Research
Ontology-Guided Neuro-Symbolic Inference: Grounding Language Models with Mathematical Domain Knowledge
via ArXiv cs.AI — Language models exhibit fundamental limitations -- hallucination, brittleness, and lack of formal grounding -- that are particularly problematic in high-stakes specialist fields requiring verifiable reasoning. I investigate whether formal domain ontolo
How will we do SFT on models with opaque reasoning?
via Alignment Forum [1] — Current LLMs externalize lots of their reasoning in human interpretable language. This reasoning is sometimes unfaithful, sometimes strange and concerning, and LLMs can do somewhat impressive reasoning without using CoT, but my overall impression is that CoT currently is a…
Live Doom Meter
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%
0% — We're fine
100% — GG
The Doom Meter is a composite score derived from prediction markets and feed sentiment, updated daily.
70%
Prediction Markets
Weighted average of Manifold Markets questions on AI catastrophe, AGI timelines, expert surveys, and key figures. Direct doom indicators weighted higher than indirect capability markers.
30%
Feed Sentiment
Percentage of recent headlines containing high-alarm keywords (existential risk, catastrophe, extinction). Higher alarm density = higher score.
This is not a scientific estimate of existential risk. It is an opinionated, transparent signal — a vibes-based thermometer for AI doom discourse.
P(Doom) Scoreboard
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