Babbage's two lives

Babbage wrote two relatively detailed, yet significantly incongruous, autobiographical accounts of his pre-Cambridge and Cambridge days. He published one in 1864 and in it advertised the existence of the other, which he carefully retained in manuscript form. The aim of this paper is to chart in some detail for the first time the discrepancies between the two accounts, to compare and assess their relative credibility, and to explain their author's possible reasons for knowingly fabricating the less credible of the tw

Sound Knowledge: Music and Science in London, 1789-1851

What does it mean to hear scientifically? What does it mean to see musically? This volume uncovers a new side to the long nineteenth century in London, a hidden history in which virtuosic musical entertainment and scientific discovery intersected in remarkable ways. Sound Knowledge examines how scientific truth was accrued by means of visual and aural experience, and, in turn, how musical knowledge was located in relation to empirical scientific practice. James Q. Davies and Ellen Lockhart gather work by leading scholars to explore a crucial sixty-year period, beginning with Charles Burney’s ambitious General History of Music, a four-volume study of music around the globe, and extending to the Great Exhibition of 1851, where musical instruments were assembled alongside the technologies of science and industry in the immense glass-encased collections of the Crystal Palace. Importantly, as the contributions show, both the power of science and the power of music relied on performance, spectacle, and experiment. Ultimately, this volume sets the stage for a new picture of modern disciplinarity, shining light on an era before the division of aural and visual knowledge

19th Conference of The Associations of Christians In The Mathematical Sciences

Association of Christians in the Mathematical Sciences 19th Biennial Conference Proceedings, May 29 - June 1, 2011, Bethel University

LMentry: A Language Model Benchmark of Elementary Language Tasks

As the performance of large language models rapidly improves, benchmarks are getting larger and more complex as well. We present LMentry, a benchmark that avoids this "arms race" by focusing on a compact set of tasks that are trivial to humans, e.g. writing a sentence containing a specific word, identifying which words in a list belong to a specific category, or choosing which of two words is longer. LMentry is specifically designed to provide quick and interpretable insights into the capabilities and robustness of large language models. Our experiments reveal a wide variety of failure cases that, while immediately obvious to humans, pose a considerable challenge for large language models, including OpenAI's latest 175B-parameter instruction-tuned model, TextDavinci002. LMentry complements contemporary evaluation approaches of large language models, providing a quick, automatic, and easy-to-run "unit test", without resorting to large benchmark suites of complex tasks.Comment: 24 pages, 2 figure

Lewis Carroll at Play

Lewis Carroll, a.k.a. Charles Lutwidge Dodgson, is a person whose books, Alice in Wonderland and Through the Looking Glass, have been quoted frequently in this century and are loved and cherished by many. Almost everyone as a child has listened to or read about Alice and her adventures in Wonderland. Why are they so popular? Florence Becker Lennon said Dodgson was able to "deal with contradictions and horrors and irrationalities, and to convert them into an art form that gives release to children and adults alike." The comedy and attention to "paradoxes of the human condition" is one reason adult readers love Lewis Carroll; because he journeys with them on the "quest for meaning and order" (Rackin 103). Yet another reason could be that he makes math puzzles and the like fun and enjoyable--One doesn't realize they are mathematical puzzles. He unified math, puzzles and games (including chess) and literature, concepts dynamically opposed which most people would not believe could ever go together. Some critics believe Lewis Carroll (a.k.a. Charles Lutwidge Dodgson) included more in than what readers usually notice. Florence Becker Lennon, Carroll's biographer, writes, "After all, Carroll was a philosopher, which means he transmuted his experiences into something beyond life" (Lennon 178). Also, Lewis Carroll was an excellent logician while Dodgson was not. If someone wants to see how great of a logician he was, Wonderland is the place to look (Weaver 24). In the math, logic and games Carroll created a series of experiences that challenged Alice and continue to challenge the reader today. Lewis Carroll has intrigued computer scientists and mathematicians-and all people interested in these subjects-by his inclusion of math, logic and games in the Alice books. Math was important to Dodgson since he was a mathematician. Computer science is built upon mathematical concepts and principles and technology during Carroll's age was increasing. Dodgson also enjoyed to reason things out by use of logical deduction. Computer science requires people to logically think about what a program is supposed to do and how to write the code so it will do it. Games are also important to Carroll and provide the basis for much of his humor in the books. These have rules by which players must abide by in order to win. The same holds true for computer scientists who must write code within certain constraints such as time and space. These three major topics of interest to Carroll provide the basis to analyze how they relate to computer science

Symbols Purely Mechanical: Language, Modernity, and the Rise of the Algorithm, 1605–1862

In recent decades, scholars in both Digital Humanities and Critical Media Studies have encountered a disconnect between algorithms and what are typically thought of as “cultural” concerns. In Digital Humanities, researchers employing algorithmic methods in the study of literature have faced what Alan Liu has called a “meaning problem”—a difficulty in reconciling computational results with traditional forms of interpretation. Conversely, in Critical Media Studies, some thinkers have questioned the adequacy of interpretive methods as means of understanding computational systems. This dissertation offers a historical account of how this disconnect came into being by examining the attitudes toward algorithms that existed in the three centuries prior to the development of the modern computer. Bringing together the histories of semiotics, poetics, and mathematics, I show that the present divide between algorithmic and interpretive methods results from a cluster of assumptions about historical change that developed in the eighteenth and nineteenth centuries and that implicates attempts to give meaning to algorithms in the modern narrative of technological progress. My account organizes the early-modern discourse on algorithms into three distinct intellectual traditions that arose in subsequent periods. The first tradition, which reached its peak in the mid-seventeenth century, held that the correspondence between algorithm and meaning was guaranteed by divine providence, making algorithms a potential basis for a non- arbitrary mode of representation that can apply to any field of knowledge, including poetics as well as mathematics. A second tradition, most influential from the last decades of the seventeenth century to around 1800, denied that the correspondence between algorithm and meaning was pre-ordained and sought, instead, to create this correspondence by altering the ways people think. Finally, starting in the Romantic period, algorithms and culture came to be viewed as operating autonomously from one another, an intellectual turn that, I argue, continues to inform the way people view algorithms in the present day. By uncovering this history, this dissertation reveals some of the tacit assumptions that underlie present debates about the interface between computation and culture. The reason algorithms present humanists with a meaning problem, I argue, is that cultural and technical considerations now stand in different relations to history: culture is seen as arising from collective practices that lie beyond the control of any individual, whereas the technical details of algorithms are treated as changeable at will. It is because of this compartmentalization, I maintain, that the idea of progress plays such a persistent role in discussions of digital technologies; similarly to the Modernist avant garde, computing machines have license to break with established semantic conventions and thus to lead culture in new directions. As an alternative to this technocratic arrangement, I call for two complementary practices: a philology of algorithms that resituates them in history, and a poetic approach to computation that embraces misalignments between algorithm and meaning

Computational Natural Philosophy: A Thread from Presocratics through Turing to ChatGPT

Modern computational natural philosophy conceptualizes the universe in terms of information and computation, establishing a framework for the study of cognition and intelligence. Despite some critiques, this computational perspective has significantly influenced our understanding of the natural world, leading to the development of AI systems like ChatGPT based on deep neural networks. Advancements in this domain have been facilitated by interdisciplinary research, integrating knowledge from multiple fields to simulate complex systems. Large Language Models (LLMs), such as ChatGPT, represent this approach's capabilities, utilizing reinforcement learning with human feedback (RLHF). Current research initiatives aim to integrate neural networks with symbolic computing, introducing a new generation of hybrid computational models.Comment: 17 page