10 books
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13 voters
Llm Books
Showing 1-50 of 264

by (shelved 9 times as llm)
avg rating 4.10 — 42 ratings — published

by (shelved 8 times as llm)
avg rating 4.62 — 203 ratings — published

by (shelved 7 times as llm)
avg rating 4.48 — 503 ratings — published

by (shelved 5 times as llm)
avg rating 4.30 — 173 ratings — published

by (shelved 5 times as llm)
avg rating 4.41 — 202 ratings — published

by (shelved 4 times as llm)
avg rating 4.50 — 40 ratings — published

by (shelved 3 times as llm)
avg rating 4.00 — 19 ratings — published

by (shelved 3 times as llm)
avg rating 3.86 — 42 ratings — published

by (shelved 3 times as llm)
avg rating 3.68 — 90 ratings — published

by (shelved 3 times as llm)
avg rating 3.58 — 12 ratings — published

by (shelved 2 times as llm)
avg rating 4.08 — 11,146 ratings — published 2000

by (shelved 2 times as llm)
avg rating 4.20 — 8,966 ratings — published 2023

by (shelved 2 times as llm)
avg rating 4.47 — 47,819 ratings — published 2019

by (shelved 2 times as llm)
avg rating 4.06 — 94,719 ratings — published 1955

by (shelved 2 times as llm)
avg rating 3.85 — 47 ratings — published

by (shelved 2 times as llm)
avg rating 5.00 — 3 ratings — published

by (shelved 2 times as llm)
avg rating 3.62 — 106 ratings — published

by (shelved 2 times as llm)
avg rating 4.21 — 4,299 ratings — published 1970

by (shelved 2 times as llm)
avg rating 3.96 — 319,564 ratings — published 1997

by (shelved 2 times as llm)
avg rating 4.75 — 8 ratings — published

by (shelved 2 times as llm)
avg rating 3.54 — 24 ratings — published

by (shelved 2 times as llm)
avg rating 4.62 — 8 ratings — published

by (shelved 2 times as llm)
avg rating 3.88 — 75 ratings — published

by (shelved 2 times as llm)
avg rating 3.86 — 1,514 ratings — published

by (shelved 2 times as llm)
avg rating 4.17 — 572,337 ratings — published 2011

by (shelved 1 time as llm)
avg rating 0.0 — 0 ratings — published 2025

by (shelved 1 time as llm)
avg rating 4.11 — 9 ratings — published

by (shelved 1 time as llm)
avg rating 4.00 — 11 ratings — published

by (shelved 1 time as llm)
avg rating 3.73 — 11 ratings — published

by (shelved 1 time as llm)
avg rating 4.15 — 2,931 ratings — published 2025

by (shelved 1 time as llm)
avg rating 3.88 — 168 ratings — published 2010

by (shelved 1 time as llm)
avg rating 4.59 — 59 ratings — published

by (shelved 1 time as llm)
avg rating 4.15 — 9,437 ratings — published 1958

by (shelved 1 time as llm)
avg rating 0.0 — 0 ratings — published

by (shelved 1 time as llm)
avg rating 3.57 — 148 ratings — published

by (shelved 1 time as llm)
avg rating 3.80 — 5 ratings — published

by (shelved 1 time as llm)
avg rating 4.00 — 5 ratings — published

by (shelved 1 time as llm)
avg rating 4.29 — 638 ratings — published 2000

by (shelved 1 time as llm)
avg rating 3.00 — 2 ratings — published

by (shelved 1 time as llm)
avg rating 4.11 — 5,149 ratings — published 2020

by (shelved 1 time as llm)
avg rating 4.15 — 5,465 ratings — published 2019

by (shelved 1 time as llm)
avg rating 4.13 — 77,370 ratings — published 2019

by (shelved 1 time as llm)
avg rating 4.13 — 179 ratings — published 2018

by (shelved 1 time as llm)
avg rating 3.92 — 623 ratings — published

by (shelved 1 time as llm)
avg rating 3.82 — 1,408 ratings — published 2016

by (shelved 1 time as llm)
avg rating 4.09 — 893 ratings — published 2016

by (shelved 1 time as llm)
avg rating 3.89 — 11,897 ratings — published 2016

by (shelved 1 time as llm)
avg rating 4.35 — 202,437 ratings — published 2016

“Many presume that integrating more advanced automation will directly translate into productivity gains. But research reveals that lower-performing algorithms often elicit greater human effort and diligence. When automation makes obvious mistakes, people stay attentive to compensate. Yet flawless performance prompts blind reliance, causing costly disengagement. Workers overly dependent on accurate automation sleepwalk through responsibilities rather than apply their own judgment.”
― Introduction to Large Language Models for Business Leaders: Responsible AI Strategy Beyond Fear and Hype
― Introduction to Large Language Models for Business Leaders: Responsible AI Strategy Beyond Fear and Hype

“LLMs represent some of the most promising yet ethically fraught technologies ever conceived. Their development plots a razor’s edge between utopian and dystopian potentials depending on our choices moving forward.”
― Introduction to Large Language Models for Business Leaders: Responsible AI Strategy Beyond Fear and Hype
― Introduction to Large Language Models for Business Leaders: Responsible AI Strategy Beyond Fear and Hype