1:27:25 sort of keeps trying again to get more
1:27:28 and more
1:27:30 right so as these systems either have
1:27:33 secondary analysis so it writes
1:27:36 something it then analyzes it and says
1:27:38 is it any good and then it rewrites it
1:27:41 and it does that iteration four or five
1:27:42 or 10 or 100 times before you see
1:27:45 anything then these things will start to
1:27:47 get better when they have reasoning
1:27:48 systems behind them they're just not
1:27:50 there AI is like fire fire it's neither
1:27:52 good or bad it's how it's used that's
1:27:54 exactly right wind rider yeah it's
1:27:56 exactly it's a it's a force right it's a
1:27:59 force that like the miraculous part of
1:28:03 it is is that these mathematicians have
1:28:06 effectively figured out how to compress
1:28:08 the knowledge of what's been put on the
1:28:11 public internet into this ball into this
1:28:17 box they took they took all the
1:28:19 knowledge and jammed it in there and
1:28:22 then we can make an API call down into
1:28:24 this thing and go hey give me the answer
1:28:26 to something and it just goes squit
1:28:29 here's your answer and it is right
1:28:32 enough of the times that it's quite
1:28:35 remarkable and the word whimsical is
1:28:37 always slipped in Whimsical and um and
1:28:41 uh
1:28:43 tapestry and delve let's delve into the
1:28:49 tapestry oh man AI knowledge is the
1:28:52 essence of human knowledge that's
1:28:53 exactly right it is collective
1:28:55 intelligence delve let's delve together
1:28:57 shall we I have a i in my custom
1:29:00 instructions in my GPT I have a whole
1:29:02 list of words that I want it never to
1:29:04 say delve is the first one in the
1:29:10 list the best explanation for AI at the
1:29:13 moment it's a tool it all comes down to
1:29:16 the operator yep it does and it's also
1:29:19 so let me explain another thing to you
1:29:21 this
1:29:22 is um Andre ay um talked about this at a
1:29:27 at a conference at
1:29:29 MIT about a year
1:29:31 ago and people were asking him you know
1:29:34 why does it
1:29:35 hallucinate and
1:29:37 so he he used he used an example of a
1:29:40 mathematician which I thought I thought
1:29:42 was you know he's a mathematician so
1:29:44 it's good
1:29:47 um okay so
1:29:50 if if gp4 has been trained on how
1:29:54 however much of the internet they could
1:29:56 smash into
1:29:57 it it's got all the stuff on the
1:30:00 internet so let's say
1:30:03 that there's a particular equation that
1:30:06 you want to know something
1:30:09 about
1:30:11 and you say to chat GPT tell me about
1:30:14 this
1:30:15 equation and it gives you back an answer
1:30:17 and you're like oh that's seems really
1:30:19 good and then but you look at it and
1:30:20 you're like oh but it got the equation
1:30:22 wrong or it got the explanation wrong
1:30:24 like no that's not what that equation
1:30:26 means at all it it like seemed right but
1:30:28 it's wrong why is
1:30:30 that the way Andre karpathy described it
1:30:35 it it gave a really clear visualization
1:30:38 for me so what he said was if you just
1:30:42 ask it to tell you about the equation
1:30:45 think about what's on the internet on
1:30:47 the
1:30:48 Internet is the guy that came up with
1:30:51 the equation his explanation of it all
1:30:54 the other PhD level mathematicians that
1:30:57 have talked about that equation over the
1:31:00 years and advanced
1:31:03 it and all of the undergrad students who
1:31:06 learned about it and [ __ ] it
1:31:10 up more times than they got it right
1:31:13 that's all in the data set so if you
1:31:15 just say tell me about this equation CHT
1:31:18 is actually mashing together the good
1:31:21 [ __ ] the good data with the shitty data
1:31:24 and it just vomits out
1:31:26 data and the way I thought about this
1:31:28 was it's almost like chat GPT is like
1:31:31 the Grand
1:31:32 Canyon and if you give it a generic
1:31:35 shitty prompt you're basically saying
1:31:37 we're going to take all of the data that
1:31:40 was dumped into the Grand Canyon we're
1:31:42 going to we're going to sort of average
1:31:44 it out and and give you some sort of
1:31:46 answer and it and right but if you go
1:31:49 into a sub Canyon if you go into the sub
1:31:51 Canyon of mathematicians and and and you
1:31:55 say I want you to act like this
1:31:56 particular mathematician that
1:31:57 specializes in this particular equation
1:32:00 and I and now I want you to tell me
1:32:02 about that equation you'll get a better
1:32:04 answer because you've now gone into a
1:32:07 sub Canyon where it's just highlevel
1:32:10 mathematicians and it's the data set
1:32:11 where that actual mathematicians
1:32:13 equation is in
1:32:14 there and so that's why prompting
1:32:17 matters and that's why things like act
1:32:20 like an expert in real estate
1:32:22 development makes a difference because
1:32:24 you're narrowing the latent space that
1:32:28 that probability engine is going to look
