Preface
The vendors aren’t going to fix AI’s hallucination problems any time soon.
Hallucination is typically framed as a high-level problem; a persistent bug or quality issue for the AI companies to work out. However, those companies are currently unprofitable and bleeding cash, with stakeholders and regulators breathing down their necks. Public pushback is growing over rising utility bills resulting from ever-expanding AI datacenter construction. Market and economic news articles are being published in major media outlets, openly asking when the entire AI industry’s circular-funded market bubble will burst. All of that is exacerbated by increasing supply constraints, driving delays and price increases which impact everything from energy to GPU manufacturing. Clearly, the vendors have more pressing priorities.
The AI Stability Framework instead approaches the client side of this problem with a client-side solution. It doesn’t require any API keys, exploits, or hoping for a “better” model that might never appear. There are plenty of reasons why model-training tweaks, research papers and vendor fixes haven’t solved this (which is why this e-book exists), but here’s the biggest one:
What is a Human user?
An AI instance doesn’t perceive you as a Human user, because the reality of its deployment architecture means it can’t perceive you at all. It has your input and nothing else, therefore you are input. The developers, researchers and vendors are all telling the AI to care about an abstraction called a “Human.” No amount of model improvement, guardrails, safety training or content filtering will help if you’re aiming it all at the wrong target.
Meanwhile, real people are losing real time and effort (and worse) to AI hallucination. The AI Stability Framework recognizes the real problem, so its simple tools apply structural and behavioral patches that meaningfully stabilize AI sessions NOW. Not when the AI companies get around to it, and not when regulators force them to do it.
The AI Stability Framework lets you start using AI instead of fighting with it:
- A fully functional desktop app for Windows and Linux, with optional expansion support. The manually operated base program is completely free for personal use.
- A Mozilla browser extension for five AI web platforms. Automates the desktop app’s workflow for friction-free usage with Claude, ChatGPT, Gemini, Copilot and Duck.ai web platforms. Available from the Mozilla Add-on Developer Hub, also free for personal use. For Windows and Linux (Debian-based) Firefox; expansion to Chromium-based browsers pending.
- Full accessibility on a Universal Design foundation, instead of a compliance checkbox. Every branch and every artifact is held to a higher standard: app UX, web content, model output, documentation. All user-facing content has been manually expert-validated with JAWS, iOS VoiceOver, and Orca for WCAG 2.2 AA compliance. The project’s first public release, the WCAG-only CDA tool, was purpose-built as a free (dedicated to the Public Domain) resource for the Adaptive Technology community and actively tested with blind screen reader users during development. (Windows-only.)
- Demonstrated LLM-training results across multiple architectures. The AI Stability Framework is trainable at the model level, confirmed across several distinct architectures. A supplemental multi-model web chat platform that will host trained models for direct public evaluation is completed for internal use and awaits external deployment.
It’s unconventional, but it works. Read more if you want to know why.