00:00:00
our next speaker is actually fortunate
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enough to have had seen his brand name
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turn into a verb one of the probably
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most fific Executives in this current
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generation is mesh Aurora the Big Daddy
00:00:13
of the cyber security space these guys
00:00:14
are really at the Forefront of the
00:00:15
industry there are very few people who
00:00:17
consistently time and time again find a
00:00:20
way to just persevere be relevant NES is
00:00:24
one of those people this is a man who
00:00:25
has tremendous insight into technology
00:00:27
he helped turn Google into the dominant
00:00:29
player in search this is the most
00:00:31
Innovative industry in the world who
00:00:32
were constantly paranoid from an
00:00:33
innovation perspective I've got to be in
00:00:35
my toes because once we figured out how
00:00:37
they did it last time they're trying a
00:00:39
new way to do it next time this is the
00:00:40
country where your dreams come true and
00:00:42
if you go around the world and you ask
00:00:44
young people where do they want to go
00:00:46
they still want to come to America I
00:00:48
think this is one of the most successful
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democracies in the world this is where
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capitalism thrives all right ladies and
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gentlemen niora
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guy appreciate you thanks for
00:01:02
coming David David how are you what's up
00:01:07
BR
00:01:09
um let me just do this intro properly
00:01:12
look at all the phones go up
00:01:16
wow you joined Google in 2004 although
00:01:20
there was a nice prolific buildup to
00:01:22
that career but you joined in 2004 you
00:01:24
left in
00:01:26
2014 um you started in ad sales and you
00:01:29
left as the SVP and chief business
00:01:31
Officer of Google Revenue went from 3
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billion I checked this actually just to
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make sure cuz I have it's staggering to
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66 billion when you left and then you
00:01:40
because we're going to talk about that
00:01:42
and then you got seduced to go work with
00:01:44
Masa yoshian at soft Bank where you're
00:01:46
Vice chairman and president yeah that
00:01:48
must have been interesting Jason has a
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look at
00:01:51
Jason he's looking
00:01:53
ATP so many good questions um there we
00:01:57
go but then you left yes and look I've
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known you for a long time we've been
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very good friends for a long time I was
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surprised because I got you know you
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called and you're like hey I'm going to
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be SE chairman and CEO of Paulo Alto
00:02:09
networks and I had known what it was but
00:02:12
I didn't really understand uh and then
00:02:14
meanwhile in the last what's it been
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seven years six and a half six and a
00:02:18
half years um market cap is up by 5x you
00:02:21
took a 20 billion company it's 110
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billion as it stands I think you've
00:02:24
tripled Revenue um so this is clearly no
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longer luck so now you're you're in the
00:02:31
skill Camp oh good um I'm in founder
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mode no founder mode is cocaine I was
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wondering when
00:02:38
that I was going I was wondering founder
00:02:41
mode on you no he has to fly to Europe
00:02:43
you cannot bring founder mode no waffles
00:02:46
on the plane no waffles on the you can
00:02:48
get founder mode in Europe though heard
00:02:50
start let let's just start and just um
00:02:53
actually let's just start there okay um
00:02:56
you've seen a lot of different
00:02:57
Executives You' played a lot of
00:02:58
different roles you've seen Founders
00:03:00
you've advised a lot of Founders tell us
00:03:02
what what what takes what what does it
00:03:05
take to be successful and you can use
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these labels or not founder mode manager
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mode whatever it is but what does it
00:03:10
take to figure things out
00:03:13
consistently look um I think you already
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put that out there didn't you didn't you
00:03:18
say that uh if you think about building
00:03:20
great businesses at the center of great
00:03:23
businesses great products if you don't
00:03:25
have a great product you're not going to
00:03:26
build a great business for the long term
00:03:28
and this is something I know Serge is
00:03:29
here I learned that with Larry and
00:03:31
Sergey at Google that they were obsessed
00:03:33
about product on a constant basis so
00:03:34
when I came to my job I said the first
00:03:36
thing I'm to focus on is build a great
00:03:38
product but I think it's slightly
00:03:40
