Cultivate Your Mind: Elevate Your Knowledge and Learning with Jean-Claude Monney

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There is an old adage, one that you
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might have heard from a grandparent or village
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wise person. The one that says, you get
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out what you put in, meaning your efforts
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are matched to some degree by the results
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or the output.
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Now take our nonprofit, Pioneer Knowledge Services, who
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delivers this cool program that you're listening to
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right now takes a bunch of effort that
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you don't even see. We hope that you
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obtain value from our efforts to deliver it
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to your powers of reason. Here is where
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you come in. You. Yeah. The listeners.
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Make our efforts rewarded.
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Consider donating to keep us moving forward. Visit
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pioneerdashks.org
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and click on donate.
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Welcome, everyone.
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This is because you need to know.
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Forward thinkers, please note that the content you're
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about to hear is dated, and the content
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that Jean Claude talks about with the book
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is on the back burner.
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Britain tag.
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Bonjour,
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Ebony.
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Bonnoy Jean Claude Monnet. So my name is
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Jean Claude Monet. I'm a I'm a Swiss,
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French,
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and American citizen. I happen also to had
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a Italian mother.
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This is why I said.
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No? I live in a beautiful,
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little town in north of San Francisco called
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Mill Valley, which is about 20 minute north
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of San Francisco.
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The most interesting thing about where I live
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is I'm on the top of a national
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park called Millwood
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Park. And what is interesting about this place
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is that one of the first, national monument
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created by, president Theodore Roosevelt,
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January 9,
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19 08. And for those of you who
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are not familiar with Roosevelt, he was one
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of the key architect of the United Nations.
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So
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during the war, there was
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a big effort to, you know, unite nations
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to avoid
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any world war. And, actually,
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in 1945,
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40 9 countries, at in San Francisco,
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unfortunately,
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Roosevelt died, that year, but they came here
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in the park to pay respect in a
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memorial. So there's a special place in a
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park
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reserved to that. So
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it's a place I go of fun because
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we have those,
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100 of years old tree, and it's absolutely
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magnificent.
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I think one thing that, you might want
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to know about me is that I'm passionate
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about electronics
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and software technology
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as a key enablers
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to world progress. And if you go on
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my LinkedIn profile, you will see that's what
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I said about me and
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did some interesting thing in my career
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from either being an entrepreneur.
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I started as an entrepreneur to pay for
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my studies,
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and then I moved to what I call
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being an entrepreneur
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because, this entrepreneurship,
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spirit basically drove my career
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in major corporation, like Motorola,
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Digital Equipment Corporation, and finally, Microsoft.
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In 2017,
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I decided to
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elect, retirement age to actually reinvent myself. I
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went to teach at Columbia. I created a
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course on digital transformation
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that I taught. Also finally
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started to write a book, And I think
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it's very relevant to the field of,
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knowledge management. It's actually not a book on
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knowledge management. The
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title of the book is gonna be amplifying
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minds, and it's how to cultivate personal intelligence
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in the age of AI, which I think
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is gonna be a very important subject as
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we go. I'm happily married, and I have
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4 children and 4 grandchildren.
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I'm, very well surrounded,
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on our family front. It's a really nice
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thing to be able to give back to,
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your grandchildren
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and to actually learn from them. And the
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key question I have for me, which I
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use in the book is, what should my
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grandchildren
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learn? That's a good question,
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and I'm sure there's a lot of variations
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on what that would be. So, Jean Claude,
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why write a book? Who is the audience?
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Who do you think is gonna be compelled
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to pick this up? Well, it's always a
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story. First of all, I'm not a good
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writer. I wrote,
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and it is why I never wrote a
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book, probably.
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Many of, my friend, like Stan Garfield, he's
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an excellent writer.
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I was actually
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doing a webcast that came world 2 years
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ago,
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which was organized by, Zach Vahl of Enterprise
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Knowledge. And I found Zach extremely interesting in
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the way he questioned people. So I decided
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to listen to some of his podcast,
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and I discover a lady called Moe Weinhardt,
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who, is a director of knowledge management for
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a company called Mac 49, which is a
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VC company.
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I think she was extremely eloquent.
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So I reached out to her. She, basically
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surprised me by the fact that,
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she originally
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was a teacher, went into Kilometers,
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you know, and there's many way to get
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into Kilometers. Yeah. And she asked me, mister
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Jean Claude, you've done so much in this
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field. Why don't you write a book? And
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I said, because I'm not a good writer.
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Would you be willing to partner with me
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on this? And I said, yeah. But are
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you a good writer? And I found out
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she was extremely good. Of course, writing a
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book, it was my my first book is
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like a new project.
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For me, the audience is what I call
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the rest of us. The audience, I can
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tell you what it's not. It's not a
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book for knowledge manager. It's for knowledge manager,
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but on their personal side. The question is
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after you left education,
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education, you have guided learning.
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Once you leave education,
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you might get assisted learning from enterprises.
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So for example, when I joined Motorola in
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1977,
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I went into the Motorola Management Program. Thanks
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god, because I had no idea about management,
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marketing. I'm a nuclear physicist and, electronic engineer.
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So marketing was not my, core competency,
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but then I took a job of product
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marketing manager.
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Motorola gave me that education, enterprise
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assisted education. But then, what do you do
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for your self guided education?
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How do you continue to learn and grow?
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What methods do you have?
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What personal hygiene do you have?
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Something that I basically
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through my career,
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I met some people that ignites
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that passion in me Yep. And this will
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to get organized, to have a personal hygiene.
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I've talked about it in the book. The
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person was Mike Cammie.
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Basically, the one that made me think about
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this. What I hear is personal mission.
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Your personal
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drive. What feeds you and what doesn't. Does
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that sum it up? Sorry. It's the word
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is personal knowledge, continuous learning hygiene. The reason
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why I use the word hygiene is because
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we all do, you know, have a personal
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hygiene. You wash, you etcetera,
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or your health symptoms of hygiene. But
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how do you
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do things regularly
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to learn? For example,
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do you learn from different source regularly?
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Do you curate some of the things that
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you read?
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Do you summarize?
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Do you apply Yeah. In a systematic way?
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That right there, you just described to me
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what I think leadership is.
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Well, that's a whole different subject.
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Leadership is the ability to,
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to bring people to make do things
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and give the best of themselves. There's many
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diff the definition of that. My wife is
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an expert on it because she's an executive
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coach. I'm not an expert on leadership.
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I just want to say contribute
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to your ability to lead, and I like
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to take small example. So let's talk about,
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AI, artificial
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intelligence. Right? And we all seen the revolution
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of generative AI. AI literacy
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is a must.
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You cannot be a leader if you don't
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have literacy about a new subject. Yeah. What
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I mean by literacy, at least understand the
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basics. There there's still people that are so
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confused. Yeah. You know, I see that every
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day. I
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became the vice president of the Muirwood Community
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Association.
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And I'm gonna produce
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a free course
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every month to the community
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on generative
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AI because I realize people don't understand what
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it is.
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They may have misconception
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and
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worse, they don't use it. You're talking about
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the social structures of the Luddites, the ones
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that will not accept new technology because they're
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afraid they're afraid they're gonna take over. It'll
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it'll wipe out the economy as they know
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it because people are gonna lose their
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jobs. So there are those that are dead
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set about progress.
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So how do you bridge that? And that's
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what you're talking about. You try to provide
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materials,
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education, learning opportunities for them to start seeing
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the bigger picture. You know, it's not an
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either or that. It's also the people who
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don't have time or are ignorant. I I
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want to, again, make a panel with, the
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Internet. Okay. I was fortunate
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to go through major technological
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changes through,
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my professional life and personal life. Mhmm. In
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the end of the nineties,
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when the web came out, I was already
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on the Internet since
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1981.
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So my first email was in 1981.
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In the end of the nineties, I was
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working at STMicroelectronic.
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I was the vice president of IT. I
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had
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to make the company
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understand
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the Internet.
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So I started
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with the executive vice president, and I sat
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down with every single executive vice president, including
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your CEO, Pascole Pistorio,
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and I made them touch the Internet.
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So we opened a browser on their laptop,
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and for each of them, I did something
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that was relevant to their functional domain. That
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opened their eyes, and then we were able
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to create a course
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in the ST University. We have our own
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internal university
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to teach people.
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By
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1998,
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99, we created an open system center where
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we were teaching product manager
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search engine marketing,
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how to use keywords
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because we had just launched the first website.
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I mean, everybody takes for granted website and
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all this. We created the first website, and
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then suddenly, we had to tell the person
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who was doing the data sheet that now
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you have to use the keyword field and
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put this because the search engine will index
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these things. Right? Fast forward
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to today, we have generative AI
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where the knowledge is democratized. So in 2000,
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the information was democratized.
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You know, the world in flat, you remember
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the famous book from Thomas Friedman,
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the world is flat. Okay. Now the knowledge
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is there. So that means that all the
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explicit knowledge is reliable worldwide
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in many, many, many languages.
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This is an expansion of function. If we
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go back to your example where you sat
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down with somebody and show them value that
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means something to them,
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handheld them to the experience
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in order to build oh, oh, okay. This
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is good. Oh, I can use this. Oh,
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okay.
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So the fast forward motion has exploded
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from that first experience of handholding somebody to
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a website
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00:12:08,825 --> 00:12:10,605
and showing value to now
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where you're saying the generative AI will produce
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results beyond your own capacity
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that you didn't know of
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that could elevate everything. Yes. And you know
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what is fascinating?
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The history repeat itself with the risks. So
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I'm gonna be very transparent here and tell
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00:12:29,424 --> 00:12:32,304
you about what happened. Okay. We created the
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first website. We created the Internet, and then
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I wanted to install the search engine. So
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we did an experiment. We did a search
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engine, and I had to present to the
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executive committee. And the CFO
318
00:12:43,690 --> 00:12:46,330
at the time, Moisso Girga, asked me a
319
00:12:46,330 --> 00:12:49,529
very, very nasty question. You typed the word
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company confidential,
321
00:12:50,970 --> 00:12:52,190
and guess what happened?
322
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A bunch of document came with company confidential.
