neurons

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#neurons

To all the unscientific ppl in this sub claiming time and time again that "brains aren't so complicated, we basically know how brains work and the singularity is a matter of scaling"

Reddit r/singularity · 2026-08-13 Cached

A new study challenges traditional assumptions about neurons, showing they can perform multiple computations simultaneously, suggesting that brain cells have vastly more computing power than previously believed.

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#neurons

Incomplete Prompt Jailbreaks in Large Language Models

arXiv cs.AI · 2026-07-24 Cached

This paper formalizes Incomplete Prompt Jailbreaks (IPJ), a vulnerability where incomplete harmful prompts cause LLMs to generate harmful continuations, and analyzes attractor types and neuron-level mechanisms for defense.

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#neurons

Scientists recorded individual neurons in bilingual brains for the first time and found that the brain does not translate words, it does something very similar to vector space isomorphism in LLMs instead

Reddit r/singularity · 2026-06-25 Cached

Scientists recorded individual neurons in bilingual brains for the first time and found that the brain does not translate words using shared neurons but instead organizes each language into a geometric map of meaning with the same structure, similar to vector space isomorphism in LLMs.

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#neurons

The discovery that changed how scientists think about memory

Hacker News Top · 2026-06-17 Cached

Oswald Steward and colleagues won the 2026 Kavli Prize in Neuroscience for discovering that neurons can produce proteins near synapses, fundamentally changing understanding of memory and brain plasticity.

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#neurons

Where Fake Citations Are Made: Tracing Field-Level Hallucination to Specific Neurons in LLMs

arXiv cs.CL · 2026-04-22 Cached

Rutgers researchers trace citation hallucination in LLMs to sparse field-specific neurons, showing causal intervention can suppress fake references.

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#neurons

Language models can explain neurons in language models

OpenAI Blog · 2023-05-09 Cached

OpenAI proposes using language models (GPT-4) to automatically generate and score explanations for neurons in language models, open-sourcing datasets and tools covering all 307,200 neurons in GPT-2. The work demonstrates iterative and scalable approaches to mechanistic interpretability, though explanation quality still lags behind humans.

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