different in consumer and Enterprise in
00:03:42
consumer you build a great product you
00:03:43
find the fly wheeel you try and figure
00:03:45
out how the fly continues to work an
00:03:47
Enterprise eventually you take a great
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product you got to figure out how to get
00:03:50
it out to all the amazing customers out
00:03:52
there so I think it requires a
00:03:54
tremendous amount of focus tremendous
00:03:56
amount of um sort of detail inspection
00:04:01
but I think at the same time you got to
00:04:02
find a way of taking lots of amazing
00:04:04
people getting them on the same train
00:04:07
and getting them to execute at scale
00:04:09
it's impossible for one human being to
00:04:11
do that at scale so you have to have a
00:04:13
lot of people doing it amazingly well
00:04:15
that's the trick tell tell us about that
00:04:16
first that first story or that version
00:04:19
of that story inside of Google because
00:04:20
you were there for a long time and a lot
00:04:21
of good things happened what was that
00:04:23
like what did you learn look Google has
00:04:26
one of the best flywheels there is in
00:04:28
the consumer space right so we were
00:04:30
blessed that we're working with a
00:04:31
product that nobody had ever seen
00:04:33
everybody wanted to use and it's funny
00:04:35
like every one of us worries about
00:04:37
customer support he didn't need it it
00:04:38
was an amazing simple product easy to
00:04:40
use free and our job was to go monetize
00:04:43
advertising so part of that was how do
00:04:45
you scale that around the world in every
00:04:47
country where there is a single product
00:04:49
with a single use case where you have to
00:04:52
see how you can attract lots of
00:04:53
advertisers and that requires building a
00:04:54
system how you get thousands of people
00:04:56
around the world to build a system and
00:04:58
execute so
00:05:00
you build a system you build a
00:05:01
programmatic system you look at stuff
00:05:03
you inspect and you have really amazing
00:05:05
people who gotten do their best that
00:05:06
they can and when you're doing that and
00:05:08
the thing is growing so fast what is the
00:05:10
what has to happen for you to go from
00:05:12
running Europe I think is how you
00:05:14
started to being the head of business
00:05:16
there what does that take well you know
00:05:19
it was such an amazing Juggernaut that
00:05:21
you had to figure out how to
00:05:22
differentiate and what is interesting
00:05:23
cuz when I joined Google was
00:05:26
24% of global Revenue when I moved to
00:05:30
the US it was
00:05:31
49% and in Europe yes in this one of the
00:05:34
few tech companies in the world whose
00:05:36
European Revenue was higher than the US
00:05:38
revenue for a brief period of time so I
00:05:41
think somebody
00:05:42
noticed and what what happens you get
00:05:44
the call and you're like we need you to
00:05:45
move to America yeah I was uh I was on a
00:05:49
trip to Russia trying to open an office
00:05:51
there which had to be shut down at some
00:05:52
point in time for a bit um and I got a
00:05:55
call from Eric Schmidt and he said your
00:05:57
boss is retiring we'd like you to come
00:05:59
here here and do what he does that was
00:06:03
it um and so why what then motivates you
00:06:06
to leave a job like that because you're
00:06:08
you're kind of then at the top of the
00:06:09
Pinnacle you see everything you're
00:06:11
meeting
00:06:13
everybody I guess uh I wanted more I
00:06:17
wanted to do more get involved sort of
00:06:18
the overall business wanted to do some
00:06:20
product work as well I didn't have
00:06:22
product jobs at Google I've seen as a
00:06:23
sales guy at P all I do is product for
00:06:26
the first six years of my life yeah so
00:06:28
do be able to go out and do that
00:06:29
differently but I had to take a brief
00:06:31
Soldier on to my Japanese trip lots of
00:06:33
good sushi and lots of it was a great
00:06:35
vacation let's talk about it oh come on
00:06:37
it wasn't a vacation well great surger
00:06:40
but I mean it this was the largest
00:06:43
Venture fund ever created $100 billion
00:06:46
and you have this Mercurial
00:06:49
brilliant individual masi yoshian and um
00:06:52
he starts placing bets in a way that
00:06:54
we've never seen what was the genius in
00:06:58
that and what was the the Achilles
00:07:00
heal look um Masa is one of those people
00:07:05
whose risk appetite grew as he grew
00:07:09
older and you mention that because that
00:07:11
is a very unique thing it usually goes
00:07:13
think about I have two young kids and
00:07:15
every time you know I'm constantly
00:07:16
trying to drisk them saying hey be
00:07:18
careful when you cross the road be
00:07:19
careful when you do this you get married
00:07:21
people tell you be careful buy a house
00:07:23
go settle down so we're constantly
00:07:25
drisking Our Lives as we get older on a
00:07:27
constant basis all of us do it we don't
00:07:29
realize we do it right Mas is the
00:07:32
opposite the older he gets like come on
00:07:35
let's go all in he's like you guys right
00:07:37
he wants to go all in so he's like N I
00:07:40
have a great idea we'll put a billion
00:07:42
we'll borrow 19 billion I'm how does
00:07:44
that work again all you got is a billion
00:07:46
yeah I have one great idea a billion in
00:07:48
19 billion that's what he did that's how
00:07:50
he buil SoftBank Japan I think he was
00:07:52
the richest man in the world for 88 days
00:07:54
in the last internet boom then he was
