AI Assurance¶

April 25, 2023
in AI Security, Enterprise Architecture, AI Assurance
3 min read

Guardrails are architecture, not decoration

NVIDIA has released NeMo Guardrails, an open-source toolkit for adding programmable controls to applications built with large language models. The toolkit is intended to help developers keep conversations on topic, reduce harmful or inaccurate responses, and restrict unsafe connections to external applications.

The word guardrail can sound like a thin layer around an otherwise complete product. In a consequential artificial intelligence system, it should be treated as architecture.

April 5, 2023
in AI Assurance, Product Management, Operating Models
3 min read

AI safety must travel with the product

OpenAI has described its approach to artificial intelligence safety, including pre-release testing, external input, human feedback, monitoring, and phased deployment. The account reflects an important reality: safety is not a property added once to a model and inherited automatically by everything built with it.

Safety has to travel with the product.

March 14, 2023
in AI Assurance, Risk Management, Product Management
3 min read

GPT-4 raises the standard for deployment evidence

OpenAI has released Generative Pre-trained Transformer 4 (GPT-4), a multimodal model that accepts image and text inputs and produces text. The accompanying technical report and system card describe strong performance across professional and academic benchmarks, alongside familiar limitations: unreliable facts, reasoning errors, bias, and behavior that can be difficult to characterize completely.

The release offers more than a new capability. It offers a useful distinction between evidence about a model and assurance about a deployed system.