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Complete Obsolete Guide to Generative AI by David Clinton
Return to Generative AI
The Complete Obsolete Guide to Generative AI by David Clinton
MEAP began October 2023 Publication in May 2024 (estimated)
ISBN 978-1633436985 170 pages (estimated)
https://www.youtube.com/watch?v=-POBfgKKLFc
The last book on AI you’ll ever need. We swear!
“How do you keep up with a topic that changes day to day? It seems like whatever you learned about artificial intelligence at lunchtime is obsolete by dinner. That means you have two choices. You can give up in frustration or you can learn what’s long-lasting about generative AI: the what and the why — even as how you use it continues to evolve.
Inside The Complete Obsolete Guide to Generative AI you will find:
- Just enough background info on AI! What an AI model is how it works
- Ways to create text, code, and images for your organization's needs
- Training AI models on your local data stores or on the internet
- Business intelligence and business analytics uses for AI
- Building your own custom AI models
- Looking ahead to the future of generative AI
The Complete Obsolete Guide to Generative AI is a lighthearted look at programming with AI, as well as a rock-solid resource for getting the best out of these insanely powerful services. Let it be your guide to creating images and presentations, working with data feeds, prompt engineering, and much more. Going far deeper than any Medium article, this book gives you the tools you need to work better, faster, and smarter with AI, while making peace with your new robot overlords at the same time.
about the book
AI technology moves so fast that this book is probably already out of date! But don’t worry — The Complete Obsolete Guide to Generative AI is still an essential read for anyone who wants to make generative AI into a tool rather than a toy. It shows you how to get the best out of AI no matter what changes come in the future. You’ll be able to use common AI automation and scripting tools to take AI to a new level, and access raw (and powerful) GPT models via API.
What else? How about creating exciting images, video, and even audio with AI. Need more? Learn to harness AI to speed up any everyday work task, including writing boilerplate code, creating specialized documents, and analyzing your own data. Push beyond simple ChatGPT prompts! Discover ways to double your productivity and take on projects you never thought were possible! AI—and this book—are here to show you how. search inside this book
about the reader
For Python programmers at any level who want to turbo-charge their results.
about the author
David Clinton is an AWS Solutions Architect and a Linux server administrator. While he has authored two previous books for Manning (as well as books and video courses for other publishers), this is his finest work yet.
- Snippet from Wikipedia: Generative artificial intelligence
Generative artificial intelligence (generative AI, GenAI, or GAI) is artificial intelligence capable of generating text, images, videos, or other data using generative models, often in response to prompts. Generative AI models learn the patterns and structure of their input training data and then generate new data that has similar characteristics.
Improvements in transformer-based deep neural networks, particularly large language models (LLMs), enabled an AI boom of generative AI systems in the early 2020s. These include chatbots such as ChatGPT, Copilot, Gemini and LLaMA, text-to-image artificial intelligence image generation systems such as Stable Diffusion, Midjourney and DALL-E, and text-to-video AI generators such as Sora. Companies such as OpenAI, Anthropic, Microsoft, Google, and Baidu as well as numerous smaller firms have developed generative AI models.
Generative AI has uses across a wide range of industries, including software development, healthcare, finance, entertainment, customer service, sales and marketing, art, writing, fashion, and product design. However, concerns have been raised about the potential misuse of generative AI such as cybercrime, the use of fake news or deepfakes to deceive or manipulate people, and the mass replacement of human jobs.
Fair Use Sources
- Generative AI for Archive Access for Fair Use Preservation, quoting, paraphrasing, excerpting and/or commenting upon
Artificial Intelligence (AI): AI Fundamentals, AI Inventor: Arthur Samuel of IBM 1959 coined term Machine Learning. Synonym Self-Teaching Computers from 1950s. Experimental AI “Learning Machine” called Cybertron in early 1960s by Raytheon Company; ChatGPT, NLP, GAN, AI winter, The Singularity, AI FUD, Quantum FUD (Fake Quantum Computers), AI Propaganda, Quantum Propaganda, Cloud AI (AWS AI, Azure AI, Google AI-GCP AI-Google Cloud AI, IBM AI, Apple AI), Deep Learning (DL), Machine learning (ML), AI History, AI Bibliography, Manning AI-ML-DL-NLP-GAN Series, AI Glossary, AI Topics, AI Courses, AI Libraries, AI frameworks, AI GitHub, AI Awesome List. (navbar_ai - See also navbar_dl, navbar_ml, navbar_nlp, navbar_chatgpt)
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