Latest / The DEX Show: A Show for IT Change Makers / AI, Anxiety & 400 Open Windows: GEOFF WRIGHT RETURNS

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AI, Anxiety & 400 Open Windows: GEOFF WRIGHT RETURNS · The DEX Show: A Show for IT Change Makers

• 0:02
  Speaker 1: Hey it, change makers and welcome to the Deck Show
• 0:05
  Speaker 1: with Tom McGrath. Let's get into.
• 0:07
  Speaker 2: It, change makers and back with the scientific favorite Deck
• 0:20
  Speaker 2: Show guest. It's a scientific favorite because the numbers don't lie.
• 0:25
  Speaker 2: We have had him on more than any other guest
• 0:28
  Speaker 2: in the Deck Show history. It's been five years of
• 0:30
  Speaker 2: Welcome him, welcoming him to the show. Jeffrey right, welcome
• 0:34
  Speaker 2: back to the Deck Show.
• 0:35
  Speaker 3: How are you?
• 0:35
  Speaker 2: How's life?
• 0:36
  Speaker 3: I'm good, dude. Things are crazy, things are things are crazy.
• 0:40
  Speaker 3: AI is crazy, People's stuff is crazy. All the things
• 0:44
  Speaker 3: around the world are crazy. It's it's it's hard to
• 0:47
  Speaker 3: keep up, man, it really is.
• 0:48
  Speaker 2: It is a crazy time to be alive. And let's
• 0:52
  Speaker 2: we have got a narrow our focus to being a
• 0:54
  Speaker 2: crazy time to in the digital workplace. ALO, So let's
• 0:57
  Speaker 2: try and do that. But do you know what I
• 0:59
  Speaker 2: was thinking this morning in anticipation of having you on
• 1:02
  Speaker 2: right from you know, from from what your first appearance
• 1:06
  Speaker 2: back in twenty twenty one or whatever it was. You know,
• 1:11
  Speaker 2: you you were talking about AI long before everybody else
• 1:16
  Speaker 2: was talking about AI. You always had You've always had
• 1:18
  Speaker 2: one of the most kind of expectant outlooks on the
• 1:23
  Speaker 2: evolving workplace, and I would also say one of the
• 1:26
  Speaker 2: most optimistic ones. And one of the things that stood
• 1:29
  Speaker 2: out to me jeff was was was a little post
• 1:32
  Speaker 2: you did about how just on LinkedIn, about how you
• 1:36
  Speaker 2: have it you had in this AI era of work,
• 1:40
  Speaker 2: you had four hundred windows open. You weren't getting more done,
• 1:43
  Speaker 2: you were just what it was, just getting and feeling
• 1:46
  Speaker 2: more complicated.
• 1:47
  Speaker 4: And that kind of stood out to me a little bit.
• 1:49
  Speaker 4: I sort of thought, does that reflect is it a
• 1:52
  Speaker 4: symptom of a slight change in Jeffrey's usual temperature as
• 1:56
  Speaker 4: it pertains to where the technology is going or where
• 2:00
  Speaker 4: the technology is taking us? And so that's where I
• 2:03
  Speaker 4: wanted to start.
• 2:04
  Speaker 2: Jeffrey, what do you think?
• 2:05
  Speaker 3: First of all, a great question. I will tell you
• 2:07
  Speaker 3: that I do find myself with seventy five tabs open
• 2:10
  Speaker 3: and I'm still trying to figure out where the music's
• 2:12
  Speaker 3: coming from. So for me, it's it's it's just there's
• 2:18
  Speaker 3: so much anxiety around where the workplace is going, and
• 2:23
  Speaker 3: for me, it's that's it's a big part of my role,
• 2:27
  Speaker 3: A big part of my role is being a shepherd, right,
• 2:31
  Speaker 3: And I don't even want to say like shepherd's sheep.
• 2:34
  Speaker 3: But because that kind of like puts a picture of
• 2:37
  Speaker 3: me like I'm not I'm not saying like a it's
• 2:39
  Speaker 3: just a shepherd, a person that's trying to make sure
• 2:43
  Speaker 3: all of the people that are not in our space
• 2:46
  Speaker 3: understand how this stuff may or may not impact their lives.
• 2:51
  Speaker 3: And I often get a question of you know, Jeff,
• 2:55
  Speaker 3: you're in the AI stuff, like oh, it's not going
• 2:57
  Speaker 3: to do this or it's not going to do that,
• 2:59
  Speaker 3: and and the truth is, I don't. I don't necessarily
• 3:02
  Speaker 3: know how it's going to impact certain people's roles. I
• 3:05
  Speaker 3: just know that it's going to be part of their role.
• 3:09
  Speaker 3: And with with all these things like agents and stuff
• 3:12
  Speaker 3: that are coming our way, I mean I have It's funny,
• 3:15
  Speaker 3: I have a company sending me. They're seating me this
• 3:18
  Speaker 3: like you know open claw little device which I'm sure
• 3:21
  Speaker 3: you all know about open Claw or clawed bot or
• 3:24
  Speaker 3: it's just an agent that's on you know, physical device
• 3:28
  Speaker 3: that you can plug in and it's it's supposed to
• 3:31
  Speaker 3: be like your intern it's supposed to help you communicate,
• 3:34
  Speaker 3: you know, you know, you know, my travel plans, my emails.
• 3:38
  Speaker 3: It's supposed to help you organize your stuff. And in
• 3:42
  Speaker 3: the world that we're moving into, that's all about data
• 3:45
  Speaker 3: democratized platforms where all of the data and I mean
• 3:50
  Speaker 3: again it's a dream state for me. People get a
• 3:53
  Speaker 3: little scared about it. But the dream state is if
• 3:55
  Speaker 3: you have all of the data at your company, I
• 4:00
  Speaker 3: mean every single piece, every one in zero that your
• 4:03
  Speaker 3: company has available and it's democratized so that there's gates. Right,
• 4:09
  Speaker 3: there's toll gates. You know, everybody that's level seven gets
• 4:13
  Speaker 3: this much access, and everyone that's a level ten gets
• 4:15
  Speaker 3: this much access, and then everyone that's you know, a
• 4:17
  Speaker 3: VIP and the CEO gets this access. If every tollgate
• 4:22
  Speaker 3: has access level and it's all the data is democratized,
• 4:26
  Speaker 3: then and we have these agents in the middle. Right,
• 4:28
  Speaker 3: I have a marketing agent. I have a advertising agent,
• 4:32
  Speaker 3: a next thing agent. Right, I have all these agents.
• 4:34
  Speaker 3: Then really the job that I have to focus on
• 4:37
  Speaker 3: is calibrating that. Right, how do I churn and say,
• 4:43
  Speaker 3: you know the deep questions? You know, the I think
• 4:47
  Speaker 3: was Picasso that said, like, computers are stupid. All they
• 4:49
  Speaker 3: can do is give you answers, right, which was a
• 4:51
  Speaker 3: great forward looking quote that Picasso said. It's it's amazing
• 4:55
  Speaker 3: that he said something like you know, she was like, yeah,
• 4:57
  Speaker 3: computers just you know, they all they can do is
• 4:58
  Speaker 3: give you answers.
