Daniel Flower-DevOps Experiments with AI_.pdf
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Prepared by: Daniel Flower
Date: 25/11/2023
Time to Experiment
DevOps Experiments
with AI
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Introduction
This is a talk about using and coding with Large Language Models.
I believe that these are very powerful, but no one knows their full potential or
how to maximise their use yet.
Therefore, now is a time to try many experiments to see what works.
This talk has a very brief overview of Large Language Models and then just
shows a few experiments.
The intention is give ideas about the kinds of things we can do with it, to inspire
others to start experimenting more.
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How they work
Large language models
• It takes some words as input. It generates the next word. It repeats this to make sentences and paragraphs.
• It remembers nothing. It learns nothing. So we need to give it everything it needs to know as input.
• It tries to guess what "sounds" best - not what is true.
• it is able to guess based not just on stats, but by generalising, "reasoning", and other things
function guessNextWord( input: words Array<String> ) output: String {
var numbers = convertWordsToNumbers(words);
var nextNumber = guessNextNumber(numbers);
return convertNumberToWord(nextNumber);
}
function guessNextNumber( input: numbers Array<Number> ) output: Number {
if (numbers.size > 8192) throw "Sorry! Too many inputs";
var guess = numbers[0] * 0.123124 + numbers[1] * 0.584935 + ...
// Huge amount of adding and multiplying numbers, but no state nor network calls etc
// Training the model takes a huge amount of time and money
return guess;
}
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