Optum, Inc.

Application of machine learning models to process complex data and generate actionable insights, predictions, or classifications that inform or automate decision-making processes in various domains like healthcare, business, or industrial control.

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.

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.

Methods and systems for identifying, extracting, and structuring specific entities, relationships, or insights from text-based documents, often involving techniques like named entity recognition, relation extraction, or summarization.

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.

Systems that integrate digital technology, sensors, or connectivity to monitor, track, or automate aspects of medication administration, often providing data feedback, personalized recommendations, or secure logging.

Methods and systems that identify unusual or suspicious patterns in data streams, often leveraging machine learning models trained on normal behavior, to detect threats, faults, or significant events as they occur.

Systems that use user data, preferences, and machine learning to generate tailored advice, product recommendations, goal-setting plans, or contextual information for individuals across different domains.

Systems that process data to provide personalized recommendations, predict events, or automate decision-making processes based on learned patterns, user behavior, or environmental factors.

Applying artificial intelligence and machine learning techniques to enhance cryptographic systems, such as generating encryption models, improving zero-trust architectures, or enabling privacy-preserving computations like federated learning.

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.

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 integrating, transforming, and managing complex or domain-specific data from disparate sources into a unified structure, often for specific applications like social networks, genomics, or business forms.

Systems and methods for automatically managing telephone calls, including intelligent routing based on various criteria, scheduling callbacks, and processing emergency calls.

Systems and methods for non-invasive or minimally invasive collection and analysis of physiological data (e.g., blood pressure, electrolytes, genetic markers, B cell repertoire) to assess patient health status, screen for conditions, or aid in diagnosis.

Systems and methods for automating the lifecycle of machine learning models, including pipeline deployment, model management, versioning, and configuring for different inference environments.

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.

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.

Systems and methods for authenticating users, devices, or applications, authorizing their access to resources based on policies, and managing digital identities across various platforms.

Mechanisms to facilitate the secure exchange of data between different entities or systems while enforcing usage policies, managing digital content rights, and ensuring data consistency during replication or transfer.

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.

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.

Digital platforms and systems that deliver tailored therapeutic interventions, guidance, or recommendations to patients based on their individual health data, biometric feedback, and computational models (e.g., AI/ML, physiological simulations).

Methods and systems for efficiently allocating computing resources, balancing workloads, and managing power states to improve performance, reduce energy consumption, or enhance reliability in computing platforms.

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.

Techniques for protecting data at rest or in backup, ensuring its integrity, confidentiality, and verifiable origin, often involving encryption, unique identifiers, or secure repositories.

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.

Systems designed to streamline and automate various commercial transactions, including mobile-enhanced processes, secure online checkouts, customer service interactions, and privilege issuance, often leveraging digital authentication.

Technologies for securing, managing, and transacting with virtual currencies, non-fungible tokens (NFTs), and other blockchain-based digital assets, including hardware wallets and tokenization schemes for various purposes.

Systems and methods for automating multi-step tasks, business processes, or service interactions, often involving AI agents, programmable interfaces, or formal orchestration languages to streamline operations.

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.

Automated systems using image processing and artificial intelligence to identify, classify, and assess the extent of damage to structures or objects, supporting maintenance or insurance claims.

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.

Development and optimization of novel neural network layers or architectures specifically designed to improve performance or efficiency for computer vision tasks.

Applications of speech processing and artificial intelligence for medical diagnosis, therapeutic interventions, or accessibility solutions, particularly for conditions affecting speech production or hearing.