Digital Commons Network^™

Interactive Photo Exploration Agent With Chained Language Model Calls, D Shin

Defensive Publications Series

Some photo library applications provide a conversational interface that enables users to retrieve photos that match their query. However, current interfaces are not multi-turn and are limited to retrieval and cannot automatically perform generation tasks. This disclosure describes an interactive, conversational interface for a digital photo library that allows users to explore their photos using natural language and receive generative, insightful answers. The exploration is multi-turn and multimodal, and is powered by a multimodal large language model (LLM). With user permission, the LLM is employed to interpret both the user's query (e.g., entered as free-form text) and the content of …

Generating Interactive, Llm-Driven Annotations For Inclusion In Digital Image Files, Ilia Labzovsky, Danny Karmon

Defensive Publications Series

While photographs capture visual information, they lack depth and interactivity. Contextual information, memories, stories, and related data associated with a photograph are external to the image file itself, and are scattered across applications, cloud services, or within the user’s mind. This disclosure describes techniques to enhance a digital image by automatically generating interactive annotations using a large language model (LLM) and incorporating the annotations into the image. Entities within a photo are identified and an LLM is instructed to generate an annotation object for the recognized entities. The annotation object is a self-contained package of data and instructions that specifies …

Integrating Generative Animations Of Photographs Into A Coherent Video Journey, Ilia Labzovsky, Danny Karmon

Defensive Publications Series

Users enjoy creating slideshows, animated videos, etc. that capture their trips. Current techniques to prepare such creations are limited by the content of the captured photographs and user knowledge of such features. This disclosure describes the use of artificial intelligence to automatically generate a dynamic video journey from a collection of user photographs. With user permission, an artificial intelligence model performs semantic analysis of user photos to infer the user’s geographic path during the photo capture journey. A generative video model accesses street-level images along the path and synthesizes a base video that simulates first-person movement along the path. The …

Thumbnail Controller User Interface For Easy Viewing Of Panoramic Images, Yujin Gu, Bethany Tsui, Chung-Hay Luk, Michelle Gu, Jessica Li, Clément Julliard

Defensive Publications Series

Zooming into a panoramic image can take many steps. Once zoomed in, it can be difficult to navigate through, observe features, and work with the image. The disclosure describes a thumbnail slider, a tool that enables rapid navigation through and zooming into wide (or long) images such as panoramas. The described thumbnail slider enables the user to view the entirety of the panorama with speed and fluidity. Simultaneously, it enables the user to zoom into details with fewer taps, pinches, or other gestures. Navigation across the panorama is achieved with a fewer number of swipes. The thumbnail slider enables accurate …

On-Device Measurement Of Impact Of Artificial Intelligence Tools On Productivity, Navid Kagalwalla, Tom Piacentini, Jacques Mouton

Defensive Publications Series

This disclosure describes techniques to measure the net productivity impact of AI-assisted workflows on user productivity. Metadata regarding user activity on a user device is obtained with user permission, using a private, on-device architecture. The data is analyzed on-device to determine whether an AI-assisted workflow is in process and the impact of the use of AI on productivity. In an example implementation, an Activity Sensing and Filtration Layer (ASFL) and a Cognitive Workflow Engine (CWE) are implemented and used to calculate the true net time saved using AI assistance. This metric takes into account the hidden cost of the user …

A Distance Based Embedding Method Using Nlp Methods To Identify Proximity To A Network, Shuhan Zhang, Anurag Tangri, Chinmay Narendra Sonar, Lin Meng, Can Liu, Chiranjeet Chetia

Defensive Publications Series

The present disclosure relates to the field of Artificial Intelligence (AI), in particular to AI methods and systems for analyzing transactional data using Natural Language Processing (NLP) techniques to identify latent relationships and proximity within networks. The disclosed system utilizes text fields within datasets to categorize input data into appropriate classifications. The input comprises a dataset containing text data that provides contextual information related to transactions. Feature embeddings are generated using a sentence-based Language Learning Model (LLM), which captures semantic meaning of sentences. The LLM converts input data of varying lengths into fixed-dimension embeddings. The sentence-based LLM is fine-tuned based …

Ai-Based Claims Assessment For Motor Vehicle Damage Detection, Anonymous

Defensive Publications Series

The insurance industry faces increasing pressure to optimize claims processing efficiency while minimizing claim leakage and fraud. Traditional rule-based and manual approaches are reaching their limits, particularly as market dynamics such as claims inflation and customer demand for faster, self-service experiences accelerate. To address these challenges, we present an AI-driven claims assessment framework that integrates computer vision and generative AI to support human interpretation of visual and textual evidence in vehicle damage claims.

