Affective Computing

By ethansailer
  • 3500 BCE

    Knapping

    Knapping
    Shaping a piece of stone is usually flint but can be chert, obsidian, or other conchoidal fracturing stone. Knapping was an important process in making stone tools. The photo provided is a group of arrowheads but this is only one of the many ways these stones were used for. The stones will continue to progress as the years go on.
  • Period: 3500 BCE to

    Affective Computing

  • Facial Recognition

    Facial Recognition
    A research team led by Woodrow W Bledsoe ran experiments between 1964 to 1966 to see whether 'programming computers' could recognize human faces. Facial recognition includes a rudimentary scanner that maps out a person's hairline, eyes, and nose. This was a fail because computers couldn't recognize faces, but then the 2D camera came out which created a flat image of a face and mapped the 'nodal points' (size/shape of eyes, nose, cheekbones, etc.). These nodes are then put into a numerical code.

  • Moore's Law

    Moore's Law
    Moore's Law is the observation that the number of transistors in an integrated circuit doubles about every two years. This doubling would hold till 2005-2007 but then would slow down after that point. This law was created through observation. There are some challenges with this law and the main challenge is running out of space on a chip because then the transistors would leak information from one to another. This is the reason why it has slowed down in recent years.

  • "Clippy"

    "Clippy"
    "Clippy" was created in 1996 by Microsoft. Clippy's main reason for creation was to help people hone their word processing skills. Microsoft thought this was going to be a great tool for people to use but actually was the quite opposite. "Clippy" quickly became one of the most hated computer assistance tools. It was a great step in the affective computing world but it scared people. People said it was more than personalization and it was more invasive than helpful for a lot of people.

  • Pepper

    Pepper
    Pepper is a humanoid robot that took the next step into the facial recognition world. Pepper was sold overseas in the UK and is still popular today. Pepper uses facial recognition to identify visitors or employees. Some of the other great things that Pepper has are voice tones, analyzing expressions, and voice tones. These are only a few of the many uses of pepper.

  • Our bodies electronic

    Our bodies electronic
    There are a bunch of ways that machines are becoming more human-centric and are learning how we go about our lives. A suite of technologies that span from eye-tracking to machine learning to BCI(brain computer-interfaces). These are all ways that machines are becoming more human-centric.

  • Dramatic decrease in the Work Force

    Dramatic decrease in the Work Force
    With everything becoming more and more technology no one will want to work anymore. There are too many easy and fast ways to make money on the internet so companies are going to struggle to find workers. Everything will be able to be learned on the web and there will be no place for employers in the world.