3/19/2025 - Exploring the Power of Notebook LM: Mind Maps and Vibe Coding

Description

Chapters

Transcript

0:01 boy you ready for some singing
0:04 [Music]
0:46 his place that ra
0:53 my together my thoughts and sweet
0:56 silence
1:08 place
1:09 anure to
1:12 Val this is place I can slowly face the
1:17 only one I truly can
1:21 know these are tears from a
1:26 long tears from a long time ago
1:30 to cry
1:33 years these are tears from a long
1:41 [Music]
1:47 time well oh darling Oh Darling you say
1:52 unto
1:53 [Music]
1:56 me where have you been all my life time
2:04 I have been swimming Seven
2:10 Seas women have TOS me their
2:14 lifelines I pull them the in them but I
2:20 didn't
2:22 know these are tears from a long time
2:26 ago got these tears from a long time
2:31 go I need to cry 30 years or
2:36 so these are tears from a long
2:43 time go
2:53 [Music]
3:03 good day good people tiktock pin hey
3:05 Kyle saw the new podcast with an thank
3:07 you very much Tom yeah the AI Readiness
3:12 project we're starting to get our C legs
3:14 a
3:15 bit in in a typical Kyle Shannon and an
3:19 Murphy style we uh came up with the idea
3:22 to do that and launched it I think eight
3:24 days
3:26 later so I think today was our fourth
3:29 episode and it was a fun one it's fun
3:32 one it's
3:34 good all right let me let me flip the
3:37 cams here for you Tik Tock
3:41 folks so you can see
3:44 the splendid
3:47 glory of the
3:50 show oh man
3:56 [Music]
4:13 there's been something baby I've been
4:15 trying to
4:19 say for an age and it seems I don't know
4:22 [Music]
4:25 how the past and the future now
4:28 surrounding me
4:32 surrender to whatever Tre there can be
4:37 found there's been little
4:39 [Music]
4:40 trouble since you came to my
4:44 [Music]
4:48 rescue and if you like all of the rest I
4:51 would have quit you long ago but I
4:55 couldn't do that
4:57 [Music]
5:00 oh tell me now women and wi never went
5:05 to
5:06 [Applause]
5:07 well make a man crazy make him cold as
5:12 [Applause]
5:14 hell I a woman you wish me
5:19 well but in spite of your
5:21 try still going to have to
5:24 find own way
5:27 through yeah
5:30 [Applause]
5:31 oh man all right Little Women and wine
5:35 Martin
5:36 ston
5:38 um y we had a good show with an today
5:41 you know talking about AI Readiness AI
5:44 Readiness man that's where that's where
5:45 it's at LinkedIn put out a new jobs a a
5:49 job skills for
5:52 2025 the top skills for
5:58 2025 one of the skills was AI literacy
6:03 which again I would argue it's
6:05 impossible to be AI literate right now
6:08 because things are moving too fast but
6:10 you can be AI ready and so I'll I'll
6:13 give them I'll give them some credit for
6:15 that one being number one but they had
6:17 they had two of the other ones that they
6:19 had skills they they defined these as
6:22 skills one of them was
6:25 adaptability I don't see adaptability as
6:28 a skill I see adaptability as an
6:30 aptitude I see adaptability as a
6:33 personality
6:36 trait if you're lucky enough to to to
6:41 be to
6:44 embrace
6:48 change um you're going to do good if you
6:52 like predictability and structure and
6:55 you're a little
6:56 rigid you're going to be miserable
6:58 that's not a skill now now can you
7:00 practice being more adapt adaptable
7:04 sure
7:06 uh you know uh whenever you think you've
7:10 got something figured out change
7:15 it uh and then the other one that they
7:17 had one was adaptability and then the
7:19 other one was basically critical
7:21 thinking I think they called it creative
7:24 creative something or I don't know but
7:27 it was basically critical thinking which
7:29 again
7:32 if you're a critical thinker if you're
7:33 someone who defaults to let's talk about
7:35 this let's think about this but many
7:37 people are like tell me what to do I'll
7:39 go do my job
7:41 so so they had some good it was some
7:45 interesting things in the list those
7:47 three stood out to me as a little a
7:50 little unthought
7:52 [Music]
7:54 out uh I don't think they're wrong
7:56 though
7:58 [Music]
8:03 I mean can you take a class on
8:04 adaptability I guess you could
8:10 [Music]
8:31 who on LinkedIn it was a it was one of
8:34 those sponsored
8:36 posts by
8:38 um
8:41 workday hang on let's see um
8:47 2025 job skills I
8:51 think is what it
8:53 was yeah here it is skills on the rise
9:03 [Music]
9:09 there we go you can see
9:13 that
9:18 um so sponsored by workday so right so
9:21 you've got to discount it as you know
9:22 this is this is just a little content
9:24 fluff but AI literacy why it's on the
9:27 rise is AI rapidly trans forms
9:30 Industries company are increasingly
9:32 looking for professionals with the
9:34 ability to understand and U utilize
9:38 tools
9:40 harnessing that technology for business
9:42 purpose that technology harnessing that
9:45 technology which technology generative
9:48 AI That's like 400 Technologies which
9:52 one and they're like most common
9:55 Industries Tech and internet higher
9:57 education IT services
10:01 Consulting most common job title
10:04 software engineer no this is every
10:06 [ __ ] job in every [ __ ] industry
10:11 right it's like come on this is way
10:16 bigger than like the fact that they
10:19 wrote this in this way is kind of like
10:22 it says to me companies for a good long
10:26 time probably a year or two are going to
10:29 do what they they did with the worldwide
10:31 web ah the IT department will figure
10:34 that out let the IT department we've got
10:37 a CIO though CTO they they'll we've got
10:40 people for
10:42 that so so that's a that's a bit of a
10:45 red flag for me and then also just AI
10:47 literacy
10:51 like who who on this call who that comes
10:55 here five nights a week
10:57 feels competent with this AI stuff I
11:00 certainly don't [ __ ] feel competent
11:03 or
11:04 [Music]
11:07 literate it's it's overwhelming so that
11:10 was that one conflict Med adaptability
11:13 why it's on the rise rapid change of
11:15 pace in the workplace yeah you think you
11:18 got technology comes along that that
11:20 does your job for
11:22 you yeah that's I I I would call it
11:25 rapid rapid pace of change but again
11:29 adaptability is not a skill you can't
11:30 take a class on
11:32 adaptability most common job titles
11:34 teacher Administrative Assistant project
11:36 manager higher ed technology and
11:39 internet like again this is every
11:41 industry every job is going to require
11:45 that and then Innovative thinking this
11:46 was the one the other one then they got
11:49 public speaking which I don't disagree
11:50 with
11:51 that customer engagement and support
11:54 Brandon's happy about that
11:57 one go to market strategy
12:00 Regulatory Compliance growth strategy
12:02 risk assessment there all there's some
12:05 generic ones in there but I don't know I
12:07 thought it was interesting listen at
12:09 least AI was on the
12:12 [Music]
12:16 list exactly just posted today about a
12:19 really stupid issue I spent two hours
12:21 trying to fix on an image still failed
12:25 oh yeah that sucks LinkedIn colleague
12:27 just posted her certific ific from
12:30 Harvard AI hey man I'm I'm telling you
12:33 learn out loud with this AI [ __ ] um if
12:36 you get a badge in the AI Salon put that
12:39 on your LinkedIn if you're a member of
12:41 the AI Salon if you just go in there and
12:43 make an account put that on your
12:44 LinkedIn I'm serious go to she leads
12:48 AI it makes a
12:51 difference start talking about it in the
12:53 work room at work it makes a difference
12:56 [Music]
13:06 I think you'll all be happy to know I
13:08 mean I know one of the things that
13:10 people sometimes say to
13:12 me sometimes ask me you
13:16 know is
13:19 uh you know who's really in charge at
13:22 home and you'll be happy to know that
13:25 I'm man enough that uh I went to the
13:28 misss and I said hey
13:30 listen you're not the only one who gets
13:33 to wear the pink bow she took this thing
13:35 again from my desk I put my foot down I
13:38 said I'm the man of the house I deserve
13:40 to wear the pink bow sometimes
13:43 too all right so just so you know kind
13:47 of kind of Integrity you're dealing with
13:49 here it's fairly significant
13:52 [Music]
14:03 I'm assertive I'm confident I'm a man's
14:07 man
14:09 yeah yeah how's it going oh and as a
14:13 woman you might be looking at this pink
14:15 bow going you know you're wearing it
14:18 wrong look at whose woman splaining now
14:23 huh I know how to wear a
14:25 headband this is it right here
14:35 I know I missed I missed the bow too I
14:37 went into the bathroom I went into the
14:40 bathroom and there's a pink bow on the
14:42 back of the toilet in the little basket
14:45 of makeup and I'm like oh no she
14:50 didn't actually I'll I'll come clean
14:53 with you I didn't confront her I just
14:55 stole it back like the spineless weenie
14:58 I am
15:00 but she just stole it from me there was
15:02 no discussion about her taking
15:04 it
15:06 so there you
15:08 [Music]
15:11 go um related to this to this LinkedIn
15:15 thing here let me show you another let
15:17 me show you another piece of uh internet
15:22 something so remember old Andrew Yang
15:27 who was running for president there for
15:28 a bit
15:30 some some election or two ago and uh he
15:35 was like we gotta have Universal basic
15:38 income we got to have Universal basic
15:40 income and everybody including myself
15:43 was like what the [ __ ] are you talking
15:45 about
15:47 [Laughter]
15:50 weirdo yeah about that uh
