Evolving challenges and strategies in AI/ML model deployment and hardware optimization have a big impact on NPU architectures ...

Quantization is a method of reducing the size of AI models so they can be run on more modest computers. The challenge is how to do this while still retaining as much of the model quality as possible, ...

Local AI concurrency perfromace testing at scale across Mac Studio M3 Ultra, NVIDIA DGX Spark, and other AI hardware that handles load ...

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 ...

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 ...