Invention Grant
- Patent Title: Real time context dependent deep learning
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Application No.: US17404153Application Date: 2021-08-17
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Publication No.: US11704564B2Publication Date: 2023-07-18
- Inventor: Lev Faivishevsky , Tomer Bar-On , Yaniv Fais , Jacob Subag , Jeremie Dreyfuss , Amit Bleiweiss , Tomer Schwartz , Raanan Yonatan Yehezkel Rohekar , Michael Behar , Amitai Armon , Uzi Sarel
- Applicant: Intel Corporation
- Applicant Address: US CA Santa Clara
- Assignee: INTEL CORPORATION
- Current Assignee: INTEL CORPORATION
- Current Assignee Address: US CA Santa Clara
- Agency: Jaffery Watson Mendonsa & Hamilton LLP
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06N20/00 ; G06N20/10

Abstract:
In an example, an apparatus comprises a plurality of execution units comprising and logic, at least partially including hardware logic, to receive a plurality of data inputs for training a neural network, wherein the data inputs comprise training data and weights inputs; represent the data inputs in a first form; and represent the weight inputs in a second form. Other embodiments are also disclosed and claimed.
Public/Granted literature
- US20220076118A1 REAL TIME CONTEXT DEPENDENT DEEP LEARNING Public/Granted day:2022-03-10
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