Invention Application
- Patent Title: HYPERBOLIC FUNCTIONS FOR MACHINE LEARNING ACCELERATION
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Application No.: US17677556Application Date: 2022-02-22
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Publication No.: US20220230057A1Publication Date: 2022-07-21
- Inventor: Bogdan Pasca , Martin Langhammer
- Applicant: Intel Corporation
- Applicant Address: US CA Santa Clara
- Assignee: Intel Corporation
- Current Assignee: Intel Corporation
- Current Assignee Address: US CA Santa Clara
- Main IPC: G06N3/063
- IPC: G06N3/063 ; G06N3/04 ; G06F7/544 ; G06F7/548

Abstract:
The present disclosure relates generally to techniques for enhancing recurrent neural networks (RNNs) implemented on an integrated circuit. In particular, approximations of activation functions used in an RNN, such as sigmoid and hyperbolic tangent, may be implemented in an integrated circuit, which may result in increased efficiencies, reduced latency, increased accuracy, and reduced resource consumption involved with implementing machine learning.
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