Posts
This article is republished from The Conversation under a Creative Commons license. Read the original article.
Prasenjit Mitra, associate dean for research and professor of information sciences and technology at Pennsylvania State University observes, The GPT-3 program can write articles, produce code, and compose poetry.
Photo: antoniokhr/iStock]
Seven years ago, my student and I at Penn State built a bot to write a Wikipedia article on Bengali Nobel laureate Rabindranath Tagore’s play “Chitra.” First it culled information about “Chitra” from the internet. Then it looked at existing Wikipedia entries to learn the structure for a standard Wikipedia article. Finally, it summarized the information it had retrieved from the internet to write and publish the first version of the entry.
However, our bot didn’t “know” anything about “Chitra” or Tagore. It didn’t generate fundamentally new ideas or sentences. It simply cobbled together parts of existing sentences from existing articles to make new ones.
Fast forward to 2020. OpenAI, a for-profit company under a nonprofit parent company, has built a language generation program dubbed GPT-3, an acronym for “Generative Pre-trained Transformer 3.” Its ability to learn, summarize, and compose text has stunned computer scientists like me...
Learning on its own
The knowledge displayed by GPT-3’s language model is remarkable, especially since it hasn’t been “taught” by a human.
Machine learning has traditionally relied upon supervised learning, where people provide the computer with annotated examples of objects and concepts in images, audio and text–say, “cats,” “happiness” or “democracy.” It eventually learns the characteristics of the objects from the given examples and is able to recognize those particular concepts.
Source: Fast Company