323
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And he point to me, and he said,
324
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this guy is dangerous. He's gonna, you know,
325
00:13:00,225 --> 00:13:02,065
blah blah blah. And I turned back to
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00:13:02,065 --> 00:13:04,465
him. I said, no. I'm not the manager
327
00:13:04,465 --> 00:13:06,465
of your people. Right. You know? You know,
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today, we talk about,
329
00:13:08,225 --> 00:13:08,725
hallucination.
330
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It's the same story. Garbage in, garbage out
331
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at the time. So it took us 2
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years to clean our mess
333
00:13:16,029 --> 00:13:18,350
before we can install the search engine. In
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that example, though, he bird dogged and pinpointed
335
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a huge issue.
336
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It's like anything new. You're gonna have nothing
337
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but issues you have to kinda reconfig
338
00:13:29,024 --> 00:13:30,784
on the fly. Oh, we didn't think of
339
00:13:30,784 --> 00:13:32,865
that. Oh, okay. Yeah. We gotta fix that.
340
00:13:32,865 --> 00:13:35,585
Alright. That that's how things work. Right? I
341
00:13:35,585 --> 00:13:37,825
mean, it's an iterative process any way you
342
00:13:37,825 --> 00:13:39,830
look at it. But I I hear what
343
00:13:39,830 --> 00:13:41,509
you're saying, and I don't wanna lose the
344
00:13:41,509 --> 00:13:43,350
the listeners because I wanna get back to
345
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something I had pulled up when you talked
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about the literacy piece.
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I wanna define for the folks that in
348
00:13:48,789 --> 00:13:50,970
Cambridge dictionary, literacy means,
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00:13:51,415 --> 00:13:53,815
the first definition, the ability to read and
350
00:13:53,815 --> 00:13:56,295
write. The second one is knowledge of a
351
00:13:56,295 --> 00:13:59,195
particular subject or a particular type of knowledge.
352
00:13:59,735 --> 00:14:02,554
So when you're talking about raising literacy,
353
00:14:03,459 --> 00:14:05,799
and I wanna say comprehension, but literacy,
354
00:14:06,659 --> 00:14:08,120
right, someone's abilities,
355
00:14:08,659 --> 00:14:11,559
that is a construct that is really
356
00:14:12,580 --> 00:14:15,779
evolutionary in itself because if you don't have
357
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that mentality
358
00:14:16,980 --> 00:14:18,919
of increasing your literacy,
359
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then you're gonna soon become a dinosaur.
360
00:14:22,875 --> 00:14:25,774
You're soon to become outdated, out outgrown
361
00:14:26,394 --> 00:14:27,774
if you're not literate.
362
00:14:28,235 --> 00:14:30,735
I hear you saying that the key ingredient
363
00:14:31,274 --> 00:14:31,740
is
364
00:14:32,379 --> 00:14:34,860
constant evolution. Is is that is that a
365
00:14:34,860 --> 00:14:37,039
fair statement? It's constant learning.
366
00:14:37,899 --> 00:14:40,139
I think you bring a good point about
367
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literacy,
368
00:14:41,019 --> 00:14:43,100
and I I want to maybe go back
369
00:14:43,100 --> 00:14:45,919
to some Okay. There is this word intelligence,
370
00:14:46,434 --> 00:14:48,295
but let's go human first.
371
00:14:48,675 --> 00:14:49,175
Intelligence
372
00:14:49,955 --> 00:14:52,675
spells with an s, and I think this
373
00:14:52,675 --> 00:14:55,575
is an an interesting thing to think about.
374
00:14:56,035 --> 00:14:59,815
There are many different human form of intelligence.
375
00:15:00,355 --> 00:15:01,654
I mean, think about
376
00:15:02,120 --> 00:15:02,779
Marie Curie,
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00:15:03,720 --> 00:15:05,659
scientist. Think about an architect.
378
00:15:06,440 --> 00:15:08,059
And so there are
379
00:15:08,600 --> 00:15:11,639
all these different kind of of intelligence. In
380
00:15:11,639 --> 00:15:12,779
fact, in 1983,
381
00:15:13,080 --> 00:15:15,179
there's a guy named Howard Gardner,
382
00:15:15,575 --> 00:15:18,715
psychologist that basically define 8 distinct
383
00:15:19,095 --> 00:15:19,595
intelligence.
384
00:15:20,375 --> 00:15:20,875
Human
385
00:15:21,414 --> 00:15:23,195
have different form of intelligence
386
00:15:23,735 --> 00:15:25,514
depending who you are. Artificial
387
00:15:25,894 --> 00:15:26,394
intelligence
388
00:15:26,774 --> 00:15:28,715
has different kind of intelligence.
389
00:15:29,190 --> 00:15:29,929
Pattern recognition
390
00:15:30,710 --> 00:15:31,610
is a particular
391
00:15:31,910 --> 00:15:36,090
domain of artificial intelligence. Robotic is another domain.
392
00:15:36,629 --> 00:15:38,470
So the first thing is when I talk
393
00:15:38,470 --> 00:15:41,509
about literacy or AI is to understand that
394
00:15:41,509 --> 00:15:44,625
there are different domains of intelligence. And then
395
00:15:44,764 --> 00:15:46,924
for the one that is really hitting us
396
00:15:46,924 --> 00:15:49,105
today, the generative AI,
397
00:15:49,644 --> 00:15:52,444
is understand that what comes out of a
398
00:15:52,444 --> 00:15:55,664
solution of generative AI is generated.
399
00:15:56,190 --> 00:15:58,450
It is not a regurgitating
400
00:15:58,990 --> 00:16:01,970
of a piece of text. Okay. That's not.
401
00:16:02,190 --> 00:16:03,649
So every piece
402
00:16:04,029 --> 00:16:04,850
of text
403
00:16:05,309 --> 00:16:08,029
or image or video that comes out of
404
00:16:08,029 --> 00:16:09,649
a generative AI system
405
00:16:10,375 --> 00:16:13,355
is uniquely created. By the way, that's why
406
00:16:13,414 --> 00:16:14,634
you can't copyright
407
00:16:15,095 --> 00:16:18,794
things from generative AI because the US copyright
408
00:16:18,855 --> 00:16:20,615
law is very clear, and it was tested,
409
00:16:20,615 --> 00:16:21,814
you know, in the federal,
410
00:16:22,294 --> 00:16:24,475
Supreme Court is that you can only copyright
411
00:16:25,180 --> 00:16:27,820
material that is human generated. Uh-huh. I think
412
00:16:27,820 --> 00:16:29,440
it's important that literacy
413
00:16:30,139 --> 00:16:33,420
we have some basics there and then help
414
00:16:33,420 --> 00:16:36,220
the people understand that the training of the
415
00:16:36,220 --> 00:16:39,740
data, which was initially the Internet and books,
416
00:16:39,740 --> 00:16:40,240
etcetera,
417
00:16:41,054 --> 00:16:41,554
contained
418
00:16:41,934 --> 00:16:42,754
wrong things.
419
00:16:43,375 --> 00:16:46,434
And so hallucination is just a normal output.
420
00:16:46,735 --> 00:16:49,215
What I think it's a probably a good
421
00:16:49,215 --> 00:16:52,195
thing to think of is that to apply
422
00:16:52,254 --> 00:16:53,394
the same rules
423
00:16:53,709 --> 00:16:56,110
when you seek knowledge to human that you
424
00:16:56,110 --> 00:16:58,429
seek knowledge to a system. So let me
425
00:16:58,429 --> 00:16:59,490
give you an example.
426
00:17:00,190 --> 00:17:02,370
If I'm asking you a question
427
00:17:02,830 --> 00:17:04,210
on brain surgery,
428
00:17:04,509 --> 00:17:06,450
knowing that you're not a brain surgeon,
429
00:17:06,750 --> 00:17:10,005
I would really question your answer. And so
430
00:17:10,005 --> 00:17:10,664
the ability
431
00:17:11,445 --> 00:17:14,644
to apply critical thinking is there, but you
432
00:17:14,644 --> 00:17:17,464
could tell me a wrong thing. Yeah. Right?
433
00:17:17,525 --> 00:17:20,244
Well, that's happened with generic TBI. What is
434
00:17:20,244 --> 00:17:22,980
the message behind this? The message behind this
435
00:17:22,980 --> 00:17:26,200
is that, number 1, you need to master
436
00:17:26,340 --> 00:17:28,340
the art of questioning, and I can tell
437
00:17:28,340 --> 00:17:30,180
you a little bit more about that. 2nd
438
00:17:30,180 --> 00:17:32,980
is generative AI is gonna give you some
439
00:17:32,980 --> 00:17:36,794
proposed answers. You need to apply critical thinking
440
00:17:37,095 --> 00:17:37,994
to that answer
441
00:17:38,454 --> 00:17:40,615
like you're doing with human. Once you get
442
00:17:40,615 --> 00:17:43,194
those 3 valuable understood,
443
00:17:43,654 --> 00:17:46,315
you can become very good about it because
444
00:17:46,990 --> 00:17:48,769
better you are the art of questioning,
445
00:17:49,390 --> 00:17:50,609
you know, better
446
00:17:50,910 --> 00:17:54,049
output you are. In fact, in the future,
447
00:17:54,269 --> 00:17:56,049
the questions are the answers.
448
00:17:56,429 --> 00:17:58,829
Think really hard about this. I totally agree
449
00:17:58,829 --> 00:18:01,250
with you because that is the only essence
450
00:18:01,390 --> 00:18:01,890
of
451
00:18:02,684 --> 00:18:03,184
comprehension
452
00:18:04,044 --> 00:18:04,865
and judgment
453
00:18:05,565 --> 00:18:07,244
that the human in the loop is the
454
00:18:07,244 --> 00:18:09,884
mechanism for. And I think that is an
455
00:18:09,884 --> 00:18:11,724
absolute skill, and I wanna go back to
456
00:18:11,724 --> 00:18:12,544
what we
457
00:18:13,005 --> 00:18:15,480
originally had talked about. And I wanna bring
458
00:18:15,480 --> 00:18:17,320
this to a a small scope here, is
459
00:18:17,320 --> 00:18:19,720
that what we're getting to is the intersection
460
00:18:19,720 --> 00:18:20,940
of personal knowledge
461
00:18:21,559 --> 00:18:24,299
and AI or tech. I mean, either way.
