Mastering Prompt Engineering
In the rapidly evolving world of AI, the ability to generate high-quality outputs from Language Models (LLMs) hinges on one crucial skill; Prompt Engineering.
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In the rapidly evolving world of AI, the ability to generate high-quality outputs from Language Models (LLMs) hinges on one crucial skill; Prompt Engineering.
Artificial Intelligence (AI) is revolutionizing the way we approach problem-solving, task automation and education.
Using Prompt Engineering to build a simple game.
2018 saw the release of Kai-Fu Lee's book 'AI Superpowers China, Silicon Valley, and the New World Order'.
Short answer is obviously yes. The longer answer depends on lots of things, one of the main ones is Effort vs Benefit.
The MNSIT (Modified National Institute of Standards and Technology) database is a large collection of handwritten numbers used for training Image Processing systems. This is, in short, the hello world of machine learning.
SVM‘s are a key part of the Machine Learning History, it is fair to say that early interest in SVM’s and the realisation that they couldn’t deliver on early promises actually set the field of Machine Learning back a little.
If AI is the tree, then Machine Learning and Deep Learning are some of the branches that make that tree.
Machine Learning systems learn how to review data inputs so that never before seen data can be predicted against results of known data.