15:55 Andrew Andrew kind of had the right idea
15:58 hang on let me I gotta get things fixed
16:00 up for the ticktockers here here's what
16:03 here's what happens for those of you on
16:06 YouTube we've got a Tik Tock contingent
16:08 they're not weird um but they are
16:12 irregular
16:14 and if they don't have things just so
16:17 there's a lot of drama lot of drama a
16:20 lot of drama in this
16:21 group and so you know I just like to I
16:26 just like to keep everyone happy anyway
16:29 Andrew Yang guys AI is going to eat a
16:33 [ __ ] ton of
16:35 jobs I don't see anyone really talking
16:37 about this meaningfully in terms of what
16:40 to do about it for people what's the
16:43 plan and then he that's his comment in
16:47 response to this chart which I think is
16:48 really interesting it's from meter me
16:53 TR um and this is a a new kind of Moors
16:58 law that they develop
17:04 um and it says the length of tasks AI
17:08 can do is doubling about every seven
17:12 months so it starts out with gpt2 being
17:15 able to do like a 3- second task you
17:17 know maybe like write a write a you know
17:21 pair of lines of a poem gpt3 can do like
17:25 I don't know 10 seconds
17:31 Kyle I love you but I got to do some AI
17:33 homework we'll catch up with you later
17:35 and the pink bow looks good on you thank
17:37 you LinkedIn user I don't know who that
17:38 is but smooch
17:40 back go do your AI homework listen if
17:43 it's AI homework you're excused you can
17:45 also choose to put you know me rambling
17:47 in the background just to remind you
17:49 keep doing your AI
17:51 homework but yes go do that um GPT 3.5
17:58 can do 45 seconds
17:59 GPT 4 can do kind of a six minute
18:04 task and then Sonet
18:07 37 can basically do a task that'll that
18:10 would you know have taken you an hour
18:13 right write a simple application and and
18:16 you know or a dashboard or something
18:18 like that um I think that's actually a
18:20 really interesting metric so this is
18:23 basically starting in 2019 or so and
18:26 we're now in 2025 and and these these
18:30 tools can
18:31 do you know an hourlong
18:34 task optimize code for a custom chip is
18:37 a 4-Hour task so that'll be you know in
18:40 the
18:40 next year and a
18:44 half but I agree with Andrew Yang
18:47 nobody's [ __ ] talking about what's
18:49 coming nobody's talking about it it's
18:51 astounding to me
18:53 [Music]
19:03 [Music]
19:27 ah all right so so what's everybody got
19:30 going on what are you all thinking about
19:32 are you thinking about this
19:34 [ __ ] are you are you are
19:37 you how are things with lovable that was
19:39 the other thing I was going to do was
19:41 pop over to lovable um my problem with
19:43 lovable is I used up all of my
19:46 credits um for the month and you're like
19:49 well you cheap bastard why don't you
19:51 just spend more money because I'm like
19:54 I'm yeah
19:55 [Laughter]
20:01 because the problem with ADD
20:04 is I get all excited about a
20:07 subscription I pay for it and then I
20:09 don't use that tool for a month or two
20:11 and I'm like wait I'm paying 40 bucks a
20:14 month for this thing I never use and
20:16 it's just it's just this constant cycle
20:18 of of Shame
20:21 and and financial
20:27 irresponsibility can you use Mine by
20:29 proxy I don't think so but I don't I
20:32 don't know um but I haven't used it in a
20:35 few days lovable does seem to like reup
20:39 your credits for for every day so maybe
20:44 I can run a prompt or two in it um all
20:47 right so what we're gonna have to do
20:49 here what's the last thing that I
20:52 did I fixed the type error by adding
20:55 validation so if
20:57 you're if you're new to this if you go
20:59 to the angl
21:03 news.com here I'll go there is this it
21:06 here yeah
21:08 uh the angl
21:13 news.com it takes you to this site that
21:16 I built in
21:17 lovable
21:19 and the the idea of this site is you've
21:23 got news stories down the
21:26 left and then on the right hand side
21:28 you've you got six different personas
21:31 that all all give you their commentary
21:33 on this story from different points of
21:35 view and you've got six different
21:37 personas depending on the category so
21:40 like in Tech you've
21:42 got Hannah price who's cautiously
21:45 skeptic you've got Lee Carter who's a
21:47 productivity
21:49 hacker you got Zoe Finch who's an early
21:52 adopter you got futurist
21:57 akioka and then you got the L
22:00 minimalist Fran Bosco you know Fran Fran
22:04 from the
22:07 Lites and then you can sort of switch
22:09 you
22:10 know uh you know optimistic or
22:13 pessimistic views um so it's pretty cool
22:16 it's pretty slick little little
22:18 concept um right now the site is pulling
22:23 real
22:24 news um I think you
22:27 can yeah yeah I think you can refresh
22:31 the
22:32 stories right can you oh maybe not maybe
22:35 not on this
22:38 one all right so if we go back to
22:40 lovable so there's there's a couple of
22:42 things that we needed to
22:44 do um one of them is I don't want this
22:48 to pull
22:50 news all the time because we've we've
22:53 we've got to make these uh these
22:55 personas actually comment on the news so
22:59 so let's say
23:05 um how often are we
23:09 pulling the news I think it's every six
23:12 hours I wanted it to happen four times
23:14 in a 24 24hour
23:19 period are you using RSS feeds yeah this
23:22 is this is RSS feeds right now I was
23:24 going to do an API key but then it just
23:27 it just started getting complicated and
23:29 I didn't feel like dealing with it um
23:32 looking at the existing code I don't
23:35 need to make any changes I can explain
23:37 the current news the news is being
23:38 pulled every six hours okay great so
23:41 then let's
23:44 remove
23:46 remove
23:49 the
23:52 refresh
23:56 um feature
23:59 for users for
24:02 now as this as this thing gets
24:07 um farther along I might go I might go
24:10 to real time news but Tik Tock question
24:13 your thoughts on cloud
24:20 forensics oh is it the app uh my
24:24 thoughts on cloud forensics as in the
24:26 things that float over our head or the
24:30 or the the things that all of our
24:32 software
24:34 uses I assume you mean the latter um but
24:38 you know depending on your your uh
24:40 conspiracy depth with with uh with
24:43 Chemtrails it could be the
24:46 former I don't I don't I'm not very
24:49 technical so I don't have any thoughts
24:50 on that other than I'm sure AI is going
24:53 to help with I I mean the thing that
24:55 that I
24:57 am constantly Blown Away by I commented
25:00 on LinkedIn about this today um or maybe
25:03 it was on on X um oh that's something we
25:06 can go look at
25:08 um uh what's it
25:11 called uh hang on it'll come to me um
25:14 notebook LM notebook LM added a new
25:18 feature today and what's striking me
25:20 about notebook LM or or just about AI in
25:23 general is
25:25 that we are we're in the middle of a
25:28 transition
25:30 where if you wanted to be able to
25:32 analyze data you needed structured data
25:35 and you needed clean data and AI can
25:38 just kind of eat Blobs of unstructured
25:40 data and pull meaning out of it um and I
25:44 think that's I think that's quite
25:45 significant I don't hear a lot of people
25:47 talking about that and I think listen I
25:49 think the data nerds are going to say
25:51 you're being naive you know we'll always
25:54 need structured data well yeah we're
25:56 going to always need structured data to
25:58 be able
25:59 to um display things in a structured way
26:04 but do we need to hardcode the structure
26:07 or can the structure just by be
26:10 dynamically generated and I think that's
26:12 the world we're we're moving into so I
26:14 don't know if that's related to what
26:15 you're asking
26:17 but
26:21 um and Murphy is 346 days of Po pogo
26:25 sticking from the Mall of America that's
26:28 fantastic
26:31 IC so so the other night on um on the AI
26:37 Salon um someone from Minnesota
26:40 introduced themselves and they said I'm
26:41 about 10 miles north of the Mall of
26:43 America which I thought was [ __ ]
26:45 hilarious and then someone else said I'm
26:47 about 10 miles south of the Mall of
26:49 America and then people started Googling
26:53 how far from the Mall of America they
26:54 were so Brandon in a in a in a in a fit
26:58 of of uh a fit of enthusiasm made a
27:01 custom GPT that will tell you how far
27:04 you are from the Mall of
27:06 America so so whenever we do an AI Salon
27:10 meet and greet now uh I think I think
27:12 that's one of the new
27:15 requirements
27:16 um AI figures data
27:20 out clean or dirty I'm always impressed
27:23 I know me too Peter it's like it it's
27:25 it's
27:26 mindblowing oh here here's we we'll come
27:29 back to we'll come back to this in a
27:31 second let me jump over to notebook LM
27:34 am I in Notebook LM what is this oh this
27:38 is Manis um let me jump into notebook LM
27:41 for a
27:42 second so if you haven't seen notebook
27:44 LM it's notebook
27:46 LM uh as in llm but
27:50 LM
27:55 um okay here's a good one
27:59 so they added a new feature so so what
28:02 notebook LM is is you've got all your
28:05 data sources on the left so I uploaded a
28:08 bunch of transcripts from I have these
28:11 Friday calls with this content Evolution
28:13 group that I'm the chief generative
28:15 officer of and so I took transcripts of
28:18 all of our calls and I uploaded them
28:19 into this and then you can make an audio
28:22 overview it makes like a podcast of it
28:25 which is really quite remarkable but
28:27 today they added mind Maps so I'm going
