Generative Marvels: Charting the Course for Future Content Creation | NTLF 2024
Summary
TLDRIn this insightful presentation, the speaker discusses the future of content creation, highlighting five key shifts: the rise of agency as the new battleground, the value of human knowledge as the new Gold Rush, the correlation between trust and content observability/alterability, the emergence of new content creation opportunities, and the evolution of business models in the AI era. The speaker, with a rich background in tech leadership, emphasizes the importance of human creativity, data protection, and innovative strategies for content generation and distribution in a rapidly changing landscape.
Takeaways
- 🌟 **Human Agency as the New Battlefield**: As AI narrows the gap between thought and execution, human creativity becomes the new productivity, with applications that protect human agency ultimately winning in the market.
- 💡 **Human Knowledge as the New Gold Rush**: Human-created knowledge is invaluable, especially in the age of generative AI. Legal and ethical considerations around intellectual property and data protection will become increasingly important.
- 🔍 **Trust and Observability/Alterability**: Trust in AI systems is directly proportional to the observability and alterability of the content they produce. Transparency in data collection, analysis, and annotation is crucial.
- 🌐 **Content Creation's New Opportunities**: The cost of content creation is decreasing, leading to a growth in both core and peripheral content. New platforms like blockchain 2.0 will enable creators and consumers to engage in novel ways.
- 🏢 **Evolution of Business Models in AI Age**: Business models will change rapidly with AI advancements. Companies should evaluate their data's uniqueness, distribution advantage, and potential for a revolutionary user interface.
- 📈 **Personalization and AI**: Personalized AI systems will learn user preferences to provide more relevant content, but it's important to maintain human control and explicit decision-making in the loop.
- 🔗 **SEO in the AI-Summary Era**: As AI summaries become more prevalent, the focus of search engine optimization will shift towards ranking highly within AI-generated content rather than traditional blue links.
- 🎯 **Targeting Credible Mass**: Media and brands will shift focus from appealing to the critical mass to engaging with a credible mass of true audiences for their content.
- 💰 **Monetizing Unique Data Sets**: Companies sitting on unique data sets can monetize this knowledge by creating new distribution models and user interfaces, such as 'bottled knowledge' concepts.
- 🚀 **AI's Impact on Existing Business Models**: AI advancements can both empower and disrupt existing business models. Industries like dating sites and music apps must innovate to maintain user engagement and platform value.
- 🤖 **The Role of AI in Decision Making**: AI is increasingly involved in decision-making processes, from crime prediction to content serving. Understanding and addressing bias in AI systems is a critical ongoing challenge.
Q & A
What is the significance of the shift towards AI in content creation?
-The shift towards AI in content creation signifies a transformation where technology is taking the lead, narrowing the gap between thought and execution. It implies that human creativity will become the new form of productivity, with AI enhancing and supporting it rather than replacing it.
How does the concept of 'agency' relate to the future of content creation?
-Agency refers to the ability of humans to control their choices and decisions. In the context of content creation, applications that protect and respect human agency will be more successful. This means that as AI becomes more capable, it will still require human input and control to ensure the relevance and personalization of content.
What is the 'new Gold Rush' in the context of the talk?
-The 'new Gold Rush' refers to human knowledge and human-created content. As AI and synthetic content become more prevalent, there is a growing need for unique, human-generated content to serve as training data for AI systems. This makes human knowledge a valuable commodity.
How does trust in AI-generated content relate to observability and alterability?
-Trust in AI-generated content is directly proportional to its observability and alterability. The more transparent and modifiable the content and its sources are, the more trustworthy it becomes. This means that AI systems should be designed to allow users to understand and, if necessary, alter the information they are provided.
What opportunities will the AI era bring for content creators?
-The AI era will lead to an explosion of content creation opportunities. The cost of creating content will decrease, allowing for a wider range of content to be produced. Additionally, new platforms such as blockchain 2.0 will emerge, enabling creators to distribute, protect, and monetize their content in novel ways.
How will business models evolve in the age of AI?
-Business models will undergo significant changes in the age of AI. Companies will need to consider how their data can be used to create unique value propositions. They will need to assess whether they have unique datasets, distribution advantages, and the ability to provide a revolutionary user interface for accessing their data.
What is the concept of 'bottled knowledge'?
-The concept of 'bottled knowledge' refers to the idea of packaging unique, proprietary data sets and selling them to businesses or individuals. This could involve historical data on investment decisions, for example, which could be used to advise on future trades.
