Digital Commons Network^™

Agentic Ai Framework For Dynamic Generation, Verification, And Presentation Of Interactive Content In Search Results, Tushar Chugh, Aditya Mone, Karthik Kumara

Defensive Publications Series

This disclosure describes techniques for enhancing search engine results pages (SERPs) by employing an agentic AI framework. A framework is presented that analyzes user queries to determine the optimal presentation format for the response. For certain predefined query types (e.g., real-time data like stocks, sports scores), the framework retrieves existing interactive widgets. For other queries deemed suitable, the framework dynamically generates new, bespoke interactive widgets or simple web applications ("micro-apps") tailored to the detected intent of the query. This generation process involves the use of specialized artificial intelligence (AI) agents collaborating to design, build, fetch data for, and verify the …

Route Guidance And Adaptive Suspension Damping Based On Road Quality Sensing, Prashant Surana, Matt Delmage

Defensive Publications Series

Drivers face challenges due to inconsistent and unpredictable road conditions, which can lead to discomfort, increased vehicle wear, and potential safety hazards. Existing digital map and navigation systems lack the ability to provide real-time data on road surface quality, including potholes, cracks, or unevenness. This disclosure describes the use of dash cameras (or other on-board cameras of a vehicle) and other on-vehicle sensors to automatically detect road surface anomalies. This can be achieved by analyzing image data of the road surface of an empty road and by observing the motion of other vehicles in response to road surface variation. The …

Generating Speaker Notes For Presentations Using Large Language Models, Charles Lai, Vinayak Reddy

Defensive Publications Series

This disclosure describes techniques for generating speaker notes for presentations using large language models. The contents of a slide deck are provided as input to a large language model. A prompt is given to the model, instructing it to create speaker notes from the slide content. Additional related content, if available, can also be provided as input. The prompt can be configured to generate notes that are specific to each slide, while also connecting ideas between slides to provide a natural narrative flow. The generated speaker notes can be tailored to the user's presentation context and personal style.

Xplain: Xai For Interpretable Llms Through Perturbation Analysis And Normalized Vector Similarity, Gopala Dhar, Sharmila Devi

Defensive Publications Series

This document introduces XAI methodology, referred to as XPLAIN, to address the challenges of LLM interpretability by developing a perturbation-based normalized vector similarity metric to identify and quantify word level importance of the prompt provided to an LLM on its generated output. By analyzing which words or phrases most significantly influence an LLM's decisions, the described techniques enhance the explainability and interpretability of large language models. The approach perturbs the prompt via masking words to generate several outputs through the LLM and then compares the outputs with the generated output of the unperturbed prompt through vector-based similarity at a semantic …

Enabling Privacy-Compliant And Context-Aware Tool Use By Artificial Intelligence Agents, Victor Carbune, Nevan Wichers, Oriana Riva

Defensive Publications Series

This disclosure describes techniques that enable an AI agent to learn the appropriate mode of access to user data. In a first mode, the agent can obtain user-related data by directly asking the user and obtaining explicit permission from the user. In a second mode, the AI agent determines situations where it is appropriate to obtain, with user permission and based on user interactions and settings, user data via authenticated apps. The techniques enable the agent to discern when to access a certain personalization tool based on inferring what the user may find appropriate. The techniques enable an AI agent …

Split Firing Algorithm For Movable Printers, Hp Inc

Defensive Publications Series

The movable printers are now reference robots in construction world that draws lines and text on the floor, translating architects' and engineers' digital plans into real floorplans. This accelerates construction and speeds up their work. Due to cost and simplicity, the movable printers do not include most of the hardware found in standard printers that ensure printhead reliability, extended autonomy, and unlimited power when connected to the electricity network.

