"1337 Use Cases for ChatGPT & other Chatbots in the AI-Driven Era" is a book written by Florin Badita that explores the potential uses of advanced large language models (LLMs) like ChatGPT in various industries and scenarios. The book provides 1337 use cases and around 4000 examples of how these technologies can be applied in the future. The author, Florin Badita, is a data scientist, social entrepreneur, activist, and artist who has written about his experiences with data analysis on Medium. He is on the Forbes 30 under 30 list, a TedX speaker, and Landecker Democracy Fellow 2021-2022. He is known for his work in activism, founding the civic group Corruption Kills in 2015, GIS, data analysis, and data mining. The book covers a variety of tips and strategies, including how to avoid errors when converting between different units, how to provide context and examples to improve the LLM's understanding of the content, and how to use the Markdown language to format and style text in chatbot responses. The book is intended for anyone interested in learning more about the capabilities and potential uses of ChatGPT and other language models in the rapidly evolving world of artificial intelligence. After the introduction part and the Table of content, the book is split into 20 categories, each category then being split into smaller categories with at least one use-case and multiple examples A real example from the book: Category: 4 Science and technology [...] Sub-Category: 4.60 Robotics 4.60.1 Text Generation General example text prompt: "Generate a description of a new robot design" Formula: "Generate [description] of [robot design]" Specific examples of prompts: "Generate a detailed description of a robot designed for underwater exploration" "Generate a brief overview of a robot designed for assisting with construction tasks" "Generate a marketing pitch for a robot designed to assist with household chores" 4.60.2 Programming Assistance General example text prompt: "Write code to implement a specific behavior in a robot" Formula: "Write code to [implement behavior] in [robot]" Specific examples of prompts: "Write code to make a robot follow a specific path using sensors and control algorithms" "Write code to make a robot respond to voice commands using natural language processing" "Write code to make a robot perform basic tasks in a manufacturing setting, such as moving objects from one location to another"

Machine learning applications perform better with human feedback. Keeping the right people in the loop improves the accuracy of models, reduces errors in data, lowers costs, and helps you ship models faster. Human-in-the-loop machine learning lays out methods for humans and machines to work together effectively. You'll find best practices on selecting sample data for human feedback, quality control for human annotations, and designing annotation interfaces. You'll learn to dreate training data for labeling, object detection, and semantic segmentation, sequence labeling, and more. The book starts with the basics and progresses to advanced techniques like transfer learning and self-supervision within annotation workflows.

A new way of thinking about data science and data ethics that is informed by the ideas of intersectional feminism. Today, data science is a form of power. It has been used to expose injustice, improve health outcomes, and topple governments. But it has also been used to discriminate, police, and surveil. This potential for good, on the one hand, and harm, on the other, makes it essential to ask: Data science by whom? Data science for whom? Data science with whose interests in mind? The narratives around big data and data science are overwhelmingly white, male, and techno-heroic. In Data Feminism, Catherine D'Ignazio and Lauren Klein present a new way of thinking about data science and data ethics—one that is informed by intersectional feminist thought. Illustrating data feminism in action, D'Ignazio and Klein show how challenges to the male/female binary can help challenge other hierarchical (and empirically wrong) classification systems. They explain how, for example, an understanding of emotion can expand our ideas about effective data visualization, and how the concept of invisible labor can expose the significant human efforts required by our automated systems. And they show why the data never, ever “speak for themselves.” Data Feminism offers strategies for data scientists seeking to learn how feminism can help them work toward justice, and for feminists who want to focus their efforts on the growing field of data science. But Data Feminism is about much more than gender. It is about power, about who has it and who doesn't, and about how those differentials of power can be challenged and changed.

This book constitutes the refereed proceedings of the Second International Conference, SLAAI-ICAI 2018, held in Moratuwa, Sri Lanka, in December 2018. The 32 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in the following topical sections: ​intelligence systems; neural networks; game theory; ontology engineering; natural language processing; agent based system; signal and image processing.

Technology drives the future we create. But are we steering that technology in directions that create that future in the best way, for the most people? In her new book

AI may be the greatest opportunity of our time, with the potential to add nearly $16 trillion to the global economy over the next decade. But so far, adoption has been much slower than anticipated, or so headlines may lead you to believe. With this practical guide, business leaders will discover where they are in their AI journey and learn the steps necessary to successfully scale AI throughout their organization. Authors Rob Thomas and Paul Zikopoulos from IBM introduce C-suite executives and business professionals to the AI Ladder—a unified, prescriptive approach to help them understand and accelerate the AI journey. Complete with real-world examples and real-life experiences, this book explores AI drivers, value, and opportunity, as well as the adoption challenges organizations face. Understand why you can’t have AI without an information architecture (IA) Appreciate how AI is as much a cultural change as it is a technological one Collect data and make it simple and accessible, regardless of where it lives Organize data to create a business-ready analytics foundation Analyze data, and build and scale AI with trust and transparency Infuse AI throughout your entire business and create intelligent workflows

State-of-the-art, flat structures called metasurfaces can filter and steer light and sound, render an object completely invisible to electromagnetic waves, and much more. They can deliver automation, remote operation, and advanced performance to a wide variety of existing systems, with applications in communications, medical imaging, sensing, and security. However, for non-specialists, individual metasurfaces are currently restricted to limited reusability and accessibility. This book brings together various scientific disciplines with the aim of outlining a programmable ‘plug-and-play’ metasurface. The book focuses on a recently proposed platform – known as the HyperSurface – that provides many electromagnetic functions of metasurfaces in a single structure, which can be controlled and reconfigured by software. This revolutionary approach paves the way for new opportunities in wireless communications and programmable wireless environments: HyperSurfaces could link networks with objects and physical environments and create smarter systems that are far more responsive to user demands. Walls that absorb radiation or block digital eavesdropping, and wireless, long-distance charging of devices are among the many possibilities. The book aspires to provide the foundational knowledge for creating an Internet of Materials, enabling smart environments at any scale – from indoor wireless communications to medical imaging equipment. Although the set of disciplines involved covers a considerable span, we hope that the material will benefit experts and students alike.