Computational Intelligence

Here is the thirty-sixth episode of Quantum Foam, Computational Intelligence. We are going over soft computing. We are covering the general topic of Artificial Intelligence this decimal of the show. What is all the hubbub about A. I. recently? It is not going to take over. It is not exactly like the cinematic matrix. We are looking at A. I. that has been created using linear computers. Computational Intelligence is a branch of Artificial Intelligence. This type of system would be able to make decisions based on acquired information. We are interested in acquiring massive data sets of Meta information. We are talking about metaphysics and also physics. We are using programmatic shortcuts to accomplish tasks intelligently. Computational Intelligence is the theory, application, design, and development of linguistic computer programming. Is your A. I. a Neural Network? Is it a Fuzzy System? Or is it Evolutionary Computation? Those are the 3 pillars of Computational Intelligence. It is a subfield of Artificial Intelligence. There is no A. I. that is at the level of Skynet. There are Feed Forward Neural Networks and Recurrent Neural Networks. There are also Fuzzy Systems that use traditional logic. These are not simple yes and no binary inclusions. The point is to have linguistic summarization capabilities. This is built into A. I. We want systems to be able to pass The Turing Test. Eugenics is like adoption. There is also Swarm Intelligence, which creates a multi-objective optimization scenario. Real-life Star Trek tractor beams are now possible. Artificial life is concerned with life itself. There is software, hardware, and wetware. The soft deals with the software, the hard deals with the hardware, and then there is wetware, which is the biochemistry approach. We are worried about the ability to natural language process English. What is happening is imperfection minimization. The idea is for a program to run with no human source of leadership. Imprecise information is debugged and corrected. New knowledge is acquired and old knowledge is deleted. The new knowledge takes the place. The difference between A. I. and C. I. is A. I. requires vast amounts of data before it can make its decision. A. I. probably uses patterns. Computational Intelligence uses fewer data points, but is reliant on good algorithms. Humans often have to run this stuff. C. I. doesn't have the same predictive capabilities as A. I. There is Generative, Game, and Predictive A. I. There is the computer's Machine Intelligence. How smart is the machine? The best A. I. systems are based on Computational Intelligence. C. I. focuses on the growth of a system, not necessarily the 1s and 0s. A. I. still can't process large amounts of data due to the limitations of computer technology. We are creating A. I. essences. It is like a personality or a book of an entity's personality traits. This is recorded in a spectrogram. A lot of A. I. is only meant for 1 specific application. This is software. We will keep writing the software to run on the current hardware. Coherent usage of software is what is under review here. How coherent is the software? We want to acquire back-end data in computable form. There is no truth in the Artificial Intelligence, but it is going to offer you information in whatever way it was programmed to do so. We can build software that meets all of the requirements to be considered Computational Intelligence. It's on the Computational Intelligence and Quantum Foam level.