00:00:00
it is the center of the technology world
00:00:03
right now it's not what Mark did it's
00:00:06
when he did
00:00:08
it and the king of the cloud is
00:00:11
Salesforce please welcome Mark
00:00:16
Ben one of the things that really
00:00:18
matters me is having a positive Global
00:00:20
impact technology is not good or bad
00:00:23
it's what you do with it that matters in
00:00:25
your quest to change the world don't
00:00:27
forget to do something for other people
00:00:31
and that was a moment in time when I
00:00:33
said wow when I start a company I'm
00:00:36
going to make sure that philanthropy and
00:00:38
giving and generosity and these values
00:00:41
are in the culture of the company from
00:00:43
day
00:00:47
one you want to stay
00:00:50
here are you want the couch you want to
00:00:53
sit on the couch where you want to sit
00:00:55
I'll give you the couch I'll sit
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here you deser you deserve the couch you
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deserve it the big couch
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okay it's little little too close it's
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nice to see you also I I warned you that
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I I'm not the the interviewer in the
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group you but this is you chose me so
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I'm
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honored but you're the nice one oh okay
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thank
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you well it is am I right is he the nice
00:01:24
one and you're the one that all the
00:01:26
women really like like I'll talk to my
00:01:28
friends at dinner there like you know
00:01:30
sax what's he like he's amazing let's
00:01:33
just say we're honored to have Mark
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Benny off here and uh truly who's a
00:01:37
Visionary in the world of software and I
00:01:40
would say you know there's probably a
00:01:43
lot of and I thank my mother for writing
00:01:44
that video by the way is well Mom thank
00:01:47
you for writing that for me great you
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know in the in the world of business
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offer in particular we don't have that
00:01:54
many people who you can describe as
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Visionaries but you consistently have
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been one you really it's true
00:02:01
you got the I think the whole we're
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sitting now on the edge of the couch
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okay here we go maybe we'll end up on
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the floor I don't know what's going to
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happen I'm trying to keep it engag
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around a lot oh okay all
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right is this how it's going to be the
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whole
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time way worse way worse okay all right
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let me finish the this little intro here
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um I forgot where I was so can I just
00:02:29
before we start you know
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listen so I want to just do something I
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would not normally do and this is like
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going to be a little bit of a thing but
00:02:37
I just have to do a little Riff on this
00:02:40
but we just heard some an extraordinary
00:02:42
presentation on an extraordinary man and
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there's somebody who's amazing that most
00:02:47
people don't get to hear of and we just
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heard his name quite a few times his
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name is shin yamanaka Yaman nakasan he
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is um based in Kyoto Japan but he works
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halime at UCSF
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and it's amazing what his vision for the
00:03:02
world is that he thinks basically that
00:03:05
we're salamanders and we're going to be
00:03:06
able to regenerate ourselves and that's
00:03:09
amazing and so I've been friends with
00:03:12
him maybe for a decade but I fund his
00:03:14
research and so a lot of these things to
00:03:17
watch him have these breakthroughs and
00:03:18
you heard about the yamanaka factors the
00:03:21
yamanaka factors which are basically
00:03:23
this idea that
00:03:24
yamanaka had this breakthrough in Kyoto
00:03:28
you know basically hanging out there in
00:03:30
his lab eating the sushi the whole thing
00:03:32
and
00:03:33
then boom and he goes if I take these
00:03:37
four things I can take an ordinary skin
00:03:40
cell just any little skin cell and turn
00:03:43
it into a stem cell which is like the
00:03:46
the heart of human existence and he did
00:03:49
it and he was able to repeat it and
00:03:50
repeat it and repeat it and he won the
00:03:53
Nobel Prize for it pretty cool and then
00:03:57
he and I'm going to get the
00:03:58
pronunciation of this wrong but but he
00:04:00
then was able to take that stem cell put
00:04:03
it into your eye if you have tacular
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generation and
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boom healed the eye because the eye
00:04:12
regenerated then he worked with a buddy
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of his in the lab next door and he took
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the same thing took the stem cells and
00:04:20
he turned it into on a cookie
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sheet and it looked like it was like a
