Where did all these books come from? The Publishing Industry and American Intellectual Life

The American book publishing industry shapes the character of American intellectual life. While the newspaper and television industries have been accused of and investigated for bias and lowering America’s intellectual standards, book publishing has gone largely unexamined by scholars. The existing studies of the publishing industry have focused on finance, procedure and history. “There are few ‘theories’ of publishing – efforts to understand the ‘whys’ as well as the ‘hows.’ Few scholarly scientists have devoted significant scholarly attention to publishing” (Altbach and Hoshino, xiii). There are many possible reasons for this lacuna. First, there is a perception that books have always been around, that they are an “old” technology and therefore they don’t appear to have had as much of an impact on our society as television and other media (which were developed quickly and suddenly) seem to have had (Altbach and Hoshino, xiv). Also, despite books’ present and past popularity, television, radio, and now the internet reach more people more easily, and are therefore more topical points of study and observation. In studying the effects of mass media on everyday American life, television and the internet may be the most logical points of study. Regarding public intellectual life however, books play a much more important role. Public intellectual life has always been associated with independent thinkers publishing their work for the masses. For this reason, this I focus on trade publishing. Trade publishing produces fiction and non-fiction works for the general reading public, as opposed to technical manuals, textbooks, and other fiction and nonfiction books targeted to small and specific audiences. Although, quantitatively speaking, “the largest part of book publishing business is embodied in that great complex of companies and activities producing educational, business, scientific, technical, and reference books and materials,” (Tebbel 1987, 439) the trade industry publishes most of the books that most people read. It is the most public segment of the industry, and the most likely place to find public intellectualism. Trade publishing is not only the most public segment of the industry, but it is also the most susceptible to corruption and lowered intellectual standards. Unlike specialty publishing, which caters to a specific, known segment of society, trade publishers must compete with countless other publications, as well as with other forms of media, for the patronage of the general public. As John Tebbel (author of a widely referenced history of the publishing industry) puts it, “The textbook, scientific, or technical book is subjected to much more rigorous scrutiny by buyers and users, and in an intensively competitive market inferior products are quickly lost" (Tebbel 1987, xiv). Since the standards for trade publishing are not nearly as specific – trade books simply need to catch the attention of a significant number of readers, they don’t have to measure up to a given level of quality – the quality of trade books is much more variable. And yet, a successful trade publication can have a much greater impact on society than the most rigorously researched and edited textbook or scholarly study.

Machine learning and small robot navigation

Developing successful navigation and mapping strategies is an essential part of autonomous robot research. However, hardware limitations often make for inaccurate systems. This project serves to investigate efficient alternatives to mapping an environment, by first creating a mobile robot, and then applying machine learning to the robot and controlling systems to increase the robustness of the robot system. My mapping system consists of a semi-autonomous robot drone in communication with a stationary Linux computer system. There are learning systems running on both the robot and the more powerful Linux system. The first stage of this project was devoted to designing and building an inexpensive robot. Utilizing my prior experience from independent studies in robotics, I designed a small mobile robot that was well suited for simple navigation and mapping research. When the major components of the robot base were designed, I began to implement my design. This involved physically constructing the base of the robot, as well as researching and acquiring components such as sensors. Implementing the more complex sensors became a time-consuming task, involving much research and assistance from a variety of sources. A concurrent stage of the project involved researching and experimenting with different types of machine learning systems. I finally settled on using neural networks as the machine learning system to incorporate into my project. Neural nets can be thought of as a structure of interconnected nodes, through which information filters. The type of neural net that I chose to use is a type that requires a known set of data that serves to train the net to produce the desired output. Neural nets are particularly well suited for use with robotic systems as they can handle cases that lie at the extreme edges of the training set, such as may be produced by "noisy" sensor data. Through experimenting with available neural net code, I became familiar with the code and its function, and modified it to be more generic and reusable for multiple applications of neural nets.