
Daniel Murfet
@danielmurfet
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Mathematician. Head of Research at Timaeus. Working on Singular Learning Theory and AI alignment.
Melbourne, Victoria
Joined June 2012
RT @mhutter42: Reflective-Oracle AIXI solves the Grain of Truth problem for super-intelligent multi-agent systems/societies. Finally the lo….
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RT @banburismus_: post-training is weird, and can have all sorts of surprising side effects - extreme sycophancy, hallucinations, mechahitl….
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RT @gsxej: Neuronal diversity is written in transcriptional codes 🧬. But what is the logic of these codes that define cell types and wiring….
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RT @GoodfireAI: (6/7) Of course, a full solution also requires tools to mitigate those behaviors once they've been identified - and we're b….
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RT @jhhalverson: Grateful to @SimonsFdn for their support of the Physics of Learning, and glad to be a part of this collaboration! Excited….
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RT @pratyushmaini: 1/Pretraining is hitting a data wall; scaling raw web data alone leads to diminishing returns. Today @datologyai shares….
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RT @strickvl: In parallel I'd been exploring how to make LLMs tangible, i.e. as physical artifacts, not just plots. I started a small proje….
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RT @ch402: Our interpretability team is planning to mentor more fellows this cycle!. Applications are due Aug 17.
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RT @tfburns: Could the key to more efficient & robust language models come from computational neuroscience? Our paper demonstrates how brai….
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RT @ChrisGPotts: For a @GoodfireAI/@AnthropicAI meet-up later this month, I wrote a discussion doc:. Assessing skeptical views of interpret….
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RT @AsteraInstitute: What’s going on inside large AI models?. Astera grantees @adamimos and @RiechersPaul are building a new theory of inte….
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RT @LabWelch: Interested in studying cell differentiation at the cellular level but don't trust your UMAP plots? Try visualizing your cell….
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RT @thebasepoint: Very cool collaboration between 5 labs that dug into circuit tracing after our paper in March. Sections on replications,….
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This charming fellow is, however, too small to be really interesting. In larger models we see more complex structures, stay tuned! To read more: joint with @georgeyw_ @Gman5938 and Andy Gordon.
arxiv.org
Understanding how language models develop their internal computational structure is a central problem in the science of deep learning. While susceptibilities, drawn from statistical physics, offer...
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