Google llc (20240256966). BINARIZED TRANSFORMER NEURAL NETWORKS FOR SEQUENCE GENERATION simplified abstract
Contents
BINARIZED TRANSFORMER NEURAL NETWORKS FOR SEQUENCE GENERATION
Organization Name
Inventor(s)
Ankush Garg of Sunnyvale CA (US)
Yuan Cao of Mountain View CA (US)
Lukasz Lew of Sunnyvale CA (US)
Orhan Firat of Mountain View CA (US)
Behrooz Ghorbani of San Francisco CA (US)
BINARIZED TRANSFORMER NEURAL NETWORKS FOR SEQUENCE GENERATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240256966 titled 'BINARIZED TRANSFORMER NEURAL NETWORKS FOR SEQUENCE GENERATION
The abstract describes methods, systems, and apparatus for performing sequence generation tasks using binarized neural networks, specifically an attention neural network with attention blocks and binarized feedforward blocks.
- Binarized neural networks are utilized for sequence generation tasks.
- The attention neural network includes attention blocks and binarized feedforward blocks.
- Each attention block is configured to perform specific tasks within the sequence generation process.
Potential Applications:
- Natural language processing
- Speech recognition
- Image recognition
Problems Solved:
- Enhancing the efficiency of sequence generation tasks
- Improving the accuracy of neural network models
Benefits:
- Faster processing speeds
- Higher accuracy in sequence generation
- Reduced computational resources required
Commercial Applications:
- AI-driven applications in various industries such as healthcare, finance, and e-commerce.
Questions about Binarized Neural Networks: 1. How do binarized neural networks differ from traditional neural networks?
Binarized neural networks use binary values (-1 or 1) for weights and activations, reducing memory and computational requirements compared to traditional networks.
2. What are the main advantages of using attention blocks in neural networks?
Attention blocks allow the model to focus on specific parts of the input sequence, improving performance in tasks like machine translation and image captioning.
Original Abstract Submitted
methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing sequence generation tasks using binarized neural networks. the binarized neural network is an attention neural network configured to perform the task and the attention neural network includes a plurality of attention blocks, with each block including an attention block and a binarized feedforward block.
