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The Atomic Human
‘The clarity, authority, wit and insight Lawrence brings to bear are like torches shining into the turbulent darkness of a subject we all wonder at, but which we mostly feel unable to even to think or talk about with any confidence. Hugely recommended’ Stephen Fry What does Artificial Intelligence mean for our identity? Our fascination with AI stems from the perceived uniqueness of human intelligence. We believe it's what differentiates us. Fears of AI not only concern how it invades our digital lives, but also the implied threat of an intelligence that displaces us from our position at the centre of the world. Neil D. Lawrence's visionary book shows why these fears may be misplaced. Ato...
Gone
The last time that anyone heard from 35-year-old Claudia Lawrence, a chef at the University of York, was when she sent a text message to a friend on 18 March 2009 at 8.23 p.m. She has never been heard from or seen again, and her disappearance is a mystery that endures to this day. What happened to Claudia that early spring evening – or was it early the following morning on her way to work? There had been nothing abnormal about her behaviour before she vanished, and there were no signs of a struggle at her home. A Crimewatch reconstruction has been broadcast, and the police investigation into the case has cost more than £750,000. Dozens of interviews have thrown up numerous leads, but there are no concrete clues. With extensive access to her family and friends, in Gone, Neil Root assesses the facts and theories and asks: where is Claudia?
The Atomic Human
A renowned computer scientist seeks the unique human quality that will prevail against artificial intelligence. The greatest fear of AI is not that it rules out digital lives but that it displaces human intelligence entirely. If artificial intelligence takes over decision-making what, then, is unique and irreplaceable about human intelligence? The Atomic Human is a journey of discovery to the core of what it is to be human, in search of the qualities that cannot be replaced by the machine. Neil Lawrence brings a timely, fresh perspective to this new, emerging era, recounting his personal journey to understand the riddle of intelligence. By understanding the essential element of what makes us...
D.H. Lawrence, Travel and Cultural Difference
This study of Lawrence's travel writings is the first book-length study to approach the subject with reference to contemporary post-colonial theory. Focusing on the writings of 1921-25, the period when Lawrence was most intensely engaged in travel, it includes chapters on Sea and Sardinia, Kangaroo, The Plumed Serpent and the essays and stories inspired by Lawrence's experience of the New World.
D H Lawrence: Women in Love
Part 1: The context of Women in Love. General Introduction; Lawrence's early life and work; The composition of Women in Love; Women in Love and the First World War; People, Places and Libel Threats; Sexuality; Class. Part 2: Artistic Influences and Strategies. Tradition and Experiment; Thomas Hardy and the Russian Novel;' You mustn't look in my novel for the old stable ego of the character'; Modernist movements: Futurism, Imagism, Expressionism; Morality and the Novel. Part 3: Reading Women in Love. Part 4: Reception. Part 5: Bibliography.
D. H. Lawrence
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Dataset Shift in Machine Learning
An overview of recent efforts in the machine learning community to deal with dataset and covariate shift, which occurs when test and training inputs and outputs have different distributions. Dataset shift is a common problem in predictive modeling that occurs when the joint distribution of inputs and outputs differs between training and test stages. Covariate shift, a particular case of dataset shift, occurs when only the input distribution changes. Dataset shift is present in most practical applications, for reasons ranging from the bias introduced by experimental design to the irreproducibility of the testing conditions at training time. (An example is -email spam filtering, which may fail...
Learning and Inference in Computational Systems Biology
Tools and techniques for biological inference problems at scales ranging from genome-wide to pathway-specific. Computational systems biology unifies the mechanistic approach of systems biology with the data-driven approach of computational biology. Computational systems biology aims to develop algorithms that uncover the structure and parameterization of the underlying mechanistic model--in other words, to answer specific questions about the underlying mechanisms of a biological system--in a process that can be thought of as learning or inference. This volume offers state-of-the-art perspectives from computational biology, statistics, modeling, and machine learning on new methodologies for l...
Deterministic and Statistical Methods in Machine Learning
This book consitutes the refereed proceedings of the First International Workshop on Machine Learning held in Sheffield, UK, in September 2004. The 19 revised full papers presented were carefully reviewed and selected for inclusion in the book. They address all current issues in the rapidly maturing field of machine learning that aims to provide practical methods for data discovery, categorisation and modelling. The particular focus of the workshop was advanced research methods in machine learning and statistical signal processing.
Lawrence of Arabia's War
This radically new perspective on T. E. Lawrence, the Arab Revolt, and WWI in the Middle East provides essential insight into today’s violent conflicts. Archaeologist and historian Neil Faulkner draws on ten years of field research in the Middle East to offer the first truly multidisciplinary history of the conflicts that raged in Sinai, Arabia, Palestine, and Syria during the First World War. Rarely is a book published that revises our understanding of an entire world region and the history that has defined it. This groundbreaking volume makes just such a contribution. In Lawrence of Arabia’s War, Faulkner sheds new light on British intelligence officer T. E. Lawrence and his legendary military campaigns. He explores the intersections among the declining Ottoman Empire, the Bedouin tribes, rising Arab nationalism, and Western imperial ambition. Faulkner arrives at a provocative new analysis of Ottoman resilience in the face of modern industrialized warfare. This analysis leads him to reassesses the relative weight of conventional operations in Palestine and irregular warfare in Syria—and thus the historic roots of today’s divided, fractious, war-torn Middle East.
