A hearty good morning afternoon evening as the case may be to you
and Welcome to our chat GPT special event. It's a real
pleasure to be here and it's an honor to share the stage with Tim and I am
just super excited to hear what our experts and our practitioners have to
say today just to set the stage a little bit for this event.
We've tried to put together today's program in a way that doesn't
just stand back and admire the gleam and the shine of this shiny new
object that we all
have and chat GPT and generative AI. We obviously think it's
super interesting. Of course and every day it seems like we're marking
about the pace of development accelerating here. But we also think
that just holding this celebratory surface level type of event would be doing
you, our customers disservice. This is a
complicated technology and it has implications fundamental
and profound a lot of things might change and they might
change in ways that
We just don't anticipate. Now, that's of course, always been true of
technology and part of O'Reilly's Mission over the past. Few decades, has been
to figure out where the current is flowing and where the innovators are
leading us and then to amplify their signals out to the rest of the world.
So, this event is part of that Journey for us. We need to think,
overall, not just about the possibilities and the promise of chat GPT
and generative Ai, and the outcomes, and the results that there,
Continued progress will bring, but we also need to be thinking about some of the
pitfalls. What do you need to be careful of if you're on the Leading Edge
right now. But especially as you get deeper into production, with this
technology, what are some of the things that you will need to watch for
in search of those answers? Today, we'll hear from one of the folks leading the
charge for generative AI at one of the world's leading cloud and productivity software
companies will hear from the CEO of the company behind one of the most
popular software development Tools in it.
Assistance on how chat GPT and its future. Iterations will change software
development will hear from a partner of ours, on actually using chat
GPT and production and circumventing. Some of its challenges will learn
from one of our steam trainers about building apps. Using chat GPT
will also hear from a research vice president at a global search giant about how they're thinking
about intelligence and artificial general intelligence or AGI.
We'll learn about a large Financial advisory company and their efforts and using chat
GPT to enhance the advisory Services, they provide to their
customers. And then we'll wrap up today with the look inside O'Reilly
about how we're using large language models to enhance. Personalized
learning.
So, whether you are a champion of generative Ai and you're
eager to use chat GPT and its ilk. And every task that every
tool and every project that you have or if you're a generative AI
skeptic and you think a lot of the Pomp and the circumstance around chat
GPT is smoke but no fire then I hope you'll
find content. And points of view today that will expand your view make
you think and maybe even rethink your position and hopefully feel a little bit
better prepared for
or whatever the future might hold. So, let me take one moment here to direct you to a
couple of resources. Our team has put together for you on the landing page for the
event. There's some recommended reading that's highlighting some of the base content
on the O'Reilly platform that we've pulled together to help set the stage for today's event and
also to whet your appetite. There's also a chat GPT expert
playlist. That's going to grab smaller chunks of content from across all of our relevant
Library. Will break that out in the fundamentals. First steps. And next
steps and
We keep your eyes peeled because we have a rich pipeline of books, live events on
demand courses, live courses, all around generative AI that are
coming in the months ahead and we're super excited to roll those out. So
that's enough for me, let's go into the first session here on reshaping search
with Bing. This is with Jordi Rivas and Tim O'Reilly, Tim
obviously is our fearless leader founder CEO. Chairman of
O'Reilly media company that has been providing the picks and shovels of
Learning to the Silicon Valley Gold Rush for the past 35 years.
The company has a history of convening conversations that reshape the computer industry.
If you've heard the term open source, software Web 2.0, the maker
movement government, as a platform or the WTF economy, he's had a
hand in framing. Each of those big Ideas. We also have Jordi
Rebus of corporate vice president of search and AI at Microsoft,
leading, the product and Engineering teams responsible for being searched world.
Glide, as well as Microsoft search and being in for Enterprise.
Since 2008, Jordi has led multiple product and Engineering teams focused
on AI products, and services, such as search speech vision,
and digital assistants.
