Company patents
Perceive Corporation
Perceive Corporation's patent strategy is overwhelmingly focused on Machine Learning & AI, comprising 96.2% of its portfolio, yet it surprisingly saw a dramatic 90.0% decline in new patent filings in this core area in 2025 after a 76.5% growth in 2024. This sharp drop in 2025 across nearly all categories, including Computer Hardware Architecture (down 90.9%) and Operating Systems & Program Control (down 100.0%), suggests a significant shift or pause in its patenting activities, rather than a sustained emerging focus in any single area.
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.
52 US filings (since 2023) · 8 categories · 8 themes
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.
Development and optimization of novel neural network layers or architectures specifically designed to improve performance or efficiency for computer vision tasks.
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.
Developing and applying machine learning algorithms that leverage quantum computing principles, such as quantum circuits or autoencoders, for tasks like simulation or 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.
Techniques employed within compilers or related tools to analyze program code, identify entities for compilation, and optimize execution on target hardware, including reconfigurable systems, to improve performance or resource efficiency.
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.
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.
Patents
Showing 1-6 of 6
Federated & Distributed ML