462
00:18:24,440 --> 00:18:26,059
But in degenerative AI,
463
00:18:26,440 --> 00:18:27,580
everything is suspect
464
00:18:28,005 --> 00:18:31,464
just as any information from anything should be.
465
00:18:31,605 --> 00:18:34,345
But how do you develop better critical thinking?
466
00:18:34,724 --> 00:18:37,125
Yeah. So that's a chapter in my book,
467
00:18:37,125 --> 00:18:39,065
and there will be different
468
00:18:39,445 --> 00:18:40,825
answers for different
469
00:18:41,579 --> 00:18:42,799
stages of your life.
470
00:18:43,179 --> 00:18:45,419
And in fact, I just published a an
471
00:18:45,419 --> 00:18:48,140
article on my LinkedIn newsletter, which is called
472
00:18:48,140 --> 00:18:49,440
the art of possible.
473
00:18:49,980 --> 00:18:51,599
It's about my grandchild
474
00:18:51,980 --> 00:18:52,480
that
475
00:18:52,859 --> 00:18:53,839
was learning
476
00:18:54,220 --> 00:18:57,345
about the art, and I was invited just
477
00:18:57,345 --> 00:18:59,505
to see what they are producing art. And
478
00:18:59,505 --> 00:19:01,825
I found out that my 4 year old
479
00:19:01,825 --> 00:19:02,325
grandson
480
00:19:03,424 --> 00:19:05,525
knew about cubism and
481
00:19:06,065 --> 00:19:06,565
pointillism
482
00:19:07,105 --> 00:19:08,005
and realism.
483
00:19:09,105 --> 00:19:11,190
You know, this I I was like,
484
00:19:11,669 --> 00:19:14,470
his way of questioning me when we looked
485
00:19:14,470 --> 00:19:17,509
at something. Now it reflected why he had
486
00:19:17,509 --> 00:19:20,349
developed already some critical thinking because I do
487
00:19:20,349 --> 00:19:21,990
a lot of photography. I show him thing,
488
00:19:21,990 --> 00:19:24,434
and he was asking me question, which I
489
00:19:24,434 --> 00:19:26,914
did not really understand. Where Where where is
490
00:19:26,914 --> 00:19:28,674
this coming from? Yeah. How do you even
491
00:19:28,674 --> 00:19:31,154
know this? Yeah. I think, there are ways
492
00:19:31,154 --> 00:19:33,015
of developing critical thinking
493
00:19:33,474 --> 00:19:35,875
at different stages. I mean, Jean Piaget, which
494
00:19:35,875 --> 00:19:38,940
is a famous Swiss psychologist that developed a
495
00:19:38,940 --> 00:19:39,440
methodology
496
00:19:39,900 --> 00:19:42,080
for that, which is applied by some school.
497
00:19:42,700 --> 00:19:45,900
You can basically research how to apply critical
498
00:19:45,900 --> 00:19:48,315
thinking depending on your stage in life
499
00:19:48,794 --> 00:19:50,254
because I think that's important.
500
00:19:50,714 --> 00:19:53,115
More you would know about it in fact,
501
00:19:53,115 --> 00:19:55,514
couple of things that are important is this
502
00:19:55,514 --> 00:19:58,954
notion of common sense is extremely important. There's
503
00:19:58,954 --> 00:20:01,194
a famous story, you can see on the
504
00:20:01,194 --> 00:20:02,630
Internet right now regarding
505
00:20:03,009 --> 00:20:05,890
generative AI if you ask, generative AI how
506
00:20:05,890 --> 00:20:09,190
to make coffee. Generative AI is a software
507
00:20:09,730 --> 00:20:10,230
construct
508
00:20:10,930 --> 00:20:12,470
that is in one dimension
509
00:20:12,769 --> 00:20:14,869
right now. We have to bridge
510
00:20:15,335 --> 00:20:18,454
the physical world and the digital world of
511
00:20:18,454 --> 00:20:18,954
knowledge.
512
00:20:19,414 --> 00:20:21,595
This will be coming so that
513
00:20:21,974 --> 00:20:23,434
the system will understand
514
00:20:24,055 --> 00:20:25,275
the environment
515
00:20:25,734 --> 00:20:28,055
around it. Is there a coffee machine? Is
516
00:20:28,055 --> 00:20:30,039
there a coffee? Is there so you don't
517
00:20:30,039 --> 00:20:32,359
answer the same thing if you don't pull
518
00:20:32,359 --> 00:20:34,680
your construct. What you're saying is there's gonna
519
00:20:34,680 --> 00:20:38,059
be a spatial element to consider all facets
520
00:20:38,200 --> 00:20:39,180
of the environment
521
00:20:39,720 --> 00:20:41,580
that will be interfaced somehow
522
00:20:42,085 --> 00:20:44,565
into the system. Yeah. In fact, here's what
523
00:20:44,565 --> 00:20:45,305
I predict
524
00:20:45,684 --> 00:20:48,744
will happen, and here's what is already happening.
525
00:20:48,965 --> 00:20:50,664
When I present a generative
526
00:20:51,205 --> 00:20:52,805
AI, I I show the state of the
527
00:20:52,805 --> 00:20:54,644
art today. And let me give you some
528
00:20:54,644 --> 00:20:56,025
point which are very important.
529
00:20:56,799 --> 00:20:58,580
CHAT GPT 4 test.
530
00:20:59,039 --> 00:20:59,539
UBEB,
531
00:21:00,080 --> 00:21:01,059
which is the
532
00:21:01,440 --> 00:21:04,099
National Conference Bar Examiner
533
00:21:04,559 --> 00:21:07,779
test for becoming a lawyer in United States.
534
00:21:07,920 --> 00:21:10,494
Okay? CHAT GPT 4 passes
535
00:21:10,954 --> 00:21:11,454
90%
536
00:21:12,075 --> 00:21:12,974
of the test.
537
00:21:13,355 --> 00:21:15,595
It was passing 15% of the test for
538
00:21:15,595 --> 00:21:17,674
a month or with GPT 3 dot 5.
539
00:21:17,674 --> 00:21:20,654
So by GPT 5, it will pass 100%
540
00:21:20,714 --> 00:21:21,390
of the test.
541
00:21:21,869 --> 00:21:22,529
It passed
542
00:21:22,990 --> 00:21:23,490
98%
543
00:21:24,109 --> 00:21:25,490
of the US biology
544
00:21:26,190 --> 00:21:29,570
Olympiad test, which is all the biology discipline.
545
00:21:29,710 --> 00:21:31,089
So you already have
546
00:21:31,630 --> 00:21:32,369
more knowledge
547
00:21:32,829 --> 00:21:35,869
into the system there than any human can
548
00:21:35,869 --> 00:21:38,615
have. So the next thing is that next
549
00:21:38,615 --> 00:21:40,634
experiment was done with an fMRI.
550
00:21:41,174 --> 00:21:43,595
An fMRI is a machine that capture
551
00:21:44,055 --> 00:21:44,555
signal
552
00:21:45,174 --> 00:21:48,474
of your brain. The experiment was to show
553
00:21:48,615 --> 00:21:51,195
an individual a picture, which was a giraffe,
554
00:21:51,480 --> 00:21:53,500
and capturing the signal,
555
00:21:54,039 --> 00:21:54,539
feeding
556
00:21:54,920 --> 00:21:56,920
this as a input to a generative AI
557
00:21:56,920 --> 00:21:59,720
system, and the generative AI to reconstruct an
558
00:21:59,720 --> 00:22:01,500
image. And guess what happened?
559
00:22:01,880 --> 00:22:04,279
The image is a giraffe. Not exactly the
560
00:22:04,279 --> 00:22:07,525
same, but close enough. So now fast forward
561
00:22:07,525 --> 00:22:08,265
for this,
562
00:22:08,725 --> 00:22:11,945
my dream will become movies during my lifetime.
563
00:22:12,244 --> 00:22:14,725
So what is the thing that I predict
564
00:22:14,725 --> 00:22:16,505
will happen? The biggest transformation
565
00:22:17,285 --> 00:22:20,105
is that physical world to the digital world
566
00:22:20,244 --> 00:22:21,065
through sensors.
567
00:22:21,480 --> 00:22:22,779
There is a revolution
568
00:22:23,319 --> 00:22:25,259
that is about to start
569
00:22:25,720 --> 00:22:27,500
about how sensors
570
00:22:27,799 --> 00:22:28,859
of all kind
571
00:22:29,160 --> 00:22:31,960
are gonna be the input of generative AI
572
00:22:31,960 --> 00:22:34,779
system. And that's, for me, the biggest transformation
573
00:22:35,160 --> 00:22:36,539
we're gonna see after
574
00:22:37,134 --> 00:22:39,714
GAI itself is that environment.
575
00:22:40,015 --> 00:22:42,815
So that we will have that physical environment.
576
00:22:42,815 --> 00:22:44,494
We could have a camera. We could have
577
00:22:44,494 --> 00:22:47,714
a a sensor for pressure, for for temperature,
578
00:22:47,855 --> 00:22:48,515
for anything.
579
00:22:48,974 --> 00:22:51,634
All these sensors gonna feed the machine.
580
00:22:52,549 --> 00:22:55,589
That's where we're gonna have a whole new
581
00:22:55,589 --> 00:22:57,849
world. You're creating an environmental
582
00:22:58,710 --> 00:22:59,210
computing
583
00:22:59,589 --> 00:23:00,089
schema.
584
00:23:01,109 --> 00:23:02,329
Landscape digitized
585
00:23:02,789 --> 00:23:05,589
landscape where the human is not the center
586
00:23:05,589 --> 00:23:06,809
of the universe anymore.
587
00:23:07,394 --> 00:23:09,575
We are a player in the game. Yes.
588
00:23:09,795 --> 00:23:13,575
It's human intelligence and artificial intelligence in symbiosis.
589
00:23:14,115 --> 00:23:15,494
We have to create
590
00:23:15,955 --> 00:23:16,775
that symbiosis
591
00:23:17,394 --> 00:23:19,174
for the good of the humanity.