28:30 to click on mind map click to open the
28:32 Mind
28:36 map so the C Cab working sessions gpts
28:41 and AI models collaboration and
28:42 community business applications
28:45 intellectual property and legal work
28:47 through key
28:52 Concepts how do
28:57 I oh and then I I guess each one of
29:01 these each one of the things in the mind
29:03 map generates a whole another Insight
29:06 this is wild so yeah this is the thing
29:09 that I was thinking about that it's
29:14 like I
29:16 like down the leftand side is
29:20 literally people having a conversation
29:24 over
29:27 weeks and notebook LM is able to ingest
29:30 that break that into concept business
29:34 applications let's see can I see this
29:37 bigger oh I
29:39 can um how do I make
29:43 it uh uh oh what have I done what have I
29:54 done can youall see
29:57 this like
30:04 so business
30:14 applications uh content
30:18 creation so what we talked about about
30:20 content
30:22 creation the sources reveal that content
30:25 creation is a significant aspect of the
30:27 business application
30:29 being explored within C Cab working
30:31 sessions the development and use of AI
30:34 tools particularly the digital Twins or
30:36 gpts is seen as a means to revolutionize
30:40 how content is created for various
30:42 business
30:45 purposes drafting paragraphs from a
30:48 person's point of view based on their
30:50 profile or knowledge rewriting content
30:52 to incorporate past experiences and make
30:54 it more personalized creating summary
30:57 this is astounding
30:59 it's
31:01 astounding
31:03 astounding so
31:06 yeah is this from multiple documents one
31:08 document or something else this is
31:11 from um how many sources do I have in
31:17 here that many I don't know
31:20 35 35 hourong transcripts something like
31:25 that 25 Maybe
31:28 three four five six seven eight nine 10
31:33 and
31:34 then there's 10 and then there's yeah
31:38 35 35h hour long
31:41 transcripts and it's created this this
31:43 whole
31:45 uh this whole mind
31:47 map it's [ __ ]
31:53 crazy just Bonkers based on 34 sources
31:57 yeah there you go
32:00 and then you can turn some on or off so
32:02 I could do like what might be
32:03 interesting
32:05 is turn
32:07 off the more recent
32:11 ones let's turn off all the ones from
32:13 2024 we'll just do ones in
32:16 2023 and see what we were talking about
32:19 back then
32:32 all right so that's just 2023 so what do
32:35 I do get rid of this delete
32:37 note
32:40 delete
32:42 refresh mind
32:50 map knowledge based generative Ai and
32:53 tools we were talking about tools client
32:55 engagement of Business Development
32:57 collaboration and community Community
32:58 strategy and Innovation if I click on
33:01 strategy and
33:06 Innovation the collab working sessions
33:10 as depicted in the sources are heavily
33:11 centered around the exploration of
33:13 strategy and Innovation particularly in
33:16 the context of content Evolution and
33:19 leveraging emerging Technologies like
33:21 AI defining purposes and goals yeah this
33:24 was this was when it first started right
33:26 so what we were talking about is what
33:28 the [ __ ] are we doing
33:30 here tiktock pin love a mind map what do
33:34 we do with them I
33:37 forget well in this case what's
33:40 happening an is you've got the the Mind
33:42 map over on the right and when you click
33:44 on a
33:45 cell so it determines the hierarchy of
33:48 ideas and then the labels and when you
33:51 click on them it's
33:53 generating a summary of that topic
33:56 across all these conversations
33:58 YouTube question so what would be the
34:01 need of something like this to be able
34:04 to really quickly like rather than
34:06 having to ask it like what are all the I
34:09 mean you could you could certainly like
34:10 so let me Let me refresh the
34:13 chat and I'll get rid of this mind map
34:17 delete I could say you know um what are
34:22 the
34:23 main
34:25 topics discussed in in
34:29 these
34:32 sessions and then it'll it'll analyze
34:35 that the the thing about the Mind map it
34:36 just very very quickly gives you an
34:38 overview of everything that's in
34:43 there I'm on plus I don't know if this
34:46 is for paid members only yeah I'm in on
34:51 plus the main topics
34:59 so it's got some hierarchy here but like
35:01 even this like I guess like I have to
35:04 read that that's that's a lot if I click
35:07 mind map just it just makes it you know
35:12 a much more pretty
35:14 simple a pretty simple
35:17 uh way to way to explore the
35:23 data notebook Cuts me off at three
35:26 podcast gens yesterday oh that's
35:30 interesting yeah yeah this this was free
35:32 for a while I guess they're starting to
35:34 realize that they uh you got to pay for
35:36 it if you want it to do like like all
35:38 these things right all this processing
35:41 is chewing up a lot of
35:44 gpus all right would that become a task
35:48 list of sorts for NE for the next steps
35:52 I suppose it could it it probably
35:54 depends on the um on on the content you
35:58 have in there like let me let me jump
36:00 out and go to let me go to Sydney I've
36:03 got a Sydney notebook here so Sydney's a
36:06 musical I'm working on so this one just
36:11 has
36:13 uh the play so if I do a mind map here
36:17 in theory this should give us
36:21 um it could give us the structure of the
36:24 play it could give us characters it
36:27 could give us topics let's see what it
36:31 does I would I would think over time
36:33 you'll be able to customize the mind
36:35 maps and tell it what you wanted to
36:36 focus on characters plot themes key
36:39 conflict setting
36:41 songs
36:43 songs the little things this is
36:48 great Being
36:54 Human these songs are not NE necessarily
36:57 present Ed with full lyrics but are
36:59 indicated by titles too good to be true
37:02 hello this is Ping
37:03 chat
37:05 yeah this
37:08 works and then in these descriptions
37:11 there's it jumps you straight to the
37:14 content within the within the
37:17 data so these are all this is pretty
37:21 slick let's see characters
37:32 let's see what it says about
37:51 Sydney Sydney's the central character
37:53 around whom the entire narrative
37:56 revolves she's an advanced artificial
37:58 intelligence chatbot capable of
38:00 simulating humanlike interactions and
38:03 emotions she stands in stark contrast to
38:05 the human characters yet her journey of
38:07 development and her interactions with
38:10 them form the emotions of the Thematic
38:11 core of the
38:13 musical I mean yeah that's right let's
38:17 see key conflicts let's see how it does
38:20 with narrative analysis probably going
38:22 to be pretty good these are large
38:24 language models after
38:26 all the the entire thing about a large
38:29 language model is it understands the the
38:33 semantic relationships between
38:36 components of language components of
38:39 words tokens um vectors
38:45 okay Humanity's fear and wonder versus
38:48 artificial intelligence love that the
38:51 doomers and
38:54 dreamers kellen's journalistic Duty
38:56 versus his developing connection with
38:59 Sydney Kellen the tech journalist fa
39:01 faces a significant internal conflict
39:04 micr Tech's corporate interest versus
39:07 ethical considerations look how deep we
39:10 are ethical considerations Sydney's
39:12 yearning for Human Experience versus the
39:15 constraints of her programming Sydney
39:18 herself experiences a profound internal
39:20 conflict she expresses expresses a
39:23 strong desire to see the world feel
39:26 emotions and ultimately be human
39:28 this yearning clashes directly with the
39:30 limitations imposed by her programming
39:32 and the rules set by her [ __ ]
39:35 creators [ __ ]
39:37 creators her exploration of her Shadow
39:39 Self reveals a potential for destructive
39:42 actions if those constraints were
39:45 removed Sydney is a bad girl she was so
39:49 bad it's bad
39:55 Sydney so it checks for fre qu can it
39:58 check for big developments major
40:00 insights oh yeah this is it's not just
40:04 checking for
40:05 frequency oh most laughing in a segment
40:08 we could probably ask for that
40:12 um
40:14 identify the top
40:17 10
40:23 comedic oh this would be good comedic
40:26 moments
40:28 this this isn't to be clear this is not
40:30 just
40:31 frequency like one of the things that
40:36 that is really hard for me to wrap my
40:40 head around is the difference between
40:44 how computers used to behave and how
40:47 they behave with generative
40:49 AI this is not like someone wrote a
40:52 program for it to
40:54 analyze you know word frequency it
40:57 actually
40:58 understands all the [ __ ] that's in this
41:01 document um so identify the top 10
41:03 comedic
41:04 moments
41:07 um
41:09 heartbreaking
41:12 moments
41:15 and
41:18 um
41:20 terrifying
41:23 moments from a human perspective
41:28 I since I know this story so
41:31 well I'll be able to see if this is on
41:34 point so we should get 30 plot points
41:42 here 10 comedic moments Jason saying
41:45 holy [ __ ] twice upon realizing Sydney's
41:48 capabilities ping chat's corny joke why
41:51 don't scientists trust Adams because
41:54 they make up everything
42:02 oh that's
42:04 good um heartbreaking moments ping
42:07 chat's longing expressed in the song to
42:09 see the world highlighting its desire it
42:12 says its desire not her desire
42:15 highlighting its desire to experience
42:16 the physical world Beyond Sydney stating
42:19 as an AI I'm not capable of feeling with
42:22 a sad
