Sudha Jamthe – författare

Generative AI (GenAI) is the hottest new area of AI, accelerating innovations affecting all industries and showcasing AI’s ability to present human-like language capabilities with large language models (LLMs). This book builds a solid foundation for the technology underlying GenAI Models, LLM, and foundation and reasoning models for the No-Code audience by explaining the models' workings in simple English. It then takes the reader on a journey to find out where there are gaps to innovate. Each chapter outlines the state of research in each topic and invites learners to build on this research to think about ethical implications and balance it with innovation to benefit everyone. The author covers the technological, product, and societal impact of Generative AI to give a comprehensive guide for this important technology. This book will help the data scientist, product manager, and business leader alike because it covers the API economy and critical industries impacted and offers a framework to think about automation and jobs impacted and what competencies are needed to excel in GenAI and offers an in-depth guide to build GenAI products and applications.

This book bridges linguistics and technology, offering an in-depth exploration of Large Language Models (LLMs) tailored for linguists. It examines how Artificial Intelligence (AI) is trained using language as data, often overlooking linguistic nuance, and empowers linguists to shape AI development to preserve diverse linguistic and cultural heritages.Key Features:Accessible to All: No prior knowledge of technology or coding required, making it ideal for anyone transitioning into AI for languages.Demystifies LLMs: Covers essential concepts like Natural Language Processing (NLP), Named Entity Recognition (NER), hallucinations, fine-tuning, and custom LLMs for languages.Global Scope: Includes research, datasets, and LLM models for languages such as Portuguese, Yoruba, Tamil, Hindi, Swahili, Spanish, Korean, Arabic, Indigenous languages, and sign languages.Cultural Context: Explores how historical trauma, colonialism, migration, and resilience shape language, emphasizing the need for AI to respect this complexity.Practical Playbook: Guides linguists and cultural stewards in creating datasets and benchmarks that honor their communities, showcasing how vocabulary reflects cultural identity.Online Resources: Offers tools, datasets, and community support for building AI tailored to specific languages at LLMLinguist.org.Ideal for humanities scholars, computational linguists, and technologists seeking to develop language models that preserve the cultural richness of the world's voices.

This book bridges linguistics and technology, offering an in-depth exploration of Large Language Models (LLMs) tailored for linguists. It examines how Artificial Intelligence (AI) is trained using language as data, often overlooking linguistic nuance, and empowers linguists to shape AI development to preserve diverse linguistic and cultural heritages.Key Features:Accessible to All: No prior knowledge of technology or coding required, making it ideal for anyone transitioning into AI for languages.Demystifies LLMs: Covers essential concepts like Natural Language Processing (NLP), Named Entity Recognition (NER), hallucinations, fine-tuning, and custom LLMs for languages.Global Scope: Includes research, datasets, and LLM models for languages such as Portuguese, Yoruba, Tamil, Hindi, Swahili, Spanish, Korean, Arabic, Indigenous languages, and sign languages.Cultural Context: Explores how historical trauma, colonialism, migration, and resilience shape language, emphasizing the need for AI to respect this complexity.Practical Playbook: Guides linguists and cultural stewards in creating datasets and benchmarks that honor their communities, showcasing how vocabulary reflects cultural identity.Online Resources: Offers tools, datasets, and community support for building AI tailored to specific languages at LLMLinguist.org.Ideal for humanities scholars, computational linguists, and technologists seeking to develop language models that preserve the cultural richness of the world's voices.