How might AI advancements impact existing business models such as dating sites or music apps?
-AI advancements could render some existing business models unsustainable. For instance, if AI becomes extremely effective at matchmaking, dating sites that rely on users repeatedly engaging with the platform may lose their appeal. Similarly, if AI can instantly find and generate preferred music, music apps may struggle to keep users engaged on their platforms.
What are the three vectors of differentiation for data in a company?
-The three vectors of differentiation for data in a company are: whether the data set is unique, whether the company has a unique distribution advantage over its data, and whether it can rebuild a revolutionary interface for users and enterprise to access the data.
What is the role of personalization in AI-enhanced content creation?
-Personalization plays a crucial role in AI-enhanced content creation. By learning unique user preferences and historical data, AI systems can generate content that is highly relevant and customized to individual users, thereby increasing the value and appeal of the content.
How can traceability and transparency of training data improve trust in AI systems?
-Traceability and transparency of training data can improve trust in AI systems by allowing users to understand where the data comes from and how it's being used. This openness can help users see the processes behind AI decisions, thereby instilling confidence in the system's outputs.
Outlines
🗣️ Introduction and Background
The speaker begins by acknowledging the challenging environment for the presentation and shares some personal background information. They mention their previous roles at Google, where they were responsible for search product strategy and launching AI efforts, and at Twitter, where they led product and business strategy. The speaker also highlights their educational background with degrees from Stanford Business School and Imperial College London. They set the stage for the presentation by stating their intention to discuss the future of content creation and the significant shifts that will shape it over the coming years.
🚀 The Five Equations
The speaker introduces five key equations or points that will shape the future of content generation. They emphasize the importance of agency, human knowledge, trust, new opportunities in content creation, and the evolution of business models in the AI age. The speaker provides a brief overview of each point, promising a more detailed discussion throughout the presentation. They also stress the importance of human creativity and productivity in the AI-driven future, suggesting that data trained on individual preferences will play a significant role in enhancing both.
🤖 Agency as the New battleground
The speaker delves into the first of the five equations, emphasizing agency as the new battleground. They argue that as AI narrows the gap between thought and execution, human creativity will become the new form of productivity. The speaker uses the example of Google search to illustrate how AI advancements are personalizing search results based on user preferences, thus enhancing human agency. They predict a future where applications that protect and enhance human agency will be the most successful.
🥇 Human Knowledge as the New Gold Rush
The speaker discusses the second equation, framing human knowledge as the new gold rush. They highlight the advancements in generative AI and synthetic content, while also pointing out the legal and ethical challenges surrounding intellectual property and data protection. The speaker encourages creators and businesses to think about content protection and compensation, and the importance of human-created content in decision-making processes. They stress the value of human knowledge in the age of AI.
🔍 Trust and Observability in AI
The speaker addresses the third equation, which links trust to observability and alterability. They discuss the increasing reliance on AI for information and decision-making, and the need for transparency in how AI systems collect, analyze, and annotate data to build trust. The speaker draws parallels with Wikipedia's high trust levels due to its open and editable nature. They advocate for the removal of obscurity in AI systems and the promotion of traceability in training datasets to instill confidence in AI-generated content.
🌐 New Opportunities in Content Creation
The speaker moves on to the fourth equation, which predicts new opportunities in content creation. They challenge the notion that AI will destroy core content creation, instead arguing that it will lead to a boom in peripheral content and a shift in focus towards niche audiences. The speaker also touches on the potential of blockchain 2.0 to revolutionize content distribution, protection, and monetization. They encourage media brands and creators to embrace these changes and adapt to the new landscape of content creation.
💡 Business Models in the AI Age
In the final equation, the speaker discusses the rapid changes in business models due to AI. They advise businesses to consider the uniqueness, distribution advantage, and potential revolutionary interface of their data. The speaker introduces the concept of 'bottled knowledge' as a case study, illustrating how unique datasets can be monetized through innovative distribution methods. They also caution against the potential negative impacts of AI on certain business models, such as dating sites and music apps, while highlighting the opportunities for those who can adapt and innovate.
Mindmap
Keywords
💡Content Creation
💡Human Agency
💡Artificial Intelligence (AI)
💡Personalization
💡Trust
💡Observability
💡Augmented Intelligence
💡Intellectual Property
💡Blockchain
💡Business Models
💡Data Provenance
Highlights
The future of content creation is shaped by five incredibly important shifts.
