Company patents
GDM Holding LLC
GDM Holding LLC's patent strategy reveals a strong and growing commitment to computing technologies, with Machine Learning & AI dominating 55.0% of its portfolio and showing a robust +37.8% YoY growth in 2026 so far. Surprisingly, despite its heavy computing focus, the company is rapidly expanding its manufacturing-related IP, with Manipulators & Robotics patents surging by +120.0% YoY and Electronic Design Automation (CAD/EDA) experiencing an exceptional +400.0% YoY increase, indicating an emerging focus on integrated hardware and automation solutions.
Patent Trend by Technology Area
Yearly patent publications since 2023
Product themes
Product-level themes inferred from filings since 2023, with category chips showing where each theme appears. Select a theme to filter the patents below.
160 US filings (since 2023) · 12 categories · 28 themes
Development and optimization of novel neural network layers or architectures specifically designed to improve performance or efficiency for computer vision tasks.
Techniques utilizing deep learning models like Generative Adversarial Networks (GANs) or diffusion models to create new images, modify existing ones, or generate synthetic data based on various inputs or conditions.
Techniques for generating human-like text or other content using large pre-trained models, often involving prompt engineering, speculative decoding, or multi-modal inputs for content creation.
Methods and apparatus for improving the visual fidelity, resolution, or compression efficiency of video signals, often through advanced processing, up-scaling, or neural network-based filters.
Systems leveraging artificial intelligence and machine learning to dynamically adjust educational content, learning paths, goals, or feedback based on individual user performance, progress, or physiological data. This includes generating personalized exercises, recommendations, and adaptive sequencing of knowledge points.
Systems and methods utilizing artificial intelligence, particularly large language models and neural networks, to extract, summarize, generate, or categorize information from unstructured or semi-structured data sources.
Algorithms and systems for generating, optimizing, and executing trajectories for autonomous vehicles or robots to move through an environment, often involving obstacle avoidance, route validation, and goal reaching.
Techniques for combining and analyzing information from multiple distinct data modalities (e.g., text, image, video, audio, sensor data) to derive richer insights or improve system performance and decision-making.
Automated methods and tools for generating, optimizing, and verifying the physical layout and interconnections of electronic components, including integrated circuits, printed circuit boards, and system-level interface protection.
Technologies for generating artificial speech that is personalized, context-aware, or adaptable to specific virtual agents or messaging campaigns, often utilizing text-to-speech (TTS) and audio caching for efficient delivery.
Methods and systems for monitoring the operational status, detecting anomalies, ensuring safe interaction, and preventing damage or injury in robotic systems.
Algorithms and hardware optimizations for rapidly identifying and characterizing relevant visual features (e.g., objects, motion, gradients) from images or video streams, often integrating machine learning for feature representation and recognition, with a focus on real-time performance and reduced computational cost.
Methods and systems for improving the quality of video streams, generating intermediate frames, or continuously locating and following objects within a sequence of images, even under occlusion.
Computational methods for modeling and simulating photolithography processes, including mask design, aerial image generation, and defect prediction for semiconductor manufacturing.
Techniques for combining data from disparate sensor types (e.g., cameras, radar, mobile device signals) to achieve a more robust and comprehensive understanding of an environment or subject, often leveraging machine learning for interpretation and correlation.
Novel hardware designs and processing pipelines tailored for specific computational tasks, such as graphics rendering, neural network operations, or matrix transformations, often involving custom circuits, memory arrays, or data flow mechanisms.
Methods and apparatus for detecting objects and determining their three-dimensional position and orientation (pose) using imagery or point cloud data, often for navigation, surveying, or environmental understanding.
Methods and systems for identifying synthetic or manipulated speech (deepfake audio) using forensic analysis of audio features, such as breath patterns, vocoder signatures, or machine learning models to determine authenticity.
AI systems designed to engage in natural language dialogue, maintain conversation state, understand user intent, and generate relevant responses, often across multiple communication channels or modalities.
Techniques for enhancing, encoding, decoding, or separating speech and audio signals, often involving multi-microphone arrays, acoustic echo cancellation, beamforming, or advanced audio compression for improved clarity and quality.
Specialized hardware, architectural designs, and computational methods to improve the speed, efficiency, and security of artificial intelligence and machine learning model execution, particularly for inference and data processing.
Methods for training machine learning models across multiple decentralized devices or servers while keeping data localized, often involving aggregation of model parameters and secure communication.
Using computational design and simulation to optimize the performance characteristics of specific components or materials within a larger engineering system.
Techniques to improve the accuracy and robustness of Automatic Speech Recognition (ASR) systems by incorporating contextual information, dynamic hint words, or customized machine learning models for specific domains or users.
Developing and applying machine learning algorithms that leverage quantum computing principles, such as quantum circuits or autoencoders, for tasks like simulation or data processing.
Techniques and hardware for autonomous systems to gather and interpret data about their surroundings, including obstacle detection, object recognition, and depth estimation, to inform control decisions.
Design and control of advanced robotic grippers, tools, and mechanical linkages for specific manipulation tasks or operating in challenging environments.
Utilizing machine learning, particularly deep learning, to analyze medical data such as images, sensor readings, or physiological signals for disease prediction, diagnosis, or treatment assessment.
Patents
Showing 1-9 of 9
Multimodal Data Fusion