In recent years, with the rapid development of large model technology, the Transformer architecture has gained widespread attention as its core cornerstone. This article will delve into the principles ...

Discover the key differences between Moshi and Whisper speech-to-text models. Speed, accuracy, and use cases explained for your next project.

For both encoder and decoder architectures, the core component is the attention layer, as this is what allows a model to retain context from words that appear much earlier in the text.

A Solution: Encoder-Decoder Separation The key to addressing these challenges lies in separating the encoder and decoder components of multimodal machine learning models.

But not all transformer applications require both the encoder and decoder module. For example, the GPT family of large language models uses stacks of decoder modules to generate text.

The What: ZeeVee is introducing the ZyPer4K-XS, smaller-footprint encoder and decoder models with the performance of its premier SDVoE and AVoIP signal distribution solutions.