The Anthropic annoucement addresses lots of this. They give an example of generating code where there is clearly a requirement to follow a specific syntax and therefore the watermarking will be much less effective and likely require much larger sample of generated content to build statistical confidence in the validity/existance of a watermark. For code, it is the generated comments that will be more likely/able to contribute to the watermark confidence.

The key to understanding the watermark technology is to realize that the model is/was already using randomness to select among the top most probable tokens, often randomly picking between choices of [nearly] equal weight. The watermarking does NOT change the distribution of the random number generation nor does it affect the range of probabilities for which tokens are being considered. Instead, it only drives the sequence of the random numbers such that they form a cryptographically generated known ordering pattern that is determined by the secret key generating the pseudo-random sequence.

As a result of the approach, assuming inference is being done with all other parameterization of token selection being the same, there should be NO impact on the output quality....the amount of variation of output is within sample of the variation in output that already exists run-to-run of the same prompt. FWIW too: Google has confirmed this experimentally as well through full scale tests and evaluation of online Gemini output in search result pages.

Thank you for the thoughts. Relative "made up words", what if the concepts reference things that didn't exist before their definition in these specifications?

ie: At one point "hyperlink" and "Uniform Resource Locator" were made up words. No different that say "web log" (blog) and "Client-Server Architecture" were being made up as well.

I contend that both "Artipoint" and "Cortex Layer" have similar parallels in the sense they refer to concepts newly formulated or at least are captured into a formalism with a label for the first time!

Cortex Layer is not made up, rather it is an anthropomorphization you want to become one of these words. Stop anthropomorphizing, it turns rational people off

Putting "Cognition" in the acronym is another example. These things are not cogniating, that's not how they work, they don't think, they have been gradient descended to use special <think> runs in their token generation

ASCP is a draft specification suite for a protocol to support persistent, structured context shared between humans and AI agents. It defines an immutable articulation grammar, a secure distribution layer, and a local-first append-only log sync model.

The work is still in draft form, but substantial: multiple detailed specifications are included, and we’re actively iterating across the grammar, security model, and synchronization layer. It’s not “finished,” but it’s well beyond half-baked.

We welcome contributions and feedback from collaboration-tool builders, protocol designers, distributed-systems engineers, and security/cryptographic reviewers who are interested in advancing an open, vendor-neutral standard for durable shared context.

Yes, I enjoyed the article as well and good for the non-technical reader.

I think of framing AI as having two fundamental problems:

- Practical problem: They operate in contextual and emotional "isolation" - no persistent understanding of your goals, values, or long-term intent

- Ethical problem: AI alignment is centralized around corporate values rather than individual users' authentic goals and ethics.

There is a direct parallel to social media's failure - platforms optimized for what they could do (engagement, monetization) rather than what they should do (serve user long term interests).

With these much more powerful AI systems emerging, we're at a crossroads of repeating this mistake...possibly at catastrophic scale even.