Podcasts about live by the computer science

Unlock the power of data in shaping your organization's future as we tear down the myths surrounding data-driven decision-making. We dissect the essential cultural shift necessary for integrating data analytics into the heart of business strategy, steering clear of reliance on gut feelings or misleading numbers. We dive into practical applications, from planning poker to interpreting customer experience metrics. We provide the knowledge to avoid common data interpretation pitfalls, such as those exemplified by the beer game in supply chain management.For those striving to guide intuition-driven leaders towards a more data-informed approach, our dialogue offers inventive tactics for leveraging trusted allies and fostering a climate of persistent, creative persuasion. This week's takeaways:Data-driven vs. number-driven decision making: Data alone isn't enough. Context and understanding of statistical deviations are crucial for sound judgments.Overcoming resistance to data-driven decisions: Inflexible leaders pose a challenge. Directly challenging their intuition might be ineffective. Empowering teams and managing technical debt: Create short feedback cycles to enable rapid decision-making and results demonstration.Resources:Algorithms to Live By: The Computer Science of Human Decisions - https://a.co/d/dzojO5kJeff Bezos- https://www.youtube.com/watch?v=Ub585Pn4yroTune in to transform how you harness data for smart, insightful leadership decisions. We love to hear your feedback! If you have questions or would like to suggest a topic, please feel free to contact us at feedback@definitelymaybeagile.com.

Chris Volpe, Senior Director of Business Development and Academy, joins us on the podcast to talk about hiring for upper level positions, and how to weed out unqualified candidates. Books:Algorithms to Live By: The Computer Science of Human DecisionsThe No Asshole Rule: Building a Civilized Workplace and Surviving One That Isn'tService AutopilotAcademyPodcastInstagramYoutubeTik Tok

Każda decyzja ma ton emocjonalny, nawet jeśli wydaje nam się super logiczna. Jak myślisz, co wspólnego ma matematyka z podejmowaniem decyzji? Dlaczego jej podejmowanie przychodzi nam z trudnością? Czy katastrofy lotnicze to przypadek, czy kwestia złego wyboru? W tym odcinku podcastu omawiamy tematy związane z bezpieczeństwem psychologicznym, działaniem grup, podejmowaniem decyzji i negocjacji. Dowiesz się na czym polega paradoks Abilene i w jakich sytuacjach ma on miejsce. MAPA ODCINKA: [5:28] Algorytm szukania żony [11:53] Podejmowanie decyzji [14:44] Bezpieczeństwo psychologiczne [16:22] Popełnianie gaf, a kreatywność [19:45] Self disclosure [23:32] Wykorzystywanie humoru w biznesie [27:03] Negocjator terapeuta vs. negocjator kowboj [28:46] Efekt Dunninga-Krugera [33:39] Koncept WEIRD [36:14] Złożony model motywacji [42:22] Paradoks Abilene [46:14] Projekt Arystoteles i psychologiczne bezpieczeństwo CIEKAWOSTKI Z TEGO ODCINKA: Popełnianie kompromitującej gafy czy opowiadanie o niej zwiększa bezpieczeństwo w grupie co z kolei prowadzi do tego, że grupa jest bardziej kreatywna. Więcej czasu poświęcamy na zarządzanie statusem niż na generowaniu rozwiązań. Dorzucenie żartu na koniec negocjacji pozytywnie wpływa na rezultaty negocjacji Aż 90% ankietowanych managerów ocenia się jako 5% najlepszych. Japonia jest bardziej kolektywną kulturą (zależność nie odstawiania od grupy). Jeżeli świetnie sobie radzą, odpuszczają by przystosować się do grupy, jeżeli są na dole, docierają do poziomu grupy. W kulturze indywidualnej ludzie skupiają się na tym by być najlepszym, a gdy ich wynik jest niski jest nieważny. Psychologiczne bezpieczeństwo ma dwa rodzaje zachowań – miękkie (odsłanianie się) i twarde (kwestionowanie, wchodzenie w merytoryczny konflikt). Ważniejsze jest jak zespół się komunikuje, niż z kogo się składa. Tipy budowania bezpieczeństwa w grupie to m.in: odsłanianie się i wyrównywanie statusu oraz budowanie kontaktu grupowego. ŹRÓDŁA WSPOMINANE W TYM ODCINKU: B. Christian, T. Griffiths Algorithms to Live By: The Computer Science of Human Decisions (książka) Rafał Żak – Yyyyy. Jak podejmować dobre decyzje (książka) Leigh Thompson – Creative Conspiracy (książka) Leigh Thompson – Negotiating the Sweet Spot (książka) WEIRD (koncept) Negativity bias – efekt negatywny Expectancy-Value Theory – model motywacji Amy Edmondson – badania dotyczące psychologicznego bezpieczeństwa (Błędy ludzkie w katastrofach lotniczych)

