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 document or database row it pulled the information from.
Quantization is a widely adopted technique in model deployment as it offers a favorable trade-off between computational overhead and performance loss. Integer-arithmetic-only quantization is an ...
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 ...
In real applications of Reinforcement Learning (RL), such as robotics, low latency, energy-efficient and high-throughput inference is very desired. The use of sparsity and pruning for optimizing ...
You can now download Gemma 4 models with quantization-aware training to reduce the amount of mobile memory required to 1GB.