IBC
Artificial
intelligence technology is swiftly moving from experiment to practical use
across production workflows and into the heart of content creation.
Not
so long ago it was the subject of science fiction, but artificial intelligence
is now being used to write pop songs, break news, assemble reality shows and
even create Hollywood blockbusters.
Software
first developed at New Zealand’s Weta Digital for Avatarand The Planet of the Apes films, has been adapted by
Vancouver-based Ziva Dynamics to create computer-generated simulations that can
transform the way visual effects studios create characters.
Its
machine learning algorithms are trained on real-world physics, anatomy and
kinesiology to simulate natural body movements, including soft tissue-like skin
elasticity and layers of fat. It is claimed to animate CG characters in a
fraction of the time and cost of traditional VFX – and it’s been used on major
productions Pacific Rim and Fantastic Beasts.
Japanese
start-up Amadeus Code is one of many AI algorithms being trained to produce
music at the touch of a button. In its case a user uploads their list of songs
and the AI will analyse them before automatically generating new pop tracks
based on era, rhythm and range, all via an iPhone app.
These
are just two examples of AI’s pervasive reach across the industry right into
the heart of content creation. It is taking on laborious, expensive tasks such
as closed captioning, metadata tagging and social media clip generation.
Because of its ability to crunch volumes of data and yield meaningful results
it is swiftly moving from experiment to practical use.
When
the half-brother of North Korean leader Kim Jong-un was murdered in Malaysia in
2017 the news agency that broke the news – half an hour before anyone else –
was Japanese start-up JX Press Corp. It used AI to scour social media to find
breaking news then used another algorithm to write it up.
So
impressive are its results, that broadcasters NHK, Fuji Television and TV Asahi
are clients, with the latter’s deputy editor-in-chief Koichiro Nishi quoted by
Bloomberg as saying “it’s a world of 100 million cameramen. A must-have tool.”
Endemol
Shine Group (ESG) is using a Microsoft Azure AI workflow to replace an entirely
manual selection process in the Spanish version of reality show Big Brother. Through machine learning, the system
recognises patterns of language, keywords and emotional reactions. It tracks,
monitors and indexes the activities of the Big Brother house’s residents and
infers relationships between them.
“Watching
screens for so many feeds and arduously logging moments is very tedious,”
explains Lisa Perrin, CEO Creative Networks, ESG. “Now, we zero in on the most
interesting actions rather than wading through hours of footage.”
Declaring
the technology “ground-breaking”, Perrin says it will “completely revolutionise
the way we produce our global formats” and open up “an unprecedented level of
creative freedom”.
Accenture
reports a major Latin American content producer experimenting with AI to
automate and optimise production script creation for telenovelas. “An AI might
help maximise the number of scenes scheduled for shooting per week, maximise
the use of scenarios, minimise actors’ idleness or reduce time to move between
shooting locations,” says Gavin Mann, the consultancy’s Global Broadcast
Industry Lead.
AI-powered
algorithms are able to analyse every nook and cranny of every frame of video,
making it possible for a sports production team to sift through a mountain of
metadata and put together a montage of great plays in a few seconds.
Getting granular
Wimbledon, for example, used IBM’s AI to automate the tagging and assembly of two-minute highlight reels for online publication. The system rates each play based on metrics such as crowd noise and player gesture to speed the search of creative editors to build more extensive highlights. Isreal’s WSC Sports has developed a similar automated workflow for the United Soccer League in the US and is currently churning out 300 clips per game in near realtime.
Wimbledon, for example, used IBM’s AI to automate the tagging and assembly of two-minute highlight reels for online publication. The system rates each play based on metrics such as crowd noise and player gesture to speed the search of creative editors to build more extensive highlights. Isreal’s WSC Sports has developed a similar automated workflow for the United Soccer League in the US and is currently churning out 300 clips per game in near realtime.
“AI essentially turns haystacks of information
into needles of insights, which might be the best metaphor yet for how
traditional media companies can advance their businesses in a big way by
focusing on all things small,” says Joe McGarvey, Marketing Director at Imagine
Communications.
AI-powered
machines are also proving adept at identifying unwanted content. Google reports
that AI, not humans, detected about 80% of the 8.28 million videos removed from
YouTube in the last quarter of 2017. Facebook acted against 1.9 million pieces
of content on its platform in the first quarter of 2018, detected as fake
accounts and fake news by AI.
