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23 November 2022 23h59

So what can you use it for? GPT-3 will attempt to answer virtually any text prompt you give it. It can answer questions, write stories, poems, create lists, write research papers, and it can write code. A lot of code. The best way to describe what it can do is to just try it.

How Language Models Function as Probabilistic Text Predictors

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23 November 2022 23h59

When a user provides the text input, the system analyzes the language and uses a text predictor to create the most likely* output. *Does not necessarily mean the most factually accurate output, but rather the most "likely" output based on the data from the training library.

How AI Models Transform Input into Predictions

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23 November 2022 23h59

This means that it can take user's input text and transform it into what it predicts the most useful result will be based on the patterns recognized from the parameter library.

GPT-3 Training Data Composition Breakdown

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23 November 2022 23h59

GPT-3 has been trained on 45 TB of text data from different categories: ⬩Common Crawl (8 years of raw web page crawling) ⬩WebText (The text of Reddit posts with 3+ upvotes) ⬩Books (The internet-based books corpora) ⬩Wikipedia Data is then "weighed" as such:

How AI Models Learn to Recognize Textual Patterns

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23 November 2022 23h59

The algorithm (or "model") utilizes a set of data that enables it to recognize certain patterns in the text. This is accomplished by training the system on the vast body of internet text to spot patterns.

Understanding Parameters in AI Models Like GPT-3

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23 November 2022 23h59

GPT-3 has a lot of "parameters" for guessing the next words in a sequence. What's a parameter? It's a variable within the model whose value can be estimated from the given data. They are required by the model when making predictions. GPT-3 has about 175,000,000,000 of them.