News from the AI & ML world
DeeperML
Edd Gent@SingularityHub
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Anthropic has unveiled a new methodology for analyzing the inner workings of large language models (LLMs), specifically focusing on their Claude model. This groundbreaking research provides unprecedented insights into how these AI systems process information, make decisions, and generate text. The findings challenge previous understandings of LLM capabilities, revealing that these models plan ahead, utilize conceptual spaces across languages, and can sometimes fabricate arguments, even when they know the truth.
Researchers have developed techniques dubbed "circuit tracing" and "attribution graphs" that map out the specific pathways of neuron-like features that activate when models perform tasks. This approach, drawing inspiration from neuroscience, allows researchers to treat AI models as analogous to biological systems, opening up new avenues for understanding AI behavior. The goal of this “AI microscope” approach to AI interpretability is to allow them to uncover insights into the inner workings of these systems that might not be apparent through simply observing their outputs.
This work is turning what were almost philosophical questions — ‘Are models thinking? Are models planning? Are models just regurgitating information?’ — into concrete scientific inquiries about what’s literally happening inside these systems. These findings are not just scientifically interesting—they represent significant progress towards our goal of understanding AI systems and making sure they’re reliable.
ImgSrc: singularityhub.
References :
Researchers have developed techniques dubbed "circuit tracing" and "attribution graphs" that map out the specific pathways of neuron-like features that activate when models perform tasks. This approach, drawing inspiration from neuroscience, allows researchers to treat AI models as analogous to biological systems, opening up new avenues for understanding AI behavior. The goal of this “AI microscope” approach to AI interpretability is to allow them to uncover insights into the inner workings of these systems that might not be apparent through simply observing their outputs.
This work is turning what were almost philosophical questions — ‘Are models thinking? Are models planning? Are models just regurgitating information?’ — into concrete scientific inquiries about what’s literally happening inside these systems. These findings are not just scientifically interesting—they represent significant progress towards our goal of understanding AI systems and making sure they’re reliable.
ImgSrc: singularityhub.
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References :
- venturebeat.com: Anthropic scientists expose how AI actually ‘thinks’ — and discover it secretly plans ahead and sometimes lies
- SingularityHub: What Anthropic Researchers Found After Reading Claude’s ‘Mind’ Surprised Them
- venturebeat.com: Anthropic has developed a new method for peering inside large language models like Claude, revealing for the first time how these AI systems process information and make decisions.
Classification:
- HashTags: #Anthropic #ClaudeLLM #AIinterpretability
- Company: Anthropic
- Product: Claude
- Feature: Internal LLM Analysis
- Type: AI
- Severity: Major