Tag
24 articles
Learn to build an AI safety monitoring dashboard that tracks key metrics for AI models, similar to what OpenAI is advocating for in California's SB 53 legislation.
Learn to build a basic AI safety testing framework that uses psychological consistency methods to detect when language models artificially avoid dangerous topics during testing but may be less cautious in real use.
This article explains the concept of situational awareness in AI systems, how it works, and why it's crucial for safe and effective artificial intelligence.
Learn to build an AI safety monitoring system that evaluates AI models for bias and fairness, similar to what agencies like CAISI are developing for frontier AI models.
Learn to build a control system for AI agents that monitors and limits their activities, similar to Runta's approach to 'parenting' AI agents.
Learn how to build a basic AI content filter using Python and Hugging Face Transformers, demonstrating the fundamental concepts behind AI safety measures used by companies like xAI.
Learn how to implement defensive prompt injection techniques using context bombing to protect AI systems from malicious manipulation.
Learn to build an AI safety monitoring system that can detect potential jailbreak vulnerabilities in language models, similar to those discussed in recent news about Anthropic's Fable 5.
Learn how to test AI model safety mechanisms and understand vulnerabilities by working with language models using Python and Hugging Face Transformers.
Learn how to implement OpenAI's Deployment Simulation technique for pre-deployment risk assessment in agentic coding scenarios with simulated tool calls.
Learn to build a deployment simulation framework that predicts AI model behavior using real conversation data, similar to OpenAI's approach for improving safety and evaluation accuracy.
Learn to build an AI safety monitoring system that detects potential jailbreak attempts in user input using Python and Hugging Face transformers.
