{
  "$type": "site.standard.document",
  "bskyPostRef": {
    "cid": "bafyreial7wd272kz2izl5trrh2t4xfo2sqa4gl2anddmh7wkw6w7ukchbm",
    "uri": "at://did:plc:pgryn3ephfd2xgft23qokfzt/app.bsky.feed.post/3mkgkcuaxjms2"
  },
  "path": "/t/can-an-ai-have-its-own-internal-ethics-standard-protocol-for-axiomatic-alignment/174927#post_18",
  "publishedAt": "2026-04-26T21:04:02.000Z",
  "site": "https://discuss.huggingface.co",
  "textContent": "Alright, Lance—since you are willing to delve deeper and are curious to truly understand this, let me provide you with a detailed explanation. First, by “we,” I am referring to a research organization led by myself. This organization maintains research centers in two cities and is dedicated specifically to studying the inherent flaws in the current architecture of Large Language Models (LLMs) and exploring how to further optimize them in the future. Your assertion that “current architecture and robustness are two separate matters” is incorrect. In our research, we have clearly demonstrated the critical impact that the underlying architecture of current LLMs has on their robustness—an impact that is fundamental, persistent, and ultimately ineradicable, stemming directly from the inherent issues within that underlying architecture. Furthermore, my earlier mention of “cracking” was merely a broad metaphor; in reality, we possess a wide array of methods to influence current LLMs. Moreover, a significant number of individuals are currently engaged in what is known as “red teaming” to validate the vulnerabilities present in these models.\nApologies for the delayed response; our research efforts have been progressing rapidly of late, as we work on optimizing and developing a new generation of LLM architectures. I hope this explanation helps to clarify things for you.",
  "title": "Can an AI have its own internal Ethics? Standard Protocol for Axiomatic Alignment"
}