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Deep learning: from theory via virality to applications in business
Berlin Machine Learning Group
Rocket Internet
Rasmus Rothe
June 2, 2016
16-18 SEPTEMBER 2016
Howhot.io
100m+ evaluations to date
1m visitors in first
12hrs after launch
Spikes in usage due
to media attention
It’s more than a joke…
• Rasmus Rothe, Radu Timofte, and Luc Van Gool. "DEX: Deep
EXpectation of apparent age from a single image.”, ICCVW. 2015.
– Winner of LAP challenge on apparent age estimation (115 teams)
– NVIDIA ChaLearn LAP 2015 Best Paper Award
• Rasmus Rothe, Radu Timofte, and Luc Van Gool. "Some like it hot-
visual guidance for preference prediction.”, CVPR, 2016
• Rasmus Rothe, Radu Timofte, and Luc Van Gool. “Deep expectation
of real and apparent age from a single image without facial
landmarks”, in submission
• IMDB-WIKI dataset publicly available:
https://data.vision.ee.ethz.ch/cvl/rrothe/imdb-wiki/
Rasmus
Rothe
Radu
Timofte
Luc Van
Gool
Alex
Zimmermann
Jan
Berchtold
How it started
120,000 profile images
22 million hot-or-not ratings
44.81% men’s ratings positive
8.58% women’s ratings positive
Dataset statistics
Datasource # Photos Gender
(m/f)
Age
(23.4yrs)
Attractiveness
(top 23%)IMDb
500,000 x x
Wikipedia
60,000 x x
Blinq
120,000 x x x
1) Data to learn from
2) Teaching the deep neural network
3) What happens when you upload a photo
There is more research to it …
?
Prediction RatersVisual space
Nearest neighbor
Collaborative filtering
PT
Q
4.0 8.4 2.5 9.7 9.1 3.2 7.7 7.6 6.0
1.5 0.5 8.7 6.0 0.8 2.5 8.5 0.8 8.2
8.9 3.8 8.1 8.2 1.8 7.0 6.7 3.9 7.4
0.8 0.8 5.4 3.9 3.8
8.2
1.8
7.0
6.7
3.9
7.4
5.9
4.0
Visual QueryPastratings
OR
Matrix factorization
Latent space (Q)
Regression
What led to winning the age estimation
challenge (115 teams)?
1. Deeper models (VGG-16)
2. Ensemble classification (20 models)
3. More training data (500k+ images)
5. Robust face alignment
6. Deep expectation layer
4. Augmentation
Global Online Players
Which of these companies was founded in Germany?
Exception:
If we look closer …
1600out of 1900 of Germany’s biggest companies, are
B2B Industry Companies.
Source: Venohr, B., Fear, J., & Witt, A. (2015). "Best of German Mittelstand- The world market leaders.", Statista
V.S.
That’s what we are excellent at and lightyears ahead of Silicon Valley.
x8 turnover!
Merantix is an AI
Research Laband
a Company
Builderthat helps
industry companies to
leverage the power of AI.
Rethinking the
German core
strengths
ENGINEERING
Why focus on
B2B industries?
Industry
1
2
27
201
230
384
B2C Chatbots
Gaming
Medical Technology
Chemicals
Machinery & Equipment
Automotive
Consumer
Turner over in EUR in Germany - Sources: Germany Trade and Invest
Why applying generic
toolboxes is not enough
1. Dirty data
2. Industry specific knowledge
3. Combination of multiple data types
4. Robustness
5. Performance requirements
6. Understand failure
Cases
Patient Big Data
Lab Group, DE
eCommerce
Product Recom
Comp Builder, DE
Quality
Assurance
Chemicals, DE
Real Estate
Market Prediction
Insurer, CH
Technology
Scouting
Defense, CH
Bot
Communication
Wealth Manager, CH
Sepsis Diagnosis
Medtech, DE
Food Recogn
App
Telco, UK
Merantix GmbH
Friedrichstraße 68
DE-10117 Berlin
Managing Director: Rasmus Rothe
Registration No.: HRB 176845 B
Get in touch
Rasmus Rothe
rasmus@merantix.com
Adrian Locher
adrian@merantix.com

