Abstract: A method and system for engramic indexing of information technology (IT) infrastructure. Specifically, the method and system disclosed herein enable the efficient access, search, and/or management of enterprise-scale IT infrastructure and topologies using semantic context and natural language processing. That is, query context may be optimized using mapped semantics based on organizational constructs and machine learning, thereby reducing query overhead, increasing response performance, and improving contextual display capabilities in mass-scale environments.

Abstract: Generating function placement recommendations and deploying functions in a manner that accounts for sustainability concerns. Function placements decisions are made that account for sustainability values. When a resource request is received, sustainability values are identified. The resources needed to fulfill the resource request are identified based on the sustainability values and available resources. The identified resources are potential placements for deploying the functions. A specific placement is selected, and the function is deployed to the corresponding resources.

Abstract: Selecting a review panel of dissimilar peers. An asset is reviewed from an ethical perspective by a panel of reviewers. The panel of reviewers includes members that are selected based on their dissimilarity to creators of the asset. Selecting dissimilar members for the panel of reviewers allows bias in the asset to be identified and remedied. A portion of the panel of reviewers may be selected randomly to further improve the effectiveness of the panel of reviewers in reviewing the asset for ethicalness.

Abstract: One example method includes extracting content metadata from data, storing the content metadata in a data catalogue, receiving at the data catalogue, from a user, a request to access the data, transmitting, by the data catalogue to a security service provider, an access request that includes the extracted content metadata and metadata relating to the access request, accessing, by the security service provider, identity metadata concerning an identity of the user, and a data access policy, and transmitting, by the security service provider to the data catalogue, a decision as to whether or not access can be granted to the data, and the decision is based on the data access policy, the identity metadata, and the metadata in the access request.

Abstract: Techniques for authenticating a digital asset represented by an NFT that is stored in a blockchain are disclosed. An NFT that has been minted for an asset is identified. The NFT was minted by generating metadata for the asset and by generating an original hash of the asset. The NFT is stored in a blockchain, and the metadata is stored in a centralized repository. The original hash is stored in either the repository or the blockchain. A potential transfer of the NFT is triggered. Triggering the potential transfer includes downloading, from the centralized repository, a local version of the asset. A local hash of the local version of the asset is generated. The local hash is compared against the original hash. If the two hashes are the same, then the transfer is permitted; otherwise, the transfer is not permitted.

Abstract: A method for managing data includes obtaining, by a data migration manager, a notification of an event occurrence from an external event source, wherein the event occurrence is predicted to take place in a geographical location, performing a threat assessment on the event occurrence to generate an impact prediction for a local data system located in the geographical location, making a first determination that the impact prediction exceeds an impact threshold for a first application executing in the local data system, performing, in response to the first determination, a location assessment to identify a migration destination for first application data stored in the local data system, and initiating a first data migration of the first application data to the migration destination.

Abstract: One example method includes building a computing asset that includes a component that has been verified as being ethically sourced, generating a bill of material for the computing asset that identifies the component, adding the bill of material to a data confidence fabric that includes the computing asset as a node, registering the component and the bill of material in the data confidence fabric, and associating a digital fair trade/ethics signature with the component, wherein the digital fair trade/ethics signature is stored in the data confidence fabric in association with the component.

Abstract: Exercising user data rights is disclosed. A rights architecture is provided that can be integrated with a data management system. When data is ingested, the associated data rights are also ingested or applied by default. When data is requested, the request is intercepted, the request is intercepted or processed to determine applicable data rights, which are then enforced as the request is handled in the data management system. The data rights may accompany the data in a header when sold or transferred such that the data rights accompany the data and can be enforced.

Abstract: A method for managing computing resources includes obtaining, by a resource use manager, a physical asset request from a client, in response to the physical asset request: initiating allocation of a landing area device to the client based on the physical asset request, determining a physical asset to be provided to the client, sending, to a manufacturer, a physical asset preparation request, obtaining a confirmation of deployment of the physical asset from the client, performing a restoration on the physical asset using a most recent landing area incremental backup, and after the initiating the restoration, initiating a transfer of operation from the landing area device to the physical asset.

Abstract: Codified graphical user experience design includes finite state machine (FSM) metadata, logic describing the graphical aspects of the user experience design, and logic describing states of the user experience design and transitions between states. A GUI to API/CLI translator uses the codified graphical user experience design to automatically create corresponding CLI packages and API playbooks. The translator walks the FSM. For each visited state, a state based functional intermediate code package is created including the one or more API call basic blocks associated with API calls to be implemented at that state, and parameter definitions for each API call at that state. For each state transition, conditional intermediate code is created and attached to the API call basic blocks. The state based functional intermediate code packages with attached conditional intermediate code are used to create a CLI package or an API playbook based on the codified graphical user experience design.

