Systems and methods for adjusting a facility configuration based on detected conditions are disclosed. An example system may include an energy and compute facility having a compute resource, and an energy source or an energy utilization requirement. The system may also include a controller having a facility description circuit to interpret detected conditions, and a facility configuration circuit to operate an adaptive learning system. The adaptive learning system is configured to adjust a facility configuration based on the detected conditions, wherein adjusting the facility configuration includes adjusting a utilization of the compute resource and at least one additional facility resource.

A campaign profile specifies products and/or content items associated with a campaign. A target group selection engine applies an affinity attribute model to user information of a user. The affinity attribute model is used to determine the user's affinity towards (a) product attributes of the products associated with the campaign and/or (b) content attributes of the content items associated with the campaign. The affinity attribute model may be generated using machine learning. A user interface accepts target user tuning parameters that specify weights to be applied to the affinity attributes determined by the affinity attribute model. Based at least on applying the weights to the affinity attributes, an inclusion score and/or exclusion score for the user is determined. The user is included in a target group, for engaging with the campaign, based on the inclusion score and/or exclusion score.

Transaction-enabled methods for providing provable access to a distributed ledger with a tokenized instruction set for semiconductor fabrication processes are described. A method may include accessing a distributed ledger including an instruction set for a semiconductor fabrication process and tokenizing the instruction set. The method may further include interpreting an instruction set access request and, in response to the access request, providing a provable access to the instruction set. The method may further include providing commands to a production tool of the semiconductor fabrication process in response to the instruction set access request, and recording the transaction on the distributed ledger.

Transaction-enabled methods for providing provable access to a distributed ledger with a tokenized instruction set for polymer production processes are described. A method may include accessing a distributed ledger comprising an instruction set for a polymer production process and tokenizing the instruction set. The method may further include interpreting an instruction set access request and providing provable access to the instruction set. The method may further include providing commands to a production tool of the polymer production process and recording the transaction on the distributed ledger.

Systems and methods are provided for generating a keyword sequence from an input query. A first text sequence corresponding to an input query may be received and encoded into a source sequence representation using an encoder of a machine learning model. A keyword sentence may then be generated from the source sequence representation using a decoder of the machine learning model. The decoder may generate a modified generation score for a plurality of prediction tokens, wherein the modified generation score is based on the respective prediction token generation score and a maximum generation score for a suffix of each prediction token. The decoder may then select the prediction token of the plurality of prediction tokens based on the modified generation score, and add the selected prediction token to the previously decoded partial hypothesis provided by the decoder.

Classification of the user of an attention application is moved from the cloud, where the classification is performed by advertisers based on trackers that follow a user, to the attention application itself. A user of the attention application controls inputs to the classification model and can exclude sensitive privacy information from inclusion in the classification model. The classification model is applied locally at the attention application to a catalog of advertisements and without revealing to trackers and advertisers whether attention was paid to particular ads. An analytics provider may have increased access to attention applications and can form ad campaigns and provide performance data thereon to advertisers without infringing attention user privacy. The system directs value away from trackers and advertisers and to attention application users and publishers.

A processor receives requests for content items and identifies a first subset of machine learning (ML) models that satisfy a reliability criterion and a second subset of ML models that fail to satisfy the reliability criterion, wherein each ML model is associated with a respective content template and is trained to output a probability that a target associated with an input set of characteristics would perform a target action responsive to being presented with a content item generated based on the respective associated content template. The processing logic assigns each request to either a first group or a second group based on a ratio of a number of ML models in the first subset to a number of ML models in the second subset. For each request in the first group, the processor generates a content item based on a content template associated with the first subset.

This document describes the autonomous collection, generation, distribution, and management of online web content. The devices, systems, and methods described herein can be used to collect and generate online web content and communications in an automatic and autonomous manner. Specifically, the disclosed methods, devices, and systems may be employed to produce one or more communications and/or advertising campaigns, as well as for monitoring, managing, defining the efficiency, effectiveness, and workability of the campaign with respect to generating predicted user engagements, thereby accurately determining the cost benefits of the communication campaign. The system may track, evaluate, and provide analytic results that may then be used to better guide the system parameters for customizing autonomous communications directed one or more characteristics of a defined target audience.

Aspects of the subject disclosure may include, for example, a method in which a processing system obtains physical and social environmental data for a communication device user, and provides content for presentation at the device. First reaction data, obtained via sensors associated with the user, indicate the user's reaction to presentation of the content; the data is analyzed to determine user affinity for the content in a context of the physical and social environments. The content is modified during the presentation; second reaction data is obtained and analyzed to determine a second user affinity for the modified content. If the affinity is enhanced, the modified content is sent to other users' equipment via a social network. Affinity responses regarding the modified content are analyzed, and a set of users is identified as an affinity group; additional content is transmitted to equipment of the affinity group. Other embodiments are disclosed.

The present disclosure describes transaction-enabling systems and methods. A system may include a smart contract wrapper configured to access a distributed ledger including a plurality of intellectual property (IP) licensing terms corresponding to a plurality of IP assets, wherein the plurality of IP assets include an aggregate stack of IP, interpret an IP description value and an IP addition request, and, in response to the IP addition request and the IP description value, to add an IP asset to the aggregate stack of IP.