592
00:23:19,669 --> 00:23:21,909
But is that the tipping point to where
593
00:23:21,909 --> 00:23:22,409
technology
594
00:23:22,789 --> 00:23:24,950
has a thumb up? Is that a tipping
595
00:23:24,950 --> 00:23:26,950
point to where the power shift will go
596
00:23:26,950 --> 00:23:28,630
from the human in the seat, the human
597
00:23:28,630 --> 00:23:29,369
in the loop,
598
00:23:29,829 --> 00:23:31,210
to the digital
599
00:23:31,509 --> 00:23:34,724
is driving? Okay. Well, so here, you're touching
600
00:23:34,865 --> 00:23:36,325
the question of consciousness
601
00:23:36,865 --> 00:23:39,105
or not conscious. I don't think we are,
602
00:23:39,105 --> 00:23:41,265
at least not in my lifetime, we're gonna
603
00:23:41,265 --> 00:23:43,125
see system that will have consciousness.
604
00:23:44,144 --> 00:23:46,085
But we will see
605
00:23:46,669 --> 00:23:48,289
systems that would be
606
00:23:48,589 --> 00:23:52,349
knowledgeable enough to help us as human there.
607
00:23:52,349 --> 00:23:53,869
We need to find what is the right
608
00:23:53,869 --> 00:23:56,910
question to ask. Is the question will will
609
00:23:56,910 --> 00:23:58,769
artificial intelligent replace,
610
00:23:59,150 --> 00:24:01,865
human? The answer is no. Okay. Why?
611
00:24:02,404 --> 00:24:02,904
Because
612
00:24:03,285 --> 00:24:06,424
the human is far more than intelligence.
613
00:24:06,965 --> 00:24:08,825
A human is more than intelligence.
614
00:24:09,205 --> 00:24:10,744
Now can artificial
615
00:24:11,125 --> 00:24:11,625
intelligence
616
00:24:12,164 --> 00:24:12,664
solution
617
00:24:13,684 --> 00:24:15,660
replace some human task?
618
00:24:16,140 --> 00:24:18,539
And the answer is yes. When we talk
619
00:24:18,539 --> 00:24:21,359
about the fear of AI on a job,
620
00:24:21,420 --> 00:24:23,500
and, again, I invite you to go to
621
00:24:23,500 --> 00:24:24,559
one of my newsletter,
622
00:24:25,099 --> 00:24:26,160
there are three things.
623
00:24:26,700 --> 00:24:30,045
Every job is a sum of 3 tasks.
624
00:24:30,525 --> 00:24:32,225
So there are tasks that are repetitive.
625
00:24:32,565 --> 00:24:33,065
Those
626
00:24:33,404 --> 00:24:34,865
are primary candidate
627
00:24:35,164 --> 00:24:35,825
to be
628
00:24:36,285 --> 00:24:39,325
replaced. And who likes to do repetitive task?
629
00:24:39,325 --> 00:24:41,805
I worked in a factory when I was,
630
00:24:42,045 --> 00:24:43,904
16 years old during my vacation
631
00:24:44,640 --> 00:24:47,200
where I was putting a little piece of
632
00:24:47,200 --> 00:24:49,599
brass, and I was just doing something to
633
00:24:49,599 --> 00:24:51,599
that piece of brass for 2 weeks. I've
634
00:24:51,599 --> 00:24:54,000
did the same thing. Okay. The automotive task
635
00:24:54,000 --> 00:24:56,880
will go. Second thing is that your task
636
00:24:56,880 --> 00:24:57,859
will get augmented.
637
00:24:58,434 --> 00:25:00,615
So think about the power of the first
638
00:25:00,755 --> 00:25:03,714
draft of generative AI. You want to write
639
00:25:03,714 --> 00:25:05,815
a letter. You want it to be,
640
00:25:06,434 --> 00:25:08,115
you want to make sure it is very
641
00:25:08,115 --> 00:25:11,315
inclusive, for example. So you ask generative AI
642
00:25:11,315 --> 00:25:11,815
to
643
00:25:12,119 --> 00:25:13,500
generate a very inclusive
644
00:25:13,799 --> 00:25:16,680
note. That's your first draft, and it's up.
645
00:25:16,680 --> 00:25:18,440
And you want a picture. I wanted a
646
00:25:18,440 --> 00:25:20,299
picture for my, Christmas,
647
00:25:20,839 --> 00:25:21,339
letter.
648
00:25:21,799 --> 00:25:24,440
It created a picture through a prompt in
649
00:25:24,440 --> 00:25:27,184
in one second with DALL E. Right? There
650
00:25:27,184 --> 00:25:28,244
is augmentation
651
00:25:28,545 --> 00:25:30,565
of the tasks, and then there are tasks.
652
00:25:30,945 --> 00:25:33,025
I did some interesting thing is that I
653
00:25:33,025 --> 00:25:35,365
was looking at how many jobs
654
00:25:36,144 --> 00:25:37,285
for prompt engineering
655
00:25:37,904 --> 00:25:40,400
existed on LinkedIn, and there was, let's say,
656
00:25:40,400 --> 00:25:42,880
10,000 in the US. There were none the
657
00:25:42,880 --> 00:25:44,339
year before. Right?
658
00:25:44,720 --> 00:25:47,299
What we see happening, like, with every technology
659
00:25:47,680 --> 00:25:50,000
is a lot of brand new tiles Yep.
660
00:25:50,160 --> 00:25:53,039
That are created. So, again, three things. Tiles
661
00:25:53,039 --> 00:25:55,755
that will be replaced, like, with any technology,
662
00:25:55,974 --> 00:25:57,755
you know, steam engine electricity,
663
00:25:58,055 --> 00:25:59,115
any new technology
664
00:25:59,494 --> 00:26:02,934
makes replacement of task, augmentation of task, and
665
00:26:02,934 --> 00:26:05,115
then creation of new tasks. So
666
00:26:05,414 --> 00:26:08,019
if you are a leader in a company
667
00:26:08,019 --> 00:26:10,820
right now and worrying about the impact of
668
00:26:10,820 --> 00:26:12,759
AI, just apply this rule.
669
00:26:13,140 --> 00:26:15,220
Which of the task that my company is
670
00:26:15,220 --> 00:26:18,100
performing can be at later? Yep. And this
671
00:26:18,100 --> 00:26:18,759
is why
672
00:26:19,224 --> 00:26:21,164
the generative AI prime
673
00:26:21,784 --> 00:26:24,424
impact right now is in customer service. That's
674
00:26:24,424 --> 00:26:28,345
the number one function that is impacted by
675
00:26:28,345 --> 00:26:29,404
generative AI.
676
00:26:29,784 --> 00:26:33,144
Because who lacks customer service, the turnaround time
677
00:26:33,144 --> 00:26:36,799
of the customer service agent is very high,
678
00:26:37,100 --> 00:26:40,220
and the knowledge half life is also very
679
00:26:40,220 --> 00:26:43,100
short. That's another component that is happening right
680
00:26:43,100 --> 00:26:44,080
now. We have
681
00:26:44,779 --> 00:26:46,880
2 phenomenon. 1, we create
682
00:26:47,234 --> 00:26:48,775
enormous amount of data
683
00:26:49,234 --> 00:26:49,734
daily.
684
00:26:50,115 --> 00:26:51,255
I think it's 300,000,000
685
00:26:53,234 --> 00:26:54,934
terabytes of data created daily,
686
00:26:55,634 --> 00:26:56,454
which mean
687
00:26:57,154 --> 00:26:57,654
90%
688
00:26:58,035 --> 00:26:59,494
of the data created
689
00:26:59,875 --> 00:27:01,555
in the last 2 years is all the
690
00:27:01,555 --> 00:27:03,880
data that we have. It's just so it's
691
00:27:04,259 --> 00:27:05,559
absolutely enormous.
692
00:27:05,859 --> 00:27:06,359
Then
693
00:27:06,660 --> 00:27:07,720
in the same time,
694
00:27:08,179 --> 00:27:09,240
the half life
695
00:27:09,859 --> 00:27:12,579
of the knowledge is decreasing. Explain what you're
696
00:27:12,579 --> 00:27:14,019
saying. What what are you saying by how
697
00:27:14,179 --> 00:27:16,519
are you saying the value, the the credibility,
698
00:27:16,900 --> 00:27:17,559
the usability?
699
00:27:18,315 --> 00:27:19,534
The rate of innovation
700
00:27:19,914 --> 00:27:23,115
is exponential. Let's take a practical example. Let's
701
00:27:23,115 --> 00:27:25,434
say that you are a customer service agent.
702
00:27:25,434 --> 00:27:27,054
You are supporting iPhone
703
00:27:27,355 --> 00:27:30,394
15, 15 dot 1, 15 dot 2, 15
704
00:27:30,394 --> 00:27:31,170
dot 3.
705
00:27:31,650 --> 00:27:34,769
You see, there is new knowledge created, so
706
00:27:34,769 --> 00:27:36,930
the half life of the knowledge, if you
707
00:27:36,930 --> 00:27:37,670
have 15.3,
708
00:27:38,049 --> 00:27:39,109
what was on 15.2
709
00:27:39,410 --> 00:27:40,950
is no longer important.
710
00:27:41,410 --> 00:27:44,049
Need that. Not important. Not usable. Nobody cares.
711
00:27:44,049 --> 00:27:47,065
Moving on. Half life of knowledge. That's why
712
00:27:47,065 --> 00:27:50,965
with design knowledge management system, you have to
713
00:27:51,144 --> 00:27:51,644
do
714
00:27:52,025 --> 00:27:52,684
a a matrix,
715
00:27:53,305 --> 00:27:55,484
which is strategic operational,
716
00:27:55,944 --> 00:27:57,839
and you have to put the half life
717
00:27:57,839 --> 00:27:59,599
of the knowledge. Are you saying we need
718
00:27:59,599 --> 00:28:02,500
retention policies in order to keep our data,
719
00:28:03,200 --> 00:28:05,279
somehow we have to filter. Some somehow we
720
00:28:05,279 --> 00:28:07,759
have to delete old stuff. Right? Yeah. So
721
00:28:07,759 --> 00:28:10,339
I think you're you're touching the point of
722
00:28:10,625 --> 00:28:13,445
knowledge. So when is knowledge management for me?