Agency, or the ability to control choices and decisions, is becoming the new battleground for content applications.
Human knowledge and creativity are the new gold rush, with AI narrowing the gap between thought and execution.
Trust in AI-generated content is directly proportional to its observability and alterability.
Content creation will present new opportunities that we haven't even thought about yet.
Business models will massively evolve in the new age of AI.
AI is enhancing human productivity by taking over routine tasks, allowing humans to focus on creativity.
Personalization in content is becoming increasingly relevant as AI learns unique user preferences.
Developers should prioritize data providence and consider the source of their training data.
Creators should think about protecting and compensating for their content in the age of AI.
Businesses with proprietary data need to establish a new contract with users for derivative work.
The importance of human-created knowledge is highlighted by the trust placed in individual reviews over synthetic content.
The transparency of data collection and annotation is crucial to building trust in AI systems.
Source attribution in content is becoming a new battleground for search engine optimization.
Content creation costs are decreasing, leading to a focus on niche audiences and the rise of blockchain 2.0.
Bottled knowledge, or the ability to package and sell unique data sets, represents a new business model opportunity.
AI advancements may render some existing business models unsustainable, such as dating sites or music apps.
Transcripts
can you hear me now yes all right
there's a resoning levels of thumbs up I
got to say this is the most uh
interesting uh uh environment in which
I've actually given a presentation I
think I can hardly hear myself so I hope
you all can hear me nonetheless it gives
me immense pleasure uh to be here uh
this is my second trip to Mumbai ever uh
and this is my first trip to nascom and
I'm excited uh to talk to you all about
uh the future of content
creation so little backstory um um I am
um uh I until recently I ran Google
search uh product strategy globally um
and also launched um many of Google
search's uh gener to AI efforts that you
heard suan talk about suman's team in
Deep Mind builds the technology and I'm
responsible for launching that through
Google search and and um I also in my
former life headed up uh Twitter I don't
know why this keeps going back to the uh
the previous slide uh but I also headed
up Twitter uh and I headed up uh product
and business strategy and operations for
Twitter excuse me and uh I'm a graduate
of Stanford Business School and also a
graduate of software engineering uh
bachelor's and Masters uh from Imperial
College
London so over over the course of uh
this next 20 minutes um I'm going to do
a worldwind tour of what I believe are
going to be five of the most incredibly
important shifts that's going to shape
the future of content generation for
years to come what I've been asked to do
is lay the foundation that you're going
to hear more and more about over the
course of today rest of today and
tomorrow I also want to warn you that
I'm going to go at a break speed um so
there's a lot of ground that I'm trying
to cover that hopefully lays the
foundation but I'm here for the
remaining two days so if you see me
walking around anywhere please grab me
you can also uh reach out to me through
Linkedin and uh it was my pleasure to
talk about this because you can imagine
as the person who's responsible for
product strategy and business strategy
for Google search content is the core of
what we do uh though I must also say
that I'm talking to you about this not
in the context as an employee or a
former employee of Google but as a
person who spends a lot of my time
thinking about where the space is going
so a lot of this is my own thoughts and
um and hopefully you find this
informative um I want to share because I
know this is the post lunch session and
uh many of you are awaking up after a
very beautiful lunch that we had I want
to share with you a few equations
because I know we're all mathematical
we're all engineers at heart and I want
to talk to you about five important
equations if there's nothing else you're
going to to take away over the course of
the next um 20 minutes or now 19 minutes
is these five equations and I've rolled
them out the first is that
agency is the new
backround for Content secondly human
knowledge and more importantly human
created knowledge is the new Gold
Rush thirdly trust is directly
proportional to observability
and alterability the more observability
and alterability you introduce to
content the more you trust that content
fourth is that content creation will
therefore present new opportunities that
we haven't even thought about so far
fifth is that business models will
massively evolve in this new age of AI
these are the five points or these are
the five equations I would love for you
to take away if nothing else over the
course of the next 20 minutes and I'm
going to spend my time into each one of
them in detail to make sure who you
understand I'm also going to present
many case studies to put this Theory
into practice so that it is much more
understandable um what I want to say is
that my idea here is to ignite a
discussion socialize ideas that you may
have heard of or partly understood or
very well understood but intentionally
my job here is to help connect the dots
uh and so some of these ideas are not my
own uh but hopefully what I'm able to do
is to connect these for you so that it's
much more palatable much more
understandable and more importantly
you're able to understand the
implications of what this means to your
individual businesses and Pursuits going
forwards okay let's start the first one
agency is the new Battleground what do I
mean by that we're at this incredible