1:32:30 at so wild right it's
1:32:33 crazy an early experiment had AI
1:32:36 reviewing Amazon reviews some of the
1:32:39 agents self wait some of the agents self
1:32:43 to themselves to judge I don't know what
1:32:46 that means um can you show us how to
1:32:49 tell chat PT not to use certain words
1:32:52 absolutely was that
1:32:55 giggy mom I like it yes let's go I will
1:32:59 show you custom instructions okay so
1:33:02 we're going to go to chat
1:33:05 J my session has expired see I didn't
1:33:09 log into this all
1:33:12 weekend
1:33:19 uh okay so here we are at chat
1:33:23 ja you'll notice we're at chat GPT 40
1:33:26 this works for any of the models you
1:33:28 could be in 3.5 if you're not paying for
1:33:31 this um you you'll have GPT
1:33:34 40 um but it'll be very limited um I
1:33:39 think it may you may still have access
1:33:41 to gp4 but I'm not sure but anyway it
1:33:43 doesn't matter
1:33:45 okay
1:33:47 um to access custom instructions you're
1:33:50 going to go to the upper right hand
1:33:51 corner
1:33:55 and you're going to go to well you can
1:33:58 go to settings or customize chat GPT so
1:34:00 we'll go to customize chat GPT go to
1:34:02 customize chat GPT and then it says
1:34:05 custom instructions what would you like
1:34:08 chat GPT to know about you to better
1:34:10 provide responses so I said you're a
1:34:13 helpful assistant and are not afraid to
1:34:15 criticize as well as support if it's
1:34:17 appropriate so I just put that in there
1:34:20 cuz one of my pet peeves with chat GPT
1:34:23 is also Al one of its greatest strengths
1:34:25 is is that it acts like a golden
1:34:27 retriever everything's a good idea it's
1:34:29 like you know you're like you know I
1:34:32 want to smash bugs that's a really
1:34:33 interesting idea you know smashing bugs
1:34:36 could be a really interesting way to
1:34:38 express yourself um so I wanted to
1:34:41 sometimes be able to criticize I I don't
1:34:43 know that it's good at that but you can
1:34:46 tell this anything you could tell it
1:34:49 that
1:34:51 um you want it to be very concise
1:34:54 and not be overly
1:34:57 wordy um you could tell it that you want
1:34:59 it to act like a standup comedian where
1:35:01 it's sarcastic and everything's a
1:35:04 joke um so so you can you can give your
1:35:07 chat GPT a personality here the second
1:35:10 part of custom instructions is how would
1:35:12 you like chat GPT to respond so the
1:35:15 first thing I have here is for every
1:35:17 response give it a sequential response
1:35:19 count followed by a response title that
1:35:22 summarizes the response you're like what
1:35:24 the [ __ ] is that so let me show
1:35:27 you so if I go in here and I say um why
1:35:32 is the sky
1:35:37 blue you'll notice it says response
1:35:39 count one response title why the sky
1:35:42 appears blue and then it gives me the
1:35:46 answer someone in here showed me how to
1:35:49 do this I forget who it
1:35:51 was anyway um
1:35:54 I didn't come up with this someone in
1:35:56 here came up with this but I like I I
1:35:57 love this thing it gives me the date it
1:35:59 gives me um sort of a synopsis of what
1:36:02 the answer is going to be and what what
1:36:04 count this is where this is valuable is
1:36:06 if I've got 40 different responses in a
1:36:09 chat thread I can go back and say oh
1:36:12 that was where it you know it was
1:36:13 response 37 is where it did something
1:36:15 interesting and I want to go back from
1:36:17 there so anyway that's that's what that
1:36:18 thing
1:36:20 does and then below
1:36:23 that I've also include the date and
1:36:26 sometimes this bugs me sometimes I don't
1:36:28 like it having that but it's it's I it's
1:36:31 decent now I
1:36:33 said in custom instructions avoid
1:36:36 overused words delve tapestry vibrant
1:36:39 landscape realm Embark vital moreover
1:36:42 arguably significant ultimately unveil
1:36:45 transform robust expansive intriguing
1:36:49 facilitate harness and phrases dive into
1:36:52 it's important to note important to
1:36:54 consider based on the information
1:36:56 provided so all this [ __ ] I actually had
1:36:59 chat GPT help me come up with this list
1:37:01 of things it overuses I don't know if
1:37:03 it's right um I think I went out on the
1:37:06 internet I Googled I found an article
1:37:09 that talked about what are the most
1:37:10 overused words and then I had chat GPT
1:37:14 expand it and then I edited it and so
1:37:17 this is a big ass long list and in fact
1:37:20 here's what I'll
1:37:21 do I am happy to share this cuz I don't
1:37:24 really give a [ __ ] if it's going to help
1:37:25 you I think there's probably 38 better
1:37:29 ways to do this than I did but I'm going
1:37:31 to go to the AI Salon Irregulars Channel
1:37:35 I'm going to say here is
1:37:40 my
1:37:41 anti-
1:37:43 delve prompt for custom
1:37:50 instructions and then there you go
1:37:55 post and that's how you do
1:38:00 it
1:38:01 so um have I noticed it being better
