Every language carries its own history of migration, resistance, and identity. This book is a practical guide for linguists and cultural stewards who want a hand in shaping how AI learns the world’s languages, not just the ones with the most training data.
ABOUT THE AUTHOR
Sudha Jamthe is a technology futurist, globally renowned author, educator and independent researcher with 25+ years of entrepreneurial and operational experience in the technology industry. Jamthe is a top LinkedIn Learning instructor for courses on AI, GenAI, Agent AI and Internet of Things who enjoys mentoring business leaders to innovate with No-Code AI. Jamthe’s research focuses on AIX Design, Autonomous Vehicles and Language AI. Jamthe builds online learning communities at weeklywed at Business School of AI and spotlights voices of women at IoTWomen. Jamthe has developed and taught AI, AI ethics and Autonomous Vehicles courses at Stanford Continuing Studies, Barcelona Technology School, Business School of AI and EMBA Consortium at Lucas School of Business. Jamthe has co-founded Global South in AI and upskills language researchers for world languages. Jamthe’s aspiration is a limitless world. Jamthe enjoys chasing self-driving cars and hugging robots.
About The Book
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.
Calling humanity scholars, linguists, computational linguists, and technologists seeking to develop language models that preserve the cultural richness of the world’s voices.
Join the Linguist Community
Join a growing community of linguists, cultural stewards, and humanities scholars working together to shape how AI learns the world’s languages. Led by Sudha Jamthe, author of Large Language Models for Linguists, the community connects people building datasets, benchmarks, and tools that honor the cultures behind every language.