Ethan Roland

@ModuloRoland

AI Researcher

Atlanta, USA Joined August 2014

219 Following 297 Followers 286 Posts

Latest posts 5

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Ethan Roland @ModuloRoland Jul 9

Excited to share our new work with @AnthropicAI

Our new paper (ICML 2026, Spotlight) tackles frontier model misuse by isolating select knowledge into detachable modules during training, enabling an on/off switch for dangerous capabilities during inference.

Anthropic Verified account @AnthropicAI Jul 8

We’re pleased to have collaborated with AE Studio on this research.

Read more here: anthropic.com/research/off-s…
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Ethan Roland @ModuloRoland Oct 24

You can train a model to only work on a single GPU

Ethan Roland @ModuloRoland Oct 20

Awesome work!! Really glad folks are pursuing GR in a posttraining setting

Jake Ward @_jake_ward Oct 19

Models love reward hacking. Maybe we should just let them!

In our new paper, we let models reward hack during RL but we dictate which parameters learn this behavior. When we disable these parameters for deployment, the model keeps its new capabilities but doesn't hack!

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Ethan Roland @ModuloRoland Oct 15

Glad to see this framing for alignment research gaining more traction

Apollo Research Verified account @ApolloResearch Oct 15

Given the stakes of building transformative AI, every developer should look for this reasoning throughout training. Because alignment faking is relevant during training, not deployment, final checkpoint evaluations are insufficient.

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Ethan Roland @ModuloRoland Oct 13

wow what an interesting spin on nanogpt

Samip Verified account @industriaalist Oct 12

Replacing backprop with zeroth-order optimization is inevitable.

Introducing Noise: a speedrun for pretraining without backprop.

Last week we presented Dust, the first method to approach backprop with SGD for pretraining transformers. We think another 1,000x improvement on top of it is possible, and it will require *co-designing* credit assignment, optimizers, architectures, and eventually, hardware.

We built Noise to iterate on this faster.

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