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