New technology and how it is transforming traditional media was the main focus at the recent Streaming Media East conference. There’s no doubt AI and machine learning are impacting media, and according to a panel of experts, it will be a boon to both consumers and the media business.
Nadine Krefetz, a consultant with Reality Software, noted that,
“Machine learning and AI are more buzzy than ever.” The reasons why
media should be focusing on these protocols include the need to harness
huge amounts of data, stitch together all of the complex parts inherent
in the data sources and automate the cost efficiencies and time.
According to Gabriella Mirabelli, EVP Consumer Insights and Brand
Strategy, Valance Media, AI is the technique that creates human learning
using logic. She noted that Machine Learning is a subset of AI that
uses, “complex statistical techniques to improve tasks that the
technology can do.” Another subset of AI is Deep Learning that “uses
algorithms to help the machine train itself.” In sum, AI uses human
intelligence while machine learning uses data to predict outcomes.
What AI Can Do
When applied to media, these
systems enable smooth processing and understanding of the mountains of
data now available to marketers. For Mirabelli, we are advancing into,
“an Era of Insight from the Era of Data,” where there is greater
complexity and too much data for humans alone to handle. She uses these
systems to make buy decisions and to answer unique questions. For Field
Garthwaite, Co-Founder and CEO, Iris.tv, these systems can be used to
improve the customer experience and, for Thomas Ohanian, Global Sales
Executive, IBM Watson, the underlying technology that these solutions
depend upon enables speech to text, object recognition, voice and other
interactive elements by “reducing human tasks and gleaning insights from
What AI is Doing Now
Sports are a ripe area for
AI. Ohanian explained that fewer people are going to events at the
stadium, preferring to watch on the glass. AI offers real time insights
by using algorithms to assess “intent, reaction and gestures to build
interesting and timely sports highlights.” It is an instantaneous way to
“pick plays, players, matches and play types through automatic curation
which is very sticky,” to reduce the bounce rate and help editors find
relevant content quickly.
Nikki Conley, Cloud Solution Architect, Microsoft, offered another
perspective. Mistakes can be corrected or monetized. A recent Game of
Thrones episode erroneously had a Starbucks cup in the frame. “If we ran
through an analysis and saw the cup, we could remove it … or ask
Starbucks for advertising support,” instead of inadvertently giving them
$2.3 billion in free advertising. AI enables the ability to “look for
occurrences in content in post-production with extensive tagging.”
From amassing data to curating content to correcting mistakes to
providing an overall better experience for viewers and more profitable
opportunities for advertisers, the future is now for AI in media.
This article first appeared in Cynopsis.