Alex Cloud (@cloud_kx) profile picture
Joined September 2019
Alex Cloud retweeted
New paper: Adding clean data to your dataset is assumed to weaken poison data. We show the opposite can occur. Clean data can *strengthen* backdoor misalignment, if the poison has an identifying trigger. We call this homeopathic learning.
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Alex Cloud retweeted
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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Alex Cloud retweeted
We’re pleased to have collaborated with AE Studio on this research. Read more here: anthropic.com/research/off-s…
New research! Some AI capabilities are both helpful and dangerous. E.g., knowledge of virology can be used to create life-saving vaccines or deadly pathogens. We introduce GRAM, a training method that puts dual-use capabilities (like virology) into removable modules.
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Alex Cloud retweeted
MATS Autumn applications due June 7! Pitch: Come work with me and Alex Cloud in Team Shard! We have fun, consistently make real alignment progress (we pioneered steering vectors in 2023!), and help scholars tap into their latent abilities.
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New Anthropic research! We study how to train models so that high-risk capabilities live in a small, separate set of parameters, allowing clean capability removal when needed – for example in CBRN or cybersecurity domains.
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Maybe *you* should apply to work with me and @cloud_kx on Team Shard in MATS. We help alignment researchers grow from small seeds into majestic trees. We have fun, consistently make real alignment progress, and have a dedicated shitposting Slack channel.
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We’re hiring someone to run the Anthropic Fellows Program! Our research collaborations have led to some of our best safety research and hires. We’re looking for an exceptional ops generalist, TPM, or research/eng manager to help us significantly scale and improve our collabs 🧵
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Alex Cloud retweeted
Yeah we did exactly that
New paper & surprising result. LLMs transmit traits to other models via hidden signals in data. Datasets consisting only of 3-digit numbers can transmit a love for owls, or evil tendencies. 🧵
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The last thing you see before you realize your alignment strategy doesn’t work
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New paper & surprising result. LLMs transmit traits to other models via hidden signals in data. Datasets consisting only of 3-digit numbers can transmit a love for owls, or evil tendencies. 🧵
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Thought real machine unlearning was impossible? We show that distilling a conventionally “unlearned” model creates a model resistant to relearning attacks. 𝐃𝐢𝐬𝐭𝐢𝐥𝐥𝐚𝐭𝐢𝐨𝐧 𝐦𝐚𝐤𝐞𝐬 𝐮𝐧𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐫𝐞𝐚𝐥.
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1) AIs are trained as black boxes, making it hard to understand or control their behavior. This is bad for safety! But what is an alternative? Our idea: train structure into a neural network by configuring which components update on different tasks. We call it "gradient routing."
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