The self-assembling brain: how neural networks grow smarter
"In this book, Peter Robin Hiesinger explores historical and contemporary attempts to understand the information needed to make biological and artificial neural networks. Developmental neurobiologists and computer scientists with an interest in artificial intelligence - driven by the promise an...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Princeton
Princeton University Press
[2021]
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| Schlagworte: | |
| Zusammenfassung: | "In this book, Peter Robin Hiesinger explores historical and contemporary attempts to understand the information needed to make biological and artificial neural networks. Developmental neurobiologists and computer scientists with an interest in artificial intelligence - driven by the promise and resources of biomedical research on the one hand, and by the promise and advances of computer technology on the other - are trying to understand the fundamental principles that guide the generation of an intelligent system. Yet, though researchers in these disciplines share a common interest, their perspectives and approaches are often quite different. The book makes the case that "the information problem" underlies both fields, driving the questions that are driving forward the frontiers, and aims to encourage cross-disciplinary communication and understanding, to help both fields make progress. The questions that challenge researchers in these fields include the following. How does genetic information unfold during the years-long process of human brain development, and can this be a short-cut to create human-level artificial intelligence? Is the biological brain just messy hardware that can be improved upon by running learning algorithms in computers? Can artificial intelligence bypass evolutionary programming of "grown" networks? These questions are tightly linked, and answering them requires an understanding of how information unfolds algorithmically to generate functional neural networks. Via a series of closely linked "discussions" (fictional dialogues between researchers in different disciplines) and pedagogical "seminars," the author explores the different challenges facing researchers working on neural networks, their different perspectives and approaches, as well as the common ground and understanding to be found amongst those sharing an interest in the development of biological brains and artificial intelligent systems"-- |
| Beschreibung: | xiii, 364 Seiten Illustrationen |
| ISBN: | 9780691181226 0691181225 |
Internformat
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| 520 | 3 | |a "In this book, Peter Robin Hiesinger explores historical and contemporary attempts to understand the information needed to make biological and artificial neural networks. Developmental neurobiologists and computer scientists with an interest in artificial intelligence - driven by the promise and resources of biomedical research on the one hand, and by the promise and advances of computer technology on the other - are trying to understand the fundamental principles that guide the generation of an intelligent system. Yet, though researchers in these disciplines share a common interest, their perspectives and approaches are often quite different. The book makes the case that "the information problem" underlies both fields, driving the questions that are driving forward the frontiers, and aims to encourage cross-disciplinary communication and understanding, to help both fields make progress. The questions that challenge researchers in these fields include the following. How does genetic information unfold during the years-long process of human brain development, and can this be a short-cut to create human-level artificial intelligence? Is the biological brain just messy hardware that can be improved upon by running learning algorithms in computers? Can artificial intelligence bypass evolutionary programming of "grown" networks? These questions are tightly linked, and answering them requires an understanding of how information unfolds algorithmically to generate functional neural networks. Via a series of closely linked "discussions" (fictional dialogues between researchers in different disciplines) and pedagogical "seminars," the author explores the different challenges facing researchers working on neural networks, their different perspectives and approaches, as well as the common ground and understanding to be found amongst those sharing an interest in the development of biological brains and artificial intelligent systems"-- | |
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| id | DE-604.BV047245810 |
| illustrated | Illustrated |
| index_date | 2024-07-03T17:06:17Z |
| indexdate | 2024-07-10T09:06:43Z |
| institution | BVB |
| isbn | 9780691181226 0691181225 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-032649979 |
| oclc_num | 1257808234 |
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| owner_facet | DE-188 DE-91G DE-BY-TUM DE-20 |
| physical | xiii, 364 Seiten Illustrationen |
| publishDate | 2021 |
| publishDateSearch | 2021 |
| publishDateSort | 2021 |
| publisher | Princeton University Press |
| record_format | marc |
| spelling | Hiesinger, Peter Robin 1972- Verfasser (DE-588)122323041 aut The self-assembling brain how neural networks grow smarter Peter Robin Hiesinger Princeton Princeton University Press [2021] xiii, 364 Seiten Illustrationen txt rdacontent n rdamedia nc rdacarrier "In this book, Peter Robin Hiesinger explores historical and contemporary attempts to understand the information needed to make biological and artificial neural networks. Developmental neurobiologists and computer scientists with an interest in artificial intelligence - driven by the promise and resources of biomedical research on the one hand, and by the promise and advances of computer technology on the other - are trying to understand the fundamental principles that guide the generation of an intelligent system. Yet, though researchers in these disciplines share a common interest, their perspectives and approaches are often quite different. The book makes the case that "the information problem" underlies both fields, driving the questions that are driving forward the frontiers, and aims to encourage cross-disciplinary communication and understanding, to help both fields make progress. The questions that challenge researchers in these fields include the following. How does genetic information unfold during the years-long process of human brain development, and can this be a short-cut to create human-level artificial intelligence? Is the biological brain just messy hardware that can be improved upon by running learning algorithms in computers? Can artificial intelligence bypass evolutionary programming of "grown" networks? These questions are tightly linked, and answering them requires an understanding of how information unfolds algorithmically to generate functional neural networks. Via a series of closely linked "discussions" (fictional dialogues between researchers in different disciplines) and pedagogical "seminars," the author explores the different challenges facing researchers working on neural networks, their different perspectives and approaches, as well as the common ground and understanding to be found amongst those sharing an interest in the development of biological brains and artificial intelligent systems"-- Neural networks (Computer science) Neural circuitry / Adaptation Learning / Psysiological aspects Artificial intelligence Erscheint auch als Online-Ausgabe 978-0-691-21551-8 |
| spellingShingle | Hiesinger, Peter Robin 1972- The self-assembling brain how neural networks grow smarter |
| title | The self-assembling brain how neural networks grow smarter |
| title_auth | The self-assembling brain how neural networks grow smarter |
| title_exact_search | The self-assembling brain how neural networks grow smarter |
| title_exact_search_txtP | The self-assembling brain how neural networks grow smarter |
| title_full | The self-assembling brain how neural networks grow smarter Peter Robin Hiesinger |
| title_fullStr | The self-assembling brain how neural networks grow smarter Peter Robin Hiesinger |
| title_full_unstemmed | The self-assembling brain how neural networks grow smarter Peter Robin Hiesinger |
| title_short | The self-assembling brain |
| title_sort | the self assembling brain how neural networks grow smarter |
| title_sub | how neural networks grow smarter |
| work_keys_str_mv | AT hiesingerpeterrobin theselfassemblingbrainhowneuralnetworksgrowsmarter |