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Internet, Big Data e Inteligencia Artificial

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Vídeo de la charla: https://www.youtube.com/watch?v=9BrIwVbZZ7c

Revisar la evolución de Internet nos sirve para ver en qué punto estamos, cómo ha surgido el concepto Big Data y por qué la Inteligencia Artificial está evolucionando rápidamente en los últimos años, cuando en realidad las primeras experiencias se dieron a mediados del siglo pasado.

El Machine Learning es una disciplina de la Inteligencia Artificial que crea sistemas (a veces llamados "robots") que aprenden de los datos. Deep Learning es una rama del Machine Learning que pretende simular el funcionamiento del cerebro humano.

Published in: Data & Analytics
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Internet, Big Data e Inteligencia Artificial

  1. 1. 1 Internet, Big Data e Inteligencia Artificial Andrés González Director de Big Data y Análisis Predictivo en CleverTask andresg@clevertask.com Twitter: @data_lytics
  2. 2. 2 La (r)evolución de la sociedad de la información “Internet llega por capas y cada capa modifica el conjunto” Genís Roca, socio-director de RocaSalvatella
  3. 3. 3 Puedes ver el vídeo de la charla en la penúltima dispositiva… … o aquí: https://youtu.be/9BrIwVbZZ7c
  4. 4. 4 1989 La Internet de los Ingenieros
  5. 5. 5 1994 La Internet de las Empresas
  6. 6. 6 2005 La Internet de las Personas
  7. 7. 7
  8. 8. 8
  9. 9. 9
  10. 10. 10
  11. 11. 11 Impacto en el sector financiero
  12. 12. 12
  13. 13. 13
  14. 14. 14 Tom Goodwin, VP de Estrategia e Innovación de Havas Media “Uber es la mayor compañía de taxis del mundo. No posee vehículos. Facebook es el propietario de los contenidos más populares del mundo. No crea ningún contenido. Alibaba es el minorista con una valoración más alta. No tiene inventario. Y Airbnb, el mayor proveedor de alojamientos, no tiene propiedades. Algo interesante está sucediendo”
  15. 15. 15
  16. 16. 16
  17. 17. 17 ¿2014? La Internet de las Cosas
  18. 18. 18
  19. 19. 19
  20. 20. 20
  21. 21. 21
  22. 22. 22
  23. 23. 23
  24. 24. 24 La materia prima de los sistemas basados en Inteligencia Artificial son los datos
  25. 25. 25 1959 Arthur Samuel, ingeniero de software de IBM Machine Learning
  26. 26. 26 Máquinas que aprenden de los datos Ir al min. 2:42 del video de la siguiente diapositiva
  27. 27. 27 Árboles de decisiones
  28. 28. 28
  29. 29. 29
  30. 30. 30https://www.google.com/settings/ads/onweb/ Lo que Google usa para conocerte
  31. 31. 31 https://history.google.com/history/ Lo que Google usa para conocerte
  32. 32. 32 Lo que Google usa para conocerte
  33. 33. 33 https://maps.google.es/locationhistory Lo que Google usa para conocerte
  34. 34. 34 https://security.google.com/settings/security/activity Lo que Google usa para conocerte
  35. 35. 35https://www.google.com/settings/accounthistory Lo que Google usa para conocerte
  36. 36. 36 Aprender del comportamiento
  37. 37. 37 Anuncios y buscadores
  38. 38. 38 Sistemas de recomenación
  39. 39. 39 Clusterización de clientes
  40. 40. 40 Predicción de bajas de clientes
  41. 41. 41 Machine Learning en sanidad
  42. 42. 42 Predicción de riesgos en salud
  43. 43. 43 Machine Learning para salvar vidas
  44. 44. 44 Máquinas que crean música
  45. 45. 45 Robots que ayudan a pacientes
  46. 46. 46 Deep Learning: máquinas que aprenden a aprender
  47. 47. 47 Se basa en cómo aprenden los humanos
  48. 48. 48
  49. 49. 49 Detección de indicadores cancerígenos
  50. 50. 50
  51. 51. 51
  52. 52. 52 Traducción simultánea inglés-chino Minuto 7:11 del video de la siguiente diapositiva
  53. 53. 53 máquinas que saben ver máquinas que saben interpretar máquinas que saben escribir máquinas que saben leer máquinas que saben oír máquinas que saben hablar máquinas que saben traducir
  54. 54. 54
  55. 55. 55
  56. 56. 56 En la charla se explican con más arte conceptos que quizás no quedan claros solo con la presentación. Pasa a la siguiente diapo si la quieres ver :)
  57. 57. 57 ¡Gracias! Andrés González andresg@clevertask.com Twitter: @data_lytics

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