Prominent AI leaders initially called for a pause in developing advanced AI systems beyond GPT-4, but breakthroughs have continued, particularly in smaller open models. Concerns persist about AI's potential to generate harmful or false information, and the lack of understanding of how these models work internally contributes to these fears. However, AI labs claim significant progress in controlling outputs using techniques such as response blocking, supervised fine-tuning (SFT), and reinforcement learning from human feedback (RLHF), which align large language models (LLMs) like GPT-4 and Claude 2 with human values. Companies like Anthropic, Microsoft, and OpenAI are employing advanced content filtering systems to mitigate harmful content, while efforts to specialize large models for specific applications continue. The development of AI safety measures, including industry collaborations and RLHF techniques, underscores ongoing improvements in AI reliability and safety, challenging the notion that we lack control over these technologies.