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plastic thing on the cookie sheet it was
00:04:27
really cool and then he's like took out
00:04:30
somebody's cornea that was all screwed
00:04:32
up cut the material out of the cookie
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sheet popped it in the eye and the guy
00:04:38
could see it was like amazing then he's
00:04:41
like listen this is
00:04:44
amazing I bet I can grow a
00:04:46
brain so he took the step cells and he
00:04:50
started growing brains called
00:04:52
organoids and he's like got a cookie
00:04:54
sheet of brains and I'm like really he's
00:04:57
like this is amazing look at all the
00:04:59
brain brains and I's like and then I
00:05:02
went and saw him and had lunch with him
00:05:04
and like I'm like what's happening with
00:05:05
the brains he's like I stopped the
00:05:07
brains I'm like why did you stop the
00:05:09
brains I think they can feel the pain
00:05:12
I'm like oh
00:05:14
scary then he's like then I said to him
00:05:17
now what are you doing oh I'm growing
00:05:21
intestines I'm like whoa intestin is
00:05:24
that good he's like huge idea I can now
00:05:27
grow intestines on the cookie sheet and
00:05:30
taking the you know stem cells I've got
00:05:31
a whole intestine here and then like he
00:05:34
can do like turn it into a lab for all
00:05:36
the horrible things that people get in
00:05:38
their gut and all these diseases that
00:05:40
have never been cured but now you have a
00:05:42
real simulated environment this is an
00:05:44
incredible person anyway where do you
00:05:47
want to go with that I'm going I'm going
00:05:50
with this you got to stay with me trying
00:05:52
to help bring the energy up in here okay
00:05:54
listen follow just hold on hold on hold
00:05:57
on hold on hold wait wait wait this is
00:06:00
going to get good okay so then I'm like
00:06:02
you heard the story like at the end they
00:06:04
said listen how do I get these
00:06:07
regenerative factors going inside myself
00:06:09
so UCSF just published research based on
00:06:12
funding grant that I and others have
00:06:14
given them and they had a breakthrough
00:06:16
that the regenerative Factor inside your
00:06:18
own blood is called
00:06:20
pf4 and the way you get pf4 and I'm not
00:06:23
going to get this exactly right because
00:06:24
you know I'm in software I'm not a
00:06:26
doctor so just follow with me I thought
00:06:28
that's what we're going to talk about
00:06:29
today that I know but I got to tell you
00:06:31
this cuz I'm got so jacked watching that
00:06:33
one is it was either that or those crazy
00:06:36
shots you have backstage I don't know
00:06:39
okay number one is P4 you get more
00:06:43
regenerative factors in your body like
00:06:44
what you know calorie restriction and if
00:06:47
you know David and I that does not sound
00:06:50
very
00:06:51
good two working out with weights also
00:06:55
not exactly our top thing
00:07:01
parabiosis do you know what that is so
00:07:04
parabiosis kind of came out of research
00:07:06
published a decade ago in New York Times
00:07:07
and others which is came from salval
00:07:10
another person I work with at UCSF where
00:07:13
they took the blood of a young Mouse and
00:07:16
put it into an old mouse and then the
00:07:19
old mouse got young again and that was
00:07:22
moving the pf4 into that old mouse so
00:07:26
that's and the fourth thing is cloth
00:07:27
theapy which is a genetic therapy that I
00:07:30
don't really understand and these four
00:07:31
things can start to generate more of
00:07:33
these things inside your body so then
00:07:35
I'm like getting excited I'm like God I
00:07:37
have these problems maybe I can
00:07:38
regenerate different parts of myself
00:07:41
whatever and so I'm talking to my doctor
00:07:44
at UCSF because I'm going through my own
00:07:46
serious problem where I'm like my left
00:07:48
leg is like a half an inch shorter than
00:07:50
my right leg and I'm running on the
00:07:52
treadmill and I'm always ripping my
00:07:54
achilles ripping ripping and all of a
00:07:56
sudden my achilles looks like it has a
00:07:57
dut and in fact I went to UCSF and
00:08:00
there's like an MRI you know well how
00:08:03
many of you have had an MRI raise your
00:08:04
hand so you know what as horrible it is
00:08:06
anyway you get in this big machine
00:08:07
they're looking at my Killers they're
00:08:09
come out they're all like this oh sorry
00:08:12
about this really horrible and I'm like
00:08:15
so I kind of took this thought and I'm
00:08:17
like talking to my doctor I'm like why
00:08:19
can't we like do use some of this figure
00:08:21
out what we can do so he's like all
00:08:24
right I'm come back on Wednesday so I
00:08:27
come back on Wednesday at 5: CL you know
00:08:30
I'm in Mission Bay at UCSF and I'm like
00:08:34
hey Anthony where is everybody we're
00:08:37
going to talk about it come into my lab
00:08:39
so I come into the lab they've got like
00:08:41
a centrifuge there all this stuff going
00:08:44
on I'm like well this is interesting
00:08:46
it's like did you work out today yes I'm
00:08:48
work out do you're following the P4 I'm
00:08:50
doing it okay this is what we're going
00:08:53
to do it's going to be very
00:08:53
straightforward because we have two we
00:08:55
have two things we can do with you mark
00:08:57
number one we can just take your kill
00:08:59
and we bring you into surgery right now
00:09:01
we'll just shave off half your Achilles
00:09:03
and then put you in a boot and see where
00:09:04
you are in 6 months I go doesn't sound
00:09:07
great second idea what we're going to do
00:09:11
is we're going
00:09:13
to we're going to take a scalpel B right
00:09:17
here we're going to cut into your
00:09:18
Achilles like 20 times and into your
00:09:21
ankle I'm going to take your butt I'm
00:09:22
going to spin it I'm going to try to
00:09:24
find the pf4 in your plasma I'm going to
00:09:26
inject it into your Achilles and into
00:09:28
your plasma slice into it with my
00:09:31
scalpel I go sounds great goes one
00:09:34
problem I go with that we don't use
00:09:35
anesthesia to do that why because it
00:09:39
destabilizes the PRP and the plasma and
00:09:41
all the pf4 and all that I'm like let's
