Methods Of Treating Plantar Fibromatosis

The USPTO published patent application US20260091092A1 on April 2, 2026, disclosing methods of treating plantar fibromatosis. The application (No. 19288073) was filed August 1, 2025, with inventors James P. Tursi, Luis A. Ortega, Qinfang Xiang, Saji Vijayan, Jeffrey David Lehrman, and David Hernandez. The patent covers therapeutic approaches using compounds classified under A61K 38/4886 and A61K 9/0019.

LLM Speculative Decoding for AI Inference Acceleration

The USPTO published patent application US20260093960A1 by inventors Yao Cui Fehlis and Jalal Uddin Mahmud, disclosing a method for accelerating large language model inference using speculative decoding. The invention uses a neural network to output speculative decoding parameters iteratively, minimizing cumulative runtime. The patent covers CPC classifications G06N 3/047, G06F 40/284, and G06N 3/092.

Method for Training ML Model to Generate Text

USPTO published patent application US20260093959A1 for a computer-implemented method training machine learning models for text generation. The method involves preprocessing input text into character vectors, encoding to word vectors, generating predictive word vectors via a backbone model, and decoding to character probabilities for model updates. Inventors: Lukas Balles and Pit Neitemeier. Application filed September 29, 2025.

AI classifier training using anomaly detection methods

The USPTO published patent application US20260093782A1 by inventors Krishnaprasad and Somashekhar describing systems and methods for training AI classifiers using anomaly detection. The application covers a two-phase approach where anomaly detection rules initially label data instances, then a trained classification model takes over once performance thresholds are met. This applies to machine learning model development for anomaly detection in various data sets.

AI system predicts task completion using resource history

USPTO published patent application US20260093528A1 by inventor John Graham Cvinar for an AI system that schedules tasks by predicting task completion using resource history, task completion history, experience, and availability data.

Processing Parallelism for Machine Learning Model Training

The USPTO published patent application US20260093523A1 for a processing system that schedules parallel training of machine learning model instances based on microbatch counts. The system identifies expected idle cycles of processing units during training and schedules additional model instances during those periods. Inventors include Sumanth Gudaparthi, Yao Cui Fehlis, Karthik Ramu Sangaiah, and Sonali Singh. The application was filed on September 30, 2024.

Configurable Artificial Intelligence Powered Software Assistant

The USPTO published patent application US20260093507A1 filed by UiPath, Inc. for a configurable AI-powered software assistant providing co-pilot guided automation experiences using contextual knowledge repositories. The application covers methods for AI model-based recommendation responses within a decision-making structure. Application No. 18941083 was filed on November 8, 2024.

Dynamic Microarchitecture Adaptation Using Machine Learning

The USPTO published patent application US20260093501A1 by inventors Zhu Zhou, Bin Li, Gilles Pokam, and Wessam Elhefnawy for dynamic microarchitecture adaptation using machine learning. The invention discloses a reinforcement learning model trained on microarchitectural performance data to configure processor settings based on telemetry and workload characteristics. Application No. 18900524 was filed September 27, 2024.

VIASAT patent for ML-based RF apparatus tuning

VIASAT patent for ML-based RF apparatus tuning

Protection Architecture Using Proof of Integrity on Distributed Ledgers

Wells Fargo Bank, N.A. received a published patent application (US20260093799A1) from the USPTO for a system and method restricting digital asset exchanges using a proof of integrity model on distributed ledgers. The system validates exchange requests against a protection model, authorizes transactions via consensus, and generates new blockchain blocks with appended protection parameters. Inventors: Govinda Rajulu Nelluri, Vinay K. Pandey, Shashank Raju Birudharaju.