00:07:56
left with a billion dollars unbelievable
00:07:59
from scratch again so yes un so there
00:08:02
were a series of incredible bets yes
00:08:04
maybe walk us through some of those bets
00:08:06
because there was Nvidia there was arm
00:08:09
so all those happened after I left but
00:08:10
that's and then you had arm happen after
00:08:12
you left that was where we kind of you
00:08:15
know unpack it sorry unpack that uh
00:08:19
unpack
00:08:20
this
00:08:23
uh well Masa likes a trillion he likes
00:08:28
the number one trillion yes
00:08:30
so okay it's a good number it's better
00:08:31
than a billion beats a billion it beats
00:08:34
it is greater than a billion it's
00:08:35
greater than a billion last day Check
00:08:36
Yes um and when I met him the first time
00:08:40
after we' done a deal at Google he was
00:08:42
uh you know we met when he was
00:08:45
uh he came to see Larry Sergey and Eric
00:08:48
and said I'd like to do a search deal
00:08:51
with you I have yaho Japan I try to
00:08:53
explain to him there's something called
00:08:55
like you can't have two search engines
00:08:57
both powered by Google in Japan and to
00:08:59
say you can as long as the advertising
00:09:00
systems are different so if you look in
00:09:03
Japan today Yahoo Japan is powered by
00:09:04
Google and Google's powered by Google
00:09:06
but the advertising systems are
00:09:07
different hence it's non-competitive so
00:09:09
he got that done and then he's uh says
00:09:12
to me showed me this plan he was going
00:09:13
to buy a lot of companies in Telecom and
00:09:15
get to $100 billion in iida which at 10
00:09:18
times iida would be a trillion
00:09:20
dollar okay so then that kind of fizzled
00:09:23
out he lost interest after a while and
00:09:24
then his next idea was to raise I think
00:09:27
it was 1 2 3 4 100 200 300 and 400
00:09:31
billion dollars yes for the vision fund
00:09:34
so that'll make a
00:09:35
trillion on a second let's we're doing
00:09:38
that yeah that's a trillion dollars one
00:09:40
two three four yeah yeah you know it's
00:09:41
interesting and then like he had the
00:09:42
whole portfolio companies and there's a
00:09:44
bunch of Japanese analysts who sit in
00:09:46
the office MBS from University of Tokyo
00:09:49
and eventually they took all the
00:09:50
business we had and forecast their fee
00:09:53
cash flow at the end where the DCF was a
00:09:56
trillion so he was good at setting goals
00:10:02
so he thought arm was going to be a
00:10:04
trillion dollar company got it um we
00:10:06
were let me ask do you think the was the
00:10:09
mistake not the mistake is is it about
00:10:12
being financially oriented as opposed to
00:10:15
product or impact oriented is there an
00:10:17
orientation thing there where if money
00:10:19
is the goal it becomes a lot harder to
00:10:21
achieve versus well I look money is a
00:10:23
way to keep track it's not the goal that
00:10:25
was the way he kept track I get it but
00:10:28
you know he was not financi unit as much
00:10:30
as he went by his gut he you know it's
00:10:32
like many Founders when he believed in
00:10:34
it he was all in he totally believed in
00:10:37
it and sometimes to a fault and you saw
00:10:40
that one thing I did learn from which is
00:10:41
very fascinating is you know like a
00:10:44
person who's like used to getting things
00:10:46
wanting to get things right I'd make an
00:10:48
investment with him and then be one
00:10:49
investment say that's not going let
00:10:51
me go and talk to the company help them
00:10:52
help them fix it we can get them up and
00:10:54
run he calls me S one day this Nik
00:10:56
you're spending too much time with the
00:10:58
mistake
00:11:01
he said if you go spend that time with a
00:11:03
company that's growing at three times
00:11:04
they can grow at six times we'll make
00:11:06
our money up six times in that company
00:11:07
instead of you trying to fix that from
00:11:09
half back to one so it's kind of
00:11:11
interesting you know that's an
00:11:12
incredible lesson
00:11:14
actually cut sunken cost I mean there's
00:11:17
a million ways to say it but you have to
00:11:19
let your winners ride you got to focus
00:11:21
on the winners go all in on the winers
00:11:23
go all on the it's hard to do it's hard
00:11:25
to say oh my God I made a mistake you go
00:11:26
and say I can fix it I'm good I'm going
00:11:28
to Sal
00:11:30
yeah that's an e problem that's a
00:11:31
Hubert's problem I don't want to have a
00:11:33
mistake on my record or a good person
00:11:35
wants to help the founder you know
00:11:38
realize their vision and the Cutthroat
00:11:41
nature of this with the power law is
00:11:44
such that six Xing something that was at
00:11:46
3x is much much more likely than getting
00:11:50
a zero to a one do you do you apply that
00:11:53
principle it's an operator and if so
00:11:55
like how at P Alto networks look uh in
00:11:57
the last 6 and a half years I've got 19
00:12:01
companies right we can show the you can
00:12:04
the slides we got slid we got some
00:12:06
slides that just here's your stock good
00:12:08
job thank
00:12:10
you it's not bad go back let's see if
00:12:14
you go back it's go back a second back y
00:12:17
what's the market cap now 110 billion
00:12:19
110 billion yeah that's where they and
00:12:21
when you started it was at 20 20 20 what
00:12:24
you're seeing here is um the um economic
00:12:27
principle of uh founder
00:12:30
mode okay and the re the revenue and the
00:12:33
uh operating income yum yum which so how
00:12:37
