Audio long-read: Rise of the robo-writers
Nature Podcast
podcast@nature.com
4.5 • 893 Ratings
🗓️ 6 April 2021
⏱️ 26 minutes
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Summary
In 2020, the artificial intelligence (AI) GPT-3 wowed the world with its ability to write fluent streams of text. Trained on billions of words from books, articles and websites, GPT-3 was the latest in a series of ‘large language model’ AIs that are used by companies around the world to improve search results, answer questions, or propose computer code.
However, these large language model are not without their issues. Their training is based on the statistical relationships between the words and phrases, which can lead to them generating toxic or dangerous outputs.
Preventing responses like these is a huge challenge for researchers, who are attempting to do so by addressing biases in training data, or by instilling these AIs with common-sense and moral judgement.
This is an audio version of our feature: Robo-writers: the rise and risks of language-generating AI
Hosted on Acast. See acast.com/privacy for more information.
Transcript
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| 0:00.0 | Hello everyone. My name is Jamie Lang and I'm the host of Great Company podcast and today we are |
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| 1:20.4 | Welcome to this audio long read from nature. |
| 1:23.0 | In this episode, RoboWriters, |
| 1:26.7 | the rise and risks of of Language Generating AI. |
| 1:30.6 | Written by Matthew Hudson and read by me, Benjamin Thompson. |
| 1:42.2 | In June 2020, a new and powerful artificial intelligence began dazzling technologists in Silicon Valley. |
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