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We recently added three new endpoints to the API for GPT-3. The Classification Endpoint makes it easy to apply classification from a data set larger than what fits inside a prompt.
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TL;DR: In an API call GPT-3 can recall details from a 1,500 word article and even repeat passages verbatim. It can also repeat over 250 items from a list as it creates a completion. The concept of memory with a large language model can be a little fuzzy. There’s how much information the model possesses
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TL;DR: For many tasks you don’t need to provide GPT-3 with examples because it already understands what you want. If you look closely at the documentation and prompts for GPT-3 provided by OpenAI you’ll notice that a number of them don’t require any examples to show the model what you want. This is because in
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TL;DR: GPT-3 is much more capable than people realize when you utilize advanced prompt design that shows it what you want performed in a task then show it how to perform this task with a list of inputs. One of my favorite prompts in our OpenAI documentation is an example showing how to get GPT-3
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Here’s a fun fact: OpenAI’s GPT-3 is actually a family of models, Ada, Babbage, Curie and Davinci that have different capabilities and speed. While Davinci gets most of the attention, the other models are amazing in their own way. Davinci is the most generally-capable model that’s exceptional at intuiting what someone wants to accomplish while
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When the first demos of GPT-3 content started to circulate it showed the amazing potential for a really smart language model to generate text and do cool things. Yet despite all the attention GPT-3 has been getting there’s one other aspect of it made available by OpenAI that’s been almost completely overlooked: Semantic Search. The
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OpenAI’s API allows for incredibly intelligent text comprehension and transformation. For fun I made a little application that takes a transcript or script and turns it into a narrative structure for a novel and vice versa. This means that you can input dialog and add some simple instructions and get a narrative form back (and
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OpenAI’s API is incredibly versatile at comprehending text and completing passages, finding data and generating new information. For fun I wanted to see what would happen if I supplied it with a different kind of text data: Emojis. Emojis are interesting because they can convey information visually and are understood around the world regardless of
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I’d like to show one of the API’s other superpowers: Its ability to expand a small thought into a larger expression.
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Will artificial intelligence ever write a novel? I believe the answer is “Yes.”
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@AndrewMayne 