do you how do you look at something like
00:12:39
this when you were first approached for
00:12:40
the job how do you underwrite the job
00:12:43
like what are you looking at and you
00:12:44
said you you I mean you spent the last
00:12:46
six and a half years in product did you
00:12:48
see a product that just it was was it
00:12:49
missing something that's the thing I
00:12:51
want to hear about it like did you go
00:12:52
all in on one or two brok that was
00:12:54
always the Steve Jobs model was pick the
00:12:55
winner and go all in on it get rid of
00:12:57
all the other stuff does that principle
00:12:59
apply here or no this is slightly
00:13:01
different principle look yeah it's $180
00:13:02
billion industry on an annual basis the
00:13:05
largest market share was one and a half%
00:13:08
which is us and it's a sub sector of
00:13:10
Technology the most amount of
00:13:11
fragmentation you look around you know
00:13:13
bennyhoff I think is going to be here
00:13:14
builds builds a platform for Salesforce
00:13:16
you have service now you have work dat
00:13:18
there is no cyber security platform you
00:13:19
sit there and say this is a phenomenal
00:13:21
opportunity one two it's a company
00:13:23
that's fully public so I don't have to
00:13:24
deal with voting controls and Founders
00:13:26
who I have to deal with which have
00:13:28
different mod motivations um it's a
00:13:32
Evergreen sector there more we get
00:13:35
connected the more people want to hack
00:13:36
the more you're going to connect it the
00:13:37
more data is there for people to take
00:13:39
away so you're not going to have a
00:13:40
demand problem yeah sadly if you can go
00:13:43
into sector where there's no demand
00:13:44
problem you can look at it and say what
00:13:46
did everybody get wrong so well
00:13:47
everybody sort of lived in their swim
00:13:48
Lane so we were in our swim Lane we did
00:13:51
one thing there are five swim Lane in
00:13:53
cyber security in six years we looked
00:13:56
forward and said where is the world
00:13:57
going to it's going to the cloud there's
00:13:59
a bunch of AI that was our sort of
00:14:00
plastics moment cloud and AI so we said
00:14:03
let's not go reinvent the past so one of
00:14:06
the things I also learned during you
00:14:07
know my time at Google and Masa is like
00:14:10
a lot of people get hung up in trying to
00:14:12
make the stuff work assuming everything
00:14:14
around you is going to stay the same so
00:14:16
say now we're just going to focus that
00:14:17
assume that 50% of the world is in the
00:14:19
public Cloud what's security going to
00:14:21
look like then assume latency is low you
00:14:23
can process in the cloud data storage is
00:14:25
cheap what's going to change so we built
00:14:28
for that we bought 19 companies we went
00:14:31
and looked at how everybody does m&a and
00:14:33
who failed oh what did you learn from
00:14:36
that well we learned that people things
00:14:39
trade at a price for a reason so very
00:14:41
often people say you know what ah number
00:14:43
one is a billion dollars number four is
00:14:45
$200 million I can take $200 million and
00:14:47
clean it up and fix it it's at 200 for a
00:14:50
reason and the billions of billion of
00:14:51
Reason they'll still be around yes so
00:14:54
why don't we guy the buy buy buy the guy
00:14:56
who's got who's worth a billion dollars
00:14:57
we'll be number one we'll be leading the
00:14:59
market we have brute force that go to
00:15:01
market we'll go use that and we're
00:15:04
probably going to slow them down a
00:15:05
little bit because they're a larger
00:15:06
company so we'll compensate for slowdown
00:15:09
with go to market that we bring to them
00:15:11
and we'll let them lose so we're the
00:15:12
only company where when we acquired
00:15:14
companies there a funny story is I got a
00:15:16
guy who says oh great we're buying a
00:15:18
company in Cloud security I'm the senior
00:15:19
vice president of blockchain cloud and
00:15:22
AI I'm like great welcome to your new
00:15:26
boss it's like what do you mean I said
00:15:28
that's the guy going to work for like we
00:15:30
just bought his company I said yeah he
00:15:31
kicked your ass with low resources out
00:15:34
there in the market you're going to
00:15:35
learn something from him there you go
00:15:36
Welcome to New York boss well you
00:15:41
know there is an analogy you uh share a
00:15:44
passion for basketball as well I see you
00:15:46
all the time at the Warriors game and I
00:15:48
I I don't think this is a jump to say
00:15:50
watching that team play and how they
00:15:52
manage talent and play as a team
00:15:54
definitely informed how you play the
00:15:56
game yeah that not lately but yes in the
00:16:01
past but look we've done that 19 times
00:16:04
we had seven out of 10 we've gotten
00:16:05
right and we still possibly have the
00:16:08
most number of Founders who still work
00:16:10
for palal yeah actually can you explain
00:16:12
that so when you buy a company isn't the
00:16:13
typical motivation wait till I Cliff
00:16:15
it's a year and then most people just
00:16:17
Vose they're gone no no so here's how it
00:16:19
works if you come to palal we'll take
00:16:21
your Equity away first we like I'm going
00:16:23
to give you back one and a half times of
00:16:25
equity if you stay with me for 3 years
00:16:28
oh wow to the founder yes okay wait a
00:16:30
second so the founder owns let's say
00:16:32
it's a100 million a billion dollar
00:16:34
company they own 20% they got 200
00:16:35
million you say hey stay again I'll give