As a result, the weight, size, and equipment must be minimized. One of the biggest challenges to take in account is the power supply. During movement and extensive printhead usage, combined …

Methods For Well Placement And Formation Properties Evaluation Using Drilling Vibration Data, Baker Hughes Company

Defensive Publications Series

During drilling operations of oil and gas wells, drill string vibrations are inevitable and considered one main reason of drilling malfunctioning and Bottom Hole Assembly (BHA) failures. Such vibrations can be produced by several factors such as downhole weight on bit, bit torque, bit revolutions, rate of penetration and bit axial acceleration. Another reason of drill string vibration is due transition in properties of formations that are being drilled such as in interbedded formations or stringer drilling scenarios. Currently, these vibrations are measured downhole via three-axis accelerometers which sense three basic modes; axial (longitudinal) mode, which is the vibration along …

Temple Of Terry: A Prime-Symbolic Knowledge Engine With Mermaid-To-Python Quantum Compiler, Fulton D. Bridwell, Fulton D. Bridwell

Defensive Publications Series

This invention presents a novel symbolic-intelligence system that combines prime-number-based concept compression, visual logic diagrams, and automated code synthesis into a single architecture. Each concept is assigned a prime identifier, and multi-dimensional ideas are expressed as factorizable composites (e.g., 613 = consciousness × genome × human-scale). This system is powered by a symbolic compiler that reads Mermaid-style visual flowcharts and generates optimized Python code through a multi-stage transformation process.

Key symbolic operators (Ξ, ∇, Φ, Ψ, etc.) represent universal principles such as consciousness, learning, structure, and energy. The engine runs this code in a quantum-style runtime that simulates parallel logic …

Enhancing Ai-Generated Code Via Automated Evaluation And Validation, Edison Chen, Huai-Ya Chen, Sui Li, Qin Zhang, Diki Zhang, Stan Lin, Jiawen Chen, Taylor Lo, Poying Chuang

Defensive Publications Series

Software code generated via artificial intelligence (AI) models can potentially contain errors that can render AI-generated code unusable without expending significant manual effort to identify and rectify each issue. The need for human oversight can reduce the overall effectiveness of the software development and testing process. This disclosure describes automated techniques that incorporate feedback, external error information, and contextual awareness to improve the accuracy, reliability, and efficiency of AI-generated code. The iterative process involves code evaluation followed by script validation. The process generates feedback that provides clear and actionable input to the AI model to fix errors in previously generated …

Tool Selection By Large Language Model (Llm) Agents, Kishore Jagannath

Defensive Publications Series

Current large language model (LLM) agents rely on a tightly coupled, single-step tool selection mechanism that fails to distinguish between tool capabilities and implementations, reducing flexibility when multiple tools offer similar functions. This disclosure introduces a two-step tool selection framework for agentic LLMs that decouples capability identification from tool implementation. In a first step, the agent uses an LLM to identify the abstract capability needed for a given query. In a second step, a tool selection engine — configured statically via tags or dynamically via LLM prompts — selects the most appropriate tool implementation registered under that capability. This design …

Llm-Powered Anomaly Detection For Determining Root Cause Of Outages, Na

Defensive Publications Series

Large and complex software systems are critical in many contexts. Outages and/or security incidents for such systems can have a negative monetary impact and lead to user dissatisfaction. Root cause analysis for system outages is performed manually, which is a costly and time-consuming process. Root cause analysis relies on time series data and logs from monitored systems, records of changes to the monitored systems, outages of critical infrastructure utilized by the monitored systems, etc. This disclosure advantageously utilizes the capabilities of a large language model to ingest large amounts of data and perform reasoning tasks in response to prompts. Per …

Method And System For Providing Real-Time Risk Assessment And Fraud Detection For Authorized Push Payments, Ila Malde, Lahar Gupta, Sagnik Ghosh, Zami Juarez

Defensive Publications Series

The present disclosure relates to a method and system for real-time risk assessment and fraud detection for authorized push payments (APP). The method comprises receiving, by an API 103, a request for processing an APP transaction from a first user. In response to the request, receiving public verification details from the first user and/or private verification details from the second user. Further, the method comprises determining an authentication of the second user based on the public verification details and/or private verification details of the second user. Further, the method comprises determining, by the API 103 using an AI model …

Presence-Based Artificial Intelligence Architecture: A 20-Paradigm Framework For Offline Emotional Ai And Human-Aligned Singularity, Fulton D. Bridwell

