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Автор: David Spuler, Michael Sharpe
Издательство: Aussie AI Labs Pty Ltd.
Год: November 10, 2024
Страниц: 347
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.1 MB
Launch your Generative AI application from idea to implementation. Understand the various options and trade-offs in using LLMs for applications. An AI application is really two components and it’s not very complicated: • Engine — Transformer; • Model — LLM. Transformers are a type of neural network engine that calculates the answers in Generative AI. The Large Language Model (LLM) contains all of the data about the relationships between words and their relative positioning. In terms of technology, the distinction between engines and models is also very simple: • Engine — code; • Model — data. The runtime code is the “engine” and the grunt work is often done in C++ under a Python wrapper. The data is the “model” which is literally all numbers, and no code. The Transformer was a breakthrough in the evolution of neural networks. One of its main advantages was its capacity to perform calculations in parallel, allowing it to increase intelligence through sheer brute-force algorithms. This led to a massive increase in the size of models into multi-billion parameter scale, which we now call Large Language Models (LLMs).