00:16:37
you 300 million right got to work for me
00:16:40
for three years pretty good because when
00:16:42
you buy a company you're buying a half
00:16:45
half a product and a full vision ah
00:16:48
right I lose the vision part of it I get
00:16:51
half a product right that's how much of
00:16:54
the success is predicated on the engine
00:16:57
at paloalto networks to drive sales to
00:16:59
sell into the Enterprise how much do you
00:17:00
come in and then the founder feels like
00:17:02
there's an interference model now that's
00:17:04
like how are you getting in my way and
00:17:06
so how do you manage that balance so
00:17:08
what happens is like look the customers
00:17:10
in security want the best product that's
00:17:11
why everybody lived in their swim Lanes
00:17:13
we said we got to be in multiple swim
00:17:14
Lanes to be in multiple swim Lanes with
00:17:16
multiple people saying I've got great
00:17:17
products you know in Enterprise there's
00:17:19
this bizarre thing called Magic
00:17:20
quadrants which Gardner has and your you
00:17:23
your badge of honor is you're on the top
00:17:25
right which is the leader cordant in in
00:17:27
Garder when I joined p in two we're in
00:17:30
24 right now in the top right so now
00:17:33
when you go to customer saying hey I got
00:17:34
some great products you're going to sell
00:17:36
me some good and some bad like you know
00:17:38
you pick there's all 24 are in the top
00:17:40
right and they all work together better
00:17:42
so for that we need the founders
00:17:43
building the product and staying there
00:17:45
yeah they do feel a little sometimes
00:17:46
they feel like they're being directed
00:17:48
but there's also another rule I had a
00:17:50
wonderful conversation with the founder
00:17:51
which was my first acquisition and I
00:17:53
think we didn't set the bit right so we
00:17:56
had to fix it in future deals SP the
00:17:58
founder reasonable amount of money
00:18:00
probably $850 million to the company he
00:18:02
had about $150 million he was going to
00:18:04
get2 200 then he comes into my office
00:18:06
and say Cas I had a
00:18:08
problem um I think we should do it this
00:18:10
way you're telling us to do it this
00:18:12
way because this way is the way it's
00:18:14
going to work for us he's like yeah but
00:18:16
when I came here you know with my
00:18:18
company I said oh wait a minute I said
00:18:22
have you ever sold a house it's like
00:18:25
yeah I said who decides what and you you
00:18:28
get to St in it who decides what color
00:18:30
the wall is going to be painted the new
00:18:32
owner the new owner of course I said
00:18:35
Thank
00:18:36
you so he stayed there he really liked
00:18:39
us and he stayed for three years he made
00:18:40
two and a half times that money he got
00:18:42
but from then on we changed the game
00:18:45
when we acquire a company we set the
00:18:46
founder down say okay the lawyers will
00:18:49
do their thing you're going to sit in my
00:18:50
head of product and design a product
00:18:52
strategy we both agree
00:18:54
on yeah so we don't buy a company until
00:18:56
we have a joint agreed product strategy
00:18:58
with the founder now in Cisco Oracle
00:19:01
Salesforce they've all kind of had this
00:19:02
m&a Playbook that they claim is part of
00:19:06
their engine of success how
00:19:07
differentiated is it for you what do you
00:19:10
what's kind of the biggest contrast for
00:19:12
your playbook versus those Eng biggest
00:19:15
contrast for us is we like to buy
00:19:18
product which we can integrate and sell
00:19:20
to customers we have a go to market
00:19:21
engine we like to keep it the way it is
00:19:24
I think if I'm going to buy a company at
00:19:27
8 to 10 times Revenue I'm just
00:19:29
overpaying for customers and sales I
00:19:32
have all the customers already why would
00:19:34
I pay 8 to 10 times Revenue to buy a
00:19:37
customer I already have it on a
00:19:38
different product so I'd rather buy the
00:19:40
product use my go to market capabilities
00:19:43
go sell them to the customer base unless
00:19:45
I can take the two companies merge them
00:19:48
and I can make it worth 16 times if you
00:19:51
you you as an investor can buy both our
00:19:52
companies enjoy yourself why would I
00:19:54
have to pay a premium to buy it at 8
00:19:55
times Revenue so we're very clear we
00:19:57
don't want to buy customer bases we want
00:19:59
to buy products which we can integrate
00:20:01
and sell into our customer base let's
00:20:02
talk a little bit about the threats that
00:20:04
are out there in the modern world how
00:20:05
they're evolving with artificial
00:20:07
intelligence obviously can be used on
00:20:09
both sides of the um of this competition
00:20:11
to see who can protect information and
00:20:13
then who can steal it who are the actors
00:20:17
what's the motivation today and how are
00:20:19
they coordinating because it feels like
00:20:21
there is now this
00:20:22
new um uh Allegiance between American
00:20:27
hackers very young anonymous
00:20:29
working with to do the social
00:20:31
engineering working with some Brute
00:20:32
Force tools out of China Russia other
00:20:35
places um who who's orchestrating these
00:20:39
very large um you know hacks that
00:20:43
occurred at the casinos recently and
00:20:46
then we can get into how should our
00:20:49
government if at all be thinking about
00:20:52
stopping these and partnering with
00:20:54
corporate America um and to neutralize
00:20:57
these threats because some of them are
00:20:58
are involving the governments of these