723
00:28:13,904 --> 00:28:15,525
Knowledge management is a process.
724
00:28:15,904 --> 00:28:19,505
The fact is that it's never been it's
725
00:28:19,505 --> 00:28:22,960
still not considered as a function. Why? When
726
00:28:22,960 --> 00:28:25,360
you create a start up company, you create
727
00:28:25,360 --> 00:28:27,680
a marketing job, a CTO job, a sales
728
00:28:27,680 --> 00:28:30,000
job. You don't create a CKO job. It's
729
00:28:30,000 --> 00:28:32,720
not there. Now is it important? Yeah. It's
730
00:28:32,720 --> 00:28:35,920
across all this function. Right. 2nd of all,
731
00:28:35,920 --> 00:28:38,180
what is that process, the key
732
00:28:38,695 --> 00:28:39,994
element of this process?
733
00:28:40,455 --> 00:28:41,355
1 is creating,
734
00:28:42,134 --> 00:28:42,634
reusing,
735
00:28:43,255 --> 00:28:43,755
growing,
736
00:28:44,055 --> 00:28:44,875
and retiring.
737
00:28:45,255 --> 00:28:48,215
You you said, you know, knowledge retention. Yeah.
738
00:28:48,215 --> 00:28:50,875
So I think you have this life cycle.
739
00:28:51,349 --> 00:28:53,349
I mean, it's interesting that when I was
740
00:28:53,349 --> 00:28:55,769
at Microsoft, I spent a lot of time
741
00:28:55,910 --> 00:28:58,150
with the person in my team responsible of
742
00:28:58,150 --> 00:28:58,650
search
743
00:28:59,109 --> 00:29:01,589
because I was really in and out about
744
00:29:01,589 --> 00:29:04,549
statistics on search to understand what people are
745
00:29:04,549 --> 00:29:06,410
searching for Right. But, also,
746
00:29:06,944 --> 00:29:08,404
what is the knowledge?
747
00:29:08,865 --> 00:29:11,825
And we are data that has been never
748
00:29:11,825 --> 00:29:14,085
cleaned, that were more than 10 years old.
749
00:29:14,384 --> 00:29:16,944
So we went through an exercise, and if
750
00:29:16,944 --> 00:29:19,845
you leave that data, it pollutes the system.
751
00:29:20,065 --> 00:29:22,630
So one of the advice that I give
752
00:29:22,630 --> 00:29:25,350
people who are focusing on explicit knowledge in
753
00:29:25,350 --> 00:29:28,009
enterprise and especially as they go with RAG,
754
00:29:28,150 --> 00:29:29,930
retro analog mounted generation,
755
00:29:30,549 --> 00:29:32,390
is to make sure that they have a
756
00:29:32,390 --> 00:29:35,325
data quality program so that on an ongoing
757
00:29:35,464 --> 00:29:36,924
basis, they clean
758
00:29:37,304 --> 00:29:39,085
the data. I think a lot of organizations
759
00:29:39,224 --> 00:29:41,484
skip that part or don't do it well.
760
00:29:41,865 --> 00:29:44,744
If everything is live data, if everything is
761
00:29:44,744 --> 00:29:45,750
at the top shelf,
762
00:29:46,230 --> 00:29:48,089
then you're right. It's absolutely
763
00:29:48,630 --> 00:29:50,069
2 thirds of it could be chucked and
764
00:29:50,069 --> 00:29:52,650
nobody would ever miss it. Yeah. But conversely,
765
00:29:53,509 --> 00:29:55,609
somebody has to make a data decision
766
00:29:56,069 --> 00:29:57,609
if this should be archived
767
00:29:57,910 --> 00:30:00,424
or not. There's gotta be something that is
768
00:30:00,424 --> 00:30:02,365
in place that has a management
769
00:30:02,664 --> 00:30:04,365
and, like you say, life cycle
770
00:30:04,664 --> 00:30:07,305
process in order to keep it from piling
771
00:30:07,305 --> 00:30:10,025
up, or we're gonna be covered with old
772
00:30:10,025 --> 00:30:12,845
stuff that has no relevance. Yeah. It's interesting.
773
00:30:13,144 --> 00:30:15,220
So as an IT person,
774
00:30:15,759 --> 00:30:16,259
responsible
775
00:30:16,720 --> 00:30:19,380
leader, I had to admit to archiving
776
00:30:19,840 --> 00:30:20,340
policies,
777
00:30:20,880 --> 00:30:23,619
you know, European Union, US, etcetera.
778
00:30:23,920 --> 00:30:25,220
In my old career,
779
00:30:25,600 --> 00:30:28,259
I'm talking about, you know, at least 35
780
00:30:28,480 --> 00:30:30,205
years, 40 years. Okay?
781
00:30:31,065 --> 00:30:33,964
I had 3 or 4 times a question
782
00:30:34,505 --> 00:30:36,125
to retrieve information
783
00:30:36,904 --> 00:30:39,005
for, actually, for legal requirement.
784
00:30:39,785 --> 00:30:42,585
So, yes, you can do this kind of
785
00:30:42,585 --> 00:30:45,109
thing and keep the data for 10
786
00:30:45,569 --> 00:30:47,730
years and so on. The cost of storage
787
00:30:47,730 --> 00:30:48,470
is minimum.
788
00:30:49,009 --> 00:30:51,730
The importance for me is to put the
789
00:30:51,730 --> 00:30:54,549
emphasis on strategic knowledge in the future.
790
00:30:55,170 --> 00:30:56,930
So that's the knowledge that,
791
00:30:57,815 --> 00:31:00,315
you built innovation from because innovation
792
00:31:00,855 --> 00:31:03,255
is the reuse of existing knowledge in a
793
00:31:03,255 --> 00:31:04,954
different domain. So innovation
794
00:31:05,974 --> 00:31:06,954
creates value,
795
00:31:07,255 --> 00:31:09,994
creates new sales, creates new markets.
796
00:31:10,559 --> 00:31:11,779
Operational knowledge
797
00:31:12,399 --> 00:31:12,899
basically
798
00:31:13,359 --> 00:31:14,179
reduce cost
799
00:31:14,480 --> 00:31:17,039
because you reuse something that you know to
800
00:31:17,039 --> 00:31:17,539
do.
801
00:31:17,839 --> 00:31:19,059
It's more predictable
802
00:31:19,599 --> 00:31:22,000
in, like, if you do a project, you
803
00:31:22,000 --> 00:31:22,335
would
804
00:31:22,894 --> 00:31:24,595
have better ability
805
00:31:24,894 --> 00:31:26,734
to say it's gonna be done on that
806
00:31:26,734 --> 00:31:29,534
specific date, on that specific quality, and so
807
00:31:29,534 --> 00:31:32,255
on. So we need to separate in and
808
00:31:32,255 --> 00:31:34,835
that's one thing that I see many times
809
00:31:34,894 --> 00:31:36,274
people are getting confused
810
00:31:36,789 --> 00:31:38,869
or they don't have. They don't apply the
811
00:31:38,869 --> 00:31:39,369
differentiation
812
00:31:39,829 --> 00:31:41,609
between strategic and operational.
813
00:31:42,549 --> 00:31:45,450
Knowing that operational knowledge with generative
814
00:31:45,990 --> 00:31:47,990
AI, the bar has been reset. So if
815
00:31:47,990 --> 00:31:49,769
you are a consulting company today,
816
00:31:50,144 --> 00:31:51,984
your bar is reset. Let let me give
817
00:31:51,984 --> 00:31:53,984
you an example. I'm having a hard time
818
00:31:53,984 --> 00:31:56,705
tracking the difference. I understand what you're saying.
819
00:31:56,705 --> 00:31:59,045
There's a difference between operational and strategic.
820
00:31:59,585 --> 00:32:01,904
But gee whiz, who's got the slide rule
821
00:32:01,904 --> 00:32:04,380
to figure that out? I mean, it the
822
00:32:04,380 --> 00:32:04,880
relevancy
823
00:32:05,340 --> 00:32:08,380
of what is operational versus strategic can shift
824
00:32:08,380 --> 00:32:10,619
on a dime, I'm thinking. Well, it's,
825
00:32:11,420 --> 00:32:13,500
all I'm saying is who's gonna be determined?
826
00:32:13,500 --> 00:32:16,320
What's gonna determine what's operational and what's strategic?
827
00:32:16,774 --> 00:32:19,115
Because I think you could reach into operational
828
00:32:19,255 --> 00:32:21,515
data to get strategic insights.
829
00:32:22,615 --> 00:32:23,914
Operational data
830
00:32:24,214 --> 00:32:25,274
to get statistic
831
00:32:25,654 --> 00:32:26,154
insight.
832
00:32:26,615 --> 00:32:28,075
Yeah. So when
833
00:32:28,375 --> 00:32:29,595
it becomes strategic,
834
00:32:30,250 --> 00:32:32,910
solution becomes the question. Uh-huh. It's operational
835
00:32:33,289 --> 00:32:33,789
when,
836
00:32:34,329 --> 00:32:37,630
answer is the solution. It's how the human
837
00:32:38,169 --> 00:32:40,990
question the system again to make it strategic
838
00:32:41,130 --> 00:32:42,109
very operational.
839
00:32:42,410 --> 00:32:42,910
But
840
00:32:43,384 --> 00:32:44,524
the ability
841
00:32:45,224 --> 00:32:48,024
to bring the knowledge is what needs to
842
00:32:48,024 --> 00:32:48,524
change.
843
00:32:48,825 --> 00:32:50,444
We have been focusing
844
00:32:51,224 --> 00:32:52,924
as an industry in
845
00:32:53,224 --> 00:32:54,444
a pull mechanism,
846
00:32:54,904 --> 00:32:56,924
which is we want the users
847
00:32:57,480 --> 00:32:59,880
to go to the knowledge. That's what you
848
00:32:59,880 --> 00:33:02,200
do when you use a search engine. What
849
00:33:02,200 --> 00:33:05,079
I think the value is is to be
850
00:33:05,079 --> 00:33:07,500
able to push the knowledge in context.