We hope you enjoy our entrepreneur podcast! To help us grow, please subscribe to our podcast and follow us on TikTok, YouTube, Instagram, Facebook and/or LinkedIn. It's the best way we can keep bringing in quality guests.Welcome to Business Over Drinks, one of the most unique podcasts you will find anywhere in the world helmed by two people from different walks of life.This entrepreneur podcast is an extension of their real-life experiences as business owners, salaried employees and industry mavericks who made mistakes along the way and lived to talk about it.WE SPEAK TO: Ryan ChewRyan Chew is a Forbes 30 under 30 Asia 2020 honouree,  is a co-founder of Tribe, Singapore's first government supported platform driving neutrality, collaboration and growth of the blockchain ecosystem.Tribe works closely with Enterprise Singapore, the Monetary Authority of Singapore, Temasek, Citibank, IBM and Intel, and others to grow the Blockchain ecosystem in Singapore and beyond.Since its inception Tribe's has accelerated more than 50 Blockchain start-ups with a combined value of more than $1 billion.Ryan joins us to talk about his life as an entrepreneur, the future of Blockchain and NFTs, as well as some handy tips on where to get the best prata in Singapore!WE'RE DRINKING:David: Giesen 0% Merlot Terng: Calrsberg Pilsner Ryan: CoffeeWE CHAT ABOUT:Ryan's experience with prata Ryan's first experiences as an entrepreneur and building videogamesRyan's early days as a waiterRyan's biggest mistakes in business What can blockchain doHow it is to sell blockchainReal world applications for blockchainWhat are NFTsAre NFTs a scam?Are we in an NFT winter?Blockchain/NFT investmentsIs Asia behind on cryptoRyan's favourite booksRyan's life lessonsFOLLOW RYAN'S WORK:TribeTribe on FacebookTribe on LinkedInBOOK RECOMMENDATIONS:Antifragile: Things that Gain from DisorderThe Hard Things About Hard ThingsAlgorithms to Live By: The Computer Science of Human DecisionsPROMOTION:Get a FREE audiobook and support our show by signing up to a free Audible trial here: https://www.audible.com.au/bod011-20Listeners get 10% of David's hilarious new book, Everyday A**holes, using the promo code BOD at checkout. Get a copy at everydayassholes.net.Listeners get a free 30-minute consultation with Terng's company, SYNC PR. Just mention this podcast when contacting them at syncpr.co

The Cognitive Crucible is a forum that presents different perspectives and emerging thought leadership related to the information environment. The opinions expressed by guests are their own, and do not necessarily reflect the views of or endorsement by the Information Professionals Association. In this crossover episode of the Phoenix Cast and Cognitive Crucible, John Bicknell is joined by John Schreiner, Kyle Moschetto and Rich Vaccariello. The podcast hosts discuss why they started their respective casts, how they view competition, the key take-aways of their casts, the top must listen episodes, and the other podcasts they listen to. Cognitive Crucible show notes page https://information-professionals.org/episode/cognitive-crucible-episode-78 Links and Resources: MCDP 1-4 Competing Phoenix Cast Episodes Mentioned: Nate Fick SolarWinds Reaction Gene Kim Cognitive Crucible Episodes Mentioned: #24 Davis on Modern Warfare, Teamwork, and Commercial Cognitive Security #38 Reynolds on Operations in the Information Environment #63 Vickers on IO and the Cyclops Books, Movie, and Other Podcast Suggestions: Algorithms to Live By: The Computer Science of Human Decisions by Brian Christian and Tom Griffiths Hackers (1995 Movie) Unlocking Us Podcast with Brene Brown Life-Changing Inventions in Literature with Dr. Angus Fletcher The New Rules of Leadership with Abby Wambach EconTalk Podcast with Russ Roberts Hard Core History Podcast with Dan Carlin  Net Assessment Podcast DarkHorse Podcast with Dr Bret Weinstein and Dr. Heather Heying Watch “Ron's Gone Wrong” movie with your children.