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Deep learning: from theory via virality to applications in business

  • 1. Deep learning: from theory via virality to applications in business Berlin Machine Learning Group Rocket Internet Rasmus Rothe June 2, 2016
  • 2.
  • 5.
  • 6.
  • 7.
  • 8.
  • 9. 100m+ evaluations to date 1m visitors in first 12hrs after launch Spikes in usage due to media attention
  • 10. It’s more than a joke… • Rasmus Rothe, Radu Timofte, and Luc Van Gool. "DEX: Deep EXpectation of apparent age from a single image.”, ICCVW. 2015. – Winner of LAP challenge on apparent age estimation (115 teams) – NVIDIA ChaLearn LAP 2015 Best Paper Award • Rasmus Rothe, Radu Timofte, and Luc Van Gool. "Some like it hot- visual guidance for preference prediction.”, CVPR, 2016 • Rasmus Rothe, Radu Timofte, and Luc Van Gool. “Deep expectation of real and apparent age from a single image without facial landmarks”, in submission • IMDB-WIKI dataset publicly available: https://data.vision.ee.ethz.ch/cvl/rrothe/imdb-wiki/
  • 12. 120,000 profile images 22 million hot-or-not ratings 44.81% men’s ratings positive 8.58% women’s ratings positive Dataset statistics
  • 13. Datasource # Photos Gender (m/f) Age (23.4yrs) Attractiveness (top 23%)IMDb 500,000 x x Wikipedia 60,000 x x Blinq 120,000 x x x 1) Data to learn from
  • 14. 2) Teaching the deep neural network
  • 15. 3) What happens when you upload a photo
  • 16. There is more research to it … ?
  • 17. Prediction RatersVisual space Nearest neighbor Collaborative filtering PT Q 4.0 8.4 2.5 9.7 9.1 3.2 7.7 7.6 6.0 1.5 0.5 8.7 6.0 0.8 2.5 8.5 0.8 8.2 8.9 3.8 8.1 8.2 1.8 7.0 6.7 3.9 7.4 0.8 0.8 5.4 3.9 3.8 8.2 1.8 7.0 6.7 3.9 7.4 5.9 4.0 Visual QueryPastratings OR Matrix factorization Latent space (Q) Regression
  • 18. What led to winning the age estimation challenge (115 teams)? 1. Deeper models (VGG-16) 2. Ensemble classification (20 models) 3. More training data (500k+ images) 5. Robust face alignment 6. Deep expectation layer 4. Augmentation
  • 19.
  • 20. Global Online Players Which of these companies was founded in Germany? Exception:
  • 21. If we look closer … 1600out of 1900 of Germany’s biggest companies, are B2B Industry Companies. Source: Venohr, B., Fear, J., & Witt, A. (2015). "Best of German Mittelstand- The world market leaders.", Statista V.S. That’s what we are excellent at and lightyears ahead of Silicon Valley. x8 turnover!
  • 22. Merantix is an AI Research Laband a Company Builderthat helps industry companies to leverage the power of AI. Rethinking the German core strengths ENGINEERING
  • 23. Why focus on B2B industries? Industry 1 2 27 201 230 384 B2C Chatbots Gaming Medical Technology Chemicals Machinery & Equipment Automotive Consumer Turner over in EUR in Germany - Sources: Germany Trade and Invest
  • 24. Why applying generic toolboxes is not enough 1. Dirty data 2. Industry specific knowledge 3. Combination of multiple data types 4. Robustness 5. Performance requirements 6. Understand failure
  • 25. Cases Patient Big Data Lab Group, DE eCommerce Product Recom Comp Builder, DE Quality Assurance Chemicals, DE Real Estate Market Prediction Insurer, CH Technology Scouting Defense, CH Bot Communication Wealth Manager, CH Sepsis Diagnosis Medtech, DE Food Recogn App Telco, UK
  • 26. Merantix GmbH Friedrichstraße 68 DE-10117 Berlin Managing Director: Rasmus Rothe Registration No.: HRB 176845 B Get in touch Rasmus Rothe rasmus@merantix.com Adrian Locher adrian@merantix.com

Editor's Notes

  1. intro