point that you heard this morning from
my former colleagues fa Le and on um
that you know we're at this point where
to date we've been in a world of human
Le and Technology enabled
Innovation at this moment in time
technology is taking over and humans are
enabling it and the question that
becomes next for us is as technology
continues to lead what role does humans
play in this space and what we seeing is
that air why is this happening is that
AI is narrowing the gap between thought
and
execution let me put this into practice
here's a case study my bold claim to you
all is that creativity is the new human
productivity what do I mean by that if
you plot in x-axis and y- axis time and
y axis being value of our
energy then where this incredible point
where machines are a better investment
of our future productive gains than
before therefore what we're going to see
is that our pent up energy which was
previously deployed for productivity is
actually now going to be used for
incredible human
creativity and what we're going to see
is that to enhance our productivity and
enhance our creativity we're going to
see data that is actually trained on you
based on what you selectively decide to
share we're going to see incredible
intelligence that is actually going to
be infused with your preferences and
purchase history and bring objectivity
to decision- making and it is going to
be everywhere and constantly updated and
it's going to be interconnected to
everything and what this means is that
applications and this is the most
important slide in this first uh shift
is that applications that protect your
agency will ultimately win human agent
is the ability to control your choices
and your
decisions and so what we're seeing I'm
going to put this in a case study for
you to understand this is uh Google
search previously I made a search for uh
best recipes to cook for Thanksgiving
and till date It produced the 20 Blue
Links in the first page and the search
engine optimizations has happened to
make sure the best content is produced
but what's happening next is that if you
now use the latest Gemini model we're
actually giving you the answer if you
want to know what's the best
Thanksgiving recipe here's the answer
and there's some level of human agency
that's being afforded to say if you
don't like this answer you can
redraft but let's fast forward this what
happens if machines over time learn that
you're a family of four and that you
actually have one person who's
pescatarian one person who's vegetarian
or vegan and that every other uh
Thanksgiving you either cook at home uh
or you go to your in-laws for
Thanksgiving which is a very common
thing in uh in the US and so what
happens is you are going to be over time
given that ability to control what is
actually being generated by Ai and so
once the AI learns that these are your
unique preferences and that's what we
mean by personalization the answer
that's going to be here it's going to
become that much more relevant then the
question you all have to ask is well
what then is going to be my agency what
else would I be able to control because
if it actually knows everything about me
and personalizes the results for me then
where am I in this Loop where is the
human in the loop to make choices and
explicit controls and this is what I
mean about applications that continues
to give humans us the control will
ultimately win so we're going to see
this incredible race where AI is going
to get better at knowing us and
producing results and then it's still
going to need and applications that
still allow us to provide control is
going to basically be the winner as
opposed to it completely doing the work
for us and so the slide that I want you
to kind of summarize this section is
that your sense of control and power
Your Capacity to influence and your
ability to manage wide range of tasks
and situations is the definition of
human agency and this is going to be the
Battleground as you're going to see a
plure of applications that I've going be
built which application gives you the
control uh and gives you the sense of
control uh is going to be the ultimate
winner all right so that's the first
section uh let's move on to the second
section human knowledge is the new Gold
Rush what do I mean by that we all have
seen uh incredible breakthroughs in
gener to Ai and uh incredible uh
developments in what could be created
that I call as synthetic content and
we're also seeing Sora that just got
launched with Incredible lifelike video
uh that's got produced and we're all
mesmerized at what it's been able to do
with very little prompting and very
little data which is incredible but at
the same time certainly in the us and
we're also starting to see this globally
a launch of uh litigious uh constraints
that are being placed in terms of what
is the protection that's being offered
to content especially human created
content because that is the training
data that's being used provide to in
order to be able to infer and generate
artificially generated content and we
also saw landmark cases um in August
last year in the US we saw that
synthetic content cannot be
copyrighted which offers some level of
protection to human created
content but we're going to see a world
where as Ai and human intelligence comes
together to form augmented intelligence
we're going to get to a world where very
quickly gender to AI has an intellectual
property
problem and questions around what is
derivative versus transformative work
and where do you draw the line and what
is the right of fair
use and fundamentally is generative AI
hindering or helping Innovation are
going to be some of the most existential
questions we're going to be
asking all over from the legal framework
to the
industry
and as entrepreneurs as developers as
technologists in this room there are
three things I would like you to be