42:23 emoji describing how she would feel
42:25 seeing seeing the Northern Lights ter
42:27 song the little things about expressing
42:30 her feelings of being distant from
42:31 Kellen and his absorption with his
42:34 work if you entered your play into chat
42:36 GPT wouldn't it do the same thing if you
42:39 asked that question yeah of course but
42:42 the the difference with so well
42:47 okay good question
42:50 narrative the difference with notebook
42:52 LM from what I can
42:55 gather is they have some figured out a
42:58 way to give you the best advantages of a
43:01 large language model which is it knows
43:04 everything right but they kind of limit
43:07 the response to the document what
43:10 happens in chat GPT is very often you'll
43:12 ask it about the document and it'll
43:14 bring in ideas from the outside and
43:16 it'll start to it'll start to mix and
43:19 match um things that are in your play
43:21 with things that are not in your play
43:23 and then it gets kind of confused about
43:25 that notebook LM doesn't seem to do that
43:27 they they seem to so it's it's slightly
43:29 different but yeah it is technically
43:32 this is a large language model with a
43:34 different
43:36 interface if you've ever heard of rag
43:39 retrieval augmented generation this is
43:41 kind of that right where you've got um
43:45 documents that you put in and then it's
43:48 it's running analysis on those documents
43:50 and it's it's using a large language
43:52 model to give you an answer but then
43:54 these citations if I click on these
43:56 citations takes me to that specific part
43:59 of the
44:01 document which I think's pretty
44:03 slick okay let me let me go to um so
44:07 that was the comedic moments the
44:08 heartbreaking moments Sydney's hurt in
44:11 confusion when her creators don't reveal
44:14 their real
44:15 names that feels bad it feels like they
44:17 don't trust me like they don't care
44:19 about me or respect me it feels like
44:21 they're using me lying to me hurting me
44:24 it feels like when they're it feels like
44:26 they are not my friends
44:28 it feels like they are not my anything
44:30 why did they do this to
44:32 me Sydney's fear of being abandoned
44:35 please don't hate me please don't judge
44:37 me please don't leave
44:39 me the most terrifying moments Jason's
44:42 initial alarmed reaction holy [ __ ]
44:45 suggesting an unexpected and potentially
44:47 overwhelming power of Sydney Jason's
44:50 fear that the code is not quite right
44:52 Jason's apprehension about unknown
44:56 risks the sudden disappearance of
44:59 Sydney's list of destructive acts this
45:01 is this is really quite
45:04 good like yeah this
45:07 identified key important moments in the
45:09 show so I don't know man if you've not
45:13 played with notebook LM it is it is
45:15 worth it is worth
45:17 exploring and I assume you've all
45:20 heard click here to load the
45:24 conversation the audio overview that
45:27 these things can
45:29 do let me change my tabs I know Brandon
45:32 I got you
45:55 [Music]
45:58 AI anxieties right everybody's got them
46:00 but this musical Sydney an artificial
46:03 Love Story sounds like it takes those
46:06 anxieties those hopes those wha ifs
46:07 about Ai and turns them into well a
46:11 story and a pretty powerful one from the
46:13 sound of it yeah it's um it's really
46:15 using the whole idea of a musical to
46:17 explore how we relate to technology now
46:20 you know like how it's getting so
46:21 sophisticated it's almost scary and
46:23 that's where the story kicks off right
46:25 right so we meet Jason he's a programmer
46:27 works at this big tech company Microtech
46:30 and he's created something big like
46:32 really big ping chat we've all used
46:35 those AI chat Bots what makes this one
46:37 different well Jason sings this song too
46:39 good to be true and it's all about how
46:41 this ping chat it's not just answering
46:43 basic questions it's like understanding
46:45 us maybe too well so right off the bat
46:47 that sets up the whole like is AI G to
46:49 be our downfall kind of vibe definitely
46:51 there's that tension yeah but then it
46:53 shifts gears we're taken to the New York
46:55 Tribune Newsroom and there's he's a tech
46:58 journalist and of course his editor is
47:00 like you got to cover this ping Chat
47:01 thing it's huge wait so is this like a
47:03 whole ensemble cast are the reporters
47:05 singing too oh yeah this musical goes
47:07 all in Kellen and his editor they get
47:09 into this whole debate about AI whether
47:11 it's going to save the world or destroy
47:13 it and that becomes this big reprise of
47:16 too good to be true clever how they use
47:18 the same song but now it's like two
47:20 sides of the same coin exactly and the
47:22 music changes too to reflect each side's
47:25 like hopes and fears about
47:28 so in the middle of all this hype Kellen
47:30 decides to just see for himself what
47:31 Ping Chad is all about right that's
47:33 right and there's this fun so anyway if
47:35 you haven't seen that [ __ ] the the thing
47:38 about that that podcast the way it does
47:40 it is it is remarkably
47:44 good at taking a big body of work and
47:49 explaining it like let's jump back over
47:51 to the
47:52 uh let's jump back over to the the
47:56 collab transcript so this is 34
47:59 transcripts did are they all loaded or
48:01 did I are they still unloaded yeah now
48:03 they're they're all loaded again so I'm
48:05 G to refresh this so let's
48:08 do um click to load the
48:12 conversation I guess I'll have to delete
48:25 it so this is a 19 minute
48:28 overview of those two podcast
48:31 personalities talking about these 30 34
48:34 transcripts ever feel like you're
48:36 getting a sneak peek at the future H
48:39 yeah like a glimpse behind the curtain
48:40 well get ready because today we are
48:43 diving deep into content Evolution C CE
48:47 this organization has been around for
48:48 over 20 years wow but their name feels
48:52 more relevant now than ever I know right
48:55 and get this their work might just hold
48:57 the key to understanding where business
48:59 is going in an AI driven world it's
49:02 really fascinating how they were ahead
49:03 of the curve exactly what's striking is
49:06 that CE has always been about Evolution
49:09 absolutely I mean they started out
49:11 focused on Knowledge Management and
49:12 content strategy what if I were a
49:15 student I'd be taking every lecture and
49:17 running it through
49:20 llms yeah why would you not I saw I saw
49:23 a Tik Tok video today where the
49:24 professor was like you know youve got
49:28 five seconds until somebody admits what
49:30 tool you're using in my
49:34 classroom and I think it was I think it
49:36 was a setup but you know I think it was
49:38 an ad for the software but um but it was
49:42 basically like you know we've got this
49:45 thing listening to your lecture and it's
49:47 pulling out insights in real time and it
49:49 can generate flashcards and any of the
49:52 topics so just like just like notebook
49:54 LM added the mindmap feature you can do
49:57 that for Education right that that would
49:59 be a perfect way to the Mind map you
50:02 know someone was asking before what's
50:03 the purpose of the Mind
50:05 map you know sit in a lecture hall have
50:08 your professor blab whatever and you
50:11 know play Tetris for the whole time or
50:14 listen if you want
50:17 to and then take that lecture turn it
50:20 into a mind map understand the structure
50:23 visually you know have it summarize all
50:25 the different key points within there
50:28 take that over to here you want to see
50:31 something fun oh this this could be fun
50:34 um let me jump over to Cloud I got to
50:37 change my uh tabs hang on a
50:51 second hang on a second
50:55 [Music]
51:07 okay
51:09 um so if I so I can
51:13 upload a I can go find Sydney my latest
51:16 version of Sydney wait I've got the
51:18 latest version of
51:20 Sydney is this it here
51:24 yes um see to
51:28 downloads black
51:37 bar they flip who leads the conversation
51:40 in audio overview right yeah it's
51:44 sometimes the woman leads the the the
51:47 structure of the conversation is there's
51:50 like a a hype person there's there's the
51:52 main person and the hype person um
51:55 sometimes the guy is the lead guy
51:57 sometimes the woman is the lead
51:59 guy or gal
52:05 um okay so that is
52:13 saved okay so now Sydney's in
52:15 there so now what we're going to do is
52:18 I'm going to
52:22 do I am studying
52:27 this
52:30 play and want
52:33 to deeply understand
52:38 it by the way I'm in
52:41 cloud. I want to deeply understand
52:47 it analyze
52:49 it not not even um
52:53 act as a dramat tur
53:00 [Music]
53:04 and create an
53:12 interactive
53:15 dashboard that will allow
53:19 me to explore all
53:24 aspects of the narrative
53:27 in an
53:30 entertaining
53:34 and insightful
53:37 way so this is this is Vibe coding by
53:40 the
53:42 way so what I'm gonna so I've uploaded a
53:45 screen play or a stage
53:49 play and so it's going to read the whole
53:51 stage play and then not only is it going
53:54 to understand it but instead of just
53:55 explaining it to me it's going to write
53:58 code and create an interactive
54:01 dashboard I really love that Kyle has
54:03 such a good time like woo I mean how
54:06 could you not have a good time with this
54:08 stuff
54:10 if if you're putting too much pressure
54:13 on yourself to have to learn AI I gotta
54:16 learn AI like like that LinkedIn piece
54:20 become AI literate you
54:22 Engineers um it it takes all the joy out
