Researchers from the Johns Hopkins Applied Physics Laboratory (APL) in Laurel, Maryland, and Johns Hopkins University in ...

Nota AI, a company specializing in AI model compression and optimization, announced that two of its papers on MoE-specific ...

Using special tags embedded in the output, the model directly links every factual claim it makes to the specific source ...

Reducing the precision of model weights can make deep neural networks run faster in less GPU memory, while preserving model accuracy. If ever there were a salient example of a counter-intuitive ...

When running an AI model through a quantum computer, scientists have increased accuracy by only adding a relatively small number of parameters.

A team of researchers from Q-CTRL and IBM says it has achieved a 3,000-fold wall-clock speedup over the best available ...

Model quantization bridges the gap between the computational limitations of edge devices and the demands for highly accurate models and real-time intelligent applications. The convergence of ...

The general definition of quantization states that it is the process of mapping continuous infinite values to a smaller set of discrete finite values. In this blog, we will talk about quantization in ...