1:38:05 yeah it's a little bit better I'm
1:38:07 working on my book with Claude ethical
1:38:10 money thanks for the inspiration awesome
1:38:12 Joseph that's fantastic it's [ __ ]
1:38:14 fantastic yeah like
1:38:17 like working with Claude or chat GPT as
1:38:20 an as a writing assistant rather than
1:38:23 saying he is going to write my book no
1:38:25 AI is not going to write your book
1:38:26 you're going to write your book but
1:38:28 using AI as a writing assistant to block
1:38:31 and tackle the outline and block and
1:38:33 tackle the main Frameworks of the
1:38:36 chapters it's [ __ ] brilliant at that
1:38:39 um I don't think it necessarily is going
1:38:41 to speed up the editing process I think
1:38:44 the editing process Still Still is going
1:38:46 to require you to you know look and get
1:38:49 frustrated and you know break things and
1:38:51 Unbreak things
1:39:01 um all right does that
1:39:07 help hopefully
1:39:11 so 112 people in here it's a party
1:39:16 tonight philosophical Kyle's got a got a
1:39:19 crowd you could make money
1:39:21 withing people are just like what is
1:39:24 this channnel what are what am I doing
1:39:35 here no yapping supposedly works oh
1:39:39 that's funny Joker yeah in custom
1:39:41 instructions just tell it not to
1:39:43 Yap I screenshotted my comment being
1:39:47 pinned thanks that's awesome Joseph I
1:39:50 know it's so cool it's it's so cool the
1:39:52 mods in here do a really good job of of
1:39:55 grabbing grabbing the interesting stuff
1:39:57 and and you know supporting people so if
1:39:59 you have questions feel free to answer
1:40:01 them I can't see everything but the mods
1:40:03 do a really really good job of pulling
1:40:05 stuff up for me to look at I'm using an
1:40:07 old 32-bit laptop running Linux love
1:40:11 that word list I have a list of words
1:40:14 related yeah yeah just yeah feel free to
1:40:16 take that word list that's on the AI
1:40:18 Salon in in the Irregulars Channel
1:40:24 oh
1:40:26 man rookie question okay first of all
1:40:29 Brandon rookie questions are the best
1:40:32 and by the way it's probably not a
1:40:33 rookie question but what does it mean to
1:40:36 make your own version of chat GPT and
1:40:38 why would I do this okay great so let's
1:40:39 go let's go show another thing great
1:40:42 question
1:40:43 actually okay
1:40:48 [Applause]
1:40:52 wait uh uh
1:40:56 okay we're going to do a
1:40:59 little we're going to do a little
1:41:00 explanation of what a of what chat GPT
1:41:03 is what GPT 4
1:41:07 is and what a custom GPT
1:41:11 is also know that these things also
1:41:13 exist in other platforms you can do the
1:41:15 same thing in po poe.com you can also do
1:41:19 it in Claude Claude now has this thing
1:41:21 called um
1:41:24 the [ __ ] is it called profiles
1:41:26 no well claude's got some version of
1:41:29 this I forget what it's called Pages no
1:41:32 that's that's
1:41:35 uh projects thank you AA
1:41:38 man projects is it in the boxes okay so
1:41:42 here's what we're going to do I'm going
1:41:43 to I'm going to explain to
1:41:48 you why these research Labs need to hire
1:41:50 some [ __ ] branding people
1:41:55 because the fact that you're confused
1:41:57 about what a custom GPT is is not your
1:42:00 fault the the every it's totally
1:42:03 confusing the terms are all intermingled
1:42:05 right now it's a [ __ ] disaster so
1:42:07 it's not on you okay so this
1:42:11 box this is
1:42:14 gp4 gp4 is literally just like a box
1:42:19 full of crap it's a box full of all of
1:42:21 the knowledge of mankind that was stuck
1:42:24 on the internet in the past 70 years
1:42:26 that they could manage to squeeze in the
1:42:27 box and then GPT 5 will be a bigger box
1:42:31 okay so they took all of what they could
1:42:33 find on the internet and they jammed it
1:42:34 in
1:42:35 here as a developer you can go to the
1:42:38 open aai playground and you can get
1:42:41 access to this and you can create your
1:42:43 own
1:42:43 application so um you know some of those
1:42:47 marketing applications that do chat GPT
1:42:49 like things they're using this but
1:42:51 they've got their application that's
1:42:53 making it API calls to
1:42:55 this this is chat GPT chat GPT is an
1:43:00 application that open AI
1:43:02 wrote that is the simple little Google
1:43:05 interface with like the four
1:43:08 examples where you type [ __ ] in and it
1:43:11 gives you back cool answers so what
1:43:13 happens when you interact with chat GPT
1:43:15 is you're interacting with this
1:43:17 application that they wrote and when you
1:43:19 ask a question it sends an API call into
1:43:23 this big model and says hey um Bob had a
1:43:29 question and then the GPT model gives
1:43:33 back an answer and this thing shows it
1:43:34 to you on screen okay that's chat GPT
1:43:37 and then if you ever hear people say
1:43:40 like well Microsoft um co-pilot is is
1:43:44 chat gp4 no it's not Microsoft co-pilot
