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PRINT NEWS WILL
NEVER BE THE
SAME
Gutemberg changed the
way news was recorded
and disseminated
Modern newspapers
turned news into a
business, they
democratized access to
information
The internet further
facilitated access and
democratized content
creation
Today we’ve hit a wall,
innovation is stalling
Our mindsets our stuck in
the print era. Innovation
only aims at taking the
newspaper experience
online.
The way we consume
print news is the same as
it was a century ago:
through reading.
What if we could change
this?
What if we could make
news articles come to
life?
Introducing KIM:
Knowledge In Motion
KIM instantly turns any
text article into a video
How KIM works
KIM uses a complex, proprietary algorithm to go through the text of any
article to capture its substance and tone.
Based on this analysis, KIM taps a database of images and video clips to
create a short video (typically between 60 and 120 seconds) that includes
video content (with most important quotes superposed above the images)
and an audio narration of the article.
Thanks to unique data compression algorithms, KIM is blazingly fast and
fully optimized for mobile access.
KIM combines the best of all
media types
Print news

•
•
•
•

Diversity of sources
Depth of analysis
Ease of access
Low cost of production

Video news
• Impact
• Easy to consume
• Usage of audio + images for
a deeper imprint
• Convenient to share

KIM tears down the barriers between news
formats to combine the best of both worlds
KIM completely changes the way
people consume news
 Faster consumption allows you to get more in less time: KIM allows to
consume a standard 1000 word article in less than 1 minute versus 3
minutes for text version
 Better retention: 30% better retention rate of key information than for
text version thanks to combination of audio + video

 Easier sharing: 100% better sharing rate than for text version
 Increase in total number of articles consumed: KIM leads to a 40%
increase in number of articles consumed by making it easier to
consume news on the go
How can KIM be used?
KIM represents a potential revolution in the news business and has
virtually limitless applications
 Creation of a proprietary content curation app
 Partnerships with established media outlets (Ex: LeMonde, Le Figaro,
New York times…)
 Partnerships with aggregators such as Flipboard or Google News
 Licensing of technology on the open market
Accolades
We are still at the early stage of product development but KIM has already
been hailed as a potential game changer.
What’s next
 Finalization of algorithm
 Roll out in French and English
 Partnerships with established media outlets
The founders
Terry Burrowitz

Michael Dupraz

At 32 Terry is a world renowned leader
in the field of automated text analysis
and language engineering. A graduate
from the Ecole Polytechnique in applied
mathematics, he was formerly head of
IBM’s Knowledge Management
Research center where he spearheaded
the development of text recognition
algorithms.

A former Rhodes Scholar, Michael is
currently the Laurence B. Albert
professor of computer science at MIT.
He is a recognized authority in the fields
of artificial intelligence and serves as an
advisor for startups in the fields of
robotics and AI.

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Kim

  • 1. PRINT NEWS WILL NEVER BE THE SAME
  • 2. Gutemberg changed the way news was recorded and disseminated
  • 3. Modern newspapers turned news into a business, they democratized access to information
  • 4. The internet further facilitated access and democratized content creation
  • 5. Today we’ve hit a wall, innovation is stalling
  • 6. Our mindsets our stuck in the print era. Innovation only aims at taking the newspaper experience online.
  • 7. The way we consume print news is the same as it was a century ago: through reading.
  • 8. What if we could change this?
  • 9. What if we could make news articles come to life?
  • 11. KIM instantly turns any text article into a video
  • 12. How KIM works KIM uses a complex, proprietary algorithm to go through the text of any article to capture its substance and tone. Based on this analysis, KIM taps a database of images and video clips to create a short video (typically between 60 and 120 seconds) that includes video content (with most important quotes superposed above the images) and an audio narration of the article. Thanks to unique data compression algorithms, KIM is blazingly fast and fully optimized for mobile access.
  • 13. KIM combines the best of all media types Print news • • • • Diversity of sources Depth of analysis Ease of access Low cost of production Video news • Impact • Easy to consume • Usage of audio + images for a deeper imprint • Convenient to share KIM tears down the barriers between news formats to combine the best of both worlds
  • 14. KIM completely changes the way people consume news  Faster consumption allows you to get more in less time: KIM allows to consume a standard 1000 word article in less than 1 minute versus 3 minutes for text version  Better retention: 30% better retention rate of key information than for text version thanks to combination of audio + video  Easier sharing: 100% better sharing rate than for text version  Increase in total number of articles consumed: KIM leads to a 40% increase in number of articles consumed by making it easier to consume news on the go
  • 15. How can KIM be used? KIM represents a potential revolution in the news business and has virtually limitless applications  Creation of a proprietary content curation app  Partnerships with established media outlets (Ex: LeMonde, Le Figaro, New York times…)  Partnerships with aggregators such as Flipboard or Google News  Licensing of technology on the open market
  • 16. Accolades We are still at the early stage of product development but KIM has already been hailed as a potential game changer.
  • 17. What’s next  Finalization of algorithm  Roll out in French and English  Partnerships with established media outlets
  • 18. The founders Terry Burrowitz Michael Dupraz At 32 Terry is a world renowned leader in the field of automated text analysis and language engineering. A graduate from the Ecole Polytechnique in applied mathematics, he was formerly head of IBM’s Knowledge Management Research center where he spearheaded the development of text recognition algorithms. A former Rhodes Scholar, Michael is currently the Laurence B. Albert professor of computer science at MIT. He is a recognized authority in the fields of artificial intelligence and serves as an advisor for startups in the fields of robotics and AI.