The proposed system comprises two modules: Motor Damage Assessment for analyzing vehicle body damage and Glass Damage Assessment for evaluating windshield damage. The Motor Damage Assessment consists …

Llm-Augmented Dynamic Selective Blocking Of Service Calls For Application Control, Johannes Start, John Lunney

Defensive Publications Series

Software applications face critical challenges in rapidly and precisely mitigating emergent threats such as safety incidents or query-of-death attacks originating from or affecting backend calls. This disclosure describes techniques for dynamic, real-time, intelligent blocking or modification of harmful or problematic backend service call responses. The techniques combine traditional filtering with semantic analysis using a large language model (LLM). A control plane enables operators such as site reliability engineers (SREs) to define and deploy mitigation rules on-the-fly, without code changes or lengthy propagation delays. This enables rapid and precise response to emergent threats, such as safety incidents involving AI-generated content or …

Enhancing Hardware Scan Coverage By Selecting A Data Streaming Interface Unconnected To The Failure, Kaushal Purohit, Victor Wong

Defensive Publications Series

Hardware scanning helps debug problems related to internal components within a device by capturing hardware states as a stream of bits, known as a scan chain. However, employing on-chip or off-chip memory for storage of scan data requires that the path to/from the memory be excluded from the hardware scan, creating a critical gap in debugging. Moreover, wired debugging interfaces are typically unavailable or inaccessible on remote production devices, which makes it challenging to retrieve the scan data quickly. This disclosure describes techniques to optimize the streaming of hardware scan data from on-chip crash manager applications employed to detect hardware …

Closed Loop Correction Of Camera-To-Display Projection Using Piezoelectric Actuation, Na

Defensive Publications Series

Reconstructing a three-dimensional (3D) image of an object of interest requires high pixel accuracy between the optical plane and sensor images. While optical centers can be corrected for in the XY plane and along the roll axis with image cropping and rotation techniques, corrections based only on image processing are difficult in the yaw and pitch orientations. This disclosure describes techniques that leverage reference features in captured images calibrated with previously captured (yaw, pitch) data to correct, via trained machine learning models, the yaw and pitch of cameras. The camera orientations can be controlled by piezoelectric actuators.

Optimizing Data Transfer From Smart Glasses To Paired Device Based On Eye Tracking, Willy Horng Jean Cheung, Shenil Navin Dodhia, Gordon Wan

Defensive Publications Series

Smart glasses and other wearable devices that include cameras can capture the user’s environment as memories and can also answer questions or surface assistance proactively. However, smart glasses have limited compute and storage capabilities, and enabling continuous perception is therefore infeasible. A paired device such as a smartphone can enable smart glasses to operate in continuous perception mode and also provide compute power for artificial intelligence models. However, a key bottleneck is the data transfer between the smart glasses and the paired device, which is constrained by wireless data transfer rates. Even with aggressive data-compression schemes, the payload over the …

Dynamic Management Of Virtual Lanes And Buffer Zones For Autonomous Traffic, Sumukh Shevde, Kamran Mustafa, Abhijit Adsule

Defensive Publications Series

Static assignment of roadway lanes can result in inefficient traffic flow, where congestion may develop in one direction while opposing lanes remain underutilized. To address this, systems and methods for dynamic traffic management are described. A computational system, such as a central server or an in-vehicle computer, can treat a roadway as a single, partitionable surface, creating and modifying virtual lanes in near real-time. The number, width, and direction of these lanes can be adjusted based on current and predicted traffic demand. Autonomous or semi-autonomous vehicles can be assigned to these virtual lanes, and a dynamic virtual buffer zone may …

A Real-Time Computer Vision System For Procedural Verification In Manual Assembly, Frank Mao, Sun Nee Chan, George Liu

Defensive Publications Series

Manual assembly processes can be susceptible to error, potentially leading to incorrect component handling or procedural deviations. A system for real-time procedural verification can use computer vision to address this. An inspection node, which may comprise an imaging device (e.g., a camera) and a processing unit, can capture and analyze an operator's physical actions at a workstation. These actions may be compared against a predefined digital blueprint, such as a standard assembly model (SAM), that codifies a specified sequence of events. Upon detection of a deviation between the operator's actions and the SAM, the system can provide feedback to the …

