AI: Myth vs Reality (November 2017)
Download as PPTX, PDF3 likes1,373 views
This document discusses myths and realities about artificial intelligence (AI). It begins by noting that AI has existed for over 60 years, having been coined in the 1950s, and discusses early pioneers. It then defines different types of AI like artificial intelligence, machine learning, and deep learning. The document then addresses five common myths about AI, providing facts to counter each myth. Some myths addressed are that AI is a fad, dark magic, or not ready for production use. The facts provided emphasize AI is grounded in math, code, and hardware and is being used successfully by many companies for practical applications. Throughout examples of real-world AI uses by Amazon Web Services customers are provided.
AI: Myth vs Reality (November 2017)
- 1. ©2017, Amazon Web Services, Inc. or its affiliates. All rights reserved AI: Myth vs. Reality Julien Simon @julsimon AI Evangelist, EMEA
- 2. Myth #1 - AI is the flavour of the month
- 3. John McCarthy (1927-2011) 1956 - Coined the term “Artificial Intelligence” 1958 - Invented LISP 1971 - Received the Turing Award Fact #1 - AI is 60 years old Marvin Minsky (1927-2016) 1959 - Co-founded the MIT AI Lab 1968 - Advised Kubrick on “2001: A Space Odyssey” 1969 - Received the Turing Award
- 4. • Artificial Intelligence: design software applications which exhibit human-like behavior, e.g. speech, natural language processing, reasoning or intuition • Machine Learning: teach machines to learn without being explicitly programmed • Deep Learning: using neural networks, teach machines to learn from data where features cannot be explicitly expressed
- 5. Data Computing power Programming models Algorithms The Rise of Deep Learning
- 6. Myth #2 - AI is dark magic aka « You’re not smart enough »
- 7. Fact #2 - AI is math, code and chips A bit of Science, a lot of Engineering
- 8. Myth #3 – The “cognitive” unicorn
- 9. Myth #3 – The “cognitive” unicorn
- 10. Fact #3: AI is a wide range of techniques and tools • Machine Learning • Natural Language Processing • Speech • Vision • Expert Systems • And more
- 11. Myth #4 - AI is reserved for esoteric use cases
- 12. Fact #4: AI shines on intuitive problems Credits: Shutterstock
- 15. Text Detection and Recognition https://github.com/Bartzi/stn-ocr
- 17. Myth #5 - AI is not production-ready
- 18. Fact #5: AI means business
- 19. Jeff Bezos’ letter to Amazon shareholders “We are solving problems with machine learning and artificial intelligence that were in the realm of science fiction for the last several decades. Natural language understanding, machine vision problems, it really is an amazing renaissance.”https://www.geekwire.com/2017/jeff-bezos-explains-amazons-artificial-intelligence-machine-learning-strategy/ https://www.forbes.com/sites/aarontilley/2017/04/18/the-great-ai-recruitment-war-amazon-is-on-top-and-apple-is-almost- nowhere-to-be-seen/
- 21. 25,000 skills
- 24. Selected customers running AI on AWS
- 27. https://news.developer.nvidia.com/expedia-ranking-hotel-images-with-deep-learning/ • Expedia have over 10M images from 300,000 hotels • Using great images boosts conversion • Using Keras and EC2 GPU instances, they fine-tuned a pre-trained Convolutional Neural Network using 100,000 images • Hotel descriptions now automatically feature the best available images
- 28. • 17,000 images from Instagram • 7 brands • Deep Learning model pre-trained on ImageNet • Fine-tuning with TensorFlow and EC2 GPU instances • Additional work on color extraction https://technology.condenast.com/story/handbag-brand-and-color-detection
- 30. https://www.oreilly.com/ideas/self-driving-trucks-enter-the-fast-lane-using-deep-learning Last June, tuSimple drove an autonomous truck for 200 miles from Yuma, AZ to San Diego,
- 31. As soon as 2018, Alexa will be your companion in BMWs https://techcrunch.com/2017/09/27/bmw-to-bring-alexa-to-its-cars-starting-in-2018/
- 32. Infrastructure CPU Engines MXNet TensorFlow Caffe Theano Pytorch CNTK Services Amazon Polly Chat Platforms IoT Speech Amazon Lex Mobile mazon AI: Artificial Intelligence In The Hands Of Every Develope Amazon ML Spark & EMR Kinesis Batch ECS GPU Amazon Rekognition Vision FPGA
- 33. 2010 61 516 1,017 159 2012 2014 2016 AWS Pace of Innovation
Editor's Notes
- #22: Amazon Echo is a hands-free speaker you control with your voice. Echo connects to the Alexa Voice Service to play music, make calls, send and receive messages, provide information, news, sports scores, weather, and more—instantly. All you have to do is ask.
- #23: Amazon Go is a new kind of store featuring the world's most advanced shopping technology. No lines, no checkout – just grab and go! %insert your experience with Amazon go here%
- #24: Amazon Prime air is a delivery system from Amazon designed to safely get packages to customers in 30 minutes or less using unmanned aerial vehicles, also called drones. Prime Air has great potential to enhance the services we already provide to millions of customers by providing rapid parcel delivery that will also increase the overall safety and efficiency of the transportation system.
- #26: Using AWS, C-SPAN can sample a frame every six seconds for recognition against indexed faces in a database of 97,000 people. Previously, this was done manually: Indexers scrolled through screen captures to identify who was speaking at any given point and select an image to represent each individual in each video. C-SPAN expects to save 8,000 to 9,000 hours a year in labor by automating that process using Rekognition, and will be able to index 100% of its incoming footage and archives.
- #33: duolingo story
- #36: XXX more precise articles on Medium