Artificial Intelligence

• applications

  • Self driving cars, delivery robots, flying drones, and autonomous ships.

    • Techniques used

      • search and planning to find the most convenient route from A to B,

      • computer vision to identify obstacles,

      • decision making under uncertainty to cope with the complex and dynamic environment

  • Content recommendation

    • Using information about yourself, via social media, items purchased or viewed, topics searched

    • Leads to personalised websites, and advertisements

    • Implication

      • filter bubbles, echo-chambers, troll factories, fake news, and new forms of propaganda.

  • Image and video processing

    • Face recognition

      • organizing your photos according to people, automatic tagging on social media, and passport control.

    • generate or alter visual content.

      • style transfer, by which you can adapt your personal photos

      • animated characters replicate gestures made by real human actors.

    • implications

      • create natural looking fake videos of events that are impossible to distinguish from real footage

  Definition

  • no officially agreed definition

  • the legacy of science fiction

    • Confuses what it is

    • Most science fiction is thus best read as metaphor for the current human condition, and robots could be seen as stand-ins for repressed sections of society, or perhaps our search for the meaning of life.

  • what seems easy is actually hard

    • hard to know which tasks are easy and which ones are hard.

    • It can be hard to appreciate how complicated a simple action which you do without thought can be

  • and what seems hard is actually easy

    • the tasks of playing chess and solving mathematical exercises can seem to be very difficult, but are easy for computers to solve

  • To define AI would be easier to define it's properties

    • Autonomy

      • The ability to perform tasks in complex environments without constant guidance by a user.

    • Adaptivity

      • The ability to improve performance by learning from experience.

  • hat different AI systems cannot be compared on a single axis or dimension in terms of their intelligence

    • Is a chess-playing algorithm more intelligent than a spam filter, or is a music recommendation system more intelligent than a self-driving car?

  • AI is a discipline, you shouldn't say “an AI“, just like we don't say “a biology“.

Related fields

• Machine learning can be said to be a subfield of AI, which itself is a subfield of computer science

• Machine learning enables AI solutions that are adaptive

• Systems that improve their performance in a given task with more and more experience or data.

• Deep learning is a subfield of machine learning,

  • the “depth” of deep learning refers to the complexity of a mathematical model, and that the increased computing power of modern computers has allowed researchers to increase this complexity to reach levels that appear not only quantitatively but also qualitatively different from before.

• Data science is a recent umbrella term (term that covers several subdisciplines) that includes machine learning and statistics, certain aspects of computer science including algorithms, data storage, and web application development.

  • Data science is also a practical discipline that requires understanding of the domain in which it is applied in, for example, business or science: its purpose (what "added value" means), basic assumptions, and constraints. Data science solutions often involve at least a pinch of AI (but usually not as much as one would expect from the headlines).

• Robotics means building and programming robots so that they can operate in complex, real-world scenarios. In a way, robotics is the ultimate challenge of AI since it requires a combination of virtually all areas of AI

  • Computer vision and speech recognition for sensing the environment

  • Natural language processing, information retrieval, and reasoning under uncertainty for processing instructions and predicting consequences of potential actions

  • Cognitive modeling and affective computing (systems that respond to expressions of human feelings or that mimic feelings) for interacting and working together with humans