Alan Jacobson

Systems and Methods for Automatic, Loss-Less Data Management of Context Windows and Persistent Memory in AI System

Modern artificial intelligence systems, particularly large language models (LLMs), remain fundamentally constrained by how they manage, retain, and retrieve information across time. Although these systems are capable of producing fluent, context-aware output within a single conversation, their ability to sustain continuity, accuracy, and coherence across extended interactions is limited

Notice Integrity: systems and methods for governed proactive notification by runtime‑enforced AI sub‑agents operating under a governance registry (e.g., a Trust Integrity Stack) and a runtime governor (e.g., Trust Enforcement)

Artificial intelligence systems increasingly engage users across health, finance, education, transportation, home automation, and personal productivity. As these systems shift from reactive tools to autonomous agents capable of anticipating needs, there is a growing requirement for proactive notifications that are not merely triggered—but governed. No matter the domain, the

Systems and methods for assigning value to ungated input (AVUI)

Modern AI systems increasingly rely on large volumes of mixed data: highly structured fields (such as form inputs and database columns) and loosely structured or unstructured “ungated” inputs (such as voice, free-text prompts, uploaded documents, URLs, behavioral signals and contextual logs). In many deployments, the majority of the useful

Systems and Methods for Deploying an Attentive Modulator and Dynamic Oversight Layer

Artificial intelligence (AI) systems are increasingly relied upon for a wide range of tasks, from customer support and medical analysis to financial decision-making and software development. As these systems become more complex, and the consequences of erroneous or hallucinated outputs grow more severe, the need for runtime governance mechanisms

Systems and Methods for Generating, Persisting, and Propagating User-Specific AI Behavior Profiles

The present disclosure relates generally to digital assistants and human–computer interaction, and more specifically to systems and methods for capturing, persisting, and enforcing user preferences and policies governing assistant behavior, including in voice-driven interfaces. State of the Art Over the past decade, digital assistants have become widely deployed

Systems and Methods for Revenue-Linked Metering and Policy-Aware Governance of Modular Cognition (AI$)

Software and online services have historically relied on a small number of familiar revenue models. Early enterprise software was typically sold as perpetual licenses with maintenance contracts. As delivery moved to the web, subscription models became dominant: customers paid a fixed monthly or annual fee per seat or per account,

PersistentMemory: Systems and Methods for Modular Cognition with Vertical Memory and Policy-Aware Context Assembly

Modern large language models (LLMs) and conversational AI systems remain fundamentally limited by the way they handle memory across time. Out of the box, most LLMs operate as stateless systems: they remember only the portion of an interaction that fits within the model’s context window, and all information outside

Don’t let your primary profile photo be a dealbreaker. The traps to avoid:

Your primary profile photo isn’t the only thing in your profile. But it’s the first and only thing people see in the first screen of data…

How to take the ultimate primary profile photo. Everything depends on it.

Your primary profile photo is the most important part of your online dating profile.

Put these photos in your profile. What to leave out will surprise you.

There is no need to slave over an album of profile photos. But these photos are essential to your success with dating apps. Here’s what I…

New user interface for ChatGPT

A technically correct answer can still be worthless. When companies pay for the tokens that produce it—and the employee time spent trying again—that’s an ROI problem. Poor prompts contribute to that waste. But why should users bear all the responsibility for getting the question right? That’s

AI needs its Model T

Henry Ford didn't bring automobiles to the masses by teaching millions of people to become automobile experts. He built a car millions of ordinary people could use. * The Model T democratized the automobile. * Today, the AI model is the transformative technology we're trying to democratize. Today&