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Large Language Models

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In the Media

Parthasarathy weighs in on implications of ChatGPT

Feb 6, 2023 Nature
Shobita Parthasarathy, Nature: "Besides directly producing toxic content, there are concerns that AI chatbots will embed historical biases or ideas about the world from their training data, such as the superiority of particular cultures, says...
News

Parthasarathy discusses implications of Large Language Models

Nov 7, 2022
Large Language Models (LLMs) are artificial intelligence tools that can read, summarize and translate texts and predict future words in a sentence letting them generate sentences similar to how humans talk and write. Shobita Parthasarathy, professor...
News

STPP research on AI highlighted in Nature Q&A

May 3, 2022
Ford School professor Shobita Parthasarathy was highlighted in a Q&A with Nature magazine, acknowledging recent research on Large Language Models (LLMs) by the Science, Technology, and Public Policy program's Technology Assessment Project....
News

STPP wins grant to explore Large Language Models  

Jun 11, 2021
Large Language Models (LLM) — machine learning algorithms that can recognize, predict, and  generate human languages on the basis of very large text-based data sets — have captured the imagination of scientists, entrepreneurs, and tech-watchers....
Technology Assessment Project

What’s in the Chatterbox?

May 2021
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Johanna Okerlund, Evan Klasky, Aditya Middha, Sujin Kim, Hannah Rosenfeld, Molly Kleinman, Shobita Parthasarathy
Large language models (LLMs)—machine learning algorithms that can recognize, summarize, translate, predict, and generate human languages on the basis of very large text-based datasets—are likely to provide the most convincing computer-generated imitation of human language yet. Because language generated by LLMs will be more sophisticated and human-like than their predecessors, and because they perform better on tasks for which they have not been explicitly trained, we expect that they will be widely used. Policymakers might use them to assess public sentiment about pending legislation,...