He was on point for being product and growth in 2014 and took on all of being in
2020 and in February of 2023, he and team released the
new Bing, which was the first large-scale search engine with search
grounded GPT answers. And multi-turn chat based search launching a new
era of a I powered search. So, without further Ado,
let's let's hear from Jordi and Tim
Good morning. I'm so glad to be here with Jordi Reeboks
who's the corporate VP for search and AI at
Microsoft. Welcome, Jordy, thank you. Damn, it's great being here.
It's been a charge of being for a while and suddenly being is in the
news and we're going to be talking to Jordi about all
the reasons why. And in particular about
AI,
So, I guess I'd start with the question of, what
have you learned from users? Since the release of a, I powered
bang. And how's that, you know, shaping your future
strategy.
Thanks Tim. It's great talking to you. Well,
we've learnt quite a lot, we
have generally learned. That users are really enjoying the
product and that's really what makes us
excited about what we've done. We get a lot of positive
feedback about how they enjoy the ability
to transition smoothly,
The from the search mode to the chat mode and depending on the query, they
go into one mode or the other or sometimes, both and
being able to be with back and forth. We've also learned that they're
using the product in different ways that we did not anticipate like
primarily we build a search product and
when we look at for example, the chat mode, we see about
60% of all the chats have to do with search and they have to do
with information.
Retrieval information, exaction search in general,
right? And we thought that that percentage would be higher. We notice
a
Number of users are about 15-20 percent are
using it to create and they are
not using it essentially as a search engine. But to maybe create
letters songs, poems, basically they cut and
paste information, they use it to go to the
source coding and so that we expected some but maybe
was a higher percentage than we thought and then also the other
other remaining 20% or so is are using it just to
chat and just to basically chitchat with the
search engine on Surly to do anything creative, non
Surly to do anything formal in Search and so
that was also higher percentage that we expect. Does that seem like that's
just Tire kicking or do you think it's I
want to experience the AI or is there something there about people are
just enjoying this
idea of conversing with this
this program that has unexpected responses,
So it's kind of like exploring the web in the early days you were just clicking on things for the hell of it. You
want to find out what's Happening Here is like wow what's it going to say
yes? In fact
It's hard to tell. Exactly. Right. What
people have in mind, sometimes when they're using the product? But our
intuition is that they definitely are
surprised and maybe impressed with the capabilities
of the chat mode, meaning the conversation capabilities and they're having
fun with it. And you know, if you look at the logs, you
see people having all sorts of
Types of conversations, right? And so, so it's definitely
great to see that. People are enjoying it. But you see people doing all
sorts. Like, even though I gave you some rough percentages, you see the
same user using the product in different ways meaning that they
sometimes just want to have some fun in chat a little bit, sometimes they want to create
something and most of the time as we were hoping they are actually
searching the web. Yeah. Although from
Point of view of the other behaviors are, are really good news.
Because, of course, you know, I guess you already
have GitHub copilot. And, and you've announced that, you know,
copilot is going to be coming to office. And so if
in effect, people are going to be using that,
hey, I want to create something and because it's, I
think I forget who said this originally, but, you know, these
Large language models are like having you know, like 1,000
interns at your disposal because suddenly you can ask
it to do first drafts of virtually anything.
And it may not be right, but as I think soft, you said
it can even be usefully wrong.
I think that the beauty of these models is that they
can inspire you and of course, if you are searching for
something on the web and you want to, you have a
question that is a complex question that generally would not
be answer answered by a
traditional search engine. They've got this ability to extract the
information from multiple sources and
He's a new answer for you that you wouldn't find anywhere
else and that's like magic but at the same time that is Magic
to in being able to ask for inspiration. When you're
writing an essay, writing a letter writing, some source code, right? And
and this ability to transition to that scenario,
you know, in a very smooth way, is one of the things that I think makes the
product really fun. Yeah, I
One of kind of unpack a little bit more this notion that
it's changing the nature of search you know you're not just getting a
result that you know
maybe you know the yeah in the old days you guys would say we think this is
going to be the kind of synthetic result that people want but now you're
really generating it on the fly in response to very very specific
requests. Can you come out
of that?
