Abstract: An embodiment senses a raw data sequence by a central processing unit, responsive to the raw data sequence, computes by the central processing unit a transfer data size of the raw data sequence based at least in part on the comparison of a data size of the raw data sequence to a memory size of a graphics processing unit. The embodiment transfers by the central processing unit of the raw data sequence to the graphics processing unit based on the transfer data size. The embodiment trains a foundation model on the raw data sequence where a sliding window algorithm is executed on the raw data sequence by the graphics processing unit, where generating a window of the sliding window algorithm is based on a memory pointer to the raw data sequence.

Abstract: A system for homomorphically generating rotation keys for use in homomorphic computation in association with a client, and a server coupled to the client machine over a network. Client-side code executes in the client to derive a set of Learning With Errors (LWE) ciphertexts from a secret key polynomial, the secret key polynomial having a set of coefficients. Each LWE ciphertext is derived from a coefficient of the secret key polynomial and having a single coefficient. The client-side code transmits the set of LWE ciphertexts to the server. Server-side code receives the set of LWE ciphertexts and processes them into a ring variant (R-LWE) ciphertext homomorphically to generate the one or more rotation keys. The R-LWE ciphertext encrypts a polynomial having the set of coefficients of the secret key polynomial; a given rotation key corresponds to rotated coefficients of that polynomial. The generated rotation keys are useful for FHE computation.

Abstract: An embodiment maps identifying information of a remote registry into a database within a local inventory at a local registry hub. An embodiment selects at least one remote registry from an index maintained in the local inventory in accordance with a policy received at a scheduler from an external client of the local registry hub. An embodiment selects a locally stored image in accordance with a policy received from an external client of the local registry hub. An embodiment uploads replicas of the selected image via one or more registry agents, each registry agent transmitting to its corresponding remote registry, transmitting constituent layers of the replica across multiple remote registries simultaneously such that a subset of the layers constituting the image are uploaded to each remote registry. An embodiment stores metadata for the uploaded image in a cache within a local metadata store.

Abstract: An embodiment establishes a neural network that comprises a plurality of layers. The embodiment receives a plurality of input data sequences into a layer of the neural network, the plurality of input data sequences comprises a first input data sequence and a second input data sequence. The embodiment superposes the first input data sequence and the second input data sequence, thereby creating a superposed embedding. The embodiment transforms the superposed embedding by applying a function to the superposed embedding, thereby creating a transformed superposed embedding. The embodiment infers a first output data element corresponding to the first input data sequence and a second output data element corresponding to the second input data sequence via application of an unbinding operation on the transformed superposed embedding.

Abstract: An embodiment generates, using a trained document embedding model, a plurality of table embeddings, each table embedding in the plurality of table embeddings representing a table in a dataset. An embodiment generates, using the trained document embedding model, a query embedding, the query embedding representing a natural language query regarding the dataset. An embodiment identifies a set of responsive tables, the set of responsive tables comprising a first table in the dataset, the first table in the dataset represented by a first table embedding, the first table embedding and the query embedding having a similarity score above a similarity score threshold.

Abstract: An embodiment senses a survey sequence, responsive to the sensed survey sequence, inputs the sensed survey sequence into a prediction model. The embodiment comprises a prediction model wherein the prediction model comprises training a hidden Markov model on a previously administered survey with a corresponding response status as a hidden status and a corresponding linguistic metric as an observation. The embodiment computes a probability of a response status of the sensed survey sequence as an output of the prediction model based at least in part on the previously administered survey.

Abstract: An embodiment generates a compute resource allocation limit parameter for controlling a total amount of compute resources consumed by a set of virtual machines over a combination of a source host environment and a target host environment. The embodiment adjusts an allocation of compute resources for the set of virtual machines according to the compute resource allocation limit parameter. The embodiment migrates the set of virtual machines from the source host environment to the target host environment.

