Eliezer Yudkowsky is not a scientist. He made a popular Harry Potter fanfiction series and a "rationality" blog-community that attracts "human biological diversity" enthusiasts.
Elizer Yudkowsky is a scientist, despite writing something you dislike 20 years ago and also having a blog. And no, he's not associated with race realism, that's just baseless libel.
Lets not forget that the 'Fermat's Last Theorem' which has been pretty visible for the non-math crowd of late due to the recent AI frenzy about a purported proof was but one small contribution to the world's math lexicon by someone with a bachelors degree in civil law, that George Green was a baker and millwright, Boole was the son of a poor shoemaker in England with no formal university education and left school at age 14. Oliver Heaviside was a telegraph operator, and Michael Faraday was an apprentice bookbinder. So, not accredited shouldn't really carry much weight when it comes to mathematics. Lets not pretend that machine learning and the narrow branch that is the current approach to LLM inductions is anything but applied math.
We might exercise our own minds and actually read the works and writings of a person, and use that as a measure of knowledge and perspective. Not all PhD dissertations are equal, and many have comprehension and ability to move us forward even without the institutional rigour.
For those who prefer to have easy access to citations, here are some relevant papers that are not "Harry Potter" related, some with coauthors from Oxford University.
I am absolutely using "not accredited" in a pejorative sense here. That he publishes papers coauthored by a couple of philosophy professors at Oxford (all of whom have made a ton of money from the Silicon Valley AI Alignment and Effective Altruism crowds) does not make him a scientist.
I will also note that the Oxford Philosophy department finally shitcanned the whole Future of Humanity Institute a couple of years back.
Yes, he's the exact reason people are distrustful. He's a crank who learned about reward hacking and made a new religious movement out of it, pretending it's a world-ending issue and deliberately avoiding much more serious issues like the concentration of power. Typical cult leader and manipulator, and his disciples in charge of major AI shops aren't any better.
I think more the idea that wrestling with new ideas and distilling them down can you help you to understand something, even if that note is then immediately thrown out. The purpose of the notetaking in this case is not for future reference.
In response to your edit, you should check out Terry tao's chat gpt logs about the recent Jacobian result. The models are smart enough to brute force some things, but can cut to the meat much faster with good prompting
i read his, too. his replies are indeed more directed, but also quite short, unstructured, and natural sounding. if i recall, maybe 1 or 2 of his prompts exceeded 50(ish) words.
in my head, the comparison is the multi-paragraph prompts (borderline essays) i would read in various communities on reddit and similar forums, that people (often self-proclaimed "prompt engineers") said were "required" to get good output. or some of the prompts ive read in various logs that are like a thousand words of setup.
even looking back at the first prompts i was sending when i started to use chatgpt were (in hindsight) crazy long and full of unnecessary guidance/caveats/"ignore xyz"/etc.
I didn't use generative AI much until a couple months ago. My last employer had a copilot license that I dabbled in in 2024, and wasn't impressed with, and then I spent the latter half of 2025 and early 2026 budget traveling/hiking a lot. I started at a new company in May, and I've been astonished at how lazy I can be at prompting and still get impressive results with 2026 Claude Code.
I can paste entire failure logs with the word "why" lowercase, no question mark, and get into a productive chat session where it significantly speeds up the bug trace. I will paste the text from a groomed ticket with no editing or additional instructions into the chat and then give it a bit of feedback on the plan for a couple iterations.
I feel so vindicated in never spending time learning prompting as a specific skill, it really just took a couple more years and the models are really easy to interact with with simple natural language.
> were (in hindsight) crazy long and full of unnecessary guidance
Not sure when you started. However: I would never judge the necessity of details provided 2 or 3 years ago based on results that the current models give.
Not under all the competitive pressure they are facing, but if an industry wide slowdown could be achieved they might spend more time on model alignment and less on pure capabilities.
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