Link collection for the "AI for humans" talk

ai-for-humans.md

Slides

• The slides of the Intel AIDC keynote are available here as a PDF
• The slides of this talk are available on Dropbox as a PDF

Intro and history of ML on the web

• Autodraw by Google is a tool that allows you to doodle what you want to paint and turns it into a proper icon by detecting the outline and making an ML based assumption what it could be.
• Quickdraw by Google is a game they created a few years before Autodraw to train the model.
• ReCaptcha is a CAPTCHA engine that feeds the data back into Google's ML systems. For example, currently being asked to detect street signs or cars is a good indicator that this data will go into the self-driving cars project.
• Amazon's Mechanical Turk is a service by Amazon to get humans to do things for you. A lot of the data accumulated with that one could be used to train models. One very famous examples back then was to ask people to paint sheep facing left.
• All the big players in IT offer AI/ML services, like Google, Microsoft and Amazon
• NVIDIA released an interesting new algorithm to automatically fill missing parts of images using a deep learning network trained on faces.

Vision services and recognition

• There is a bot scouring Twitter that turns images into alternative text. All you have to do is to tag a thread with an image with #vision_api.
• The Vision API of Microsoft's Cognitive Services analyses images and detects what is in them. You get a list of tags and a human readable description. It also detects known entities, faces, celebrities and gives you the colours used in the image.
• The Face API of Microsoft's Cognitive Services detects human faces in an image. You get a truckload of data back: Age, Emotion, Gender, Pose, Smile, and Facial Hair along with 27(!) landmarks for each face in the image.
• Emotion detection is interesting and can be done by pretty basic means Susan Hinton's Emoji Face Demo is a good example how you can run this on your own machine.
• Ganpaint filling images with Gan generated content.

Speech Services

• The Speech API of Microsoft's Cognitive Services and Bing turns spoken words into text and speaks out text content using generated voices in various languages. Try it out on this demo.
• An excellent article on Smashing Magazine by Burke Holland on The Rise Of Intelligent Conversational UI with examples on why this is a useful thing and how to build your own speech recognition services without using the Alexa API.
• LUIS, an interface allowing you to train your own data sets for trigger words in spoken sentences, based on the LUIS API
• Converting speech to text is much easier when you trained the system on the person speaking. The Speaker recognition API allows you to detect who spoke a certain audio file and allows you to train the recognition algorithm on your own voice for much better results.

Ethics, Security and AI

• China's Social Credit System planned to be rolled out by 2020
• Chinese authorities are considering using "gait recognition" to detect people according to this Associated Press report
• You can generate photos of people by merging lots of celebrity photos and [create fake avatars](https://blog.insightdatascience.com/ generating-custom-photo-realistic-faces-using-ai-d170b1b59255)
• Social Mapper is an attack tool to detect users across dozens of social networks using facial recognition

Having fun

• PointerPointer - finding photos pointing at where the mouse is currently on the screen
• Move Mirror Google experiment finding photos with your current pose
• Cassie Evan's Shy Blob that only moves when you don't look
• Charlie Gerard's Teachable Keyboard
• Suz Hinton's Emoji face overlay demo
• Linda Liukas' Hello Ruby - a kid's book series going from "what is a computer" to "how does machine learning work?
• De-oldify - colouring old photos by comparison
• Inspirobot - a network trained by inspirational posters to create new ones. With hilarious results.
• Google's Deep Mind teaching a sensor array to walk like humans and almost hitting it, except for the arms

Interesting further materials

• W3C discussion group on Machine Learning on device in JavaScript
• Microsoft's AI for good program
• Object detection of ML is not infallible, it is actually pretty easy to Trick AI into recognising the wrong things using a few image tricks
• CGP Grey's "How machines learn" is a great 7 minutes video debunking a few AI myths.
• Chris Heilmann's AI course on Skillshare
• Microsoft offers a full length Machine Learning course for free ending with an "Microsoft Professional Program Certificate in Artificial Intelligence". You will learn about
  • The Math behind ML
  • The ethics of AI
  • Working with Data using Python
  • Machine Learning Models
  • Deep Learning Models
  • Reinforcement Learning Models
• Skillshare Course on Demystifying Artificial Intelligence

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