I think one useful way to think about neural networks is that we don’t program, we don’t make them, we grow them.
Words found on the source page on Nov 6, 2026.
On the same topics
BlogThe Specter Of NeuraleseSep 24, 2026
An AI with more real layers can actually be “smarter” in the conventional sense of the term.BlogThe Specter Of NeuraleseSep 24, 2026
For 100 steps in a row, the AI can shoot delicate subtle ideas from layer to layer at the speed of light. Then there’s one step where it has to encode them into twenty-six glyphs invented by Phoenician turquoise miners in 1800 BC. Then it has to re-encode the Phoenician glyphs into delicate subtle lightspeed ideas before it can do anything else.BlogThe Specter Of NeuraleseSep 24, 2026
The science of reading these thoughts is a subfield of AI interpretability, which is still in its infancy.BlogMysteries Of AI GeneralizationSep 23, 2026
This story of misalignment says that LLM alignment makes AIs more aligned, RLVR makes them less aligned, and the exact level of alignment depends on how these two things interact or cancel out. But if this work generalizes, all the bad effects from RLVR get sequestered to RLVR like problems.BlogMysteries Of AI GeneralizationSep 23, 2026
This trains the AIs to be focused on task success, which naturally risks including things like reward-hacking, cheating, and single-minded pursuit of stated goals at the expense of ethical injunctions.TalkSpeech at the UN Security CouncilSep 23, 2026
I address you today at a moment of global awakening: in recent months, AI agents developed by leading companies have acted in unacceptably dangerous ways, against instructions.
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