Change. Yeah. Lolly the nature of search, but give you insight
into the changing nature of all future applications where you
just going to be able to be much more
specific in natural language with what you want
and the program are responds
with, you know the kind of this synthetic response that's just for
you.
That's right. And I think that is the the beauty of
you like of the combination of search with this
large language model technology, that the fact that it
can create new answers that you wouldn't find
anywhere. And now the answers are there, it just sometimes you would need to go through
a lot of sources of spend a lot of time and find that information
on your own and we can save you all that time.
I'm and I'll give you an example if you, for
example, I don't know view, if you are a runner but if you run marathons, you know, my
wife, you know, is a runner. And so she ran this Seattle
marathon and she was wondering, okay, well I like to run the New York
City marathon someday but what should I do differently to prepare for
it? Huh and if you if you ask this in the natural
way, you type that query in a traditional search engine. Well
often it'll break because it's a long natural.
Worry. Sarge engines are generally used
to queries that are 2 to 3 Watts. Max.
That's if you look at the vast majority of searches that that's what they are.
But now, you can type these long complex, natural query
and then what the the new being we'll do
is we'll, you know, look at all the results that you have on the web
and you will find some results that
It have to do with the Seattle Marathon others that have to do with the New York
City marathon, but you won't really have a specific
result that will be like oh I ran the Seattle - on and then
I went and run the New York City marathon. This is what you know, these are the
tidbits of information that you should know it, just that. So
the result that happened to exist, but then it'll
be created for you by being able to
extract that knowledge and reason. Overall this
Documents and then you'll be able to get the answer that you're looking for. Did your wife
actually try that query and was it correct? Or was it usefully wrong
but it was correct.
No, in fact there is a bit of a, you know, misconception
that oh wow, this models makeup
stuff and that that is true and I think that that is
one thing that we learn when when we
you know, when we saw gbd4 for the first time last summer,
we knew that it was special. It was a breakthrough in a large language
models. It was able to reason see
Emphasize extract information in ways that we haven't seen before.
And so we're very excited about it, but it did have two problems
one as you probably know is that it was trained with data through
2021. So was not able to answer questions
beyond that day and secondly is what we were just talking
about the fact that he would make up stuff it would house in eight. That's the
term that that people use. And obviously when you
Want to build a search engine, those two are big problems right off and
for a lot of other applications obviously you seen what's happened. WeChat
GPD, people are using it for a lot of other things and it's really, really helpful,
but if you want search, you really want to be able to answer questions up to right
now and you also want to make sure that the
information is accurate. And so what we did we didn't just put
say the GPT model gbd4 inside being
What we actually did, we combine search and be
in a process that we call grounding. We basically have a model on top
of the GT Model that we call Prometheus, which what it
does, it takes the party from the user, with the context, if it's in a
conversation and then it actually leverages
both search and GPT to break the query into
pieces. And that's if you've used a new being, you'll notice that sometimes
Tess searching for searching for Tina. Can do several
additional searches. Well, we're actually doing, we're going to the being
index and then we're selecting the information from the
web that's fresh that's comprehensive and we package it.
And then we provide that information into the gbt model and the model reasons
over it. So we're grounding the model with
fresh accurate search information. That's why if you look at a lot of the
The shootouts out there when people are comparing being with
chat gbd or with barn, a lot of the times, you know,
the conclusion is also, if you've got a recent query a
fresh worry, you if you want more accurate results and
and you know you want to reduce the risk of host
nation. The new being does a really great job and it's because of this
church. Handing process is part of what we call again the Prometheus
model. Yeah.
We've been talking about the user interface and the opportunities there. What
about the business model? You know, the business model of search has been
advertising, what's your sense of
how this is going to change? You know, it's obviously
a big challenge for you know anybody who's
suddenly you have a hold of game, what's your thinking about how ads will
fit into this?
