Abstract: Apparatuses, systems, and techniques to generate computer graphics. In at least one embodiment, an application programming interface call to output an application-generated frame of computer graphics is intercepted. One or more interpolated frames of computer graphics are generated based on the application-generated frames. The application-generated and interpolated frames are output in accordance with a goal rate.

Abstract: Traditionally, a software application is developed, tested, and then published for use by end users. Any subsequent update made to the software application is generally in the form of a human programmed modification made to the code in the software application itself, and further only becomes usable once tested, published, and installed by end users having the previous version of the software application. This typical software application lifecycle causes delays in not only generating improvements to software applications, but also to those improvements being made accessible to end users. To help avoid these delays and improve performance of software applications, deep learning models may be made accessible to the software applications for use in providing inferenced data to the software applications, which the software applications may then use as desired. These deep learning models can furthermore be improved independently of the software applications using manual and/or automated processes.

Abstract: Traditionally, a software application is developed, tested, and then published for use to end users. Any subsequent update made to the software application is generally in the form of a human programmed modification made to the code in the software application itself, and further only becomes usable once tested and published by developers and/or publishers, and installed by end users having the previous version of the software application. This typical software application lifecycle causes delays in not only generating improvements to software applications, but also to those improvements being made accessible to end users. To help avoid these delays and improve performance of software applications, deep learning models may be made accessible to the software applications for use in performing inferencing operations to generate inferenced data output for the software applications, which the software applications may then use as desired.

Abstract: Traditionally, a software application is developed, tested, and then published for use by end users. Any subsequent update made to the software application is generally in the form of a human programmed modification made to the code in the software application itself, and further only becomes usable once tested, published, and installed by end users having the previous version of the software application. This typical software application lifecycle causes delays in not only generating improvements to software applications, but also to those improvements being made accessible to end users. To help avoid these delays and improve performance of software applications, deep learning models may be made accessible to the software applications for use in providing inferenced data to the software applications, which the software applications may then use as desired. These deep learning models can furthermore be improved independently of the software applications using manual and/or automated processes.

Abstract: Methods for code protection are disclosed. A method includes using a security processing component to access an encrypted portion of an application program that is encrypted by an on-line server, after a license for use of the application program is authenticated by the on-line server. The security processing component is used to decrypt the encrypted portion of the application program using an encryption key that is stored in the security processing component. The decrypted portion of the application program is executed based on stored state data. Results are provided to the application program that is executing on a second processing component.

Abstract: Methods for code protection are disclosed. A method includes using a security processing component to access an encrypted portion of an application program that is encrypted by an on-line server, after a license for use of the application program is authenticated by the on-line server. The security processing component is used to decrypt the encrypted portion of the application program using an encryption key that is stored in the security processing component. The decrypted portion of the application program is executed based on stored state data. Results are provided to the application program that is executing on a second processing component.