Florida Patent of the Month – January 2026

Strategic Overview

The digital landscape is currently witnessing a fundamental shift from static information retrieval to dynamic, context-aware interrogation of media. At the forefront of this transition is US Patent 12,524,465, titled “Systems and methods for browser extensions and large language models for interacting with video streams.” Applied for on October 26, 2023, and officially awarded to CurioXR, Inc. on January 13, 2026, this intellectual property has been recognized as the Florida Patent of the Month by the specialist advisory firm Swanson Reed. This designation is not merely ceremonial; it underscores the patent’s critical role in the state’s burgeoning high-tech economy and its eligibility for specific fiscal incentives. This report provides an exhaustive analysis of the invention, emphasizing its real-world impact on education and enterprise, benchmarking it against deep-pocketed competitors like Google and OpenAI, forecasting its future potential in the spatial web, and detailing the precise mechanisms for leveraging R&D tax credits to monetize such innovation.

As video content becomes the primary vernacular of the internet—accounting for the vast majority of global data traffic—the ability to “converse” with a stream in real-time represents a trillion-dollar opportunity. Current interactions with video are passive: play, pause, rewind. US Patent 12,524,465 introduces an active layer, employing a browser extension architecture to intercept video frames, extract semantic features, and utilize Large Language Models (LLMs) to generate context-specific responses. This effectively turns every video frame into a queryable database.

This document serves as a strategic dossier for stakeholders including investors, CTOs, and policy makers. It deconstructs the technical claims of the patent, positions them within the fiercely competitive “Agentic AI” marketplace, and provides a tactical guide to the fiscal compliance required to sustain such high-stakes research and development.

The Architecture of Interrogation: Technical Deep Dive

To understand the valuation of US Patent 12,524,465, one must first dissect the technical “inventive step” that justifies its protection. The patent addresses a persistent bottleneck in multimodal AI: the friction between the video player (usually a closed, rendered stream) and the intelligence layer (the LLM).

The “Over-the-Top” (OTT) Browser Extension Model

The genius of the invention lies in its delivery mechanism. Rather than building a new video player or a proprietary hosting platform, CurioXR has patented the method of using a browser extension as a middleware layer.

The Dominance of the DOM

Modern web browsers render video via the HTML5 <video> tag or within Canvas elements. A browser extension has privileged access to the Document Object Model (DOM). This allows the patented system to:

• Inject UI Elements: Overlay buttons or “hotspots” directly onto the video player without requiring the video host (e.g., YouTube, Netflix, Coursera) to modify their code.
• Read State: Access metadata such as the video title, current timestamp, and closed captions, which are crucial for grounding the AI’s responses.
• Capture Frames: Programmatically snapshot the rendered video buffer.

This architecture ensures platform agnosticism. The technology is not “YouTube AI” or “Vimeo AI”; it is “User-Centric AI” that functions on any URL. This decoupling of the intelligence from the content host is a significant strategic moat, preventing platform lock-in.

The Core Interaction Loop: Claim Analysis

The patent’s independent claims describe a sophisticated sequence of operations that differentiates it from simple “screen recording” tools. Based on the patent classification (G06N) and snippets, the workflow proceeds as follows:

• Event Listeners & Interaction Detection: The system does not waste computational resources analyzing every frame (which would cost small fortunes in API tokens). Instead, it “determines participation in an interaction function”. This implies a listener that waits for a specific user intent—a click, a gaze dwell (in XR contexts), or a hotkey press.
• Selective Frame Extraction: Upon triggering, the extension captures the specific video frame. In technical terms, this likely involves drawing the current state of the video element to an off-screen HTML Canvas and encoding it (e.g., to Base64 or a Blob).
• Feature Identification & “Visual Prompting”: This is the core of the intellectual property. Sending a raw image to an LLM like GPT-4o is useful, but often lacks context. The patent describes “identifying one or more features within the image” and “generating a prompt based on the identified features”.
  • Contextual Injection: The system likely combines the visual data with the video transcript (if available) and the user’s click coordinates.
  • Example: If a user clicks on a beaker in a chemistry video, the prompt isn’t just “What is this image?”; it is “The user clicked at coordinates (x,y) on a frame from a video titled ‘Titration Basics’. Identify the object at (x,y) and explain its function in the context of titration.”
• LLM Inference & Overlay: The prompt is sent to the LLM, and the textual response is generated. Crucially, the patent covers “causing display of the textual response within the interaction function”. This means the answer appears inside the video player, maintaining the user’s immersion and preventing the “tab switching” fatigue that plagues current educational workflows.