On this week's episode, the crew debates whether or not music has become more regional (2:14), the longevity of an artist (20:30), talks Larry Hoover and other inmates in ADX (42:43), then we have a breakdown of hoe culture...it gets deep (1:09:33). Last Name Good's Bruh Where: Goapele Lingo Steve: Word Of The Week: Beleaguer - To beset, as with difficulties; harass. Producer Black's Book Of The Week: Algorithms to Live By: The Computer Science of Human Decisions by Brian Christian Chiane XO's Shoutout Of The Week: @gfb3 Be sure to subscribe to The No Buffer Podcast for more exclusive footage. www.youtube.com/channel/UCkZyLaIm…ub_... Listen to the Culturally Ratchet Playlist open.spotify.com/playlist/1R1...​ Listen to The No Buffer Podcast smarturl.it/4sa7h8​ New Culturally Ratchet Merch available at nobufferpodcast.com/shop​ Follow the crew on social: IG www.instagram.com/nobufferpodcast www.instagram.com/lastnamegood/ www.instagram.com/chianexo www.instagram.com/lingostevo www.instagram.com/jabariblackmond www.instagram.com/h_imperial763

AI & machine learning have been at the center of moral debate for decades now. Scientists and lay people alike know, or assume, that there will come a day where machines will not just figure out how to accomplish goals, but will also figure out what those goals are. That is the central question of our guests latest book, The Alignment Problem.Brian Christian is a visiting scholar at UC Berkeley working with human compatible AI and the Citrus Foundation. He is also known for co-authoring Algorithms To Live By: The Computer Science Of Human Decisions. How do we make sure that our training dataset is representative? How do we make sure learning systems are learning the right things? And how can we make statistical classifiers more accurate when it comes to using algorithms for issues like probation and parole? These questions and more are all tackled in this episode.Episode Quotes:How can we aim to avoid unconscious bias in datasets?I think there's a lot of work to be done both in terms of thinking about what are the data sets that we're really using, how do they generalize to the populations of people that are really going to be affected by a technology?And also how do we articulate what we are truly trying to get this system to do? If certain mistakes are many orders of magnitude more costly than others, we have to find some way of expressing that or else by default, we're going to get a system that doesn't do anything close to what we want. Issues with statistical classifiers to think about probation, parole in US:But what you did see in terms of the difference between black and white defendants was a difference in the actual kinds of errors that it was making.So, if you look specifically at the defendants that were mispredicted, misclassified, you find that black defendants relative to white defendants are about two to one more likely to be misclassified as high-risk. White defendants, the other way around, two to one more likely to have been misclassified as lower risk than they really were.Encouraging research on the future of machine learning:My personal favorite is a paper between open AI and deep mind, where they were able to get a system to learn how to perform a backflip in this virtual world. Merely by showing users pairs of video clips of it moving randomly and saying which of these is slightly more like a backflip.And by showing people 900 such video clips and just saying which of these is slightly more like a backflip, the system was able to infer a representation of what a backflip was. That was good enough for it to then learn how to execute these beautiful gymnastically, perfect backflips, sticking the landing, et cetera. And I think that to me frankly, it's about as hopeful as I have felt about this problem space in many years, because I think there is this promise that we can develop a methodology for extracting, somehow , the norms, the preferences that we have in our head. Show Links:Guest Profile:Brian Christian WebsiteBrian Christian on TwitterAcademic Profile at Simons Institute for the Theory of Computing at UC BerkeleyHis work:The Alignment Problem: Machine Learning and Human ValuesAlgorithms to Live By: The Computer Science of Human DecisionsGameMaker Programming By ExampleThe Most Human Human: What Talking with Computers Teaches Us About What It Means to Be Alive