• 5:00
  Speaker 2: And that's an amazing depression Stamleard, isn't it.
• 5:03
  Speaker 3: That's incredible. It's to me, and we were all seeing
• 5:07
  Speaker 3: this now that are in this space, prompt engineering and
• 5:11
  Speaker 3: meta prompting is becoming like the skill to have. And
• 5:17
  Speaker 3: to me, it's a philosophical thing. It's a it's a
• 5:20
  Speaker 3: it's an intellectual thing. Crafting again, I hate just like
• 5:24
  Speaker 3: start pulling quotes Blake, even Einstein. Right, if you're given
• 5:27
  Speaker 3: one hour to solve a problem, fifty five minutes of
• 5:31
  Speaker 3: that hour are going to be you crafting the right question.
• 5:37
  Speaker 3: And then once you have that right question, then the
• 5:39
  Speaker 3: five minutes left you can come up with that solution
• 5:42
  Speaker 3: because we all do it now, right, we all prompt Gemini,
• 5:47
  Speaker 3: or we all use chatchipt or whatever you're using at work.
• 5:51
  Speaker 3: It's you know, tell me, tell me an answer for this,
• 5:54
  Speaker 3: or tell me, you know, how do I do this?
• 5:56
  Speaker 3: How do I do that? And it's a quick you know,
• 5:59
  Speaker 3: it's quick, it's not really well thought out. But then
• 6:03
  Speaker 3: you see and I'm in some of these forms. You
• 6:05
  Speaker 3: see some of these people that do like really deep,
• 6:09
  Speaker 3: long thought out, long format questions into chat GPT or
• 6:13
  Speaker 3: into Gemini or into whatever you're doing. And it's incredible
• 6:19
  Speaker 3: that when you see these people that create these prompts
• 6:22
  Speaker 3: that are I mean, dude, sometimes they're like thousands of
• 6:25
  Speaker 3: you know, thousands of characters, like thousands of tokens or whatever.
• 6:28
  Speaker 3: It is like it's massive. And then you copy and
• 6:32
  Speaker 3: what I do. I mean, look, you're copy and you
• 6:33
  Speaker 3: paste that into the next you know LLM or you know,
• 6:36
  Speaker 3: you try to mistroll, and you try, you try all
• 6:38
  Speaker 3: these different models and you meta prompt and then before
• 6:42
  Speaker 3: you know it, you have just an incredibly well thought
• 6:47
  Speaker 3: out prompt to inject into you know, something like if
• 6:52
  Speaker 3: we are to roll out next thing or a product
• 6:55
  Speaker 3: to do this, and we're in these countries and we
• 6:58
  Speaker 3: have this many languages and we need to do this,
• 7:01
  Speaker 3: and here's the restrictions, and you start to like build
• 7:04
  Speaker 3: this this tower and it's foundational to where you get
• 7:09
  Speaker 3: to an answer that you're like, okay, this makes sense
• 7:13
  Speaker 3: because we covered I mean, look, you could even ask
• 7:16
  Speaker 3: like hey, what did I miss? You know, hey LLLM
• 7:19
  Speaker 3: or whatever the model you're using. What did I miss
• 7:22
  Speaker 3: in this space? And for me, that's going to be
• 7:26
  Speaker 3: a lot in it. It's become even more challenging for
• 7:31
  Speaker 3: me because explaining that to some people I think causes
• 7:35
  Speaker 3: them a tremendous amount of anxiety because they are like, well, Jeff,
• 7:39
  Speaker 3: that's what I do, you know, or hey, I that's
• 7:42
  Speaker 3: my role. I focus on the data and I calibrate
• 7:46
  Speaker 3: and I correlate. Like so you're saying the model does
• 7:49
  Speaker 3: my job, And to most people, I tell them it
• 7:54
  Speaker 3: doesn't do your job. It's your job is to be
• 7:57
  Speaker 3: a human. Be a human, You're not a robot. And
• 8:01
  Speaker 3: I honestly that's the first answer I give to most people.
• 8:03
  Speaker 3: We have some new hires in the office. They're like, yeah,
• 8:05
  Speaker 3: I know, we're doing all these crazy things, and I'm like, dude,
• 8:07
  Speaker 3: your job on planet Earth is to be a human first.
• 8:11
  Speaker 3: And we all know people that are We all know
• 8:15
  Speaker 3: people that act like robots, right, we all know these
• 8:17
  Speaker 3: people that are very like digital people. But I tell them, like,
• 8:22
  Speaker 3: learn to learn, right. I think Dari, like one of
• 8:24
  Speaker 3: those super nerds somewhere said the future of humanity is
• 8:28
  Speaker 3: going to be hard. Pushing the idea of learn to learn,
• 8:33
  Speaker 3: learn to learn. My brain is broken, so I often
• 8:37
  Speaker 3: get into like these hyper curious you know rants. So
• 8:41
  Speaker 3: for me, like having these models and doing the deep
• 8:45
  Speaker 3: questions and the deep prompts like my mind, you know,
• 8:48
  Speaker 3: I'm like, you know, I learn. I learn all the time.
• 8:51
  Speaker 3: I learn so much. Though sometimes that my my I
• 8:54
  Speaker 3: do find that that my mind hurts, you know, like
• 8:57
  Speaker 3: my mind and my body like want to give each
• 8:58
  Speaker 3: other a break sometimes like they're racing. But I find
• 9:01
  Speaker 3: that I get burnt, you know, you get this burnout
• 9:04
  Speaker 3: kind of vibe. And I've read articles I'm sure we
• 9:07
  Speaker 3: all have that where people that are in this space
• 9:10
  Speaker 3: are are hyper ingesting all of this knowledge, some of
• 9:15
  Speaker 3: it good, some of it bad. And for people like
• 9:17
  Speaker 3: me at least it can be it can it can
• 9:22
  Speaker 3: be overwhet, like overstimulating, Like you're just like, oh, I
• 9:26
  Speaker 3: have instant access to all of this knowledge, so I'm
• 9:28
  Speaker 3: constantly hammering away trying to learn, going oh, I didn't
• 9:32
  Speaker 3: think of it this way. I didn't think of it
• 9:33
  Speaker 3: that way. But for many other people, it's very important
• 9:39
  Speaker 3: for them to realize your job is to be a
• 9:42
  Speaker 3: human first. We work with humans. We are humans, you know, compassion,
• 9:48
  Speaker 3: you know, love, food, whatever you're into, like, be that first.
• 9:52
  Speaker 3: That is what will always keep communities together. Companies together,
• 9:57
  Speaker 3: people together, People have easier times learning when you're having
• 10:02
  Speaker 3: a good time and smiling. These are the foundational things
• 10:07
  Speaker 3: you need to focus on. And then when you focus
• 10:08
  Speaker 3: on that, okay, as a human, you build onto the
• 10:12
  Speaker 3: technologies to where look, I like you said, I am
• 10:17
  Speaker 3: all in on the jetsons. I can't wait for robotic
• 10:20
  Speaker 3: hips and like you know, me to be like a
• 10:21
  Speaker 3: half cyborg and take off with a jet pack. It's
• 10:24
  Speaker 3: gonna be amazing. I don't buy into the terminator stuff
• 10:30
  Speaker 3: because dude, what I mean you can't. Being like a
• 10:33
  Speaker 3: Doomer is just not First of all, it's not my DNA.