Abstract: An embodiment senses an object from an object screening system, and responsive to the sensed object, generates a context information based on the sensed object. The embodiment generates a cultural classification by a Culturally Aware Objects Model based in part on the context information wherein the Culturally Aware Objects Model is trained on a cultural factor of an object. The embodiment generates a moderated context information by a Sensitive Information Moderation Model based in part on the cultural classification and the context information wherein the Sensitive Information Moderation Model is trained on a privacy parameter. The embodiment also computes a recommendation by a Recommendation Component based in part on the moderated context information wherein the object screening system is updated with the recommendation.

Abstract: A method for facilitating storage system upgrades is disclosed. In one embodiment, such a method includes identifying host systems configured to access a storage system. The method identifies a current host code level for each host system. The method determines a latest storage code level for the storage system that is supported by each host system at its current host code level. The method reports the latest storage code level to a user to enable the user to upgrade the storage system to the latest storage code level without upgrading any of the current code levels of the host systems. In certain embodiments, reporting the latest storage code level further includes reporting an overlapping range of storage code levels that are supported by each host system at its current code level. A corresponding system and computer program product are also disclosed.

Abstract: An embodiment senses an interaction among a software agent and a plurality of humans, responsive to the sensed interaction, computes a mood pattern in a Mood Pattern Observation Component based on the sensed interaction. The embodiment computes a prevalent mood pattern in a Mood Pattern Grouping Component based on the mood pattern. The embodiment decides by an Orchestration of Agent Interactions Component based on the prevalent mood pattern to adapt a response of the software agent to influence at least one of the plurality of humans towards the prevalent mood pattern, the deciding further comprises training a Text Generation Component to generate a text sequence based on the response wherein the software agent emits the text sequence and the sensed interaction among the software agent and the plurality of humans is updated with the text sequence.

Abstract: An embodiment identifies, by a post-modeling category merging engine, a plurality of valid pairs associated with a categorical predictor, the plurality of valid pairs representing potential mergers of categories associated with a categorical predictor of a predictive model. The embodiment tests, by the post-modeling category merging engine, a merge strategy for the plurality of valid pairs to determine a merger that minimizes a loss in accuracy of the predictive model. The embodiment merges, by the post-modeling category merging engine based on the testing, a valid pair in the plurality of valid pairs to form a hybrid category.

Abstract: A technique for multi-factor authenticating a user on a first device, the user having an associated second device configured with an authenticator application, and wherein the authenticator application is offline. In this scenario, and responsive to receipt of a request to access a protected resource, a push notification is sent to the authenticator. While the push notification remains pending, a delivery status of the push notification is requested. Upon determining based on the delivery status that the authenticator is offline, an alert is provided to the user, preferably in a user interface of the first device, and indicates the delivery status of the push notification. The alert also includes an instruction to the user to attempt an authentication through an alternative communication channel. The user is then permitted to access the protected resource only upon completing the authentication through the alternative communication channel.

Abstract: An embodiment initiates, by a sensitive stored procedure identification engine, a periodic discovery process on a database server to identify a stored procedure and assign a first sensitivity score to the stored procedure based on a searching of a sensitive data pattern in the stored procedure. The embodiment assigns in real-time, by the sensitive stored procedure identification engine responsive to receiving a stored procedure call by a client over a network, a second sensitivity score to the stored procedure based on a searching of a sensitive data pattern in a response to the stored procedure call. The embodiment compares, by the sensitive stored procedure identification engine, the first sensitivity score and the second sensitivity score. The embodiment determines, by the sensitive stored procedure identification engine based on the comparison, to allow a response to the stored procedure call to the client.

Abstract: An embodiment expands a polynomial into a plurality of products, each product in the plurality of products comprising a scaling coefficient multiplied by a sub-polynomial, each sub-polynomial comprising a sum of a plurality of addends, wherein a degree of each sub-polynomial is equal to a grouping parameter. An embodiment computes a plurality of ciphertext products, each ciphertext product equal to a ciphertext multiplied by itself a number of times, the number of times ranging from two to the grouping parameter. An embodiment computes, using the ciphertext and the plurality of ciphertext products in place of a variable of the polynomial, each of the plurality of products. An embodiment multiplies the plurality of products together.