00:09:45
rock let's rock so he did the whole
00:09:49
thing and then boom like an I'm like a
00:09:52
salamander they grew me a new Achilles
00:09:54
right in place so that thing that you
00:09:56
just heard that is real
00:10:00
and you know it's pretty awesome what
00:10:03
can what and uh it's yeah I have a
00:10:06
question for you um so if he can sell
00:10:10
three billion into his startup I should
00:10:11
probably start I'm ready to go got the
00:10:13
pitch did do you ever consider that you
00:10:16
missed your calling as a scientific
00:10:18
researcher definitely not definitely not
00:10:21
you're happy with the choices you made
00:10:22
well no that's an incredible story so
00:10:23
you are one of the first to actually try
00:10:25
using the yamanaka factors on yourself I
00:10:29
wouldn't think I'm one of the first but
00:10:30
I think that it's very real and it's
00:10:32
going to going to have a huge impact on
00:10:34
our whole on our lives and I think that
00:10:36
we should be supporting these medical
00:10:38
researchers I think it's it's one of the
00:10:40
reasons that I've you know put almost a
00:10:42
billion dollars into UCSF of
00:10:43
philanthropy because I believe in these
00:10:45
people who have absolutely yeah they've
00:10:49
dedicated their lives you know to basic
00:10:53
science and doing and meeting them they
00:10:55
so inspiring to me and like I just had
00:10:58
lunch with yamanaka and salval and
00:11:01
Anthony Luke and another incredible
00:11:02
researcher Mark moiser at my house and
00:11:05
like we're talking about the
00:11:06
intersection between oncology and
00:11:08
regenerate medicine which is like two
00:11:10
completely different worlds that don't
00:11:11
talk to each other and it's what
00:11:13
inspires me that you know we can you
00:11:16
know work with others to kind of get
00:11:19
give them the entrepreneurial push to go
00:11:20
do something incredible and these people
00:11:22
are just awesome each one is amazing
00:11:24
that is that is incredible so let's
00:11:26
shift gears and talk about something
00:11:28
else nice coincidence with the yeah no
00:11:29
it's incredible it's a great story I
00:11:31
know you you're very philanthropic and
00:11:33
do a lot with UCSF so uh kudos to you
00:11:36
for encouraging that type of research uh
00:11:38
let's shift to to another thing that's
00:11:39
having a huge impact in our lives which
00:11:41
is the cloud and software where you were
00:11:43
a Pioneer you started Salesforce back in
00:11:46
1999 25 years ago 25 years ago and how
00:11:50
long have you been a public company for
00:11:51
at this point
00:11:54
24 to 20 years 20 years and one of the
00:11:58
things I noticed count 80 earnings calls
00:12:01
yeah well actually speaking of earnings
00:12:03
let's here let's see if we have this
00:12:04
slide do we have earnings well first oh
00:12:07
yeah oh boy what's what slide is that
00:12:10
this is your stock chart over 25 I think
00:12:13
25 years 20 years yeah you're almostly
00:12:15
your all I guess there's no linear
00:12:17
success exactly right yeah really good
00:12:19
point yeah we had a keep basically had a
00:12:21
bubble we had a bubble inate 21 we had a
00:12:24
huge correction in 22 there was I need
00:12:25
to make a note of that we should talk
00:12:27
about that but you're your basic back to
00:12:29
where you were this is one of your
00:12:30
tweets actually this is one of the
00:12:32
things I appreciate about the way you do
00:12:34
earnings calls is you just put out this
00:12:36
really simple tweet and it just and it
00:12:38
shows a
00:12:39
progression and if you know if you like
00:12:42
looking at numbers the way I do and
00:12:43
seeing patterns in them one of the
00:12:45
things I noticed a while ago was that if
00:12:48
you start at the bottom and work your
00:12:49
way to the top that Salesforce is
00:12:51
growing by about 20% a year and if you
00:12:56
look at it over 3 years that's roughly a
00:12:58
dou
00:12:59
so every 3 years Salesforce was doubling
00:13:02
and that means that over a decade it's
00:13:04
growing 10x and so every decade is
00:13:07
basically an exponential if you can
00:13:09
stick with it long enough that was one
00:13:11
of the patterns I noticed with sales
00:13:13
look I I think that you know that the
00:13:15
growth obviously is incredible to 38
00:13:17
billion and obviously the cash flow is
00:13:20
incredible you know it's more than C
00:13:22
Coca-Cola did I think last quarter and
00:13:24
the margin is incredible but let me just
00:13:26
say probably the best decision we made
00:13:28
in not on the slide which is the day we
00:13:31
started the
00:13:32
company um we put 1% of our Equity 1% of
00:13:37
our profit 1% of our product 1% of all
00:13:40
of our employees time into a 50613
00:13:44
foundation now at the time it was very
00:13:46
easy because we had no employees we had
00:13:48
no equity we had no profit we had no so
00:13:51
wasn't very complicated but that idea
00:13:55
though really kind of created the
00:13:57
foundation of the company because we're
00:13:59
able to do now and I think you know the
00:14:01
numbers right where you know almost 10
00:14:03
million hours of volunteerism we've been
00:14:05
able to give away almost a billion in
00:14:07
Grants we run almost 100,000 nonprofits
00:14:09
and NOS for free on our service and I
00:14:12
think it really set the stage that
00:14:14
business could be the greatest platform
00:14:15
for change when it came for Salesforce
00:14:17
it un it gave it that philanthropic
00:14:19
platform so is there two billion in
00:14:22
equity sitting in that 501c3 at this
00:14:24
point a lot well there's more I think
00:14:27
there's about a half a billion in the
00:14:28
foundation and a lot of has been already
00:14:30
given out and then we give out more
00:14:32
every year and every month every day
00:14:35
whatever but like on Monday we'll give
00:14:36
another $25 million approximately to the
00:14:40
San Francisco and Oakland Public Schools
00:14:42
and that is you know we've given them
00:14:44
about $150 million I mean it's it's
00:14:48
obviously I went to Public Schools it
00:14:50
was very important to me but all my
00:14:52
mother was a teacher in the San
00:14:54
Francisco Public Schools but also our