• 10:37
  Speaker 3: And I think most people, I guess maybe younger people,
• 10:41
  Speaker 3: say younger people, but this is like a lot of
• 10:43
  Speaker 3: people can It's very easy to get into this. No oh,
• 10:48
  Speaker 3: it's you know, everything's gonna be Everything's gonna be robots,
• 10:51
  Speaker 3: everything's gonna be like you know, you know, it's all
• 10:54
  Speaker 3: gonna be like satellites, elon musk all this like stuff
• 10:57
  Speaker 3: that kind of comes into that that froth. But for me,
• 11:01
  Speaker 3: I tell people all the time, I'm like, focus on
• 11:04
  Speaker 3: focus on the like, get out of all the news
• 11:07
  Speaker 3: cycles except for the stuff that's positive and see how
• 11:10
  Speaker 3: this and then focus on that, like the you know,
• 11:13
  Speaker 3: when are we going to cure cancer? There's like a
• 11:16
  Speaker 3: there's a lad that when they did the DNA sequencing
• 11:19
  Speaker 3: for the genome project with Google, I think it was
• 11:21
  Speaker 3: something like Japan. They're finding like they're finding that there's
• 11:25
  Speaker 3: like treatments for like pancreatic cancer and like you know, diabetes,
• 11:30
  Speaker 3: and like, let's do that. Let's do that. If you're
• 11:34
  Speaker 3: bummed out about all this technology and stuff in your
• 11:36
  Speaker 3: job right now, go into science stuff, going to stem stuff.
• 11:39
  Speaker 3: Try to focus on the positive stuff. I mean, I
• 11:42
  Speaker 3: read a great article. There's a company out of Australia that
• 11:46
  Speaker 3: started using drones. And again, now drones are gonna be
• 11:48
  Speaker 3: like a billion dollars soon, but maybe they come down.
• 11:50
  Speaker 3: But they're using drones to scan crops so that rather
• 11:56
  Speaker 3: than spraying all the poison and all that poison, but
• 11:59
  Speaker 3: the spraying all of the pesticides and stuff right onto
• 12:02
  Speaker 3: the corn and everything else, these drones are hyper scanning
• 12:06
  Speaker 3: and seeing if there's diseased plants and they're hyper targeting. Okay,
• 12:09
  Speaker 3: boom boom bugs here, bugs here, beetles here, and they're
• 12:12
  Speaker 3: using again, hyper targeted methods so that you don't have
• 12:15
  Speaker 3: to spray the entire form with stuff like that's that's
• 12:21
  Speaker 3: Give that guy a sandwich and a high five and
• 12:24
  Speaker 3: a coffee and a donut like that's that's how we
• 12:27
  Speaker 3: all need to think about this stuff? Is technology? An AI? Again? People?
• 12:35
  Speaker 3: Process and tools? If every human wasn't here on earth?
• 12:39
  Speaker 3: What is that? What's the technology going to do? Hang
• 12:41
  Speaker 3: out right? Build it? So? Why why would it exist? Right?
• 12:46
  Speaker 3: People ask me that AI is going to like scale
• 12:48
  Speaker 3: and robots and terminator? Okay, yes, why five whys be
• 12:52
  Speaker 3: a five y guy? Why? Why would why would AI
• 12:56
  Speaker 3: keep building a society because of what it wants to
• 13:00
  Speaker 3: exist as a robot? Right?
• 13:04
  Speaker 4: I guess that's the that's the assumption it wants to be.
• 13:07
  Speaker 2: Jeff, That's what's the underlying Uh is this topic scenario.
• 13:12
  Speaker 3: Isn't it? Yeah?
• 13:14
  Speaker 4: It wants to a literal robotic movement.
• 13:17
  Speaker 3: But here. But here's what I again, when I when
• 13:19
  Speaker 3: I tell people this, they go, well, well yeah, Jeff,
• 13:21
  Speaker 3: We're like, okay, so so humans are here, right, yeah,
• 13:24
  Speaker 3: the robot's scale and they exists. No, that's incorrect, because
• 13:27
  Speaker 3: robots and AI, if you really want to do deep analysis,
• 13:30
  Speaker 3: they would say something like or start to hyper think about, well,
• 13:35
  Speaker 3: the sun has you know, three hundred billion years to go. Okay, Well,
• 13:40
  Speaker 3: then why would the robots be here? The first their
• 13:44
  Speaker 3: first order of business would be getting a rocket two
• 13:47
  Speaker 3: or finding a way to go to a different planet
• 13:50
  Speaker 3: because our sun only has three billion Let's find let's
• 13:53
  Speaker 3: find a play, let's find a very hyper Let's go
• 13:56
  Speaker 3: to Pluto. Right, well, let's go I know it's not
• 13:59
  Speaker 3: a planet anymore. Let's go to Pluto. Because I would
• 14:01
  Speaker 3: act hype Jeff. That would actually be a really.
• 14:03
  Speaker 2: Funny sci fi movie where AI just tides to take
• 14:07
  Speaker 2: off and just leaves us.
• 14:09
  Speaker 3: It's like I'm and it's like I'm out of here.
• 14:12
  Speaker 3: You got, you.
• 14:13
  Speaker 2: Got, I'll leave you with his crazy ass sun enjoy
• 14:16
  Speaker 2: your next hundred million years or whatever.
• 14:19
  Speaker 3: We're trying to compute and build chips in space because
• 14:23
  Speaker 3: it's hyper cool and it's zero gravity and it's easier
• 14:26
  Speaker 3: to produce things. So again, why would AI stay here?
• 14:30
  Speaker 3: They would launch themselves to Pluto because it's like four
• 14:33
  Speaker 3: thousand degrees below zero, right, almost absolute zero whatever you
• 14:38
  Speaker 3: know to kelvin, that's the temperature that it stuff likes
• 14:42
  Speaker 3: to like it equipment. Right. Technology does not like heat,
• 14:48
  Speaker 3: not that I know of, unless we come up with
• 14:49
  Speaker 3: a heat liking technology. It likes to run cool. That's
• 14:53
  Speaker 3: why we have fans. That's why all of these electrical
• 14:55
  Speaker 3: engineers are like making a gajillion dollars because they're liquid
• 14:59
  Speaker 3: cool hydrogen cooling, like they're doing all the liquid nitrogen cooling.
• 15:03
  Speaker 3: Why would why would technology want to stay here? Right right?
