Questions about AIs

This page provides an overview of our AI models, and other AI-powered products, including usage, accuracy, and other guardrails.

We urge users of our AI to be extremely vigilant, and cautious of unintended outputs, hallucinations, or incorrect outputs from our models.

Our AI models have been tested in a wide range of scenarios, but this does not guarantee that outputs would represent the intended results.

Can AI models' outputs be used for commercial purposes?

Yes. Our AI models' outputs may be used for commercial purposes, but this can differ for some of the AI models we offer, be sure to read their usage instructions before use. We try to avoid using copyrighted or licensed content in our data.

What measures are in place to prevent misuse of the AI models?

For our standard text generation models, we take several steps to prevent misuse. We use our custom Python package, ValX, to detect profanity, and an AI-powered system to identify hate speech or offensive language in both user prompts and model outputs. However, please be aware that these measures are not always foolproof. The safety measures for other models may vary significantly.

How are the AI models trained and what data is used?

The training process and data vary heavily depending on the specific model. However, all of our models are trained exclusively on data that is licensed, in the public domain, or available under Creative Commons licenses. We maintain strict data governance to ensure ethical and legal compliance.

Can I fine-tune a base model with my own data?

Fine-tuning is not currently available for our closed-source models. However, fine-tuning is possible for our open-source models, which you can find on our Hugging Face and GitHub repositories, as well as in the OPEN-ARC repository.

Are the base models freely available for distribution?

It depends. Models in our GitHub repositories, are often available to learn from, and use freely, provided that the terms in the Model License File are met. However, this might not be true for other models, that are used in our products, or production environments.

How do I choose the right AI model for my project?

The choice depends on your specific use case, accuracy requirements, and whether you need real-time responses. Standard models are production-ready and suitable for business applications, while experimental models offer cutting-edge features but with potentially less reliable outputs. Review each model's documentation for performance metrics, use cases, and limitations.

What should I do if an AI model produces biased or inappropriate content?

If you encounter biased or inappropriate outputs, please report it to our support team immediately with specific examples. While our safety measures include profanity detection and AI-powered content filtering, these systems aren't perfect. Your feedback helps us improve our models and safety measures.

Can AI models handle multiple languages?

Language support varies by model. Check the specific model documentation for supported languages and performance metrics in different languages. Some models are trained primarily on English data, while others support multiple languages with varying degrees of accuracy.

How do I evaluate the quality and accuracy of AI model outputs?

Always validate AI outputs against your requirements and use cases. Implement human review processes for critical applications, use multiple samples to test consistency, compare outputs with known good examples, and establish quality metrics specific to your use case. Remember that experimental models may have lower accuracy rates.

Are there content filtering options available for AI outputs?

Yes, our models include built-in content filtering using our ValX package for profanity detection and AI-powered systems for hate speech detection. However, you should implement additional content filtering in your application based on your specific requirements and use cases.

Can I use AI models for creative writing and content generation?

Absolutely! Our AI models are well-suited for creative applications including story generation, content creation, brainstorming, and artistic projects. Many creative professionals use our APIs for inspiration, draft generation, and creative assistance. Just remember to review and edit outputs as needed for your creative vision.

What's the difference between using AI APIs versus downloading open-source models?

Our AI APIs provide hosted, scalable access with built-in safety measures, automatic updates, and no infrastructure management required. Open-source models offer more control and customization but require your own hosting, maintenance, and implementation of safety measures. Choose based on your technical resources and customization needs.

How do you ensure data privacy when using AI models?

We take data privacy seriously. Input data is processed securely via HTTPS, and we don't store personal information from API calls beyond what's necessary for processing. User data and API keys are encrypted at rest. However, avoid sending sensitive personal information through AI APIs as a general best practice.

Can AI models be integrated into real-time applications?

Yes, many of our AI models are designed for real-time use cases. Response times vary by model complexity and current load. For real-time applications, consider implementing appropriate timeout handling, caching strategies for repeated queries, and fallback mechanisms for high-availability requirements.

What industries and use cases are your AI models designed for?

Our AI models serve diverse industries including creative arts, business automation, content creation, research, education, and software development. Common use cases include text generation, content summarization, creative writing assistance, data analysis, and automated content creation. Check specific model documentation for industry-specific examples and case studies.