High impact
Show HN: LLM Attention Visualization
What happened
The project is a web‑based visualizer that lets users inspect the attention patterns of large language models (LLMs) in real time, showing which tokens each layer focuses on while generating text. By turning opaque attention matrices into interactive graphics, it makes it easier to understand how LLMs process and relate words across a prompt.
Why it matters
Such transparency tools can accelerate model debugging, safety research, and education, helping developers spot biases or inefficiencies and fostering more trustworthy AI systems.
Is this a big deal?
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