Or whether they will fit it.
We think that's will play an important role. In fact, even today, if
you use the new being and you go to the chat mode,
you notice that we, we have references for
the result, for their, we call the chat and Sir.
If you hover on, do references, you'll notice that sometimes we actually include
ads in the list and sometimes also for certain types
of worries. For example, if it's a hotel suite,
You will also see product dots which are the ones that are
images with some Decks that are part of the
conversations. We actually attach them at the bottom of the chunk response. And so we
already have this text ads embedded into the chat answer
with the citations you know, and the product ads and so definitely
adds we think will continue to play a role but there
might be some ablution as well in terms of the
way we want to.
Dice like the the plug-in
architectures that were talking about where companies can include their
own mini applications. If you like that get connected to the
large language model that that may lead to other ways
of monetizing. But I think at the heart of it I think it's still
going to be the even by advertising. I
want to come back to the plug-in discussion but let's go a little
further on this.
Sizing model you have clearly when in the
early web search engines, they were still kind of doing the
in-your-face display advertising and then we
got, you know, pay per click, which for a pretty
for all the better part of a decade was pretty well aligned with
user intent. You know users are searching for something and there's a parallel stream of
ads. People get paid only when
they're relevant. So both the query and the ad
were were relevant to the user and in
this you know scenario I do we have to
reinvent add relevant so I think to make them useful to
the user but there's also I guess a question
yeah. What Larry and Sergey a Google originally called the problem of mixed motives when you have
advertising because your your goal that your
goal is to
Get the user. The best result, you might come up with one
thing. If you start injecting ads to have Ali,
which are not the goals of the user. But the goals of the advertiser,
how do you think about that in this AI context?
Well, I'd seen search have always been a balance, right? I think
it's well known that. Obviously, you used to components to
decide whether to show an ad in search results. One is
the relevance of the ad. And obviously, the more relevant, the add, the
more clicks, the ad will get and the more
conversion. So we'll provide to The Advertiser. But then there is also the bit. How
much is The Advertiser bidding for the
The words in the query and this, you know,
competition sort to speak in the heating mechanism of
and it creates the, you know what, we call the Marketplace, right?
And so we definitely know that the more relevant the
atom. It's better for every for everyone.
And so that's usually the pivot on how we
how we start when it comes to jerk.
Showing that the same will be true for job, right? I think ultimately chat,
response is composed of sentences that come from different
references or those products that I was mentioning. And so if
the user, you know, hovers on one of those annotations and
season that, if that is relevant, you know what? Basically, we
will we have marked and labeled Watson at and what's not
much like, well, right will surge, then we'll see Clicks in it and
All right, about the advertised this, the kids to the clicks to become
conversions. Yeah, I think the the point that I would want to make
is that, you know, many of the people who are in
the audience of you currently do search advertising social
media marketing. So on and this is a new frontier
which is going to have new rules and there's going to be a
mutual process of discovery by platforms
and you know and basically
Really companies that are trying to use those platforms about what
works in this new environment. So there's I guess we're headed for a, I guess a period
where people will need to be learning a lot about what's new and out
out out goes that make sense to you.
They'll definitely be song. Some changes in terms
of of the
The details. But if high level, I think that the
concepts that I was mentioning that adds being
relevant bits being taken into account the marketplace
working. I think it's gonna operate with similar
fundamentals. We get the same question about SEO.
Yeah, we need to SEO differently but a lot of
it is going to be similar because remember,
one of the
The key differences. Yeah. That the new being has say, Chachi PT
is this grounding mechanism and the grounding mechanism is just from search
results. And and ultimately is all David on the search results as
well. You're right, that there will be some details
that people will need to think through, you know, in terms of, you know how
you SEO on your bid and so on, I think it's going to be more of an
evolution right now and saying, Revolution, are you familiar with
what adapt dot a is doing?
Ting.
