USPTO Patent Grant: Integrated Memory System for Neural Networks

The USPTO has granted patent US12585927B2 for an integrated memory system for neural networks, developed by The Board of Trustees of the University of Illinois. The patent covers a memory module designed to compute, store, and sample neural network weights, optimizing precision for machine learning data streams.

Microsoft Patent: Neural Network Training Precision Adjustment

The USPTO has granted Microsoft Technology Licensing, LLC, patent US12585926B2 for a method of adjusting numerical precision and topology during neural network training based on performance metrics. This patent covers techniques for optimizing training efficiency and accuracy using block floating-point formats and accelerator hardware.

USPTO Patent Grant: Spike Neural Network Circuit for Error Prevention

The USPTO has granted a patent (US12585925B2) for a spike neural network circuit designed to prevent errors in charge calculation. The patent, assigned to Electronics and Telecommunications Research Institute, was filed on June 7, 2022, and is set to be granted on March 24, 2026.

USPTO Patent Grant: Authorship Attribution with Event Tracking

The USPTO has granted patent US12585922B2 to U.S. Bank National Association for a system that generates authorship tokens to distinguish human-authored content from AI-generated content. This patent aims to provide auditable tracking of content creation events.

USPTO Patent for Text-to-Image Generation Using Language Models

The USPTO has granted Salesforce, Inc. a patent (US12585919B2) for systems and methods related to text-to-image generation using language models. The patent describes a mechanism to integrate pre-trained language models into text-to-image generation models, enhancing image generation capabilities based on textual prompts.

Raytheon Company Patent for ML Model Drift Detection

The USPTO has granted Raytheon Company a patent for a method of detecting machine learning (ML) model drift using a modified generative adversarial network (GAN). The patent details a system that monitors the output of a deployed ML model to identify drift and determine if re-deployment is necessary.

USPTO Grants Reinforcement Learning Patent to Google LLC

The USPTO has granted a patent (US12585917B2) to Google LLC for reinforcement learning using advantage estimates. The patent covers methods and systems for computing Q values in continuous action spaces, potentially impacting AI development and deployment.

USPTO Patent US12585915B2: Neural Network Training Method

The USPTO has granted patent US12585915B2 to BEIJING BAIDU NETCOM SCIENCE TECHNOLOGY CO., LTD. for a neural network training method involving encrypted feature representations and gradient updates. This patent details a specific technical approach for training neural networks, potentially impacting AI development and data security practices.

USPTO Patent Grant: Structural Model Architecture Generation Method

The USPTO has granted patent US12585914B2 for a method of generating structural model architectures. The patent covers a method that receives an input causality map and generates a structural model architecture based on it, enabling prediction of output variable values.

Samsung Patent for Neural Network Convolution Operation

The USPTO has granted Samsung Electronics Co., Ltd. a patent (US12585913B2) for a method and apparatus related to neural network convolution operations. The patent details a processor-implemented method for generating output features by performing convolution operations and efficiently storing them in memory.