Helping Commercial Trailer Fleet Operators Successfully Hook Up A Trailer & Allowing The Fleet Manager To Monitor Their Skill, Anonymous

Defensive Publications Series

Commercial users of a trailer feature where an operator may be required to hook up various trailers and various vehicles, some of which may have different specific connections or different orientation/requirements. The truck using its cameras and sound exciters can become a trailer validation coach/monitor for commercial and fleet vehicle operators, reducing risk and liability of incorrect connections.

Thumbfeel, A Tactile Rear Display With Passthrough For Thumb-Position That Could Facilitate Blind Typing In Augmented Reality, Anonymous

Defensive Publications Series

A handheld digital electronic device with a rear tactile display that is also multitouch-sensitive is disclosed. In the context of blind thumb-typing (such as when the electronic device is connected to augmented reality glasses), the present invention can provide tactile passthrough for the thumb-position that readily provides feedback on the character about to be input. The multitouch-sensitivity of the tactile display would be used to measure the positions of the fingers on the back holding the device, and image processing would establish a correspondence between finger parts and location on the rear. Upon touching a control element for input on …

Method And System For Automated Incident Lifecycle Management With Self-Learning Agents, Soumendra Kumar Mishra, Amitabh Ranjan

Defensive Publications Series

The present disclosure relates to a system and method for automating the resolution of incidents in enterprise environments through a modular multi-agent orchestration framework. The system includes an intelligent log processing engine that analyzes and cleanses enterprise logs to extract relevant error contexts, a repository intelligence agent that maps error stack traces to corresponding code files, and an incident analysis agent that identifies root causes while generating actionable insights. A code generation agent produces targeted code fixes based on these insights, while a conversational assistant provides real-time guidance and validation for developers. The framework implements a standardized communication protocol for …

The Picotesla Protocol: Energy-Matched Neuromorphic Brain–Ai Interface With Quantum-Responsive Event, Samuel Church

Defensive Publications Series

This disclosure presents a brain–AI interface architecture that operates under a strict sub-50 W system power envelope to reduce electromagnetic and thermal noise to near-brain levels, enabling event-driven coupling between biological neural surprise events and a neuromorphic spiking system. The system comprises: (i) a brain signal receiver (EEG) with alpha/theta-band feature extraction; (ii) an optional quantum-responsive transducer (e.g., NV-center magnetometer or QRNG correlator) for timing-level sensitivity to picotesla-scale field perturbations; and (iii) an energy-matched neuromorphic processor (e.g., Loihi-class SNN or low-power NPU) that converts biological “surprise” events into discrete spikes with < 40 μs latency and learns via STDP. The disclosure includes enabling details: system diagrams, energy budgets, filtering equations, spike-encoding logic, and experimental protocols (including physically isolated, Faraday-caged conditions) to ensure that the design is reproducible and citable as prior art. This publication is intended as a defensive disclosure to dedicate these concepts to the public domain and prevent later patenting of substantially similar systems

Multi-Agent Ai For Automated Creation And Quality Assurance Of Cloud Incident Response Playbooks, Nitin Garg, Kunwar Vikas, Lakshmipriya Baskar, Ranjeet Ranjan, Anusha Bansal, Heer Mehta, Varun Bhardwaj, Savit Gupta

Defensive Publications Series

A trusted partner cloud (TPC) is a cloud deployment model that addresses the sovereignty requirements of governments by building isolated clouds operated by local partners and powered by a commercial cloud services provider. High-quality incident response playbooks are critical to successful TPCs. However, TPC partner operators may have limited skills and tools compared to the commercial cloud services provider. This disclosure describes multi-agent artificial intelligence (AI) techniques for the automated creation and quality assurance of TPC incident-response playbooks. A playbook-creation agent automatically converts playbooks internal to the commercial cloud-services provider to a high-quality, standardized format required for TPC operators. An …

Novel 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 And Processes For The Preparation Thereof, Srinivasan Thirumalai Rajan, Sagyam Rajeshwar Reddy, Kammari Bal Raju, Garai Abhijit, Msn Laboratories Private Limited, R&D Center, Hyderabad, India.