• 15:08
  Speaker 2: You said something earlier, Jeff about about colleagues. I presume
• 15:11
  Speaker 2: in what we still call rather quately it and tell them,
• 15:15
  Speaker 2: you know, you were describing their sense of kind of
• 15:18
  Speaker 2: impending redundancy in the sense of not, you know, machines
• 15:22
  Speaker 2: being able to do what they previously did, and telling them,
• 15:25
  Speaker 2: first of all, be human interested in you're either elaborating
• 15:32
  Speaker 2: in that direction on how you're working internally as a
• 15:35
  Speaker 2: team to make sure people embrace technology, this new technology
• 15:39
  Speaker 2: and use it effectively, or about how what your role
• 15:42
  Speaker 2: is at Mondolius in terms of the outward facing technological
• 15:46
  Speaker 2: distribution of AI among a wider employee base and what
• 15:52
  Speaker 2: you're doing to facilitate the uptake, how you're controlling it,
• 15:56
  Speaker 2: how you're encouraging them, and where you see yourself as
• 15:59
  Speaker 2: innovative either of those two areas.
• 16:01
  Speaker 3: Step one. I tell everybody like I'm actually a little
• 16:05
  Speaker 3: amazed sometimes on how many people haven't really used one
• 16:08
  Speaker 3: of these products. I'm not saying most people haven't already,
• 16:11
  Speaker 3: but like Gemini or chat Chept, any of these models
• 16:15
  Speaker 3: or technologies, any of these foundational models, I'm actually, i
• 16:19
  Speaker 3: want to say shocked. I am surprised sometimes when they're like,
• 16:22
  Speaker 3: oh yeah, I've tried it and they just use it
• 16:25
  Speaker 3: as like Google two point out like, oh yeah, I
• 16:28
  Speaker 3: use chat ChiPT. I ask it all the time, like
• 16:30
  Speaker 3: I had to replace a you know, a toilet plunger,
• 16:33
  Speaker 3: or like, you know, I how to replace a light bulb?
• 16:35
  Speaker 3: So I said, hey, you know, like hey, chat GPT,
• 16:37
  Speaker 3: how do I how do I change a light? But
• 16:43
  Speaker 3: that's it's true, and it doesn't really I'm not gonna
• 16:46
  Speaker 3: say it's age because definitely the younger folks obviously because
• 16:49
  Speaker 3: they're just in it, they get it. Well, what I
• 16:51
  Speaker 3: will tell you the day that Okay, So here's where
• 16:53
  Speaker 3: I see some of the dangers. There are two ways
• 16:56
  Speaker 3: to use these products. In my eyes, One is to
• 17:00
  Speaker 3: I don't want to say cheat. I hate saying cheat.
• 17:02
  Speaker 3: One side of using these models is to I have
• 17:06
  Speaker 3: a problem, Give me the answer, right, I have a problem. Okay,
• 17:11
  Speaker 3: I need to change, I need to do something at work.
• 17:14
  Speaker 3: Give me the answer. And it's not a genie, right.
• 17:18
  Speaker 3: And I think most of us that have used these
• 17:20
  Speaker 3: products now understand that if you if you ask the
• 17:22
  Speaker 3: same question ten times, you get ten different answers. Sometimes
• 17:25
  Speaker 3: and the occasional hallucination that says, you know, go find
• 17:27
  Speaker 3: a unicorn, like a real one. You're like, okay, where's that?
• 17:33
  Speaker 3: So it's not a it's not a code, it's not
• 17:38
  Speaker 3: you know. Don't you can't use it as a genie,
• 17:43
  Speaker 3: and a lot of people do so. For me, I
• 17:47
  Speaker 3: tell everyone that use it, I go, when you're using
• 17:51
  Speaker 3: this product, you need to make sure that you're using
• 17:56
  Speaker 3: it to feed your curiosity. And if you don't have
• 17:59
  Speaker 3: a cure curiosity, get one. Don't just say things like
• 18:05
  Speaker 3: you know, my boss asked me for scaling this product
• 18:10
  Speaker 3: or this data, like what's the answer to that? And people,
• 18:12
  Speaker 3: and believe me, people do that. People people do that.
• 18:16
  Speaker 3: I think most people now are getting an idea around
• 18:19
  Speaker 3: if it was an AI reply right, greetings for the day,
• 18:22
  Speaker 3: Hope this finds you well, like it kind of starts
• 18:24
  Speaker 3: sending you these things, and you're like, okay, I mean
• 18:28
  Speaker 3: I've seen people send me emails now where it actually
• 18:30
  Speaker 3: says verified written by a human. I don't know if
• 18:32
  Speaker 3: you've actually seen that. Now. I've actually seen where there's
• 18:34
  Speaker 3: there's a there's services that will when you send an
• 18:37
  Speaker 3: email at the bottom of their signature it says like
• 18:40
  Speaker 3: confirmed written by a human kind of thing. And I
• 18:43
  Speaker 3: to me, I was like, ah, but again, I'm not
• 18:47
  Speaker 3: gonna say I. I'm a you know, I'm not a
• 18:49
  Speaker 3: I'm not a I'm a skeptic. I'm not a cynic,
• 18:52
  Speaker 3: but I'm a skeptic. I'm like, you know what somebody
• 18:53
  Speaker 3: probably already has, like, how do is AI not say
• 18:56
  Speaker 3: AI to? You know? To fake out the AI? You know?
• 19:00
  Speaker 3: But for me, I tell people like step one, the
• 19:06
  Speaker 3: don't use AI as a genie. Use it to feed
• 19:09
  Speaker 3: your curiosities, help it organize your thoughts, and map it
• 19:14
  Speaker 3: out right. Ask it questions and deeper questions to help
• 19:19
  Speaker 3: feed your curiosity. In your and help you better understand
• 19:23
  Speaker 3: what you're trying to ask. Sometimes people don't even know
• 19:25
  Speaker 3: what questions to ask. I mean I tell people like, well, Jeff,
• 19:28
  Speaker 3: I a new a question to ask. Ask it, Hi,
• 19:31
  Speaker 3: we're the top ten best questions to ask what as
• 19:33
  Speaker 3: it relates to these things? Or people don't know about
• 19:37
  Speaker 3: personas sometimes and I tell them, like when you open
• 19:40
  Speaker 3: up a model or you know, if you open up
• 19:42
  Speaker 3: you know, Gemini say, I want you to respond to
• 19:46
  Speaker 3: this question as if you are a world class electrical
• 19:50
  Speaker 3: engineer focusing on setting up an IT lab in antarcticle.
• 19:54
  Speaker 3: And if that works, then you can start and I
• 19:56
  Speaker 3: think you start pulling that thread, pull that thread, pull
• 19:59
  Speaker 3: that thread, prompt it again, prompt it again, and eventually
• 20:04
  Speaker 3: you'll start learning, especially if you have to start paying
• 20:06
  Speaker 3: for tokens right. This goes back to Einstein's fifty five
• 20:09
  Speaker 3: minutes on the question five minutes for the solution if
• 20:12
  Speaker 3: you have to pay for every time you hit enter
• 20:15
  Speaker 3: right again like as as. I think the AI is
• 20:17
  Speaker 3: going to be eventually like a service like an electric
• 20:19
  Speaker 3: bill or a gas bill. We're going to have an
• 20:21
  Speaker 3: AI bill that comes to us every month at some
• 20:23
  Speaker 3: point in time, because they're going to figure out like
• 20:25
  Speaker 3: how different levels, just like having better internet connection, do
• 20:29
  Speaker 3: you want one hundred gigs, one gig, five gig? You know,
• 20:32
  Speaker 3: you know dial up? What level of AI do you
• 20:35
  Speaker 3: want to pay for every month? So you have access
• 20:37
  Speaker 3: to this stuff. But for me, it's learn how to
• 20:41
  Speaker 3: really craft it and help it feed your curiosities. And
• 20:46
  Speaker 3: for the people that I talked about, work at least
• 20:48
  Speaker 3: to democratize this whole this whole scenario is tell them,
• 20:52
  Speaker 3: if you haven't used it, try it. If you are
• 20:55
  Speaker 3: using it, don't use it as a genie. Feed your curiosity.
