Abstract: Techniques described herein relate to systems, methods, and non-transitory computer readable mediums for performing workloads on hardware configurations. The method includes determining compliant hardware configurations of the data cluster using workload features associated with the workload, hardware specification information associated with hardware of data nodes of a data cluster, and a first machine learning model; generating performance predictions associated with the compliant hardware configurations using the workload features, a portion of the hardware specification information associated with the compliant hardware configurations, and a second machine learning model; and generating a recommendation using the performance predictions, and the recommendation specifies a hardware configuration of the compliant hardware configurations. The workload is performed using the recommendation.

Abstract: The method for producing medium viscosity carboxymethyl cellulose from date palm fronds includes drying date palm fronds, grinding the dried date palm fronds to a powder, mixing the powder with an alkaline solution to a provide a slurry, isolating a cellulose extract from the slurry, drying the cellulose extract, grinding the dried cellulose extract to a powder, adding isopropanol to the powder to provide a mixture, adding an alkaline solution to the mixture to provide an alkaline mixture, and adding a mixture of monochloroacetic acid and trichloroacetic acid to the alkaline mixture to provide carboxymethyl cellulose (CMC) as an alkaline salt thereof. The CMC can be used for cultivating desert land while saving water.

Abstract: An information handling system for servicing search requests for information stored in data assets includes storage for storing a graph database based on at least one data catalog for the data assets. The information handling system also includes a processor that obtains, from a requestor, a search request of the search requests, the search request specifies a keyword search term; obtains a first identifier of a data asset of the data assets using the graph database and the keyword search term; and provides the first identifier as a supplemental result for the search request.

Abstract: A method for performing workloads is performed by a recommendation engine.

Abstract: Described herein is a mechanism for improving the accuracy of a language model interpreting short input utterances. A language model operates in a stateless manner, only ascertaining the intents and/or entities associated with a presented input utterance. To increase the accuracy, two language understanding models are trained. One is trained using only input utterances. The second is trained using input utterance-prior dialog context pairs. The prior dialog context is previous intents and/or entities already determined from the utterances in prior turns of the dialog. When input is received, the language understanding model decides whether the input comprises only an utterance or an utterance and prior dialog context. The appropriate trained machine learning model is selected and the intents and/or entities associated with the input determined by the selected machine learning model.

Abstract: Described herein is a mechanism for improving the accuracy of a language model interpreting short input utterances. A language model operates in a stateless manner, only ascertaining the intents and/or entities associated with a presented input utterance. To increase the accuracy, two language understanding models are trained. One is trained using only input utterances. The second is trained using input utterance-prior dialog context pairs. The prior dialog context is previous intents and/or entities already determined from the utterances in prior turns of the dialog. When input is received, the language understanding model decides whether the input comprises only an utterance or an utterance and prior dialog context. The appropriate trained machine learning model is selected and the intents and/or entities associated with the input determined by the selected machine learning model.

Abstract: Methods of printing metallic objects include providing parameters of an object for printing, and controlling a deposition of a fluid metallic material to form the object. At least an outer surface region of the fluid metallic material is converted to a solid region after deposition.