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.