MARC details
| 000 -LEADER |
|---|
| fixed length control field |
04367nam a22003257a 4500 |
| 001 - CONTROL NUMBER |
|---|
| control field |
20912141 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
IIITD |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20230926020002.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
190318s2019 mau 000 0 eng c |
| 010 ## - LIBRARY OF CONGRESS CONTROL NUMBER |
|---|
| LC control number |
2019011886 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9781633697898 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
MH/DLC |
| Language of cataloging |
eng |
| Transcribing agency |
MH |
| Description conventions |
rda |
| Modifying agency |
DLC |
| 042 ## - AUTHENTICATION CODE |
|---|
| Authentication code |
pcc |
| 050 00 - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
Q335 |
| Item number |
.A778 2019 |
| 082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
658.05 |
| Edition number |
23 |
| Item number |
HAR-A |
| 110 ## - MAIN ENTRY--CORPORATE NAME |
|---|
| Corporate name or jurisdiction name as entry element |
Harvard business review |
| 130 0# - MAIN ENTRY--UNIFORM TITLE |
|---|
| Uniform title |
Artificial intelligence (Harvard Business Review Press) |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Artificial intelligence : |
| Remainder of title |
insights you need from Harvard business review |
| Statement of responsibility, etc |
by Harvard business review |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Place of publication, distribution, etc |
Boston : |
| Name of publisher, distributor, etc |
Harvard Business Review Press, |
| Date of publication, distribution, etc |
©2019 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xvi, 176 p. ; |
| Dimensions |
22 cm |
| 490 ## - SERIES STATEMENT |
|---|
| Series statement |
The insights you need from Harvard Business Review |
| 505 0# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Section 1. Understanding AI and machine learning: The business of artificial intelligence: what it can - and cannot - do for your organization / Erik Brynjolfsson and Andrew McAfee -- Inside facebook's AI workshop: at the social network behemoth, machine learning has become a platform for the platform, an interview with Joaquin Candela by Scott Berinato -- Why companies that wait to adopt AI may never catch up: the "fast follower" strategy won't work / Vikram Mahidhar and Thomas H. Davenport -- Section 2. Adopting AI: 3 questions about AI that nontechnical employees should be able to answer: how does it work, what is it good at, and what should it never do? / Emma Martinho-Truswell -- Is your company's data actually valuable in the AI era?: the problem with "data is the new oil." / Ajay Agrwawal, Joshua Gans, and Avi Goldfarb -- How to choose your first AI project: pick a quick win to build internal support / Andrew Ng -- How Harley-Davidson used artificial intelligence to increase New York sales leads by 2,930%: and it led to more revenue and more jobs / Brad Power -- What will happen when your company's algorithms go wrong?: you need to have a plan / Roman V. Yampolskiy -- Section 3. AI and the future of work: How will AI change work?: here are 5 schools of thought: in some versions, society will fundamentally change / Mark Knickrehm -- Collaborative intelligence: humans and AI are joining forces: humans and machines can enhance each other's strengths / H. James Wilson and Paul Daugherty -- Section 4. The future of AI: 3 ways AI is getting more emotional: as we spend more time with our devices, we emit more data to be analyzed / Sophie Kleber -- How AI will change strategy: a thought experiment: E-commerce could move from shopping-then-shipping to shipping-then-shopping / Ajay Agrwawal, Joshua Gans, and Avi Goldfarb -- The future of AI will be about less data, not more: we need computers with some common sense / H. James Wilson, Paul Daugherty, and Chase Davenport. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc |
Companies that don't use AI to their advantage will soon be left behind. Artificial intelligence and machine learning will drive a massive reshaping of the economy and society. What should you and your company be doing right now to ensure that your business is poised for success? These articles by AI experts and consultants will help you understand today's essential thinking on what AI is capable of now, how to adopt it in your organization, and how the technology is likely to evolve in the near future. Artificial Intelligence: The Insights You Need from Harvard Business Review will help you spearhead important conversations, get going on the right AI initiatives for your company, and capitalize on the opportunity of the machine intelligence revolution. Catch up on current topics and deepen your understanding of them with the Insights You Need series from Harvard Business Review. Featuring some of HBR's best and most recent thinking, Insights You Need titles are both a primer on today's most pressing issues and an extension of the conversation, with interesting research, interviews, case studies, and practical ideas to help you explore how a particular issue will impact your company and what it will mean for you and your business.-- |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Artificial intelligence. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Artificial intelligence |
| General subdivision |
Industrial applications. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Technological innovations |
| General subdivision |
Economic aspects. |
| 906 ## - LOCAL DATA ELEMENT F, LDF (RLIN) |
|---|
| a |
7 |
| b |
cbc |
| c |
orignew |
| d |
1 |
| e |
ecip |
| f |
20 |
| g |
y-gencatlg |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
Books |
| Koha issues (borrowed), all copies |
1 |
