Abstract: In one example embodiment, data is received at a node of a network. The data includes encrypted data segments containing data portions and error correction information. The encrypted data segments are decrypted to produce the data portions and the error correction information. Error correction is performed on the data portions using the error correction information. Corrupt data is determined based on the error correction indicating uncorrectable data.

Abstract: Techniques are disclosed for training and/or utilizing an automatic post-editing model in correcting translation error(s) introduced by a neural machine translation model. The automatic post-editing model can be trained using automatically generated training instances. A training instance is automatically generated by processing text in a first language using a neural machine translation model to generate text in a second language. The text in the second language is processed using a neural machine translation model to generate training text in the first language. A training instance can include the text in the first language as well as the training text in the first language.

Abstract: Techniques are disclosed for training and/or utilizing an alignments and language model (“ALM”) in automatically determining an ALM score corresponding with natural language text generated using a natural language generation model. The natural language text generated using the natural language generation model can be based on a set of structured data. Additionally or alternatively, the ALM can include a fluency model portion and a semantics model portion. The fluency model portion can be used in determining the fluency and/or grammar of the text. The semantics model portion be used in evaluating the content of the natural language text with respect to the content of the structured data.

Abstract: Techniques are disclosed for training and/or utilizing an automatic post-editing model in correcting translation error(s) introduced by a neural machine translation model. The automatic post-editing model can be trained using automatically generated training instances. A training instance is automatically generated by processing text in a first language using a neural machine translation model to generate text in a second language. The text in the second language is processed using a neural machine translation model to generate training text in the first language. A training instance can include the text in the first language as well as the training text in the first language.

Abstract: Disclosed are a test instrument and testing methods for audibly providing signal metrics (such as signal strength and/or signal quality) of fifth-generation network (5G) beams to assist installation of 5G Customer Premises Equipment (CPE) antenna at a premises. A test instrument may obtain signal metrics and provide audio output based on the signal metrics at various locations of the premises. The audio output may be transmitted to a headphone device worn by a user or a speaker. In this manner, the user may select an appropriate location on the premises at which to install the 5G CPE antenna via audible queues that are based on the measured signal metric at a given location. The test instrument may provide fine-tuning capabilities by also audibly providing directional information that indicates where the 5G CPE antenna should be pointed or moved to align the 5G CPE antenna to a 5G beam.

Abstract: Disclosed are a test instrument and testing methods for audibly providing signal metrics (such as signal strength and/or signal quality) of fifth-generation network (5G) beams to assist installation of 5G Customer Premises Equipment (CPE) antenna at a premises. A test instrument may obtain signal metrics and provide audio output based on the signal metrics at various locations of the premises. The audio output may be transmitted to a headphone device worn by a user. In this manner, the user may select an appropriate location on the premises at which to install the 5G CPE antenna via audible queues that are based on the measured signal metric at a given location. The test instrument may provide fine-tuning capabilities by also audibly providing directional information that indicates where the 5G CPE antenna should be pointed or moved to align the 5G CPE antenna to a 5G beam.

Abstract: A system and computer-implemented method for routing an encrypted packet through a cloud enforcement network based on a metadata tag. The cloud enforcement network applies policy and routing attributions or tags outside of the encrypted packet payload in such a way as to not require an inner packet to first be decrypted. Traffic prioritization, data protection, and per application policies are achieved by using such metadata tags for internode routing without the need for DPI or decryption. Furthermore, the metadata itself can also be signed or encrypted depending on the provenance of the data. As such, applying meta-tagging external to an encrypted packet, the payload would not be needed to be decrypted during transit of the packet to express end-to-end policy and routing decisions.

Abstract: Disclosed are a test instrument and testing methods for audibly providing signal metrics (such as signal strength and/or signal quality) of fifth-generation network (5G) beams to assist installation of 5G Customer Premises Equipment (CPE) antenna at a premises. A test instrument may obtain signal metrics and provide audio output based on the signal metrics at various locations of the premises. The audio output may be transmitted to a headphone device worn by a user. In this manner, the user may select an appropriate location on the premises at which to install the 5G CPE antenna via audible queues that are based on the measured signal metric at a given location. The test instrument may provide fine-tuning capabilities by also audibly providing directional information that indicates where the 5G CPE antenna should be pointed or moved to align the 5G CPE antenna to a 5G beam.

Abstract: Presented herein are methodologies for establishing secure communications in a post-quantum computer context. The methodology includes receiving, from a first communications device, at a second communications device, a secret seed value, or otherwise obtaining the secret seed value; initializing a session key service with the secret seed value; receiving, from the first communications device, at the second communications device, a pre-shared key identifier; querying the session key service for a pre-shared key corresponding the pre-shared key identifier; receiving, from the session key service, the pre-shared key; deriving a session key based, at least in part, on the pre-shared key; receiving from the first communications device, at the second communications device, data encrypted with the session key; and decrypting the data at the second communications device using the session key.

Abstract: Techniques are disclosed for training and/or utilizing an alignments and language model (“ALM”) in automatically determining an ALM score corresponding with natural language text generated using a natural language generation model. The natural language text generated using the natural language generation model can be based on a set of structured data. Additionally or alternatively, the ALM can include a fluency model portion and a semantics model portion. The fluency model portion can be used in determining the fluency and/or grammar of the text. The semantics model portion be used in evaluating the content of the natural language text with respect to the content of the structured data.