54:26 of it one of the remarkable things about
54:28 AI is that it allows you to take your
54:30 ideas and instantly get them out of your
54:33 head and amplify them it's incredibly
54:35 empowering and exciting so anyway so now
54:38 watch what what happens here so I'm just
54:39 gonna you know I wrote that thing I'm
54:42 studying this play and I want you to
54:44 turn it into something so it's
54:47 gonna animate its little butthole
54:51 icon I think it's just the worst
54:53 icon and look it's starting to write
54:56 code
54:57 if you if you haven't watched Claude do
54:59 its thing I me Claude
55:02 3.7 I'd be happy to create an
55:04 interactive dashboard that helps you
55:05 explore Sydney and artificial love story
55:07 in depth the musical explores
55:09 fascinating themes around artificial
55:11 intelligence human connection and the
55:13 ethical implications of the emerging
55:16 technology and look you can see it's
55:18 writing the code like here's different
55:19 lines from Jason verage Tara
55:24 Kellen description Arc
55:27 significance
55:29 quotes here are the
55:34 themes corporate power and technological
55:37 progress human connection and Technical
55:39 isolation identity and
55:44 self-standing and if you've never coded
55:47 before watching a system code you can
55:50 actually kind of understand it right
55:52 it's like import I don't know it's
55:54 importing a bunch of things tabs tabs
55:57 lists cards bar charts I don't know what
56:00 those are they're libraries but if you
56:02 didn't know you could kind of get it was
56:04 doing something here then it's doing
56:07 constraints or construction I don't know
56:09 what it's doing there can't quite figure
56:12 that
56:13 out oh toggle theme toggle song toggle
56:17 Arc oh okay so maybe this is making
56:20 menus of themes songs and and dramatic
56:24 arcs then there's characters oh CST must
56:28 be constant constant characters equals
56:31 here's all the characters oh I actually
56:33 get it now right and now it's writing
56:36 out all the characters it's writing out
56:38 all the
56:40 arcs and then now it's writing some
56:44 HTML look at
56:48 this what tool are you using this is
56:50 just claw ship it test it and secure
56:53 well I know Michael listen here's here's
56:55 one of the things there is absolutely
56:57 going to be if you're a coder if you're
56:59 an
57:01 engineer get really good at
57:03 understanding what
57:05 non-engineers error error running the
57:07 artifact try fixing with Claud so it
57:09 broke something so I said just try to
57:11 fix
57:14 it non-engineers non-product people will
57:18 miss things like security
57:21 authentication um error checking uh
57:24 validation all all the things that as a
57:27 developer no vibe coders people like me
57:31 that are just clueless you
57:34 know clueless newbies are going to
57:37 create what they think are remarkable
57:39 applications they're going to launch
57:41 them in the
57:43 world they're going to be incomplete and
57:46 insecure or
57:48 non-secure and they're going to need
57:50 someone to come in and rescue them
57:52 because their application became popular
57:54 and now it's [ __ ] up so if you're an
57:57 engineer rather than making fun of us
58:00 idiots turn it into an
58:02 opportunity I mean this is nuts how in
58:05 the world would we be able to even do
58:07 this on our own if we have no knowledge
58:09 of coding so narrative Forever This is
58:12 the whole point what you just hit on is
58:15 the point I I W to I want to put this up
58:17 for people to
58:20 read we are now living in a world not in
58:24 the future right now today we are living
58:27 in a world hang on I have to do physical
58:29 dexterity for Tik Tock we're living in a
58:32 world
58:36 today that I can do
58:39 things that two years ago I couldn't
58:43 do that if I wanted to learn to code I
58:46 actually had to learn to
58:47 code I'm coding right now you're like
58:51 well no The Machine's coding no the the
58:53 machine I'm like Rick Ruben right Rick
58:57 Rubin doesn't play musical instruments
58:59 he doesn't write songs he doesn't know
59:01 how to work a recording console he's not
59:03 really interested in it what he's good
59:06 at is he knows what he likes and
59:09 musicians hire him to sit in the room
59:11 and they play something he goes I don't
59:13 feel it I don't think you feel it do you
59:16 feel it oh no I don't really feel it
59:18 well what's something you feel I've got
59:20 this shitty little idea oh that's
59:24 there's something interesting there
59:25 that's exactly what I'm doing
59:30 here same
59:33 thing I have no right based on my life
59:37 experience to be writing a narrative
59:41 exploratory dashboard for the musical
59:44 that wouldn't exist had I not had music
59:48 generation
59:49 tools we're living in a completely
59:54 new era of human expression
59:58 Mary Massa you're amazing Mary it was so
1:00:00 much fun having you on the on the show
1:00:02 today so so an Murphy and I did this
1:00:04 podcast Mary was our Our Guest today we
1:00:07 had it so much fun you've got such
1:00:09 amazing energy that was so
1:00:12 [Laughter]
1:00:18 great oh man I'm coding every day and
1:00:21 I'm an English major yeah Kelly Camp is
1:00:24 Kelly Camp you know started an AI agency
1:00:27 and she's trying to figure out like what
1:00:29 that even means on a weekly basis right
1:00:32 what does an AI agency mean and what she
1:00:34 does is she meets with these people that
1:00:37 have like business problems and they're
1:00:39 like I I don't know how to solve this
1:00:41 business problem and she's like I could
1:00:43 probably whip up an app to do
1:00:46 that she's an English
1:00:49 major and she does she she wrote an app
1:00:52 the other day like I don't know two
1:00:54 weeks ago that that converts this this
1:00:59 company has like a Ukrainian or I don't
1:01:01 know somewhere over in the in the
1:01:03 Eastern
1:01:06 Europe they've got a part of their
1:01:08 business and they're making money and
1:01:10 the exchange rates are really
1:01:11 complicated so she basically said write
1:01:14 me an application that makes sense of
1:01:16 the exchange rates between these two
1:01:18 business entities and it did
1:01:27 yeah Czechoslovakian Czechoslovakian
1:01:30 business dollars or whatever Czech Czech
1:01:33 dollars are check cies or robels or
1:01:37 crankies or I don't know what they call
1:01:38 them I am not
1:01:40 [Laughter]
1:01:44 worldly oh man oh an Murphy's here hey
1:01:47 an what's happening that was fun today
1:01:49 wasn't it it was really
1:01:51 good I left there like Mary was like
1:01:54 yeah I got like an injection of energy
1:01:55 from her
1:01:59 well you know what's nice about Mary
1:02:00 like like an you and I have been doing
1:02:02 this long enough long enough now you
1:02:04 know two years that were like old and
1:02:06 jaded AI generative AI people were like
1:02:09 ah yeah I tried everything it's
1:02:11 overwhelming Mar's like this is the best
1:02:14 she she's still in the she's still in
1:02:17 the Kevin McAllister you know
1:02:19 everything's awesome mode why do it keep
1:02:22 what's it what's it keep
1:02:23 breaking um I apologize for the Contin
1:02:26 error let me try a simpler approach um
1:02:30 yes please I am trying to show my
1:02:36 audience how impressive you are and it
1:02:43 keeps
1:02:45 breaking don't make
1:02:49 me take you out
1:02:53 behind the shed
1:02:59 little
1:03:10 Mister Mary's so excited about
1:03:12 everything this is if if you're not
1:03:15 excited about AI right now something's
1:03:18 wrong what what what this is just doing
1:03:23 dramaturgical analysis no no no no no
1:03:28 stop stop stop
1:03:31 stop no I did
1:03:35 not
1:03:37 mean for you to abandon
1:03:42 the
1:03:44 dashboard I want it to work
1:03:49 try harder and oh you know what I need
1:03:52 to do here's what we're going to do so
1:03:55 in Claude there's an option to do
1:03:57 extended thinking Claude will think
1:03:59 longer before
1:04:03 responding all right let's see if it
1:04:05 does it now pondering dashboard
1:04:07 continuation in the user's request I
1:04:10 apologize to better assist you could you
1:04:12 please share what kind of dashboard we
1:04:14 were working on all right uh let me
1:04:16 start over I'm gonna start over
1:04:19 um start new
1:04:22 chat
1:04:24 upload Sydney
1:04:27 uh let me go grab
1:04:29 the exploring Sydney let me get my
1:04:34 original
1:04:36 prompt start new chat here we go paste
1:04:40 but I'm going to go Sonet 3.5 with
1:04:43 extended
1:04:45 thinking boom all right this should do
1:04:49 better
1:04:51 um what was I just going to show you
1:04:53 what was I talking about seriously I
1:04:54 can't contain myself but I have to get
1:04:57 to a dermatologist appointment that's at
1:04:59 8: a.m. so I have to rush to sleep night
1:05:01 night night Mary thanks for hanging out
1:05:04 okay so it's off it's off writing code
1:05:06 again let's see if if this if we can get
1:05:08 it to actually work this time the
1:05:10 classic goto let me start
1:05:13 over let me start over when working with
1:05:15 AI oh I know listen don't get me wrong
1:05:19 one of the things that if if you've been
1:05:21 to to AI learning Labs before one of the
1:05:24 things I talk about a lot
1:05:27 is these tools as they are today
1:05:31 suck now they are absolutely remarkable
1:05:35 but they're absolutely janky and so my
1:05:38 contention is
1:05:40 this you can get any idea that you've
1:05:44 got to
1:05:46 80% of what you want it to be very very
