The self-assembling brain: how neural networks grow smarter
What neurobiology and artificial intelligence tell us about how the brain builds itself How does a neural network become a brain? While neurobiologists investigate how nature accomplishes this feat, computer scientists interested in artificial intelligence strive to achieve this through technology....
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Princeton
Princeton University Press
[2021]
|
| Schlagworte: | |
| Online-Zugang: | FAB01 FAW01 FCO01 FHA01 FKE01 FLA01 UPA01 URL des Erstveröffentlichers |
| Zusammenfassung: | What neurobiology and artificial intelligence tell us about how the brain builds itself How does a neural network become a brain? While neurobiologists investigate how nature accomplishes this feat, computer scientists interested in artificial intelligence strive to achieve this through technology. The Self-Assembling Brain tells the stories of both fields, exploring the historical and modern approaches taken by the scientists pursuing answers to the quandary: What information is necessary to make an intelligent neural network?As Peter Robin Hiesinger argues, "the information problem" underlies both fields, motivating the questions driving forward the frontiers of research. How does genetic information unfold during the years-long process of human brain development-and is there a quicker path to creating human-level artificial intelligence? Is the biological brain just messy hardware, which scientists can improve upon by running learning algorithms on computers? Can AI bypass the evolutionary programming of "grown" networks? Through a series of fictional discussions between researchers across disciplines, complemented by in-depth seminars, Hiesinger explores these tightly linked questions, highlighting the challenges facing scientists, their different disciplinary perspectives and approaches, as well as the common ground shared by those interested in the development of biological brains and AI systems. In the end, Hiesinger contends that the information content of biological and artificial neural networks must unfold in an algorithmic process requiring time and energy. There is no genome and no blueprint that depicts the final product. The self-assembling brain knows no shortcuts.Written for readers interested in advances in neuroscience and artificial intelligence, The Self-Assembling Brain looks at how neural networks grow smarter |
| Beschreibung: | Description based on online resource; title from PDF title page (publisher's Web site, viewed 29. Jul 2021) |
| Beschreibung: | 1 Online-Ressource (xiii, 364 Seiten) Illustrationen |
| ISBN: | 9780691215518 |
| DOI: | 10.1515/9780691215518 |
Internformat
MARC
| LEADER | 00000nmm a2200000zc 4500 | ||
|---|---|---|---|
| 001 | BV047415301 | ||
| 003 | DE-604 | ||
| 005 | 20230113 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 210812s2021 xxu|||| o||u| ||||||eng d | ||
| 020 | |a 9780691215518 |c Online |9 978-0-691-21551-8 | ||
| 024 | 7 | |a 10.1515/9780691215518 |2 doi | |
| 035 | |a (ZDB-23-DGG)9780691215518 | ||
| 035 | |a (OCoLC)1224585570 | ||
| 035 | |a (DE-599)BVBBV047415301 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 044 | |a xxu |c XD-US | ||
| 049 | |a DE-1043 |a DE-1046 |a DE-858 |a DE-Aug4 |a DE-859 |a DE-860 |a DE-739 |a DE-11 | ||
| 082 | 0 | |a 006.3/2 |2 23 | |
| 084 | |a ST 301 |0 (DE-625)143651: |2 rvk | ||
| 100 | 1 | |a Hiesinger, Peter Robin |d 1972- |e Verfasser |0 (DE-588)122323041 |4 aut | |
| 245 | 1 | 0 | |a The self-assembling brain |b how neural networks grow smarter |c Peter Robin Hiesinger |
| 264 | 1 | |a Princeton |b Princeton University Press |c [2021] | |
| 264 | 4 | |c © 2021 | |
| 300 | |a 1 Online-Ressource (xiii, 364 Seiten) |b Illustrationen | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 500 | |a Description based on online resource; title from PDF title page (publisher's Web site, viewed 29. Jul 2021) | ||
| 520 | |a What neurobiology and artificial intelligence tell us about how the brain builds itself How does a neural network become a brain? While neurobiologists investigate how nature accomplishes this feat, computer scientists interested in artificial intelligence strive to achieve this through technology. The Self-Assembling Brain tells the stories of both fields, exploring the historical and modern approaches taken by the scientists pursuing answers to the quandary: What information is necessary to make an intelligent neural network?As Peter Robin Hiesinger argues, "the information problem" underlies both fields, motivating the questions driving forward the frontiers of research. How does genetic information unfold