Abstract: Systems and methods for autonomous vehicle (AV) simulation and code build scheduling are provided. A method includes receiving a first task specification for a first task associated with a first AV simulation and/or a first AV code build, receiving, a second task specification for a second task associated with a second AV simulation and/or a second AV code build, and executing a portion of the first task concurrently with a portion of the second task based on the portion of the first task and the portion of the second task have different resource requirements. The portion of the first task is associated with one of an AV asset download, an AV code execution, or an AV artifact upload. The portion of the second task is associated with a different one of the AV asset download, the AV code execution, or the AV artifact upload.

Abstract: A system may include a content repository that stores multi-modal content comprising text, visual content, and/or audio content. The system may include a processor programmed to: access a prompt comprising a text query, a visual query comprising text that describes a visual to be found, and/or an audio query comprising text that describes audio to be found, execute a language model based on the prompt to identify content from the content repository, receive, from the language model, a request for a callback function that seeks additional information to satisfy the multi-modal query, execute the callback function to obtain the additional information and provide the additional information to the language model in response to the request for the callback function, re-execute the language model based on the multi-modal query and the additional information, obtain, from the language model, content responsive to the prompt based on the additional information.

Abstract: A system may, in a first pass: divide content to be summarized into a plurality of chunks and, for each chunk: execute a language model with the chunk and an instruction to summarize the chunk, generate, based on the executed language model, a summary of the chunk. In a subsequent pass, the system may: generate a plurality of groups of summaries, each group of summaries from among the plurality of groups of summaries comprising two or more summaries, each summary corresponding to a respective chunk, for each group of summaries from among the plurality of groups: execute a language model with the group of summaries and an instruction to summarize the group of summaries, generate, based on the executed language model on the group of summaries, a group summary. The system may iteratively repeat the subsequent pass for group summaries until a summary of the content is reached.

Abstract: A system may, in a first pass: divide content to be summarized into a plurality of chunks and, for each chunk: execute a language model with the chunk and an instruction to summarize the chunk, generate, based on the executed language model, a summary of the chunk. In a subsequent pass, the system may: generate a plurality of groups of summaries, each group of summaries from among the plurality of groups of summaries comprising two or more summaries, each summary corresponding to a respective chunk, for each group of summaries from among the plurality of groups: execute a language model with the group of summaries and an instruction to summarize the group of summaries, generate, based on the executed language model on the group of summaries, a group summary. The system may iteratively repeat the subsequent pass for group summaries until a summary of the content is reached.

Abstract: A system may access content comprising text content, visual content, and/or audio content. The system may perform, based on a harmonization model and/or consistency model, a harmonization check and/or a consistency check on the content. The system may recognize, based on the harmonization check and/or the consistency check, a conflict to be corrected. The system may identify a property of the content that should be changed based on the recognized conflict. The system may generate a corrective action based on the property of the content that should be changed.

Abstract: A system may, in a first pass: divide content to be summarized into a plurality of chunks and, for each chunk: execute a language model with the chunk and an instruction to summarize the chunk, generate, based on the executed language model, a summary of the chunk. In a subsequent pass, the system may: generate a plurality of groups of summaries, each group of summaries from among the plurality of groups of summaries comprising two or more summaries, each summary corresponding to a respective chunk, for each group of summaries from among the plurality of groups: execute a language model with the group of summaries and an instruction to summarize the group of summaries, generate, based on the executed language model on the group of summaries, a group summary. The system may iteratively repeat the subsequent pass for group summaries until a summary of the content is reached.

Abstract: A system may include a content repository that stores multi-modal content comprising text, visual content, and/or audio content. The system may access a prompt comprising a text query that describes text to be found, a visual query comprising text that describes a visual to be found, and/or an audio query comprising text that describes audio to be found, execute a language model based on the prompt to identify content from the content repository, receive, from the language model, a request for a callback function that seeks additional information to satisfy the multi-modal query, execute the callback function to obtain the additional information and provide the additional information to the language model in response to the request for the callback function, re-execute the language model based on the multi-modal query and the additional information, and obtain, from the language model, content responsive to the prompt based on the additional information.

Abstract: A system may include a content repository that stores multi-modal content comprising text, visual content, and/or audio content. The system may include a processor programmed to: access a prompt comprising a text query, a visual query comprising text that describes a visual to be found, and/or an audio query comprising text that describes audio to be found, execute a language model based on the prompt to identify content from the content repository, receive, from the language model, a request for a callback function that seeks additional information to satisfy the multi-modal query, execute the callback function to obtain the additional information and provide the additional information to the language model in response to the request for the callback function, re-execute the language model based on the multi-modal query and the additional information, obtain, from the language model, content responsive to the prompt based on the additional information.

Abstract: Systems and methods for autonomous vehicle (AV) simulation and code build scheduling are provided. A method includes receiving a first task specification for a first task associated with a first AV simulation and/or a first AV code build, receiving, a second task specification for a second task associated with a second AV simulation and/or a second AV code build, and executing a portion of the first task concurrently with a portion of the second task based on the portion of the first task and the portion of the second task have different resource requirements. The portion of the first task is associated with one of an AV asset download, an AV code execution, or an AV artifact upload. The portion of the second task is associated with a different one of the AV asset download, the AV code execution, or the AV artifact upload.

Abstract: Systems and methods for autonomous vehicle (AV) simulation and code build scheduling are provided. A method includes receiving a first task specification for a first task associated with a first AV simulation and/or a first AV code build, receiving, a second task specification for a second task associated with a second AV simulation and/or a second AV code build, and executing a portion of the first task concurrently with a portion of the second task based on the portion of the first task and the portion of the second task have different resource requirements. The portion of the first task is associated with one of an AV asset download, an AV code execution, or an AV artifact upload. The portion of the second task is associated with a different one of the AV asset download, the AV code execution, or the AV artifact upload.

Abstract: An electronic device that provides a user interface that allows individuals to listen to an alarm is described. In particular, an environmental monitoring device may monitor an environmental condition in an external environment that includes the environmental monitoring device. This environmental monitoring device may provide to a computer a notification based on the environmental condition and an audio recording of sounds associated with the environmental condition. Then, using registered-device information specifying the electronic device of an individual, the computer may provide a message with the notification and the audio recording. In response, the electronic device provides the user interface that indicates the notification and/or a location of the environmental monitoring device.

Abstract: Methods and compositions for treating or preventing parenteral nutrition associated liver disease are provided. Methods and compositions for advancing enteral tolerance in subjects receiving enteral nutrition are provided. The methods involve the use of omega-3 fatty acid compositions. In some embodiments the omega-3 fatty acid compositions comprise docosahexanoic acid and eicosapentaenoic acid. In some embodiments the omega-3 fatty acid compositions comprise fish oil. In some embodiments the subjects to be treated are receiving parenteral nutrition. In some embodiments the subjects to be treated are infants having a low birth weight, very low birth weight, extremely low birth weight, a low gestational age, short bowel syndrome, necrotizing entercolitis, or any combination thereof.