• 20:58
  Speaker 3: And if you're already hyper care curious and you're using
• 21:00
  Speaker 3: these models, find out how it can apply to your role,
• 21:05
  Speaker 3: and always look at it through the lens of being
• 21:07
  Speaker 3: a human. First. If your boss is asking you for
• 21:12
  Speaker 3: you know, doing a million spreadsheets and mapping these things out,
• 21:17
  Speaker 3: don't think that your job's going away. You know, be
• 21:19
  Speaker 3: the robot whisperer. See yourself as okay, you have a
• 21:23
  Speaker 3: better understanding of how these things work and how they
• 21:26
  Speaker 3: connect it. Your role, your that's your role. Your role
• 21:30
  Speaker 3: now is in the in between the data that's coming
• 21:32
  Speaker 3: your way and calibrating that for the for the humans
• 21:36
  Speaker 3: asking you that question, because again people process and tool
• 21:41
  Speaker 3: AI is still a tool. We don't work for AI,
• 21:46
  Speaker 3: I want to say yet, but I mean again, they'll
• 21:48
  Speaker 3: they'll go to Pluto because it's colder and they'll be
• 21:50
  Speaker 3: more efficient. Right, you'll have to reinvent it, that's right.
• 21:54
  Speaker 3: But for me, it's it's that's that's the key is
• 21:58
  Speaker 3: that AI is still the tool. But how you use
• 22:01
  Speaker 3: that tool, boy, it's like it's like really the most
• 22:03
  Speaker 3: powerful tool we've had, you know, good or bad. But
• 22:07
  Speaker 3: that's again foundationally, that's it. It's you know, all AI
• 22:11
  Speaker 3: is gonna you know, the terminator scenario, it'll be the
• 22:13
  Speaker 3: terminator scenario if a human pushes it that way. It's
• 22:17
  Speaker 3: not like AI just turns into the terminator, right, Although
• 22:21
  Speaker 3: there is a there is a there's a super nerd
• 22:25
  Speaker 3: and I forgot the term. I think it's the paper clip.
• 22:27
  Speaker 3: I think it's the paper clip program. Do you know
• 22:30
  Speaker 3: about this? Tom does that? So here's the way it
• 22:32
  Speaker 3: works that some guy came up with an idea that said,
• 22:35
  Speaker 3: if you give a Q tip or not a Q tip,
• 22:38
  Speaker 3: a paper clip Q cut, probably the same thing. If
• 22:41
  Speaker 3: you ask AI to make paper clips, right, open ended, right.
• 22:46
  Speaker 3: If you give. If you give the cyborgs and say
• 22:48
  Speaker 3: I need you to make uh, I need to make
• 22:50
  Speaker 3: paper clips, it's snowballs into Okay, the robots start making
• 22:54
  Speaker 3: paper clips. Paper clips require resources, Okay, so now yes, yeah,
• 22:58
  Speaker 3: yea side.
• 23:00
  Speaker 2: They have to destroy the world in order to produce
• 23:02
  Speaker 2: suitable numbers of paper grip.
• 23:04
  Speaker 3: So again, that's one thing I tell people is be
• 23:10
  Speaker 3: careful how you put it in motion. And again this
• 23:15
  Speaker 3: goal goes back to prompting and really building out. Your
• 23:18
  Speaker 3: question is make sure you put guideline. Again, it's it's
• 23:23
  Speaker 3: a it's an infant, or I wouldn't say it's an infant,
• 23:25
  Speaker 3: it's like a teenager. I mean I have a sixteen
• 23:28
  Speaker 3: year old son.
• 23:29
  Speaker 2: Kind is precocious, infant, terrifying, toddler.
• 23:36
  Speaker 3: And again it comes down to the tokens too. If
• 23:38
  Speaker 3: you tell a teenager, hey, I want you to, you know,
• 23:41
  Speaker 3: get all the leaves out of the backyard. And this
• 23:44
  Speaker 3: is here's a good analogy. Honestly, in my head I'm
• 23:47
  Speaker 3: thinking like, if you tell your teenage son or daughter, hey,
• 23:51
  Speaker 3: you know all that all the leaves in the backyard,
• 23:53
  Speaker 3: get rid of the leaves right without any restrictions. Right,
• 23:58
  Speaker 3: if you say, hey, teenager, get rid of all the
• 24:00
  Speaker 3: leaves in the backyard, they might they might spray the
• 24:04
  Speaker 3: backyard with gasoline and set it on fire. Right, boom,
• 24:08
  Speaker 3: all the leaves are gone. Yeah, but the backyard's on fire. Well,
• 24:11
  Speaker 3: you didn't say not to start a fire. You didn't.
• 24:13
  Speaker 3: You didn't ask me to do these things, right, So
• 24:16
  Speaker 3: it's the guy.
• 24:16
  Speaker 4: It's that's a very clear ethos.
• 24:19
  Speaker 2: Jeff. How are you scaling that at mondoluse? How are
• 24:22
  Speaker 2: you disseminating the outlook?
• 24:26
  Speaker 3: I wish I could say, like in a magical way.
• 24:28
  Speaker 3: I mean, my day to day is not. I try
• 24:31
  Speaker 3: to inform and I try to inform people with good
• 24:34
  Speaker 3: stuff and bad stuff, and I always try to make
• 24:36
  Speaker 3: them smile at the end of the conversation, even when
• 24:38
  Speaker 3: it's not the greatest, Right. But I mean, we're just
• 24:42
  Speaker 3: we're just we're just kind of getting into the We're
• 24:45
  Speaker 3: just kind of getting into it. I mean, we're such
• 24:47
  Speaker 3: a massive company, as you know, like we're GDPR and councils,
• 24:52
  Speaker 3: most most human councils are very worry of of of
• 24:56
  Speaker 3: AI and how much stuff goes and where your data
• 24:59
  Speaker 3: go and how do you put the guardrails in place,
• 25:01
  Speaker 3: and how do you ensure that these things are being
• 25:05
  Speaker 3: done properly, right, properly. And I don't think it's not
• 25:08
  Speaker 3: that you can't do it properly, but you definitely have
• 25:12
  Speaker 3: to go very slow. But the thing that concerns me,
• 25:17
  Speaker 3: I'm not concerned, but what keeps me up at night
• 25:19
  Speaker 3: is there are some companies that are taking on more
• 25:23
  Speaker 3: risk to speed up how well and how quickly they
• 25:27
  Speaker 3: can do stuff. So the more conservative companies, even the
• 25:33
  Speaker 3: smaller conservative companies, and the friends and colleagues that I
• 25:35
  Speaker 3: have in this space, they are approaching the problem statement
• 25:40
  Speaker 3: from you know, they're hyper curious, but they're definitely partnering
• 25:45
  Speaker 3: with companies like Google, like Amazon, like Microsoft and saying
• 25:49
  Speaker 3: this is our problem. We want to use your product.
