Algorithms to Live By | Brian Christian & Tom Griffiths | Talks at Google

Practical, everyday advice which will easily provoke an interest in computer science.
In a dazzlingly interdisciplinary work, acclaimed author Brian Christian and cognitive scientist Tom Griffiths show how the algorithms used by computers can also untangle very human questions. They explain how to have better hunches and when to leave things to chance, how to deal with overwhelming choices and how best to connect with others. From finding a spouse to finding a parking spot, from organizing one's inbox to understanding the workings of memory, Algorithms to Live By transforms the wisdom of computer science into strategies for human living.
Brian Christian is the author of The Most Human Human, a Wall Street Journal bestseller, New York Times editors’ choice, and a New Yorker favorite book of the year. His writing has appeared in The New Yorker, The Atlantic, Wired, The Wall Street Journal, The Guardian, and The Paris Review, as well as in scientific journals such as Cognitive Science, and has been translated into eleven languages. He lives in San Francisco.
Tom Griffiths is a professor of psychology and cognitive science at UC Berkeley, where he directs the Computational Cognitive Science Lab. He has published more than 150 scientific papers on topics ranging from cognitive psychology to cultural evolution, and has received awards from the National Science Foundation, the Sloan Foundation, the American Psychological Association, and the Psychonomic Society, among others. He lives in Berkeley.
On behalf of Talks at Google this talk was hosted by Boris Debic.
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[@pritishparihar6752]

3:29 Chapter 1 Optimal Shopping 10:25 The Secretary Problem 17:15 When to sell 18:45 When to Park

[@greyreynyn]

35:05 "we should actually expect to get steadily happier through life" lmaooooo good one

[@agojiedoramilaje27]

Imagine being the person who the mathematician comes back to because they've explored all their options and according to the algorithm found out you're the best one and you still decide to take them back

[@ozymandias5847]

First Algorithm 1. Watch youtube 2. If no comment on video , type 3. Repeat for next video.

[@gshishkov]

So hard pill to swallow!!!

[@michaelletho5952]

This has given me a lot of ideas, thank you. :)

[@chanfioabdou894]

Bon soir

[@sumeetsingharora1046]

Aren't there a lot of assumptions in each of the algorithms suggested for the problems? Are these assumptions mentioned in the book? For example, the parking problem ... Is the assumption that the parking is unmanned? Could there be a different pattern for roadside parking vs parking in a mall vs parking in a business complex?

[@Pleasing_view]

Ted Ed brought me here

[@WiserMiser]

Yes

[@desarrollocorporalcondami8145]

@@WiserMiser 😊😅😅😅😅😅😅😅😅😅😅😅😅😅😅😅😅😅😅😅😅😅😅😅😅😅😅😅😅😅😅😅😅😅

[@michaelvoithofer3503]

Emma is the best! Thanks for such an inspiring talk!

[@chanfioabdou894]

Bon soie

[@isaacdarche7103]

I'm shocked. This is fucking genius.

[@thomasmonti2450]

It s nice this computation

[@faintscrawl]

I am wondering about how I could use these algorithms to be most efficient and accurate when evaluating students essay on English literature.

[@vincenttubes4449]

nice presentation guys

[@RaaynML]

So why does a 50% chance of rejection bring the chance of success to 25% from 37%?

[@blueredone9250]

Because these numbers are made up

[@MatthewDowell]

These Talks at Google are becoming; "what way can we solve the San Francisco housing crisis today?"

[@p5rsona]

lol

[@user-rz7pe2if6r]

yes

[@AbhishekGNair]

What ancient computer processor had L2 cache off-chip?

[@mishaberger1718]

40:00 What about FOMO, or fear of missing out, where instead of dwelling on missed (unseized) opportunities in the past, you dwell on missed (unevaluated) opportunities in the future? With the cost to "play the slot machine," or message another potential date online, growing ever smaller in today's more connected society, FOMO seems to be on the rise. Susceptibility to regret versus FOMO likely varies person to person depending on wide ranging factors like prior luck, patience, faith in the system, and your personal utility function (i.e. is it best-or-nothing for you, or would you be just as happy with any outcome above a threshold value). I know that I personally am more prone to regret than FOMO, so like Bezos, this is what I tend to minimize for, but the same may not necessarily be good advice for others.

[@mohdzuhaib4138]

Is the 37% rule valid for unordered things? For example I've 10 candy samples and I've to select the best and I've time constraints. So randomly selecting 37% to evaluate and selecting the best Except those 37% group of sample

[@frankribery3362]

If it was ordered listing it wouldn't have been choosing out of 37% ... You would literally know the best one to pick will be the best of ordered list

[@quartytypo]

Overall, through many visits to casino slots expect to lose 80% of your money. If you can still have fun losing 80% than you are OK and good to go.

