The Khronos Group, Inc. is an American non-profit member-funded industry consortium based in Beaverton, Oregon, focused on the creation of open standard, royalty-free application programming interfaces (APIs) for authoring and accelerated playback of dynamic media on a wide variety of platforms and devices.

Khronos members may contribute to the development of Khronos API specifications, vote at various stages before public deployment, and accelerate delivery of their platforms and applications through early access to specification drafts and conformance tests.

Parallel computing is a type of computation in which many calculations or the execution of processes are carried out simultaneously.

Large problems can often be divided into smaller ones, which can then be solved at the same time.

There are several different forms of parallel computing: bit-level, instruction-level, data, and task parallelism.

Parallelism has been employed for many years, mainly in high-performance computing, but interest in it has grown lately due to the physical constraints preventing frequency scaling.

As power consumption (and consequently heat generation) by computers has become a concern in recent years, parallel computing has become the dominant paradigm in computer architecture, mainly in the form of multi-core processors.

Augmented reality (AR) is a live direct or indirect view of a physical, real-world environment whose elements are augmented (or supplemented) by computer-generated sensory input such as sound, video, graphics or GPS data.

It is related to a more general concept called mediated reality, in which a view of reality is modified (possibly even diminished rather than augmented) by a computer.

As a result, the technology functions by enhancing one’s current perception of reality.

By contrast, virtual reality replaces the real world with a simulated one.

Augmentation is conventionally in real time and in semantic context with environmental elements, such as sports scores on TV during a match.

Artificial neural networks (ANNs) or connectionist systems are a computational model used in computer science and other research disciplines, which is based on a large collection of simple neural units (artificial neurons), loosely analogous to the observed behavior of a biological brain's axons.

Each neural unit is connected with many others, and links can enhance or inhibit the activation state of adjoining neural units.

Each individual neural unit computes using summation function.

There may be a threshold function or limiting function on each connection and on the unit itself, such that the signal must surpass the limit before propagating to other neurons.

These systems are self-learning and trained, rather than explicitly programmed, and excel in areas where the solution or feature detection is difficult to express in a traditional computer program.

Three-dimensional computer graphics (3D computer graphics, in contrast to 2D computer graphics) are graphics that use a three-dimensional representation of geometric data (often Cartesian) that is stored in the computer for the purposes of performing calculations and rendering 2D images.

Such images may be stored for viewing later or displayed in real-time.