Research Paper: Dissertation Chapter 2

Abstract in artificial intelligent

Artificial intelligence is one of the innovative trends in the market place today. Machines can continually learn from the experience in addition to adjusting from new inputs and act like human beings in performing manual tasks. Artificial intelligence has helped human beings not only in the innovative sector but also in their healthy lifestyle like chess-playing machines (Karam, 2012). There are also electric driven automobiles that use the information coded in them to move from one place to another. However, the trends have changed over the years, with innovations being done every year. There are common trends in the field of artificial intelligence as focused on this paper (Karam, 2012).

Artificial intelligence was used to develop an artificial Dactyl that is being used to solve the puzzle of the Rubik Cube. Even the robot was developed in a simulated environment for an extended period, the knowledge was transferred to it, and, after it was relocated, the induced experience continued to work (Karam, 2012). To improve the efficiency of the robot, the domain randomization procedure was used to ensure that its capabilities were enhanced. The success of the project was not the developing phase, but the ability of the robot to operate in the areas that it had not been trained in.

In the field of online texting, there have been random developments made to ensure that the communication path is digitalized. Last year, Generative Pre-Training was released to release a synthetic message automatically. This model operates based on the fact that when as few words of a text are written, it automatically generates the remaining text without any command from the operator (Hanako, 2015). This was the second version of the project, and after its success, it was launched and used in over eight million website pages, which often create and generate the desired content.

This is a project that was initiated by Google LLC to incorporate future events into the present. The developers use Temporal Value Transport to send assignments and lessons from the future to understand the significant drawbacks of the decisions that are being made in the present (Hanako, 2015). It is a way of aligning the current concerning the future. Even though this idea was incorporated in a standard game, little did we know that it would soon be included in the field of artificial intelligence.

References

Karam, P. A. (2012). Artificial intelligence. New York: Chelsea House.

Hanako, A. (2015). A modern approach to artificial intelligence. Jersey City, NJ: Clanrye International.