thinking about which is first uh if
you're a developer the word data
Providence has to be featured very
highly in your thinking in the words
where did the data that I'm using coming
from secondly if you're creators you
should be thinking about protection and
compensation of my content and thirdly
if you're a business and if you're
sitting on a w chest of proprietary data
how do I protect it but most importantly
how do I redraft a new contract with all
of
my all of the users of my content who
are using that content for derivative
work how do I actually add another clo
to make sure that I get fairly
compensated for the data that I have
created and one of the things that I
want to bring back with why human
creative knowledge is important is that
you know if you're Amazon and they've
done a fantastic job in actually
summarizing for a particular product uh
what is the what is why are the reasons
why people are buying it and that's what
you see at the top there um what we
seeing is that actually even in a world
where there is synthetic content that is
creating that's generated from AI That's
generated from text of consumer reviews
people still look at the individual
reviews that humans have actually
created and they're using that to form
their decisions so this is why premium
will always be placed on human created
knowledge all right let's move on the
third section trust is direct IR L
proportional to observability and
alterability
okay by the way each of these three five
things that I'm talking about are
billions of dollars of ideas and
industries that I'm hoping each of you
are thinking about and if the next big
startup is solving one of these problems
then I'm really glad to have contributed
towards that conversation um all right
so trust is directly proportional to
observability and alterability what do I
mean by that more and more of us are
going to be asking this question do I
trust the information that my AI is
serving
me this is going to be as Soloman
mentioned this morning you're all going
to have your own personal agents these
personal agents with the affordance of
some level of human agency are still
going to be making decisions for us and
the question that's going to be asked is
can I trust it and this is not a new
question ml bias is actually a very
well-known con concept and it's been
very uh well studied in the industry and
we still don't have answers for it and
that machines today are making decisions
on who's going to likely to uh uh commit
a crime for insurance purposes who sees
ads for good housing who should be
eligible for same day delivery and who
hears about particular research that I'm
doing and opportunities in that space ml
all around us are making decisions
already for us in terms of what the
content is being served but imagine a
world where personal agents are by you
and are actually telling you what you're
going to see then how can you trust
those agents and how can you trust the
content that's being produced by those
agents that's going to be the key
question and it all comes back down to
fundamentally in the ml process how is
data collected and analyzed and annotate
annotated so that is the training data
how it's collected and annotated that's
where bias is introduced and we don't
have to go that far we can actually take
a look at Wikipedia The largest source
of human creative knowledge in the world
Wikipedia it has its flaws but one thing
it has taught us is that the trust
levels in general are fairly high with
Wikipedia why because the content is
open observable and
alterable and so what we need to do is
that we need to remove the obscurity and
the alterability uh we need to remove
the obscur ability and increase the
alterability and promote traceability of
the training data
sets and so what do I mean by that we
need to remove the obscur ability uh
obscurity as to how much and what
percentage and what weights are being
afforded to any data on your training
sets and we need to ensure that systems
are continuously updated in ways that
allows us to edit and alter in a public
and transparent way especially if you
see bias in that
data and lastly we need to instill
confidence as to so that people know
where does this data come from
instilling confidence at that data will
promote confidence all the way above so
I'm drawing an analogy that we don't
need to reinvent the wheel here we need
to actually learn lessons from where we
have seen this work for example at
Wikipedia but I'll leave you with this
thought in this section which is I did a
search on perplexity AI recently which
is where's the best place to get
Gujarati food in Mumbai it's my second
time in Mumbai as I said I was very keen
to understand where is authentic food
and I did the search and what's
interesting is it gave me this results
and to give me the confidence that I'm
not hallucinating I'm actually knowing
what I'm talking about there is this use
of sources at the top that you've seen
it perplexity is not the only product
that does that many products today are
doing that to instill confidence and
Trust in the data that it's using to
generate the summary however what I
foresee happening very quickly is if I'm
a content creator who's created this
content that you're seeing there before
and in the future if I'm not coming
through this content because there's no
Blue Links for me to click anymore then
how am I going to get compensated that
you have used my data to train and come
up with the summaries and all you've
done is Citation how do I ensure that
each of those things at the top are
ranked as highly as possible and I get
compensated therefore ladies and
gentlemen what we're going to see is
that that Source attribute is going to
become the new Battle Ground for search
engine optimization so if you are in
marketing Departments of your companies
the question you should be asking asking
is not search engine optimization of the