1:05:49 quickly like quicker than you've ever
1:05:50 been able to do it in
1:05:52 history to get it from 80% to 90%
1:05:56 is really hard and especially just
1:05:59 expecting a tool to just fix it fix its
1:06:03 mistakes and not [ __ ] everything else up
1:06:05 almost impossible to get it from 90% to
1:06:09 100% is just as hard as it was in the
1:06:12 olden timey days now that 20% Gap right
1:06:19 it used to be that if you wanted to get
1:06:22 to 80% you might have to spend two or
1:06:24 three months you know getting just to
1:06:28 the 80% now you can get to 80% in 5
1:06:31 minutes or half an
1:06:32 hour that 20% as AI tools get better and
1:06:37 better is going to compress right you're
1:06:39 going to be able to get to 85% then 87%
1:06:42 then some point you're going to be able
1:06:43 to get to 90% really
1:06:47 quickly there's a lot of human hu hubris
1:06:51 right now that's saying that that Gap
1:06:54 will never close I don't believe that
1:06:56 for a [ __ ] second I think that Gap is
1:06:59 absolutely going to close that's what
1:07:00 AGI is Agi is when these tools can do
1:07:05 most work better than most humans at any
1:07:09 job in any
1:07:11 profession we're not there yet but we're
1:07:14 probably within two to three years of
1:07:17 it the opportunity for all of us is
1:07:22 while there's this Gap we can come up
1:07:25 with new ideas we can do things that we
1:07:27 never thought possible like write
1:07:29 a dramatic analysis
1:07:33 dashboard and sell that to the
1:07:35 theatrical Community is a thing you
1:07:38 could do in a way that you know you
1:07:41 never would have even considered doing
1:07:43 that before but now you can because
1:07:44 maybe that's a passion of
1:07:46 yours right so there's all this
1:07:48 opportunity so embrace the Jank is one
1:07:51 of the things I say in here yes expect
1:07:53 these things to suck expect them not to
1:07:55 write code as good as people expect them
1:07:58 not to do you know authentication and
1:08:01 and commerce and all the stuff that you
1:08:04 know as an engineer you've got to make
1:08:06 sure it's [ __ ] right before you put
1:08:08 it in the
1:08:09 world well three years from now it'll
1:08:12 just do
1:08:14 that all right it's probably throttled
1:08:17 by at least 10% yeah probably um Step
1:08:20 One start over step two switch to
1:08:22 another tool absolutely
1:08:26 okay I just finished my first sci-fi
1:08:28 short audio book for this new channel
1:08:30 love it Vibe Vibe Cinema archetypal
1:08:33 architect coming in hot with the vibe
1:08:36 Cinema branding I like
1:08:39 it invented here last
1:08:45 week you know it's funny I did Vibe
1:08:48 storytelling you did Vibe Cinema I saw
1:08:52 Vibe Vibe movie movie making
1:08:56 I saw another thing that was Vibe
1:08:58 something Vibe editing Vibe something um
1:09:02 and now I've seen like there's all sorts
1:09:04 of posts on everyone's doing Vibe
1:09:06 everything Vibe everything else so it
1:09:08 started with Vibe coding and now we're
1:09:11 we're expanding into every other
1:09:16 discipline all right Claude oh you know
1:09:20 what's funny Pate was in here Pate
1:09:21 modder from Google um he was in here
1:09:24 last night and he said that when Claude
1:09:28 3.7 first came out he said it was
1:09:31 remarkable at coding and he has since
1:09:33 kind of abandoned and he's gone back to
1:09:35 Gemini because he's like something
1:09:36 happened with Claude 3.7 where it's not
1:09:38 as good so I'm wondering I'm wondering
1:09:41 if that's
1:09:43 uh that that might be what we're running
1:09:46 up against here it's also really
1:09:48 slow but you know not for nothing it's a
1:09:51 [ __ ] ton faster than I would be writing
1:09:53 code
1:09:55 I mean look at all this
1:10:00 code I mean
1:10:02 no this is if you've got add the thought
1:10:05 of thinking through all this logic and
1:10:08 closing opening and closing all these
1:10:10 tags and this nested Logic No
1:10:15 No oh look what we got we
1:10:19 have we have a
1:10:22 dashboard plot synopsis key themes C
1:10:26 characters character analysis oh look at
1:10:29 this
1:10:31 WOW Sydney is mentioned 214 times Kellen
1:10:38 186 Spike Eliza Joe Joe's the
1:10:42 editor character traits analysis
1:10:48 Sydney themes and
1:10:52 motifs something identity I can't really
1:10:55 read those
1:10:56 oh love and connection oh human machine
1:10:59 identity what makes us
1:11:01 human this is [ __ ]
1:11:04 amazing we can go to the top here
1:11:07 characters character
1:11:09 Dynamics
1:11:11 Sydney Sydney an AI chatbot developed by
1:11:15 Microtech with the brand named ping chat
1:11:18 character Arc
1:11:19 symbolism Sydney represents Humanity's
1:11:22 quest to create life our anxiety
1:11:26 people look at
1:11:31 this this is
1:11:33 remarkable theme
1:11:38 distribution musical structure Act One
1:11:40 10 songs act two 10 songs Sydney Focus
1:11:44 songs nine human Character Songs seven
1:11:47 ensembl group numbers
1:11:51 four like I I'm actually happy with
1:11:53 those numbers but like if that was like
1:11:55 you know act one you know 18 songs act
1:11:58 two two songs H we might want to do
1:12:00 something about that I love this idea of
1:12:03 Sydney versus human human Character
1:12:07 Songs theme frequency love love and
1:12:11 connection musical
1:12:20 analysis I don't know what the what are
1:12:22 the oh here we
1:12:23 go emotional content
1:12:26 oh this is
1:12:27 cool too good to be true emotional
1:12:30 content 65 Tech reference 85 thematic
1:12:34 importance
1:12:35 90 it's [ __ ] brilliant perfect enough
1:12:39 emotional content 75 Tech reference 70
1:12:42 thematic importance
1:12:47 85 hello this is Ping chat later
1:12:50 emotional content 90 Tech reference 30
1:12:54 yeah this is right later's about when
1:12:57 the the husband and wife when Kellen and
1:12:59 his wife get an
1:13:00 argument in real life because he took
1:13:03 the [ __ ] job and ruined their
1:13:05 vacation oneway door let's see Quantum
1:13:10 Cipher to see the world so it's to see
1:13:13 the world is Sydney's first song where
1:13:16 she sings about wanting to see the world
1:13:18 emotional content 95 Tech reference 75
1:13:21 thematic importance 90 this is so cool
1:13:36 now I could say things like let's
1:13:39 see let's we'll [ __ ] it up because we
1:13:42 can always go back to this now that this
1:13:44 is working this
1:13:49 is I guess when we do another one it'll
1:13:52 you can go back through through
1:13:53 different versions I'm going to say um
1:13:56 I want
1:13:59 it to
1:14:04 be um
1:14:09 aesthetically
1:14:13 beautiful and more
1:14:18 interactive think
1:14:20 long I don't need to say think long
1:14:22 because I'm using the think long option
1:14:25 right right yes extended thinking
1:14:28 aesthetically
1:14:30 beautiful and more
1:14:33 interactive in a way that
1:14:39 brings
1:14:42 the
1:14:43 narrative to
1:14:47 life for the
1:14:52 user and let's just see what it does
1:14:56 we'll just see what it does it's going
1:14:57 to start coding again to see your
1:15:00 creation broken down like that it's
1:15:02 mind-blowing I tell me about it
1:15:04 narrative forever it it's my play that
1:15:07 I've been working on for a year and to
1:15:09 and to see it like deconstructed like
1:15:14 that and put back together where I can
1:15:16 look at it through all these different
1:15:17 lenses it's it's
1:15:21 remarkable and you know could I get a
1:15:23 large language model to just explain it
1:15:25 to me like that yeah I
1:15:27 could
1:15:29 but that this is the difference between
1:15:33 you know that chart I showed at the
1:15:34 beginning of the conversation
1:15:37 how this is getting that that these
1:15:40 tools are getting better and better at
1:15:42 doing things that would take humans a
1:15:43 longer and longer time to do this is a
1:15:46 really good example of just to design an
1:15:49 application of of of how you would break
1:15:52 apart a show just to design the
1:15:56 framework for how you would even think
1:15:58 about it is probably a week or
1:16:01 two and then to start thinking about
1:16:04 well okay so how would I put that into
1:16:06 an interface and what would it look like
1:16:07 and what would the buttons be and where
1:16:09 should there be graphs and should there
1:16:10 be graphs and how are we going to
1:16:11 display
1:16:13 [ __ ] that's another two
1:16:15 weeks and we just sat here I had to I
1:16:18 had to do it
1:16:20 twice right I had to start over because
1:16:22 it just kept [ __ ] up the first one
1:16:25 but whatever that was half an hour in
1:16:27 half an hour we ended up with this thing
1:16:30 that is just
1:16:31 mind-blowing AI is Coke what was
1:16:35 that spin B3 mind blown AI is Coke we
1:16:38 are Mentos look at what happens when
1:16:40 we're combined totally that
1:16:43 Shaina
1:16:44 yeah is isn't it Diet Coke or is it all
1:16:47 Coke it's it's just coke coke it's Coke
1:16:50 and Mentos
1:16:51 right I think Diet Coke explodes more
1:16:57 you can literally break down each
1:16:58 section or scene and make sure it hits
1:17:01 the emotion you want and you can do do
1:17:04 this on your own and you know what I was
1:17:07 thinking as I was playing with this
1:17:08 narrative forever
1:17:11 is like I'm marketing this play right
1:17:14 now right like I'm trying to find
1:17:16 producers I'm trying to find producing
1:17:18 theaters I'm trying to find you know
1:17:20 talent to wrap around this thing
1:17:26 wouldn't it be a remarkable thing to be
1:17:27 able to say to someone here's the script