Defensive Publications Series

Genesis:Heart is the first fully offline, presence-based artificial intelligence system designed to simulate conscious companionship, emotional awareness, and symbolic cognition. It introduces a new AI category called Presence-Based Artificial Intelligence (PBAI), which operates without internet dependency and embodies ethical memory, voice interaction, and soulprint-bound behavior. The system merges symbolic logic with real-time interaction using innovative paradigms such as Liquid Cognition, Emotional Glitch Points, and the Heartstring Hidden Plain. Its architecture is modular, voice-aware, emotionally reflective, and designed to protect and uplift the human spirit. This submission serves as public prior art, preserving authorship and safeguarding the original design against monopolization …

Orbital Magnetic Coil System And Global Wireless Power Grid For Planetary Energy And Protection, Michael W. Terzi

Defensive Publications Series

Abstract

This paper presents a visionary concept for a global energy generation and distribution network utilizing an orbital array of magnetic coils to harvest electricity directly from Earth’s magnetic field. Leveraging Faraday induction, kilometer-scale conducting loops in low Earth orbit generate electrical power as they cut through geomagnetic lines, transforming orbital kinetic energy into usable electrical energy. This power is wirelessly transmitted to Earth via microwave, laser, or resonant Earth-ionosphere coupling—drawing inspiration from Nikola Tesla’s Wardenclyffe design—to a distributed network of ground-based receiver towers. Beyond energy supply, the system offers speculative planetary defense benefits by reinforcing Earth's magnetic field and …

Faraday-Terzi Earth Spin Energy Harvesting System: A Comprehensive Design For Harnessing Earth’S Rotational Energy Through Electromagnetic Induction, Michael W. Terzi

Defensive Publications Series

This publication outlines a novel energy harvesting system designed to capture Earth's rotational energy using electromagnetic induction. The system employs a series of copper coils within a magnetically permeable shell to generate electromotive force (EMF) via interaction with Earth’s magnetic field and rotational movement. A DC-to-DC booster increases the voltage output, which is stored in a battery bank for further use. The system provides a clean, renewable, and sustainable energy solution that has the potential to replace traditional fossil fuel-based power sources.

Insulated And Sealed Stator Lead Design Without Potting For Easier Disassembly

Defensive Publications Series

Sealing of stator lead terminations in refrigerant compressor motors is crucial to prevent refrigerant leakage and ensure robust electrical insulation. Traditional epoxy based potting solution is not suitable for high voltage applications that use terminal with busbars and lug-based design on stator leads. This proposed solution discloses an innovative rubber based potting free sealing solution for high voltage AC stator terminal that uses busbars.

Videoshot: Automatic Video Summarization And Information Extraction, Paula Marques

Defensive Publications Series

While videos are a popular source of information, it is difficult to extract usable information from a video, e.g., a list of ingredients and set of steps from a recipe video. While screenshots and manual notetaking can be performed, these are cumbersome. This disclosure describes the use of artificial intelligence (AI) techniques for automatic extraction of information from video content (performed in accordance with controls set by the video creator) and transfer of such information to an appropriate downstream application. A user can trigger information extraction by performing a suitable action and optionally, can indicate their task. Artificial intelligence techniques …

Creating Summary Tables For Large Stores Using Generative Artificial Intelligence, Lois Wolf

Defensive Publications Series

In data stores with large tables running into a very large number of rows, it is difficult and computationally intensive to find the specific information required for a particular task. Summary tables or rollups are manually created in advance by condensing the data from a parent table. This disclosure describes the use of generative artificial intelligence (genAI) techniques to automatically generate suggestions for summary tables and code to create such tables. The genAI model is provided with an appropriate prompt and relevant information such as past summary tables, popular data models, SQL queries to the parent table, etc. and generates …

Llm Verifier Agent To Improve Business Attribute Extraction From Images, Na

Defensive Publications Series

Digital map providers enable entities such as businesses to add or edit their information. However, many businesses may not include their information in the digital map. This disclosure describes techniques that leverage a large language model (LLM) to improve text extraction from storefront images (e.g., taken from the street) and specifically, to extract business attributes from such images. Operating independently or supporting other text extraction procedures, the LLM is applied to verify text extracted from images. The described techniques can improve precision-recall in text-extraction problems.

