Breaking The Language Barrier Demystifying Language Models With Openai
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Breaking the Language Barrier: Demystifying Language Models with OpenAI by Rayan Wali Pdf
Breaking the Language Barrier: Demystifying Language Models with OpenAI is an informative guide that covers practical NLP use cases, from machine translation to vector search, in a clear and accessible manner. In addition to providing insights into the latest technology that powers ChatGPT and other OpenAI language models, including GPT-3 and DALL-E, this book also showcases how to use OpenAI on the cloud, specifically on Microsoft Azure, to create scalable and efficient solutions.
Impact of AI on Advancing Women's Safety by Ponnusamy, Sivaram,Bora, Vibha,Daigavane, Prema M.,Wazalwar, Sampada S. Pdf
Women encounter multifaceted threats, ranging from personal safety hazards to discrimination deeply embedded in societal structures. The existing landscape demands innovative strategies to ensure women can participate fully in society without fear or impediment. Traditional systems often fall short, necessitating a paradigm shift in our approach to women's safety. Impact of AI on Advancing Women's Safety emerges as a groundbreaking solution to address the pervasive challenges they face. From the shadows of harassment to systemic biases in justice systems, women navigate a complex landscape. This book delves into the pressing issues, unveiling a visionary approach that leverages artificial intelligence to create tangible, transformative solutions.
A Practical Guide to AI and Data Analytics by Rayan Wali Pdf
Whether you are looking to prepare for AI/ML/Data Science job interviews or you are a beginner in the field of Data Science and AI, this book is designed for engineers and AI enthusiasts like you at all skill levels. Taking a different approach from a traditional textbook style of instruction, A Practical Guide to AI and Data Analytics touches on all of the fundamental topics you will need to understand deeper into machine learning and artificial intelligence research, literature, and practical applications with its three parts: Part I: A Conceptual (and Visual) Illustration [topics including, but not limited to, are listed below] Fundamentals of Data Science The Data and Machine Learning Pipelines Data Preprocessing + Worked Data Preprocessing Strategy Data Visualization Python for Data Analysis Calculus & Linear Algebra Fundamentals Data Structures and Algorithms Exercises Machine Learning Models & Algorithms (kNN, Neural Networks, Hidden Markov Models, Ensemble Methods, etc.) Deep Learning for Computer Vision & NLP (CNNs, RNNs, etc.) Data Mining Model Deployment Time Series Data Analysis AI Systems in the Real-World Applications of Data Analysis Exercises Database Systems & Cloud Computing (with practical example) Functional Programming for Data Analytics Part II: 10 Full-Length Case Studies Case Study I: Sports Web Scraping Case Study II: NLP Textual Analysis Case Study III: Emergency Response Duration Analysis Case Study IV: MNIST Image Classification Case Study V: COVID-19 Statistical Data Analysis Case Study VI: COVID-19 Chest X-Ray Screening Case Study VII: Signal Strength Geospatial Analysis Case Study VIII: NYC Crash Accidents Data Analysis Case Study IX: Sales Forecasting Case Study X: Meteorite Landings Analysis Part III: A Full-Length Data Science and Analytics Skills Assessment (DSSA) With exercises that span a wide range of AI problems from different domains, from the economics and finance to transportation and medical industries, the DSSA aims to provide a comprehensive assessment to measure your understanding through cleverly-designed AI reasoning, problem-solving, and scenario-based exercises, whether you use it to enhance your understanding in the AI and Data Analytics field or use it to prepare for your AI/Data Analytics problem solving and system design interviews. Section I: 60 Multiple-Choice and Short-Answer Exercises Section II: 5 AI & Data Analytics Problem Solving and Coding Exercises Solutions to Sections I and II are included With an illustrative approach to instruction, worked examples, and case studies, this easy-to-understand book simplifies many of the AI and Data Analytics key concepts, leading to an improvement of AI/ML system design skills.