Diese Woche in der Zukunft: In dieser Episode beginnt die Zukunftsstaffel mit der Frage von https://www.linkedin.com/in/stefan-kermas-658392196/?originalSubdomain=de (Stefan Kermas) und wird von HR-Visionär https://www.linkedin.com/in/jess-koch-72683579/ (Jess Koch) beantwortet. Er wiederum gibt den Staffelstab in Form einer neuen Frage an die Zukunft weiter. Michael Carl spricht in dieser Folge mit KI-Expertin https://www.ivow.ai/ourteam.html (Davar Ardalan) über kulturell sensible Künstliche Intelligenzen. Was sind typische Einsatzfelder von kulturell sensiblen KIs? Wie genau regieren die Maschinen auf unterschiedliche kulturelle Hintergründe? Und was bedeutet das für uns Menschen? An dieser Stelle werden wir auch regelmäßig über Bücher, Filme, Serien etc. sprechen, die uns inspirieren, die wir für hilfreich und anregend halten. In Folge 2 stellen wir zwei Bücher gegenüber, deren Autoren jeweils unterschiedliche Perspektiven auf den Umgang von uns Menschen mit Algorithmen haben. In „https://www.amazon.de/New-Dark-Age-Technologie-Zukunft/dp/3406741770 (New Dark Age – Der Sieg der Technologie und das Ende der Zukunft)“ von James Bridle erkennt der Autor einen tückischen automation bias im allzu vertrauten Umgang mit Maschinen und automatisierten Vorgängen. Positiver bewerten die Autoren Brian Christian und Thomas Griffith die Interaktion mit Maschinen: In ihrem Buch „https://www.amazon.de/Algorithms-Live-Computer-Science-Decisions/dp/0007547994/ref=sr_1_1?adgrpid=73770770831&dchild=1&gclid=CjwKCAjwh7H7BRBBEiwAPXjadgEpWwc79nA-Bq9r4T0Zoyvn5ACaav2xyy-wix4B2Yu-9MRzXmCc-hoCx0MQAvD_BwE&hvadid=391552927122&hvdev=c&hvlocphy=9042985&hvnetw=g&hvqmt=e&hvrand=12158161355925964418&hvtargid=kwd-300531550968&hydadcr=27957_1978104&keywords=algorithms+to+live+by&qid=1600937093&sr=8-1&tag=googhydr08-21 (Algorithms to Live By: The Computer Science of Human Decisions)“ gehen die Autoren der Frage nach, was wir für unser humanes Denken von künstlichen Algorithmen lernen können. Vertrauen wir automatisierten Reaktionen zu sehr und wie können wir besser denken und glücklicher werden, wenn wir uns die Erfolgsprinzipien von Algorithmen zu Nutze machen? Noch ein Hinweis in eigener Sache: Vom 02.-04. Dezember veranstaltet das https://future-carl.institute/ (carl institute for human future) das Zukunftscamp „https://future-carl.institute/update-zukunft-dezember-2020/ (Update Zukunft Winter 2020)“ in Leipzig. Eine auf 12 Personen limitierte exklusive Veranstaltung mit Live Screening vom https://websummit.com/ (Web Summit 2020 in Lissabon). Mit inspirierenden Gästen und dem Team vom carl institute for human future aktualisieren wir unser Zukunftsbild. Die Gäste dieser Woche:https://www.linkedin.com/in/stefan-kermas-658392196/?originalSubdomain=de (Stefan Kermas), Volljurist und ehemaliger Bundestrainer der Hockey-Nationalmannschaft. https://www.linkedin.com/in/jess-koch-72683579/ (Jess Koch), HR-Manager, Agile Trainer und Coach bei HR Pioneers. https://www.ivow.ai/ourteam.html (Davar Ardalan), erfahrene und vielfach ausgezeichnete US-amerikanische Journalistin und Gründerin von IVOW AI. Dort trainiert sie gemeinsam mit ihrem Team KIs in kultureller Intelligenz.

