Pallavi’s Kindle Notes & Highlights for Algorithms to Live By: The Computer Science of Human Decisions

Algorithms to Live By: The Computer Science of Human Decisions

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Daniel Dantas

Daniel Dantas

2 notes & 544 highlights

Casey E.

Casey E.

5 notes & 13 highlights

Daryl Ducharme

Daryl Ducharme

44 notes & 64 highlights

Balint Erdi

Balint Erdi

1 note & 210 highlights

Queenie Nguyen

Queenie Nguyen

6 notes & 11 highlights

Mike Massie

Mike Massie

6 notes & 33 highlights

Caitlin Wilson

Caitlin Wilson

1 note & 354 highlights

Yuan

Yuan

14 notes & 249 highlights

Rudie Rai

Rudie Rai

1 note & 2 highlights

Rob

Rob

4 notes & 31 highlights

Travis Chambers

Travis Chambers

2 notes & 32 highlights

Jesse Gardner

Jesse Gardner

Megan

Megan

Athul Jacob

Athul Jacob

Shashikant

Shashikant

Nicktzr

Nicktzr

HARJOT S KAHLON

HARJOT S KAHLON

Janie Tran

Janie Tran

Gray Spencer

Gray Spencer

Primož Centa

Primož Centa

Kevin Oliveros

Kevin Oliveros

Annie

Annie

Vince Snow

Vince Snow

Shubha

Shubha

Gregory

Gregory

Vano Maisuradze

Vano Maisuradze

Kristjan

Kristjan

Matej Navara

Matej Navara

Adam

Adam

Brian

Brian

Steve Fenton

Steve Fenton

Faried Nawaz

Faried Nawaz

Juan Luis Cordero

Juan Luis Cordero

Sergey

Sergey

Angel Lemke

Angel Lemke

Luis Conejo-Alpizar

Luis Conejo-Alpizar

EK McClelion

EK McClelion

Attila Bertók

Attila Bertók

Adil Asad

Adil Asad

Wildan Zulfikar

Wildan Zulfikar

Kindle Notes & Highlights

Pallavi

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Algorithms to Live By: The Computer Science of Human Decisions

by Brian Christian

Read between August 20, 2021 - February 7, 2025

1%

tackling real-world tasks requires being comfortable with chance, trading off time with accuracy, and using approximations.

4%

Gold digging is more likely to succeed than a quest for love.