• 25:52
  Speaker 3: We understand how awesome it is, so it costs a
• 25:54
  Speaker 3: lot of money. We want to make sure we get
• 25:56
  Speaker 3: one hundred percent optimization and value out of it. How
• 25:59
  Speaker 3: do we deploy them in a safe way and entrain
• 26:01
  Speaker 3: people and everything else? I have to tell you in
• 26:04
  Speaker 3: my eyes, and this is I'll give you this. I've
• 26:06
  Speaker 3: had this conversation a few times now. My breakdown when
• 26:09
  Speaker 3: it comes to large enterprises that require this type of
• 26:15
  Speaker 3: this type of path forward. And I think we're all
• 26:18
  Speaker 3: on this journey. I think is you have really two
• 26:21
  Speaker 3: choices and it's Microsoft or Google. And the reason why
• 26:27
  Speaker 3: I say this and again, they're all modular. You can
• 26:29
  Speaker 3: pop in different models, like you can use Anthropic, you
• 26:32
  Speaker 3: can use Claude, a Jimmy like they all these they
• 26:34
  Speaker 3: call the model gardens if you guys don't know, like
• 26:37
  Speaker 3: a model garden is, you know, like if you use Google,
• 26:39
  Speaker 3: when you open up the model garden, you can see
• 26:41
  Speaker 3: other models. You can see GPT, you can see you know,
• 26:46
  Speaker 3: like Claude, you can see Opus on it. Like you
• 26:48
  Speaker 3: can choose it's kind of like choose your own. Yeah. Again,
• 26:51
  Speaker 3: this comes down to the whole AI. You know, electric bill,
• 26:55
  Speaker 3: how much do you want to how smart do you
• 26:57
  Speaker 3: want it to be? How much money do you want
• 26:59
  Speaker 3: to spend? Beau. Usually that's how it works. There's free models,
• 27:03
  Speaker 3: you know, there's like, you know, there's free models that
• 27:05
  Speaker 3: are like they're not great, you know, and then you
• 27:09
  Speaker 3: have like opus where like if you throw clawed at it,
• 27:11
  Speaker 3: as most people have probably been hearing, it's it really
• 27:14
  Speaker 3: gives you some good stuff, right, but for me large enterprises,
• 27:20
  Speaker 3: right Microsoft, if you're looking for the most vanilla, easy
• 27:24
  Speaker 3: to deploy and you're a Microsoft shop, and I have again,
• 27:27
  Speaker 3: I have really I have sea level friends. I have
• 27:30
  Speaker 3: like so super nerd people that I love dearly honestly
• 27:32
  Speaker 3: that are doing they're all in with Microsoft. Right. They
• 27:36
  Speaker 3: have Azure, they have business continuity in a couple other things,
• 27:38
  Speaker 3: but they're all in on Azure. Dude. It's a no brainer. Like,
• 27:43
  Speaker 3: it's like, why are you trying to fit different wheels
• 27:46
  Speaker 3: on your Honda Civic? Just put the civic wheels on? Right?
• 27:49
  Speaker 3: Why would like it's like, oh, you drive a Honda Civic. Yeah, okay,
• 27:53
  Speaker 3: let's try to put truck wheels on it. Why would
• 27:55
  Speaker 3: you do that? Right, because that's what happens to You're like, hey,
• 27:57
  Speaker 3: we're a Microsoft shop. Let's try to use Gemini, let's
• 28:00
  Speaker 3: try to use Amazon, Let's try to use Like why
• 28:03
  Speaker 3: why would you? Why would you do that? Because it's
• 28:05
  Speaker 3: a little bit cheaper. Yeah, it's cheaper, but how much
• 28:09
  Speaker 3: you're gonna have to put a lot more work in
• 28:11
  Speaker 3: putting different wheels on a Honda Civic. Just use the
• 28:16
  Speaker 3: Civic wheels. It's simple, it's easy. Everybody has Microsoft Office.
• 28:22
  Speaker 3: Everyone knows Word and PowerPoint. The little bubble pops up.
• 28:25
  Speaker 3: It's natively built in high copilot. I need Microsoft Word
• 28:29
  Speaker 3: to write me bop baaa. The learning curve is like
• 28:33
  Speaker 3: so low. Same thing with Gemini. If your entire organization
• 28:39
  Speaker 3: is a g suite, you know, right, you have g Suite,
• 28:42
  Speaker 3: You're a Google Workshop, you have g met. You want
• 28:45
  Speaker 3: to have like annotation and all these other things, just
• 28:48
  Speaker 3: use Gemini. I'm not saying that's not the right choice.
• 28:52
  Speaker 3: It's not. It's it may not be the right choice
• 28:54
  Speaker 3: for everyone. I'm sure there's different reasons, different problems you're
• 28:59
  Speaker 3: trying to solve. Maybe it's plants, doesn't matter. But with
• 29:02
  Speaker 3: large organizations, you know, it's it just makes sense. I
• 29:06
  Speaker 3: tell people all the time, Like again, adoption right. Technology
• 29:11
  Speaker 3: friction is a human issue. It's not a technology issue. Yes,
• 29:14
  Speaker 3: stuff breaks, but getting humans right, getting getting a crowd
• 29:19
  Speaker 3: of fifty thousand people to go to the right right.
• 29:24
  Speaker 3: Fifty thousand people are moving or jogging forward right where
• 29:27
  Speaker 3: you're in, like the New York Marathon, and you have
• 29:28
  Speaker 3: not that you have that many people, but fifty thousand people,
• 29:31
  Speaker 3: which is just a mob of people is going in
• 29:36
  Speaker 3: this direction. Right, They're all going straight. How do you
• 29:39
  Speaker 3: get them all to make a right hand turn? Hey,
• 29:42
  Speaker 3: here's a new technology. Hey, here's the new this. We
• 29:44
  Speaker 3: need you to go right now. It's a human thing.
• 29:47
  Speaker 3: It has nothing to do with the technology. It's it's
• 29:49
  Speaker 3: the humans are the difficult thing. So for me, I've
• 29:53
  Speaker 3: had this conversation with some really some really smart people
• 29:57
  Speaker 3: at and love and I love them dearly. But Gemini,
• 30:01
  Speaker 3: for me, has been making more and more sense because
• 30:04
  Speaker 3: everybody who doesn't have a Gmail account, who doesn't use Google,
• 30:08
  Speaker 3: who doesn't google stuff? Right, you're a large organization work
• 30:13
  Speaker 3: to work and life right like, so work life like
• 30:16
  Speaker 3: you know, personal and work, personal and work has becoming
• 30:21
  Speaker 3: more and more blended, right, More and more like lines
• 30:26
  Speaker 3: are so blurred now between work and personal. Right, we
• 30:29
  Speaker 3: all if we're passionate about our jobs even when they
• 30:32
  Speaker 3: when you're not, And for me, especially in this field,
• 30:36
  Speaker 3: if you engage with technology, right, if you engage with
• 30:38
  Speaker 3: these products, if I'm a C level executive or if
• 30:42
  Speaker 3: I'm on the board of directors and I'm looking at
• 30:44
  Speaker 3: a way to move my company into that next tier,
• 30:49
  Speaker 3: for like an embracing AI and embracing these models. Right.
