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Introducing Claude 2.1
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Thoughts on the US Executive Order, G7 Code of Conduct, and Bletchley Park Summit
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Dario Amodei’s prepared remarks from the AI Safety Summit on Anthropic’s Responsible Scaling Policy
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Specific versus General Principles for Constitutional AI
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Towards Understanding Sycophancy in Language Models
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Collective Constitutional AI: Aligning a Language Model with Public Input
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Decomposing Language Models Into Understandable Components
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Towards Monosemanticity: Decomposing Language Models With Dictionary Learning
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Challenges in evaluating AI systems
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Claude on Amazon Bedrock now available to every AWS customer
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Expanding access to safer AI with Amazon
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Prompt engineering for Claude's long context window
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Anthropic's Responsible Scaling Policy
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The Long-Term Benefit Trust
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Anthropic partners with BCG
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Introducing Claude Pro
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Claude 2 on Amazon Bedrock
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SKT Partnership Announcement
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Releasing Claude Instant 1.2
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Tracing Model Outputs to the Training Data
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Studying Large Language Model Generalization with Influence Functions
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Frontier Threats Red Teaming for AI Safety
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Frontier Model Security
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Measuring Faithfulness in Chain-of-Thought Reasoning
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Question Decomposition Improves the Faithfulness of Model-Generated Reasoning
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Claude 2
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Towards Measuring the Representation of Subjective Global Opinions in Language Models
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Charting a Path to AI Accountability
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Circuits Updates — May 2023
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Interpretability Dreams
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Anthropic Raises $450 Million in Series C Funding to Scale Reliable AI Products
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Zoom Partnership and Investment in Anthropic
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Introducing 100K Context Windows
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Claude’s Constitution
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Distributed Representations: Composition & Superposition
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Partnering with Scale to Bring Generative AI to Enterprises
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An AI Policy Tool for Today: Ambitiously Invest in NIST
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Claude, now in Slack
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Privileged Bases in the Transformer Residual Stream
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Introducing Claude
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Core Views on AI Safety: When, Why, What, and How
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The Capacity for Moral Self-Correction in Large Language Models
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Anthropic Partners with Google Cloud
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Superposition, Memorization, and Double Descent
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Discovering Language Model Behaviors with Model-Written Evaluations
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Constitutional AI: Harmlessness from AI Feedback
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Measuring Progress on Scalable Oversight for Large Language Models
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Toy Models of Superposition
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Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned
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Language Models (Mostly) Know What They Know
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Softmax Linear Units
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Scaling Laws and Interpretability of Learning from Repeated Data
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Anthropic Raises Series B to Build Steerable, Interpretable, Robust AI Systems
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Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback
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In-context Learning and Induction Heads
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Predictability and Surprise in Large Generative Models
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A Mathematical Framework for Transformer Circuits
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A General Language Assistant as a Laboratory for Alignment
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Anthropic raises $124 million to build more reliable, general AI systems