00:21:00
countries yeah so I think look if you
00:21:02
trace the history of cyber hacking we
00:21:04
had these big hacks which used to take
00:21:06
30 or 50 days to figure out people were
00:21:08
doing them as a hobby you'd think of
00:21:11
your notion of a hacker was some kid
00:21:12
sitting in their parents' basement who
00:21:14
didn't get out of there on his little
00:21:16
you know PC trying to hack this and
00:21:17
trying to get all the data out of there
00:21:19
and then suddenly people discovered wait
00:21:21
I can get better than this right because
00:21:23
it was usually to prove it's a badge of
00:21:25
honor oh I hacked into this database or
00:21:26
I hacked in there I got in there you
00:21:28
guys aren't strong enough now as the
00:21:29
world got more connected what happens
00:21:31
was people says wait why am I wasting my
00:21:33
time hacking one user one company at a
00:21:35
time let me go after a piece of supply
00:21:37
chain if I hack The Exchange Server
00:21:39
everybody uses an exchange server is
00:21:41
fair game if I hack a agent or not an
00:21:44
antivirus I can get everybody's computer
00:21:46
if I hack you know a large email
00:21:48
provider I can have access to every
00:21:49
dissident email which is when nation
00:21:51
states got involved nation state said
00:21:53
wait a minute if I got want data why
00:21:55
bother hacking one person let me go hack
00:21:58
the back end and get in let me Gmail yes
00:22:01
more effective so when that began to
00:22:04
happen began to happen nation states
00:22:06
started getting Wasing that's
00:22:06
interesting if I can if I can do that I
00:22:09
can destabilize Nations I can get data
00:22:11
about other people that I want so that
00:22:13
became a bit of a nation state activity
00:22:15
now cyber security offenses is way
00:22:17
easier than defense the defense you got
00:22:20
to right 100% of the time offens is
00:22:21
going to find one door so so put that
00:22:25
aside then what happen on top of that is
00:22:27
that nation state started cultivating
00:22:29
these entrepreneurs and the hacking
00:22:31
World saying listen that's how you keep
00:22:33
your skills up to date if you go after
00:22:34
stuff we'll look the other way while
00:22:36
we're going and doing it because if we
00:22:38
need you we' have found a way and then
00:22:41
we discovered this notion wait there's
00:22:43
tremendous economic value now in hacking
00:22:45
so we can ran somewhere people when to
00:22:48
says you and there's like a magic number
00:22:50
they ask for $30 million or less because
00:22:51
that's director's liability
00:22:54
insurance wait sorry sorry sorry when
00:22:55
when you get when you get hacked for
00:22:57
ransom 30 million is what is what
00:22:59
companies can give you where it's
00:23:00
covered by Insurance oh it's covered by
00:23:02
Insurance purely working backwards from
00:23:04
that
00:23:06
policy huh so there's about $2 billion
00:23:09
that's been paid in the last 12 months
00:23:10
on ransomware wow wow that if you think
00:23:13
here's here's the anatomy of a hack
00:23:15
right somebody says I found a solar wind
00:23:17
server it's hackable so they some set of
00:23:19
guys go quickly and plant themselves at
00:23:21
1,800 solar wind servers which are
00:23:23
exposed to the internet then there's a
00:23:25
separate industry sub Subs segment they
00:23:27
sell it to saying listen I'm only in the
00:23:29
seating business you can go run Ransom
00:23:31
as a Ser ransomware as a service
00:23:33
negotiations with customers wow that's
00:23:36
their go- to Market yes say they go to
00:23:37
market amplification to system
00:23:39
integration yes yeah and then there's a
00:23:41
third set of people who are payment
00:23:42
clearing people say I'll collect the
00:23:43
money I I know how to process $30 milon
00:23:45
bit oh my go so sophisticated this is so
00:23:48
sophisticated and where are they
00:23:49
geographically like where is it all over
00:23:51
everywhere everywhere everywhere where
00:23:52
extradition treaties are
00:23:54
light and uh Are there specific foreign
00:23:57
Nationals that it mooved to
00:23:58
jurisdictions to do this is this
00:24:01
like there's there's a lot of people in
00:24:04
the world out there who do this and
00:24:05
they're hard to find and remember think
00:24:07
about the
00:24:08
enforcement like where are you going to
00:24:10
go go to your local police station
00:24:11
you're freaking me
00:24:13
out somebody takes a million doll away
00:24:15
from your bank account who you going to
00:24:16
local police guy says actually sir this
00:24:18
looks like somebody in Greece yeah do
00:24:21
you know our our our like panic attack
00:24:23
yeah let me let me shift the
00:24:25
conversation I want to talk about AI for
00:24:27
a second cuz you mentioned it as well
00:24:29
um but I want to first ask it to you
00:24:31
more as just a smart Observer of the
00:24:33
market you're in the market you've
00:24:34
invested in a bunch of companies as well
00:24:36
um what's the state of
00:24:39
AI take it however you want whever yes I
00:24:41
mean look what's interesting is I think
00:24:44
a lot of people are chasing llms and I
00:24:46
think there's a very well established
00:24:49
expectation out there these llms will
00:24:50
get smarter and smarter inflence will
00:24:52
come latency will go down uh cost to
00:24:56
deploy cost to train will all come down
00:24:58
so the good news is we've seem to have
00:25:00
established a nicely competitive space
00:25:02
