Intel ARM Nvidia pushes draft specification, wants to unify AI data exchange format

On Wednesday local time chip companies Intel, ARM and Nvidia jointly released a draft specification for a so-called common exchange format for artificial intelligence, which aims to make the process of processing artificial intelligence by machines faster and more efficient.

In the draft, Intel, ARM and NVIDIA recommend the 8-bit FP8 floating-point processing format for artificial intelligence systems. They say that the FP8 floating-point processing format has the potential to optimize hardware memory usage, thereby accelerating AI development. The format is suitable for both AI training and inference, helping to develop faster and more efficient AI systems.

When developing AI systems, the key problem facing data scientists is not only collecting large amounts of data to train the system. It is also necessary to choose a format to express the system weights, which are important factors that the AI learns from the training data to influence the system's predictive effectiveness. Weights allow AI systems like GPT-3 to automatically generate entire paragraphs from a long sentence cue, and also allow the DALL-E 2 AI to generate realistic portraits based on a particular headline.

The common formats for AI system weights are half-precision floating point FP16, which uses 16 bits of data to represent system weights, and single-precision floating point FP32, which uses 32 bits. Half-precision floating-point numbers and lower-precision floating-point numbers reduce the memory space required to train and run AI systems, while also speeding up computation and even reducing the amount of bandwidth resources and power consumed. But because there are fewer bits than in single-precision floating-point numbers, accuracy can be reduced.