This post is based on the following report: Dathathri, R., Madotto, A., & Chandra, B. (2022). Generative Language Models: A Survey and Taxonomy. arXiv preprint arXiv:2301.04246.
Books
The AI Revolution in Medicine by Peter Lee; Carey Goldberg; Isaac KohaneAI is about to transform medicine. Here's what you need to know right now. ''The development of AI is as fundamental as the creation of the personal computer. It will change the way people work, learn, and communicate--and transform healthcare. But it must be managed carefully to ensure its benefits outweigh the risks. I'm encouraged to see this early exploration of the opportunities and responsibilities of AI in medicine.'' --Bill Gates Just months ago, millions of people were stunned by ChatGPT's amazing abilities -- and its bizarre hallucinations. But that was 2022. GPT-4 is now here: smarter, more accurate, with deeper technical knowledge. GPT-4 and its competitors and followers are on the verge of transforming medicine. But with lives on the line, you need to understand these technologies -- stat. What can they do? What can't they do -- yet? What shouldn't they ever do? To decide, experience the cutting edge for yourself. Join three insiders who've had months of early access to GPT-4 as they reveal its momentous potential -- to improve diagnoses, summarize patient visits, streamline processes, accelerate research, and much more. You'll see real GPT-4 dialogues -- unrehearsed and unfiltered, brilliant and blundering alike -- all annotated with invaluable context, candid commentary, real risk insights, and up-to-the-minute takeaways. Preview a day in the life of a doctor with a true AI assistant. See how AI can enhance doctor-patient encounters at the bedside and beyond. Learn how modern AI works, why it can fail, and how it can be tested to earn trust. Empower patients: improve access and equity, fill gaps in care, and support behavior change. Ask better questions and get better answers with "prompt engineering." Leverage AI to cut waste, uncover fraud, streamline reimbursement, and lower costs. Optimize clinical trials and accelerate cures with AI as a research collaborator. Find the right guardrails and gain crucial insights for regulators and policymakers. Sketch possible futures: What dreams may come next? There has never been technology like this. Whether you're a physician, patient, healthcare leader, payer, policymaker, or investor, AI will profoundly impact you -- and it might make the difference between life or death. Be informed, be ready, and take charge -- with this book.
Call Number: R859.7 .A78
ISBN: 9780138200138
Publication Date: 2023-05-06
Generative Deep Learning by David FosterGenerative AI is the hottest topic in tech. This practical book teaches machine learning engineers and data scientists how to use TensorFlow and Keras to create impressive generative deep learning models from scratch, including variational autoencoders (VAEs), generative adversarial networks (GANs), Transformers, normalizing flows, energy-based models, and denoising diffusion models. The book starts with the basics of deep learning and progresses to cutting-edge architectures. Through tips and tricks, you'll understand how to make your models learn more efficiently and become more creative. Discover how VAEs can change facial expressions in photos Train GANs to generate images based on your own dataset Build diffusion models to produce new varieties of flowers Train your own GPT for text generation Learn how large language models like ChatGPT are trained Explore state-of-the-art architectures such as StyleGAN2 and ViT-VQGAN Compose polyphonic music using Transformers and MuseGAN Understand how generative world models can solve reinforcement learning tasks Dive into multimodal models such as DALL.E 2, Imagen, and Stable Diffusion This book also explores the future of generative AI and how individuals and companies can proactively begin to leverage this remarkable new technology to create competitive advantage.
Call Number: Q325.5 .F67 2023
ISBN: 9781098134143
Publication Date: 2022-06-28
Regular Expression Puzzles and AI Coding Assistants: 24 Puzzles Solved by the Author, with and Without Assistance from Copilot, ChatGPT and More by David MertzLearn how AI-assisted coding using ChatGPT and GitHub Copilot can dramatically increase your productivity (and fun) in writing regular expressions and other programmes. "How these tools can be both so very amazing in what they produce, and simultaneously so utterly doltish in their numerous failures, is the main thing this book tries to understand. For reasons I attempt to elucidate throughout, of all the domains of computer programming, games with regular expressions are particularly well suited for getting a grasp on the peculiar behaviors of AI." From the Preface For programmers of any experience level - no experience with AI coding tools is required. Regular Expression Puzzles and AI Coding Assistants is the story of two competitors. On the one side is David Mertz, an expert programmer and the author of the Web's most popular Regex tutorial. On the other are the AI powerhouse coding assistants, GitHub Copilot and OpenAI ChatGPT. Here's how the contest works: David invents 24 Regex problems he calls puzzles and shows you how to tackle each one. When he's done he has Copilot and ChatGPT work the same puzzles. What they produce intrigues him. Which side is likelier to get it right? Which will write simple and elegant code? Which one makes the smartest use of lesser-known Regex library features? Read the book to find out. David also offers AI best practices, showing how smart prompts return better results. By the end, you'll be a master at solving your own Regex puzzles, whether you use AI or not. About the technology Ground-breaking large language model research from OpenAI, Google, Amazon, and others, have transformed expectations of machine-generated software. But how do these AI assistants, like ChatGPT and GitHub Copilot, measure up against regular expressions--a workhorse technology for developers used to describe, find, and manipulate patterns in the text? Regular expressions are compact, complex, and subtle. Will AI assistants handle the challenge?