‘Guardrails AI’ and ‘Guardrails Hub’: AI Development Assistant for Superior Models

Inaccurate information and bias can pose significant challenges for large language models (LLMs) or generative AI (GenAI) platforms. San Francisco-based ‘Guardrails AI’ is tackling this problem with Guardrails Hub, an open-source project aimed at improving the security and credibility of AI applications. Addressing these challenges is critical to ensure the development of AI efficiency and reliability in the future.

Why Are Modern AI Challenging?

Generative AI offers immense potential, but challenges remain. These include the generation of incorrect or misleading results, referred to as ‘hallucinations’. Imagine a health insurance chatbot giving inaccurate medical advice or a chatbot service promoting a competitor's product. Such faulty information can have serious consequences, potentially causing harm, inciting violence or fueling discrimination and conspiracy theories.

Guardrails AI: Safeguarding AI’s Credibility with Guardrails Hub

Guardrails is comparable to a trust and verification system for AI applications, it achieves this goal by utilizing 2 functions:

• 1. Identify and Find Solutions: Guardrails acts as a watchdog, inspecting input and output data of AI applications, in order to identify potential issues that could affect credibility, such as biased data, nonsensical information or security vulnerabilities.

• 2. Regulate LLM: Large Language Models (LLMs) that can generate vast amounts of information, but the complexity can make it challenging to use effectively. Guardrails can manage data by structuring and organizing LLM outputs, rendering the structure more coherent and user friendly.
  

                                                                               Photo credit: www.guardrailsai.com

Guardrails Consists of Two Main Components:

• 1. Guardrails integrated into user AI applications: Is the component functions as a built-in monitoring system, constantly checking for potential issues

• 2. Guardrails Hub: Is similar to an online information resource with its own separate pre-built components called "Validators" that target specific risks in AI applications. Users can combine these Validators to create a customized and powerful examiner. Guardrails Hub also provides a list of all validators with detailed descriptions.

How Does Guardrails Hub Work?

Guardrails Hub is an open-source platform similar to a developer community, fosters the creation of even more rigorous inspection tools. It achieves this through the following processes:

• Create and Distribute Validators: Developers can create and share inspection tools called Validators. These Validators examine the authenticity of data used in AI applications, preventing issues such as incorrect information, violations of regulations and standards, and the use of unsafe code.

• Focus on Collaboration: Guardrails Hub's open-source platform encourages collaboration. Developers can share their Validators, which in turn helps others expand their AI models and improve Generative AI efficiency.

• Safer with Crowdsourcing: Guardrails AI leverages a crowdsourced developer community to collaboratively build a more secure and reliable Generative AI ecosystem.

What Issues does Guardrails Solve?

• Boosting AI Credibility: empowers Generative AI developers to build models that are safer, more trustworthy and reliable.

• Boosting Confidence: Ensure Generative AI model can generate results based on accurate information, while adhering to regulations and high security standards."

• Boosting Collaboration: Unite developers to collaborate, build tools and techniques for a more secure Generative AI.

How does Guardrails Hub Boost AI Credibility?

Guardrails Hub is a platform for developers to easily develop, share and utilize inspection tools called validators. This open-source platform already contains over 50 pre-made validators contributed by both Guardrails AI and the community.

What are Validators on Guardrails Hub?

Validators are the basic components of Guardrails Hub, inspecting the outputs of Large Language Models (LLMs) for accuracy and potential biases. This prevents end users from receiving incorrect or unsafe results.

Validators, acting as building blocks for developers, help them construct robust security systems that enhance the credibility of AI applications. Validators achieve this by thoroughly examining data authenticity and identifying potential security vulnerabilities, ensuring efficient operations and reliable results.

The Benefits of Guardrails Hub

• Create Validators to Prevent Mistakes and Boost AI Credibility: Guardrails Hub isn't just a tool repository; it's comparable to a validator factory for AI. Developers can build custom Validators to fit their needs, using either simple rules or complex machine learning algorithms. These Validators can detect and improve issues like bias, inaccuracy, and the risk of violating regulations.

• • Examples of Validators:
    • Filtering out impolite messages from chatbots
    • Ensuring that AI models processing loan applicant’s health data comply with the Personal Data Protection Act (PDPA)
    • Analyzing AI outputs to prevent discriminatory outcomes, such as job recommendations based on sex or gender.

• Creating Validators Repository Together to Increase AI’s Sector Credibility: Guardrails Hub isn't just a repository for pre-made validators; it's also a collaborative space for all developers to share with the entire community within the Hub, benefiting everyone.

• Reusing Existing Validators: Guardrails Hub is not just a repository for validators; it's a valuable tool that helps developers save time on AI development. The Hub offers a library of over 50 pre-built validators that developers can easily reuse.  This not only speeds up the development process but also helps ensure the resulting AI applications are safe and credible, meeting high standards.

• Customizing ‘Guards’ From Validators Repository: Developers can combine Validators like building blocks to create custom “Guards” that adjust credibility standards. These Guards tailor security measures to the specific risks and needs of each AI application, enhancing both flexibility and efficiency for developers.

• Enforcing Standards of Credibility for AI: "Guards" act as enforcers for the credibility standards set by developers. These Guards are built by combining validators, allowing developers to define specific boundaries for security and efficiency within their AI applications, ensuring that the AI operates according to predetermined ethical and regulatory frameworks, ultimately reducing the risk of unforeseen consequences.

• Example of Guards in use:
• Prevent chatbots from responding impolitely.
• Prevent insurance AI from approving a contract without thoroughly investigating the insured first.

Additional example of Validators in use:

• Verify the authenticity of information summarized by AI.
• Ensure chatbots communicate within the context of specific brands.
• Make sure the AI operation does not violate regulations.

Guardrails AI Secured $7.5 millions in investment

Guardrails AI has secured a significant investment of $7.5 million to accelerate the expansion of the team and Guardrails Hub project. This funding round was led by Zetta Venture Partners, a leading venture capital firm focused on the AI sector.  Joining Zetta were prominent names in the AI community, including Bloomberg Beta, Pear VC, Factory, and GitHub Fund. Additionally, renowned AI experts Ian Goodfellow and Logan Kilpatrick participated in the fundraising.

Summary

Guardrails AI is a groundbreaking platform that empowers various companies to confidently utilize modern AI. This empowerment comes through Guardrails Hub, an instrumental open-source community for developers. Guardrails Hub provides the resources and collaboration needed to build credible, safe, and feasible next-generation AI models.

Sources:

https://www.finsmes.com/2024/03/guardrails-ai-raises-7-5m-in-seed-funding.html  

https://www.thesaasnews.com/news/guardrails-ai-closes-7-5-million-in-seed-round  

https://techcrunch.com/2024/02/15/guardrails-ai-builds-hub-for-genai-model-mitigations/

https://www.guardrailsai.com