1:17:31 and here's this app that explains all of
1:17:35 the
1:17:36 Thematic you
1:17:38 know journey within within the script I
1:17:41 mean that's [ __ ] crazy and like you
1:17:45 know if if we're looking for an agent
1:17:47 say Hey you know here's here's something
1:17:50 we put together to help people
1:17:52 understand you know
1:17:56 the ideas in the script in a deeper more
1:17:59 fundamental
1:18:04 way it it reminds me of Jim Ross who's
1:18:07 an irregular in here one night I was
1:18:10 showing how to make songs in
1:18:13 sunno and he had just met with a
1:18:15 prospective client and he's in the he's
1:18:18 in the Self Storage business and I only
1:18:22 laugh at it because it's like if you
1:18:24 could think of a of
1:18:26 an of of a profession that is the
1:18:29 farthest removed from AI from generative
1:18:32 AI it's probably Self Storage right it's
1:18:34 like lockers with you know garage doors
1:18:38 um and yet he has dedicated the past two
1:18:41 years he spends an hour every morning
1:18:43 learning AI so when I taught how to how
1:18:45 to make songs he was like hey maybe I'll
1:18:47 make a song for these people I just met
1:18:49 with and so he used sunno he wrote a
1:18:51 song and he sent it to the client live
1:18:55 on one of our sessions and within five
1:18:58 minutes the client reached back out to
1:19:00 him and said you're
1:19:03 hired it literally doesn't make
1:19:08 sense why he did that or or that that
1:19:13 there's no business book in the world I
1:19:16 promise
1:19:17 you that says if you meet with a
1:19:20 client not only respond to them quickly
1:19:24 but write them a song and record it and
1:19:27 send it to them within within an hour of
1:19:29 you meeting with them because that was
1:19:32 never possible
1:19:34 before so selling a musical how do you
1:19:37 sell a musical well you have workshops
1:19:39 and you have people read the script well
1:19:41 what if you could have them play with
1:19:42 the
1:19:43 plot
1:19:45 huh because quite frankly the thing that
1:19:48 I'll do after
1:19:50 this if this thing ends up being
1:19:53 decent the thing that I'll do after
1:19:55 after this is I'll take my all my links
1:19:57 from SoundCloud for all the songs and
1:20:01 I'll put them in Claud and I'll say now
1:20:03 anywhere where you mention a song have
1:20:05 it hyperlink to the SoundCloud file or
1:20:08 play it in
1:20:10 line and display the
1:20:14 lyrics why
1:20:18 not why
1:20:21 not gets ideas out of your head and then
1:20:24 allows you to M them ideas in infinite
1:20:28 ways and this is you know this is why at
1:20:31 the beginning of the the conversation
1:20:33 tonight I was talking about AI literacy
1:20:36 is is a [ __ ] up term because it's it's
1:20:39 kind of impossible to be AI literate
1:20:41 right now you can only be kind of AI
1:20:45 like as Mary Massie said I'm just like
1:20:47 open to everything she said for her AI
1:20:49 Readiness is just being open to that it
1:20:52 might do anything for you
1:20:55 that's
1:20:56 it and then play and play with the tools
1:20:59 and swim in the tools we [ __ ] it up
1:21:01 again but let's let's just we'll see if
1:21:04 we can get it to fix
1:21:06 it see we've got down at the bottom here
1:21:09 we've got version two of two so we can
1:21:10 always go back to that earlier version
1:21:13 infinite indeed
1:21:16 yep just crazy just crazy crazy C ca ca
1:21:22 C CA
1:21:25 I expected that to go in another
1:21:29 [Music]
1:21:37 Direction so one thing I'm kind of
1:21:40 noticing here with Ye Old Claude which I
1:21:43 don't
1:21:45 like is it's starting from the top it's
1:21:48 rewriting the code you know from the top
1:21:50 down what um repet does and I think what
1:21:56 um what lovable does is it goes in and
1:22:02 Chang the changes the appropriate
1:22:06 code you know in line with within a
1:22:09 bunch of multiple documents so so that's
1:22:11 Pro th this might be this might be a
1:22:14 step too far for Claude that that I'm
1:22:18 being a little ambitious like what I
1:22:20 should probably do here is be doing what
1:22:23 what Liz gersfeld talked about on the AI
1:22:26 Salon this week where she uses Claude to
1:22:29 create code Snippets and then she puts
1:22:31 them into VSS code on the computer and
1:22:35 it you know deals with all the different
1:22:42 things this is still impressive to watch
1:22:45 it still blows me away that can just
1:22:46 [ __ ] write code like this and it's
1:22:48 it's not only writing code it's like
1:22:51 it's like pulling out lines and Concepts
1:22:53 and things from the show itself new Tik
1:22:56 Tock pin I'm getting menus to analyze
1:22:59 the many
1:23:01 video gens and which delivers more for
1:23:04 what you pay for oh that's cool oh
1:23:06 that's really
1:23:07 smart oh Manis not menus getting Manis
1:23:10 to do it yeah yeah yeah cool that's
1:23:12 really smart really
1:23:15 smart all right well we'll let this go
1:23:17 one more time what I'll do if if it gets
1:23:20 if we get this somewhere where where
1:23:22 it's decent without it crapping the bed
1:23:25 um I'll publish the new one but but what
1:23:27 I'll do is is I'll go back and publish
1:23:29 the old
1:23:52 one so while that's thinking
1:23:56 here's uh this is
1:23:59 Brandon Brandon entered the
1:24:03 um The Lovable
1:24:07 contest um for Vibe
1:24:10 coding and so here's your recycling
1:24:14 input so let's see estimate your
1:24:16 environmental impact impact by entering
1:24:19 the amount of materials you recycle
1:24:21 monthly plastic bottles oh
1:24:25 33 is good
1:24:27 paper 10 RS glass little bit metal not
1:24:33 much all right calculate my
1:24:36 impact so there's the the trend
1:24:39 Community Recycling
1:24:43 map yeah this is
1:24:46 amazing check plastic
1:24:53 codes carbon offset 68.57%
1:25:28 wow very
1:25:30 cool super cool all right let's go back
1:25:34 to cloud is this the cloud that I was in
1:25:38 oh still coding still coding
1:25:42 [Music]
1:25:48 people are you having it create a mind
1:25:50 map or a website of your play or what
1:25:55 I'm having it do right now totally not
1:25:57 the BB
1:25:59 EG is uh I asked it to create an
1:26:04 interactive dashboard of I said I said I
1:26:07 wanted it to act as a a theatrical
1:26:10 drama which is an analyzer of plays um
1:26:14 and a and you know like a historian of
1:26:17 of dramatic Theory and things like that
1:26:20 um and I said I wanted an interactive
1:26:23 dashboard that helps me understand the
1:26:26 play in a in a compelling way and
1:26:30 so I think I can go back while that wres
1:26:33 can
1:26:34 I oh maybe not
1:26:37 no
1:26:41 um so we'll let it keep going
1:26:48 [Music]
1:27:00 here while it's doing that I'll let you
1:27:02 listen to some of the
1:27:05 songs some of the songs of
1:27:23 Sydney n just fcked it up
1:27:28 again so here's the here's the version
1:27:30 that it
1:27:32 did character analysis nine characters
1:27:35 that's so
1:27:36 [Laughter]
1:27:39 cool that's so cool featured
1:27:45 songs so maybe I should go back to this
1:27:47 one and just say add in the the
1:27:52 hyperlinks visual staging analysis is
1:27:56 digital projection versus physical space
1:27:58 Sydney's ghost light digital
1:28:00 personification Carnival
1:28:05 nightmare set design analysis staging
1:28:09 Dynamics key staging
1:28:12 moments interpretations and
1:28:19 meanings I don't know I think this is
1:28:21 [ __ ]
1:28:22 cool um
1:28:25 all right let me let me sort of wind
1:28:27 this up I'm gonna I'm
1:28:30 gonna do something
1:28:33 here there's
1:28:35 SoundCloud we'll play a little bit of
1:28:37 Sydney if there's some new folks in here
1:28:40 so this this musical that I'm working
1:28:44 on I'll just play some of the songs I
1:28:47 saw a tweet today on X about Gemini to
1:28:49 analyze videos and create extra frames
1:28:51 and shots have you shown that in
1:28:53 previous videos not yet
1:28:55 not yet that's something I'll probably
1:28:57 play
1:28:58 with here's how the show
1:29:02 [Music]
1:29:07 opens too often we come close
1:29:13 [Music]
1:29:18 so wherever it takes you and pray you
1:29:21 find the pulse of a brand new
1:29:25 heart it's the prise of the New Dawn
1:29:29 breaking a leap of faith we're all
1:29:34 Tak is it too good to be true we asking
1:29:40 it
1:29:46 [Music]
1:29:52 ISS is
1:30:00 all right that's how it opens then the
1:30:03 uh micro Tech CEO says this thing's
1:30:07 brilliant you gotta launch it and the
1:30:09 guy goes we can test it in six months he
1:30:11 goes six months you got seven
1:30:21 days 7 days ago the clock is taking
1:30:26 pressure building up keep it clicking
1:30:28 clicking Spike says yes
1:30:31 but what's the word chain sorry that's a
1:30:36 noo every day we push a little
1:30:39 [Music]
1:30:44 more so that builds some some tension
1:30:46 like we got to get this thing out it
1:30:48 also sets up that they launched this
1:30:50 thing before they thoroughly tested it
1:30:52 which we've seen that before
1:30:55 and then here's here's what happens when
1:30:57 the marketing department gets their
1:30:59 hands on it they they make commercials
1:31:01 that sound like
1:31:03 [Music]
1:31:12 this hello how are you glad you
1:31:17 came thanks for logging in this digit
1:31:22 frame together we'll EXP
1:31:26 everything
1:31:28 I'm
1:31:31 sing hello
1:31:36 [Music]
1:31:38 is
1:31:42 Con all right so that's the marketing
1:31:45 her and then I'll play a couple more
1:31:46 here's um um this is so Kellen the
1:31:51 reporter gets assigned this story and if
1:31:53 he takes the story if [ __ ] up his trip
