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The bot problem is solvable by using a web of trust system. You don't need a digital ID for that (i.e. you don't need to tie your digital world identity to a real world identity, nor you need a central agency to manage these).

In web of trust, anyone could publicly certify who they know is a real person (i.e. validate a link from their id to another id). Then, if you received a message from someone, the system would find the path in the graph of real people you trust, to determine the trustworthiness of the source. So if the account is a bot, there would be no path from it to you in the trust graph.

The advantage is that everyone could supply their own subjective trustworthiness score, altering the graph. They could even publish it, so that other people could use trustworthiness assesment of accounts they personally trust.

The big issue with a system of web of trust is that it is too efficient, and just kills commercial advertising (and also propaganda). Because that is all about overcoming the natural web of trust that humans have.


Honestly, I found these two attempts at universal theory more interesting:

https://arxiv.org/abs/2510.12269

https://www.mdpi.com/1099-4300/28/3/332

I am also interested in connection with fuzzy logic - it seems that NNs can reason in a fuzzy way, but what they are doing, formally? For years, people have been trying to formalize fuzzy reasoning but it looks like we don't care anymore.

I feel like NNs (and transformers) are the OOP (object-oriented programming) of ML. Really popular, works pretty well in practice, but nobody understands the fundamentals; there is a feeling it is a made up new language to express things expressible before, but hard to pinpoint where exactly it helps.


I wonder if it emits orgasmic moans when working with a particularly pleasureable codebase.

I thought about a similar concept for fun - each hex digit was replaced by 4x4 pixel matrix, where amount of pixels roughly corresponded to the value. So dot for 0, two dots for 1, checkerboard for 8 etc.

Then byte was represented as 16x16 matrix where each 4x4 area had the lower digit pattern, and these were arranged in the shape of the higher digit.

But at the end of the day, it wasn't really more readable.


I think semantic coloring (based on structure) is more useful. Also (can't help as someone working with z/OS), if you really want to make hex output readable, I recommend using big-endian machine.

American "belt & road" has been tried, but in a neoliberal way, through WB and IMF, and it has been an utter failure (see Joe Stiglitz or Ha-Joon Chang for examples). Chinese are way more pragmatic (smarter) about it.

I thought that you were about to write: "as a janitor in a restaurant, the dessert topping is sometimes used as a floor polish".

Something as expensive as dessert toppings would only be used as floor polish by the people who truly were high... and only if they could do it without the boss knowing what they were doing.

A very human thing to do is - not to tell us which model has failed like this! They are not all alike, some are, what I observe, order of magnitude better at this kind of stuff than others.

I believe how "neurotypical" (for the lack of a better word) you want model to be is a design choice. (But I also believe model traits such as sycophancy, some hallucinations or moral transgressions can be a side effect of training to be subservient. With humans it is similar, they tend to do these things when they are forced to perform.)


Codex in this case. I didn't even think about mentioning it. I'll update the post if it's actually relevant. Which I guess it is.

EDIT: It's specifically GPT-5.4 High in the Codex harness.


weird, for me it was too un-human at first, taking everything literally even if it doesn't make sense; I started being more precise with prompting, to the point where it felt like "metaprogramming in english"

claude on the other hand was exactly as described in the article


Also the exact model/version if you haven't already.

Also, there's no specific examples of what the prompt was and what the result was. Just a big nothingburger

Can you be more specific?

Trump issued an EO against "woke AI" that allows them to directly influence how models respond

https://www.lawfaremedia.org/article/evaluating-the--woke-ai...


I think they're counting on an ego hit - "you're just a tool" - although it might be negated by the human satisfaction of figuring things out.

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