Abstract: A system for monitoring an environment may include an input device for monitoring and capturing pattern-based states of a model of the environment. The system may also include a thalamobot embodied in at least a first processor in communication with the input device. The thalamobot may include at least one filter for monitoring captured data from the input device and for identifying at least one state change within the captured data. The system may also include at least one critic and/or at least one recognition system. The at least one filter forwards said at least one state change to the critic and/or recognition system. Novel schemes are introduced to allow processors to interconnect themselves into brain-like structures that contemplate both the environment and the model thereof, unifying disparate data into discoveries. The significance of such discoveries is recognized either through neural activation patterns or the topologies of interconnecting neural modules.

Abstract: A system for monitoring an environment may include an input device for monitoring and capturing pattern-based states of a model of the environment. The system may also include a thalamobot embodied in at least a first processor in communication with the input device. The thalamobot may include at least one filter for monitoring captured data from the input device and for identifying at least one state change within the captured data. The system may also include at least one critic and/or at least one recognition system. The at least one filter forwards said at least one state change to the critic and/or recognition system. Novel schemes are introduced to allow processors to interconnect themselves into brain-like structures that contemplate both the environment and the model thereof, unifying disparate data into discoveries. The significance of such discoveries is recognized either through neural activation patterns or the topologies of interconnecting neural modules.

Abstract: A system for monitoring an environment may include an input device for monitoring and capturing pattern-based states of a model of the environment. The system may also include a thalamobot embodied in at least a first processor in communication with the input device. The thalamobot may include at least one filter for monitoring captured data from the input device and for identifying at least one state change within the captured data. The system may also include at least one critic and/or at least one recognition system. The at least one filter forwards said at least one state change to the critic and/or recognition system. Novel schemes are introduced to allow processors to interconnect themselves into brain-like structures that contemplate both the environment and the model thereof, unifying disparate data into discoveries. The significance of such discoveries is recognized either through neural activation patterns or the topologies of interconnecting neural modules.

Abstract: A system for monitoring an environment may include an input device for monitoring and capturing pattern-based states of a model of the environment. The system may also include a 5 thalamobot embodied in at least a first processor, in which the first processor is in communication with the input device. The thalamobot may include at least one filter for monitoring captured data from the input device and for identifying at least one state change within the captured data. The system may also include at least one critic and/or at least one recognition system.

Abstract: A system for monitoring an environment may include an input device for monitoring and capturing pattern-based states of a model of the environment. The system may also include a 5 thalamobot embodied in at least a first processor, in which the first processor is in communication with the input device. The thalamobot may include at least one filter for monitoring captured data from the input device and for identifying at least one state change within the captured data. The system may also include at least one critic and/or at least one recognition system.

Abstract: A discovery system employing a neural network, training within this system, that is stimulated to generate novel output patterns through various forms of perturbation applied to it, a critic neural network likewise capable of training in situ within this system, that learns to associate such novel patterns with their utility or value while triggering reinforcement learning of the more useful or valuable of these patterns within the former net. The device is capable of bootstrapping itself to progressively higher levels of adaptive or creative competence, starting from no learning whatsoever, through cumulative cycles of experimentation and learning. Optional feedback mechanisms between the latter and former self-learning artificial neural networks are used to accelerate the convergence of this system toward useful concepts or plans of action.

Abstract: An artificial neural network-based system and method for determining desired concepts and relationships within a predefined field of endeavor, including a neural network portion, which neural network portion includes an artificial neural network that has been previously trained in accordance with a set of given training exemplars, a monitor portion associated with the neural network portion to observe the data outputs produced by the previously trained artificial neural network, and a perturbation portion for perturbing the neural network portion to effect changes, subject to design constraints of the artificial neural network that remain unperturbed, in the outputs produced by the neural network portion, the perturbation portion operable such that production of an output by the neural network portion thereafter effects a perturbation of the neural network portion by the perturbation portion, the monitor portion responsive to detection of the data outputs being produced by the previously trained neural networ

Abstract: A system and process for readily determining, for a specified knowledge domain in a given field of endeavor, perturbations applicable to an artificial neural network embodying such a specified knowledge domain that will produce a desired output, comprising a first, previously trained, artificial neural network containing training in some problem domain, which neural network is responsive to the presentment of a set of data inputs at the input portion thereof to produce a set of data outputs at the output portion thereof, a monitoring portion which constantly monitors the outputs of the first neural network to identify the desired outputs, and a network perturbation portion for effecting the application of perturbations, either externally or internally, to the first neural network to thereby effect changes in the output thereof.