during the years-long process of human brain development-and is there a quicker path to creating human-level artificial intelligence? Is the biological brain just messy hardware, which scientists can improve upon by running learning algorithms on computers? Can AI bypass the evolutionary programming of "grown" networks? Through a series of fictional discussions between researchers across disciplines, complemented by in-depth seminars, Hiesinger explores these tightly linked questions, highlighting the challenges facing scientists, their different disciplinary perspectives and approaches, as well as the common ground shared by those interested in the development of biological brains and AI systems. In the end, Hiesinger contends that the information content of biological and artificial neural networks must unfold in an algorithmic process requiring time and energy. There is no genome and no blueprint that depicts the final product. The self-assembling brain knows no shortcuts.Written for readers interested in advances in neuroscience and artificial intelligence, The Self-Assembling Brain looks at how neural networks grow smarter | ||
| 650 | 7 | |a SCIENCE / Life Sciences / Neuroscience |2 bisacsh | |
| 650 | 4 | |a Artificial intelligence | |
| 650 | 4 | |a Learning |x Psysiological aspects | |
| 650 | 4 | |a Neural circuitry |x Adaptation | |
| 650 | 4 | |a Neural networks (Computer science) | |
| 650 | 4 | |a Neural networks (Computer science) | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 978-0-691-18122-6 |
| 856 | 4 | 0 | |u https://doi.org/10.1515/9780691215518 |x Verlag |z URL des Erstveröffentlichers |3 Volltext |
| 912 | |a ZDB-23-DGG | ||
| 999 | |a oai:aleph.bib-bvb.de:BVB01-032816180 | ||
| 966 | e | |u https://doi.org/10.1515/9780691215518?locatt=mode:legacy |l FAB01 |p ZDB-23-DGG |q FAB_PDA_DGG |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1515/9780691215518?locatt=mode:legacy |l FAW01 |p ZDB-23-DGG |q FAW_PDA_DGG |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1515/9780691215518?locatt=mode:legacy |l FCO01 |p ZDB-23-DGG |q FCO_PDA_DGG |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1515/9780691215518?locatt=mode:legacy |l FHA01 |p ZDB-23-DGG |q FHA_PDA_DGG |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1515/9780691215518?locatt=mode:legacy |l FKE01 |p ZDB-23-DGG |q FKE_PDA_DGG |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1515/9780691215518?locatt=mode:legacy |l FLA01 |p ZDB-23-DGG |q FLA_PDA_DGG |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1515/9780691215518?locatt=mode:legacy |l UPA01 |p ZDB-23-DGG |q UPA_PDA_DGG |x Verlag |3 Volltext | |
Datensatz im Suchindex
| _version_ | 1804182687320113152 |
|---|---|
| adam_txt | |
| any_adam_object | |
| any_adam_object_boolean | |
| author | Hiesinger, Peter Robin 1972- |
| author_GND | (DE-588)122323041 |
| author_facet | Hiesinger, Peter Robin 1972- |
| author_role | aut |
| author_sort | Hiesinger, Peter Robin 1972- |
| author_variant | p r h pr prh |
| building | Verbundindex |
| bvnumber | BV047415301 |
| classification_rvk | ST 301 |
| collection | ZDB-23-DGG |
| ctrlnum | (ZDB-23-DGG)9780691215518 (OCoLC)1224585570 (DE-599)BVBBV047415301 |
| dewey-full | 006.3/2 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.3/2 |
| dewey-search | 006.3/2 |
| dewey-sort | 16.3 12 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| discipline_str_mv | Informatik |
| doi_str_mv | 10.1515/9780691215518 |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>04475nmm a2200541zc 4500</leader><controlfield tag="001">BV047415301</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20230113 </controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">210812s2021 xxu|||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9780691215518</subfield><subfield code="c">Online</subfield><subfield code="9">978-0-691-21551-8</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1515/9780691215518</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-23-DGG)9780691215518</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1224585570</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV047415301</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="044" ind1=" " ind2=" "><subfield code="a">xxu</subfield><subfield code="c">XD-US</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-1043</subfield><subfield code="a">DE-1046</subfield><subfield code="a">DE-858</subfield><subfield code="a">DE-Aug4</subfield><subfield code="a">DE-859</subfield><subfield code="a">DE-860</subfield><subfield code="a">DE-739</subfield><subfield code="a">DE-11</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">006.3/2</subfield><subfield