“For
many, the primary driver of adoption of AI technology is the opportunity to
automate routine workflows that are manually executed,” says Stuart Almond,
Head of Marketing and Communications, Sony Professional Europe. “Calling upon
metadata in particular is a catalyst towards a richer environment for
audiences. When applying this consumer lens, that’s when AI gets really smart and
creates real, tangible benefits for both companies and end-users.”
Netflix
is probably one of the best examples of how AI can help create a richer and
more tailored experience for consumers, while at the same time driving business
efficiencies.
“Its
AI-driven recommendations engine is safeguarding over $1 billion of revenue
each year by showing consumers the content they are really interested in and,
in turn, keeping them from cancelling the service,” says Almond.
“It
is a strong proof point that shows AI-based solutions can have a significant
positive effect on revenues, if done right. The key going forward is adopting
media supply chains that support this, bringing content acquisition and
production into this process.”
Data,
down to the finest detail, is now the currency with the most spending power in
the media and entertainment industry. The more granular that media companies
can get when it comes to knowing their networks, their audience and the way
their audience is consuming content, the richer they will be.
“The
challenge for media companies is finding a way to manage all the information
generated from every aspect of workflow from viewer preferences to rights and
network errors,” says Ian Munford, Akamai’s Director Product Marketing, Media
Solutions. “Most media companies are drinking from the fire hose but AI has the
potential to turn that data into action. Most uses of AI today are cutting
edge.”
Speaking
at CES at the beginning of this year, Amazon Vice President of Alexa Software
Al Lindsay had advice for those concerned about an AI-powered future.
“Learn
to code now,” he said. “If you know how to code, you can help change the
outcome the way you want it to be. It’s that simple.”
AI
at IBC
There has been a large focus on AI within Sony’s media services, which returns to IBC under the banner of ‘Go Make Tomorrow’. “The key drivers will be to open up more efficiencies and possibilities with how content is used in any workflow,” says Almond. “Sony is fiercely committed to collaborating with industry bodies and innovators to help our customers drive efficiencies and untap the potential of new technologies like AI and machine learning.”
There has been a large focus on AI within Sony’s media services, which returns to IBC under the banner of ‘Go Make Tomorrow’. “The key drivers will be to open up more efficiencies and possibilities with how content is used in any workflow,” says Almond. “Sony is fiercely committed to collaborating with industry bodies and innovators to help our customers drive efficiencies and untap the potential of new technologies like AI and machine learning.”
Accenture
is working with broadcast and video clients to incorporate AI into projects
spanning basic automation of back office processes and compliance checks, to
the optimisation of programming schedules and interpreting payments for
complicated royalties contracts.
“We
believe AI’s real power is helping reimagine business by augmenting, not
replacing, human capabilities,” asserts Mann. “Automation in content review is
one area in which companies can use AI to leap ahead on innovation and
profitability.”
With
such a new technology, and one developing at an incredible pace, Mann says
often clients want to start with a small proof of concept to demonstrate that
it actually works. “We can help them measure what is working, scale fast when
it does and fail fast when it doesn’t.”
Accenture
also offers access to its Amsterdam-based Innovation Center (only a mile from
the RAI) for further discussion and demonstration of its “very wide range of
use cases and client stories”.
Nuance
Communications, which describes itself as a pioneer in conversational AI,
says it is seeing demand for enhanced targeting based on voice profiles.
“Telecommunications customers are asking for the ability to better target and
tailor specific offers and messages to their end users,” states Dan Faulkner,
SVP & GM. “Developments are beginning to make this targeting more
intelligent.”
At
IBC2018, Nuance is presenting a new voice biometrics tool for its voice and
natural language understanding platform Dragon TV. Aimed at Smart TV
deployments, the innovation is intended for more secure authentication through
natural voice patterns. For example, when purchasing a film, rather than PINs,
passwords and security questions, this technology allows consumers to buy the
movie using their voice alone.
According
to AWS Elemental Chief Product Officer Aslam Khader, the next phase of AI will
involve the concept of “content lakes”, which means having all content and
related metadata in a unified location and proximal to scalable, cost-effective
and easy-to-use cloud-based AI services. He says: “The content lakes concept
makes searching, identifying and moving huge chunks of content across different
media workflows easy and efficient. You might think about this as media asset
management 2.0.”
At
IBC, AWS will showcase ways to make it easier for media companies to enrich and
monetise their content, with demonstrations of machine learning applications
that highlight capabilities such as video analysis for metadata enrichment,
automated compliance and editing use cases, automated transcription,
translation and text to voice capabilities for closed captions, subtitling and
audio description use cases, and clip production for personalised clip
generation and advanced sports graphics creation.
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