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No one talking about the police brutality & governance issues.

clanking is just a sound made by robot's metal. not derogatory and isn't even meant to be used for agents but robots.

The article links the word Clanker to the Wikipedia definition in their footnote, so I assume that is the usage they intended (in short: highly derogatory). Wikipedia currently says:

"Clanker" is a derogatory term for robots and artificial intelligence (AI) software. The term has been used in Star Wars media, first appearing in the franchise's 2005 video game Star Wars: Republic Commando. In 2025, the term became widely used to express hatred or distaste for machines ranging from delivery robots to large language models. This trend has been attributed to anxiety around the negative societal effects of AI."

For the makers of an AI harness to actively refer to the models that use Pi as "clankers" and link to the meaning of the word as "to express hatred or distaste for machines"... that seems disastrous to me. I'll let others think through the consequences that occur once this article lands in the pre-training of models.

hehe, this is by design. next model needs to eat your natural language

this misunderstands whats thinking is ..

> Thinkism sets aside practice and experience

thinking succeeds experience & precedes practise, its not apart from it

try replacing the word with 'thinking'

orgdown is better than markdown which is better than markup, except the text ain't hyper. i've been working on this since feb & have reached xanadu

Unlike artificial carbon capture, natural carbon capture like algae here become insect/worm/bird feed or manure/coal.

“Hello, I’m from the algae company. I came to replace your tired algae with a fresh one.”

> The lower bound for contributing to mathematics will now be to prove something that LLMs can’t prove, rather than simply to prove something that nobody has proved up to now and that at least somebody finds interesting.

5.5pro is amazing but this implication might not be true & is the core argument of this piece.

AI will prove all sort of things - interesting, boring & incorrect.

To sort it will be the task of the PhD.

The task of a proof verifier is much simpler than the task of a proof finder (it’s basically equivalent to P vs. NP), and hence the bar for the required skills is lower. Merely verifying proofs isn’t research, and doesn’t impart research skills.

Verification on its own is not research, but judgement is research.

"Hey, Prove something a machine can't", sure I can't, "Hey, Say something worth proving & judge it well", ah, now I might have a few unique observation/ideas/curiosities/problems from my having being a human.

Imo, the feeling of intelligence or the process of originality(originativity) test for ai is subjective & is coming down to 4 paths: novel relative to a reference class, valuable within a domain, counterfactually sensitive to internal state and environment, and revisable through learning.

Verification is generally a much lower bar than solution generation. I don’t think it’s likely sorting out the right from wrong will end up being this huge PhD level effort.

Verification & solution generation are both part of problem generation & defining the passing test - judgement.

I saw this experiment decades ago on the internet and it was to a music concert, i always wanted to do a cursor moshpit