Abstract: Examples disclosed herein relate to processing health information of a computing device according to a deep learning model to determine whether an anomaly has occurred. Multiple computing devices can be part of a system. One of the computing devices includes a host processing element, a management controller separate from the host processing element, and a deep learning model that includes parameters that are trained to identify anomalistic behavior for the computing device. The management controller can receive health information from multiple components of the computing device and process the health information according to the deep learning model to determine whether an anomaly occurred.

Abstract: In some examples, a management controller includes a communication interface to communicate with a computing device, where the management controller is separate from a processor of the computing device. The management controller includes a management processor to receive, from the computing device, a first hash value that is based on a first hash function applied on an input value and a salt, generate a second hash value based on applying a second hash function on the first hash value and a pepper, and send the second hash value to the computing device.

Abstract: In some examples, a management controller includes a communication interface to communicate with a computing device, where the management controller is separate from a processor of the computing device. The management controller includes a management processor to perform a validation of program codes of virtual entities of the computing device, and in response to the validation of the program codes, unlock access of information in an information store to allow access of the information by the computing device, wherein the information is for use by the virtual entities of the computing device, and wherein the management processor is to block access of the information in the information store prior to the validation.

Abstract: In some examples, a management controller includes a communication interface to communicate with a computing device, where the management controller is separate from a processor of the computing device. The management controller includes a management processor to receive, from the computing device, a first hash value that is based on a first hash function applied on an input value and a salt, generate a second hash value based on applying a second hash function on the first hash value and a pepper, and send the second hash value to the computing device.

Abstract: In some examples, a management controller includes a communication interface to communicate with a computing device, where the management controller is separate from a processor of the computing device. The management controller includes a management processor to perform a validation of program codes of virtual entities of the computing device, and in response to the validation of the program codes, unlock access of information in an information store to allow access of the information by the computing device, wherein the information is for use by the virtual entities of the computing device, and wherein the management processor is to block access of the information in the information store prior to the validation.

Abstract: Examples disclosed herein relate to processing health information of a computing device according to a deep learning model to determine whether an anomaly has occurred. Multiple computing devices can be part of a system. One of the computing devices includes a host processing element, a management controller separate from the host processing element, and a deep learning model that includes parameters that are trained to identify anomalistic behavior for the computing device. The management controller can receive health information from multiple components of the computing device and process the health information according to the deep learning model to determine whether an anomaly occurred.

Abstract: A pick-and-place system for plant embryos includes a tray for receiving a suspension of plant embryos. The tray is movable to repeatedly reposition the plant embryos. An identification system is proximate the tray for identifying a target plant embryo amongst the plant embryos in the suspension. The identification system is configured to identify the target plant embryo while the tray is moving. A robotic arm is proximate the tray and is in communication with the identification system. The robotic arm is actuatable to pick the target plant embryo out of the suspension while the tray is moving, and deposit the target plant embryo at a target location.

Abstract: Examples disclosed herein relate to using a baseboard management controller (BMC) to convey data between two networks. The BMC has a network interface. Before the BMC connects to a first network, it performs a security assessment including a check on a storage. Then the BMC receives and stores, on the storage, data from the first network. The network interface is then disconnected from the first network and connected to a second network. The data is conveyed to another device using the second network.

Abstract: Examples disclosed herein relate to generating a shared secret. A processor and a memory. A register in a computing device that is set to a first value. Reading the register when the value of the register has changed to a second value. The register changes to a third value. A shared secret is generated based on the second value.

Abstract: Provided are methods of inserting seedlings into soil plugs. The method includes: a) automatically identifying a target seedling located in a pick-up area using seedling detection apparatus; b) pick-up up the target seedling with an automated seedling handling apparatus; c) transporting the target seedling to an insertion area; d) providing a first soil plug in the insertion area to receive the target seedling, the first soil plug having a first plug end, a second plug end longitudinally spaced apart from the first plug end and a longitudinal slit extending from the first plug end toward the second plug end; e) spreading the slit in the first soil plug; f) inserting a root portion of the seedling into the slit while a stem portion of the seedling is positioned outside the first soil plug; and g) stripping the target seedling from the handling apparatus whereby the seedling remains received within the slit in the first soil plug.

Abstract: A pick-and-place system for plant embryos includes a tray for receiving a suspension of plant embryos. The tray is movable to repeatedly reposition the plant embryos. An identification system is proximate the tray for identifying a target plant embryo amongst the plant embryos in the suspension. The identification system is configured to identify the target plant embryo while the tray is moving. A robotic arm is proximate the tray and is in communication with the identification system. The robotic arm is actuatable to pick the target plant embryo out of the suspension while the tray is moving, and deposit the target plant embryo at a target location.

Abstract: For each pairwise permutation comprising a first and second node of a plurality of nodes in a peer to peer network, the second node may be a peer node of the first node if a distance between the first and second nodes is closer than a distance between the first node and any other node that has a same range as a range between the first and second nodes. The instructions to perform and distribute a task may be sent from a root node of the plurality of nodes to each of its peer nodes. For each of the nodes other than the root node, the instructions may be received by each of the peer nodes of the each node if the range between the each node and the each peer node is less than the range between the each node and the node from which the instructions were received.

Abstract: For each pairwise permutation comprising a first node and a second node of a plurality of nodes in a peer to peer network, a range between the first and second nodes may be determined based on a bitwise comparison between one or more bits of a first identifier of the first node and one or more bits of a second identifier of the second node, and a distance between the first and second nodes may be determined. For each pairwise permutation the second node may be added to a list of one or more peer nodes of the first node if the distance between the first and second nodes is closer than the distance between the first node and any other node of the plurality of nodes that has the same range as the range between the first and second nodes.

Abstract: A respective identifier of each node of a plurality of nodes in a plurality of subnetworks of a peer to peer network may be generated. The identifier may include a node address identifying the node and a subnetwork address identifying a subnetwork in the plurality of subnetworks in which the node is located. For each pairwise permutation of the plurality of nodes comprising a first node and second node, a range and a distance between the first and second nodes may be based on their identifiers. For each pairwise permutation, the second node may be added to a list of one or more peer nodes of the first node if the distance between the first and second nodes is closer than the distance between the first node and any other node of the plurality of nodes that has the same range as the range between the first and second nodes.

Abstract: A server system may include a baseboard management controller and a host system. The baseboard management controller may obtain an identification of a peer system over a management network connection. The baseboard management controller may provide the identification of the peer system to the host system. The host system may use the identification of the peer system to obtain a virtual machine image.