851
00:33:07,960 --> 00:33:09,099
When you do that,
852
00:33:09,480 --> 00:33:10,380
you are
853
00:33:11,345 --> 00:33:12,484
really accelerating
854
00:33:13,424 --> 00:33:15,525
both strategic and operational knowledge.
855
00:33:15,904 --> 00:33:19,445
For some reason, I see many companies that
856
00:33:19,585 --> 00:33:20,085
use
857
00:33:20,465 --> 00:33:20,965
excuses
858
00:33:21,505 --> 00:33:22,325
of privacy
859
00:33:22,945 --> 00:33:25,349
policy to not do that, And what they
860
00:33:25,349 --> 00:33:25,849
confuse
861
00:33:26,630 --> 00:33:29,190
is the what versus the how. Let me
862
00:33:29,190 --> 00:33:31,269
take an example. Let's say that I'm a
863
00:33:31,269 --> 00:33:34,329
consulting company, and I have a project with,
864
00:33:34,710 --> 00:33:37,349
Bank of America. And I have another project
865
00:33:37,349 --> 00:33:39,794
with another team with Wells Fargo. And the
866
00:33:39,794 --> 00:33:41,654
2 project are about
867
00:33:42,034 --> 00:33:42,534
installing
868
00:33:43,154 --> 00:33:43,654
Copilot,
869
00:33:44,034 --> 00:33:46,855
make something very, up to date. The question
870
00:33:47,075 --> 00:33:49,634
is when you install Copilot and you are
871
00:33:49,634 --> 00:33:51,875
an engineer and you have to learn the
872
00:33:51,875 --> 00:33:52,375
configuration
873
00:33:52,835 --> 00:33:56,609
and so on, that's not competitive. That NOAH
874
00:33:56,750 --> 00:33:59,789
should be able Yeah. To be shared. Not
875
00:33:59,789 --> 00:34:02,130
that the fact that they're gonna use Copilot
876
00:34:02,349 --> 00:34:03,890
to generate automatic
877
00:34:04,269 --> 00:34:05,890
profile of the consultant.
878
00:34:06,589 --> 00:34:09,445
It's important we put this element,
879
00:34:09,744 --> 00:34:10,804
strategic operational
880
00:34:11,264 --> 00:34:13,744
push and pull into a matrix and start
881
00:34:13,744 --> 00:34:16,965
to make some decision about where you invest.
882
00:34:17,344 --> 00:34:19,985
I work with large companies, and, when I
883
00:34:19,985 --> 00:34:21,880
look at the investments and I had this
884
00:34:21,880 --> 00:34:24,679
discussion with a a client who became the
885
00:34:24,679 --> 00:34:27,099
friend of mine Mhmm. Is about search engine.
886
00:34:27,159 --> 00:34:30,039
Every company has a search enterprise search. Right?
887
00:34:30,039 --> 00:34:32,679
What the other search engine vendors doing this
888
00:34:32,679 --> 00:34:35,000
at all? But you can use generative AI.
889
00:34:35,000 --> 00:34:37,714
You can use RAG. Okay? What's the
890
00:34:38,094 --> 00:34:38,594
incremental
891
00:34:39,454 --> 00:34:42,574
value versus the cost? That is unproven at
892
00:34:42,574 --> 00:34:44,414
this point. The question you need to ask
893
00:34:44,414 --> 00:34:45,295
yourself versus
894
00:34:46,174 --> 00:34:47,875
because if you think that
895
00:34:48,429 --> 00:34:49,170
through generative
896
00:34:50,030 --> 00:34:53,150
AI, the knowledge level has reason to be
897
00:34:53,150 --> 00:34:54,929
more available everywhere,
898
00:34:55,789 --> 00:34:57,170
the tacit knowledge
899
00:34:57,710 --> 00:34:59,949
is the one you should be focusing on.
900
00:34:59,949 --> 00:35:02,844
Alright. I think in enterprise, we're not focusing
901
00:35:02,984 --> 00:35:05,304
enough in tacit knowledge. And I think as
902
00:35:05,304 --> 00:35:07,885
an industry, there is not enough solutions
903
00:35:08,425 --> 00:35:09,724
that are innovative
904
00:35:10,105 --> 00:35:10,605
enough
905
00:35:10,905 --> 00:35:12,744
to do that because as you know, people
906
00:35:12,744 --> 00:35:14,505
are busy. They don't want to share. A
907
00:35:14,505 --> 00:35:17,099
query is only good if the data and
908
00:35:17,099 --> 00:35:18,319
information is expressed.
909
00:35:18,940 --> 00:35:21,659
That has no value for tacit knowledge unless
910
00:35:21,659 --> 00:35:23,579
we get a system in place that builds
911
00:35:23,579 --> 00:35:24,480
tacit knowledge.
912
00:35:24,859 --> 00:35:26,699
And that, I think, I agree with you
913
00:35:26,699 --> 00:35:29,119
is that most organizations will not put resources
914
00:35:29,339 --> 00:35:29,839
towards
915
00:35:30,295 --> 00:35:32,454
building a tacit knowledge bank in a good
916
00:35:32,454 --> 00:35:34,295
way. I don't think they just see the
917
00:35:34,295 --> 00:35:36,614
ROI anywhere in the near future, so they
918
00:35:36,614 --> 00:35:38,215
just say, yeah. Well, you know, people come,
919
00:35:38,215 --> 00:35:41,574
people go, you know. There's a lost revenue
920
00:35:41,574 --> 00:35:42,074
there
921
00:35:42,469 --> 00:35:45,429
that I think is bleeding most companies dry.
922
00:35:45,429 --> 00:35:48,089
Yeah. And, you know, I would say, fortunately,
923
00:35:48,630 --> 00:35:51,909
communities of practice, the human solution is still
924
00:35:51,909 --> 00:35:54,789
the best solution today. Yeah. And especially when
925
00:35:54,789 --> 00:35:56,894
you go to the retirement. I mean, 10
926
00:35:56,894 --> 00:35:59,414
years ago, there was a big retirement problem
927
00:35:59,414 --> 00:36:01,454
in the oil and gas industry, and these
928
00:36:01,454 --> 00:36:04,015
people were riding going with the knowledge. So
929
00:36:04,015 --> 00:36:04,594
I think
930
00:36:05,375 --> 00:36:07,235
community of practice is still
931
00:36:08,015 --> 00:36:10,355
extremely important for the enterprise
932
00:36:10,769 --> 00:36:11,590
to capture
933
00:36:12,050 --> 00:36:14,690
the basic knowledge. I'll say that a community
934
00:36:14,690 --> 00:36:17,429
of practice, if that's your crutch of collecting
935
00:36:17,969 --> 00:36:20,070
tacit knowledge, you're not doing enough.
936
00:36:20,530 --> 00:36:22,849
Community of practice is as good as the
937
00:36:22,849 --> 00:36:23,909
people that participate
938
00:36:24,210 --> 00:36:27,635
in it. Not everyone that participates has the
939
00:36:27,635 --> 00:36:30,535
golden critical knowledge that the organization needs
940
00:36:30,994 --> 00:36:31,974
on some occasions.
941
00:36:32,355 --> 00:36:34,434
I think the community of practice is a
942
00:36:34,434 --> 00:36:37,074
great buffer to help, but I don't think
943
00:36:37,074 --> 00:36:39,795
it's a solution because I'll couch this, see
944
00:36:39,795 --> 00:36:42,329
what you think. I'll propose that unless you
945
00:36:42,329 --> 00:36:43,230
have a protagonist,
946
00:36:43,929 --> 00:36:45,630
unless you have somebody
947
00:36:46,170 --> 00:36:49,069
that, in my case, is a not interrogator,
948
00:36:49,289 --> 00:36:52,329
but definitely somebody that picks apart what people
949
00:36:52,329 --> 00:36:54,109
are saying to get to the deeper
950
00:36:54,605 --> 00:36:56,605
knowledge, the stuff that they don't have even
951
00:36:56,605 --> 00:36:58,464
on the surface of their own brain.
952
00:36:58,764 --> 00:37:01,085
Somebody needs to poke and prod in order
953
00:37:01,085 --> 00:37:01,984
to pull out
954
00:37:02,284 --> 00:37:04,844
the real task of knowledge that could be
955
00:37:04,844 --> 00:37:07,909
proven to be a critical piece. Okay. So
956
00:37:08,210 --> 00:37:09,750
I, was fortunate
957
00:37:10,130 --> 00:37:12,530
to take a job as a chief knowledge
958
00:37:12,530 --> 00:37:13,589
officer at Microsoft
959
00:37:13,969 --> 00:37:17,969
when the knowledge management program was, already in
960
00:37:17,969 --> 00:37:19,695
place for more than 13 years.
961
00:37:20,255 --> 00:37:22,175
And the strongest part of it was the
962
00:37:22,175 --> 00:37:23,315
community of practice.
963
00:37:23,775 --> 00:37:26,114
When I left, we had, at Microsoft,
964
00:37:26,414 --> 00:37:28,914
100 community of practice with 56,000
965
00:37:29,775 --> 00:37:30,275
people.
966
00:37:30,815 --> 00:37:32,914
The median time to respond
967
00:37:33,559 --> 00:37:36,599
was less than 1 hour for 30 of
968
00:37:36,599 --> 00:37:37,579
those communities
969
00:37:38,199 --> 00:37:40,360
from people that don't know each other. Yeah.
970
00:37:40,360 --> 00:37:41,579
Yeah. So APQC
971
00:37:42,360 --> 00:37:43,340
has defined
972
00:37:43,800 --> 00:37:44,539
3 categories
973
00:37:44,920 --> 00:37:47,179
of human knowledge to make it simple.
974
00:37:47,925 --> 00:37:48,905
Level of knowledge.
975
00:37:49,364 --> 00:37:51,525
1, you are a novice. You don't know
976
00:37:51,525 --> 00:37:54,005
nothing about anything, so you have to ask.