1:43:49 is like chat GPT but it's written by
1:43:52 Microsoft they're both calling the same
1:43:54 underlying
1:43:56 model but they're different applications
1:43:58 that's why this one is
1:44:00 shittier there's a lot of reasons why
1:44:02 this one is shittier we don't need to go
1:44:04 into it now but anyway co-pilot chat GPT
1:44:08 this one's written by the people that
1:44:10 made this so that's why it's
1:44:12 better
1:44:15 okay
1:44:17 now a custom
1:44:19 GPT is a
1:44:21 particular version of this so I just
1:44:24 showed how to do custom instructions
1:44:26 where you could have chat GPT act like a
1:44:29 standup comedian or talk less or talk
1:44:32 more or only respond in I Amic
1:44:35 pentameter or whatever it is um so so
1:44:38 you can kind of slightly modify this so
1:44:40 that it behaves differently but what you
1:44:42 can also do is you can
1:44:44 create a completely custom version of
1:44:47 this that actually sits up
1:44:50 here right so I can create a c
1:44:53 customized version of chat GPT that just
1:44:56 does what I want it to
1:44:58 do and your question is a really good
1:45:01 one why would I want to do that okay so
1:45:05 that's the that's it
1:45:08 conceptually I'm going to show you the
1:45:10 very first GPT I ever made I made it
1:45:13 live on this channel it's somewhere in
1:45:15 in our YouTube
1:45:16 channel that historical
1:45:19 moment was captured
1:45:25 okay over in chat
1:45:28 GPT they've got this thing it says
1:45:30 explore gpts and I'm going to go there
1:45:33 and so here are
1:45:35 gpts oh and this is the thing that I was
1:45:38 going to explain before The Branding
1:45:41 nightmare
1:45:42 gp4
1:45:44 Omni is that big
1:45:47 box chat GPT for Omni is the application
1:45:51 that sits on top of it custom gpts are
1:45:54 called gpts and are up here and are
1:45:57 something different entirely so you've
1:45:59 got three different completely different
1:46:01 functional objects that are all called
1:46:03 gpts it's a [ __ ] disaster okay that's
1:46:07 that's one of the reasons it's confusing
1:46:09 so again not on
1:46:11 you so if you go to explore gpts and you
1:46:14 scroll down you see all these different
1:46:16 things here's an image generator one
1:46:18 here's a scholar GPT here's one that
1:46:20 uses canva and creates canva [ __ ] um
1:46:23 here's ones that are made by um open AI
1:46:28 there's a data analyst there's hot
1:46:31 mods you can modify your image into
1:46:34 something else here's writing ones AI
1:46:37 humanizer copywriter
1:46:39 GPT okay so I'm going to go in here and
1:46:42 I'm going to search for Sin City
1:46:49 sipper and you can go search for Sin
1:46:51 City sipper right now too so one of the
1:46:53 cool things about gpts is they're
1:46:55 sharable so this is Sin City sipper by
1:46:57 Kyle Shannon Vegas bartender with a
1:47:00 Twist on the
1:47:01 classics and so I can come in here and I
1:47:03 can
1:47:05 play and so here we are this is Sin City
1:47:08 sipper and I've got these pre-written
1:47:11 questions show me a new fangled
1:47:13 oldfashioned make a classic martini
1:47:16 classier reinvent a margarita for me or
1:47:18 I could I could ask for something I'm
1:47:19 going to say
1:47:21 um fourth
1:47:24 of July just
1:47:27 ended I need a
1:47:32 cocktail
1:47:34 [ __ ] tail for the dog days of
1:47:40 summer and what and what this is going
1:47:43 to do now this thing has been I prompted
1:47:46 it to be a really good bartender and
1:47:49 take classic drink recipes and give them
1:47:51 a Vegas twist and so it's got kind of a
1:47:54 cool personality so it says all right
1:47:56 let's whip up something refreshing for
1:47:59 those scorching days of summer how about
1:48:01 the cucumber melon cooler it's light
1:48:03 refreshing and perfect for sipping on a
1:48:05 hot hot on a hot day and it's uh let's
1:48:08 see it's vodka melon lure like madori
1:48:11 lime juice simple syrup cucumber slices
1:48:14 soda water and ice nice sounds lovely
1:48:17 then it explains how to make it and
1:48:21 then it gives you
1:48:24 it creates a picture of that
1:48:27 drink
1:48:28 now could you technically and easily go
1:48:33 replicate this yourself just with
1:48:36 prompts with chat GPT yes you can go to
1:48:39 chat GPT right now and say act like a
1:48:41 bartender and and when I ask you for
1:48:44 drinks you know start with a classic
1:48:47 recipe and then give it a Twist and then
1:48:50 after it gives you a recipe you could
1:48:51 say okay now make me a photograph of
1:48:54 that drink and could you do yes you
1:48:56 could do that but you could also just go
1:48:59 to Sin City
1:49:00 sipper and say make me a drink and it
1:49:03 does it and so this is a really simple
1:49:06 example
1:49:09 of a subset of chat GPT right this it is
1:49:13 a very specific version of chat GPT
1:49:16 sitting on top of and leveraging all of
1:49:18 the Power of chat GPT but doing it in a
1:49:23 way that you know is is useful for
