Abstract: A method, an apparatus, and a computer program product for scaling of subscriber capacity in a cloud native radio access network (RAN). A processing capacity being assigned to one or more containers in a plurality of containers of a cloud native radio access network for providing communication to at least one user equipment in a plurality of user equipments is determined. The determined processing capacity is compared to at least one predetermined threshold in a plurality of predetermined thresholds. Based on the comparing a determination is made whether to change an assignment of the processing capacity.

Abstract: A brain-inspired spoken language understanding system, comprises: a first module that facilitates the conversion of a voice input into phoneme sequences; a buffer module that facilitates the storing of the phoneme sequences until they are clustered into a first storage as one or more meaningful thought representations; a second module that facilitates the monitoring of the reasoning, disambiguation, and prioritization of the system, in addition to controlling the system; a seventh module and an eighth module that facilitate the capturing of at least one non-verbal signal from a conversation, and create at least one time-synchronized non-verbal object, with the help of a third knowledge base; a third module that facilitates the conversion of the phoneme sequences and at least one time-synchronized non-verbal object into sequences of phonetics-based words; a fourth module that facilitates the conversion of the phonetics-based words into sequences of thought representations, with the help of a first knowledge ba

Abstract: A system to convert phonemes into phonetics-based words that is implemented in one or more computing systems, in association with a system that provides required inputs is disclosed. Said system comprises a phoneme enhancer, a phoneme sequence buffer, a phoneme sequence to phonetics-based word converter that comprises a sliding window phoneme sequence matcher, a phoneme sequence to phonetics-based word custom data memory, a most frequent phonetics-based word predictive memory, a phoneme similarity matrix, and a phonetics-based word output unit.

Abstract: An example pull-print server may include a processor and a memory coupled to the processor. The memory may include a receiving unit to receive a print job including variable print data, a reference identifier, and a passcode specific to the print job. Further, the memory may include a mapping unit to identify a template corresponding to the reference identifier and store mapping information that maps the variable print data and the passcode to the identified template. Furthermore, the memory may include a controller to receive, via a printer, a pull print request including the passcode. In response to receiving the pull print request, the controller may retrieve the variable print data and the stored template corresponding to the passcode using the mapping information. Further, the controller may generate print content by overlaying the variable print data onto the identified template and transmit the print content to the printer.

Abstract: A system to convert sequences of words, along with concurrent non-verbal data, into thought representations, said system being used in association with a language understanding system, where words to thought transformation is needed, is disclosed. Said system comprises: an entity look-up subsystem that comprises: a pre-processing unit, a word database, and a cache; a controller or thought representation formation and reasoning unit; a multi-word entities buffer; an entity knowledge base; a predictive word meaning memory; and an output thought representation unit.

Abstract: A system to convert sequences of human thought representations into coherent stories, in association with a language understanding system is disclosed. Said system comprises: an entity dereferencing and enrichment module, an anomaly detecting unit that comprises: a context anomaly module, and a meaning anomaly and reinforcement module; an inter thought representation reasoning and transformation unit; an entity knowledge base; a thought representation knowledge base; and an output thought representation cloud. The system takes sequences of thought representations as input and tries to make sense out of them. The system is used in association with any type of language understanding system for creating meaning out of the sequence of thoughts.

Abstract: A system to convert phonemes into phonetics-based words that is implemented in one or more computing systems, in association with a system that provides required inputs is disclosed. Said system comprises a phoneme enhancer, a phoneme sequence buffer, a phoneme sequence to phonetics-based word converter that comprises a sliding window phoneme sequence matcher, a phoneme sequence to phonetics-based word custom data memory, a most frequent phonetics-based word predictive memory, a phoneme similarity matrix, and a phonetics-based word output unit.

Abstract: A system to convert sequences of words, along with concurrent non-verbal data, into thought representations, said system being used in association with a language understanding system, where words to thought transformation is needed, is disclosed. Said system comprises: an entity look-up subsystem that comprises: a pre-processing unit, a word database, and a cache; a controller or thought representation formation and reasoning unit; a multi-word entities buffer; an entity knowledge base; a predictive word meaning memory; and an output thought representation unit.

Abstract: A brain-inspired spoken language understanding system, comprises: a first module that facilitates the conversion of a voice input into phoneme sequences; a buffer module that facilitates the storing of the phoneme sequences until they are clustered into a first storage as one or more meaningful thought representations; a second module that facilitates the monitoring of the reasoning, disambiguation, and prioritization of the system, in addition to controlling the system; a seventh module and an eighth module that facilitate the capturing of at least one non-verbal signal from a conversation, and create at least one time-synchronized non-verbal object, with the help of a third knowledge base; a third module that facilitates the conversion of the phoneme sequences and at least one time-synchronized non-verbal object into sequences of phonetics-based words; a fourth module that facilitates the conversion of the phonetics-based words into sequences of thought representations, with the help of a first knowledge ba

Abstract: A system to convert sequences of human thought representations into coherent stories, in association with a language understanding system is disclosed. Said system comprises: an entity dereferencing and enrichment module, an anomaly detecting unit that comprises: a context anomaly module, and a meaning anomaly and reinforcement module; an inter thought representation reasoning and transformation unit; an entity knowledge base; a thought representation knowledge base; and an output thought representation cloud. The system takes sequences of thought representations as input and tries to make sense out of them. The system is used in association with any type of language understanding system for creating meaning out of the sequence of thoughts.

Abstract: One embodiment of the invention sets forth a mechanism for controlling the initialization order of an iGPU and a dGPU in a hybrid graphics processing environment to ensure that the iGPU is recognized by the operating system as the primary GPU. When the device initialization request associated with the dGPU is received, the interface module determines whether the iGPU has already been initialized. If the iGPU has already been initialized, then the interface module transmits the device initialization request to the dGPU driver for dGPU initialization. However, if the iGPU flag indicates that the iGPU has not yet been initialized, then the interface module terminates the device initialization request and transmits an initialization failure notification to the operating system. In such a manner, the dGPU is initialized only after the iGPU has previously been initialized, thereby ensuring that the iGPU is recognized by the operating system as the primary GPU.

Abstract: A method for destructively reading out data from a stolen or lost mobile phone. A special switch off feature disables all the services associated with the mobile phone, except for a messaging service and the ability to destructively read out data. A user can retrieve the data stored in the mobile phone from a remote location. Once the data is retrieved, all the data in the mobile phone is erased.

Abstract: A method for destructively reading out data from a stolen or lost mobile phone. A special switch off feature disables all the services associated with the mobile phone, except for a messaging service and the ability to destructively read out data. A user can retrieve the data stored in the mobile phone from a remote location. Once the data is retrieved, all the data in the mobile phone is erased.