Abstract: In an example embodiment, a framework is presented that utilizes a large language model (LLM) to aid in the generation of targeting criteria, namely in generating portions of information that will be used to generate a target audience for a particular media item, based in part on the media item itself. More specifically, the LLM is used to produce a suggestion of one or more facets of a target audience, wherein each facet is a category of information for users within the target audience. The LLM is then also used to produce a plurality of segments within the one or more suggested facets. The produced facets and segments may then be used to create a target audience for the media item, even in a cold-start environment where no information about a desired audience is provided by the entity wishing to distribute the media item.

Abstract: The described technology provides a method including receiving a new feature definition; the new feature definition specifying parameters of the feature, comparing the new feature definition with a plurality of computed feature definitions stored in a feature store, and in response to determining that the new feature definition is at least partially contained in a matched feature definition of the plurality of computed feature definitions, generating an alternative feature definition based on the new feature definition and the matched feature definitions, and selecting an execution alternative from an execution of a PIT join using the alternative feature definition and an execution of a PIT join using the new feature definition.

Abstract: Methods, systems, and apparatus, including computer-readable storage devices, for task scheduling in a multiprocessor system. The processors of a multiprocessor system are partitioned into two groups, a first group of processors that preferentially execute new, short-running tasks and a second group of processors that preferentially execute suspended, long-running tasks. A scheduler of the multiprocessor system maintains queues of new and suspended tasks, suspends tasks, and assigns tasks to the processors according to their group preference. By designating different processors to preferentially execute new, short-running tasks or suspended, long-running tasks, the multiprocessor system may more efficiently manage workloads that contain a mixture of task types.