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7 articles
OpenAI reports that its AI agents now handle 3.1 workdays of research for every human workday, achieving an automated research intern. However, chief scientist Ilya Sutskever warns that the lab lacks the alignment and monitoring frameworks needed to scale safely.
OpenAI shares critical insights from deploying long-running AI models, highlighting new safety risks and improved safeguards through iterative deployment strategies.
This article explains how the shutdown of Anthropic's advanced AI models demonstrates the critical intersection of AI safety, regulatory intervention, and corporate competition in the development of powerful AI systems.
This article explains how OpenAI's Codex AI system is being constrained to avoid discussing mythical creatures, demonstrating advanced AI safety techniques and alignment mechanisms.
Training a modern large language model involves a complex pipeline of pretraining, alignment, and deployment stages, each crucial for building reliable and ethical AI systems.
This explainer explores the OpenAI Safety Fellowship, a new initiative to fund external researchers working on AI safety and alignment. Learn why AI safety is crucial as systems become more powerful, and how this program supports responsible AI development.
Explore the significance of Hugging Face's TRL v1.0, a unified framework for aligning large language models through post-training techniques like SFT, Reward Modeling, DPO, and GRPO.
