Mixture of experts (MoE) is a machine learning technique where multiple expert networks (learners) are used to divide a problem space into homogeneous...

pioneering integration of the Mixture of Experts (MoE) technique with the Mamba architecture, enhancing the efficiency and scalability of State Space Models...

expensive to train and use directly. For such models, mixture of experts (MoE) can be applied, a line of research pursued by Google researchers since 2017...

Mixtral 8x7B uses a sparse mixture of experts architecture. The model has 8 distinct groups of "experts", giving the model a total of 46.7B usable parameters...

architecture, a mixture-of-experts approach, and a larger one-million-token context window, which equates to roughly an hour of silent video, 11 hours of audio...

size of the model is simply the number of parameters. However, one complication arises with the use of sparse models, such as mixture-of-expert models...

2024. It is a mixture-of-experts Transformer model, with 132 billion parameters in total. 36 billion parameters (4 out of 16 experts) are active for...

relies on a mixture-of-experts architecture and is built on the MegaBlocks open source project. DBRX cost $10 million to create. At the time of launch, it...

Transformer (2021): a mixture-of-experts variant of T5, by replacing the feedforward layers in the encoder and decoder blocks with mixture of expert feedforward...

learning restricted Boltzmann machines. Mixture of experts Boltzmann machine Hinton, G.E. (1999). "Products of experts". 9th International Conference on Artificial...