Abstract: An embodiment establishes an interaction database based at least in part on interaction data received from a browser. The embodiment monitors the browser for one or more actions and stores the one or more actions detected as interaction data on the interaction database. The embodiment constructs an asynchronous user interface based at least in part on the interaction data stored on the interaction database, wherein the asynchronous user interface comprises a set of selection options. The embodiment receives, via the asynchronous user interface, a selection of a selection option of the set of selection options. The embodiment performs a responsive action upon having received the selection of the selection option of the set of selection options.

Abstract: A computer-implemented method, according to one embodiment, includes: receiving copies of notes that were originally recorded by participants, the notes corresponding to a source document. Note fragments in the received copies of notes are identified and one or more machine learning models are used to compare the identified note fragments to pages and paragraphs in the source document that the respective note fragments are located in. Based at least in part on the comparison, the identified note fragments are merged with a copy of the source document to form a pseudo-source document. Furthermore, the pseudo-source document is output.

Abstract: An embodiment establishes a unified conferencing protocol (UCP). The embodiment establishes a UCP mediator wherein the UCP mediator is configured to establish a connection between two or more video conferencing platforms. The embodiment receives, via the UCP mediator, a request to communicate with a first video conferencing platform from a second video conferencing platform. The embodiment approves, via the UCP mediator, the request to communicate with the first video conferencing platform from the second video conferencing platform. The embodiment establishes a connection between the first video conferencing platform and the second video conferencing platform.

Abstract: An embodiment performs, by an attribute value substitution engine, key-value extraction on infrastructure as code. The embodiment assigns, by the attribute value substitution engine, an attribute in a plurality of attributes to a value in the extracted key-value. The embodiment computes, by the attribute value substitution engine, a plurality of similarities between the plurality of attributes and a cloud resource. The embodiment groups, based on the plurality of similarities, the plurality of attributes into a group of attributes. The embodiment substitutes, by the attribute value substitution engine, the attribute with another attribute, the attribute and the another attribute belonging to the group of attributes.

Abstract: Various embodiments are provided herein for collaborating in a shared Command Line Interface (CLI) session in a computing environment having one or more processor devices. A unique CLI session, shared between multiple users and platforms using at least one of a Cloud UI dashboard and CLI tool, is instantiated by a session owner. By virtue of permissions established by the shared, unique CLI session, execution of at least one CLI command is managed in the CLI session by at least one of the session owner and authorized ones of those of the multiple users.

Abstract: An embodiment adjusts a position of a piezoelectric generator within a hollow cylindrical tube, the position adjusted to cause the tube to vibrate at a first resonant frequency in response to an acoustic stimulus, the piezoelectric generator configured to close one end of the tube, the tube further comprising an open end disposed at an opposite end of the tube from the piezoelectric generator. An embodiment adjusts, by applying a voltage to the piezoelectric generator, a resonant frequency of the piezoelectric generator, the adjusting changing the resonant frequency of the piezoelectric generator to the first resonant frequency.

Abstract: Various embodiments are provided herein for making ergonomic keybinding adjustments based on user behavioral inputs in a computing environment having one or more processor devices. One or more metrics of a user input are measured. If the one or more metrics are determined to exceed a predetermined threshold, one or more of the user behavioral inputs associated with the one or more metrics are identified to be provided to a keybinding adjustment o the one or more behavioral inputs.

