


OpenAI develops new tool to try to explain the behavior of language models
Language model is an artificial intelligence technology that can generate natural language based on given text. OpenAI's GPT series language models are currently one of the most advanced representatives, but IT House has noticed that they also have a problem: their behavior is difficult to understand and predict. To make language models more transparent and trustworthy, OpenAI is developing a new tool that can automatically identify which parts of a language model are responsible for its behavior and explain it in natural language.
The principle of this tool is to use another language model (that is, OpenAI's latest GPT-4) to analyze other language models (such as OpenAI's own GPT-2) internal structure. A language model is composed of many "neurons", each of which can observe a specific pattern in the text and influence the next output of the model. For example, given a question about superheroes (such as "Which superheroes have the most useful superpowers?"), a "Marvel superhero neuron" might increase the probability that the model mentions a specific superhero from a Marvel movie. .
OpenAI’s tools use this mechanism to decompose the various parts of the model. First, it feeds a text sequence into the model being evaluated and waits for a certain neuron to "fire" frequently. It then "shows" these highly active neurons to GPT-4, and lets GPT-4 generate an explanation. To determine the accuracy of the interpretation, it feeds GPT-4 some text sequences and asks it to predict or simulate the neuron’s behavior. It then compares the behavior of the simulated neurons to the behavior of actual neurons.
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