Introducing Trust but Verify: A New Paradigm for Gen Native Application Development

Unlocking trust in AI applications: introducing God rails, an open-source framework for verifying the correctness of large language model outputs.

  • 1. Shrea Rajal, co-founder and CEO of Godral AI, will discuss the need for a new programming paradigm, "trust but verify," in generative AI application development.
  • 2. Shrea has a background in machine learning, previously serving as the machine learning infrastructure lead at Prase and working on self-driving cars.
  • 3. There has been an explosion of AI applications, but many lack proper validation and verification methods, leading to potential issues with reliability and safety.
  • 4. The "trust but verify" paradigm would involve validating and verifying AI outputs, ensuring they are accurate and safe before being used in real-world applications.
  • 5. Validation checks can include testing for specific constraints or properties, while verification confirms that the output meets the desired criteria.
  • 6. Existing solutions like prompt engineering or fine-tuning models may not guarantee accurate results, as language models are known to be sarcastic and may not always follow instructions.
  • 7. Grounding AI outputs in external systems can help improve reliability, especially for code generation applications.
  • 8. Rule-based heuristics, traditional machine learning methods, or high-precision deep learning classifiers can also be used to address basic constraints without requiring the full power of a language
  • 9. For chatbot applications, ensuring every utterance has some leaning in a source of truth, such as an article or document, can help reduce hallucinations and improve correctness.
  • 10. Guardrails are one solution for implementing validation and verification methods in AI applications, providing custom validations, orchestration, and a catalog of commonly used guardrails, as well
  • 11. Guardrails can help prevent issues like financial or healthcare advice, unuseable code, private questions to customers, or profanity in outputs, among others.
  • 12. Shrea encourages developers to explore the GitHub project at Shar r/g guardrails and the Godral AI website for more information on implementing guardrails in their own projects.

Source: AI Engineer via YouTube

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