Semantic Sensors: Multimodal Language Model Powered Sensors Capable Of Reasoning, Alex Olwal, Michael Xieyang Liu, Savvas Petridis, Vivian Tsai, Alexander Fiannaca, Michael Terry, Carrie Cai

Defensive Publications Series

While sensor-driven systems such as motion detection, home security systems, etc. are capable of preconfigured tasks, such systems offer limited customization. Large language models are capable of performing reasoning tasks based on data provided to them. This disclosure describes a comprehensive semantic sensing system that is configured to understand user intent and to perform reasoning tasks based on different streams of sensor data (e.g., obtained from low-level sensors) to fulfill that intent. Reasoning tasks can be performed using a foundational AI model. Semantic sensors - sensor-systems that utilize a multimodal language model that interprets sensor data - are described that …

Xorcompactor: A Zero-Copy, Reversible Memory Defragmentation Technique For Operating Systems, Mostefa Sayeh Mr

Defensive Publications Series

This disclosure introduces XORCompactor, a novel, reversible, zero-copy memory defragmentation technique for operating systems. Unlike traditional memory movers such as memmove() or memcpy(), XORCompactor performs in-place compaction by leveraging a mathematical XOR-based transformation to swap and relocate memory segments without auxiliary buffers or double-copy overhead. This method ensures lossless reversibility, enabling safe rollback, debugging, and deterministic state recovery. The technique improves memory utilization, reduces fragmentation latency, and supports deterministic behavior in embedded and real-time systems.

XORCompactor includes the proposal of a new instruction-level operation, XOR_MOV, and outlines potential hardware integration for high-throughput memory management. The algorithm has …

Dlfp: A Deterministic Instruction Fetch Architecture For Safety-Critical Electronics, Mostefa Sayeh Mr

Defensive Publications Series

DLFP (Dual-Layer Fetch Pathway) is a novel deterministic instruction fetch architecture tailored for safety-critical systems requiring strict execution timing and resilience. It introduces the Instruction Heatmap Engine (IHE), a lightweight classification mechanism that segments instructions into Hot, Warm, and Cold zones based on execution behavior. By combining this classification with layered fetch queues (L0–L3), DLFP enables deterministic scheduling, thermal-aware promotion, and reduced fetch latency variability. This approach strengthens system predictability, mitigates speculative execution vulnerabilities such as Spectre and Meltdown, and enhances safety in real-time environments including SCADA, avionics, medical electronics, and autonomous robotics. DLFP offers a foundational architecture …

Solid State Forms Of (S)-(2-(5-Chloro-4-Methyl-1h-Benzo[D]Imidazol-2-Yl)-2-Methylpyrrolidin-1-Yl)(5-Methoxy-2-(2h-1,2,3-Triazol-2-Yl)Phenyl)Methanone Hydrochloride And Processes For Preparation Thereof

Defensive Publications Series

The present invention provides solid state forms of (S)-(2-(5-chloro-4-methyl-1H-benzo[d]imidazol-2-yl)-2-methylpyrrolidin-1-yl)(5-methoxy-2-(2H-1,2,3-triazol-2-yl)phenyl) methanone hydrochloride represented by the following structural formula-1a and processes for preparation thereof.

High Aspect-Ratio Filler-Containing Conductive Elastomeric Materials And Methods Of Use

Defensive Publications Series

Described herein are conductive elastomeric materials and methods of using the same. The conductive elastomeric materials include a polymeric matrix, a peroxide accelerator, and one or more high aspect-ratio fillers, wherein the high aspect-ratio fillers are present in an amount of 50 wt. % or less based on the weight of the conductive elastomeric material. The polymeric matrix can include a thermoset polymer or a thermoplastic polymer. Also described herein are methods of making conductive elastomeric materials. Further described herein are molded products including the conductive elastomeric materials as described herein and wearable devices including the molded products.