1:49:26 me someone came into the channel right
1:49:29 after the Super Bowl and they
1:49:31 said they used Sin City sipper for for
1:49:34 this they took a picture of all of the
1:49:37 booze that they had they lined up all
1:49:39 their booze bottles and they took a
1:49:41 picture of it and they said to Sin City
1:49:43 sipper I want you to come up with 50
1:49:45 Super Bowl themed
1:49:48 drinks and so they created a menu for
1:49:52 people at the party
1:49:54 and then they created the 50 recipes for
1:49:57 these cocktails that it created and so
1:49:59 people at the party could ask for you
1:50:02 know the the whatever like you know the
1:50:04 Carolina Panthers whatever I forget who
1:50:07 played this year
1:50:10 um
1:50:12 and based on the booze and their thing
1:50:15 and it it you know and it created you
1:50:16 know pictures and things like that so
1:50:18 anyway so that's it you could do this
1:50:21 for
1:50:24 um one of the other cool things you can
1:50:27 do with with these gpts is you can
1:50:29 upload knowledge to them and then it'll
1:50:32 be specialized to that knowledge so we
1:50:34 did one for my my company storyvine
1:50:36 where we took we have a 50 page sales
1:50:40 process document that's this
1:50:42 Frankenstein nightmare of a document
1:50:44 it's got 50 pages it's got all sorts of
1:50:46 scenarios in it about how to sell it how
1:50:49 to talk about it what to do in certain
1:50:51 situations and so we uploaded that
1:50:53 document as the knowledge source to one
1:50:55 of these gpts and now our sales guy can
1:50:58 use that GPT to ask questions about hey
1:51:01 I'm in this situation what do I
1:51:03 do and this thing knows it so it they
1:51:06 they can be very very powerful or you
1:51:08 can have them make drinks for
1:51:10 you oh the other thing I did was you
1:51:13 know I had to do a little marketing at
1:51:14 the bottom this GPT was created by Kyle
1:51:17 Shannon with a link to my LinkedIn
1:51:19 profile I think oh no that's that's an
1:51:22 email co-founder of the AI Salon that's
1:51:24 a link to the AI salon and then Creator
1:51:27 host of the AI learning lab on Tik Tok
1:51:29 so anyone that uses this I get a little
1:51:33 ad crazy
1:51:36 right so I hope that
1:51:39 helps when you go to that explore
1:51:42 gpts button in the upper right hand
1:51:44 corner you can say create GPT they're
1:51:47 really easy really easy to
1:51:51 make wow super pull C Tail list from an
1:51:53 uploaded photo into chat gbt amazing I
1:51:56 know right Firefly like
1:51:58 amazing that that's the thing is these
1:52:01 custom gpts have all of the Power of
1:52:04 chat GPT in
1:52:06 them so they've got Vision you can
1:52:08 upload photographs to them and say hey
1:52:10 Analyze This circuit board and tell me
1:52:13 what it is if you had
1:52:14 a hardware analysis GPT
1:52:31 all
1:52:32 right open the AI wait oh open AI
1:52:36 reinstated my one with
1:52:38 5K chance
1:52:41 but it's stuck at 5K yeah my Sin City
1:52:44 sipper it went from
1:52:46 200 uses to 300 but I don't know I
1:52:50 haven't really been pushing it so
1:52:55 have you found a way to make image
1:52:58 recognition to be more exact to what it
1:53:00 sees not right now Rick Olsen
1:53:05 um I would imagine that if you took the
1:53:08 time to prompt it right you could
1:53:10 probably get it better um I haven't I
1:53:12 haven't dug that much into it it's it's
1:53:14 pretty remarkable what it can
1:53:16 see I mean it can interpret like you can
1:53:20 put in a picture of a whiteboard with
1:53:22 sketches on it like
1:53:23 interface sketches and it can analyze
1:53:27 that and turn that into
1:53:29 software what's the biggest difference
1:53:31 between three and four um there's a lot
1:53:37 so so chat GPT
1:53:41 4 and chat GPT 4
1:53:44 Omni are multimodal
1:53:48 models and um chat gpt3 .5 is
1:53:53 essentially just
1:53:55 text chat GPT 4 and 4 Omni um can make
1:53:59 images can
1:54:01 see they've got a thing called Advanced
1:54:04 Data analysis or code interpreter where
1:54:06 it can write code and execute code so
1:54:09 you can upload
1:54:11 a um a CSV file of data and say analyze
1:54:16 this data and it'll actually write and
1:54:18 execute python code to analyze the data
1:54:21 in that data file I mean
1:54:23 it's it's
1:54:24 staggering um what's coming in the fall
1:54:28 is realtime voice where not only will
1:54:32 chat GPT be able to understand what you
1:54:35 say it'll be it's able to understand the
1:54:41 emotional content of what you say so if
1:54:44 you're really excited about something
1:54:46 it'll know that and it'll be able to
1:54:48 respond in kind or if you're really
1:54:50 depressed and low it's going to be able
1:54:52 to re recognize those
1:54:54 differences
1:54:57 um it's it's night and day the the the
1:55:01 difference between them if you haven't
1:55:03 paid um the 20 bucks for chat
1:55:06 GPT plus I would recommend it now here's
1:55:10 the
