Hoy en día es difícil no hablar de la Inteligencia Artificial y pensar en cómo se ha aplicado para resolver tareas difíciles y repetitivas para el ser humano. Pero en los últimos años, gracias a la llegada de las Redes Generativas Adversariales (GANs), la IA adoptó capacidades creativas que le permiten generar información artificial. Es la era de los Deepfakes, en la que puedes poner tu cara al actor de tu película favorita o ser felicitado por el presidente de los Estados Unidos. En esta charla, veremos gran parte de estas capacidades adquiridas por la IA, algunos ejemplos, y pondremos a prueba nuestro ojo para comprobar si estamos preparados para detectar que es real y que no.

1. ¿Qué es real? Cuando la IA
intenta engañar al ojo humano

2. O R G A N I Z A T I O N
P L A T I N U M S P O N S O R S
Thank you!
C O L L A B O R A T O R S

3. What is real?

4. How do you define 'real'? If you're talking about
what you can feel, what you can smell, what you
can taste and see, then 'real' is simply electrical
signals interpreted by your brain.
MorpheusWhat about AI and its own existence?

7. A computer would deserve to be called
intelligent if it could deceive a human
into believing that it was human.
Alan Turing

8. What is Artificial
Intelligence?
• More than simply code
• Solve hard human tasks
• Capacity to learn from the environment
• Intelligent Agents
Features
Any system that interacts with the environment, perceives
it, learn from it, and takes actions to achieve successfully
its goals and tasks through flexible adaptation.

9. @ematde
ematallanas@plainconcepts.com
Knowmad interested in:
• Changing live through AI
• Passionate in robotics
• Data lover
• Films & series
• Bike enthusiast & martial artist practioner
Eduardo Matallanas
AI Team Lead @ Plain Concepts

10. Things we will talk today
• What is AI
• Why using it
• Benefits of using AI
• AI applications
ATTENTION: A deep change is coming!

11. Let’s look back!!

12. Artificial Intelligence
Machine learning
Deep learning
𝑡1950 1960 1970 1980 1990 2000 2010
Dark Ages
A new hope: Alexnet

13. Why using AI now?
Challenges
Reducing Costs
Escalating demand
Optimization
Usability
Interactions
Data Increase
Increase of
unstructured data
Organize data
Sensor information
Increase articles
Technology
Maturity
Previous effort
Improved
algorithms
Specialized HW
Cloud platforms
General Access
Democratization
Open source code
Frameworks
Cognitive services
Entrepreneurship
Investment
Specialization
Innovation
Business
transformation

14. Applications by source
•Image
classification
•Object
detection
Image
•Fraud detection
•Defect
enhancement
•Speech
recognition
Audio
•Knowledge
extraction
•Information
retrieval
•Sentiment analysis
Text
•Time series
analysis
•Forecasting
•Clustering
•Dimensionality
reduction
Signal processing

15. AIs Victories

16. Current AI Focus
• Narrow or Weak AI
• Only for solving specific problems
• Problems can be decomposed
• Complex models based on
• Model composition
• Deeper structures
• Towards a more general AI
• Models that can solve more than one task
• Making decisions
• Evolve from their response and environment
Which feature is necessary?

18. How about AI in fashion design?

19. D
Discriminator
How can we create our own fashion?
G
Generator
Latent
space
Noise (s)
Real
Samples
𝑧(𝑥, 𝑠)𝑥
ො𝑢 = 𝐺(𝑧)
𝑦
𝐿 𝐺𝐴𝑁 𝑙𝑜𝑠𝑠
Is D
correct?
Fine Tune Training
𝐿1(𝑦, ො𝑢)
𝐷(𝑦, 𝑧)
Generate fake samples to fool the discriminator
Classify fake images vs real images

20. What about the final product?

21. Does not end here

23. What about art?
Transfer style
+ =

24. How does it work?

27. Can I really
use it in
people?

28. StyleGAN =
GAN + Style Transfer
by NVlabs

29. Even create your own people
https://generated.photos/

31. Obama wants to say something

32. Deepfake 101: Lyp syncing from audio
Time-delayed LSTM
ℎ0 ℎ1 ℎ2 ℎ 𝑛
𝑥0 𝑥1 𝑥2 𝑥 𝑛
𝑦0 𝑦 𝑛−2
Input video
Masked
Input
U-net
Audio Input
Texturize mouth and generate it.
𝑣(𝑡)

33. Deepfake 101:
• Problems
• Blurring
• Synchronization
• Masking
• Similar audio profile
• Solutions
• Enhance the realistic mouth
• Create enhancement process for the mouth
• Use better masking

34. Hablemos del mileniarismo de los Deepfakes

35. What are Deep fakes?

36. I have a dream: Ctrl + Shift + Face
≡ ⟹

37. FaceSwap: Facial Extraction
Original Frame Face Detection Aligned Face

38. FaceSwap: Autoencoders
ො𝑥 = ℎ 𝑊,𝑏 ≈ 𝑥

39. FaceSwap: Facial Modification
Training
Reconstructed A
Encoder Decoder A
Latent face A
Latent face B
Encoder Decoder B
Original A
Original B Reconstructed B
Generation
Encoder Decoder A
Latent face A
Latent face B
Encoder Decoder B
Original A
Original B Reconstructed B
From Face A
Reconstructed A
From Face B

40. FaceSwap: Facial Transfer
Original Frame
Reconstructed
Face B from A
Merged Face Color Correction
Merged Frame

41. FaceSwap-GAN
What about autogenerating the mask?

42. It’s showtime

43. Raúl Cimas as Mark Zuckberg
Mark Zuckberg as Raúl Cimas

44. One more thing …

45. What about generating
text?
• OpenAI project
• Based on Transformer approach
• Training on larger datasets:
• books, webs…
• Increases:
• Reading comprehension
• Translation
• Summarization
• QA
• Entire code not publish → Model with 1.5b words
GPT-2

47. Conclusions
• AI is key to
• Automatize processes
• Create new business models
• It is here to help!!!
• Decision making support
• Towards a Generalized AI
• New features → Creativity
• Explaining what is inside
• Harder, better, faster, stronger
• Get ethics inside!!!
• The risks of fakes
• Images rights
• Biased data
• DeepFake forensics → https://github.com/ondyari/FaceForensics

48. Questions?

49. Thanks and …
See you soon!
Thanks also to the sponsors.
Without whom this would not have been posible.
O R G A N I Z A T I O N
P L A T I N U M S P O N S O R S
C O L L A B O R A T O R S