As artificial intelligence gets more and more powerful, the need becomes greater to ensure that machines do the right thing. But what does that even mean? Brian Christian joins Vasant Dhar in episode 13 of Brave New World to discuss, as the title of his new book goes, the alignment problem. Useful resources: 1. Brian Christian's homepage. 2. The Alignment Problem: Machine Learning and Human Values -- Brian Christian. 3. Algorithms to Live By: The Computer Science of Human Decisions -- Brian Christian and Tom Griffiths. 4. The Most Human Human -- Brian Christian. 5. How Social Media Threatens Society -- Episode 8 of Brave New World (w Jonathan Haidt). 6. Are We Becoming a New Species? -- Episode 12 of Brave New World (w Molly Crockett). 7. The Nature of Intelligence -- Episode 7 of Brave New World (w Yann le Cunn) 8. Some Moral and Technical Consequences of Automation -- Norbert Wiener. 9.Superintelligence: Paths, Dangers, Strategies -- Nick Bostrom. 10. Human Compatible: AI and the Problem of Control -- Stuart Russell. 11. OpenAI. 12. Center for Human-Compatible AI. 13. Concrete Problems in AI Safety -- Dario Amodei, Chris Olah, Jacob Steinhardt, Paul Christiano, John Schulman, Dan Mané. 14. Machine Bias -- Julia Angwin, Jeff Larson, Surya Mattu and Lauren Kirchner. 15. Inherent Trade-Offs in the Fair Determination of Risk Scores -- Jon Kleinberg, Sendhil Mullainathan, Manish Raghavan. 16. Algorithmic Decision Making and the Cost of Fairness -- Sam Corbett-Davies, Emma Pierson, Avi Feller, Sharad Goel, Aziz Huq.. 17. Predictions Put Into Practice -- Jessica Saunders, Priscillia Hunt, John S. Hollywood 18. An Engine, Not a Camera: How Financial Models Shape Markets -- Donald MacKenzie. 19. An Anthropologist on Mars -- Oliver Sacks. 20. Deep Reinforcement Learning from Human Preferences -- Paul F Christiano, Jan Leike, Tom B Brown, Miljan Martic, Shane Legg, Dario Amadei for OpenAI & Deep Mind.

On this episode of Design Cast I had the opportunity to speak with Eric Burton. Eric is the founder and creator of Classwork Zoom, which is a Chrome Extension that educators can use that utilizes the revision history of Google Docs and other items in your Google Classroom. It allows the teacher to look at the time spent on an assignment by a student and includes analytics. I have used it and it is an amazing tool to make your work as a teacher more efficient and effective. Eric has made this product free to review a single student’s work at a time! His website is http://classworkzoom.com and you can search for it in the Chrome Extension Store. I highly recommend checking this out to anyone that uses Google Classroom. Please subscribe, rate, and share this podcast. If you have ideas for future episodes or would like to be a guest, please reach out through my website www.jasonreagin.ga as there is a contact form on the website. If typing a message isn’t your thing, you can use this link to share a voice message! https://anchor.fm/design-cast-podcast/message Now, sit back and enjoy the chat that I had with Eric Burton! You can connect with Eric: Website - http://classworkzoom.com Twitter - @ericb321 @ClassworkZoom GEG: Thirsty Thursday YouTube Channel Book recommendation: Algorithms to Live By: The Computer Science of Human Decisions [Join my Newsletter for this podcast and, OF COURSE, I will never share your information with anyone] --- This episode is sponsored by · Anchor: The easiest way to make a podcast. https://anchor.fm/app --- Send in a voice message: https://anchor.fm/design-cast-podcast/message

В епизод #17 на Beyond Numbers show  с гостите ни Елена Николова и Искрен Митев, съоснователи на ESCREO, ви предизвикваме да творите. Елена, Исрен и Ясен Николов се срещат, докато са част от предприемаческа програма в САЩ. Като се връщат в България се събират като екип и решават да приложат наученото от програмата. Тестват няколко  идеи, които по различни причини не осъществяват. ESCREO създават, инспирирани от преживяване по време на обучението им в Америка. Всяка повърхност става бяла дъска за многократно писане с боя от ESCREO. Към екипа си привличат технолог, който разработва собствена формула на боята. Екипът кандидатства за финансиране от фонда за рисков капитал Eleven и успява да спечели инвестиция в проекта.  Продуктът си младите предприемачи определят като инструмент за креативност, а с него искат да вдъхновят хората да творят по-често у дома или в офиса.  За пет години Елена, Искрен и Ясен се сблъскват с интересни предизвикателства на малкия български пазар, но с упорита работа, успяват да се наложат не само в България, а да продават успешно в Англия и на други европейски пазари. "Обграждайте се с хора, които ви вдъхновяват, преследвайте всички ваши луди идеи и ги споделяйте. Търсете решения, това всъщност е смисъла на предприемачеството", окуражи всички бъдещи предприемачи Елена.  "Бъдете достатъчно упорити, замислете се кои са променливите около вас, кое е важното и кое нещото, което си струва да правите за времето, което имате.", заключи Искрен. Приятно слушане! Заредете се доза вдъхновение да творите и вземете вашия нов инструмент за креативност ➡️ ESCREO.  Книгите, които нашите гости препоръчаха: Елена Николова: Let My People Go Surfing: The Education of a Reluctant Businessman - Yvon Chouinard Искрен Митков: Algorithms to Live By: The Computer Science of Human Decisions - Brian Christian & Tom Griffiths  Ще се радваме на обратна връзка: Кои са хората, които бихте искали да чуете в подкаста? Хареса ли ли ви този епизод? Пишете ни: Facebook LinkedIn Instagram Twitter Всички епизоди на шоуто и други интерeсни подробности може да откриете на нашия сайт: Beyond Numbers.