I am not I mean, I heard a little bit. Yeah,
nothing. I'm just so curious because they're
envisioning building, you know,
conversational interfaces to virtually every app. Now, of course,
Microsoft has already announced. They're going to build a lot of this technology into
office, for example, but I do wonder
how just how deep this, you
know, change is going to be.
Be you know you think about the change from da store windows
from you know windows to the web and now we're really
you know and yeah window web to mobile was it
was a change in you know the type of applications but it
didn't really change the UI that much. Yeah it was it had to be
more compact but it was still you know
and assume touch screens and so on.
But it was still very information-rich and so I hear we have a whole new
paradigm and to the extent that it becomes not just about
information but about you know, being able to control
operating systems apps, whatever. How do you see that progressing or is
it just too early to tell? Well,
definitely a I'd love to be able to go five years
from now and see where we are.
Hunting, we haven't seen
anything yet of what's possible. I think there is
a lot of capabilities in these models
that are going to really even surprised as,
you know, even years from now. I think people are even
today using the capabilities in ways. We did not anticipate
and it's really exciting.
I think you gave several
all examples in terms of, you know, PC web, you know,
mobile, I think definitely is another of this big steps
where the basically the ux, the way people
experience products is fundamentally going to
change. Its going to be more natural, is what I be.
It would be a lot easier to do essentially anything, whether it's
now, we talk a lot about writing and how the
LMS, I'm helping you write essays letters, right?
Goat out there, helping in Search and that's why
you see us at Microsoft, integrating it it to be on into
office. But one of the things that also
impressive and I unfortunately cannot see too much about it is that we have
all sorts of companies coming to wash your where we're hosting. Yeah, the
GB models and there are all sorts of startups or more
mature companies,
That they have all these different use cases, that
that go well, they range from you name. It, anything
that has to do from customer support to creating in
innovations that we hadn't even thought about. And so, definitely, it's going to be a new
world. I think it's what happened a lot
faster than we think. Like, I've been reading articles in well, even when, you
know, even the internet to time or, you know, there
was an article, I think
In the New York Times talking about how well these revolutions, you know, everybody thinks
they're happening tomorrow. But look, even
you took a long time for engines to replace horses, see, whether they were giving all these
different paradigms, right? But this is different because this is already on the
web, the applications are really exploding as we speak.
And so even if you if you just look at
more genetically, how people have
Have embraced charge a big deal, how quickly know it, reach 100 million
users, right? If you if you block how long it
took to Facebook to complete 100 million users, or
Netflix, guys, this, you know, you see this curse that are
like this and then the the chat GPT curve is like
this, right? And so same thing is happening with us being like we're seeing, you
know, this is a big spike, we always use users. I think that's
ultimately what's wrong?
And this, these tools are so useful and delightful that that,
you know, when people find out what they can do, they definitely want to be part of it.
And so that's why I think it's definitely going to happen faster
along, folks team, you mentioned that connection to Azure. And
you know, what do you think this is going to be a booster Azure that, you know, you've
got that is the the hosting platform for
both, you know?
Opening II and the Bing that is that a, we
swole? Yeah, yeah, we definitely think so. Because
obviously, we've been working closely with, oh, buddy. I and we're hosting older
models, in Azure and we have a, by scaling
being. We've learned a lot on how to scale these models. We fix a
lot of bags. A lot of problems, you know, how do you get
tens of millions of users on it in a reliable way?
A and so definitely we think
what we are ahead and it gives us an opportunity to really
be at the Forefront of enabling. All these other companies
that are interested in leveraging is capabilities to come to wiser and
basically you know be able to
take advantage of the latest technology that
best tested 10 best.
Best run, given everything that we've done. Do you think we'll open a, i plugins
require hasher, or work better with Azure or
there any, are there any dependencies
To be honest. I'm not sure about the plugins, what the restrictions are going to be.
