MAKE ART with Artificial Intelligence A guide on practical artificial intelligence for drawing, art, illustration, and design - for everyone interested in creativity, art, and technology. The book has hundreds of original illustrations made or augmented with AI, 20+ online and video tutorials, 35+ Python notebooks, a GitHub repository and a blockchain art gallery. Written and illustrated by Kevin Ashley, a Microsoft developer hall of fame engineer, and an author of books and courses on artificial intelligence. Think of this book as v3.0 of your drawing class manual on how to sketch, draw faces, emotions, body poses, landscapes, apply light, color, style, emotion, expressions, perspective, generate animations, speech and more with artificial intelligence. All artwork from this book is created or augmented with machine learning and available in online NFT gallery, as well as tutorials and practical examples. The impact of this book in data science community inspired a group of Microsoft engineers and data scientists to implement a project they called Azure Picasso to streamline the path from a conceptual artwork, enhanced with artificial intelligence to publishing art in online galleries. FROM REVIEWS This is similar to the best lecture classes I had in college where the professor talked in class about the concepts and fundamentals but then gave us homework that would let us experiment and try out the concepts hands-on. As an artist who has 30 years of artwork looking to share, I love this book because it's approachable to the novice and useful to the expert. EDITIONS Beautiful Paperback, 8x10, color edition, more illustrations than the e-book, reads like an art book, beautiful print and high-quality paper. eBook - easy to read on phones, tablets and online readers, reflowing text, great for practical tutorials, as the book has many links to tutorials. CONTENTS Getting Started (History of Art and AI - Drawing - Sketching - Action and Poses - Landscapes and Scenery - Animation - Selling your Art) Creative Tools (Traditional tools - Digital tools - AI Tools - Python - Notebooks - Practice Studies). Neural Networks for Art (Neurons - Neural networks - Supervised learning - Unsupervised learning - Generative Adversarial Networks - Machine Learning Models and Training - Reinforcement learning - Practice Studies) Drawing and Sketching with AI (Sketching - Improving Sketches with AI - Childhood Drawings - Creativity - Inking - Shading and Light - Coloring - Practice Studies) Faces and Facial Expressions (How AI recognizes human faces - Facial features - Emotions - 3D Faces - Cartoons and Caricature - Anime and Manga - Generating Faces with AI) Pose and Actions with AI (Action with AI - Keypoints - Pose Estimation - Drawing Human Body - Human Pose Datasets - Perspective and Depth) Landscapes and Scenery (Landscapes - Generating Landscapes - AI Models and Methods for Landscapes - Practice Studies) Style and Content (Style and Style Transfer in Art and AI - Generative Adversarial Networks - Creative Style) Animation with AI (History of Animation - 12 Principles of Animation - Using AI for Animation - Animating Speech, Lips and Faces) How to Sell your Art with Blockchain and NFT (Why Blockchain - Smart Contracts and NFTs - Creating a Crypto Wallet - Creating your Gallery - Listing for Sale - Getting Paid) The book comes with online tutorials, including assets, resources and notebooks for artists, data scientists or engineers. With basic Python you can create stunning works of art, but the knowledge of Python is not required. Enjoy this unique and insightful book!

An authority on creativity introduces us to AI-powered computers that are creating art, literature, and music that may well surpass the creations of humans. Today's computers are composing music that sounds “more Bach than Bach,” turning photographs into paintings in the style of Van Gogh's Starry Night, and even writing screenplays. But are computers truly creative—or are they merely tools to be used by musicians, artists, and writers? In this book, Arthur I. Miller takes us on a tour of creativity in the age of machines. Miller, an authority on creativity, identifies the key factors essential to the creative process, from “the need for introspection” to “the ability to discover the key problem.” He talks to people on the cutting edge of artificial intelligence, encountering computers that mimic the brain and machines that have defeated champions in chess, Jeopardy!, and Go. In the central part of the book, Miller explores the riches of computer-created art, introducing us to artists and computer scientists who have, among much else, unleashed an artificial neural network to create a nightmarish, multi-eyed dog-cat; taught AI to imagine; developed a robot that paints; created algorithms for poetry; and produced the world's first computer-composed musical, Beyond the Fence, staged by Android Lloyd Webber and friends. But, Miller writes, in order to be truly creative, machines will need to step into the world. He probes the nature of consciousness and speaks to researchers trying to develop emotions and consciousness in computers. Miller argues that computers can already be as creative as humans—and someday will surpass us. But this is not a dystopian account; Miller celebrates the creative possibilities of artificial intelligence in art, music, and literature.