Technical Hurdles and Solutions

The implementation of such a system involves solving several non-trivial engineering challenges, which likely form the basis of the “Process of Experimentation” required for R&D tax credits (discussed in the R&D Tax Credit Analysis section).

• Latency vs. Accuracy Trade-off: Real-time video interaction requires sub-second responses. However, multimodal LLMs are computationally heavy. The patent likely covers methods for optimizing this, such as using smaller, faster “vision-only” models to identify objects (e.g., YOLO or CLIP) before engaging the larger “reasoning” LLM.
• Video DRM (Digital Rights Management): Platforms like Netflix use Encrypted Media Extensions (EME) to prevent screen scraping. A significant technical challenge for CurioXR would be ensuring the extension can capture frames from protected streams without violating DRM, perhaps by interacting with the browser’s compositing layer rather than the video element itself.
• Context Window Management: Video is data-dense. Sending a continuous stream of frames would overflow any LLM’s context window. The patent’s focus on interaction-triggered capture is a specific solution to this, acting as a “gating mechanism” for information flow.

The Innovator Profile: Ethan Fieldman and CurioXR

The commercial viability of a patent is often inextricably linked to the track record of its inventor. Ethan Fieldman is not a speculative entity but a seasoned operator in the Florida educational technology ecosystem.

From Study Edge to CurioXR

Ethan Fieldman founded Study Edge in 2005, a company that pioneered “supplemental instruction” via video for college students. This background provides critical context:

• Domain Expertise: Fieldman understands the limitations of passive video learning. Study Edge’s success was built on high-quality content; CurioXR addresses the interaction with that content.
• Pivot to Platform: The transition from Study Edge (content) to CurioXR (tech platform) represents a scalable pivot. Instead of making videos, CurioXR makes all videos better.
• XR Ambitions: The company name (CurioXR, formerly VR-EDU) and Fieldman’s other patents (e.g., US 12,347,009 regarding avatars) suggest this browser extension is a stepping stone. The ultimate vision is likely Spatial Computing—where the “video stream” is the user’s view of the real world through a headset.

The Florida Innovation Corridor

The awarding of the Florida Patent of the Month by Swanson Reed highlights the state’s strategic focus on the “I-4 Corridor” (Orlando-Tampa-Gainesville) as a hub for simulation, training, and AI.

• Institutional Support: Fieldman’s work often intersects with the University of Florida and the Cade Prize for Innovation.
• Economic Strategy: Florida offers specific incentives for “Target Industries” including Information Technology and Simulation. This award signals to investors that CurioXR is aligned with state economic priorities, facilitating access to grants and tax credits.

Competitive Benchmarking: The Battle for the Interface

The “AI Video Understanding” market is crowded, but US Patent 12,524,465 carves out a specific niche. The key distinction is between Platform-Native solutions (Walled Gardens) and Overlay solutions (User-Agonistic).

The Walled Gardens: Google and OpenAI

Major tech giants are integrating video understanding directly into their platforms.

• Google (YouTube/Gemini): Google has deployed “Ask about this video” features for YouTube Premium users.
  • Mechanism: Google indexes the video on their servers. The AI analyzes the pre-indexed data.
  • Limitation: It only works on YouTube. It does not help a student watching a lecture on a university’s proprietary Blackboard player or a corporate employee watching a compliance video on Vimeo.
  • Patent Contrast: CurioXR’s browser extension model works universally, giving it a “Swiss Army Knife” advantage.
• OpenAI (Sora/GPT-4o): OpenAI provides the raw intelligence (the API).
  • Limitation: OpenAI generally lacks the “Last Mile” interface for specific video interaction. While they have “Computer Use” agents, these are general-purpose and high-latency.
  • Patent Contrast: CurioXR focuses on the specific workflow of video interrogation, which is a patentable application layer on top of the raw model.

The Agentic AI Insurgents

A new wave of “Agentic” browser tools (e.g., Mariner, various Chrome extensions) is emerging.

• The “Generalist” Problem: Tools like “Project Mariner” or “Comet” attempt to do everything—browse the web, book flights, read emails. As noted in research snippets, these generalists often fail at specific, nuanced tasks like “drag and drop” or precise frame analysis because they lack specialized logic.
• The CurioXR Advantage: By specializing in video stream interaction, CurioXR avoids the “Jack of all trades, master of none” trap. The patent claims specific methods for handling video data, which implies a higher degree of reliability than a generic screen-reading agent.

Real-World Impact: Verticals of Disruption

While the immediate application is educational, the claims of US 12,524,465 support a much broader commercialization strategy.

