Inventec had 17 patents in artificial intelligence during Q1 2024. In Q1 2024, Inventec Corp filed patents for a federated learning system with client devices verifying model updates, a setting method for an in-memory computing simulator to optimize parameters, a machine learning model training method involving pre-training and fine-tuning models, and a packing method using genetic algorithms and greedy algorithms to optimize packing programs. GlobalData’s report on Inventec gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Inventec grant share with artificial intelligence as a theme is 29% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Method for verifying model update (Patent ID: US20240080180A1)
The patent filed by Inventec Corp describes a federated learning system that includes a moderator and client devices. Each client device performs a method for verifying model updates by receiving a hash function and a general model, training a client model, calculating a difference as an update parameter, sending the update parameter to the moderator, generating a trust value based on hash values, and updating the client model when the to-be-verified value equals the trust value. The method ensures secure and accurate model updates in a distributed learning environment.
The patent claims detail the steps involved in the method for verifying model updates in a federated learning system, including the encryption and decryption processes, the use of homomorphic hash functions, and the generation of public and private keys for secure communication. The claims also cover scenarios where multiple moderators are involved in the verification process, ensuring that the client model is updated correctly based on the aggregated parameters. Overall, the patent outlines a comprehensive approach to maintaining the integrity and accuracy of model updates in a distributed learning system.
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