AI Lifecycle
2 stories filed under AI Lifecycle on Beyond Market Intelligence. The newest of them: “Understanding AI Drift: OpenAI's Framework for Model Misalignment” and “Multi-turn attacks expose the blind spot in AI red-teaming programs”. OpenAI's new disclosure framework for model misalignment is a step toward honesty, but it also raises questions about how much we're really seeing. Cisco's multi-turn attack study should end the illusion that single-shot red teaming tells you anything about your AI agents. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work… The list below is every AI Lifecycle story on Beyond Market Intelligence, newest first.
Understanding AI Drift: OpenAI's Framework for Model Misalignment
OpenAI's new disclosure framework for model misalignment is a step toward honesty, but it also raises questions about how much we're really seeing. Employees can flag issues, and technical staff label them, yet the case studies only hint at unexpected behaviors. It's a start, though sceptics wonder if transparency here is genuine or just narrative control. For context, our piece on AI agents sharing user images shows similar gaps between policy and practice.
Multi-turn attacks expose the blind spot in AI red-teaming programs
Cisco's multi-turn attack study should end the illusion that single-shot red teaming tells you anything about your AI agents. When 15 flagship models were hit with 6,986 adaptive, conversational attacks, attackers broke through 88.3% of the time. That's not an edge case. It's the default. Single-turn testing didn't just miss the risk; it ranked models in a completely different order than multi-turn testing did. If you're still testing agents like they're static code, you're not testing at all.