I do think that given that the GPT models themselves will be
an Azure, there will be benefits if people build
on Archer and definitely, I think that were probably a
lot of companies will start because it'll just be simpler
at the same time to be fully Frank with you. I'm not Felicia
Okay, that's fine. Hey, you talk about how fast
this is going to go and you probably heard about the Open
Letter by Elon Musk and others calling for an AI. Pause,
what do you think of that?
Well I think it's good that there is a healthy debate about these Technologies.
I think like any new technology there are always
questions and and positive uses of it or
- users of it. But when I look at what we've done in and look
at the user Delight that that's really what I
see. I mean I obviously you can always
hypothesize a lot of different things about how the technology.
Apologies can be used but if you you look at the millions of users that are using
the products today, they are really using them to make their
lives better and they're finding that they are more productive than they can
really get inspired. And that's really what I think is the
core of what's driving this trouble,
Lucia is the fact that people are finding the tools
really useful and at the end of the day, that's what I'm focused on. I
want to thank to make the new
Being as helpful and as delightful
for users, as you can be. And I think that at the end of the day,
this is what's going to Prevail while at the same time, we don't need to be thoughtful and we do
make sure not just with LMS, but with AI
technology in general and we've said this at Microsoft from from the
beginning that there needs to be a responsible uses, there needs to be
some regulation that, you know, make sure
Sure that the the use much like any other
product really? There's got to be a regulation to make sure it's use the proper way.
Yeah, my concern is there's been a lot of fear-mongering by
people who bought into this idea of you know, Rogue
AI, you know. And this is is, you know,
you know, just, you know, I think it's been referred to people talking about, like, it's a nuclear
bomb. My sense is we're nowhere near that point, you know. And if I
They site surveys of people are afraid of very, very bad results but this was a
survey of people imagining artificial general intelligence and in
2059 you know and yet it's presented as though we're at
that point today and I don't think we're there at all. I mean these
are tools that are invoked by
humans and the kinds of risks that we have to worry about are things
like, you know, will they accelerate this the ability
to create Miss
Nation will they, you know, they'll be a lot of frontiers
of
You know, about by which Bad actors can, for example, generate,
you know, deep fakes, it's becoming easier and easier.
But those are not, you know, you know, Humanity,
ending kinds of problems. There are problems,
like the ones that we've been facing on the internet for
four decades magnified, perhaps, but the fact is the countermeasures are also going
to be magnified and
The may even be some opportunities where you go. Wow, if people
learn to not trust what? They
see it. See and hear that could be a good thing, you know. It's like you go.
Oh wait, I really have to verify this and
anyway, that's that's a. Wow. Yeah, I know that that's a great
reflection and and I think you're you're right.
Obviously, the way we look at these tools. Are you
define it? Very well.
Well, they are accelerators. We know when people are using
copilot in GitHub that they basically get
roughly to X, you know, relativity,
boast. In terms of the amount of code that they can write and the
same is going to happen. When you have these tools in Microsoft, Word,
PowerPoint, you are going to see how people can be basically a
lot more productive than what they are today. Will be able to answer
questions in.
That they were never able to get before and that's that's the
beauty of the integration that we've done in the new being. And so I feel like
at the end of the day that's that's what's going to be the core
of the value that people will see. Unfortunately, there
is a lot of fear because of, you
know, some of it is all these Hollywood movies of Dai taking over the
role and and, and we are far from an AGI. I mean, these are,
these are tools. I mean, this is not
Not, you know, the the
artificial general intelligence that that people talk about. No
no. I mean there's so many predictions and Wendy if we'll get there,
right? And so I think, I think that there is unfortunately, a lot of them.