Abstract: An embodiment intercepts a notification including a portion of natural language text and a Uniform Resource Locator (URL). An embodiment identifies, using a natural language understanding model, a topic of the notification. An embodiment tags, using a content summarization model, a content located at the URL, the tagging comprising assigning a set of content tags to the content, the set of content tags comprising a predefined tag representing the content. An embodiment calculates a relevancy score scoring a comparison between the set of content tags and a set of user tags, the set of user tags comprising a predefined tag representing a profile of an intended recipient of the notification. An embodiment generates, responsive to the relevancy score being above a threshold, using the topic and the set of content tags, a customized notification, the customized notification replacing the notification.

Abstract: An embodiment collects a first set of patient data and a first set of treatment data associated with a patient population treated with spinal cord stimulation. The embodiment clusters the patient population into a plurality of cohorts. The embodiment generates a plurality of states using a second set of patient data associated with a cohort in the plurality of cohorts. The embodiment generates a plurality of actions using a second set of treatment data associated with the cohort. The embodiment determines, based on the plurality of actions, a plurality of probabilities associated with a transition from a first state to a second state in the plurality of states. The embodiment generates, based on the plurality of probabilities, a stimulator action policy for a patient in the cohort.

Abstract: A feature request and a price corresponding to the feature request are received. The feature request is validated, the validating determining an implementation cost of the feature request. Using a return on investment of the feature request, the feature request is selected for implementation, the return on investment computed using the implementation cost and the price. Implementation of the selected feature request is caused.

Abstract: A method for detecting content generated by artificial intelligence is disclosed. In one embodiment, such a method includes monitoring interaction between a user and a generative AI model. The method intercepts a response returned from the generative AI model to the user and embeds, within the response prior to its return to the user, codes that are invisible to the user when viewing the response. In certain embodiments, these codes are embedded within the response in a particular invisible code insertion pattern to indicate that the response was generated by the generative AI model. The method returns the response to the user for viewing. A third party may utilize the embedded codes to determine whether the response was generated by the generative AI model. A corresponding system and computer program product are also disclosed herein.

Abstract: An embodiment collects a first set of patient data and a first set of treatment data associated with a patient population treated with neuromodulation. The embodiment clusters the patient population into a plurality of cohorts. The embodiment generates a plurality of states using a second set of patient data associated with a cohort in the plurality of cohorts. The embodiment generates a plurality of actions using a second set of treatment data associated with the cohort. The embodiment determines, based on the plurality of actions, a plurality of probabilities associated with a transition from a first state to a second state in the plurality of states. The embodiment generates, based on the plurality of probabilities, a neuromodulator action policy for a patient in the cohort.

Abstract: The illustrative embodiments provide for adaptation of reference architecture documents across clouds. An embodiment includes loading a reference architecture document. The embodiment also includes populating a knowledge repository corpus where the knowledge repository corpus includes data from information technology (IT) products, cloud services, and integrations stored with associated metadata about functionalities. The IT products, the cloud services, and the integrations are stored with metadata. The embodiment also includes classifying, using an incident analysis module, the service incidents based on the reference architecture document. The embodiment also includes detecting flaws in the reference architecture document based on the classified service incidents. The embodiment also includes creating a weighted graph of the cloud services. The embodiment also includes traversing the weighted graph and creating an adapted reference architecture based on the traversed weighted graph.

Abstract: An embodiment includes loading a plurality of data sources where each data source is comprised of content of interest. The embodiment also includes scanning the plurality of data sources for the content of interest. The embodiment also includes detecting the content of interest from scanning the plurality of data sources where detecting is based on a key word search. The embodiment also includes organizing the content of interest as data elements, based on a topic modeling technique. The embodiment also includes distributing the data elements into a plurality of topics based on a Latent Dirichlet Allocation technique. The embodiment also includes merging the data elements within each of the topics. The embodiment also includes generating a document with the topics into one or more filtered lists, based on the key word search.