Peter Svarre, foredragsholder, forfatter og digital strateg og Søren Dahlgaard co-founder og ansvarlig for AI hos SupWiz gør os klogere på GPT3 og potentialer i machine learning. Vi dykker ned i teknologien og hvordan vi som mennesker og organisationer kan udnytte de nye muligheder. Hvordan skal vi realisere teknologiens potentialer? Hvad skal der være på plads i organisationen, så man meningsfuldt kan arbejde med bots? Det svarer gæsterne på. Vi perspektiver også udviklingen og får indblik i SupWiz' arbejde med at levere intelligent kundeservice. Noter: Link til mere om Peter Svarres arbejde inkl. bogen ‘Hvad skal vi med mennesker?': https://www.petersvarre.dk/ Link til SupWiz: https://www.supwiz.com/ Bøger om AI anbefalet af Lars K. Jensen - Twitter @larskjensen: ‘Gods and Robots' af Adrienne Mayor: https://www.amazon.com/Gods-Robots-Machines-Ancient-Technology/dp/0691183511 ‘Rebooting AI' af Gary Marcus og Ernest Davis: https://www.amazon.com/Rebooting-AI-Building-Artificial-Intelligence-ebook/dp/B07MYLGQLB ‘The Creativity Code' af Marcus du Sautoy: https://www.amazon.co.uk/Creativity-Code-Marcus-du-Sautoy/dp/0008288151 ‘Algorithms to Live By: The Computer Science of Human Decisions' af Brian Christian og Tom Griffiths: https://www.amazon.com/Algorithms-Live-Computer-Science-Decisions/dp/1627790365 Vært og tilrettelæggelse: Mathias Lund Schjøtz

Steph is the Head of Publications at Toptal, a serial maker, and a supporter of women in technology.  Outside of leading a remote team of a few dozen, she is a self-taught developer that builds projects related to women in technology, remote work, and self-improvement.    She’s launched products that have hit #1 on Product Hunt, articles that have trended the top of Hacker News, and was nominated for Maker of the Year in 2018.  She actively supports women in technology by speaking about the psychology behind inclusion and through building resources like FeMake and is a judge for the Toptal Women’s Scholarship.   On today's episode we discuss some of the best practices for managing remote teams based on her recent blog post."Managing Remote Teams: A Psychological Perspective." Continue on for a great discussion with Steph.   Contact Info: Personal website: https://stephsmith.io Twitter: >?q=https://twitter.com/stephsmithio&source=gmail&ust=1554743123782000&usg=AFQjCNFW2gh0QlgMfBOjUSeqUQrZvcDJbw">https://twitter.com/stephsmithio LinkedIn: https://www.linkedin.com/in/stephaniesmith93/     Show Notes:   Steph's Awesome Book List   Best Practices for Managing Remote Teams: A Psychological Perspective   Thanks for the Feedback    Radical Candor   Algorithms to Live By: The Computer Science of Human Decisions   Give and Take: Why Helping Others Drives Our Success   The Four Tendencies: The Indispensable Personality Profiles That Reveal How to Make Your Life Better (and Other People's Lives Better, Too)  