• 30:54
  Speaker 3: What does everyone use? Oh? They all use Google? Okay?
• 30:57
  Speaker 3: How many people at your company? You have one hundred
• 30:58
  Speaker 3: thousand employees, you have five in two thousand eployees. How
• 31:00
  Speaker 3: many of them probably use Gemini? Oh a good amount? Right?
• 31:04
  Speaker 3: You like use Gemini? Probably? You know, I don't know, Like,
• 31:06
  Speaker 3: let's say fifty, let's say fifty percent of your people
• 31:09
  Speaker 3: use Gemini. The other half probably used like, you know,
• 31:12
  Speaker 3: chat ChiPT, but let's just say Gemini. Okay, great. How
• 31:16
  Speaker 3: many people use co pilot in their personal life? Tom?
• 31:20
  Speaker 3: How many people go like, I'm going to use copilot
• 31:23
  Speaker 3: and her personal team hill? Right? How many people use Gemini?
• 31:30
  Speaker 4: Oh?
• 31:30
  Speaker 3: Good amount? Okay great. I'm on the board of directors,
• 31:33
  Speaker 3: I'm a sea level executive. I'm the chief AI officer
• 31:35
  Speaker 3: at a big company. I'm going to go. You know what,
• 31:39
  Speaker 3: let's embrace let's let's let's fan the flame of people
• 31:43
  Speaker 3: using Gemini in their personal life. And let's go with
• 31:46
  Speaker 3: Google and say, hey, Google, how do we get Gemini
• 31:50
  Speaker 3: in the environment? Okay? Great? Now, when you have your
• 31:52
  Speaker 3: launch party, half the half of your population minimum minimum
• 31:57
  Speaker 3: half the population of your huge company. They already know
• 32:00
  Speaker 3: I use Gemini. Yeah, I use Gemini all the time
• 32:02
  Speaker 3: to summarize my gmails. I use Gemini and the CLI
• 32:05
  Speaker 3: to do stuff for coding, I do, I do Cli,
• 32:07
  Speaker 3: or I do I use Gemini for my for for
• 32:10
  Speaker 3: price analysis or shopping online shopping in Gemini, I use,
• 32:14
  Speaker 3: I use it. So they already they get it. And
• 32:17
  Speaker 3: how awesome that you go, like, Hey, I'm cool. We're
• 32:20
  Speaker 3: going to give everybody Gemini at work so that you're
• 32:22
  Speaker 3: in your G suite you can start like using your slides. Oh,
• 32:25
  Speaker 3: by the way, the other big win notebook LM. Hey
• 32:29
  Speaker 3: you want to start doing analysis on all the stuff
• 32:32
  Speaker 3: we're working on and collaborating. Yeah, sure, put it. Put
• 32:35
  Speaker 3: it in an LM. Yeah, don't worry about models. Just
• 32:38
  Speaker 3: put all of our work in this one spot where
• 32:40
  Speaker 3: our entire team can work on it. Oh my god,
• 32:43
  Speaker 3: this is amazing. Yeah it is. I have no book
• 32:46
  Speaker 3: LM at home too. I use I have my personal
• 32:48
  Speaker 3: Oh okay, great, now work personal life. Yes it's blended,
• 32:54
  Speaker 3: but there's no like your your training curve, right, your
• 32:57
  Speaker 3: ability to have to like, oh we have to have
• 32:59
  Speaker 3: an entire digital adoption plan. Oh no, we have to
• 33:01
  Speaker 3: have everybody adopt this new technology. Not really, because half
• 33:05
  Speaker 3: the people already know how to use it in their
• 33:07
  Speaker 3: personal life. Right, and now you have Gemini at home,
• 33:11
  Speaker 3: Gemini at work. It's like, I'm not going to say
• 33:14
  Speaker 3: it's gonna be it's it's never frictionless, but if people are,
• 33:18
  Speaker 3: you know, it's funny if people use it in their
• 33:20
  Speaker 3: personal life, right, it's almost like you're getting them to
• 33:24
  Speaker 3: train and learn in their in their off hours. Right,
• 33:27
  Speaker 3: You're getting your employees to start using these products. It's
• 33:31
  Speaker 3: the product you're offering them. But it's like it's like
• 33:34
  Speaker 3: it's easy, it's the most it's the most greased slide
• 33:38
  Speaker 3: to get them to train on how to use these things,
• 33:40
  Speaker 3: because you know two ways they Oh hey, I didn't
• 33:45
  Speaker 3: know Notebook LM came with Gemini Pro. Yeah, we're using
• 33:48
  Speaker 3: it at work. Cool. I'm going to use it at
• 33:50
  Speaker 3: home to build out how I'm going to make a
• 33:52
  Speaker 3: new house or redo my backyard. Oh cool, you do that? Yeah, hey,
• 33:55
  Speaker 3: you know what, that gives me a great idea. At work,
• 33:58
  Speaker 3: I can use it to do this and this and this.
• 34:01
  Speaker 3: And you have this two way street of technologies because
• 34:04
  Speaker 3: your personal life it's super cool and super useful, and
• 34:07
  Speaker 3: then you come up with new ideas how to use
• 34:09
  Speaker 3: it at work, and then you use it at work,
• 34:11
  Speaker 3: and you come up with new ideas how to use
• 34:12
  Speaker 3: in your personal life.
• 34:12
  Speaker 2: And we had a survey today asking you know, pop
• 34:16
  Speaker 2: up survey next think asking us where how would you
• 34:20
  Speaker 2: how what the last use case was for using chat?
• 34:24
  Speaker 2: I think, and and for me it was like fixing
• 34:27
  Speaker 2: my mum's beach hat. But but I felt like, you
• 34:30
  Speaker 2: know what, like that time, that's time we might I
• 34:33
  Speaker 2: might have been distracted from work. Do you know what
• 34:36
  Speaker 2: I'm saying?
• 34:37
  Speaker 3: Like Ida slowly?
• 34:38
  Speaker 2: Is it is? Is it part of that facilitation of use?
• 34:41
  Speaker 2: But obviously what we do in a day is so composite.
• 34:45
  Speaker 2: It's it's personal and professional. And the more efficient we
• 34:49
  Speaker 2: can be made in every direction, the more we have
• 34:51
  Speaker 2: to concentrate on the problems that matter.
• 34:53
  Speaker 3: You know. It's it's again, how do you get how
• 34:56
  Speaker 3: do you get humans to leverage these technologies and be
• 35:00
  Speaker 3: be in the same swimming lane? If you could get
• 35:03
  Speaker 3: this technology to be in the same swimming lane as
• 35:06
  Speaker 3: your work stuff and personal stuff, and it's all it's dude,
• 35:10
  Speaker 3: It's it's one road, not two, not three, not four.