AI and education by Miao, Fengchun,Holmes, Wayne,Ronghuai Huang,Hui Zhang,UNESCO Pdf
Artificial Intelligence (AI) has the potential to address some of the biggest challenges in education today, innovate teaching and learning practices, and ultimately accelerate the progress towards SDG 4. However, these rapid technological developments inevitably bring multiple risks and challenges, which have so far outpaced policy debates and regulatory frameworks. This publication offers guidance for policy-makers on how best to leverage the opportunities and address the risks, presented by the growing connection between AI and education. It starts with the essentials of AI: definitions, techniques and technologies. It continues with a detailed analysis of the emerging trends and implications of AI for teaching and learning, including how we can ensure the ethical, inclusive and equitable use of AI in education, how education can prepare humans to live and work with AI, and how AI can be applied to enhance education. It finally introduces the challenges of harnessing AI to achieve SDG 4 and offers concrete actionable recommendations for policy-makers to plan policies and programmes for local contexts. [Publisher summary, ed]
Applied Natural Language Processing in the Enterprise by Ankur A. Patel,Ajay Uppili Arasanipalai Pdf
NLP has exploded in popularity over the last few years. But while Google, Facebook, OpenAI, and others continue to release larger language models, many teams still struggle with building NLP applications that live up to the hype. This hands-on guide helps you get up to speed on the latest and most promising trends in NLP. With a basic understanding of machine learning and some Python experience, you'll learn how to build, train, and deploy models for real-world applications in your organization. Authors Ankur Patel and Ajay Uppili Arasanipalai guide you through the process using code and examples that highlight the best practices in modern NLP. Use state-of-the-art NLP models such as BERT and GPT-3 to solve NLP tasks such as named entity recognition, text classification, semantic search, and reading comprehension Train NLP models with performance comparable or superior to that of out-of-the-box systems Learn about Transformer architecture and modern tricks like transfer learning that have taken the NLP world by storm Become familiar with the tools of the trade, including spaCy, Hugging Face, and fast.ai Build core parts of the NLP pipeline--including tokenizers, embeddings, and language models--from scratch using Python and PyTorch Take your models out of Jupyter notebooks and learn how to deploy, monitor, and maintain them in production
Exploring GPT-3 by Steve Tingiris,Bret Kinsella Pdf
Get started with GPT-3 and the OpenAI API for natural language processing using JavaScript and Python Key FeaturesUnderstand the power of potential GPT-3 language models and the risks involvedExplore core GPT-3 use cases such as text generation, classification, and semantic search using engaging examplesPlan and prepare a GPT-3 application for the OpenAI review process required for publishing a live applicationBook 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 book 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 book will help you get started. Beginning with a high-level introduction to NLP and GPT-3, the book 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 book illustrates the possible applications of GPT-3 in production. By the end of this book, 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 learnUnderstand what GPT-3 is and how it can be used for various NLP tasksGet a high-level introduction to GPT-3 and the OpenAI APIImplement JavaScript and Python code examples that call the OpenAI APIStructure GPT-3 prompts and options to get the best possible resultsSelect the right GPT-3 engine or model to optimize for speed and cost-efficiencyFind out which use cases would not be suitable for GPT-3Create a GPT-3-powered knowledge base application that follows OpenAI guidelinesWho this book is for Exploring GPT-3 is for anyone interested in natural language processing or learning GPT-3 with or without a technical background. Developers, product managers, entrepreneurs, and hobbyists looking to get to grips with NLP, AI, and GPT-3 will find this book useful. Basic computer skills are all you need to get the most out of this book.
