Previously we explored the notion of big ML models like GPT-3 standing in place of search engines for some types of search queries. We looked at navigational and informational queries first, and are now going to look at commercial or transactional queries.
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GPT-3 and other AI models replacing search is an interesting supposition; but can it really happen? To really compare the two we’ll need to break down what search is, how it is used, and what the actual outputs are.
Welcome to Part 2 of the series ‘Big ML Content Generation’ where we tackle using the models for creating whole new ideas. In this part we’ll be focusing on the idea generation capabilities of models like GPT-3.
Continuing the series on [Generating Content with Big ML Models] we’ll be using GPT-3 to generate marketing materials for business.
In this article we are going to be using GPT-3 to write a press release. Press releases can be hard for business owners to write because they are often not familiar with the format or style of a press release, or what information should be included. But GPT-3 can help you with that.
Another great use of Big ML models like GPT-3 is to summarize text by extracting the main points being made. Virtually all types of text can be summarized, including news articles, blog posts, research papers, novels, and poems.
In this article we continue the series on generating business content with Big ML models. The second in the series, this article is about formulating complete replies using OPT-175B.
One of the most exciting things about Big ML is its potential for generating content. Whether you want to write emails faster or generate entire articles on a given topic, Big ML models can do it all. In this series of articles, we’ll explore how Big ML can be used to generate content and some of the potential business applications for this technology.
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