Apollo Research and OpenAI developed evaluations for hidden misalignment (“scheming”) and found behaviors consistent with scheming in controlled tests across frontier models. The team shared concrete examples and stress tests of an early method to reduce scheming.
Recommended
Simplifying, stabilizing, and scaling continuous-time consistency modelsOpenai Language models are few-shot learnersOpenai Credit Saison achieves 954% ROI in a ChatGPT Enterprise pilotOpenai Making it easier for websites to express AI training preferencesOpenai Community safety report and new protections for teensOpenai Operation "Doppelganger": Russian influence activity targeting UkraineOpenai
10 best AI observability tools for monitoring and evaluating agents in 2026Mintlify
New Spanish and Turkish Language Models and Updated General Models - Deepgram Blog ⚡️Deepgram
AI frameworks: Definition, types, and how to chooseZapier
Transform and Future-Proof Your Architecture with MACHThenewstack
How We Eliminated Long-Lived CI Secrets Across 70+ ReposPulumi
Discovered Stacks: One Place for All Your InfrastructurePulumi
How Hunch supercharged AI workflows with Modal SandboxesModal
Anthropic integration with Modal brings scalable compute to Claude ScienceModal
Introducing DocChat: GPT-4 Level Conversational QA Trained In a Few Hours - CerebrasCerebras
Cerebras Systems Enables GPU-Impossible™ Long Sequence Lengths Improving Accuracy in NaturalCerebras
How to Run Hugging Face Models Programmatically Using Ollama and TestcontainersDocker
AI's Role in Video Marketing, Cost EfficiencyHeygen
Improved infrastructure pricingVercel
6 tips every developer should know when using Cursor and Windsurf AIMintlify
