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AI4All, AI4Good Presentation in Tarragona

Miguel
February 08, 2019

AI4All, AI4Good Presentation in Tarragona

Artificial Intelligence is changing the present, how to use AI and learn it, while making AI accessible to all for good

Miguel

February 08, 2019
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  1. Saturdays.AI is a Non-Profit Organization in a mission to deliver

    AI4Good brought to you with LOVE by diverse individuals like you, why not join us? #ai4all #ai4good CO ORGANIZER CO FOUNDER https://saturdays.ai CO ORGANIZER
  2. The 4th Industrial Revolution “85% of jobs that will exist

    by 2030 have not been yet invented.“ - What is the root cause of this trend? - What will be the implications for our society? Three factors to consider: • Time • Scalability • Wealth
  3. • 4th industrial revolution ◦ Productivity increase ◦ Negative implications

    ◦ Fast changes → society? How can we use AI to spark positive change? AI and the Future of Work
  4. Source: https://towardsdatascience.com/cousins-of-artificial-intelligence-dda4edc27b55 Machine Learning: it’s a subset of AI which

    uses statistical methods to enable machines to improve with experience, without being explicitly programmed. Deep Learning is a subfield of machine learning concerned with algorithms inspired by the structure and function of the brain called artificial neural networks” (the computer can learn complicated tasks as image recognition) Machine Learning and Deep Learning?
  5. AI 4 All • “Good” vs “Bad” AI • Aiming

    for positive change • Establishing a code of ethics • Diversity: Region • Diversity: Background • Diversity: Accessibility • Diversity: Gender • Diversity: Inclusivity
  6. AI Saturdays Community Began on January 2018! +10 +50 +500

    +100 Cities Ambassadors Members AI Projects + Alicante, Bogota, Lima, Monterrey, Almeria, Cordoba ...
  7. Learn by doing 1st Code2Learn (~8 saturdays) code exercises on

    notebooks 2nd Build2Learn (~6 saturdays) build an end2end AI prototype + Demo Day credit: Fast.ai Jeremy Howard
  8. Community building Intensive focus In a world of distractions, we

    provide the right environment and incentives so our fellows can focus on learning and coding AI during intense work sessions. Together with our activities and support, we transform such focus into an active community. Pair-Programming The key to our courses are our alumni, their motivation and their ability to help each other. We match them according to their goals and ensure that they work together to push their projects beyond their comfort zone. Learn By Doing The AI scientist mindset is forged by combining the theoretical lessons and building open-source projects, which enables our students to implement and test end-to-end AI apps with real customers.
  9. From when to when? Track Options • Beginner: Para cualquiera

    que quiera aprender sobre Machine Learning (ML). Utilizamos el curso “Introduction to ML for Coders” de Fast.ai, entre otros recursos. • Intermediate: Para aquellos que han entendido los conceptos básicos de Machine Learning y que desean adquirir una mayor comprensión sobre Deep Learning. Realizamos el curso “Deep Learning For Coders Part 1” de Fast.ai. • Advanced: Para estudiantes avanzados que ya conocen cómo implementar modelos de IA. Proponemos algunos de los siguientes cursos: UCL course on Reinforcement Learning (UCL RL), Berkeley CS294, Stanford Natural Language Processing (CS224n) y Stanford Computer Vision (CS231n). Sesión Contenido #0 Crash Course* Google’s ML crash-course / Python wrap-up #1 Meet & Greet Presentation / Setup / Speaker #2 Session 1 Fast.ai DL Lesson 1 / Fast.ai ML Lesson 1 #3 Session 2 Speaker / Fast.ai DL Lesson 2 / Fast.ai ML Lesson 2 & 3 #4 Session 3 Fast.ai DL Lesson 3 / Fast.ai ML Lesson 4 & 5 #5 Session 4 Fast.ai DL Lesson 4 / Fast.ai ML Lesson 6 & 7 #6 Session 5 Fast.ai DL Lesson 5 / Fast.ai ML Lesson 8 & 9 #7 Session 6 Fast.ai DL Lesson 6 / Fast.ai ML Lesson 10 & 11 #8 Session 7 Fast.ai DL Lesson 7/ Fast.ai ML Lesson 12 / Projects #9 Session 8 Practice / Projects / Speaker #10 Session 9 Practice / Projects #11 Session 10 Practice / Projects / Speaker #12 Session 11 Practice / Projects #13 Session 12 Practice / Projects #14 Session 13 Speakers / Demo Day
  10. Bias Corrector Aims to reduce cognitive biases in AI by

    creating a tool that helps to generate online content that is less offensive and that shows special to sexist and racist, proof of concept combining a RNN and a LSTM network. Authors: Irene Font Perajordi, Nora Lama and David Collado
  11. Far away on implementation, right PoC https://www.blog.google/technology/ai/fight-against-illegal-deforestation-tensorflow/ Reducing gender bias

    in Google Translate https://www.blog.google/products/translate/reducing-gender-bias-google-translate/ AI Sensors to fight Illegal Deforestation
  12. Deep learning to Save Lives in the Sea https://github.com/sfrias/sat4survive a

    CNN using Satellites to detect adrift small boats in the coast of Libya and empower anyone with a smartphone to save lives Inspired by
  13. • Udacity Nanodegree (800€) • MIT AI Course (3k€) •

    Masters on AI (7k+€) • AI Coding bootcamp (5k+€) Some resources • Harvard CS50X - (100€) • fast.ai - Free • deeplearning.ai - 40€/m • Come to AI Saturdays ;) Self-Taught Guided Approach http://bit.ly/tarragona1
  14. Thank You Let’s open the pod bay doors CODE 30%

    OFF: AI_FELLOW http://bit.ly/tarragona1