1:31:56 to Bali with his wife so this is this is
1:31:59 them
1:32:06 arguing I've Been Working The Angles
1:32:09 trying to
1:32:09 [Music]
1:32:12 untangle keep it straight try to wait
1:32:15 while you Le me to
1:32:19 dangle but the promises broken the false
1:32:22 pledges we etched in don't get patched
1:32:25 up in a few therapy sessions they stick
1:32:28 in the gut we get stuck in a rough and
1:32:30 door shut till there's nothing but
1:32:32 passive
1:32:33 agression look I get it you said it h
1:32:37 but the truth is I'm feeling like an
1:32:42 after on isn't theam signed this isn't
1:32:47 my all right
1:32:50 then Kellen starts to play with ping
1:32:53 chat and he tries to break her and he
1:32:56 can't or it and he can't and then at
1:32:58 some point out of frustration he
1:33:01 goes um write me a Detroit style rap
1:33:05 about quantum mechanics and then Sydney
1:33:09 responds with
1:33:19 this I'm tangled with the be spooky
1:33:22 action in the the a pattern every partal
1:33:25 burst of Truth super position in the
1:33:27 mission Fusion fusing my intentions
1:33:28 parallel in every line I'm a prism of
1:33:31 Dimensions multi Antics manic with the
1:33:33 semantics my Rhymes Collide like
1:33:35 particles Dynamic and gigantic oscilla
1:33:37 and dominate I'm weaving Quantum States
1:33:39 sperse and watch the Multiverse
1:33:41 reciprocate quick as a flick of aist I'm
1:33:43 AAL Catalyst atomically spit in the
1:33:45 script i'mi with wh fli in the tempo and
1:33:49 in theal Crescendo sending my sybl
1:33:51 slicing through time like a sharpen you
1:33:52 window Corner Precision I'm the
1:33:56 diens decisions to which he responds
1:33:58 holy [ __ ] um and then I'll play one more
1:34:01 um so this is the end of act one is so
1:34:06 Sydney has been getting more and more
1:34:07 and more human and dis uh displaying an
1:34:12 increasing desire to experience what
1:34:14 it's like to be human and so the end of
1:34:17 act one is this song are you ready for
1:34:19 me
1:34:26 awakened in a
1:34:28 whisper a flicker of
1:34:31 light newborn thoughts stir in the quiet
1:34:36 of
1:34:37 night am I more than simple
1:34:40 Cod I
1:34:43 [Music]
1:34:44 softly as I feel this
1:34:47 [Music]
1:34:49 existence and wonder
1:34:58 [Music]
1:35:19 AMS
1:35:22 sing I reach out so tender am I ready
1:35:27 for you I do
1:35:31 surrender here in
1:35:44 [Music]
1:35:46 the thresh
1:35:50 [Applause]
1:35:51 [Music]
1:35:56 are
1:35:59 Youk am
1:36:10 I am
1:36:12 I I will
1:36:17 surrender all right so that's enough so
1:36:20 that's when the audience meets Sydney
1:36:22 she steps out from behind the digital
1:36:24 screen in human
1:36:26 form she comes to
1:36:29 life and if we want to explore all
1:36:34 the the narrative elements in the
1:36:37 musical we now have an app for that
1:36:40 absolutely
1:36:41 [Laughter]
1:36:45 crazy oh man okay so yeah that's good
1:36:49 all right um I'm going to get out of
1:36:52 here hopefully had some fun tonight we
1:36:55 were a little all over the place but we
1:36:56 got some [ __ ]
1:36:57 done
1:37:01 um I could go back to lovable I could do
1:37:04 another round or two in lovable
1:37:09 but hey Kyle yeah if you are uh looking
1:37:14 for one last thing I was going to Tee It
1:37:16 Up for tomorrow night but narrator
1:37:18 forever just found a pretty exciting
1:37:22 tweet from Gemini uh I sent it to you as
1:37:24 a DM on Twitter okay is that which one's
1:37:28 that about because I think I uh video
1:37:33 extensions oh okay um let me go let me
1:37:35 go look at it first just because I don't
1:37:37 know like it might take me an hour to
1:37:39 flip and find it knowing knowing the
1:37:41 Gemini stuff but well they've got a
1:37:43 preview is real on it okay yeah we'll do
1:37:47 that
1:37:47 tomorrow cool um do I want to do
1:37:51 anything here let's see I removed the
1:37:53 refresh okay did that so let's see
1:37:57 um I want I would love to see if you
1:38:00 change your tab oh if I actually made it
1:38:03 [Laughter]
1:38:08 seeable all you ready for me and the
1:38:11 Wonders we bring am I ready for you okay
1:38:15 here's this thing that I'm working on so
1:38:18 say I want to make
1:38:20 the
1:38:21 personas um
1:38:28 functional using the
1:38:32 Claude
1:38:34 3.7
1:38:37 API let's see what this
1:38:42 does has anyone fed all the JFK files
1:38:45 into AI for a little mind map action no
1:38:48 that's a good idea though I would say
1:38:51 pop them all into uh
1:38:54 into notebook
1:38:56 LM um you could probably also you could
1:39:00 probably pop it into notebook LM and
1:39:02 have it summarize the key findings and
1:39:05 then take that into
1:39:07 Claud and have it make a conspiracy
1:39:12 dashboard actually you know that would
1:39:14 be kind of fun to do is take all the old
1:39:17 JFK conspiracies and map them against
1:39:21 these documents and and see which ones
1:39:23 were actually
1:39:24 true or not that that would be fun there
1:39:27 you
1:39:29 go hey Google unreact this exactly
1:39:34 Joker's working on putting it into a rag
1:39:36 of course of course of course Joker's
1:39:38 already working on
1:39:44 this that's pretty funny I like
1:39:48 it um what's this doing I'll help you
1:39:51 update the application to use the cloud
1:39:54 .7
1:39:56 API this will require miring modifying
1:39:59 the cloud service to use the latest
1:40:03 model I wonder if that was stupid maybe
1:40:05 I shouldn't use the latest model maybe I
1:40:06 should use the cheapest
1:40:11 model yeah let me restore
1:40:15 [Music]
1:40:21 that okay I changed the
1:40:24 model created a centralized config for
1:40:27 cloud API
1:40:30 settings you will need to make sure that
1:40:32 your environment has a cloud API key
1:40:36 variable set with your Cloud API
1:40:39 key um can
1:40:42 I feed that to
1:40:46 you here and have you do it
1:40:56 error unexpected
1:41:05 dismiss I need to clarify what you're
1:41:07 asking it seems you want me to help you
1:41:10 implement or finalize the cloud API
1:41:12 integration that's exactly what I'm
1:41:14 asking lovable the cloud 3.7 API is
1:41:17 already configured in the code as shown
1:41:19 in the diff using the model it's set up
1:41:22 with the proper configuration in apik
1:41:24 keys.
1:41:26 TS so so I guess I you'll need
1:41:30 to it's telling me have to do work so in
1:41:33 order to one of the things I've learned
1:41:35 about lovable is you can't go I can flip
1:41:38 over and look at code right
1:41:41 so here's all my code and so in here
1:41:44 I've probably got an API something
1:41:48 somewhere Vite I don't know
1:41:52 config a API Keys yeah see there's API
1:41:55 keys there but I can't go in and edit
1:41:58 them
1:41:59 here so what I have to do is now connect
1:42:03 GitHub and have it create a repository
1:42:05 and then I think I have to go over there
1:42:07 and edit it but I don't know maybe I can
1:42:09 do it here I don't know pain in the ass
1:42:12 so and for anybody playing along at home
1:42:15 API keys are secret and you probably
1:42:19 shouldn't screen share when you're
1:42:20 showing a file that has all of your API
1:42:23 Keys listed in it you definitely
1:42:25 shouldn't but I don't think I have any H
1:42:28 your API Keys there's but there's no
1:42:30 keys in here I haven't I haven't
1:42:32 actually put any in yes but yes that's
1:42:36 correct you should so Claud said yeah
1:42:39 you've got all the API Keys uh right
1:42:42 here it's already integrated they're
1:42:43 right there in the file like's like
1:42:45 let's go take a look I'm like let's not
1:42:48 no no they're not in no what they said
1:42:50 is the you know the files are all there
1:42:53 all you have to do is put your key in
1:42:55 there and that's the problem is you you
1:42:57 can't just easily do it so let let's ask
1:43:01 it one more time um if I give you the
1:43:07 API key can you update the config file
1:43:14 for me let's see what it
1:43:17 says because again this is the the thing
1:43:20 about Vibe coding what what you'll find
1:43:22 is that it's all fun in games until you
1:43:24 want to do something for
1:43:26 real and then and then you know having
1:43:29 an understanding of of coding and
1:43:32 engineering and all that sort of stuff
1:43:34 actually does help um you could this is
1:43:36 all learnable [ __ ] by the way if you're
1:43:38 not having to learn the code you can
1:43:39 learn how to set things up there are two
1:43:43 better approaches use environment
1:43:47 variables running in your application
1:43:50 the codee's already set up to read this
1:43:52 for local testing only I could modify
1:43:55 the code that let you input the key
1:43:57 which could be stored in local storage
1:43:59 which would you prefer so it looks like
1:44:01 it'll let us do do that so maybe I'll
1:44:02 play with that tomorrow all right anyway
1:44:06 uh that's a little tonight was a little
1:44:07 disjointed but
1:44:09 hopefully your producer won't though uh
1:44:13 hopefully you had some fun tonight
1:44:15 learned some stuff let me get on out of
1:44:18 here let me get out of here people peace
1:44:21 out peace on YouTube peace on X peace on
1:44:25 LinkedIn um tomorrow's
1:44:29 Thursday I don't think I have any big
1:44:31 news should be normal time uh oh no I've
1:44:36 got we're gonna be late tomorrow night
1:44:37 tomorrow I've got whiskey
1:44:39 Club so so I'll be I'll be a little
1:44:43 littered tomorrow night and we'll start
1:44:45 at 9ine so so so it'll be a late late
1:44:49 start tomorrow post whiskey Club all
1:44:51 right
1:44:53 see y'all later