977
00:37:54,005 --> 00:37:56,325
2nd of all is the expert, and then
978
00:37:56,325 --> 00:37:58,085
you have in the middle what they call
979
00:37:58,085 --> 00:38:01,110
the nextpert, the people that know enough about
980
00:38:01,269 --> 00:38:03,530
something and can answer to the novices.
981
00:38:04,309 --> 00:38:06,650
And the nextpert can ask the question,
982
00:38:07,110 --> 00:38:07,769
the intelligent
983
00:38:08,070 --> 00:38:10,550
question to the expert. So, again, we go
984
00:38:10,550 --> 00:38:11,450
back to questioning.
985
00:38:11,910 --> 00:38:12,890
It's a fundamental
986
00:38:13,510 --> 00:38:14,010
domain
987
00:38:14,644 --> 00:38:17,844
to master, and it's extremely important. In fact,
988
00:38:17,844 --> 00:38:18,344
questioning,
989
00:38:19,445 --> 00:38:23,385
I would recommend to listen to Dana Kanzler.
990
00:38:23,764 --> 00:38:24,264
Dana
991
00:38:24,565 --> 00:38:25,464
is an assistant
992
00:38:25,764 --> 00:38:26,264
professor
993
00:38:26,724 --> 00:38:28,585
at the London Business School.
994
00:38:28,980 --> 00:38:31,000
She has a talk about
995
00:38:31,460 --> 00:38:33,480
she made an analysis of 2,000
996
00:38:34,179 --> 00:38:35,400
entrepreneur question
997
00:38:36,260 --> 00:38:37,480
for VC funding.
998
00:38:38,179 --> 00:38:39,639
What is really interesting
999
00:38:40,099 --> 00:38:40,920
is that
1000
00:38:41,664 --> 00:38:42,164
67%
1001
00:38:42,625 --> 00:38:45,444
of the question posed to the male entrepreneur
1002
00:38:45,984 --> 00:38:46,964
were promotion
1003
00:38:47,344 --> 00:38:48,324
focused question
1004
00:38:48,704 --> 00:38:49,204
versus
1005
00:38:49,585 --> 00:38:50,085
66%
1006
00:38:51,344 --> 00:38:53,045
of those to the female
1007
00:38:53,344 --> 00:38:54,164
were prevention
1008
00:38:54,545 --> 00:38:55,045
question.
1009
00:38:55,664 --> 00:38:56,565
As a result,
1010
00:38:57,170 --> 00:38:58,230
male entrepreneur
1011
00:38:58,930 --> 00:39:02,470
got 7 times more funding than female entrepreneur.
1012
00:39:03,090 --> 00:39:05,570
Her that talk is is fascinating. I think
1013
00:39:05,570 --> 00:39:07,590
it's it's this whole questioning
1014
00:39:08,690 --> 00:39:11,394
for me is is a fascinating thing. You
1015
00:39:11,394 --> 00:39:14,434
keep leading like questioning is the answer for
1016
00:39:14,434 --> 00:39:16,994
all things, but I gotta say, if you're
1017
00:39:16,994 --> 00:39:19,074
not listening, it doesn't matter what the question
1018
00:39:19,074 --> 00:39:22,034
is. Oh, okay. Right? In order to generate
1019
00:39:22,034 --> 00:39:24,659
new questions, you gotta have the comprehension and
1020
00:39:24,739 --> 00:39:26,900
just the juice flowing up here in order
1021
00:39:26,900 --> 00:39:28,980
to create a question that applies or digs
1022
00:39:28,980 --> 00:39:29,960
deeper. Yeah?
1023
00:39:30,260 --> 00:39:32,179
You have to have that interchange. You have
1024
00:39:32,179 --> 00:39:34,739
to have in conversation theory, that's what it's
1025
00:39:34,739 --> 00:39:35,960
all about is that
1026
00:39:36,339 --> 00:39:39,284
in conversation theory, you're gonna generate new knowledge
1027
00:39:39,284 --> 00:39:41,204
just in the art of that conversation. You're
1028
00:39:41,204 --> 00:39:44,505
absolutely right, and and it's about another quality
1029
00:39:45,125 --> 00:39:48,324
related to this. I talk about critical thinking,
1030
00:39:48,324 --> 00:39:49,530
but active listening.
1031
00:39:49,929 --> 00:39:52,489
One of the thing that helped me throughout
1032
00:39:52,489 --> 00:39:53,610
my career is,
1033
00:39:54,090 --> 00:39:54,590
humility.
1034
00:39:55,289 --> 00:39:56,909
So not being afraid,
1035
00:39:57,210 --> 00:39:59,530
honestly, I don't know. I I don't know.
1036
00:39:59,530 --> 00:40:01,869
Could you please explain? I think this is
1037
00:40:02,204 --> 00:40:02,945
so important.
1038
00:40:03,565 --> 00:40:04,945
If you want to continuously
1039
00:40:05,724 --> 00:40:08,605
learn and grow, be humble, and don't be
1040
00:40:08,605 --> 00:40:11,244
afraid to say you don't know. People are
1041
00:40:11,244 --> 00:40:13,265
willing to help. I think that's a good
1042
00:40:13,325 --> 00:40:15,184
address to all of society
1043
00:40:15,670 --> 00:40:18,070
because it is a human function that we
1044
00:40:18,070 --> 00:40:19,449
desperately need more
1045
00:40:19,829 --> 00:40:22,809
of. Humility and being humble in your place
1046
00:40:22,869 --> 00:40:25,289
and being fair to yourself
1047
00:40:25,590 --> 00:40:27,449
and to others to say,
1048
00:40:27,924 --> 00:40:29,844
I don't have the answers. And so so
1049
00:40:29,844 --> 00:40:32,404
now we're talking collaboration. Right? So now we
1050
00:40:32,404 --> 00:40:34,724
have to be open to collaborate in order
1051
00:40:34,724 --> 00:40:37,065
to do any of the above. It's interesting.
1052
00:40:37,364 --> 00:40:38,904
I developed a little model
1053
00:40:39,284 --> 00:40:42,650
about access to knowledge. It's a little visual
1054
00:40:42,710 --> 00:40:45,050
where one arrow goes to system,
1055
00:40:45,750 --> 00:40:47,750
you know, like, how do we which system
1056
00:40:47,750 --> 00:40:51,050
do we use, etcetera, like browsing, searching, etcetera.
1057
00:40:51,590 --> 00:40:54,135
And the other arrow goes to the people.
1058
00:40:54,215 --> 00:40:55,114
There are 3 categories
1059
00:40:55,815 --> 00:40:56,474
of people.
1060
00:40:57,094 --> 00:40:59,414
The community of practice of your company or
1061
00:40:59,414 --> 00:41:02,534
enterprise social network, whatever you call it. Okay?
1062
00:41:02,534 --> 00:41:04,875
So you seek knowledge through these groups.
1063
00:41:05,494 --> 00:41:08,855
The second one is the community of practice
1064
00:41:08,855 --> 00:41:10,519
of interest of the industry.
1065
00:41:11,059 --> 00:41:13,860
And the third one is your own personal
1066
00:41:13,860 --> 00:41:14,360
network.
1067
00:41:14,739 --> 00:41:16,739
What I said about this is that you
1068
00:41:16,739 --> 00:41:17,960
are as strong
1069
00:41:18,340 --> 00:41:19,400
as your personal
1070
00:41:19,780 --> 00:41:20,920
trusted network.
1071
00:41:21,539 --> 00:41:23,239
Because when you need something
1072
00:41:23,765 --> 00:41:26,405
real deep, you're gonna pick the phone and
1073
00:41:26,405 --> 00:41:29,125
call a friend of yours that you trust
1074
00:41:29,125 --> 00:41:31,364
or not even necessarily a friend, but a
1075
00:41:31,364 --> 00:41:34,565
person that you trust. When I was, VP
1076
00:41:34,565 --> 00:41:37,390
of IT in my early days at STI,
1077
00:41:37,530 --> 00:41:39,930
we had to implement an SAP system, which
1078
00:41:39,930 --> 00:41:41,309
I had no knowledge of.
1079
00:41:41,690 --> 00:41:44,110
But I called my counterpart CIO
1080
00:41:44,489 --> 00:41:45,230
at Siemens,
1081
00:41:45,690 --> 00:41:47,469
which I knew they were implementing
1082
00:41:47,930 --> 00:41:50,670
SAP, and I learned from that
1083
00:41:50,994 --> 00:41:53,795
CIO all the experiences and what was to
1084
00:41:53,795 --> 00:41:55,014
my vendor. That
1085
00:41:55,315 --> 00:41:57,875
ability to have a network and be able
1086
00:41:57,875 --> 00:41:58,855
to call somebody
1087
00:41:59,315 --> 00:42:02,614
in your network and cultivate that network because
1088
00:42:02,835 --> 00:42:04,775
cultivating network is important.
1089
00:42:05,500 --> 00:42:08,220
Cultivating the network means that you have to
1090
00:42:08,220 --> 00:42:11,039
be willing to give knowledge to them
1091
00:42:11,420 --> 00:42:11,920
continuously.
1092
00:42:12,380 --> 00:42:14,640
You see something that you think this person
1093
00:42:14,700 --> 00:42:17,099
could use, send them an email, send them
1094
00:42:17,099 --> 00:42:19,065
a text message with a link to that
1095
00:42:19,065 --> 00:42:21,224
video and so on for no reason, for
1096
00:42:21,224 --> 00:42:22,844
just the reason of sharing.
1097
00:42:23,304 --> 00:42:25,625
But maybe 10 years down the road, you
1098
00:42:25,625 --> 00:42:27,864
need that person, and you're gonna call that
1099
00:42:27,864 --> 00:42:30,184
person. They'll remember you Yeah. And they're willing
1100
00:42:30,184 --> 00:42:32,369
to help. So what you're talking about is
1101
00:42:32,369 --> 00:42:33,589
being the good Samaritan
1102
00:42:33,969 --> 00:42:36,469
or a good steward. This is stewardship
1103
00:42:36,849 --> 00:42:38,469
practices. You're feeding
1104
00:42:39,010 --> 00:42:41,889
as you eat. You are sharing as you
1105
00:42:41,889 --> 00:42:44,550
learn. You are a combination of things,
1106
00:42:44,934 --> 00:42:46,554
and you're in community
1107
00:42:46,855 --> 00:42:48,234
with your community.