Blockchain Technology and Applications by Ahmed Banafa Pdf
Blockchain is an emerging technology that can radically improve transactions security at banking, supply chain, and other transaction networks. It’s estimated that Blockchain will generate $3.1 trillion in new business value by 2030. Essentially, it provides the basis for a dynamic distributed ledger that can be applied to save time when recording transactions between parties, remove costs associated with intermediaries, and reduce risks of fraud and tampering. This book explores the fundamentals and applications of Blockchain technology. Readers will learn about the decentralized peer-to-peer network, distributed ledger, and the trust model that defines Blockchain technology. They will also be introduced to the basic components of Blockchain (transaction, block, block header, and the chain), its operations (hashing, verification, validation, and consensus model), underlying algorithms, and essentials of trust (hard fork and soft fork). Private and public Blockchain networks similar to Bitcoin and Ethereum will be introduced, as will concepts of Smart Contracts, Proof of Work and Proof of Stack, and cryptocurrency including Facebook’s Libra will be elucidated. Also, the book will address the relationship between Blockchain technology, Internet of Things (IoT), Artificial Intelligence (AI), Cybersecurity, Digital Transformation and Quantum Computing.Readers will understand the inner workings and applications of this disruptive technology and its potential impact on all aspects of the business world and society. A look at the future trends of Blockchain Technology will be presented in the book.
This book goes beyond the hype, delving into real world technologies and applications that are driving our future and examines the possible impact these changes will have on industries, economies and society at large. It details the actions governments and regulators must take in order to ensure these changes bring about positive benefits to the public without stifling innovation that may well be the future source of value creation. It examines how organisations in a world of digital ecosystems, where industry boundaries are blurring, must undertake radical digital transformation to survive and thrive in this new digital world. The reader is taken through a framework that critically examines (i) Digital Connectivity including 5G and IoT; (ii) Data Capture and Distribution which includes smart connected verticals; (iii) Data Integrity, Control and Tokenisation that includes cyber security, digital signatures, blockchain, smart contracts, digital assets and cryptocurrencies; (iv) Data Processing and Artificial Intelligence; and (v) Disruptive Applications which include platforms, virtual and augmented reality, drones, autonomous vehicles, digital twins and digital assistants.
Responsible Data Science by Peter C. Bruce,Grant Fleming Pdf
Explore the most serious prevalent ethical issues in data science with this insightful new resource The increasing popularity of data science has resulted in numerous well-publicized cases of bias, injustice, and discrimination. The widespread deployment of “Black box” algorithms that are difficult or impossible to understand and explain, even for their developers, is a primary source of these unanticipated harms, making modern techniques and methods for manipulating large data sets seem sinister, even dangerous. When put in the hands of authoritarian governments, these algorithms have enabled suppression of political dissent and persecution of minorities. To prevent these harms, data scientists everywhere must come to understand how the algorithms that they build and deploy may harm certain groups or be unfair. Responsible Data Science delivers a comprehensive, practical treatment of how to implement data science solutions in an even-handed and ethical manner that minimizes the risk of undue harm to vulnerable members of society. Both data science practitioners and managers of analytics teams will learn how to: Improve model transparency, even for black box models Diagnose bias and unfairness within models using multiple metrics Audit projects to ensure fairness and minimize the possibility of unintended harm Perfect for data science practitioners, Responsible Data Science will also earn a spot on the bookshelves of technically inclined managers, software developers, and statisticians.
