Net-Interactive Documents - Generative Pre-trained Transformer

(NIDGPT)

 URL:  https://nid-library.com/gpt https://www.austria-forum.org 

We are introducing a new NID module that empowers its users to leverage the capabilities of generative AI. This feature makes use of completely localized Large Language Models (LLMs) and vector embedding stores to generate answers to users queries based on information available in NID library and Austria-Forum. This creates a cutting edge yet secure environment to encode the semantic meaning and context of text, allowing LLMs to understand context and judge similarity when returning answers to query prompts.

At the moment we are testing various embedding schemes and LLMs for optimal results. We are also exploring how effective the system performs on standard CPU servers and value additions in form of GPU based NID hosting infrastructure.

At the moment only limited document sources from NID are being added to NID-GPT vector store once the module matures the functionality will be extended to a larger dataset available in NID and Austria-Forum repository.

We believe that a well-curated knowledge base for a GPT system or a Retrieval-Augmented Generation (RAG) application can significantly enhance information access and its practical use. Addition of LLM powered module not only will facilitate the information access in this cutting edge way but will also extend NID systems capabilities in terms of keyword detection, automated linking of contents, translations etc. 

Besides the Retrieval Augments Generation (RAG) module, the LLM locally available in NID will be put to task to perform the following additional functions for our upcoming NID applications.

Automated Content Generation summarization, linking
LLMs can automatically generate summaries for complex topics and large documents (e.g., climate change, nuclear energy) or suggest relevant sources. This reduces the workload for moderators when creating foundational content and ensures discussions start with evidence-based information. LLMs can quickly analyze existing contributions in AF and NID library and propose logical outlines or counterarguments to promote balanced discussions.
Moderation Support
LLMs can be used for sentiment analysis detecting hate speech, or obvious misinformation. Suspicious contributions are flagged for manual moderator review. For polarizing topics (e.g., migration, nuclear power), LLMs alert moderators to potential biases in annotations or provide sentiment analysis reports.
User Interaction & Assistance
An LLM-powered chatbot (NID GPT system with a more comprehensive knowledge store) helps can users draft annotations by suggesting clearer phrasing or such AI chatbots generate instant answers to common questions about discussion topics.
Dynamic Discussion Analysis
Extended and more modern multimodal LLMs can analyze discussion threads to identify recurring arguments, knowledge gaps, or controversies. These insights help moderators create targeted educational content. Capable AI systems can also automatically generate mind maps or argument networks to visualize debate progress, making complex topics (e.g., pros/cons of nuclear energy) more accessible.
Personalization & Accessibility
LLMs can also translate contributions into plain language or other languages to improve accessibility.
Integration with existing NID features
LLMs suggest cross-references between NID documents (e.g., linking a CO₂ storage section and potential hazards to lithium mining discussions). This can be called Transclusion 2.0 in NID. An LLM powered AI chatbot can explain NID features (e.g., creating annotations, applying filters) to new users in real-time (NID GPT already provides the guidance to some extent).
Risks & Limitations
AI/LLMs do not replace experts however they can certainly assist the moderators by offering the right information and timely responses; the information/contents generated by AI must be validated by moderators and feedback system for NID administrators about incorrect data can help eliminate the bias or hallucinations in any generative AI systems.
NID with the right AI assistive tools will serve as a cutting-edge platform combining expert authority with public engagement, capable of presenting/managing "complex and sensitive" debates through transparency, moderation, and interdisciplinary collaboration.

How it works!!

Ask Questions in NID GPT interface / “Fragen” button on right-side of Austria-forum

1. In order to ask a question, type a question into the search bar like: 
2. What is NID Library System 
3. Hit enter on your keyboard or click Ask! 
4. Wait (Please be patient!!) while the LLM model consumes the prompt and prepares the answer. Currently, the system's processing is offloaded to the local CPU and a modest onboard GPU. In the future, adding a more powerful GPU cluster will enhance the system's response time and capabilities. 
5. Once done, it will print the answer and the 4 sources it used as context from your documents; you can then ask another question without re-running the script, just wait for the prompt again.

 Warning:   This module is under development and going through continuous changes, the service may go down without any prior notice.

NOTE: All such systems do not give guaranteed correct answers, see the paper on AI Hallucinations.