code="2">23</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">ST 301</subfield><subfield code="0">(DE-625)143651:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Hiesinger, Peter Robin</subfield><subfield code="d">1972-</subfield><subfield code="e">Verfasser</subfield><subfield code="0">(DE-588)122323041</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">The self-assembling brain</subfield><subfield code="b">how neural networks grow smarter</subfield><subfield code="c">Peter Robin Hiesinger</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Princeton</subfield><subfield code="b">Princeton University Press</subfield><subfield code="c">[2021]</subfield></datafield><datafield tag="264" ind1=" " ind2="4"><subfield code="c">© 2021</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (xiii, 364 Seiten)</subfield><subfield code="b">Illustrationen</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Description based on online resource; title from PDF title page (publisher's Web site, viewed 29. Jul 2021)</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">What neurobiology and artificial intelligence tell us about how the brain builds itself How does a neural network become a brain? While neurobiologists investigate how nature accomplishes this feat, computer scientists interested in artificial intelligence strive to achieve this through technology. The Self-Assembling Brain tells the stories of both fields, exploring the historical and modern approaches taken by the scientists pursuing answers to the quandary: What information is necessary to make an intelligent neural network?As Peter Robin Hiesinger argues, "the information problem" underlies both fields, motivating the questions driving forward the frontiers of research. How does genetic information unfold during the years-long process of human brain development-and is there a quicker path to creating human-level artificial intelligence? Is the biological brain just messy hardware, which scientists can improve upon by running learning algorithms on computers? Can AI bypass the evolutionary programming of "grown" networks? Through a series of fictional discussions between researchers across disciplines, complemented by in-depth seminars, Hiesinger explores these tightly linked questions, highlighting the challenges facing scientists, their different disciplinary perspectives and approaches, as well as the common ground shared by those interested in the development of biological brains and AI systems. In the end, Hiesinger contends that the information content of biological and artificial neural networks must unfold in an algorithmic process requiring time and energy. There is no genome and no blueprint that depicts the final product. The self-assembling brain knows no shortcuts.Written for readers interested in advances in neuroscience and artificial intelligence, The Self-Assembling Brain looks at how neural networks grow smarter</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">SCIENCE / Life Sciences / Neuroscience</subfield><subfield code="2">bisacsh</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Artificial intelligence</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Learning</subfield><subfield code="x">Psysiological aspects</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Neural circuitry</subfield><subfield code="x">Adaptation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Neural networks (Computer science)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Neural networks (Computer science)</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="z">978-0-691-18122-6</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1515/9780691215518</subfield><subfield code="x">Verlag</subfield><subfield code="z">URL des Erstveröffentlichers</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-23-DGG</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-032816180</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1515/9780691215518?locatt=mode:legacy</subfield><subfield code="l">FAB01</subfield><subfield code="p">ZDB-23-DGG</subfield><subfield code="q">FAB_PDA_DGG</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1515/9780691215518?locatt=mode:legacy</subfield><subfield code="l">FAW01</subfield><subfield code="p">ZDB-23-DGG</subfield><subfield code="q">FAW_PDA_DGG</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1515/9780691215518?locatt=mode:legacy</subfield><subfield code="l">FCO01</subfield><subfield code="p">ZDB-23-DGG</subfield><subfield code="q">FCO_PDA_DGG</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1515/9780691215518?locatt=mode:legacy</subfield><subfield code="l">FHA01</subfield><subfield