00:14:58
employees you know have 75,000 employees
00:15:00
their kids are in the public schools and
00:15:03
so it's a key part of our Mantra and our
00:15:06
culture that we're trying to support
00:15:09
public education I adopt a public school
00:15:12
I really think that each one of us can
00:15:14
needs to focus more on the public educ
00:15:16
education system in the United States
00:15:18
it's something I encourage in not all my
00:15:21
employees but whenever I do a
00:15:22
presentation I'm like you know my public
00:15:25
school is like a block for my house
00:15:27
procedo middle school and I just went
00:15:28
down there and knocked on the door and
00:15:32
they're like who are you and I'm
00:15:34
like what do you how can I help you and
00:15:37
what can I do to support you they need a
00:15:39
new playground they need this they need
00:15:41
that and maybe they just need some me
00:15:44
some support moral support um but uh
00:15:47
it's been a great thing to really anchor
00:15:50
the company in those values and I think
00:15:52
it's an important thing uh for every
00:15:54
company so what did you think when you
00:15:56
saw that open AI started with a non
00:15:59
profit not as 1% but as 100% but then it
00:16:01
became a for-profit what did you think
00:16:03
of that Innovation confusing I you know
00:16:08
I mean 18,000 companies have now
00:16:10
followed our 111 model you can find out
00:16:12
about it at pledge
00:16:14
1.org that other model I don't really
00:16:17
understand I think we've proven our
00:16:18
model this is important you know we came
00:16:20
out with three models the cloud model
00:16:22
which you also have been part of that
00:16:25
the subscription model you've also been
00:16:27
part of that and the philanthropic model
00:16:29
and you've been part of that and those
00:16:31
ideas that we're doing three models
00:16:33
that's continues to be the fuel for the
00:16:36
company and extremely important and I
00:16:38
think that for a lot of these companies
00:16:40
that have followed us that have gone
00:16:41
onto scale and have had huge IPOs and
00:16:44
whether it was slack or whether it was
00:16:46
at lasan or whether it was eilo or
00:16:49
whatever they have these huge
00:16:51
foundations and have had huge impact and
00:16:54
business can be the greatest platform
00:16:56
for change and you can do a lot with
00:16:57
your business and you you know we are
00:16:59
all building great products okay that's
00:17:02
great and we're selling them that's
00:17:05
great too but we can also do a little
00:17:07
more with our business and we can use it
00:17:09
in a positive way and try to move the
00:17:12
world maybe a little bit more in the
00:17:14
right direction okay so let's talk about
00:17:16
the cloud part of that Innovation where
00:17:19
do you think we're at right now I mean
00:17:20
is it it's is it all AI all the time how
00:17:24
how are you thinking about it we're at
00:17:26
the precipice of the greatest moment in
00:17:29
the history of enterprise software and
00:17:31
of cloud computing there there's no
00:17:34
question we you know I had a moment I
00:17:37
would say more than a decade ago which I
00:17:39
call my kind of AI freakout moment where
00:17:41
I really felt I mean maybe it's you know
00:17:44
obviously we've all spent how many of
00:17:45
you watched Minority Report all right we
00:17:49
saw that movie and what about war games
00:17:51
War Games anybody remember that from
00:17:53
okay uh
00:17:54
her um yeah we all saw these movies
00:17:57
Terminator Okay that one's a little
00:18:00
scary but we all seen the movies and you
00:18:03
know like Peter Schwarz who wrote or was
00:18:05
a key part of writing Minority Report
00:18:07
and um also war games uh you know as our
00:18:11
chief futurist at Salesforce and a
00:18:13
decade more than a decade ago I had this
00:18:15
moment where I was like okay this is
00:18:17
really happening here we go and bought a
00:18:19
bunch of companies and put together
00:18:21
Einstein and Einstein has done amazing
00:18:23
you know it's doing trillion
00:18:25
transactions trillion and a half
00:18:26
transactions a week predictive
00:18:28
generative I really thought okay this is
00:18:30
was going to be the moment but now I'm
00:18:33
really convinced that we are now really
00:18:36
at the moment right now where enterprise
00:18:40
software is going to be completely
00:18:42
transformed with artificial intelligence
00:18:44
and we're going to see it and obviously
00:18:46
I'm getting tuned up for dreamforce
00:18:49
which is going to be Tuesday of next
00:18:50
week how many of you are coming to
00:18:52
dreamforce not enough
00:18:55
anyway sad these aren't my people I'm
00:18:58
leaving now
00:18:59
well it's good you well they look but no
00:19:01
let me just tell like since you're not
00:19:03
going to be there let me tell you what's
00:19:04
going to
00:19:06
happen thanks for being part of my team
00:19:09
anyway number one
00:19:11
is you know we're going to you know we
00:19:14
really see a moment right now where we
00:19:17
are 100% focused on one thing and one
00:19:20
idea and I can tell you why that is if
00:19:22
you're interested but it's agent force
00:19:24
and agent force is the most exciting
00:19:27
thing I have ever worked on in my
00:19:30
career um it's the culmination really of
00:19:32
everything that we've done at Salesforce
00:19:34
because to make agent force really
00:19:36
deliver we had to have all of our
00:19:38
customer touch points wired up which we
00:19:40
do we have to have an Amalgamated data
00:19:43
Cloud because we need the data
00:19:44
especially to achieve the AI accuracy
00:19:47
and the metadata as well and we have to
00:19:50
have the agents it's these three layers
00:19:53
that are really going to deliver this
00:19:55
next generation of capability and I was
00:19:56
just with Disney last night and Disney
00:19:59
has agent force they have the newest
00:20:01
version which we call Atlas which is our
00:20:03
most accurate not just model but we have
00:20:05
an extremely unusual technique that
00:20:07
we'll talk about and Atlas delivers for
00:20:10
for Disney for their cast members which
00:20:12
are their employees through extremely
00:20:16
complex uh problems that it's solving
