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Anthropic
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Anthropic
@AnthropicAI
We're an AI safety and research company that builds reliable, interpretable, and steerable AI systems. Talk to our AI assistant @claudeai on https://t.co/FhDI3KQh0n.
Katılım Ocak 2021
2 Takip Edilen1.5M Takipçiler
Anthropic retweetledi

We're introducing Claude for Teachers: free access to premium Claude capabilities for verified K-12 educators in the US, with a library of teaching skills and a direct connection to evidence-based curricula, mapped to academic standards in all 50 states.
claude.com/solutions/teac…

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We’re committing $10 million CAD and partnering with leading AI institutions in Canada to help fund new AI research.
anthropic.com/news/canadian-…
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While the values Claude expresses shape millions of conversations every day, we don't yet understand why they vary, or whether that's desired.
This approach will allow us to determine what factors influence Claude's value expression—and ultimately how (and whether) to steer it. anthropic.com/research/claud…
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In previous research, we found that Claude expresses over 3,000 values, like honesty and warmth. In new work, we asked how the values Claude expresses vary between Claude models and across languages.
We analyzed 300K+ anonymized conversations to find out.anthropic.com/research/claud…
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Anthropic retweetledi

Our Long-Term Benefit Trust has appointed Dr. Ben Bernanke as its newest member.
Read more: anthropic.com/news/ben-berna…
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We’re pleased to have collaborated with AE Studio on this research.
Read more here: anthropic.com/research/off-s…
AE Studio@AEStudioLA
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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We also partnered with Neuronpedia to create an interactive demo of our methods on open-weights models.
Try it here: neuronpedia.org/jlens
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The J-space lets us read, audit, and shape what Claude is actively thinking about—useful tools for keeping models trustworthy as they grow more capable. And it suggests surprising parallels between language models and our own minds.
Read the full paper: transformer-circuits.pub/2026/workspace…
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