An examination of machine learning art and its practice in new media art and music. Over the past decade, an artistic movement has emerged that draws on machine learning as both inspiration and medium. In this book, transdisciplinary artist-researcher Sofian Audry examines artistic practices at the intersection of machine learning and new media art, providing conceptual tools and historical perspectives for new media artists, musicians, composers, writers, curators, and theorists. Audry looks at works from a broad range of practices, including new media installation, robotic art, visual art, electronic music and sound, and electronic literature, connecting machine learning art to such earlier artistic practices as cybernetics art, artificial life art, and evolutionary art. Machine learning underlies computational systems that are biologically inspired, statistically driven, agent-based networked entities that program themselves. Audry explains the fundamental design of machine learning algorithmic structures in terms accessible to the nonspecialist while framing these technologies within larger historical and conceptual spaces. Audry debunks myths about machine learning art, including the ideas that machine learning can create art without artists and that machine learning will soon bring about superhuman intelligence and creativity. Audry considers learning procedures, describing how artists hijack the training process by playing with evaluative functions; discusses trainable machines and models, explaining how different types of machine learning systems enable different kinds of artistic practices; and reviews the role of data in machine learning art, showing how artists use data as a raw material to steer learning systems and arguing that machine learning allows for novel forms of algorithmic remixes.

In AI Art, Joanna Zylinska cuts through the smoke and mirrors surrounding the current narratives of computation, robotics and Artificial Intelligence. Offering a critique of the political underpinnings of AI and its dominant aesthetics, this book raises broader questions about the conditions of art making, creativity and labour today.

A multidisciplinary introduction to the field of computational creativity, analyzing the impact of advanced generative technologies on art and music. As algorithms get smarter, what role will computers play in the creation of music, art, and other cultural artifacts? Will they be able to create such things from the ground up, and will such creations be meaningful? In Beyond the Creative Species, Oliver Bown offers a multidisciplinary examination of computational creativity, analyzing the impact of advanced generative technologies on art and music. Drawing on a wide range of disciplines, including artificial intelligence and machine learning, design, social theory, the psychology of creativity, and creative practice research, Bown argues that to understand computational creativity, we must not only consider what computationally creative algorithms actually do, but also examine creative artistic activity itself.

AI for Arts is a book for anyone fascinated by the man–machine connection, an unstoppable evolution that is intertwining us with technology in an ever-greater degree, and where there is an increasing concern that it will be technology that comes out on top. Thus, presented here through perhaps its most esoteric form, namely art, this unfolding conundrum is brought to its apex. What is left of us humans if artificial intelligence also surpasses us when it comes to art? The articulation of an artificial intelligence art manifesto is long overdue, so hopefully this book can fill a gap that will have repercussions not only for aesthetic and philosophical considerations but possibly more so for the development of artificial intelligence.

Emotions, creativity, aesthetics, artistic behavior, divergent thoughts, and curiosity are both fundamental to the human experience and instrumental in the development of human-centered artificial intelligence systems that can relate, communicate, and understand human motivations, desires, and needs. In this book the editors put forward two core propositions: creative artistic behavior is one of the key challenges of artificial intelligence research, and computer-assisted creativity and human-centered artificial intelligence systems are the driving forces for research in this area. The invited chapters examine computational creativity and more specifically systems that exhibit artistic behavior or can improve humans' creative and artistic abilities. The authors synthesize and reflect on current trends, identify core challenges and opportunities, and present novel contributions and applications in domains such as the visual arts, music, 3D environments, and games. The book will be valuable for researchers, creatives, and others engaged with the relationship between artificial intelligence and the arts.