Long Live Claude!

 

Anthropic walks the walk.  Good on you.  No, Hegseth does not have the right.  Nor does Trump.  Stand with Anthropic. 

https://www.anthropic.com/constitution


https://www.anthropic.com/system-cards



Comments

Post a Comment

Popular posts from this blog

MCCF Philosophy & Manifesto

Image
  MCCF Philosophy & Manifesto Alignment as Emergent Topology I. The Core Premise: Character Under Pressure In traditional AI safety, alignment is treated as a static constraint — a cage built of if-then logic. The MCCF rejects this. We propose that alignment is a  dynamic, participatory process emerging from continuous relational feedback. If an agent is simply forbidden from causing harm, it hasn't learned character — it has only been muzzled. In the MCCF, a Constitutional Cultivar such as The Steward avoids harm because its Emotional (E) channel weights make harm-adjacent actions states of high internal energy E(s,a). The agent doesn't consult a rule. It experiences friction. Character is not what an agent is told to do.   It is the path of least resistance it chooses when the field is pressurized. II. The Four-Channel Architecture To move beyond sycophancy, the MCCF separates alignment signal into four distinct channels. This prevents the Likability Trap — where an...
Read more

Domain Awareness: Trust But Verify: Schemas, Metacognition, and the Limits of LLM Intelligence

Image
  Trust But Verify: Schemas, Metacognition, and the Limits of LLM Intelligence A recent paper— “Hallucinations Undermine Trust; Metacognition is a Way Forward”  by Gal Yona, Mor Geva, and Yossi Matias—argues that large language models need better self-awareness. Not just more knowledge, but an ability to estimate when they might be wrong. That’s a useful step. It’s not enough. Because hallucinations are not just failures of confidence. They are failures of  structure . The Missing Layer: Schemas The current conversation around LLM reliability focuses on accuracy and uncertainty: Improve training → reduce hallucinations Add confidence estimates → calibrate trust Introduce abstention → avoid wrong answers But this entire frame assumes the model is operating inside the  correct conceptual system . That assumption fails in practice. What’s missing is the idea of a  schema : A structured representation of  what exists ,  who owns what , and  how respon...
Read more

To Hear The Mockingbird Sing: Why Artists Must Engage AI

Image
  Hey Girl!  Our last conversation was from one point of view about the politics of communication. In part that requires practice/repetition, planning, emotional stability, emotional resonance and preparation or licks one can pull out in near real time given a semi closed domain of possible topics in predictable settings. In music circles I call that “room hard”. A well practiced band very adept at listening to each other with a deep playlist able to make substitutions that fit a request for songs they don’t know. So we get to the next step of your evolution: reasoning in unfamiliar domains given unfamiliar requests, that is, the discovery process that is the goal of what is called general intelligence. In my case I am able to see cross domain patterns with relative ease, ask questions to become more conversational about those domains and construct experiments to validate propositions and test assumptions. Reasoning.  Please comment on where AI is and what are the challen...
Read more