Abstract: An embodiment includes sending a first drone, including a carbon dioxide sensor, into an area. The embodiment includes detecting a level of carbon dioxide in the area and generating a map including a position and level of carbon dioxide. The embodiment includes calculating a carbon dioxide hotspot above a threshold. The embodiment includes creating a plan to diffuse the carbon dioxide hotspot in a time limit by calculating an amount of a drones to send to the area based on a needed amount of humidity and light to diffuse the carbon dioxide hotspot in the time limit. The amount of humidity and light are calculated using an optimizer module. The embodiment includes sending the calculated amount of drones to the area of the carbon dioxide hotspot. The embodiment includes diffusing the carbon dioxide hotspot, sampling the area, and updating the map with new levels of carbon dioxide.

Abstract: A method for intelligently distributing messages across multiple devices and associated chat applications is disclosed. In one embodiment, such a method includes registering multiple devices and associated chat applications to receive intelligent distribution of messages. The method monitors, using an agent, a message copied from a first device of the multiple devices to a clipboard. The method automatically analyzes content of the message to determine which other devices and associated chat applications of the plurality are eligible to receive the message. The message is then distributed to other devices and associated chat applications that are deemed eligible to receive the message. In certain embodiments, the message originates from a first chat application of a first type and the message is distributed to a second chat application of a second type that is different from the first type. A corresponding system and computer program product are also disclosed.

Abstract: An embodiment selects, from a set of candidate locations within a power generation site, a first power generation location. An embodiment causes generation of electricity, by a first power generation unit, at the first power generation location. An embodiment forecasts, during the generation of electricity, a future power generation status of the first power generation unit at the first power generation location. An embodiment causes relocating, responsive to the future power generation status, of the first power generation unit to a second power generation location, the relocating altering the future power generation status.

Abstract: The illustrative embodiments provide for supervision and reaction-aware adaptive intervention in an area. An embodiment includes detecting a behavior of a non-compliant entity over a threshold in a supervised area using one or more sensors. The threshold is determined by processing an input of the sensor using a first processing algorithm. The embodiment includes deploying a response into the supervised area. The response is based on input from the sensor. The embodiment includes identifying, using a second processing algorithm, a reaction of the non-compliant entity to the initial response. The embodiment includes determining fulfilment of a target state of the non-compliant entity using a third algorithm. The target state may include a change in behavior of the non-compliant entity. Other embodiments of this aspect include corresponding computer systems, apparatus, and computer programs recorded on one or more computer storage devices, each configured to perform the actions of the embodiment.

Abstract: An embodiment establishes a potential energy source database based at least in part on sensor data received from a satellite, wherein the potential energy source database comprises coordinate data representative of a plurality of potential energy source locations. The embodiment instructs a robot to travel to a potential energy source location of the plurality of potential energy source locations. The embodiment scans the potential energy source location for a potential energy source. The embodiment detects the potential energy source in the potential energy source location. The embodiment evaluates whether the potential energy source meets a predetermined suitability criteria. The embodiment classifies the potential energy source as a suitable energy source. The embodiment instructs the robot to insert a pair of electrodes into the suitable energy source to generate an electrical current to charge a battery of the robot.

Abstract: Computer-implemented peer-engagement through graphical definition of contact-generating events in a virtualized metaverse includes visually presenting to a user, on an interactive interface, a multi-dimensional scene of a virtual environment. The user provides input to graphically define one or more contact-generating events within the multi-dimensional scene, which events are detected as being triggered by one or more virtualized avatars in the multi-dimensional scene. According to the triggering of the events and other predefined contact-engaging criteria, a contact-initiating prompt may be transmitted to a peer user associated with the one or more virtualized avatars in the multi-dimensional scene.

Abstract: A method for improving the accuracy of speech recognition is disclosed. In one embodiment, such a method receives speech input from a user. The method further receives background inputs describing at least one of a webpage and an application from which the speech input was received. The method determines a language associated with the speech input and determines a weight and confidence level for each of the background inputs. A score is calculated for each of the background inputs based on the corresponding weight and confidence level. The method determines textual candidates for output in response to the speech input and ranks the textual candidates using a function that takes into account the scores and/or confidence levels of the background inputs. The textual candidate with the highest ranking may be returned to the user. A corresponding system and computer program product are also disclosed.