Abstract: A device for generating useful information employing a first neural network trained to produce input-output maps within a predetermined initial knowledge domain, an apparatus for subjecting the neural network to perturbations which may produce changes in the predetermined knowledge domain, the neural network having an optional output for feeding the outputs of the first neural network to a second neural network that evaluates the outputs based on training within the second neural network. The device may also include a reciprocal feed back connection from the output of the second neural network to the first neural network to further influence and change what takes place in the aforesaid neural network.

Abstract: Constructing and simulating artificial neural networks and components thereof within a spreadsheet environment results in user friendly neural networks which do not require algorithmic based software in order to train or operate. Such neural networks can be easily cascaded to form complex neural networks and neural network systems, including neural networks capable of self-organizing so as to self-train within a spreadsheet, neural networks which train simultaneously within a spreadsheet, and neural networks capable of autonomously moving, monitoring, analyzing, and altering data within a spreadsheet. Neural networks can also be cascaded together in self training neural network form to achieve a device prototyping system.

Abstract: Constructing and simulating artificial neural networks and components thereof within a spreadsheet environment results in user friendly neural networks which do not require algorithmic based software in order to train or operate. Such neural networks can be easily cascaded to form complex neural networks and neural network systems, including neural networks capable of self-organizing so as to self-train within a spreadsheet, neural networks which train simultaneously within a spreadsheet, and neural networks capable of autonomously moving, monitoring, analyzing, and altering data within a spreadsheet. Neural networks can also be cascaded together in self training neural network form to achieve a device prototyping system.

Abstract: Constructing and simulating artificial neural networks and components thereof within a spreadsheet environment results in user friendly neural networks which do not require algorithmic based software in order to train or operate. Such neural networks can be easily cascaded to form complex neural networks and neural network systems, including neural networks capable of self-organizing so as to self-train within a spreadsheet, neural networks which train simultaneously within a spreadsheet, and neural networks capable of autonomously moving, monitoring, analyzing, and altering data within a spreadsheet. Neural networks can also be cascaded together in self training neural network form to achieve a device prototyping system.

Abstract: Constructing and simulating artificial neural networks and components thereof within a spreadsheet environment results in user friendly neural networks which do not require algorithmic based software in order to train or operate. Such neural networks can be easily cascaded to form complex neural networks and neural network systems, including neural networks capable of self-organizing so as to self-train within a spreadsheet, neural networks which train simultaneously within a spreadsheet, and neural networks capable of autonomously moving, monitoring, analyzing, and altering data within a spreadsheet. Neural networks can also be cascaded together in self training neural network form to achieve a device prototyping system.

Abstract: A method and apparatus for coating the surface of a substrate suspends a coating material above the surface of the substrate and irradiates both the coating material and the underlying surface of the substrate. By irradiating both the coating material and the underlying surface of the substrate, a first portion of the coating material is melted to form an at least partially molten droplet of coating material. In addition, at least a second portion of the coating material is ablated to thereby create an ablation plume which propels the at least partially molten droplet of coating material toward the substrate. Thus, a metallic powder can be suspended within a carrier and can be directed along the substrate so as to be irradiated by a pulse of laser energy.

Abstract: A device for simulating human creativity employing a neural network trained to produce input-output maps within some predetermined knowledge domain, an apparatus for subjecting the neural network to perturbations that produce changes in the predetermined knowledge domain, the neural network having an optional output for feeding the outputs of the neural network to a second neural network that evaluates and selects outputs based on training within the second neural network. The device may also include a reciprocal feed back connection from the output of the second neural network to the first neural network to further influence and change what takes place in the aforesaid neural network.

Abstract: A method and apparatus for coating the surface of a substrate suspends a coating material above the surface of the substrate and irradiates both the coating material and the underlying surface of the substrate. By irradiating both the coating material and the underlying surface of the substrate, a first portion of the coating material is melted to form an at least partially molten droplet of coating material. In addition, at least a second portion of the coating material is ablated to thereby create an ablation plume which propels the at least partially molten droplet of coating material toward the substrate. In addition, the portion of the substrate toward which the at least partially molten droplet of coating material is propelled is simultaneously heated, such that the at least partially molten droplet coating material adheres to the heated substrate, thereby coating the surface of the substrate.

Abstract: Laser energy is used to make precursors of crystalline materials, such as diamond, by providing an environment in which optical radiation may be efficiently absorbed to create significant precursor concentrations. In some instances this process is augmented by evaporating or liquefying a sacrifice to induce heterogeneous nucleation. In other cases two chemically and spatially distinct plasmas are juxtaposed to initiate the required chemistry.

Abstract: A method of depositing diamond-like films produces depositing species from a plasma of a hydrocarbon gas precurser. The plasma is generated by a laser pulse which is fired into the gas and is absorbed in an initiater mixed with the gas. The resulting detonation produces a plasma of ions, radicals, molecular fragments and electrons which is propelled by the detonation pressure wave to a substrate and deposited thereon.