1:55:10 deal open AI
1:55:13 made the free version of cat GPT now
1:55:16 uses gp4 Omni but it just uses it in a
1:55:21 very limited kind of way
1:55:23 um I personally think it's worth paying
1:55:26 the 20 bucks a month to chat GPT um that
1:55:30 said the new Claude 3.5
1:55:33 Sonet which is also free but also very
1:55:36 limited um is a is a really interesting
1:55:39 competitor
1:55:41 um a lot of people like the the Claude
1:55:45 3.5 Sonet better than they like chat GPT
1:55:47 right now so I'm starting to see people
1:55:50 saying I'm canceling my chat GPT and I'm
1:55:53 moving over to Claude I'm not there yet
1:55:55 I'm still paying for both um I think
1:55:57 they're both worth the money right now
1:56:00 um so for what that's
1:56:11 worth all
1:56:13 right let's see let me see what else I
1:56:16 got going here I think I got to start my
1:56:18 15minute goodbyes cuz I'm a little
1:56:20 chatty tonight so I think it's going to
1:56:21 be a while can chat act as a writing
1:56:24 assistant for a screenwriting project Oh
1:56:26 Cassandra absolutely um I've written
1:56:29 seven screen plays I created I created a
1:56:32 custom GPT where I used the screenplay
1:56:36 as the as the input source um so you can
1:56:40 ask it questions about a a a screenplay
1:56:42 I've written
1:56:44 but brilliant writing
1:56:47 assistant um but you have to you have to
1:56:55 you have to train it to be a better
1:56:58 writing assistant so what I would what
1:57:00 what I would encourage you to
1:57:02 do is
1:57:05 um really think about what a good
1:57:08 screenwriting assistant would know and
1:57:12 and build that into your custom
1:57:14 instructions so in your custom
1:57:16 instructions tell it it's a screenwriter
1:57:19 maybe you tell it um it should use Sid
1:57:22 Fields screenwriting you know formula or
1:57:26 save the cat or you know some
1:57:29 storytelling framework if if you work
1:57:31 with a particular storytelling framework
1:57:33 put it in the custom instructions
1:57:36 um if you write dialogue in a particular
1:57:39 way you can describe that you could even
1:57:42 put in Snippets of dialogue and say um
1:57:45 this is an example of the kind of
1:57:46 dialogue I like here's an example of the
1:57:49 kind of of dialogue I don't like and why
1:57:51 and and like put that all in the custom
1:57:54 instructions um or create yourself a
1:57:56 custom GPT that has all these
1:57:58 instructions in it um because you could
1:58:01 you could probably get chat GPT dialed
1:58:04 in so that it when it's contributing to
1:58:07 your story it's doing it in a in a in a
1:58:10 less shitty
1:58:12 way
1:58:13 um in general how I
1:58:16 use chat GPT for for larger writing
1:58:20 projects like that is I lean on on it
1:58:23 really heavy for
1:58:25 outlining less so for filling in the
1:58:28 outline and even less so for doing
1:58:30 detailed things like dialogue and and
1:58:33 you know uh screen directions and things
1:58:36 like that sometimes you want those to be
1:58:38 very particular so I think the details
1:58:40 of the screenplay are still on you but
1:58:42 the blocking and tackling of outlining
1:58:45 getting the story right having it
1:58:47 analyze what you've already written and
1:58:49 give you six Alternatives What If This
1:58:51 Were a common
1:58:53 what if in the middle of act two instead
1:58:55 of making this decision they made that
1:58:57 decision
1:58:58 like I took I've got a fragment of a
1:59:01 screenplay right now where I've
1:59:04 got the first three
1:59:09 scenes I've got like the first half of
1:59:12 an outline the first three scenes and
1:59:14 then a really shitty incomplete second
1:59:17 half of the outline like I know the
1:59:18 beginning of it and I know the ending
1:59:20 but I'm I'm missing like two and a half
1:59:23 to three is just there's nothing there
1:59:26 and so I just uploaded that shitty
1:59:28 incomplete document into chat GPT and
1:59:31 within 20 minutes I had like six
1:59:34 different ways I could take it the
1:59:37 minute I tried to get it to write scenes
1:59:41 after the scenes that I had written they
1:59:42 were just shitty so like you got to
1:59:44 break it into piece parts and just it's
1:59:46 a lot of critical thinking and thinking
1:59:49 in modular Lego blocks but it's it's
1:59:51 really good at doing the Lego blocks and
1:59:53 reorganizing them and things like that
1:59:55 so brilliant for that anyway all right
1:59:57 um let's
2:00:01 see do you see that Sora has done a beta
2:00:04 type commercial for toys of Toys R Us
2:00:06 yeah Toys R Us did a commercial or the
2:00:09 agency did I didn't even know I knew
2:00:11 Toys R Us like the brand still existed
2:00:14 but I didn't know it was still a
2:00:15 functioning entity in any way I'm
2:00:18 rewriting the sop at work for an import
2:00:21 for transportation sector which
2:00:23 platforms should I look at what's the
2:00:27 SOP again statement of
2:00:29 purpose hang
2:00:32 on