Create conversational UIs using cutting-edge frameworks Key FeaturesBuild AI chatbots and voicebots using practical and accessible toolkitsDesign and create voicebots that really shine in front of humansWork with familiar appliances like Alexa, Google Home, and FB MessengerDesign for UI success across different industries and use casesBook Description We are entering the age of conversational interfaces, where we will interact with AI bots using chat and voice. But how do we create a good conversation? How do we design and build voicebots and chatbots that can carry successful conversations in in the real world? In this book, Rachel Batish introduces us to the world of conversational applications, bots and AI. You’ll discover how - with little technical knowledge - you can build successful and meaningful conversational UIs. You’ll find detailed guidance on how to build and deploy bots on the leading conversational platforms, including Amazon Alexa, Google Home, and Facebook Messenger. You’ll then learn key design aspects for building conversational UIs that will really succeed and shine in front of humans. You’ll discover how your AI bots can become part of a meaningful conversation with humans, using techniques such as persona shaping, and tone analysis. For successful bots in the real world, you’ll explore important use-cases and examples where humans interact with bots. With examples across finance, travel, and e-commerce, you’ll see how you can create successful conversational UIs in any sector. Expand your horizons further as Rachel shares with you her insights into cutting-edge voicebot and chatbot technologies, and how the future might unfold. Join in right now and start building successful, high impact bots! What you will learnBuild your own AI voicebots and chatbotsUse familiar appliances like Alexa, Google Home, and Facebook MessengerMaster the elements of conversational user interfacesKey design techniques to make your bots successfulUse tone analysis to deepen UI conversation for humansCreate voicebots and UIs designed for real-world situationsInsightful case studies in finance, travel, and e-commerceCutting-edge technology and insight into the future of AI botsWho this book is for This book is for you, if you want to deepen your appreciation of UI and how conversational UIs - driven by artificial intelligence - are transforming the way humans interact with computers, appliances, and the everyday world around us. This book works with the major UI toolkits available today, so you do not need a deep programming knowledge to build the bots in this book: a basic familiarity with markup languages and JavaScript will give you everything you need to start building cutting-edge conversational UIs.
How to Compete in the Age of Artificial Intelligence by Soumendra Mohanty,Sachin Vyas Pdf
Get started with artificial intelligence in your business. This book will help you understand AI, its implications, and how to adopt a strategy that is rational, relevant, and practical. Beyond the buzzwords and the technology complexities, organizations are struggling to understand what AI means for their industry and how they can start their journey. How to Compete in the Age of Artificial Intelligence is not a book about complex formulas or solution architectures. It goes deeper into explaining the meaning and relevance of AI for your business. You will learn how to apply AI thinking across enterprise functions, including disruptive technologies such as IoT, Blockchain, and cloud, and transform your organization. What You'll Learn: Know how to spot AI opportunities and establish the right organizational imperatives to grow your business ; Understand AI in the context of changing business dynamics and the workforce/skills required to succeed ; Discover how to apply AI thinking across enterprise functions, from the boardroom to cybersecurity, IoT, IT operations, policies, and implement a sustainable and integrated human-machine collaboration strategy.
This book provides a trove of insightful perspectives on the current state and the realization of digital surgery. Digital surgery entails the application of artificial intelligence and machine learning toward automation in robotic-assisted surgery. More generally, the objective is to digitally define the patient, the surgical field, and the surgical problem or task at hand; to operate based on information, rather than based on anatomic planes alone. But digital surgery has shapeshifted into other, equally intriguing faces – many of which are exemplified by topics throughout this book. Digital surgery is fundamental to 3D-printed organs, mind-controlled limbs, image-guided navigation, and tele-mentoring. It is the key that unlocks the metaphorical doorway to surgical access, thereby creating a global framework for surgical training, education, planning, and much more. This text provides methods of measurement and perception outside of the human umwelt – including the ability to visualize fields beyond the visible light spectrum, via near infrared fluorescent organic dyes which are rapidly being bioengineered to target specific tumors, as well as native anatomic structures of interest. Written by experts in the field, Digital Surgery is designed to help surgeons operate with an enriched understanding of an individual’s specific attributes: including the human phenome, physiome, microbiome, genome, and epigenome. It also aids surgeons in harnessing the power and fluidity of the cloud, which is emerging as a significant resource for surgeons both regionally and globally.