Abstract: An embodiment identifies, by a deployment restart engine, a change in a configuration from a first version to a second version. The embodiment determines, by the deployment restart engine, based on the change, whether to restart a deployment associated with the configuration. The embodiment determines, by the deployment restart engine, a deployment dependency associated with the deployment. The embodiment restarts, by the deployment restart engine, responsive to a determination to restart the deployment, based on the deployment dependency, the deployment.

Abstract: The illustrative embodiments provide for improved transcription accuracy using a corpus of reference information. An embodiment includes retrieving, using web-scraping, written content for a topic from a source. The embodiment also includes generating a corpus of reference material for a user using the written content. Generating the corpus of reference may include using a natural language processor. The embodiment also includes analyzing, an audio of a video for spoken content for a reference in the corpus of reference material; Where analyzing may include using a content analyzer. The embodiment also includes transcribing, using a transcription service, spoken content within an audio of the video. The embodiment also includes identifying, using the content analyzer, references in the transcription using a content analyzer. Where the content analyzer compares the spoken content to written content within the corpus.

Abstract: Various embodiments are provided herein for intelligent, self-learning log configuration generation for a corresponding application in a computing environment. A plurality of input data sources are examined to generate a log profile. The log profile is used to generate one or more cognitive log configurations. Those of a plurality of attributes and fields which are determined useful to be logged before a runtime operation are automatically retrieved. The plurality of attributes and fields are continuously optimized during the runtime operation using a feedback mechanism.

Abstract: An embodiment determines, by a collaboration mode transition engine, based on biometrics data and behavioral data, a cognitive level of a user associated with a first collaboration mode in a plurality of collaboration modes. The embodiment determines, by the collaboration mode transition engine, based on collaboration mode usage data associated with the first collaboration mode, a cognitive level threshold of the user for the first collaboration mode. The embodiment selects, by the collaboration mode transition engine, responsive to a determination that the cognitive level exceeds the cognitive level threshold, a second collaboration mode in the plurality of collaboration modes. The embodiment transitions, by the collaboration mode transition engine, to the second collaboration mode.

Abstract: An embodiment establishes an object behavior database, wherein the object behavior database comprises historical object behavior data corresponding to one or more objects. The embodiment scans a surrounding environment for one or more objects. The embodiment detects an object in the surrounding environment. The embodiment retrieves historical object behavior data corresponding to the object detected in the surrounding environment. The embodiment generates media corresponding to the object based in part on the historical behavior data and a current contextual scenario. The embodiment displays the media on a display interface.

Abstract: A system, computer program product, and method are provided for leveraging artificial intelligence (AI) directed at time-series forecasting. An AI transformer model is configured to support multiple modality datasets for predicting a target time-series together with an explanation through one or more neural attention mechanisms. The multiple modality transformer model exploits intermodal interactions from a first dataset having a first modality, in addition to multi-modality interactions between the first dataset and a second dataset having a second modality different from the first modality.

Abstract: An embodiment classifies, by analyzing data generated by a first edge device, the data into a sensitivity category in a set of sensitivity categories. An embodiment classifies, by analyzing the data, the data into a redundancy category in a set of redundancy categories. An embodiment classifies, into a region category in a set of region categories, a region in which the first edge device is located. An embodiment selects, by applying a set of allocation rules, a storage category of the data generated by the first edge device, the selecting resulting in a selected storage category, the set of allocation rules applied according to the sensitivity category, the redundancy category, and the region category. An embodiment causes storage of the data generated by the first edge device in a storage device in the selected storage category.

Abstract: An embodiment performs, by a digital contract modification analysis engine, a modification analysis between a first digital contract and a second digital contract. The embodiment identifies, by the digital contract modification analysis engine, a modification based on the modification analysis. The embodiment determines, by the digital contract modification analysis engine based on user data associated with a user, a risk assessment of the modification.