out there between all these people that
00:25:05
you can expect some sort of economic
00:25:07
rationality to Trail and a lot of people
00:25:09
are sort of investing a lot of dollars
00:25:11
to get it there and thanks to Mark
00:25:12
Zuckerberg throwing out open source
00:25:14
models he keeps them honest and fair
00:25:16
everywhere around there so we'll all get
00:25:17
access to to these models but for the
00:25:20
most part as you get into the
00:25:21
application of these models I think the
00:25:23
world changes in consumer Enterprise in
00:25:26
consumer you got to figure out how these
00:25:27
models are going to translate into
00:25:29
consumer services and make them better
00:25:31
and you can see that the question is do
00:25:33
we get a whole new Google that's formed
00:25:35
or a whole new Facebook that's created
00:25:38
or do the existing players move fast
00:25:40
enough to embody sort of to to embed AI
00:25:43
in there and our hooks those Services
00:25:45
have to us are so strong that we don't
00:25:47
shift yeah our usage yeah so let's spark
00:25:50
that for a second we'll go go back there
00:25:51
in a minute on the Enterprise side it's
00:25:54
not useful unless you can train on my
00:25:56
data and you'll disc 90% of companies
00:25:59
has bad
00:26:00
data 90% of companies like how do you
00:26:03
solve this from I don't know I don't
00:26:04
know how I fix the last firewall that
00:26:06
broke down if I don't have that data and
00:26:08
if I don't have 10 good instances how do
00:26:10
I make it work in the 11th instance so
00:26:13
we're all busy refactoring our data
00:26:15
figuring out how to collect good data on
00:26:16
the Enterprise side which is going to
00:26:18
happen it's all the easy stuff that
00:26:20
Sebastian will tell clar I've got it
00:26:21
figured out I'm going to answer
00:26:22
questions those are easy questions how
00:26:23
much balance do I owe you when do I owe
00:26:25
you can I pay you tomorrow no you have
00:26:26
to pay me today that even in iBot can
00:26:28
answer that question right but it's very
00:26:30
hard to say my firewall broke down I
00:26:31
don't know what happened how do I fix it
00:26:34
CU I need a lot of data so I think on
00:26:35
Enterprise side a lot of companies have
00:26:37
to do a lot of work to get their data
00:26:38
sorted and that's in process what we've
00:26:40
done is we stimulated all of us to go
00:26:42
out and get that figured out on the
00:26:44
consumer side it's going to be very
00:26:45
interesting I think we can all imagine a
00:26:47
future which says hey my favorite phone
00:26:50
or favorite Hardware device or favorite
00:26:51
interface go book me a ticket to Geneva
00:26:55
which I'm going after this and book me a
00:26:58
a restaurant and a hotel room now you
00:27:01
just in your brain said wait wait wait
00:27:03
wait I just did booking.com I did open
00:27:05
table and I did
00:27:07
hotels.com now we're going to see this
00:27:10
happen who's going to control the user
00:27:12
interface and whose agent is going to
00:27:13
talk to who right try telling any of the
00:27:17
existing app guys that listen suppressor
00:27:20
UI I'm just going to send you an API
00:27:21
call send it back to me I'll control the
00:27:23
data about the consumer yeah let's see
00:27:25
how far that lasts I mean that's yeah
00:27:28
might you're just handing over your
00:27:29
business to them yeah well then what's
00:27:31
going to happen one or two things happen
00:27:32
that always happens right these people
00:27:35
become the Legacy players and you'll
00:27:37
have new companies that are formed which
00:27:38
are agent based only it's like you know
00:27:41
yeah half your fortune is better than
00:27:43
none yeah so if I start a company
00:27:45
tomorrow I would say listen I only have
00:27:46
an agent that does Airline bookings just
00:27:48
pay me 20% I'm good I don't need a
00:27:51
brand what happens then so I think
00:27:54
there's going to be I think there's
00:27:55
going to be much more upheaval in the
00:27:56
consumer space than anyone of us realiz
00:27:59
this I think 5 million apps will be
00:28:00
redesigned in the next 10 years they'll
00:28:03
all become agents right the ones that
00:28:05
want to survive will do that first but
00:28:08
it's very hard yeah your margins my
00:28:10
opportunity I guess is the way we say it
00:28:12
in the industry yes yes but it's very
00:28:14
hard can you try going to any of these
00:28:16
large branded apps that sit on
00:28:17
everybody's phone and say listen shut it
00:28:20
off yeah become a service provider of
00:28:22
data they would they would just talk to
00:28:24
Siri just talk to whatever whatever it
00:28:26
is yeah and we'll get it done for you
00:28:28
um Ai and attacks and sophistication of
00:28:32
the attacks that
00:28:33
occur how how often does human factors
00:28:36
fishing tricking people come into play
00:28:40
these days and and how much of that can
00:28:42
is going to be exacerbated by AI deep
00:28:45
fakes Etc oh the attacks are most simple
00:28:49
most simple explain you know uh we had a
00:28:52
whole B Des company uh and they do this
00:28:58
is a thing they said listen we're going
00:28:59
to penetrate your defenses it's not not
00:29:02
possible it's just impossible we're
00:29:04
going to figure it out the guy goes in
00:29:06
the morning 8:00 at the parking lot
00:29:08
drops a bunch of USB T sticks with
00:29:10
little tape on it taks my home videos oh
00:29:13
my god wow he drops about 25 of them six
00:29:17
of them log in with the USB stick in the
00:29:19
