Abstract: An information processing system includes a first information processing device and a second information processing device. The first information processing device is configured to receive the atomic information from the second information processing device, calculate a processing result corresponding to the atomic information by inputting the atomic information into a neural network, and transmit the processing result to the second information processing device. The second information processing device is configured to transmit atomic information to the first information processing device.

Abstract: A display device includes a display, an acquirer, and a controller. The display is configured to display a display image containing identification information of a purchase item to a reader of a cash register. The acquirer is configured to acquire external output information from the cash register. The controller is configured to control a display operation of the display on the basis of the external output information. When the controller determines, on the basis of external output information of a first purchase item from the cash register, that the cash register has identified the first purchase item, the controller causes the display to display a display image containing identification information of a second purchase item.

Abstract: An inferring device includes one or more memories and one or more processors. The one or more processors are configured to acquire a plurality of latent variables; generate a plurality of structural formulas by inputting the plurality of latent variables, respectively, in a model; and calculate a plurality of scores by evaluating the plurality of structural formulas, respectively. The one or more processors execute processing of the acquisition of the plurality of latent variables, the generation of the plurality of structural formulas, and the calculation of the plurality of scores, at least two times or more. The one or more processors acquire, based on the acquired plurality of latent variables and the calculated plurality of scores, the plurality of latent variables in any of the execution of at least second time or thereafter.

Abstract: An inferring device includes one or more memories and one or more processors. The one or more processors are configured to acquire a latent variable; generate a structural formula by inputting the latent variable in a first model; and calculate a score with respect to the structural formula. The one or more processors execute processing of the acquisition of the latent variable, the generation of the structural formula, and the calculation of the score, at least two times or more, to generate the structural formula indicating the score higher than that of the structural formula generated at the execution of the first time.

Abstract: Provided are a training device, a disease affection determination device, a machine learning method, and a program that are applicable to various living organisms other than humans without performing time-consuming mapping. The present disclosure provides a machine learning unit that trains a model for a predetermined disease using, as an input, a training feature vector based on an appearance frequency of a plurality of types of substrings in a base sequence obtained from a training sample collected from a learning subject and, as an output, label information indicating whether the learning subject is a subject affected by the predetermined disease or a subject not affected by the predetermined disease.

Abstract: A learning method of a mixing ratio prediction of element comprising causing a machine learning model to learn to output, in response to input of group expression level data indicating an expression level of each element in a group to be predicted, a mixing ratio of an element contained in the group, wherein in the causing a machine learning model to learn, a virtual mixing ratio that differs among a plurality of pieces of learning data is set as desired, and a learning dataset is used, the learning dataset including data generated, for each piece of the learning data, by obtaining a virtual expression level that is a virtual expression level corresponding to the virtual mixing ratio based on original data indicating an expression level in each element.

Abstract: Provided is a steering device which can be reduced in size and weight and easily adapted even to a vehicle with a small engine room, such as a front-wheel-drive car.