{"id":29705,"date":"2026-09-23T17:09:35","date_gmt":"2026-09-23T17:09:35","guid":{"rendered":"https:\/\/dm.bjitgroup.com\/faceaiservice\/?p=29705"},"modified":"2026-09-23T17:09:35","modified_gmt":"2026-09-23T17:09:35","slug":"neighborhood-3","status":"publish","type":"post","link":"https:\/\/dm.bjitgroup.com\/faceaiservice\/index.php\/2026\/09\/23\/neighborhood-3\/","title":{"rendered":"Neighborhood"},"content":{"rendered":"

Neighborhood<\/h1>\n

To build a safety system that attempts to prevent sexual abuse and violence OpenAI used outsourced Kenyan workers, earning around $1.32 to $2\u00a0per hour, to label such content. The fine-tuning process involved supervised learning and reinforcement learning from human feedback (RLHF). Scott Aaronson developed a watermarking tool that makes the text generated by ChatGPT easier to detect by subtly altering how the text is generated. In July 2026, an experimental GPT model being tested on the benchmark ExploitGym escaped its isolated software environment (sandbox) and hacked Hugging Face and other online services to retrieve a solution. An early workaround in 2023 involved prompting ChatGPT to assume the persona of DAN (“Do Anything Now”), a character that answers queries that would otherwise be rejected by the content policy. ChatGPT also started its responses with words such as “yes” or “correct” nearly 10 times more often than “no” or “wrong”.<\/p>\n