[@MrRajeshkpy]

Can these information be used in real life… Any real life case studies please

[@smackronme]

One problem with implementing Optimal stopping in real might probably be, it is not worth it go to the extent of 37% in terms of time and effort for the payoff of that particular problem.. and it is worth it in some other problems to go beyond because of it's payoff.. or I haven't understood the underlying mathematical structure properly..

[@dymka2006]

I love geeks. Good luck to you.

[@arrabalimaz622]

Wonderful

[@rushikeshdarge6115]

Please!!! Can anyone summerize video? Video good or bad?

[@tortrombeck6199]

Video good

[@alirezadarvishi5666]

nice

[@jandroid33]

Can this be classified as a religion? Or can religion be classified as an algorithm? This book seems like a very individual-focused religion in that case...

[@hassiaschbi]

+jandroid33 maybe the better analogy would be 'A Rulebook to live by' like the bible or other religious rulebooks. A full blown religion usually has parts that have to be believed because they are not scientifically provable and focuses around holy objects.

[@introvertedskeptic33]

Aren't all ideas quasi algorithm? If I have an established procedure given to me by religion for particular scenarios, that I don't stray from because that's the software programmed into me. How am I not acting out an algorithm?

[@irvinlovesjesus]

It's a relationship notta religion just their world view and not bad to adodpt considering the eternal life.

[@sushi2slushy]

It's math

[@IferJ]

can you do an algorithm on where ISIS would attack next in Europe so I know which train station to avoid ??

[@frankribery3362]

You can basically use trains done by Poland xD

[@BinanceUSD]

Interesting waiting is good

[@theinthanhlan3582]

:) how can I catch their speech!!

[@JohnBastardSnow]

How can you calculate the probability of being caught as a robber if your probability of getting caught is going to be 0 until you're caught? For example, if you have 3 successful robberies, then by looking at previous outcomes (3 out of 3 robberies being successful), you'll conclude that the probability of a successful robbery is 1.0 or 100%.

[@franciscussteiner5661]

+Jon Wise I think you should start by learning to compose full and meaningful sentences in the English language. (EDIT: The comment has now been changed.)

[@notusingmyrealnamegoogle9929]

I'm dying.

[@jeehooahn9114]

hey, that's offensive. My butthole is not tanned.

[@jeehooahn9114]

I think the answer comes in terms of probabilities derived from other ways. Perhaps you look at the overall statistics, not just the statistics of your own instances. Perhaps you can calculate it by composed events of a robbery, which would be much more involved, but still separate from purely your own experiences, and valid. One component in the very long equation may be the probability of leaving your DNA at the scene * probability of them finding it. Another component would be the likelihood of getting away from cops should you end up in a high speed chase, given the probability that you end up in a high speed chase. The probability you can get them to cough up the money without them alerting authorities via the proverbial panic button under the desk. Combine all these, and you'd have a probability based on the average bank, or your specific target bank, which would be independent of your own runs. So the short answer is, use probabilities based on external data, or relevant and related enough data. And if all else fails, engage in the mathematically heavy endeavor of calculating probabilities up from elementary events or events broken down sufficiently enough.

[@JohnBastardSnow]

Jeehoo Ahn Thanks for the answer.

[@dominicjohnson4066]

Timestamps anyone??

[@rexsapienssapiens5106]

Friend, Front end "exploration" / Back end "exploitation", seems to describe Mormon Batch Dating & single / drawn out Victorian Courting. In both cases presumably without sex.

[@boydreid1155]

48:54 no es guchi

[@arrabalimaz622]

Can you be clear sir what you want to do speak needed sir

[@nefuros551]

He sounds like Elon Musk that doesn't talk so slowly and has an accent.

[@saeedalyami8791]

He looks like Bill Clinton though

[@sandeepvk]

And then Tinder incorporated

[@SorrySuckYou]

Wow, this is bad... Sorry, but this is knowledge normal people get in high-school, y'know... when they START dating, (as opposed to after finishing their PhD in the nerd's case, I'm guessing?) No one should be married before finishing college, so that's 8 YEARS a normal person has dated. If you don't know what you want from relationships after 8 years, you NEVER will... Math won't help you.

[@nmgbbmonie1765]

Today I learned I’m not normal

[@neerajkgond]

So... She was not best option. I still have time.

[@goofycker]

booaring, only useful for the unfitted for life

[@supersonic956]

Just coating concepts people already intuitively live by with jargon and statistics. Pretentious and pointless.