10 Blue Links but how does my content
get very highly ranked up in an AI
summary all right the fourth concept
that or fourth shift that I want to talk
about is content creation will therefore
produce new opportunities this is
particularly important if you're in the
world of media Brands our
creators and so there's a worry
especially um among um media in in the
in in Hollywood um as a starting point
that um there's going to be core of
content creation is going to be
destroyed um but instead what I believe
and many many of us believe is that
there's going to be a bodal growth we're
going to see um that fundamentally core
is only going to get stronger and
there's going to be a long tail of
periphery content that's going to become
100x bigger what do I mean by that
there's going to be in a not too distant
world that because the cost of content
creation has come so low if you're a
brand or if you're media agency the cost
has come so low that the risk and the
ROI that you're going to take in making
sure I need to land this one feature
movie on in a summer blockbuster right
or I need to get this one particular ad
perfectly right to hit my target
audience that pressure is going to be
alleviated the cost of content creation
has just become lower and you've been
able to appeal to a long tale of
audience and so what you're going to see
is that instead of appealing to the
critical mass those folks who are on
social media who thumbs up thumbs down
on a particular movie or a particular
campaign that you've launched you're
going to start focusing on your credible
Mass the true audience for the content
that you're creating the true audience
for the movie that you're making the
true audience for the brand that you
want to reach and that long tail is
going to engage and it's going to become
a new audience and it's going to engage
with your content in new ways that you
have not actually seen in the past
and the other thing that we're going to
see is that there's going to be a birth
of blockchain 2.0 where there's going to
be ways in which creators and consumers
of created content are able to engage
with each other in new ways and that you
can distribute protect and monetize
content in ways you have not done before
through
blockchain all right my final Point um
and then I'll conclude which is business
models in the age of AI as going to
rapidly
change
and many of you are actually sitting on
gold but you may not know it so if
there's something that I want you to
walk away from this session today is if
you're a business please think about how
is your data
non-portable and can you protect in ways
so that you can actually build use your
data as your new mode and there's three
vectors of differentiation that's going
to matter I would like you to ask three
questions um for the data that you have
in your organization first is it in any
way a unique data set secondly do you
have a unique distribution advantage
over your data and thirdly can you if
you don't already have today a re build
a revolutionary interface for users and
Enterprise to access your
data and I want to leave you this
section with a case study and a concept
called bottled knowledge imagine a world
where you are now uh bursh hatway
sitting on 30 years worth of investment
history that you made uh Charles Munger
and um uh Warren Buffett have and that
data of all the trades they've made is a
unique proprietary data set that is
their Moote and imagine if they could
actually package that knowledge or
bottle that knowledge and actually sell
to investment um uh firms and financial
planners all around the world and more
importantly imagine if they can actually
sell it directly to you so next time
you're making a trade you're not going
to your financial planner you're not
going to your broker but instead you're
talking to this uh agent this bottle
knowledge that is telling you based on
30 years worth of trade this is the
particular trade pick to make this is
the right time to make that trade and
this is what you should do Post you post
making that trade that is the power of
unique data sets that have a
distribution Advantage with a
revolutionary user interface so that's
the question each of you should be
asking which is what is in my company
the secret Source what is that bottle
knowledge that I can actually figure out
new ways to
monetize and at the same time be aware
there is an increasing perversion of
certain business models that are liable
to be gained or constrained by AI what
do I mean by that is if AI becomes
incred inedibly brilliant in the
matching algorithm and you come in and
you find and you go then what happens to
dating sites that are optimizing on the
number of people that you're actually
coming on the platform turn left and
turn right do they become unsustainably
effective similarly if you're actually
are in the music business and you
provide apps that are spending time on
the platform and if they're coming in
and actually finding their particular
music straight away or worse yet if
they're actually tuning into synthetic
content how do music apps keep you on
the platform for longer it may not be
possible anymore so this is actually
having some very interesting business
model implications on the other side as
well all right in this session ladies
and gentlemen hopefully uh you had a
whistle uh stop tour of five shifts that
are profoundly going to impact content
and future of content creation I do
appreciate that I went through this at
break neck speed and there's probably uh
hours worth of session to Deep dive into
each one of these Concepts I'm here for
the next two days my name is Lakshmi
Shanker you can see me up on LinkedIn
and uh I'm Keen to hear from you and uh
thank you so much for affording me this
this time post lunch thank
you for more content on Tech and
Leadership subscribe to nascom YouTube
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