Abstract:
A design application generates a spectrum of design options that meet certain design criteria. Each design option may potentially be composed of a different type of material. The design application filters the spectrum of design options for presentation in a graphical user interface (GUI). The GUI illustrates different design options based on material of composition within a parallel axis plot that includes separate axes for different material attributes. The GUI also displays envelopes of design options for each different material or material type, where each envelope has a different color, pattern, opacity, or other visual attribute. A GUI engine dynamically updates the GUI to reflect constraints and other design criteria applied to the spectrum of design options.
Abstract:
A method includes providing a wearable device compatible with and worn by an animal, the wearable device including a processing engine, a plurality of sensors, and a communication interface to a remotely located base station. The method includes monitoring an environment around the wearable device as the animal traverses a space and collecting information based on data generated by the plurality of sensors. The method also includes analyzing the data generated by the plurality of sensors and inferring activities associated with a human in proximity to the animal, wherein inferring activities includes determining a current location of the human based on data generated by one or more of the sensors, and determining activities of the human over a period of time based on data generated by the one or more sensors.
Abstract:
One embodiment of the present invention sets forth a technique for generating design variations. The technique involves identifying a first design variable and a second design variable associated with a first design. The technique further involves generating a first plurality of design variations based on the first design. Each design variation is generated by varying at least one of the first design variable and the second design variable. Finally, the technique involves causing the first plurality of design variations to be displayed to a user.
Abstract:
In various embodiments, a stylization application generates designs that reflect stylistic preferences. In operation, the stylization application computes characterization information based on a first design and a trained machine-learning model that maps one or more designs to characterization information associated with one or more styles. The stylization application then computes a style score based on the characterization information and a target style that is included in the one or more styles. Subsequently, the stylization application generates a second design based on the style score, where the second design is more representative of the target style than the first design. Advantageously, because the stylization application can substantially increase the number of designs that can be generated based on the target style in a given amount of time, relative to more manual prior art techniques, the overall quality of the design ultimately selected for production can be improved.
Abstract:
An iterative design environment performs an iterative design process of a product by implementing usage feedback of the product when utilized under real-world conditions. Sensors are installed on the physical product and collect data about the behavior of the product under real-world conditions. The sensor data comprise usage feedback implemented to inform and produce a design problem statement and one or more design solutions. The sensor data is received by a problem statement engine to produce a problem statement based, at least in part, on the sensor data. A design engine then produces one or more design solutions for the problem statement and one of the design solutions is fabricated to produce a new physical product. Sensors are then installed onto the new physical product and the iterative design process may be performed again. The iterative design process may be performed multiple times until a satisfactory physical product is achieved.
Abstract:
A design application includes a design engine and a tracking engine. The design engine allows end-users to create and modify a design space. The design space includes a spectrum of possible design options, as well as other information related to the process of creating designs. When changes are applied to the design space, the design engine transmits event data to the tracking engine that reflects those changes. The tracking engine, based on the event data, updates a design space timeline. The design space timeline illustrates the evolution of the design space over time.
Abstract:
An iterative design environment performs an iterative design process of a product by implementing usage feedback of the product when utilized under real-world conditions. Sensors are installed on the physical product and collect data about the behavior of the product under real-world conditions. The sensor data comprise usage feedback implemented to inform and produce a design problem statement and one or more design solutions. The sensor data is received by a problem statement engine to produce a problem statement based, at least in part, on the sensor data. A design engine then produces one or more design solutions for the problem statement and one of the design solutions is fabricated to produce a new physical product. Sensors are then installed onto the new physical product and the iterative design process may be performed again. The iterative design process may be performed multiple times until a satisfactory physical product is achieved.
Abstract:
A design application allows an end-user to define an engineering problem, and then synthesizes a spectrum of design options that solve the engineering problem. The design application then generates various tools to allow the end-user to explore that spectrum of design options. The design application allows the end-user to compare various attributes of each design option, and to filter the spectrum of design options based on those attributes. In response to end-user selections of certain design options, the design application identifies other similar design options, and then displays these design options to the end-user.
Abstract:
A design application generates a spectrum of design options that meet certain design criteria. Each design option may potentially be composed of a different type of material. The design application filters the spectrum of design options for presentation in a graphical user interface (GUI). The GUI illustrates different design options based on material of composition within a parallel axis plot that includes separate axes for different material attributes. The GUI also displays envelopes of design options for each different material or material type, where each envelope has a different color, pattern, opacity, or other visual attribute. A GUI engine dynamically updates the GUI to reflect constraints and other design criteria applied to the spectrum of design options.
Abstract:
A design application is configured to determine design problem geometry and design criteria associated with a design problem to be solved. Based on this information, the design application identifies one or more design approaches to creating a custom material having specific material attributes needed to solve the design problem. The design application then executes the design approaches to create material designs that reflect one or more custom materials. With these designs as input, a manufacturing machine may then construct physical instances of those custom materials. A given custom material may have a unique combination of material attributes potentially not found among existing materials. Additionally, a design fabricated from a custom material may better satisfy the design criteria than a design fabricated from a known material.