/
Navigation
Chronicles
Browse all articles
Explore
Semantic exploration
Research
Entity momentum
Nexus
Correlations & relationships
Story Arc
Topic evolution
Drift Map
Semantic trajectory animation
Posts
Analysis & commentary
Pulse API
Tech news intelligence API
Browse
Entities
Companies, people, products, technologies
Domains
Browse by publication source
Handles
Browse by social media handle
Detection
Concept Search
Semantic similarity search
High Impact Stories
Top coverage by position
Sentiment Analysis
Positive/negative coverage
Anomaly Detection
Unusual coverage patterns
Analysis
Rivalry Report
Compare two entities head-to-head
Semantic Pivots
Narrative discontinuities
Crisis Response
Event recovery patterns
Connected
Search: /
Command: ⌘K
Embeddings: large
TEXXR

Chronicles

The story behind the story

days · browse · Enter similar · o open

Anthropic says it created a new tool for deciphering how LLMs “think” and used it to resolve some key questions about how Claude and probably other LLMs work

Anthropic CEO Dario Amodei.  Today the company announced that its researchers had made a breakthrough in probing …

Fortune Jeremy Kahn

Discussion

  • @dancow Dan Nguyen on bluesky
    Anthropic's overview of its new paper is a pretty digestible and entertaining read.  The usual objections apply to the claims that AIs actually “think”.  But this is a concise summary of the current mysteries:  —  “Claude begins to give bomb-making instructions after being tricke…
  • @maxxxv Maxx on bluesky
    So, now we're using CLT AI to tell us why LLM's are doing what they do.  —  Can the CLT be trusted not to hallucinate?
  • @markduffy.sh Marcus O'Dubhthaigh on bluesky
    Do they know how their tool works?
  • @emollick Ethan Mollick on x
    There's at least a dozen dissertations to be written from this paper by Anthropic alone, which gives us some insight into how AIs “think” and reveal a lot of complexity and unexpected abilities, including generalization and planning. https://transformer-circuits.pub/ ... [image]
  • @antonioregalado Antonio Regalado on x
    LLMs have Jennifer Aniston neurons. Or something. What Anthropic found when they tried to trace back Claude's “thoughts” to their sources. [image]
  • @chaitjo Chaitanya K. Joshi on x
    Beautiful! 😍 Graphs encode some notion of structure which could be how we start mechanistically understanding these large models [image]
  • @mlpowered Emmanuel Ameisen on x
    We use language models like Claude to help us write, code, and think better. But we don't understand how they work! We've built a new tool which allows us to look inside the model's “brain” as it is “thinking” Using it, we found really surprising behaviors 🧵 [image]
  • @nickcammarata Nick on x
    I think we're in the timeline that solves interpretability before any true takeoff. between this and a couple other directions I've never been more excited about the field
  • @nicholasturner0 Nicholas Turner on x
    As people that know me well can attest, I love a good mystery! 🔍 Fortunately for me, this work had twists both surprising and peculiar. 🧵
  • @adamrpearce Adam Pearce on x
    Addition has been extensively studied in simple toy models. In our latest paper, we describe a method for untangling circuits of computations and examine how Claude understands “calc: 36+59=” https://www.anthropic.com/... [image]
  • @anthropicai @anthropicai on x
    New Anthropic research: Tracing the thoughts of a large language model. We built a “microscope” to inspect what happens inside AI models and use it to understand Claude's (often complex and surprising) internal mechanisms. [video]