Humans have always dreamed of automating laborious physical and intellectual tasks, but the latter has proved more elusive than naively suspected. Seven decades of systematic study of Artificial Intelligence have witnessed cycles of hubris and despair. The successful realization of General Intelligence (evidenced by the kind of cross-domain flexibility enjoyed by humans) will spawn an industry worth billions and transform the range of viable automation tasks.The recent notable successes of Machine Learning has lead to conjecture that it might be the appropriate technology for delivering General Intelligence. In this book, we argue that the framework of machine learning is fundamentally at odds with any reasonable notion of intelligence and that essential insights from previous decades of AI research are being forgotten. We claim that a fundamental change in perspective is required, mirroring that which took place in the philosophy of science in the mid 20th century. We propose a framework for General Intelligence, together with a reference architecture that emphasizes the need for anytime bounded rationality and a situated denotational semantics. We given necessary emphasis to compositional reasoning, with the required compositionality being provided via principled symbolic-numeric inference mechanisms based on universal constructions from category theory.• Details the pragmatic requirements for real-world General Intelligence.• Describes how machine learning fails to meet these requirements.• Provides a philosophical basis for the proposed approach.• Provides mathematical detail for a reference architecture.• Describes a research program intended to address issues of concern in contemporary AI.The book includes an extensive bibliography, with ~400 entries covering the history of AI and many related areas of computer science and mathematics.The target audience is the entire gamut of Artificial Intelligence/Machine Learning researchers and industrial practitioners. There are a mixture of descriptive and rigorous sections, according to the nature of the topic. Undergraduate mathematics is in general sufficient. Familiarity with category theory is advantageous for a complete understanding of the more advanced sections, but these may be skipped by the reader who desires an overall picture of the essential concepts This is an open access book.
In this book, Jasper Neel’s sure-to-be-controversial resituating of Aristotle centers around three questions that have been constants in his twenty-two years of teaching experience: What does itmean to teach writing? What should one know before teaching writing? And, if there is such a thing as "research in the teaching of writing," what is it? Believing that all composition teachers are situated politically and socially, both as part of the institution in which they teach and as beings with lived histories, Neel examines his own life and the life of composition studies as a discipline in the context of Aristotle. Neel first situates the Rhetoric as a political document; he then situates the Rhetoric in the Aristotelian system and describes how professional discourse came to know itself through Aristotle’s way of studying the world; finally, he examines the operation of the Rhetoric inside itself before arguing the need to turn to Aristotle’s notion of sophistry as a way of negating his system. By pointing out the connections among Aristotelian rhetoric, the contemporary university, and the contemporary writing teacher, Neel shows that Aristotle’s frightening social theories are as alive today as are Aristotelian notions of discourse. Neel explains that by their very nature teachers must speak with a professional voice. It is through showing how to "hear" one’s professional voice that Neel explores the notion of professional discourse that originates with Aristotle. In maintaining that one must pay a high price in order to speak through Aristotle’s theory or to assume the role of "professional," he argues that no neutral ground exists either for pedagogy or for the analysis of pedagogy. Neel concludes this discussion by proposing that Aristotelian sophistry is both an antidote to Aristotelian racism, sexism, and bigotry and a way of allowing Aristotelian categories of discourse to remain useful. Finally, as an Aristotelian, a teacher, and a writer, Neel responds both to Aristotle and to professionalism by rethinking the influence of the past and reviving the voice of Aristotelian sophistry.
The writers of CollegeHumor.com share irreverent advice on how to navigate the peaks and valleys of today's sexual, financial, and social arenas, from bluffing one's way through an on-the-job conversation to using buzzwords to impress cultural circles.
The author describes her experiences during a fourteen-year stay in Tibet, as she studied and participated in the occult philosophies of mystics and magicians
Jasper Neel analyzes the emerging field of composition studies within the epistemological and ontological debate over writing precipitated by Plato, who would have us abandon writing entirely, and continued by Derrida, who argues that all human beings are written. This book offers a three-part exploration of that debate.
Humans have always dreamed of automating laborious physical and intellectual tasks, but the latter has proved more elusive than naively suspected. Seven decades of systematic study of Artificial Intelligence have witnessed cycles of hubris and despair. The successful realization of General Intelligence (evidenced by the kind of cross-domain flexibility enjoyed by humans) will spawn an industry worth billions and transform the range of viable automation tasks.The recent notable successes of Machine Learning has lead to conjecture that it might be the appropriate technology for delivering General Intelligence. In this book, we argue that the framework of machine learning is fundamentally at odds with any reasonable notion of intelligence and that essential insights from previous decades of AI research are being forgotten. We claim that a fundamental change in perspective is required, mirroring that which took place in the philosophy of science in the mid 20th century. We propose a framework for General Intelligence, together with a reference architecture that emphasizes the need for anytime bounded rationality and a situated denotational semantics. We given necessary emphasis to compositional reasoning, with the required compositionality being provided via principled symbolic-numeric inference mechanisms based on universal constructions from category theory.• Details the pragmatic requirements for real-world General Intelligence.• Describes how machine learning fails to meet these requirements.• Provides a philosophical basis for the proposed approach.• Provides mathematical detail for a reference architecture.• Describes a research program intended to address issues of concern in contemporary AI.The book includes an extensive bibliography, with ~400 entries covering the history of AI and many related areas of computer science and mathematics.The target audience is the entire gamut of Artificial Intelligence/Machine Learning researchers and industrial practitioners. There are a mixture of descriptive and rigorous sections, according to the nature of the topic. Undergraduate mathematics is in general sufficient. Familiarity with category theory is advantageous for a complete understanding of the more advanced sections, but these may be skipped by the reader who desires an overall picture of the essential concepts This is an open access book.
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