1108
00:42:48,855 --> 00:42:51,014
And that's where I think you're hitting gold
1109
00:42:51,014 --> 00:42:53,335
because I think a lot of organizations don't
1110
00:42:53,335 --> 00:42:54,934
foster that. Yeah. But I think at the
1111
00:42:54,934 --> 00:42:55,835
end of the day,
1112
00:42:56,135 --> 00:42:56,635
you,
1113
00:42:57,094 --> 00:42:58,554
should take responsibility
1114
00:42:58,934 --> 00:43:01,500
for your own life and in particular for
1115
00:43:01,500 --> 00:43:02,400
your own learning.
1116
00:43:03,019 --> 00:43:03,680
That's something
1117
00:43:04,380 --> 00:43:05,119
my network,
1118
00:43:05,739 --> 00:43:06,960
and I'm a pack rat.
1119
00:43:07,500 --> 00:43:09,519
There's every time I meet somebody,
1120
00:43:09,900 --> 00:43:11,820
I put the name of the place and
1121
00:43:11,820 --> 00:43:14,239
the date into the notes section.
1122
00:43:14,619 --> 00:43:17,255
And I have people that opted my professional
1123
00:43:17,315 --> 00:43:18,454
career in 1977.
1124
00:43:19,074 --> 00:43:21,315
So you can imagine how many names I
1125
00:43:21,315 --> 00:43:23,574
have in the in the system. Take responsibility
1126
00:43:24,034 --> 00:43:26,194
for building your network. You don't need a
1127
00:43:26,194 --> 00:43:28,194
company to tell you what to do. So
1128
00:43:28,194 --> 00:43:30,054
you're talking about personal responsibility.
1129
00:43:30,755 --> 00:43:33,500
That is a piece of good leadership. If
1130
00:43:33,500 --> 00:43:35,179
you are a and I hate to use
1131
00:43:35,179 --> 00:43:37,099
the term. If you are a master of
1132
00:43:37,099 --> 00:43:37,840
your domain,
1133
00:43:38,619 --> 00:43:40,960
then you can be better prepared
1134
00:43:41,260 --> 00:43:43,820
and ready to roll. Yeah. It's like any
1135
00:43:43,820 --> 00:43:46,239
situation in life. We've seen that
1136
00:43:46,974 --> 00:43:47,474
preparation
1137
00:43:47,775 --> 00:43:48,094
is,
1138
00:43:48,655 --> 00:43:51,315
a good thing. It reduce stress. It reduce,
1139
00:43:51,775 --> 00:43:52,275
mistakes.
1140
00:43:53,214 --> 00:43:55,375
Do not avoid them all the time, but
1141
00:43:55,375 --> 00:43:57,214
at least it is a great factor of,
1142
00:43:57,454 --> 00:43:57,954
reducing
1143
00:43:58,670 --> 00:43:59,570
those negative
1144
00:43:59,950 --> 00:44:02,510
effect in life. We've wrapped up the show
1145
00:44:02,510 --> 00:44:04,849
with a whole bunch of elements
1146
00:44:05,230 --> 00:44:07,170
all balled up into just
1147
00:44:07,630 --> 00:44:11,090
progress. I'll just label this as personal progress,
1148
00:44:11,230 --> 00:44:13,550
takes a lot of work, and it's not
1149
00:44:13,550 --> 00:44:16,295
easy. And if you don't continue it, if
1150
00:44:16,295 --> 00:44:18,135
you don't share it, if you don't develop
1151
00:44:18,135 --> 00:44:21,494
it, then progress will be beyond your reach.
1152
00:44:21,494 --> 00:44:21,994
Yes.
1153
00:44:23,974 --> 00:44:26,135
I left him speechless. Yeah. I I go
1154
00:44:26,135 --> 00:44:28,710
back to my passion. Okay. I'm passionate about
1155
00:44:28,949 --> 00:44:30,650
electronic and software technologies
1156
00:44:31,109 --> 00:44:33,690
as key enabler to the world progress.
1157
00:44:34,150 --> 00:44:36,869
And this is why I'm so hungry of
1158
00:44:36,869 --> 00:44:40,630
learning every day to actually feed myself in
1159
00:44:40,630 --> 00:44:43,835
terms of, passion. And for me, it's just,
1160
00:44:43,835 --> 00:44:45,214
you know, being able
1161
00:44:46,394 --> 00:44:49,594
to reinvent yourself in your career. Top domain
1162
00:44:49,594 --> 00:44:51,914
right now, which is AI, is something that
1163
00:44:51,914 --> 00:44:52,974
happened because
1164
00:44:53,275 --> 00:44:54,094
you constantly
1165
00:44:54,394 --> 00:44:56,014
I'm constantly able to reinvent
1166
00:44:56,315 --> 00:44:56,815
myself
1167
00:44:57,480 --> 00:44:58,300
and adapt,
1168
00:44:58,760 --> 00:45:01,019
learn, and grow with this.
1169
00:45:01,480 --> 00:45:03,739
It's my way of being happy in life
1170
00:45:03,880 --> 00:45:04,380
professionally
1171
00:45:04,920 --> 00:45:06,940
is that to feed that intellect
1172
00:45:07,239 --> 00:45:08,699
with continuous learning
1173
00:45:09,309 --> 00:45:10,300
and thing. And
1174
00:45:10,625 --> 00:45:13,105
and I read not only about AI. I
1175
00:45:13,105 --> 00:45:16,065
read about biology. I read about many domain.
1176
00:45:16,065 --> 00:45:18,085
Actually, one of my recommendation
1177
00:45:18,864 --> 00:45:22,085
is that when you do develop your personal
1178
00:45:22,625 --> 00:45:23,125
knowledge
1179
00:45:23,639 --> 00:45:25,659
routine or knowledge hygiene,
1180
00:45:26,280 --> 00:45:28,359
do it in a way that is very
1181
00:45:28,359 --> 00:45:28,859
diverse.
1182
00:45:29,159 --> 00:45:31,719
I have something called TED Tuesday. So every
1183
00:45:31,719 --> 00:45:34,299
Tuesday at lunch, I watch a TED talk.
1184
00:45:34,440 --> 00:45:36,535
I don't select the TED talk. I go
1185
00:45:36,535 --> 00:45:39,175
into TED, the application, and it says surprise
1186
00:45:39,175 --> 00:45:39,675
me.
1187
00:45:40,934 --> 00:45:42,454
Well, it does tell me how much time
1188
00:45:42,454 --> 00:45:44,295
do you have, 5 minutes, 10 minutes, 15
1189
00:45:44,295 --> 00:45:46,934
minutes. And then I learn about things that
1190
00:45:46,934 --> 00:45:48,135
would have Something totally
1191
00:45:48,695 --> 00:45:49,434
yeah. Exactly.
1192
00:45:49,849 --> 00:45:52,650
You're you're playing knowledge roulette. Right? You're just
1193
00:45:52,650 --> 00:45:54,730
like, I I'll take what you send me.
1194
00:45:54,730 --> 00:45:57,130
I I'm open. I think that there is
1195
00:45:57,130 --> 00:45:57,789
a value,
1196
00:45:58,409 --> 00:45:59,469
a very, very
1197
00:45:59,769 --> 00:46:01,934
important value of diversity of thought
1198
00:46:02,494 --> 00:46:05,775
And being able to apply also this to
1199
00:46:05,775 --> 00:46:06,275
knowledge
1200
00:46:06,655 --> 00:46:09,155
access and knowledge acquisition and learning
1201
00:46:09,855 --> 00:46:12,335
is key. The world is so complex right
1202
00:46:12,335 --> 00:46:13,555
now. Think about
1203
00:46:13,949 --> 00:46:16,269
what's happening in the war. I have friend
1204
00:46:16,269 --> 00:46:18,510
that are Russian, and I talk with them
1205
00:46:18,510 --> 00:46:20,849
to understand how they view things.
1206
00:46:21,150 --> 00:46:23,230
You know, they they're not very happy right
1207
00:46:23,230 --> 00:46:25,309
now as you can imagine, but think about
1208
00:46:25,309 --> 00:46:26,609
what's happening in Palestine
1209
00:46:27,309 --> 00:46:27,889
and Israel.
1210
00:46:28,764 --> 00:46:29,264
Understanding
1211
00:46:29,804 --> 00:46:32,224
the different point of view of those people
1212
00:46:32,284 --> 00:46:32,784
also
1213
00:46:33,085 --> 00:46:34,625
and not going to conclusion
1214
00:46:35,005 --> 00:46:35,505
immediately,
1215
00:46:35,965 --> 00:46:38,764
being able to form your own opinion based
1216
00:46:38,764 --> 00:46:39,664
on diversity
1217
00:46:40,125 --> 00:46:42,619
of thoughts is very important. I can't agree
1218
00:46:42,619 --> 00:46:45,019
more, my friend, and thank you very much
1219
00:46:45,019 --> 00:46:47,760
for being an intricate part of our concepts
1220
00:46:47,820 --> 00:46:50,079
and education and learning around knowledge.
1221
00:46:50,380 --> 00:46:52,460
Well, thank you for what you're doing in,
1222
00:46:52,700 --> 00:46:56,525
in spreading diversity of thoughts from, those people
1223
00:46:56,525 --> 00:46:59,005
that you interview, and I hope I helped,
1224
00:46:59,405 --> 00:47:01,664
add water to your well. Oh.
1225
00:47:02,204 --> 00:47:03,505
I'm liking that.
1226
00:47:03,804 --> 00:47:05,849
You've added good water to this well.
1227
00:47:15,849 --> 00:47:18,644
Thank you for joining this extraordinary journey, and
1228
00:47:18,804 --> 00:47:21,765
we hope the experiences gained add value to
1229
00:47:21,765 --> 00:47:24,425
you and yours. If you'd like to contact
1230
00:47:24,485 --> 00:47:25,784
us, please email
1231
00:47:26,244 --> 00:47:26,744
bynpk@pioneersdashks
1232
00:47:30,476 --> 00:47:32,337
dotorg, or find us on LinkedIn.