Abstract: Herein are machine learning techniques that adjust reconstruction loss of a reconstructive model, such as a principal component analysis (PCA), based on importances of features. In an embodiment having a reconstructive model that more or less accurately reconstructs its input, a computer measures, for each feature, a respective importance that is based on the reconstructive model. For example, importance may be based on grading samples that the reconstructive model correctly or incorrectly inferenced. For each feature during production inferencing, a respective original loss from the reconstructive model measures a difference between a value of the feature in an input and a reconstructed value of the feature generated by the reconstructive model. For each feature, the respective importance of the feature is applied to the respective original loss to generate a respective weighted loss, which compensates for concept drift.

Abstract: Disclosed are amino-substituted heteroaromatic compounds such as 4-amino-quinazolines, pharmaceutically acceptable salts of the compounds, and pharmaceutical compositions thereof. Also disclosed are methods of treating or preventing cancer using the amino-substituted heteroaromatic compounds, pharmaceutically acceptable salts of the compounds, and pharmaceutical compositions thereof.

Abstract: A system for training and deploying an artificial conversational entity using an artificial intelligence (AI) based communications system is disclosed. The system may comprise a memory storing machine readable instructions. The system may also comprise a processor to execute the machine readable instructions to receive a request via an artificial conversational entity. The processor may also transmit a response to the request based on a dialog tree generated from at least a model-based action generator and a memory-based action generator. The processor may further provide a training option to a user in the event the response is suboptimal. The processor may additionally receive a selection from the user via the training option. The selection may be associated with an optimal response.

Abstract: Methods, systems, apparatuses, and computer program products are provided for extracting an entity value from a sentence. An embedding set that may include one or more sentence embeddings is generated for at least part of a first sentence that is tagged to associate a first named entity in the sentence with an entity type. A plurality of candidate embeddings is also generated for at least part of a second sentence. The one or more sentence embeddings in the embedding set may be compared with each of the plurality of candidate embeddings, and a match score may be assigned to each comparison to generate a match score set. A particular match score of the match score set may be identified that exceeds a similarity threshold, and an entity value of the entity type may be extracted from the second sentence associated with the identified match score.

Abstract: A system for training and deploying an artificial conversational entity using an artificial intelligence (AI) based communications system is disclosed. The system may comprise a memory storing machine readable instructions. The system may also comprise a processor to execute the machine readable instructions to receive a request via an artificial conversational entity. The processor may also transmit a response to the request based on a dialog tree generated from at least a model-based action generator and a memory-based action generator. The processor may further provide a training option to a user in the event the response is suboptimal. The processor may additionally receive a selection from the user via the training option. The selection may be associated with an optimal response.

Abstract: A method for measuring the displacement of a planar motor rotor. The measuring method comprises: four magnetic induction intensity sensors are distributed on the planar motor rotor; sampled signals of the four distributed sensors are processed to obtain signals Bsx, Bcx, Bsy and Bcy and magnetic field reference values Bksx, Bkcx, Bksy and Bkcy; and X-direction displacement and Y-direction displacement can be measured respectively according to inequalities (I) and (II) by judgments, wherein ?x and ?y are X-direction displacement resolution and Y-direction displacement resolution respectively, and BM is the magnetic induction intensity amplitude of the magnetic field of said planar motor. The method provided by the invention is simple in calculation, can avoid calculation of a transcendental function and solve the quadrant judgment problem, is favorable to real-time high-speed operation and has a high engineering value.

Abstract: A method for measuring the displacement of a planar motor rotor. The measuring method comprises: four magnetic induction intensity sensors are distributed on the planar motor rotor; sampled signals of the four distributed sensors are processed to obtain signals Bsx, Bcx, Bsy and Bcy and magnetic field reference values Bksx, Bkcx, Bksy and Bkcy; and X-direction displacement and Y-direction displacement can be measured respectively according to inequalities (I) and (II) by judgments, wherein ?x and ?y are X-direction displacement resolution and Y-direction displacement resolution respectively, and BM is the magnetic induction intensity amplitude of the magnetic field of said planar motor. The method provided by the invention is simple in calculation, can avoid calculation of a transcendental function and solve the quadrant judgment problem, is favorable to real-time high-speed operation and has a high engineering value.