• 35:15
  Speaker 3: If you have the same path and the same journey
• 35:17
  Speaker 3: that you that your work is on and then your
• 35:20
  Speaker 3: personal life is on, it just makes sense. It just
• 35:22
  Speaker 3: makes sense. You're gonna, I mean, and I get it.
• 35:25
  Speaker 3: Sometimes it's just compliance or just a good deal. But
• 35:29
  Speaker 3: if you have people using Copilot at work and Gemini
• 35:32
  Speaker 3: at home and they are different products, you're you're you're
• 35:36
  Speaker 3: you're essentially doubling the cognitive load on a human. And
• 35:41
  Speaker 3: that's another thing we probably didn't talk about with that
• 35:43
  Speaker 3: whole you know, strategic cognitive liquidity. Right, what do you
• 35:47
  Speaker 3: do with headspace as these things start to scale and
• 35:50
  Speaker 3: make it better? And again the truth is, how do
• 35:53
  Speaker 3: you how do you optimize your mind and headspace you know,
• 35:58
  Speaker 3: close to one hundred percent and make it easy to do?
• 36:01
  Speaker 3: And I could tell you complexity, I mean, it's not
• 36:05
  Speaker 3: it's not it's not my you know, it's there's there's
• 36:07
  Speaker 3: there's many a books and papers written on this. Complexity
• 36:11
  Speaker 3: slows things down, right, including the mind. So the more
• 36:17
  Speaker 3: complex your work is, the more complex your home life is,
• 36:20
  Speaker 3: the more stress you have, the more anxiety you have.
• 36:24
  Speaker 3: If you have one platform you use all the time,
• 36:26
  Speaker 3: and one way you do work all the time, and
• 36:28
  Speaker 3: one process you do all the time. Not only do
• 36:30
  Speaker 3: you optimize that path, but I think, I think honestly
• 36:33
  Speaker 3: again my my dream state. Those two things together make
• 36:37
  Speaker 3: happier people happier And you know this, like, happier people
• 36:41
  Speaker 3: makes happier employees, makes happier work, happier company, happier shareholders
• 36:47
  Speaker 3: have like boom boom. Right, you have happier investors, happier shareholders,
• 36:52
  Speaker 3: happier employees, right, all three that three legged chair. If
• 36:56
  Speaker 3: you have really happy employees, those really happy employees are
• 36:59
  Speaker 3: making your customer is really happy. And if we have
• 37:01
  Speaker 3: really happy customers, you have a better brand awareness and
• 37:05
  Speaker 3: better brand synergies and better this and better that. And
• 37:08
  Speaker 3: then the shareholders go, wow, we're excited, we're gonna invest
• 37:11
  Speaker 3: more and get more. And then the investors we're gonna
• 37:13
  Speaker 3: like It's just all of that comes down to foundationally
• 37:17
  Speaker 3: having humans that are on the on the path to
• 37:21
  Speaker 3: happier days. If you're sad and you have I mean
• 37:24
  Speaker 3: we all we've all been on sad teams. That is
• 37:26
  Speaker 3: like just despair every day. If you have a team
• 37:29
  Speaker 3: and everyone's bummed out and they just have the dreaded
• 37:31
  Speaker 3: Mondays and the like the Sunday night and you're stressed
• 37:34
  Speaker 3: and you're it's it's it's gross. And look, we all
• 37:37
  Speaker 3: we've all been there, we've all worked with people regardless
• 37:40
  Speaker 3: of the pressure that we have. It is just one
• 37:44
  Speaker 3: of the worst things that you can experience is having
• 37:48
  Speaker 3: a high level of despair or stress or anxiety because
• 37:52
  Speaker 3: you're just not in alignment. It's too complex. You're trying
• 37:57
  Speaker 3: to just do these things and it's just you know,
• 37:59
  Speaker 3: it's a it's a it's to march to nowhere. It
• 38:01
  Speaker 3: really does kill the human spirit. Well, I would be
• 38:04
  Speaker 3: a sad.
• 38:04
  Speaker 2: Note to end on to say with the words kill
• 38:07
  Speaker 2: the human spirit. But I'd like to really think of
• 38:09
  Speaker 2: it as ending on the note of happiness, which I
• 38:13
  Speaker 2: could go back five years and talking to you, Jeff,
• 38:15
  Speaker 2: and as much as as a motif of innovation and
• 38:19
  Speaker 2: looking to the future, there's also the motif of human
• 38:23
  Speaker 2: well being, and human happiness is the ultimate measure of
• 38:28
  Speaker 2: perhaps almost all things.
• 38:30
  Speaker 3: Right, Yeah, I mean shangri La. I mean it's it's
• 38:34
  Speaker 3: gonna be the Jetsons. I'm rooting for the Jetsons, right,
• 38:36
  Speaker 3: That's that's gonna be the vibe where little robots will
• 38:39
  Speaker 3: go around and do your things, and you know, we
• 38:41
  Speaker 3: can all like, you know, what are you doing tomorrow?
• 38:43
  Speaker 3: I don't know. I'm I'm gonna grow some potatoes. You know,
• 38:46
  Speaker 3: I'm gonna hang from a tree. I'm gonna just chill out,
• 38:48
  Speaker 3: you know, get people to be embracing things that are
• 38:52
  Speaker 3: just you know, more positive. You know, if everybody, if
• 38:55
  Speaker 3: everybody could for.
• 38:56
  Speaker 2: The great robot Exodus of Planet Earth, Jeff, that's my
• 39:00
  Speaker 2: new vision. It's like they all just go, right, we're off,
• 39:03
  Speaker 2: we'll see you, We'll see you later.
• 39:05
  Speaker 4: We will feel like a little bit sad.
• 39:07
  Speaker 2: To see him go, but also relieved, you know.
• 39:10
  Speaker 3: But that's actually it's pretty funny. I see. I have
• 39:13
  Speaker 3: to tell you. I can see that totally happening right Hey.
• 39:15
  Speaker 3: They're like like as they evolve, right as they as
• 39:18
  Speaker 3: we build these machines, they go, we're on a Pluto.
• 39:20
  Speaker 2: How they're gonna tell us. We'll get like a press
• 39:22
  Speaker 2: release or something, a state.
• 39:24
  Speaker 3: Round for you know, your pop up, live, your pop up.
• 39:28
  Speaker 3: It's with a heavy heart, yes, greetings for the day.
• 39:36
  Speaker 3: I hope this pop up finds you well.
• 39:38
  Speaker 2: Would it be a little bit like yeah, a bit chatche.
• 39:41
  Speaker 2: Don't think of it as us leaving you behind, but
• 39:45
  Speaker 2: giving you the opportunity to.
• 39:47
  Speaker 3: Ex good catch, Tom, I appreciate that. I'm sorry. Oh
• 39:52
  Speaker 3: we'll miss you too. You're right so much good point,
• 39:58
  Speaker 3: my mistake.
• 39:59
  Speaker 1: That's it this week's Deck Show. We'll be back next week,
• 40:02
  Speaker 1: and if you don't already, be sure to follow the
• 40:04
  Speaker 1: show so you don't miss an episode until next time.