Transformers Unveiled An In Depth Study Of Large Language Models And Their Innovations
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Transformers Unveiled: An In-Depth Study of Large Language Models and Their Innovations
Imagine a world where machines understand and respond to your every command, crafting eloquent prose, generating intricate code, and answering your questions with unparalleled accuracy. This is the reality brought forth by Large Language Models (LLMs), the next generation of artificial intelligence that is revolutionizing every aspect of our lives. "Transformers Unveiled" takes you on a journey to the heart of this groundbreaking technology, unraveling the complexities of LLMs and their extraordinary capabilities. From their foundational principles to the latest advancements, this book equips you with the knowledge to understand and appreciate the immense power of these intelligent machines. Within these pages, you'll explore the architecture of transformer networks, the driving force behind LLMs. Discover how these models are trained on massive datasets, allowing them to learn intricate patterns and generate human-like text. Explore the fascinating world of natural language processing (NLP), where LLMs are transforming the way we interact with machines, enabling seamless communication and unlocking new possibilities. This book is your guide to understanding the transformative impact of LLMs on our world.
Research and Innovation Forum 2024
This book features research presented and discussed during the Research & Innovation Forum (Rii Forum) 2024. As such, this book offers a unique insight into emerging topics, issues and developments pertinent to the fields of technology, innovation and education and their social impact. Papers included in this book apply inter- and multi-disciplinary approaches to query such issues as technology-enhanced teaching and learning, smart cities, information systems, cognitive computing and social networking. What brings these threads of the discussion together is the question of how advances in computer science—which are otherwise largely incomprehensible to researchers from other fields—can be effectively translated and capitalized on so as to make them beneficial for society as a whole. In this context, Rii Forum and Rii Forum proceedings offer an essential venue where diverse stakeholders, including academics, the think tank sector and decision-makers, can engage in a meaningful dialogue with a view to improving the applicability of advances in computer science.
Machine Learning and Immersive Technologies for User-centered Digital Healthcare Innovation
Author: Federico Colecchia
language: en
Publisher: Frontiers Media SA
Release Date: 2025-06-09
Emerging technologies such as machine learning and immersive technologies (including virtual reality and augmented reality) hold great potential for driving disruptive healthcare innovation. However, the adoption of digital technology in healthcare, including use of data-driven tools in support of clinical decision-making and patient-facing applications relying on consumer electronic devices, is often hindered by issues of user experience, trust, equitability, and fairness. There is increasing recognition of a need to facilitate further convergence between the development of emerging technologies and user-centered design research for healthcare, with a view to achieving a positive impact on patients, care professionals, and the healthcare system. This article collection addresses current development trends relating to user-centered digital healthcare innovation based on machine learning and immersive technologies, in order to identify opportunities associated with the deployment of new solutions in a range of environments – including clinical, domestic, and educational settings – and barriers to the adoption of technology by end users. A key aim is to identify opportunities for strengthening interdisciplinary collaboration as well as methods of lowering barriers and overcoming obstacles for the benefit of patients, care professionals, and the healthcare system. Examples of potential outcomes are effective design and use of solutions based on machine learning and immersive technologies to improve user experience, strategies to facilitate ethical development of digital technology for healthcare, and methods of encouraging adoption of advanced tools developed in line with principles of equitability and fairness. Articles should address issues of user-centered digital healthcare innovation driven by machine learning and immersive technologies. Submissions should ideally be positioned at the intersection of digital technology development with user-centered design, although contributions more technical in nature as well as user experience studies are also welcome. A non-exhaustive list of suitable topics and manuscript types is given below: • Machine learning and/or immersive technologies (including augmented reality and virtual reality) for user-centered digital healthcare. • Clinical decision support systems. • Patient-facing applications. • Tools for education and training of future medical professionals. • Potential barriers to adoption of technology: issues of user experience, trust, equitability, and fairness in digital healthcare. • Reviews and contributions discussing the development of intuitive, accessible, and inclusive digital interfaces. • All aspects of healthcare that are being or have the potential to be impacted by machine learning and immersive technologies.