@Google DeepMind Blog
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Researchers are making strides in understanding how AI models think. Anthropic has developed an "AI microscope" to peek into the internal processes of its Claude model, revealing how it plans ahead, even when generating poetry. This tool provides a limited view of how the AI processes information and reasons through complex tasks. The microscope suggests that Claude uses a language-independent internal representation, a "universal language of thought", for multilingual reasoning.
The team at Google DeepMind introduced JetFormer, a new Transformer designed to directly model raw data. This model, capable of both understanding and generating text and images seamlessly, maximizes the likelihood of raw data without depending on any pre-trained components. Additionally, a comprehensive benchmark called FACTS Grounding has been introduced to evaluate the factuality of large language models (LLMs). This benchmark measures how accurately LLMs ground their responses in provided source material and avoid hallucinations, aiming to improve trust and reliability in AI-generated information. References :
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Ryan Daws@AI News
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Anthropic has unveiled a novel method for examining the inner workings of large language models (LLMs) like Claude, offering unprecedented insight into how these AI systems process information and make decisions. Referred to as an "AI microscope," this approach, inspired by neuroscience techniques, reveals that Claude plans ahead when generating poetry, uses a universal internal blueprint to interpret ideas across languages, and occasionally works backward from desired outcomes instead of building from facts. The research underscores that these models are more sophisticated than previously thought, representing a significant advancement in AI interpretability.
Anthropic's research also indicates Claude operates with conceptual universality across different languages and that Claude actively plans ahead. In the context of rhyming poetry, the model anticipates future words to meet constraints like rhyme and meaning, demonstrating a level of foresight that goes beyond simple next-word prediction. However, the research also uncovered potentially concerning behaviors, as Claude can generate plausible-sounding but incorrect reasoning. In related news, Anthropic is reportedly preparing to launch an upgraded version of Claude 3.7 Sonnet, significantly expanding its context window from 200K tokens to 500K tokens. This substantial increase would enable users to process much larger datasets and codebases in a single session, potentially transforming workflows in enterprise applications and coding environments. The expanded context window could further empower vibe coding, enabling developers to work on larger projects without breaking context due to token limits. References :
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