Abstract: Techniques are disclosed for training and/or utilizing an automatic post-editing model in correcting translation error(s) introduced by a neural machine translation model. The automatic post-editing model can be trained using automatically generated training instances. A training instance is automatically generated by processing text in a first language using a neural machine translation model to generate text in a second language. The text in the second language is processed using a neural machine translation model to generate training text in the first language. A training instance can include the text in the first language as well as the training text in the first language.

Abstract: Techniques are disclosed for training and/or utilizing an automatic post-editing model in correcting translation error(s) introduced by a neural machine translation model. The automatic post-editing model can be trained using automatically generated training instances. A training instance is automatically generated by processing text in a first language using a neural machine translation model to generate text in a second language. The text in the second language is processed using a neural machine translation model to generate training text in the first language. A training instance can include the text in the first language as well as the training text in the first language.

Abstract: Presented herein are methodologies for establishing secure communications in a post-quantum computer context. The methodology includes receiving, from a first communications device, at a second communications device, a secret seed value, or otherwise obtaining the secret seed value; initializing a session key service with the secret seed value; receiving, from the first communications device, at the second communications device, a pre-shared key identifier; querying the session key service for a pre-shared key corresponding the pre-shared key identifier; receiving, from the session key service, the pre-shared key; deriving a session key based, at least in part, on the pre-shared key; receiving from the first communications device, at the second communications device, data encrypted with the session key; and decrypting the data at the second communications device using the session key.

Abstract: A method divides data traffic into multiple optical transport units formatted according to an optical transport network (OTN) standard. The multiple optical transport units include a master optical network unit and one or more slave optical network units. Each optical network unit includes overhead and a payload. The overhead includes used overhead specifically defined in the OTN standard and unused overhead not specifically defined in the OTN standard. The method encrypts each optical network unit with a respective one of multiple encryption keys, defines security control parameters identifying the multiple encryption keys, and inserts the security control parameters into the unused overhead of a first slave optical network unit among the one or more slave optical network units. The method transmits the optical network units in encrypted form.

Abstract: Disclosed are a test instrument and testing methods for audibly providing signal metrics (such as signal strength and/or signal quality) of fifth-generation network (5G) beams to assist installation of 5G Customer Premises Equipment (CPE) antenna at a premises. A test instrument may obtain signal metrics and provide audio output based on the signal metrics at various locations of the premises. The audio output may be transmitted to a headphone device worn by a user. In this manner, the user may select an appropriate location on the premises at which to install the 5G CPE antenna via audible queues that are based on the measured signal metric at a given location. The test instrument may provide fine-tuning capabilities by also audibly providing directional information that indicates where the 5G CPE antenna should be pointed or moved to align the 5G CPE antenna to a 5G beam.

Abstract: Techniques are disclosed for training and/or utilizing an automatic post-editing model in correcting translation error(s) introduced by a neural machine translation model. The automatic post-editing model can be trained using automatically generated training instances. A training instance is automatically generated by processing text in a first language using a neural machine translation model to generate text in a second language. The text in the second language is processed using a neural machine translation model to generate training text in the first language. A training instance can include the text in the first language as well as the training text in the first language.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for providing a natural language based program interface to software applications. One of the methods includes, obtaining, via a natural language front end, a natural language query or a natural language update statement issued by a software application; converting the natural language query or natural language update statement into structured operations to be performed on APIs of a knowledge base; performing the structured operations on the APIs to produce a natural language output statement; and providing, via a natural language output interface, the natural language output statement to the software application. The knowledge base stores entity information according to a data schema and has structured APIs for use by software applications to query the knowledge base; the software applications are limited to communicating with the knowledge base through the interfaces provided by the natural language front end.

Abstract: An application service system receives, from a merchant service system, an application program code comprising identifying information. The identifying information is extracted and the application is distributed for operation on a user device. A user interacts with the application, creating an access request that is transmitted to the application service system along with the extracted identifying information. The application service system transmits an access token to the user device comprising the received identifying information. The user device transmits the access token with a service request to the application service system. The application service system compares the identifying information from the access token to the identifying information extracted from the application program code received from the merchant services system. If the identifying information matches, the service request is processed.

Abstract: An application service system receives, from a merchant service system, an application program code comprising identifying information. The identifying information is extracted and the application is distributed for operation on a user device. A user interacts with the application, creating an access request that is transmitted to the application service system along with the extracted identifying information. The application service system transmits an access token to the user device comprising the received identifying information. The user device transmits the access token with a service request to the application service system. The application service system compares the identifying information from the access token to the identifying information extracted from the application program code received from the merchant services system. If the identifying information matches, the service request is processed.

Abstract: A method divides data traffic into multiple optical transport units formatted according to an optical transport network (OTN) standard. The multiple optical transport units include a master optical network unit and one or more slave optical network units. Each optical network unit includes overhead and a payload. The overhead includes used overhead specifically defined in the OTN standard and unused overhead not specifically defined in the OTN standard. The method encrypts each optical network unit with a respective one of multiple encryption keys, defines security control parameters identifying the multiple encryption keys, and inserts the security control parameters into the unused overhead of a first slave optical network unit among the one or more slave optical network units. The method transmits the optical network units in encrypted form.