00:20:18
for them more than 90% accuracy and
00:20:21
almost no hallucinations and in some
00:20:23
cases 95% accuracy and almost no
00:20:26
hallucinations and that idea that we can
00:20:29
kind of come into a very difficult and
00:20:32
complex and sophisticated data set now
00:20:34
with now with Disney if you go to
00:20:37
disneystore.com that's Salesforce if you
00:20:39
go to the Disney parks do you still go
00:20:41
to Disneyland sometimes yeah okay you
00:20:42
ever get a Disney guide sometimes yeah
00:20:45
it's great because you get to cut around
00:20:46
the lines and all that how many of you
00:20:48
have done the Disney guides thing we got
00:20:50
like a lot of poor people here
00:20:54
actually sad anyway she get these Disney
00:20:57
guides cuz they're like get you around
00:20:59
the lines you got do 30 rides a day and
00:21:02
it's much better than having to wait
00:21:04
okay but
00:21:06
anyway Disney guides run on sales force
00:21:09
they just SL they have slack too they've
00:21:10
got we do disneystore.com we have Disney
00:21:13
plus because you know the service now
00:21:16
like fell over and we had to like
00:21:18
replace that inside the Disney plus call
00:21:20
center we have we're do the Disney
00:21:23
Cruises and the Disney real estate and
00:21:25
we have every Disney customer test Point
00:21:27
all wired up so The Amalgamated data set
00:21:30
that we have around Disney is awesome so
00:21:32
when we can take that Disney data set
00:21:34
and then we apply Atlas and agent force
00:21:37
okay so how do you define we are able to
00:21:38
deliver a level of accuracy that has
00:21:41
been incredible and I've got a couple
00:21:43
more examples I can tell you that are
00:21:44
just blowing my mind and I never thought
00:21:46
it was really possible but now it really
00:21:49
is go ahead yes well I just wanted to
00:21:52
you want me to ask you a question
00:21:54
also no no no um what do you mean by
00:21:59
agent because we're starting to hear
00:22:00
this term a lot but I think a lot of
00:22:01
people here may not know what that means
00:22:03
in the context of AI did you see the
00:22:05
movie The Matrix yes I did so are we
00:22:07
talking about agent Smith or what are we
00:22:08
talking about well we're at some level I
00:22:10
mean I think like I'll give you an
00:22:12
example that you know um we're working
00:22:14
with a large medical company not so far
00:22:17
away from her Kaiser they've got 20
00:22:19
million patients they have a super
00:22:21
complex data set they have all of the
00:22:23
data from epic they are the largest epic
00:22:25
customer in the world and more than 90%
00:22:30
of all patient inquiries and scheduling
00:22:32
requests and schedule my doctor schedule
00:22:35
my CT scan my MRI my this my that are
00:22:38
being resolved by agent force and Atlas
00:22:41
that idea that we can resolve through a
00:22:44
autonomous agent a deep and complex
00:22:48
customer interaction is a breakthrough
00:22:50
thought obviously we have to do a few
00:22:52
things to make it really work for our
00:22:53
customers number one is it's got to be
00:22:55
trusted because our customers Trust
00:22:58
we're running the largest banks
00:23:00
insurance companies media companies cpg
00:23:02
companies blah blah blah blah blah in
00:23:04
the world number two is it's got to be
00:23:06
easy for them it can't be some separate
00:23:08
team that they're going to spin up it's
00:23:10
their existing Salesforce team it's
00:23:12
happening within the Salesforce platform
00:23:14
it's got to be open it has to have be
00:23:17
able to work with and interoperate with
00:23:18
other systems it's going to have to be
00:23:21
multimodal so it's going to have to
00:23:22
speak to them and have voice and video
00:23:25
and do all of those kind of incredible
00:23:27
capabilities and one other key thing
00:23:29
because evidently the humans have not
00:23:32
gone away the doctors have not gone away
00:23:35
from Kaiser and the cast members have
00:23:37
not gone away from Disney and on and on
00:23:40
so we're going to have to handshake
00:23:42
seamlessly with our apps so even though
00:23:44
we have all these apps and we've wired
00:23:46
up all these customer touch points the
00:23:48
agents are autonomously interacting with
00:23:51
and building the data and metadata and
00:23:53
extending it and by the end of this
00:23:56
month we'll have more than a thousand
00:23:57
customers on our agent force platform
00:24:00
the efficiency and productivity that
00:24:03
we've been had with agent force is like
00:24:05
nothing I have ever seen with any of our
00:24:07
customers or technology in the history
00:24:09
of software but there's a second point
00:24:12
it isn't just about this kind of ease of
00:24:14
use it's that that they have the ability
00:24:16
to do things that are truly astonishing
00:24:21
and that is also generate Revenue so
00:24:23
they can go out and like on a day like
00:24:25
today like it's 10 something degrees
00:24:27
outside or if you been out there it's
00:24:28
pretty
00:24:29
hot and Disneyland may not be as full
00:24:33
today as it's going to be and they knew
00:24:34
that was going to be true two days ago
00:24:36
that a heat wave was coming Disney can
00:24:38
proactively go out to their consumers
00:24:41
and their customers and say hey come
00:24:43
enjoy the heat with us all you know
00:24:45
Disneyland and we're going to give you a
00:24:47
special promotion or Price or contest or
00:24:49
whatever it is to come to Disneyland so
00:24:52
we want to be able to proactively go out
00:24:53
and generate revenue and we also want to
00:24:56
be able to kind of bring that customer
00:24:58
service in I think last night I had
00:25:00
dinner at Beverly Hills at the grill
00:25:02
have you been there great right cream
00:25:04
spinach well I did something different B
00:25:06
what do you want what do you prefer um
00:25:09
well I like like potatoes you know
00:25:11
potatoes okay po you know any kind of
00:25:13
potato you like any kind of potato baked
00:25:15
potato steak fries all so I'm on Open
00:25:17
Table Right anybody here use Open Table
00:25:21
not it's very weird group
00:25:24
anyway
00:25:26
so oh I'm using anyway you can use Open
00:25:28
Table to make restaurant
