Abstract: At least a method and an apparatus are presented for secure access of shared data for machine learning training. In one embodiment, a virtual machine is created based on a virtual machine environment type input, wherein the virtual machine permits access to one or more training data sets for training a machine learning system if the virtual machine environment type input indicates access to data enabled mode, and wherein the virtual machine prohibits the access to the one or more training data sets for training the machine learning system if the virtual machine environment type input indicates access to data disabled mode.

Abstract: Methods and apparatus for tuning are disclosed. One embodiment of the invention is directed to a tuner formed on a substrate. The tuner comprises a first die that receives an analog input signal and processes the analog input signal using analog processing circuitry to form analog output signals, and a second die that receives the analog output signals, converts the analog output signals to digital signals, and processes the digital signals to form output signals. Another embodiment of the invention is directed to a multi-chip module comprising a tuner adapted to process television signals of a plurality of types and of a plurality of standards to form output signals.

Abstract: Methods and apparatus for tuning are disclosed. One embodiment of the invention is directed to a tuner formed on a substrate. The tuner comprises a first die that receives an analog input signal and processes the analog input signal using analog processing circuitry to form analog output signals, and a second die that receives the analog output signals, converts the analog output signals to digital signals, and processes the digital signals to form output signals. Another embodiment of the invention is directed to a multi-chip module comprising a tuner adapted to process television signals of a plurality of types and of a plurality of standards to form output signals.