Education: The “24/7 AI Preceptor”

The “Two Sigma Problem” posits that 1-on-1 tutoring is vastly superior to classroom instruction. CurioXR democratizes this.

• Use Case: A medical student watching a surgical video.
• Friction: The student sees a specific suture technique but doesn’t know its name.
• Patented Solution: The student pauses, clicks the hand movement. The extension identifies the technique (e.g., “Horizontal Mattress Suture”) and explains why it is being used in this tissue type.
• Impact: This reduces cognitive load and keeps the student in the “flow state” of learning, moving from passive consumption to active inquiry.

Corporate Compliance and Training

Enterprises spend billions on compliance training that employees largely ignore.

• Use Case: Cybersecurity training videos.
• Patented Solution: Instead of a multiple-choice quiz at the end, the video is interactive. “Click on the phishing indicator in this email video.” The extension verifies if the user identified the correct visual element (e.g., a suspicious URL bar) using the LLM’s vision capabilities.
• Impact: True competency verification rather than just “attendance” tracking.

Accessibility: The Visual Interpreter

For the visually impaired, the web is becoming increasingly opaque as it moves from text to video.

• Use Case: A blind user encountering an unlabelled chart in a video.
• Patented Solution: A hotkey triggers the extension to “Describe this frame.” The LLM generates a rich text description (“A bar chart showing Q3 revenue growth of 20%…”), which is then read aloud by a screen reader.
• Impact: This fulfills the promise of the ADA (Americans with Disabilities Act) in the AI era, making video content natively accessible.

Media and Commerce: “Shoppable Everything”

• Use Case: A user watching a home improvement video sees a drill they want.
• Patented Solution: Clicking the drill triggers the extension to identify the model (e.g., “Dewalt 20V Max”) and overlay a price comparison or purchase link.
• Impact: This bypasses the need for content creators to manually tag products, unlocking affiliate revenue from legacy content archives.

Strategic R&D Tax Credit Analysis (Swanson Reed)

The development of the technology underpinning Patent 12,524,465 involves significant financial risk and technical uncertainty. Swanson Reed, a specialist R&D tax advisory firm, provides the framework to recover a substantial portion of these costs. This section details the eligibility requirements for the Federal Section 41 Credit and the Florida R&D Tax Credit, specifically tailored to the nuances of this AI patent.

The Federal R&D Tax Credit (IRC Section 41)

To qualify for the federal credit, the activities undertaken by CurioXR (or any company developing similar AI tools) must meet the Four-Part Test.

Permitted Purpose

The activity must relate to a new or improved business component (product, process, software) intended to improve functionality, performance, reliability, or quality.

• CurioXR Application: The development of the “Browser Extension-to-LLM Bridge” is a new business component. The purpose was to create a capability (interactive video querying) that did not previously exist in the company’s product suite.

Technological in Nature

The research must fundamentally rely on the hard sciences, such as computer science, engineering, or mathematics.

• CurioXR Application: The invention relies on:
  • Computer Vision: Algorithms for feature extraction from video buffers.
  • Distributed Systems Engineering: Managing the asynchronous communication between the browser client and the cloud inference API.
  • Prompt Engineering: The algorithmic construction of prompts based on visual tokens.

Elimination of Uncertainty

At the outset, there must be uncertainty regarding the capability, methodology, or design.

• CurioXR Application:
  • Capability Uncertainty: “Can we capture high-resolution frames from 4K video streams without causing the browser tab to crash due to memory spikes?”
  • Methodology Uncertainty: “Is it better to process frames on the client-side (using TensorFlow.js) to save bandwidth, or server-side for higher accuracy?”
  • Design Uncertainty: “How do we design the overlay UI so it doesn’t obstruct the video content while still being accessible?”

Process of Experimentation

Substantially all activities must constitute a process of evaluating alternatives to eliminate the uncertainty.

• CurioXR Application: This is the most critical area for documentation.
  • Hypothesis: “Using html2canvas will be sufficient for frame capture.”
  • Test: Engineers implemented html2canvas.
  • Failure: The library failed to capture video from cross-origin iframes due to CORS policies.
  • Iteration: The team pivoted to using the Chrome Extension captureVisibleTab API.
  • Swanson Reed Note: Documenting these failures is what proves the credit. If it worked the first time, it wasn’t R&D; it was just engineering.

The “Internal Use Software” (IUS) Trap

A common pitfall for software companies is the “Internal Use Software” exclusion. If software is developed primarily for internal operations (e.g., an internal tool for CurioXR tutors to grade videos), it must meet a higher threshold of innovation to qualify.