Diffusion and Adoption of Information Technology by Karlheinz Kautz,Jan Pries-Heje Pdf
It. is well known that t.he introduction of a new technology in one organization not always produces the intended benefits (Levine, 1994). In many cases, either the receivers do not reach the intended level of use or simply the technology is rejected because it does not match with the expectations (true or false) and the accepted psychological effort to use it. The case of formal methods is a paradigmatic example of continual failures. The published cases with problems or failures only constitute the visible part of a large iceberg of adoption cases. It. is difficult to get companies to openly express the problems they had; however, from the experience of the author, failure cases are very common and they include any type of company. Many reasons to explain the failures (and in some cases the successes) could be postulated; however, the experiences are not structured enough and it is difficult to extract from them useful guidelines for avoiding future problems. Generally speaking, there is a trend to find the root of the problems in the technol ogy itself and in its adequacy with the preexistent technological context. Technocratic technology transfer models describe the problems in terms of these aspects. Although it is true that those factors limit the probability of success, there is another source of explanations linked to the individuals and working teams and how they perceive the technology.
Today, early-stage investors and entrepreneurs find themselves in a dilemma in which they must choose between profit and impact; between traditional, for-profit-only models on the one hand, and multiple-bottom-line structures with a positive social or environmental impact on the other. At a time in which climate change, exponentially growing technologies, social polarization, and looming pandemics are calling into question humanity’s priorities, this Report to the Club of Rome and the World Academy of Art and Science dissolves this dilemma by proposing a new investment paradigm, namely Integral Investing. Integral Investing incorporates and transcends the best practices of both traditional venture capital and impact investing. It provides a seamless integration and shows how technological progress need not be our rival, but can instead be our ally in ensuring the prosperous society we all want. Drawing on her own investments and stellar track record since 1995, the author reveals the mechanism of Integral Investing. At the heart of it is a powerful, 360-degree de-risking tool called the Theta Model, which reveals how to make smart investment decisions based on the comprehensive integration of traditional due-diligence criteria, sustainability metrics, and assessments of the founders’ and team culture. But it doesn’t stop there. In turn, this handbook demonstrates how to use human-centered AI to scale and digitalize the investment process. The goal here is to accelerate the use of exponential tech, capital, and consciousness leadership to transition to a sustainable global society: a process the author refers to as the Investment Turnaround. The 21 principles of Integral Investing, which she defines using Ken Wilber’s Integral Theory, lead to her manifesto on how to implement the UN Sustainable Development Goals within Planetary Boundaries by 2050 through early-stage investing and entrepreneurship. Similar to the 15th century, when the Medicis inspired the Renaissance, today humanity is once again at a crucial turning point where pioneering public and private financiers, investors, entrepreneurs, and other committed individuals have the opportunity to leave behind the legacy of a prosperous society. This handbook provides a source of inspiration, and shows how self-actualization, a positive mindset, and a consciousness that is backed by a world-centric desire can become the driving force for solving the global grand challenges.
Deep Reinforcement Learning with Python by Nimish Sanghi Pdf
Deep reinforcement learning is a fast-growing discipline that is making a significant impact in fields of autonomous vehicles, robotics, healthcare, finance, and many more. This book covers deep reinforcement learning using deep-q learning and policy gradient models with coding exercise. You'll begin by reviewing the Markov decision processes, Bellman equations, and dynamic programming that form the core concepts and foundation of deep reinforcement learning. Next, you'll study model-free learning followed by function approximation using neural networks and deep learning. This is followed by various deep reinforcement learning algorithms such as deep q-networks, various flavors of actor-critic methods, and other policy-based methods. You'll also look at exploration vs exploitation dilemma, a key consideration in reinforcement learning algorithms, along with Monte Carlo tree search (MCTS), which played a key role in the success of AlphaGo. The final chapters conclude with deep reinforcement learning implementation using popular deep learning frameworks such as TensorFlow and PyTorch. In the end, you'll understand deep reinforcement learning along with deep q networks and policy gradient models implementation with TensorFlow, PyTorch, and Open AI Gym. What You'll Learn Examine deep reinforcement learning Implement deep learning algorithms using OpenAI’s Gym environment Code your own game playing agents for Atari using actor-critic algorithms Apply best practices for model building and algorithm training Who This Book Is For Machine learning developers and architects who want to stay ahead of the curve in the field of AI and deep learning.