00:25:31
reservations and there's 160 million
00:25:34
consumers on Open Table they're not in
00:25:36
this room but they're somewhere and
00:25:39
they've got also 60,000 restaurants and
00:25:42
they've got a lot of complex issues you
00:25:45
know in regard you know I didn't get my
00:25:46
table or my food wasn't right my potato
00:25:48
didn't get cooked whatever it is these
00:25:51
things are going to get worked out but
00:25:52
also all of a sudden the restaurant's
00:25:54
like oh look we're not as full tonight
00:25:55
as we want to be and we're willing to do
00:25:57
let's go out to our customer base and
00:25:59
bring them in but let's do it through a
00:26:01
complex conversation you know an
00:26:04
empathic conversation as an agent with
00:26:06
our customers I think it's going to be a
00:26:08
rocket ship okay so so how long will it
00:26:12
be until when you call a customer
00:26:14
support center you're talking to an AI
00:26:18
that sounds like a human and you can't
00:26:19
tell the difference are we there yet or
00:26:22
we're there yet we are already at that
00:26:23
point we already have that live and we
00:26:27
will have that scaled for thousands of
00:26:30
customers before the end of um live for
00:26:34
with thousands of customers live before
00:26:36
the end of this year and we just I just
00:26:39
demoed it I was just just at a
00:26:40
conference and spoke uh mile couple
00:26:42
miles away from here at KPMG and we
00:26:44
showed them that exact situation where
00:26:47
you know through you know we used to
00:26:49
call you know this kind of voice
00:26:51
response system whatever but you would
00:26:54
kind of hit a wall pretty quickly with
00:26:56
your Bot you know but these aren't Bots
00:26:59
these are not the Bots you're looking
00:27:01
for these are like we're really getting
00:27:04
to like another level capability and I
00:27:07
think that it's pretty impressive and I
00:27:09
think in the example of Disney you know
00:27:10
Google has some great products I know
00:27:11
Serj was here yesterday and they've done
00:27:13
a great job with AI as you know but in a
00:27:16
head-to-head Benchmark of sales forces
00:27:18
agent force against Google's AI uh we
00:27:22
twox them on accuracy and the reason why
00:27:25
is we'll explain it next week um you
00:27:28
know it's a couple of things not only is
00:27:30
there our NextGen models but it's also
00:27:32
new techniques involving Next Generation
00:27:35
retrieval augmented generation rag
00:27:37
techniques that no one has seen before
00:27:39
and it's really incredible what's
00:27:40
possible so you're kicking Google's ass
00:27:43
I'm cool with that well they're good
00:27:45
partner also customer and I love them
00:27:47
but yeah it's it's competitive just yeah
00:27:49
let me keep let me keep holding on this
00:27:51
we're trying to all make AI a little
00:27:52
more accurate and a lot of less a little
00:27:54
few less hallucinations along the way
00:27:56
let me give the audience a little update
00:27:58
about something we just heard at open AI
00:28:00
they just did a a a day where they
00:28:03
brought in relatively small number of
00:28:06
investors and kind of give gave us all a
00:28:07
update on their product road map and it
00:28:09
sounds kind of similar because
00:28:10
everyone's moving in the same direction
00:28:12
so there are three big takeaways number
00:28:14
one was that they said that llms would
00:28:17
soon be at PhD level reasoning right now
00:28:20
it's more like a smart high school or
00:28:23
college student in terms of the answers
00:28:24
we're going to be at the next level
00:28:26
shortly behind that is agents like
00:28:29
you're talking about and then third and
00:28:31
closely related is that agents will have
00:28:33
the ability to use tools and a tool can
00:28:36
be a website so if you think about it
00:28:39
now you've got this llm it's really
00:28:41
smart it's got you know it's like a
00:28:43
PhD it you can give it an objective it
00:28:46
will break that objective into a list of
00:28:48
tasks and those tasks can include using
00:28:52
other pieces of software and thanks to
00:28:55
things like open AI just launched the
00:28:58
audio API which developers can use it's
00:29:01
in private beta we have some companies
00:29:03
using it the llm can now basically
00:29:06
pretend to be a human and you know
00:29:08
there's it won't be hard to find a piece
00:29:10
of software to enable a phone call so
00:29:12
you can imagine telling a a personal
00:29:15
assistant agent that and it could be you
00:29:18
know it could be open table that hey
00:29:21
book me book me a a dinner reservation
00:29:23
at the grill and it could place a phone
00:29:25
call on your behalf and actually talk to
00:29:27
the grill it could also go on open table
00:29:29
and just use open table and book it but
00:29:31
if for some reason that didn't work it
00:29:33
could literally place a phone call on
00:29:34
your behalf and the person picking up at
00:29:37
Open Table wouldn't even know that your
00:29:39
agent actually isn't a human it's an AI
00:29:42
but here's where I think it gets really
00:29:44
crazy is when the phone gets picked up
00:29:47
on the other end that could be an AI too
00:29:49
pretending to be a human so you could
00:29:51
have two AIS pretend to be humans
00:29:53
talking to each other and resolving
00:29:55
tasks on your behalf and I I literally I
00:29:57
think that's where it's at it we're
00:29:59
definitely moving in this direction but
00:30:01
there's a cautionary tale here and I
00:30:03
think that I'll just tell you the real
00:30:05
world experience with my customers and
00:30:07
what I'm the problems that I'm trying to
00:30:08
solve for them I I think in the last few
00:30:11
years we've kind of heard and you know
00:30:13
some of it has come from open AI but
00:30:15
especially from Microsoft that we're in
00:30:17
this co-pilot world and these co-pilots
00:30:19
have universally failed the level of
00:30:22
accuracy the spillage of information the
00:30:24
lack of trusted environment co-pilot has
00:30:26
been a complete disaster
00:30:28
and that idea that this kind of amount
00:30:31
of Technology got you know released and
00:30:34
sold into these very large customers
00:30:36