My guest this week is unique and so requires a short story. I met our guest Michael Mayer because of twitter. I followed and enjoyed one of several pseudonymous accounts that he maintains to experiment with ideas. His various accounts have wide followings. I think many of the best accounts on twitter are anonymous or pseudonymous, and I’ve always made a point to get to know the ones I like best. As it turns out, Michael was also an entrepreneur. He’d been building a new company and was raising a small amount of outside capital. I didn’t invest personally, in part because he raised it so quickly after I spoke with him. Ever since, I’ve gotten to know him better and followed his company, Bottomless, with interest. You know that I am always hyper transparent about any potential conflicts of interest, so it’s worth noting that while I am not an investor in this company, I expect to be at some point in the future. The topic of our conversation is both his social media activity and his company. I am a coffee fanatic, and the problem he is solving is one I live. I order a weekly bag of coffee beans, but I often have too much coffee or run out. Bottomless solves this by shipping you a simple scale which you keep wherever you store your coffee, connect to your Wi-Fi, and set your bag of coffee on. It automatically orders new coffee for you at the right time. Thus the name: Bottomless. If you like the conversation, check out bottomless.com  With this podcast, all I’m really trying to do is find, meet, and learn from interesting people. Michael certainly qualifies. I hope you enjoy this unique episode.   For more episodes go to InvestorFieldGuide.com/podcast. Sign up for the book club, where you’ll get a full investor curriculum and then 3-4 suggestions every month at InvestorFieldGuide.com/bookclub. Follow Patrick on Twitter at @patrick_oshag   Show Notes 2:06 - (First Question) – Why he writes under a pseudonym online 2:58 – Positive impacts of writing this way 3:45 – His background 5:02 – Habits he improved upon 7:03 – Where did his exploration into technology and start-ups come from             7:33 – Algorithms to Live By: The Computer Science of Human Decisions 10:32 – Elements of business that interest him most 13:26 – Building social capital vs the current state of education 17:06 – What information does he like to consume             18:17 – Zero to One: Notes on Startups, or How to Build the Future             18:34 – Jerry Neumann blog Reaction Wheel | Podcast episode             18:39 – Kevin Simler’s blog  Melting Asphalt| Podcast Episode 21:01 – Why the current education system is busted 22:54 – Formation of his business 24:04 – Importance of making things legible 25:54 – On demand delivery vs subscription business models 30:16 – Early day in developing the scale for his business 33:50 – What he learned about coffee roasters 35:29 – thoughts on supplier power 36:17 – The customer relationship 39:50 – Best objections to his business 41:58 – Biggest operational/emotional challenges 42:56 – Best moment 44:39 – Time at Y combinator 46:28 – His unique co-founder story 49:47 – Marketing strategies and acquisition costs 51:37 – The idea of a commercial loop 53:27 – Discarded ideas, such as spaced repetition social networks 57:38 – Having a long-term plan vs reformatting a business into success 1:00:35 – What works on twitter based on his experience 1:03:09 – Most controversial opinion 1:05:59 – Kindest thing anyone has done   Learn More For more episodes go to InvestorFieldGuide.com/podcast.  Sign up for the book club, where you’ll get a full investor curriculum and then 3-4 suggestions every month at InvestorFieldGuide.com/bookclub Follow Patrick on twitter at @patrick_oshag

Algorithms to Live By: The Computer Science of Human Decisions - Stay “on the bottom of things” (instead of on top), and get ahead again at strategic times - Focus on the most urgent and time-intensive tasks first to keep high productivity - It’s impossible to optimize your life UNLESS you (1) make assumptions, (2) show bias toward simple solutions, (3) consider the cost of your time, and (4) take risks.   Check out our survey at MotivationMinute.com and tell us what books you’d like to hear on the show!

Look before you leap. We’ve all heard this piece of advice. But is it helpful? Whether considering trivial matters, like trying to find a parking spot or weighing life-changing decisions like choosing a spouse, it’s difficult to find the balance between passing up a great opportunity or making a choice too quickly. Author Brian Christian and cognitive scientist Tom Griffiths have teamed up to bring you a statistically tested formula for decision-making. In Algorithms to Live By: The Computer Science of Human Decisions, they explore the way that algorithms can be applied to our everyday lives to help us know exactly how long we should look before we leap. They will talk about how these algorithms designed for computers can also untangle our human questions.  Buy the book Recorded live at Town Hall Seattle Monday, April 10, 2017

