http://
cs.washington.edu/homes/pedrod/p
apers/iclr18.pdf
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AI
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Machine Learning Research Paper from University of Washington
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ContentFries Featured as AI-Powered Content Creation Tool
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Today's featured tool is @ContentFries
! Check them out on Futurepedia: https://
futurepedia.io/tool/contentfr
ies
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Three Eras of Programming: From Assembly to AI
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The three eras of programming:
1. Assembly code
2. High-level languages
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Prefrontal Cortex as the Brain’s Rationalization Module
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A better term for the prefrontal cortex would be the rationalization module.
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Self-Curating Database Invention Could Bring Significant Wealth
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If someone invents a self-curating database, they’ll be on their way to untold riches.
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Capabilities and use cases for GPT-3
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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.
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How AI Models Transform Input into Predictions
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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.
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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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GPT-3 Training Data Composition Breakdown
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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:
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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.