telling them that the all promise of AI
00:30:38
is here but didn't do it in a trusted
00:30:41
way didn't do it with the level of
00:30:42
accuracy didn't do it with the level of
00:30:44
security needed and one of the things
00:30:46
that was interesting because I was with
00:30:47
one of the customers would trying to do
00:30:49
this exact technique that you're talking
00:30:51
about which is a large
00:30:52
telecommunications company in
00:30:54
Seattle and what this company did is
00:30:57
take model of nope going to just tell
00:31:01
you training a model retraining a model
00:31:04
building their own model Mark we have to
00:31:06
have our own models we're going to DIY
00:31:08
it we're going to DIY our Ai and it's
00:31:11
going to be awesome then we're going to
00:31:13
write our own agents and we're going to
00:31:14
do this we're going to do that the other
00:31:15
thing and I'm sitting there and I'm
00:31:17
going through it and whatever and I'm
00:31:18
then I finally I'm like now show me your
00:31:19
benchmarks and show me all these
00:31:21
different pieces and and you know for
00:31:23
them it's a bit of a science project and
00:31:24
I've seen this now with a number of our
00:31:26
customers that they're kind of DIY and
00:31:28
their Ai and you know DIY I think it's
00:31:32
fine if you're like Neil Young and it's
00:31:34
homegrown and it's Canada and it's you
00:31:36
know Ontario but this is not what you
00:31:39
should be doing with your artificial
00:31:40
intelligence but what are you guys using
00:31:43
as your foundation model is it llama 2
00:31:45
like what do you guys use we have a lot
00:31:46
of our own models our own techniques our
00:31:49
own and then we let you bring in the
00:31:51
model that you want but we are all about
00:31:53
achieving your accuracy because what
00:31:55
I've seen with these kind of approaches
00:31:57
especially the one that you just
00:31:58
outlined is that yeah you can get maybe
00:32:01
30 or 40% accuracy you know in this case
00:32:04
this customer is 25% you had somebody on
00:32:07
the stage yesterday I won't tell it is
00:32:09
who's a common friend of both of ours
00:32:11
who tried to take this approach for a
00:32:13
large telecommunications company that he
00:32:15
owns and he said he was getting about a
00:32:16
25% accuracy with this homegrown model
00:32:19
and I'm like why are you doing that
00:32:21
instead in our platform the platform is
00:32:23
building the model for you you're not
00:32:25
having to train and retrain your own
00:32:27
models you're building your own models
00:32:29
in our platform and we're going to
00:32:31
deliver much higher levels of accuracy
00:32:33
for you and we're going to deliver AI
00:32:36
this is the AI that you want this is
00:32:39
this next generation of AI and I think
00:32:42
that we'll have to prove that with
00:32:43
benchmarks and with bake offs and to
00:32:45
show customers because the promise is
00:32:48
amazing but at a very deep level
00:32:50
customers are going to need you know
00:32:52
what you and I have done for the last
00:32:54
you know 20 years of our life which is
00:32:55
build professional Enterprise software
00:32:57
and delivered to them and a capability
00:32:59
And in regards to an agent running
00:33:01
enterprise software I mean you just saw
00:33:03
like that was the
00:33:04
fundamental business model of adept
00:33:06
which was David Lewan's company you know
00:33:09
and that's he built gpt3 then he left
00:33:11
open AI to start Adept and this idea to
00:33:13
build agents that are going to drive
00:33:15
apps I'm sure that all of those things
00:33:17
are going to happen but again you have
00:33:20
to get to a level of accuracy because
00:33:22
everyone in this room and you and I
00:33:24
we've all had this experience where on
00:33:26
these models and it's like this is not
00:33:29
really more than hallucinations and
00:33:32
that's no good or as we say here in Los
00:33:34
Angeles no es bueno when it comes to
00:33:38
okay Kaiser and you're dealing with
00:33:40
health care you know when you're dealing
00:33:42
with health care and you've got a
00:33:43
patient and you're reading their medical
00:33:45
records you better be delivering more
00:33:47
than 90 or 95% accuracy because the 50%
00:33:50
accuracy thing is no good well I can see
00:33:54
you're ready for dream Force I'm trying
00:33:55
to go find it I'm testing mat out here a
00:33:58
little bit what do you guys think I'm
00:34:04
like are you are you guys excited for
00:34:06
the rise of Agents yeah it's going to be
00:34:10
a really big deal I think that
00:34:12
everything we've seen so far with llms
00:34:14
has been again about reasoning and and
00:34:17
generating but with agents the AI is
00:34:20
going to be able to take actions and and
00:34:22
they're going to know how to use tools
00:34:24
which until now it's been some the only
00:34:25
human I got to tell you a really good
00:34:26
story because you're like inspiring me
00:34:28
around uh you know Steve Jobs had a huge
00:34:32
impact on my life and at I worked at
00:34:34
Apple in 1984 when I was a I was uh in
00:34:37
high school and coming into college and
00:34:40
I was an assembly language program I
00:34:42
wrote the first Native Assembly Language
00:34:44
um on this Macintosh know the 68,000
00:34:48
assembler and sitting there in the cubes
00:34:50
and Steve is running whatever it is and
00:34:54
thank God you know I have this
00:34:55
relationship and influenced me so much
00:34:57
in my life and then called me on a
00:34:59
series of times and after I started
00:35:01
Salesforce gave me really key advice
00:35:03
anyway it was 2010 and he calls me come
00:35:07
down here I need to talk to you I'm like
00:35:09
what the hell what did I do this
00:35:11
time so I go down there to his office
00:35:13
and I always bring a few Salesforce
00:35:15
employees with me and I've got some
00:35:16
great folks with me and we're sitting
00:35:19
there and he's like I'm going to show
00:35:20
you this and I'm like all right let's go
00:35:23
and he brings out the iPad and he's got
00:35:25
two of them he's got the big one and the
00:35:27
small one
00:35:28
and he's like yeah Mark here it is you
00:35:30
know but I don't like the small one I'm
00:35:32
