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:
LLMS
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How Language Models Function as Probabilistic Text Predictors
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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.
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How AI Models Learn to Recognize Textual Patterns
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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.
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Understanding Parameters in AI Models Like GPT-3
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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.
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What is GPT-3?
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Background: GPT-3 stands for "Generative Pre-trained Transformer (3rd Generation)" and was developed by @OpenAI in 2020. What does it do? GPT-3 generates human-like text.
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A Simple Explanation of How LLMs Function
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GPT-3 is what's called a "language learning model", or LLM.
— AI Breakfast (@AiBreakfast) 23 novembre 2022
Simply put, language models use statistics to guess the next word(s) in a sequence. pic.twitter.com/OJK3lETSkwGPT-3 is what's called a "language learning model", or LLM. Simply put, language models use statistics to guess the next word(s) in a sequence.
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Understanding GPT-3: Capabilities and Practical Applications
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What exactly is GPT-3? Here's how it works, what it can do, and how you can use it today. ↓ [fun graphics] ↓
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Large Language Models Should Be Called Infrastructure Models
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A better name for large language models is infrastructure models.
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Old NLP Experts Underestimate Language Models’ Capabilities
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Some old-time NLPers can be closed minded about the "range of tasks" that LMs can do. They are still thinking about LMs through BERT, etc. I rarely see this issue with new-joiners to NLP.
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MIT AI Beats 90% of Humans at Diplomacy Game
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MIT researcher helps create AI that beats 90% of humans at Diplomacy, combining language models w/strategic reasoning: https://
bit.ly/3VjWgJN @MetaAI @apjacob03