The present application discloses self-learning file transmitting, data reading and writing, and APP communication reading and writing methods of a game handle. The self-learning file transmitting method includes the following steps: S1: initializing a chip and scanning a key value; S2: erasing a FLASH chip and forming a reminder of usage; S3: scanning the key value and starting timing; and S4: timing and scanning the key value, and forming a reminder showing the end of learning. The present application provides a learning AI key with a special function on the game handle, and the AI key function can record operations of all users and save them as data for internal storage.

Provided is a system for providing an item generation service for generating an artificial intelligence-based dynamic game environment, the system comprising: a space database unit that collects topography and weather information of at least one area, converts the collected topography and weather information into 3D content, stores the 3D content, and includes a user interface for designing and setting a real estate object corresponding to at least one building or land; a character setting unit including a user interface for setting the gender, height, weight, and body type of a character, and setting a growth rate according to a training level; an item generation service providing server including an item generation unit for generating an item having the desired size, weight, design, resistance, hardness, and durability by combining at least one type of material; and a user terminal for defining and designing each of at least one attribute forming a space, a character, and an item in the item generation service providing server, and selling, purchasing, and exchanging a completed item.

An information handling system includes a memory to store data associated with metrics of an individual and gaming performance metrics, and a processor. The processor correlates the metrics of an individual with the gaming performance metrics. Based on the correlation, the processor creates a gaming performance score. The processor determines changes to implement based on the gaming performance score. When the changes are implemented, the changes improve the gaming performance score. The processor provides the changes to the individual in a non-intrusive manner.

An information handling system includes a memory to store data associated with metrics of an individual and gaming performance metrics, and a processor. The processor correlates the metrics of an individual with the gaming performance metrics. Based on the correlation, the processor creates a gaming performance score. The processor determines changes to implement based on the gaming performance score. When the changes are implemented, the changes improve the gaming performance score. The processor provides the changes to the individual in a non-intrusive manner.

Systems and methods for a computer-based process that detects improper behavior of avatars in a computer-generated environment, and marks these avatars accordingly, so that other users may perceive marked avatars as bad actors. Systems of embodiments of the disclosure may monitor avatar speech, text, and actions. If the system detects behavior it deems undesirable, such as behavior against any laws or rules of the environment, abusive or obscene language, and the like, avatars committing or associated with this behavior are marked in some manner that is visually apparent to other users. In this manner, improperly-behaving avatars may be more easily recognized and avoided, thus improving the experience of other users.

A system, method, and computer-readable medium are disclosed for improved threat sensitivity in a gaming application. As audio streams are received during a gaming scenario, a threat profile is selected that best matches the audio streams. The threat profile is a machine language cluster of noise used to adjust speaker equalization profile to emphasize threat noises. Digital signal processing (DSP) coefficients of the speaker equalization profile are adjusted as the gaming application continues.

A game processing system for processing a game having a first mode and a second mode according to an aspect includes one or more computer processors. The one or more computer processors are configured to provide an interaction with a virtual character in the first mode and the second mode. In a switch process for switching the game from the first mode to the second mode, the one or more computer processors are configured to, start the second mode if a switch object is selected by a player of the game gazing at the switch object during a predetermined period of time since the switch object is displayed, and return to the first mode if the switch object is not selected during the predetermined period of time.

A game processing system for processing a game having a first mode and a second mode according to an aspect includes one or more computer processors. The one or more computer processors are configured to provide an interaction with a virtual character in the first mode and the second mode. In a switch process for switching the game from the first mode to the second mode, the one or more computer processors are configured to, start the second mode if a switch object is selected by a player of the game gazing at the switch object during a predetermined period of time since the switch object is displayed, and return to the first mode if the switch object is not selected during the predetermined period of time.

A method of generating a multi-modal prediction is disclosed herein. A computing system retrieves event data from a data store. The event data includes information for a plurality of events across a plurality of seasons. Computing system generates a predictive model using a mixture density network, by generating an input vector from the event data learning, by the mixture density network, a plurality of values associated with a next play following each play in the event data. The mixture density network is trained to output the plurality of values near simultaneously. Computing system receives a set of event data directed to an event in a match. The set of event data includes information directed to at least playing surface position and current score. Computing system generates, via the predictive model, a plurality of values associated with a next event following the event based on the set of event data.

A method of controlling online gaming behavior. The method including monitoring at a game server a plurality of game plays of a plurality of players playing a video game in a gaming session over a period of time. The method including extracting features from the plurality of game plays related to a plurality of activities associated with the plurality of game plays, the plurality of activities being controlled by the plurality of players. The method including running the features through an artificial intelligence (AI) learning model configured to classify the plurality of activities. The method including classifying an activity as abusive behavior.