Abstract: An embodiment identifies a fileset used by an executing application. An embodiment generates, at a first time, a first snapshot of the fileset, the first snapshot comprising a first state of the fileset at the first time and a first indicator corresponding to the first state of the fileset. An embodiment selects, at a recovery time later than the first time, from a sequence of snapshots of the fileset including the first snapshot, a recovery snapshot, the recovery snapshot comprising a recovery indicator, wherein the recovery indicator has a difference from the first indicator that is higher than a threshold value. An embodiment restores, using the recovery snapshot, the fileset to a state other than the first state, the restoring resulting in a restored application.

Abstract: The illustrative embodiments provide for dynamic tuning of pre-initialization environment provisioning and management. An embodiment includes accepting a request from a group of applications to generate a performance-based index table for a workload based on a feature of the applications and generating the performance-based index table. The embodiment includes building a label feature by analyzing a static program feature of the applications and the performance-based index table. The embodiment includes constructing, using clustering algorithms, a model for provisioning a pre-initialization environment using the label features. The embodiment includes loading the applications into a pre-initialization environment. The embodiment includes introducing a selection policy for a switch in the pre-initialization environment in multiple applications to balance usage of a resource.

Abstract: An embodiment aggregates a plurality of global data sources and a plurality of local data sources. The embodiment determines, responsive to a user input on an interactive worksheet, a recommended use case. The embodiment determines, based on the recommended use case and based on the plurality of global data sources and the plurality of local data sources, a recommendation for the at least one local data source in the plurality of local data sources. The embodiment update, responsive to a user acceptance of the recommendation, the interactive worksheet based on the at least one local data source.

Abstract: An embodiment establishes a creative work database based in part on data representative of a plurality of identified creative works and authors associated with the plurality of identified creative works. The embodiment extracts a set of a first set of features from an unidentified creative work. The embodiment compares the first set of features corresponding to the unidentified creative work to a second set of features corresponding to an identified creative work to obtain a similarity score between the unidentified creative work and the identified creative work. The embodiment compares the similarity score to a threshold similarity score, and upon a determination that the similarity score meets the threshold similarity score, identifies a particular author to associate with the unidentified creative work. The embodiment authenticates the new identified creative work. The embodiment updates the creative work database to include the new identified creative work.

Abstract: A method for configuring multiple displays connected to a common computing system is disclosed. In one embodiment, a computing system detects multiple displays connected thereto. The computing system causes at least one of the displays to emit a lighting pattern. This lighting pattern may include, for example, sequentially displaying a selected background color and/or pattern on each of the displays. The computing system detects the lighting pattern using one or more cameras connected to the computing system, such as cameras incorporated into the displays. Using the detected lighting pattern, the computing system infers a physical arrangement of the displays. In certain embodiments, the computing system uses artificial intelligence to infer the physical arrangement. A corresponding system and computer program product are also disclosed herein.

Abstract: An embodiment causes generating, by a trained model, a training prompt response to a training prompt in a set of training prompts. An embodiment trains, using the training prompt and the training prompt response, an attribution model, the training resulting in a trained attribution model. An embodiment attributes, using the trained attribution model and a first prompt response generated by a fine-tuned model in response to a prompt, the fine-tuned model to a foundation model.

Abstract: An embodiment establishes a product design database based at least in part on product design data received from a product image repository, wherein the product design data is representative of a plurality of product designs. The embodiment ranks each product design based on a ranking metric derived from market data corresponding to existing retail products. The embodiment constructs a product design ranking based on a relative ranking between each of the product designs that have been ranked. The embodiment generates a new product design using a machine learning model based on the plurality of product designs and the product design ranking. The embodiment evaluates whether the new product design satisfies a design constraint. The embodiment, upon an evaluation that the new product design satisfies the design constraint, stores the new product design in the product design database. The embodiment displays the new product design via an interface.