Abstract: Provided are computing systems, methods, and platforms that automatically produce production-ready machine learning models and deployment pipelines from minimal input information such as a raw training dataset. In particular, one example computing system can import a training dataset associated with a user. The computing system can execute an origination machine learning pipeline to perform a model architecture search that selects and trains a machine learning model for the training dataset. Execution of the origination machine learning pipeline can also result in generation of a deployment machine learning pipeline configured to enable deployment of the machine learning model (e.g., running the machine learning model to produce inferences and/or optionally other tasks such as re-training and/or re-tuning the model).

Abstract: An integrated high-power gallium arsenide field-effect-transistor device for operation in the gigahertz range comprises a multiple-gate structure. The device, which features gate cross-under fingers, is fabricated in microminiature form by directly processing a wafer using electron-beam lithographic techniques.

Abstract: In pattern generating apparatus of the type employing a reciprocating laser beam for scanning a substrate surface, three scan lines are formed simultaneously. During reciprocation in one direction, the beam is deflected upwardly at an angle of arccot (1/3) with respect to the reciprocating direction, and during reciprocation in the opposite direction, the beam is deflected downwardly at an angle of arccot (1/3).