Defensive Publications Series

The present disclosure relates to novel 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 compound of formula-1 and processes for preparation thereof.

Formula-1

Novel Solid State Forms Of (Rr,Ss)-1,3,4,6,7,11b-Hexahydro-9,10-Di(Methoxy-D3)-3-(2-Methylpropyl)-2h-Benzo[A]Quinolizin-2-One And Processes For Preparation Thereof, Srinivasan Thirumalai Rajan, Sagyam Rajeshwar Reddy, Kammari Bal Raju, Garai Abhijit, Msn Laboratories Private Limited, R&D Center, Hyderabad, India.

Defensive Publications Series

The present disclosure provides novel solid state forms of (RR,SS)-1,3,4,6,7,11b-hexahydro-9,10-di(methoxy-d₃)-3-(2-methylpropyl)-2H-benzo[a]quinolizin-2-one and processes for preparation thereof.

(RR,SS)-1,3,4,6,7,11b-Hexahydro-9,10-di(methoxy-d₃)-3-(2-methylpropyl)-2H-benzo[a]quinolizin-2-one is represented by the following structural Formula-1.

Formula-1

System For Llm-Driven Orchestration And Live Migration Of Isolated Software Agents, Johannes Start, John Lunney

Defensive Publications Series

Systems for managing autonomous software agents in distributed environments can be limited by a lack of runtime mobility, rigid communication protocols, and poor observability. An integrated platform for executing software agents can combine isolated agent execution environments for fault containment with a live agent migration module for stateful mobility between host computing devices, such as physical servers or virtual machines. A central communication fabric, which can utilize a large language model (LLM), may mediate inter-agent communication. The LLM can analyze the semantic intent of a request to dynamically generate and execute a multi-step orchestration plan. This approach can support resilient …

Real-Time Preferred Agent Availability Predictions For Enhanced Contact Center Routing, Rajarathinam Chidambaram, Jibin George, Gururaj B T, Riyad Ottayil, Anil Kumar M L

Defensive Publications Series

A novel system and techniques are presented herein for intelligent contact center call routing that leverages a multi-factor, real-time predictive model using live transcript analysis, call complexity, agent historic performance, and scheduling data. When a customer is waiting and their preferred agent is predicted to become available imminently, the system dynamically calculates and applies an optimal wait extension to enable a more meaningful and efficient connection. This approach optimizes routing by combining agent availability forecasting with customer preference and contextual data, resulting in improved call resolution, reduced average handling time, and enhanced customer satisfaction.

Llm-Powered Agents For Context-Aware Validation Of Code And Configurations, Peng Chen

Defensive Publications Series

Enforcing complex, team-specific software development rules that are beyond the scope of some static analysis tools can present challenges, and manual review for such rules may be slow and error-prone. The described techniques may address these challenges by employing automated agents powered by large language models within a code review workflow. These agents can be configured with natural language prompts that codify domain-specific knowledge and complex validation logic. When triggered by a code change, an agent can analyze the modification and its relationship to other relevant files in the codebase. This method can provide automated, inline feedback on adherence to …

Time-Series Forecasting Using Dynamic Covariates From Text-Based Event Extraction, Leonid Kuligin, Thomas Zettl

Defensive Publications Series

Computer-implemented time-series forecasting systems, such as those executing on a server or distributed computing platform, may have difficulty anticipating demand volatility caused by real-world events due to a potential reliance on historical quantitative data. This disclosure relates to systems and methods for adjusting short-term forecasting by processing unstructured text data, for instance from news articles, to identify and quantify events that could influence future demand. A data processing pipeline can use a large language model to extract event descriptions, generate numerical embeddings for those events, and aggregate them into structured features. These features can then be integrated as dynamic covariates …

Solid State Forms Of 2-[4-[[(2r)-2-Ethoxy-3-[4-(Trifluoromethyl) Phenoxy]Propyl]Thio]-2-Methylphenoxy]Acetic Acid Lysine And Processes For Preparation Thereof

Defensive Publications Series

ABSTRACT

Title of the invention: Solid state forms of 2-[4-[[(2R)-2-ethoxy-3-[4-(trifluoromethyl) phenoxy]propyl]thio]-2-methylphenoxy]acetic acid lysine and processes for preparation thereof

The present invention relates to solid state forms of 2-[4-[[(2R)-2-ethoxy-3-[4-(trifluoromethyl)phenoxy]propyl]thio]-2-methylphenoxy]acetic acid lysine and processes for preparation thereof.