Abstract: One example method is performed in connection with a data confidence fabric. This method includes generating information about data as the data transits a data confidence fabric, ingesting the information, mapping the ingested information to a timeline, evaluating the timeline, based on the evaluating, generating a recommendation for an action concerning the data, and implementing the action in the data confidence fabric. In this method, the evaluating includes determining if any unexpected time gaps occurred as the data transited the data confidence fabric.

Abstract: A data confidence fabric for generating data confidence scores for a build pipeline is disclosed. Confidence scores are generated for data or jobs in a build pipeline. The scores may be combined into a final confidence score that reflects a confidence in the artifact generated by the pipeline and in the pipeline. A user or infrastructure may or may not perform the artifact based on the associated confidence score.

Abstract: Generating policy-based confidence scores for data is disclosed. Data captured by a data confidence fabric is annotated when the data is created, mutated, transited or otherwise handled in the data confidence fabric. The annotations are weighted by a policy to generate policy-based confidence scores. The policy-based confidence scores are used in determining whether the data is sufficiently trusted for use by an application.

Abstract: One example method includes annotating data with confidence information as the data transits a data confidence fabric, after the data has transited a portion of the data confidence fabric, using the confidence information to generate a data confidence score, assigning the data confidence score to the data, and adjusting the data confidence score. In some cases, the data confidence score may be automatically adjusted downward over time and/or may be adjusted based on input concerning the data.

Abstract: Recompiling code based on sustainability. Code is recompiled in a manner that accounts for sustainability values. When a deployment request is received, sustainability values are identified. The resources needed to fulfill the deployment request are identified based on the sustainability values and available resources. Once the resources that are likely to best meet the sustainability values are identified, the code is recompiled accordingly.

Abstract: A system, method, and computer-readable medium are disclosed for performing a data center monitoring and management operation. The data center monitoring and management operation includes: enabling a customer to identify a customer metric, the customer metric representing an aspect of a data center infrastructure configuration of importance to the customer; analyzing the customer metric, the analyzing comprising at least one of prioritizing and weighting the customer metric; and, generating a recommendation for a data center infrastructure configuration based upon the analyzing.

Abstract: One example method includes formulating a hypothesis for development of computing model, annotating the hypothesis with ethics metadata, storing the hypothesis and the ethics metadata, in association with each other, in a ledger, performing ‘n’ phases of a development lifecycle for the computing model, annotating each of the ‘n’ phases with ethics metadata specific to the phase, updating the ledger to include the ‘n’ phases and the ethics metadata respectively associated with each of the ‘n’ phases, and calculating an ethics confidence score for the computing model.

Abstract: Ethics-based decision making is disclosed. Outputs of artificial intelligence processes are tagged or labeled with ethics scores. When decisions are made using the outputs, the ethics tag inform the decision engine regarding the ethics of the outputs. The decisions can, based on the ethics scores, proceed or be delayed until additional input is received. In one example, the selection of an asset may depend the output ethics score.

Abstract: A PCIe resource management system includes a PCIe resource registration subsystem and a PCIe resource monitoring subsystem. Assets register to use PCIe resources of other assets and to allow other assets to use their PCIe resources. Assets specify which types of PCIe resources it can borrow, when it can borrow those PCIe resources, and a logical group of other assets from which the asset can borrow the PCIe resources. Assets also specify which types of PCIe resources it will lend, when it will lend those PCIe resources, and a logical group of other assets to which the asset will lend the PCIe resources. The PCIe resource registration subsystem maintains a PCIe resource registration datastore maintaining PCIe borrow and lending rules associated with assets in logical groups of assets. PCIe resources are shared between assets in the logical groups as needed, as determined by the PCIe resource monitoring subsystem.

Abstract: One example method includes for each pillar in a group of AI ethics pillars, storing, in a datastore, context data concerning the AI ethics pillar, and the context data is determined using context rules. The method further includes storing, in the datastore, the context rules as minimum context requirements, and receiving, by the datastore, a request from a user to register an asset in the datastore. When user-supplied context information for the asset meets ethical requirements specified by the context rules, registering the asset in the datastore, and ensuring that an assessment mechanism is able to access, and assess, the context data for each AI ethics pillar.