At Invariable, we don't just modify Large Language Models (LLMs); we redefine them, focusing on increased security, reduced errors, and enhanced performance.

1. Pre-Logic & Post-Logic

We begin by implementing logical rules before and after the AI process. This bookended approach ensures that the AI stays within predetermined boundaries, guaranteeing the reliability of every output.

Pre-Logic: Sets the stage by defining parameters that the LLM should follow.
Post-Logic: Scrutinizes the AI output to ensure it adheres to predefined logic and safety guidelines.

2. Training on Smaller Fixed Data Sets

Traditional LLMs are trained on vast, open-ended datasets, making them versatile but prone to errors. Our Alpacas are trained on smaller, focused data sets to ensure relevance and accuracy.

3. Enforcing Personas

Our SLMs come with inbuilt personas, facilitating more specific and human-like interactions. Whether you want a customer service agent or a data analyst, our Alpacas can mimic the role effectively.

4. Prompt Manipulation

We optimize the queries fed into the model, ensuring that the LLM understands the context better, thus providing more accurate and targeted responses.

5. Fixed Data Set Generation

Our experts curate data sets that are free from noise and irrelevant variables, thus reducing the room for errors or biases. This ensures that our SLMs operate on the highest quality data.

6. AI & Human Verification

Finally, we employ a dual verification system:

AI Verification: Automated checks for accuracy and security.
Human Verification: Experts vet the final output, serving as the ultimate layer of quality control.

Unveil The Power of SLMs

Steer clear of the limitations of conventional LLMs and embrace the unparalleled precision of our SLMs. With Alpacas, you're not just choosing a smarter AI; you're choosing an AI that's smarter in the ways that matter.

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