• Strategic Advice: It is vital to clearly delineate the “Business Component.”
  • Component A: The consumer-facing extension sold to universities (Qualified).
  • Component B: The internal dashboard for managing user accounts (Likely IUS/Excluded).
  • Swanson Reed’s “6-Eye Review” process (involving engineers, scientists, and CPAs) is designed to segregate these costs accurately to prevent audit flags.

The Florida R&D Tax Credit: A Race Against Time

The Florida Patent of the Month award is a strong indicator of eligibility for the state credit, but the mechanics are distinct from the federal system.

The “Target Industry” Prerequisite

Florida restricts its credit to specific “Target Industries,” including Information Technology, Simulation, and Training.

• Requirement: CurioXR must obtain a Certification Letter from the Florida Department of Commerce confirming they fall into one of these buckets. This is a mandatory precursor to the application.

The “First-Come, First-Served” Mechanism

Unlike the federal credit, which is unlimited, Florida has a statutory cap of $9 million per year.

• The Application Window: The portal typically opens on or around March 20th.
• The Bottleneck: The cap is often reached very quickly.
• Action Plan:
  1. January-February: Finalize Federal Form 6765 (as the Florida credit is based on federal QREs). Secure the Target Industry Certification.
  2. Early March: Prepare the Florida Form F-1120 credit schedule.
  3. March 20 (Launch Day): Submit the application electronically the moment the window opens.

Calculation of the Benefit

• Formula: The credit is equal to 10% of the excess QREs over the base amount (average of the prior 4 years).
• Example:
  • Average QREs (2021-2024): $500,000.
  • Current Year QREs (2025): $1,500,000.
  • Excess: $1,000,000.
  • Florida Credit: $100,000.
• Constraint: The credit cannot exceed 50% of the Florida corporate income tax liability, though it can be carried forward for 5 years.

Leveraging Swanson Reed’s Tools

To manage this complexity, CurioXR and similar firms can utilize specific tools:

• TaxTrex: An AI-driven platform that helps technical staff document their R&D activities in real-time (hypotheses, tests, results), ensuring that the “Process of Experimentation” is captured contemporaneously rather than reconstructed years later.
• Audit Defense: Given the novelty of AI patents, IRS scrutiny is increasing. Swanson Reed’s “6-Eye Review” ensures that the claim is technically sound (reviewed by an engineer) and fiscally accurate (reviewed by a CPA) before submission.

Future Potentials: Beyond the Browser

While Patent 12,524,465 is currently implemented as a browser extension, its claims cover broader “interaction systems,” positioning CurioXR for the next computing paradigm.

The “Spatial Web” (XR) Transition

The “XR” in CurioXR is a clear signal of intent. As users migrate from 2D screens to mixed reality headsets (Apple Vision Pro, Meta Quest), the “browser” becomes the user’s entire field of view.

• The Patent’s Power: The patent protects the method of “identifying an image associated with participation in an interaction function.” In a headset, the “interaction function” is gaze.
• Scenario: A user wearing smart glasses looks at a car engine. They “click” (gesture) on a specific part. The system captures the frame (what the user is seeing), sends it to the LLM, and overlays the repair manual instructions directly onto the physical engine. This is the holy grail of “Just-in-Time” information.

Action Models: From “Read” to “Write”

Current implementations are “Read-Only”—they answer questions. The future is “Write” access (Action Models).

• Potential: The system doesn’t just explain the video; it acts on it.
  • Video: A cooking show.
  • Action: User clicks the ingredients.
  • Result: The extension identifies the items via computer vision and adds them to the user’s Instacart basket automatically. This transforms video from a passive entertainment medium into a direct transactional layer.

Licensing and Acquisition Targets

Given the strategic value of the “interaction layer,” CurioXR is a prime target for acquisition or licensing.

• LMS Giants: Canvas (Instructure) or Blackboard could license this to make their millions of hours of lecture content interactive.
• Browser Vendors: Brave or Opera could integrate this natively to compete with Chrome, offering “AI Vision” as a default browser feature.

Final Thoughts

US Patent 12,524,465 represents a pivotal moment in the evolution of the web. It marks the transition of video from a “black box” of pixels into a structured, queryable data stream. By awarding it the Florida Patent of the Month, Swanson Reed has correctly identified a technology that not only exemplifies technical innovation but also holds significant economic promise for the region.

For CurioXR, the path forward involves aggressive commercialization of the browser overlay model while rigorously leveraging the Florida and Federal R&D Tax Credits to fund the high cost of AI development. For the broader industry, the patent serves as a notice: the interface for AI is not just a chat box; it is the video stream itself. Those who control the interaction layer between the user’s eyes and the video content will define the next decade of digital engagement.