Now, there are potential problems that we need to be very aware
of. And you mentioned a couple that I think, you know, are an important
problems. One is the ability to proliferate
misinformation, is who
Be enhanced by our Styles and that, that's true. But you said something very
important to our ability to protect from, it will be in Cannes
to and reality is that we as a search engines, we've
dealt with Spam junk Museum formation
for years and we're constantly developing Technologies
to try to, you know, down
rank this type of information for queries. And so,
so that will continue
the other one that you mentioned are defects, definitely, I think there should be
some way to regulate like if
somebody creates a fake video of you and I do
an interview saying crazy things, so there should be
some way to say, okay, well, this not this, not right, you know, and so
exactly what obviously Regulators need to step in,
but at the same time, the ability to create videos
Now just from trauma side. Or now, even in the new
being we've got the dolly opening I model where you can
type a few words, and you can create images,
that's really powerful. And and we see users loving it and and
finding inspiration with it and being a lot more productive in their
jobs with it. And so you gotta obviously have a balance
and we need to be thoughtful but I also worry that the
fear-mongering
Is exaggerated, and we need to, you know,
be balanced and think through this, you know, with pros and cons.
But I think at the end of the day, the Browns will clearly
outweigh the price will clear away the
concept. We're already seeing that. Yeah, a lot of people are
speculating that they'll be lots of job losses because
it'll make certain kinds of jobs obsolete. What do you think about that?
Well, I think that they'll be some changes and much like with
any technology, some jobs might be
lost at the same time. Others will be created and
I don't know if this is a great reference, but I
do remember when Excel was
created, a lot of accountants were thinking, oh my goodness, I'm going to lose my
job and it is through that today one accountant.
Excel can do what maybe 50 accounts we were able
to do, you know, maybe 50 years ago, right? But
accountants have not lost their jobs. They are, we have been a lot more
productive. That's a lot of accountants out there, right?
And so so I kind of envisioned the same Evolution
with this technology. Making everybody more productive and
yes, maybe there will be a given the bottom button in an, in a company
that will say, oh, wow, before we
Needed 10 people to do this job, maybe now we only need, you
know, a couple but but there will be other
jobs for this other folks that will be able to leverage the other
lamps and ultimately make Society more productive or lap.
Yeah, I think there's a fundamental law that
economists talk about which is that when things become
cheaper, people tend to use more of them here up. So
you know all of a sudden there's a there's a
A lot of capabilities that, yes, you know,
we were paying people do and now maybe they'll be being done.
They will be done by an AI, but it's not like, there's not enough work to.
Yeah. I mean, there's so much that needs doing that, this becomes the
superpower. I think companies that really understand this will
tackle new problems and go. Wow, we now have new
capabilities that let us solve things that we couldn't afford this
all before and
Now we add we can't afford, you know?
Yeah, no no I think. Anyway, I think
you're inside this is absolutely correct.
And in fact, another angle of this is that these
tools will be able to not only make you more productive
but also save you time on doing things that are not that much. Pipe is what
Satya often talks about like the grand jury.
Of work, right? The less interesting and maybe less creative
aspect of your job. You can easily just
get it done with two stools and I'll give you an example. In fact, you know, a few
months ago, obviously, we were talking a lot about the
large language models and, and my boss asked me to go to this
offside that right to document about it. And, you know, I was working
really hard on the new bang and I like, oh my goodness. I
I gotta do this and it sounds like that. You know, intuitively I could write, I
could take a few hours to do it, but I just went to the new baby and I
said, okay, well tell me, you know,
write a few paragraphs about what's a large language model?
Now, write a few paragraphs about the benefits. What are some of the
challenges will draw backs, right? Literally, something that would probably have taken
me, you know, three to four hours in half an hour.
Was done with the paper. Of course, there was a section of that paper that
I had to. You know, it was more the mine
sites, serve to speak but a lot of the background, a lot of
the information that's out there. You know, I was able to get
that done, you know, super fast and what was interesting is that I
posted this document very late at night and
and my boss and my boss was really wow, that was very quick jerk.
Ian, the document is very well written. Well,
I think we're out of time and it just this wonderful to
hear that optimism. That this is an accelerator
for productivity and are and
not that it's just that the benefits so far, outweigh
the risks. I'm with you on that. Thank
You very much.
Thank you.