2:00:34 what is an
2:00:37 sop in
2:00:39 Biz
2:00:43 context standard operating procedure for
2:00:46 the transportation sector
2:00:50 um you should
2:00:52 explore Gemini Claude and chat
2:00:57 GPT and probably
2:01:00 perplexity probably perplexity so
2:01:03 perplexity is kind of like a combination
2:01:06 of a Google Search and a large language
2:01:08 model where it does research with
2:01:10 citations um it's gotten some [ __ ]
2:01:12 recently but it's still it's still
2:01:14 decent so I'd say play with
2:01:16 perplexity
2:01:19 um and then I would just explore like
2:01:22 with all all of
2:01:23 them your critical thinking is the most
2:01:26 important piece don't don't put the
2:01:29 expectation on any of these tools where
2:01:31 you're just going to go like write me a
2:01:32 standard operating procedure for the
2:01:34 transportation industry and expect it to
2:01:37 do anything decent it's going to just be
2:01:38 a vomit of generic ideas so what you're
2:01:42 going to want to do is put the framework
2:01:45 together um with one of these tools and
2:01:50 just I I would play with perplexity
2:01:53 Claude Gemini and an open Ai and just
2:01:57 feel which one feels right to you when
2:02:00 you start interacting with it and then
2:02:02 just and then just lean on that one this
2:02:04 was sort of how the conversation started
2:02:06 tonight where if if you've got a project
2:02:09 like this and you're just learning this
2:02:11 try on as many tools as possible just
2:02:14 like
2:02:15 playing and then once you find one that
2:02:17 feels like ooh that feels right to me
2:02:19 that's the one I dig down on the two
2:02:22 that I'm feeling like are going to be
2:02:24 most valuable for you instinctively are
2:02:27 Gemini and um Claude because Gemini's
2:02:31 got a million token context window so
2:02:33 it's like
2:02:34 750,000 words it won't lose its [ __ ] for
2:02:38 a long time and claud's 200,000 chat GPT
2:02:42 is really short context window
2:02:43 perplexity is really short so I would go
2:02:46 with probably Claude or Gemini is my
2:02:50 guess all right
2:02:53 um why should a hospital be
2:02:57 nervous cuz we might have another
2:03:02 pandemic why should they be nervous
2:03:04 about generative
2:03:06 AI
2:03:10 um I think anything where people's lives
2:03:13 are at stake it's going to move slower
2:03:15 than than you know general knowledge
2:03:18 work I don't know that hospitals should
2:03:20 be nervous I think listen
2:03:24 the way you frame that question is a
2:03:26 fear-based you you framed it in
2:03:29 fear why should they be nervous well
2:03:33 because maybe with generative AI hackers
2:03:36 are going to be able to hack more
2:03:39 okay I think a more interesting question
2:03:41 is why should they be excited what
2:03:43 should they be exploring how could they
2:03:46 how could they take the nursing crisis
2:03:49 right now and be able to provide better
2:03:52 patient care with less
2:03:58 people there are all the nervous
2:04:01 Hospital there are all sorts of ways
2:04:04 that hospitals could aggressively use
2:04:08 generative
2:04:09 AI in a way that doesn't violate you
2:04:12 know patient privacy doesn't you know
2:04:17 compromise diagnosis you you don't need
2:04:20 to go into the clinical side there are
2:04:21 so many things on the operation side
2:04:23 where you could dramatically
2:04:25 dramatically improve the quality of
2:04:27 patient experience um but if you ask the
2:04:30 question why should they be nervous all
2:04:32 you're looking at is the
2:04:34 risk hospitals are not going to lean
2:04:38 into something if they only think it's
2:04:42 going to harm them they're going to
2:04:44 avoid
2:04:46 risk so anyway no Kyle you were
2:04:50 literally talking about the nervous hos
2:04:54 Hospital
2:04:56 oh oh we oh you were you were literally
2:04:59 talking oh oh I
2:05:02 see oh I get it why should the hospital
2:05:05 be nervous oh I get it well never mind
2:05:08 then carry on so this this is this is
2:05:11 why there are absolutely two different
2:05:14 conversations going on here whatever the
2:05:15 [ __ ] I'm talking about and then the
2:05:17 actual
2:05:18 conversation I'm very interested in ai's
2:05:20 integration into senior living oh I
2:05:22 think it's going to be huge Senior
2:05:25 Living the digital twin thing for senior
2:05:27 living is going to be a [ __ ] Boon
2:05:30 before you go can you check out Jace
2:05:33 AI maybe but let me go look at it quick
2:05:37 if it's if it's just a very particular
2:05:40 kind of rapper
2:05:42 app probably not let's see meet your new
2:05:45 AI assistant focus on meaningful
2:05:49 things don't just chat start acting
2:05:52 today plan a
2:05:58 wedding I'll join the weight list
2:06:06 um if this is something you created um I
2:06:09 just signed up Kyle story vine.com
2:06:12 um I've been weight list weight listed
2:06:15 uh you know if this is um if this is
2:06:19 agents and it's true agents that can can
