Understand the power of potential GPT-3 language models and the risks involved
Explore core GPT-3 use cases such as text generation, classification, and semantic search using engaging examples
Plan and prepare a GPT-3 application for the OpenAI review process required for publishing a live application
Description
Generative Pre-trained Transformer 3 (GPT-3) is a highly advanced language model from OpenAI that can generate written text that is virtually indistinguishable from text written by humans. Whether you have a technical or non-technical background, this audiobook will help you understand and start working with GPT-3 and the OpenAI API.
If you want to get hands-on with leveraging artificial intelligence for natural language processing (NLP) tasks, this easy-to-follow audiobook will help you get started. Beginning with a high-level introduction to NLP and GPT-3, the audiobook takes you through practical examples that show how to leverage the OpenAI API and GPT-3 for text generation, classification, and semantic search. You'll explore the capabilities of the OpenAI API and GPT-3 and find out which NLP use cases GPT-3 is best suited for. You’ll also learn how to use the API and optimize requests for the best possible results. With examples focusing on the OpenAI Playground and easy-to-follow JavaScript and Python code samples, the audiobook explores the possible applications of GPT-3 in production.
By the end of this audiobook, you'll understand the best use cases for GPT-3 and how to integrate the OpenAI API in your applications for a wide array of NLP tasks.
What you will learn
Understand what GPT-3 is and how it can be used for various NLP tasks
Get a high-level introduction to GPT-3 and the OpenAI API
Implement JavaScript and Python code examples that call the OpenAI API
Structure GPT-3 prompts and options to get the best possible results
Select the right GPT-3 engine or model to optimize for speed and cost-efficiency
Find out which use cases would not be suitable for GPT-3
Create a GPT-3-powered knowledge base application that follows OpenAI guidelines
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Steve Tingiris is the founder and managing director of Dabble Lab, a technology research and services company that helps businesses accelerate learning and adoption of natural language processing, conversational AI, and other emerging technologies. He has been designing and building automation solutions for over 20 years and has consulted on conversational AI projects for companies including Amazon, Google, and Twilio. He also publishes technical tutorials on Dabble Lab’s YouTube channel— one of the most popular educational resources for conversational AI developers—and manages several open-source projects, including the Autopilot CLI, Twilio’s recommended tool for building Autopilot bots. To connect with Steve, you can find him on GitHub tingiris or on Twitter tingiris.
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