only going to have one size you know
00:35:34
that I'm like yes sir and he's like uh
00:35:37
listen you know I've been working on
00:35:39
this concept for a long time and you
00:35:40
know in
00:35:42
2007 um I introduced a iPhone and you
00:35:45
know I said thank you for sending me one
00:35:47
I love it it's great like but do you
00:35:49
know why now we're doing the iPad I'm
00:35:51
like no because I know you had that too
00:35:54
in 2007 oh yeah but you know what the
00:35:56
real situation here is that couple I'm
00:35:58
like what is it Steve he's like we only
00:36:00
have one a team here one a team so we're
00:36:03
only focused on one thing at a time and
00:36:05
then he lays out like five or six
00:36:08
products on his coffee table and he goes
00:36:10
and we will never have more products
00:36:11
than can fit on my coffee table and I'm
00:36:14
like well that's really awesome and he's
00:36:16
like I've been focused on 2007 on the
00:36:18
iPhone and now I'm gonna zero in and I'm
00:36:20
only going to do iPad one focus at a
00:36:24
time remember that Mark that's the way
00:36:26
you need to rent
00:36:28
Salesforce and I'm like okay is that why
00:36:31
you brought me down here yes you may
00:36:34
go and and that's how I feel right now
00:36:38
about agent force this is all I am doing
00:36:40
just try to take our company you know we
00:36:42
have a great company 38 billion Revenue
00:36:46
75,000 employees hundreds of thousands
00:36:48
of customers and one Focus agent force
00:36:51
this is the because of what you're
00:36:53
saying this is the moment this is the
00:36:56
greatest opport opportunity in the
00:36:58
history of enterprise software and it
00:37:00
must be executed with absolute Acuity
00:37:02
and excellence and that is what I think
00:37:05
we all need to
00:37:08
do you know so so I agree with you I
00:37:12
mean I think the agents are going to be
00:37:14
huge and Elon say something kind of
00:37:16
similar to the other day um he said we
00:37:18
was we got him talking about Optimus you
00:37:20
know his his robot heard about the farm
00:37:22
animals I didn't know about the what was
00:37:24
was there another part of the
00:37:25
presentation he said well he was talking
00:37:26
about he's talking about Optimist and um
00:37:30
oh you the the thing thing about these
00:37:32
jokes are all each one is kind of dying
00:37:34
very fast it's sad took me a second to
00:37:36
to realize that you were talking about
00:37:38
his
00:37:40
um but now I got it okay um no he was
00:37:44
referring to um it's great how you bring
00:37:46
this humor into uh the Allin yes it's
00:37:49
very subtle I understand
00:37:52
um so what Elon mentioned that really
00:37:55
stuck with me is he said that humanoid
00:37:58
robots the creation of these humanoid
00:37:59
robots are the biggest Economic
00:38:01
Opportunity in the history of the world
00:38:05
the average person is he making some of
00:38:06
them by any chance he is but well it's
00:38:09
kind of like you saying that uh agents
00:38:11
are the biggest opportunity in the
00:38:12
history of Enterprise sofware let me
00:38:14
write that down thank you for letting me
00:38:16
know that it's it strikes me that
00:38:18
there's something similar here which
00:38:19
isan is a good salesman is that your
00:38:20
point well I'm I'm saying there's an
00:38:22
analogy here between he didn't give you
00:38:25
the regenerative pitch is that my
00:38:28
well no what here me the point is this
00:38:30
is that is that where we're going with
00:38:33
AI is it's going to be able to take real
00:38:35
actions and in the case of Optimus is in
00:38:37
the physical world and it's going to be
00:38:38
the brain for these humanoid robots in
00:38:41
the Enterprise it's basically the brain
00:38:43
for these agents I think these things
00:38:45
are actually pretty they're on Parallel
00:38:49
tracks I wouldn't say they're competing
00:38:51
and these are the droids you're looking
00:38:53
for so I think anyway I think that uh I
00:38:56
I think you're right about this
00:38:57
opportunity and what I'm saying is I
00:38:59
think it's analogous to what Elon is
00:39:00
seeing with robotics I think there's no
00:39:03
question and I think that for our
00:39:05
customers they're going to augment their
00:39:07
employees they're going to make things
00:39:08
lower cost they're going to increase
00:39:09
their revenues they're going to increase
00:39:11
their margins we're going to take some
00:39:12
customers and just turn them into margin
00:39:14
machines and I think that the
00:39:17
opportunity in the Enterprise is
00:39:18
unbelievable he's also directly
00:39:20
addressing the consumer Market which I
00:39:22
think is very exciting obviously he's an
00:39:24
expert in that area and yeah we're about
00:39:27
to move into this new world of AI of
00:39:29
droids of all these things and you know
00:39:32
it's a bunch of waves of you know where
00:39:34
you know look technology is getting
00:39:36
lower cost and easier to use it's a
00:39:39
Continuum and we're all rioting that
00:39:41
Continuum this is extremely important
00:39:43
but also what's very important is
00:39:45
especially as we move into this we all
00:39:48
have to think about what are the values
00:39:50
that are going to guide this technology
00:39:52
because each of us have seen the movies
00:39:54
we all watched the movies that was the
00:39:56
one place where I got the hands to go up
00:39:58
right so we know how it can go really
00:40:00
wrong right everybody saw that part of
00:40:02
the movie so what are the values what's
00:40:06
going to be really important to us will
00:40:07
it be trust is it customer success is it
00:40:09
Innovation is it equality is it
00:40:12
sustainability is what are the values as
00:40:14
we kind of guide into the next level of
00:40:16
the future because those core values
00:40:18
that we need to manifest and really
00:40:20
focus on that is I think still out there
00:40:23
as a major discussion item it's got to
00:40:25
be figured out and that is why we're
00:40:27
very lucky that you are one of the great
00:40:29
Visionaries of our industry because
00:40:31
you're not just a great entrepreneur and
00:40:33
CEO but you're a great human being so
00:40:35
thank you
00:40:37
Mark thank you
