Bøker av Yair Neuman

Searching for a needle in a haystack is an important task in several contexts of data analysis and decision-making. Examples include identifying the insider threat within an organization, the prediction of failure in industrial production or pinpointing the unique signature of a solo perpetrator, such as school shooter or a lone wolf terrorist.

This concise volume offers an accessible introduction to state-of-the-art AI language models, providing a platform for their use in textual interpretation across the humanities and social sciences.

Crowds are misleading, both in their simplicity and in their complexity. On the one hand, they behave according to expected trends; on the other, they present sudden shifts and frantic, unexpected behavior. Therefore, "betting against the crowd," whether in politics, sports, or finance, requires a deep understanding of the crowd's dynamics. In this book, Prof. Neuman addresses this challenge by delving into the complexity of crowds. The book involves foundational issues and novel ideas, such as why crowds behave unexpectedly, why betting against the crowd is possible only in short time frames, why is it important to be attentive to suspicious signs that are indicative of the crowd's behavior, and why the long tail of fatalities in armed conflicts leaves us surprised by blitz attacks of violent mobs. The book combines scientific knowledge, experiments, and accessible, often humorous, exposition. It can be read by anyone with a basic science education who seeks to understand crowds and how one can act within and against them.

Searching for a needle in a haystack is an important task in several contexts of data analysis and decision-making. Examples include identifying the insider threat within an organization, the prediction of failure in industrial production, or pinpointing the unique signature of a solo perpetrator, such as a school shooter or a lone wolf terrorist. It is a challenge different from that of identifying a rare event (e.g., a tsunami) or detecting anomalies because the "needle" is not easily distinguished from the haystack. This challenging context is imbued with particular difficulties, from the lack of sufficient data to train a machine learning model through the identification of the relevant features and up to the painful price of false alarms, which might cause us to question the relevance of machine learning solutions even if they perform well according to common performance criteria. In this book, Prof. Neuman approaches the problem of finding the needle by specifically focusing on the human factor, from solo perpetrators to insider threats. Providing for the first time a deep, critical, multidimensional, and methodological analysis of the challenge, the book offers data scientists and decision makers a deep scientific foundational approach combined with a pragmatic practical approach that may guide them in searching for a needle in a haystack.

Most of us are intuitively familiar with small social systems, such as families and soccer teams. The book aims to explain, illustrate, and model the unique and fascinating nature of small (social) systems by relying on deep scientific foundations and by using examples from sport, movies, music, and the martial arts.

This book uncovers mathematical structures underlying natural intelligence and applies category theory as a modeling language for understanding human cognition, giving readers new insights into the nature of human thought.

Provocative and engaging, this text invites you into a unique thought experiment, using portraits from some of Shakespeare's most stirring works to illustrate how our psychological understanding of human nature and personality can be significantly enriched through literature.