computer in the office they're in oh my
00:29:21
God oh my God so great oh my so I
00:29:26
don't know if you need to go like get a
00:29:28
battery RAM and break your door do this
00:29:30
is It's human behavior human behavior
00:29:33
it's like and they possibly said
00:29:34
something more colorful than my home
00:29:35
videos on that but I'm just going to
00:29:37
keep it PG here right so you can decide
00:29:40
at what point in time your curiosity
00:29:42
with a
00:29:44
z that got 100% yeah so it's like these
00:29:47
are not heart attacks like you know
00:29:50
there's we had a we sent an email out
00:29:52
there we saying National Pet Day please
00:29:55
take a picture of your fluffy pet at
00:29:56
home and upload it to with his website
00:29:58
and the person who does it will give
00:30:00
$10,000 to the SPCA oh my God you seen
00:30:03
the beautiful fuzzy pictures uploaded to
00:30:06
this hacking site where we had all your
00:30:08
details all the IP addresses everything
00:30:11
yes everything no no you had to actually
00:30:12
add to your username oh godword and
00:30:14
there's things like is your pet so
00:30:16
wonderful that he used their name as a
00:30:18
password yeah let's what's your pet's
00:30:21
name love it let's uh love it let's F so
00:30:25
great this is not hard you don't need
00:30:27
like you know use cyber security sensors
00:30:29
to block this stuff uh okay wait flip it
00:30:31
around for a second there's something
00:30:32
going on I don't know if you read you
00:30:33
probably did uh there's a there's a an
00:30:36
explosion of deep fake porn in South
00:30:40
Korea going on right now that's not my
00:30:42
area of specialization
00:30:45
no you guys you guys might know more
00:30:47
about that heard from a friend I don't
00:30:49
have time for that kind of stuff no no I
00:30:51
met more he read on Twitter and jam
00:30:53
search for and there wasn't any no but
00:30:55
so there's all this fake content that's
00:30:56
going to emerge there's going to be all
00:30:58
is it fake somebody's fake is somebody's
00:31:00
reality yeah I know but my point is more
00:31:02
different how do you if you're asked by
00:31:04
a customer tell me if that's real or not
00:31:06
how do you figure out tomorrow if
00:31:07
something is real well look there's a
00:31:09
huge conversation going on that there
00:31:12
needs to be some form of Regulation that
00:31:14
insist that water marking needs to
00:31:15
happen if you generate a video using any
00:31:18
AI tool it has to say created by AI if
00:31:21
it doesn't it's very hard to tell the
00:31:23
difference yeah and as I was saying to
00:31:25
somebody else the other day it's like
00:31:26
most likely if it seems to perfect it
00:31:28
was probably created by how is that
00:31:30
different let me just ask philosophical
00:31:31
how is that different than airbrushing
00:31:33
in Photoshop than making the person look
00:31:35
completely different we we don't have
00:31:37
any of those disclosures today I always
00:31:39
feel like there's a spectrum that I
00:31:41
guess scale would be the issue right and
00:31:43
Fidelity I don't know sorry scale and
00:31:45
Fidelity like you know the number of
00:31:47
people who can do what you're saying is
00:31:49
.1% of the population or 1% now it's 100
00:31:52
I think if if it's with the intent to
00:31:54
deceive I see ah yeah anyway and then
00:31:57
what about on the other side in terms of
00:31:59
Defense have you started to make AI you
00:32:02
know uh Shields that yes yes so look the
00:32:06
two biggest risks today in AI are is
00:32:09
that I think about 20 to 30% of most
00:32:11
companies have employees the younger
00:32:12
side who are using AI apps to try and
00:32:16
get their job done faster and easier
00:32:17
write me a marketing blog try and figure
00:32:19
something out you know write me a script
00:32:21
for this or take this data analyze it
00:32:23
for me the risk there is that you're
00:32:24
sending proprietary data up into a model
00:32:27
oh yeah for company you know here's a
00:32:29
here's a napkin drawing of a chip design
00:32:31
I just made for inferencing turn this
00:32:33
into real CAD drawing for me they could
00:32:35
do it but except that that llm was
00:32:38
brought down from hugging face and it's
00:32:39
going back to North Korea yep so there's
00:32:42
that risk that your employees are being
00:32:44
targeted with AI apps in your company
00:32:45
who are uploading proprietary data in a
00:32:47
happy way very nicely for you same guy
00:32:50
who picked up the USB stick so there you
00:32:54
have we have a product that watches all
00:32:55
these apps and makes sure that what
00:32:56
you're using what you're uploading is is
00:32:57
not being sent to dangerous apps or if
00:33:00
you don't want your employees to send it
00:33:01
will block you the other one which is
00:33:03
kind of interesting is that I think
00:33:05
almost every company is experimenting
00:33:07
with deploying llms internally because
00:33:09
they all want their favorite proprietary
00:33:11
chat interface and there you need to be
00:33:15
careful because you can what you used to
00:33:17
do with SQL injection you can do with
00:33:19
prompt injection you can bombard models
00:33:21
you can bias them you can do a whole
00:33:22
bunch of stuff so we have you know what
00:33:24
we call an a firewall that will protect
00:33:26
you I want to be sensitive time I know
00:33:28
you have to fly to Geneva thank you very
00:33:29
much for coming ladies and gentlemen the
00:33:31
C thank you for
00:33:34
[Applause]