The present invention further relates to 2-[4-[[(2R)-2-ethoxy-3-[4-(trifluoromethyl)phenoxy]propyl]thio]-2-methylphenoxy]acetic acid L-arginine represented by the following structural formula-1a and process for preparation thereof.

Formula-1a

The Generative Asset Pipeline: "Live Code Assets" And Local Inference Orchestration, Matthew D. Judson

Defensive Publications Series

Disclosed is a Generative Asset Pipeline for NLE environments. The core innovation is the definition of "Live Code Assets"—executable code modules (e.g., React components, R3F scenes, .tsx files) treated as primary media primitives on the timeline. The NLE rendering engine includes a runtime for executing these modules. The system features "Dynamic Module Loading and Automatic Control Surfaces": it inspects the code asset (e.g., via Zod schema extraction) to identify parameters and automatically generates a visual control interface (Inspector Panel), allowing non-coders to manipulate the asset. The pipeline integrates local AI inference engines (e.g., ComfyUI) via the "Flow Workspace," orchestrated as …

The Agentic Nle Interface: System-Wide Copilot With "Rag On The Timeline" And Direct Tool Execution, Matthew D. Judson

Defensive Publications Series

Disclosed is an Agentic NLE Interface featuring a "System-Wide Copilot" with deep context awareness and direct tool execution capabilities. The core innovation is "RAG on the Timeline," a local Retrieval Augmented Generation pipeline focused on the NLE timeline state (OTIO). The application continuously vectorizes the OTIO state (structure, metadata, semantic content) into a local vector database. This enables the AI Copilot to understand the project context and answer semantic queries ("Find the shot where..."). The RAG pipeline integrates Vision-Language Models (VLMs) for analyzing current frame pixel data. The Copilot functions as an agent with access to executable tools mapped to …

"Live Otio": Decentralized Nle Timeline Synchronization Via Opentimelineio And Rga Crdt Mapping, Matthew D. Judson

Defensive Publications Series

Disclosed is a method for decentralized, real-time synchronization of Non-Linear Editor (NLE) timelines by mapping the OpenTimelineIO (OTIO) schema to Conflict-Free Replicated Data Types (CRDTs). The core innovation is the specific application of the Replicated Growable Array (RGA) algorithm (e.g., via Automerge) to manage the temporal sequence of clips in an OTIO Track. RGA avoids array indices, instead using persistent UUIDs and relative positioning ("Insert Clip B after UUID-A"). This mathematically guarantees convergence and solves the "index shifting" problem inherent in concurrent timeline edits, enabling offline-capable collaboration without central servers. The system defines a direct isomorphism between OTIO components and …

The "Neo-Nle" Hybrid Architecture: Unifying Generative Ai Synthesis And Deterministic Media Assembly, Matthew D. Judson

Defensive Publications Series

Disclosed is the "Neo-NLE" (Next-Generation Non-Linear Editor) architecture, a hybrid system unifying traditional deterministic video assembly workflows with generative AI synthesis within a decentralized, local-first framework. The core innovation is the seamless integration of "Assembly Workspaces" (optimized for deterministic playback) and "Generative Workspaces" (for AI synthesis and code execution) within a single application. Both layers operate on a shared, decentralized data fabric (KTKN-OS/Automerge), enabling real-time interaction between generated assets and the assembly timeline. The architecture mandates a Local-First implementation, ensuring zero-latency interaction and data sovereignty, with P2P synchronization eliminating centralized cloud reliance.

Project Chimera: Real-Time Disaster Resilience Simulation Platform (Digital Twin), Matthew D. Judson

Defensive Publications Series

Disclosed is Project CHIMERA, a real-time simulation platform (Digital Twin) for testing the resilience of decentralized infrastructure (DePIN) during disaster scenarios.10 The integrated simulation engine combines high-fidelity geospatial data (DEM) with real-time environmental simulations (e.g., hurricanes) and infrastructure failures (power outages). The core innovation is the high-fidelity simulation of decentralized network dynamics (e.g., ChurchMesh/LoRa), including accurate RF propagation physics based on terrain, node failures, and dynamic message routing. The platform functions as a strategy evaluation tool, scoring infrastructure deployment strategies based on Coverage, Uptime, and Cost Efficiency within the simulated disaster.