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On May 18, Google CEO Sundar Pichai announced an impressive new tool: an AI system called LaMDA that can chat to users about any subject.

To start, Google plans to integrate LaMDA into its main search portal, its voice assistant, and Workplace, its collection of cloud-based work software that includes Gmail, Docs, and Drive.

LaMDA is what’s known as a large language model (LLM)—a deep-learning algorithm trained on enormous amounts of text data.

Unfortunately, very little research is being done to understand how the flaws of this technology could affect people in real-world applications, or to figure out how to design better LLMs that mitigate these challenges.

Working together under the BigScience project led by Huggingface, a startup that takes an “open science” approach to understanding natural-language processing (NLP), they seek to build an open-source LLM that will serve as a shared resource for the scientific community.

“We can’t really stop this craziness around large language models, where everybody wants to train them,” says Thomas Wolf.

Started by former Google researchers, it promises to bring LLMs to any business that wants one—with a single line of code.

Noble worries this could make the problems she uncovered even worse: “The fact that Google’s ethical AI team was fired for raising very important questions about the racist and sexist patterns of discrimination embedded in large language models should have been a wake-up call.”

“I want NLP to help people,” she says, “not to put them down.”

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