code="p">ZDB-23-DGG</subfield><subfield code="q">FHA_PDA_DGG</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1515/9780691215518?locatt=mode:legacy</subfield><subfield code="l">FKE01</subfield><subfield code="p">ZDB-23-DGG</subfield><subfield code="q">FKE_PDA_DGG</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1515/9780691215518?locatt=mode:legacy</subfield><subfield code="l">FLA01</subfield><subfield code="p">ZDB-23-DGG</subfield><subfield code="q">FLA_PDA_DGG</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1515/9780691215518?locatt=mode:legacy</subfield><subfield code="l">UPA01</subfield><subfield code="p">ZDB-23-DGG</subfield><subfield code="q">UPA_PDA_DGG</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield></record></collection> |
| id | DE-604.BV047415301 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T17:55:38Z |
| indexdate | 2024-07-10T09:11:30Z |
| institution | BVB |
| isbn | 9780691215518 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-032816180 |
| oclc_num | 1224585570 |
| open_access_boolean | |
| owner | DE-1043 DE-1046 DE-858 DE-Aug4 DE-859 DE-860 DE-739 DE-11 |
| owner_facet | DE-1043 DE-1046 DE-858 DE-Aug4 DE-859 DE-860 DE-739 DE-11 |
| physical | 1 Online-Ressource (xiii, 364 Seiten) Illustrationen |
| psigel | ZDB-23-DGG ZDB-23-DGG FAB_PDA_DGG ZDB-23-DGG FAW_PDA_DGG ZDB-23-DGG FCO_PDA_DGG ZDB-23-DGG FHA_PDA_DGG ZDB-23-DGG FKE_PDA_DGG ZDB-23-DGG FLA_PDA_DGG ZDB-23-DGG UPA_PDA_DGG |
| 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] © 2021 1 Online-Ressource (xiii, 364 Seiten) Illustrationen txt rdacontent c rdamedia cr rdacarrier Description based on online resource; title from PDF title page (publisher's Web site, viewed 29. Jul 2021) What neurobiology and artificial intelligence tell us about how the brain builds itself How does a neural network become a brain? While neurobiologists investigate how nature accomplishes this feat, computer scientists interested in artificial intelligence strive to achieve this through technology. The Self-Assembling Brain tells the stories of both fields, exploring the historical and modern approaches taken by the scientists pursuing answers to the quandary: What information is necessary to make an intelligent neural network?As Peter Robin Hiesinger argues, "the information problem" underlies both fields, motivating the questions driving forward the frontiers of research. How does genetic information unfold during the years-long process of human brain development-and is there a quicker path to creating human-level artificial intelligence? Is the biological brain just messy hardware, which scientists can improve upon by running learning algorithms on computers? Can AI bypass the evolutionary programming of "grown" networks? Through a series of fictional discussions between researchers across disciplines, complemented by in-depth seminars, Hiesinger explores these tightly linked questions, highlighting the challenges facing scientists, their different disciplinary perspectives and approaches, as well as the common ground shared by those interested in the development of biological brains and AI systems. In the end, Hiesinger contends that the information content of biological and artificial neural networks must unfold in an algorithmic process requiring time and energy. There is no genome and no blueprint that depicts the final product. The self-assembling brain knows no shortcuts.Written for readers interested in advances in neuroscience and artificial intelligence, The Self-Assembling Brain looks at how neural networks grow smarter SCIENCE / Life Sciences / Neuroscience bisacsh Artificial intelligence Learning Psysiological aspects Neural circuitry Adaptation Neural networks (Computer science) Erscheint auch als Druck-Ausgabe 978-0-691-18122-6 https://doi.org/10.1515/9780691215518 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Hiesinger, Peter Robin 1972- The self-assembling brain how neural networks grow smarter SCIENCE / Life Sciences / Neuroscience bisacsh Artificial intelligence Learning Psysiological aspects Neural circuitry Adaptation Neural networks (Computer science) |
| 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 |
| topic | SCIENCE / Life Sciences / Neuroscience bisacsh Artificial intelligence Learning Psysiological aspects Neural circuitry Adaptation Neural networks (Computer science) |
| topic_facet | SCIENCE / Life Sciences / Neuroscience Artificial intelligence Learning Psysiological aspects Neural circuitry Adaptation Neural networks (Computer science) |
| url | https://doi.org/10.1515/9780691215518 |
| work_keys_str_mv | AT hiesingerpeterrobin theselfassemblingbrainhowneuralnetworksgrowsmarter |