BRIAN CHRISTIAN is the author of The Most Human Human: What Artificial Intelligence Teaches Us About Being Alive, and coauthor (with Tom Griffiths) of Algorithms to Live By: The Computer Science of Human Decisions. Brian Christian's Edge Bio Page (https://www.edge.org/memberbio/brian_christian) The conversation: https://www.edge.org/conversation/brian_christian-how-should-a-society-be

My guest today is Brian Christian, an American non-fiction author, poet, programmer and researcher, best known for the two bestselling books The Most Human Human (2011) and Algorithms to Live By (2016). The topic is his book Algorithms to Live By: The Computer Science of Human Decisions. In this episode of Trend Following Radio we discuss: Optimal stopping What is an algorithm Process vs. Outcome The explore, exploit trade off The multi-arm bandit problem Win stay, lose shift Regret minimization framework Frequency and intensity of mistakes related to age Upper confidence bound algorithm Threading Jump in! --- I'm MICHAEL COVEL, the host of TREND FOLLOWING RADIO, and I'm proud to have delivered 10+ million podcast listens since 2012. Investments, economics, psychology, politics, decision-making, human behavior, entrepreneurship and trend following are all passionately explored and debated on my show. To start? I'd like to give you a great piece of advice you can use in your life and trading journey… cut your losses! You will find much more about that philosophy here: https://www.trendfollowing.com/trend/ You can watch a free video here: https://www.trendfollowing.com/video/ Can't get enough of this episode? You can choose from my thousand plus episodes here: https://www.trendfollowing.com/podcast My social media platforms: Twitter: @covel Facebook: @trendfollowing LinkedIn: @covel Instagram: @mikecovel Hope you enjoy my never-ending podcast conversation!

Brian Christian, co-author of “Algorithms to Live By: The Computer Science of Human Decisions,” is on today’s podcast. The book shows how common algorithms relate to our everyday lives. Brian starts off giving a historical explanation of an “algorithm”. Algorithms do not just relate to computers or mathematical procedures. A cooking recipe can be described as an algorithm or you could use an algorithm to solve the question, “How do you know when your best opportunity is?” Brian says you use an algorithm known as “optimal stopping” to solve this question. He explains the algorithm that provides the best probability of the best outcome. Probability is the next. Is it worth exploring a new business possibility? Or is it better to hone in your skills and continue on with what you are doing? There is a formal framework or algorithm to help make these decisions. Brian explains the “win stay, lose shift” approach. If a restaurant is good, go back. If you don’t have a good experience, don’t go back. It may not be the optimal approach but it is a good approach and easy to live by. Michael jumps to an example with Jeff Bezos, the CEO of Amazon. Brian tells Jeff’s story of Amazon and how he left his successful job at the time to start up this “online bookstore”. He ultimately used a “regret minimization framework” to make his decision. There was a possibility Jeff may not have been successful starting Amazon, but had he not tried it, he would have regretted not trying for the rest of his life. Brian also gives other examples of regret minimization algorithms. Michael and Brian discuss threading next. Lastly, Michael brings up the “searching vs. sorting conundrum” that Brian discusses thoroughly in his book. Brian gives examples about sorting through information on the computer. He says that people should ask themselves “Should you be sorting at all?” Brian explains why “messy” is sometimes better. In this episode of Trend Following Radio: Optimal stopping What is an algorithm Process vs. Outcome The explore, exploit trade off The multi-arm bandit problem Win stay, lose shift Regret minimization framework Frequency and intensity of mistakes related to age Upper confidence bound algorithm Threading

It is possible to be extremely astute about how we manage difficult decisions. With just a few mental tools we get the benefit of better outcomes along with release from agonizing about the process of deciding. Many mental tools—algorithms—developed with obligatory clarity for computers turn out to have ready application for humans facing such problems as: when to stop hunting for an apartment (or lover); how much novelty to seek; how to get rid of the right stuff; how to allot scarce time; how to consider the future; when to relax constraints; how to give chance a chance; how to recognize when you’re playing the wrong game; and how to make decisions easier for others (“computational kindness”). Brian Christian, the co-author of Algorithms to Live By: The Computer Science of Human Decisions, lives in San Francisco, deploying his degrees in philosophy, computer science, and poetry.