Playing who wants to be a millionaire using Universal Artificial Intelligence

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This video shows a robot playing who wants to be a millionaire. There are no sound in the video because I wanted to show the viewers what the robot is thinking while playing the game. The flashing text and freeze frames are the internal thoughts of the robot and not instruction text for the viewers. These internal thoughts describe the details of how the robot produce intelligence.

My robot doesn't use: planning programs/heuristic searches (used by MIT and Stanford University), Bayesian's probability theories for decision making, Bayesian's equation for induction and deduction, semantic networks for natural language understanding, predicate calculus, common sense systems, first-order logic, rule-based systems, genetic programming, or MACHINE LEARNING.

The IBM Watson back in 2011 played Jeopardy and beat the best human players (Ken Jennings and the other guy). This robot works completely different from the IBM Watson. First of all, my robot doesn't use machine learning (these are the right answers and these are the wrong answers). The Watson uses massive servers to store and process information because it's a computational system and not an analytical system. My robot doesn't need to crunch out all possible answers to a question (millions of them, ranked in descending order). My robot contains trained pathways that go "directly" to the answer. Think of the Watson as a million missiles fired at a target randomly, and my robot as 1 missile fired at a target intelligently. Both methods will destroy the target, but my robot took only 1 shot, while the Watson took a million shots.

There is a reason why the human brain can do so much, but the space that it occupies is so small. The IBM Watson, if it was built efficiently, wouldn't take up more than 1 server. I believe that if we build my robot correctly, the brain of this robot won't take up more than 1 server (2013). This includes storage of data and processing intelligence in the robot. Believe it or not, the human brain can store a lot of data (videos, music files, static data, linear procedures, and memories) in a very tiny space. Why can't we do the same thing with a robot brain?

All information to answer questions is learned from teachers in school or through personal experience. For example, the first question asked in the video was about content in a movie. The robot has to extract the movie, Gladiator from memory and search for a particular scene. Once he finds the correct scene, he uses analytical methods to identify targeted objects in the scene. This QandA method was learned from teachers in school. Teachers teach the robot how to search for information and how to extract information from pictures.

Another notable difference between the IBM Watson and my robot is the Watson can only play Jeopardy (it can't do anything else). My robot can do "any" human task. It can play Monopoly, drive a car, cook, write complex software programs, fly a plane, do college assignments, etc. The Watson can do other things only if engineers modify the internal codes. For example, if you want the Watson to diagnose patients, software engineers has to spend 5-10 years designing the algorithm.

By the way, if my human robot was competing with the IBM Watson, my robot will probably lose because it thinks and acts like a human being.

In the video, the robot is actually doing multiple tasks at the same time. He is following the rules and objectives of the game, using strategies to beat the game, and answering questions. For example, if the robot was given the same question twice, he will tell the judge that he has already answered the question. This is based on common sense. He is aware of common sense things during the game, which is important. In the Jeopardy challenge, Watson was unable to understand and sense what answers were given by other players. Thus, Watson sometimes gave the same answers as other players.