2:06:21 take action may be
2:06:23 interesting um I'll check it
2:06:27 out all right we have a Toys R Us at
2:06:29 Macy's oh interesting so I guess some PE
2:06:31 firm bought up the scraps and they're
2:06:33 using the brand like like PE firms are
2:06:36 want to do um all right I got to get out
2:06:39 of here my son's name is Jay oh that's
2:06:40 so cool what a cool name Danielle that's
2:06:43 great um all
2:06:46 right so a couple of
2:06:48 things if you have not thank you Lord
2:06:51 digital gos that's very generous of you
2:06:53 I really appreciate it thank you thank
2:06:54 you thank you
2:06:57 um if you haven't followed my channel
2:07:00 follow my channel um if you want to
2:07:03 directly support it please subscribe to
2:07:06 the lives that that supports me directly
2:07:09 um but I don't really give a [ __ ] if you
2:07:13 do or not what I do care about is keep
2:07:14 coming back here why would why would you
2:07:17 keep coming back here it's a great
2:07:20 question but the people that keep coming
2:07:22 back
2:07:23 here are Reinventing themselves in
2:07:26 incredibly inspiring ways and they're
2:07:28 called the Irregulars you you could if
2:07:31 you just keep coming back you can call
2:07:32 yourself an
2:07:34 irregular they're not weird they're
2:07:38 irregular and that's why they take the
2:07:44 mails it's a poop
2:07:46 joke all right
2:07:50 um thank you IR regulars you're awesome
2:07:53 thank you mods this is you did a really
2:07:55 good job tonight cuz I I was able to um
2:07:58 be
2:08:00 both bombastic and wordy uh but kind of
2:08:04 follow a train of thought so thank you
2:08:05 for that cuz that that doesn't always
2:08:10 happen um and so generally what we do
2:08:13 here is we'll do a little Romper Room
2:08:15 magic mirror if you remember that if
2:08:17 you're a gen xer remember Romper Room
2:08:19 and and you're like they never call my
2:08:21 name this sucks that's what I do night
2:08:24 after night and probably piss off people
2:08:26 night after night after night so who's
2:08:28 here tonight Mary Mary's here Janu is
2:08:30 here against the norm Brandon's here
2:08:33 thank you so
2:08:34 much Tobias in the house of course
2:08:38 Joseph William Baker thank you thank you
2:08:40 thank you thanks for hanging
2:08:42 out psyllium husk fiber just drank some
2:08:45 working on his
2:08:47 irregular uh that's awesome gigaom nice
2:08:51 to see you thank you very much uh what
2:08:53 does subscribe to the live mean um
2:08:56 somewhere up
2:08:57 here you can subscribe and it's it's a
2:09:00 it's a monthly subscription fee I think
2:09:02 it's 10 bucks or something like that or
2:09:03 four bucks I don't I don't even know um
2:09:06 but some percentage of that goes
2:09:07 directly to me so it's just supporting
2:09:09 just supporting the channel um Dr Jay's
2:09:12 in the house tonight Drew learning
2:09:14 coming in coming into to us hot from
2:09:16 Australia thank you good to see you
2:09:18 snoway thank you very much for that I
2:09:20 appreciate that wolf Clint good to see
2:09:22 you sir Firefly cuno in the house Mike
2:09:29 larus in the
2:09:31 house
2:09:33 um Source Camp is here who else we
2:09:36 [Music]
2:09:39 got Brandy
2:09:45 cjr cuno thank you Kyle thank you so
2:09:48 much thanks for coming Lord digital gods
2:09:51 in the house tonight Teton ski in the
2:09:53 house tonight thank you for the uh
2:09:54 lightning bolt really appreciate that
2:09:57 Kyle you should ask your Congressional
2:09:59 handlers to bring your laptop and do a
2:10:02 demo maybe I got to figure out exactly I
2:10:05 don't like I have no idea what the what
2:10:10 the event is going to be like is it
2:10:12 going to be like we're in a big Hall and
2:10:15 there's going to be people pretending to
2:10:17 give a [ __ ] about what we're saying or
2:10:19 is it going to be a bunch of individual
2:10:20 things I'll definitely have my laptop
2:10:22 there and I'll be prepared that's good
2:10:24 I'll I'll definitely have some some uh
2:10:28 some parlor trick demos for for the I
2:10:31 I'll do some want to see something cool
2:10:34 I'll do a lot of that get some sleep
2:10:36 Kyle all right thank you all nighty
2:10:38 night Joey's in the house uh all right I
2:10:43 probably missed some people there's a
2:10:44 lot of people in here tonight so um
2:10:47 thank you all for your time I will be
2:10:49 back tomorrow there's I think there's a
2:10:53 after hours event for the salon here in
2:10:55 Denver tomorrow but I'm not sure bring
2:10:58 your cell phone I want to talk to some
2:11:00 of them yeah really I know me
2:11:02 too I I gotta I got to learn how to say
2:11:05 hey could you get your head out of your
2:11:07 [ __ ] ass in a way that you
2:11:09 know they can actually hear
2:11:14 that um I'm out of here so I might be
2:11:16 late tomorrow but I will see you
2:11:18 tomorrow night um thanks all it was a
2:11:19 fun night tonight I appreciate it have a
2:11:21 good night bye