Simple Explanation of Large Language Models Applications | Learn Prompt Engineering

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This video includes the introduction of large language models (LLMs) applications, a powerful neural network. Large Language Models (LLMs) and Generative AI both fall within deep learning, where their paths converge. Watch this video to learn about LLMs, including use cases, Prompt Engineering, Prompt Tuning, and GenAI development tools.

Discover the art of prompt engineering to guide your models with precision, delve into the advanced world of augmented LLMs to enhance your solutions, and wrap up with a toolkit of resources to explore more.

Whether you’re new to the field or looking to level up, our hands-on approach and expert guidance make this a must-watch tutorial for anyone interested in the cutting-edge world of Language Models.

Table of Contents:
0:00 – Introduction of Large Language Models
5:54 – Basics of Large Language Models (LLMs)
18:20 – Overview of Artificial Intelligence and Generative AI
20:00 – Different LLM (Large Language Models) applications
21:47 – Foundations of Machine Learning
41:00 – Understand BERT, T5, and GPT
52:00 – QnA

#largelanguagemodels #llms #generativeai

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07:29 Introduction to Large Language Models and their Applications
14:58 Large Language Models are primarily focused on predicting the next word in a sentence.
22:27 LLMs should be connected with external data to avoid hallucination or making up facts.
29:56 Explanation of machine learning types: unsupervised, supervised, reinforcement
37:25 Large language models consist of billions of parameters and are used for various AI tasks.
44:54 Discussing the background and training data of GPT-2 model
52:23 Byte pair encoding is a good approach for large language models to learn new words and achieve good performance.
59:52 IBM announced Watson X LLM model with multilingual capabilities
Crafted by Merlin AI.

Researcher-zu

i did build an app using gpt and whisper api

petswolrd

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