A system provides for collaborative training in a graphically simulated virtual reality (VR) environment by causing display, by at least one participant device, a first graphical indicium controlled by a first real-time human participant and causing display, by at least one other participant device, a second graphical controlled by a second real-time human participant. A training session is conducted via virtual interaction of the first graphical indicium and the second graphical indicium in the three dimensional virtual reality environment. The first graphical indicium is displayed in the three dimensional virtual reality environment to said second real-time human participant by said at least one participant device. The second graphical indicium is displayed in the three dimensional virtual reality environment to said first real-time human participant by said at least one other participant device.

The technology relates generally to an interactive avatar training system. The interactive avatar training system utilizes an interactive platform that allows at least two users, such as a trainer and a trainee, to be in interactive communication in a training program. The interactive avatar training system may assist generating a processed answer or response from the trainer to the trainee so that the answer presented to the trainee has high level of accuracy. Thus, the training efficiency and accuracy may be enhanced and improved.

Obtain, as input, in electronic form, structured information including tasks for a plurality of occupations in a plurality of industries over a length of time; compute, from the structured information, a time series of normalized occupation task shares over the length of time; train a computerized machine learning model, on the time series, to predict future task shares for the plurality of occupations in the plurality of industries; and, with the trained computerized machine learning model, predict the future task shares.

Apparatuses, method, systems, and program products are disclosed for assessing instructor ratings on a defined rating scale for skewness. An apparatus includes a processor and a memory that stores code executable by the processor. The code, when executed by the processor, receives a raw instructor rating data set, comprising a plurality of ratings from an individual instructor, on a defined rating scale. The code is executable to determine a rating skewness of the raw instructor data set by subtracting a central tendency measure of the plurality of ratings from a central tendency measure of the defined rating scale, and dividing the result by the standard deviation of the plurality of ratings. The code is further executable to compare the rating skewness of the raw instructors rating data set to at least one comparative rating skewness to generate a skewness comparison report. The code is further executable to determine if the individual instructor requires instructor training based on the skewness comparison repair and identify a required instructor training to provide to the individual instructor. The code is also executable to make the data accessible to one or more end users.

A method, performed by a server, for supporting equipment service at a site includes receiving, from Head Mounted Equipment (HME) associated with an installer at a site, data relating to an inventory and location of equipment at the site, wherein the data is collected by the HME during equipment service, wherein the equipment includes one or more of a circuit pack, a line module, a cable and power equipment; and checking the equipment service based on the received data and at least one of plans associated with the site and configuration rules of the equipment.

Techniques for presenting a recommendation to a member of a social network in a specific field of study are described. A predictor can access, from a database in the social network, educational data of a plurality of students and post-graduate data of a plurality of graduates in the social network. Additionally, the predictor can determine a subset of students associated with a specific field of study, and can calculate a demand for the specific field of study based on the accessed data. A recommendation generator can calculate a competition value for the specific field of study based on the determined subset of students and the calculated demand for the specific field of study. Subsequently, the recommendation generator can cause a presentation, on a display of a device, of a recommendation associated with the specific field of study, the recommendation being based on the calculated competition value.

In an example embodiment, a method is provided where information regarding a member of a social networking service and a job opening are obtained. Then information about a plurality of courses available for the member to take is obtained, the information including cost, time, and a vector including, for each of a plurality of skills identified in a member profile of the member, an effect of taking the corresponding course. A subset selection algorithm is then used to select an optimal combination of courses selected from the plurality of courses, based on minimizing cost and time while maximizing cumulative increase in odds of the member successfully obtaining the job opening from taking the selected courses.

A member profile including a vector containing a field for each of a plurality of skills and a rating of one or more of the skills in the vector for a member of a social networking service is obtained. A first distance indicating a vector distance between the vector of the member profile and a vector of a hypothetical member profile representing the perfect job candidate is obtained. A hypothetical member profile for the member is created by combining the vector of the member profile with the indication of how each of the one or more skills is improved through taking the course from course information. A second distance between the member and the hypothetical perfect candidate for the job is obtained, and the difference between the first distance and the second distance is calculated to determine an estimate of how much the course will increase the member's job chances.

The embodiments herein provide a system and a method for creating a real time environment depending on the historical era preferred by a tourist. The method provides a tour program that provides a historical era experience to the tourists according to their preference. The method allows the tourist to choose the preferred historical era from a list of created historical environment setup. The tourists selecting similar historical era are grouped and allocated with a tourist guide. The tour program provides the tourists with real time event experience of certain situations. The tour program also entertains the tourists by providing situations that create a sense of excitement, fear and other emotions among the tourists.

Embodiments are directed to managing skill proficiencies. Declared skills may be determined based on a job description and natural language processing (NLP) actions declared in one or more extraction models. An inference prompt for a large language model (LLM) may be generated based on the job description such that the job description and the declared skills may be included in the inference prompt. The LLM may be trained with the inference prompt to generate a response such that the inference prompt may be iteratively updated based on validations of the response. The LLM may be retrained with the updated inference prompt to generate an updated response that includes the inferred skills that may be separate from the declared skills. A job profile that corresponds to the job description may be updated to include the declared skills and the separate inferred skills.