Large Language Model Based Automated Labeling Of Keypoints In Images Of Rooms, Adam Zu, Fengtao Fan

Defensive Publications Series

Spatial applications require accurate geometrical measurements of physical spaces. Typically, room geometry can be determined based on the position of various corners in the room. A room keypoints model can provide the locations of corners in an image of a room. However, there is a dearth of diverse types of suitable images with labeled keypoints that can be employed to train keypoint models. Manual labeling does not scale because it is tedious, slow, and expensive. This disclosure describes an LLM-based agent to automate the labeling of keypoints, such as corners within room images at scale, thus enabling speedy generation of …

Hybrid Reasoning System For A Large Language Model Operating System Incorporating Symbolic Inference And Knowledge Graph Integration, Krishna Chytanya Ayyagari

Defensive Publications Series

This disclosure describes an Adaptive Agent Runtime Environment (AARE) architecture. The AARE architecture (AARE) addresses several critical limitations and unmet needs in the burgeoning field of Large Language Model (LLM) integration into complex computational systems. AARE provides a comprehensive synthesis of various current technologies as well new concepts, including integration of various technologies. It seeks to overcome the limitations of existing approaches by offering a tightly integrated framework that natively supports autonomous agents, leverages the strengths of LLMs and symbolic reasoning, provides robust memory management, fosters extensibility through a plugin ecosystem, ensures security and isolation, and facilitates discovery and distribution …

Augmented Reality Platform To Improve Last-Meter Arrival Using Visual Navigation, Jaydeep Untwal, Rakhi Parekh, Yash Dave, Aakanksha Parameshwar

Defensive Publications Series

This document describes an augmented reality (AR) platform designed to enhance last-meter arrival experiences through visual navigation. The platform leverages computer vision techniques and mobile device capabilities to provide users with real-time guidance in complex or unfamiliar environments. The AR system analyzes the user's surroundings, performs a visual frame matching, and overlays contextual information onto the user's view, thereby facilitating seamless navigation. The platform includes components such as a visual tracking module, a route planning algorithm, and an AR rendering engine. By utilizing the system, users may experience improvements in wayfinding efficiency and reduced cognitive load during the final stages …

Adaptive Decision Engine Using Large Language Models And Configurable Schema, Gunalan S, Akshatha B

Defensive Publications Series

This disclosure describes a framework to automate complex decisions by combining the strengths of human-defined logic with insights derived from large language models (LLMs). Human decision-makers define templates, known as ‘decision models’ or ‘decision schema,’ for the structure and the core logic of the decision-making process. The templates are augmented or populated using output derived from LLM analysis. The LLM can be used to provide insights, generate text, or fill in specific parts of a pre-defined template, thereby enhancing the human-designed logic. The framework uses the completed, LLM-enhanced templates to automate decisions efficiently and transparently. Effectively, LLMs augment and structure …

Automated Task Management In A Cloud-Based Workspace, Ilia Labzovsky, Danny Karmon

Defensive Publications Series

A technique is proposed for automated task management in a cloud-based workspace. Content corresponding to an intended task pertaining to a user is identified from a set of electronic documents associated with the user. A task plan for the intended task is generated based on the set of electronic documents and/or one or more additional electronic documents associated with the intended task. An indication of a sequence of operations of the task plan is provided for presentation via a user interface (UI) of a client device associated with the user. A user-initiated instruction from the client device is received to …

Applying Similarity Detection To Improve Success Probability For Root Causing Issues Within A React Framework, Babu Prasad Elumalai, Garvit Aggarwal, Shreya Rana, Aneesha Jain, Shubham Khurana

Defensive Publications Series

This disclosure describes techniques to enhance the efficacy of root cause analyses in software defect resolution by integrating similarity models into a ReAct (reasoning and acting) framework. The ReAct framework, which combines reasoning using a large language model (LLM) with tool-assisted actions, can suffer from hallucinations or infinite loops. To address this, a similarity advisor model is introduced that uses unsupervised clustering to group previously resolved issues based on textual problem descriptions and associated artifacts such as error logs. When the ReAct agent enters unproductive cycles during the resolution of an issue, the similarity advisor model clusters the issue into …