Podcast appearances and mentions of Cassie Kozyrkov

Cassie Kozyrkov created the discipline of decision intelligence, combining the power of AI with data science to enable companies to make better choices. She's now an AI advisor, and she writes the popular Decision Intelligence newsletter. Kozyrkov joined the WorkLab podcast to discuss how leaders can maximize the potential of AI and data, why having too many options is as unhelpful as having too few, and how to avoid falling prey to confirmation bias. WorkLab Subscribe to the WorkLab newsletter  

Cassie Kozyrkov, Google's first-ever Chief Decision Scientist, joins us on The Augmented Life to share her insights on decision-making, data, and AI. During her tenure at Google, Cassie trained over 20,000 Googlers on data-driven decision-making and advised leadership on building data-driven organizations. Now the CEO of a stealth AI startup, she brings an abundance of wisdom from her 20+ year career spanning data science, consulting, and academia. With a unique blend of expertise in statistics, economics, and psychology, Cassie offers a multidisciplinary perspective on how we can improve our decision-making processes. In this episode, Cassie explores the complex relationship between human cognition, data, and technology. She challenges us to rethink our assumptions about decision-making and provides practical strategies for leveraging tools and self-awareness to make better choices. Throughout the conversation, Cassie emphasizes the importance of cognitive realism, personal data collection, and embracing the potential of AI while maintaining a critical perspective on its limitations. Her insights offer a roadmap for navigating an increasingly data-driven world and making more informed, intentional decisions in our personal and professional lives. Key topics include: - [7:02] Recognizing and Compensating for our Cognitive Limitations - [26:44] Bridging the Gaps in our Memory and Cognition - [27:58] Digitizing Personal Data for a Future of Powerful AI tools - [3:02] The Importance of Defining Terms and Operationalizing Concepts - [38:02] Balancing Intuition and Data in Decision-Making

Robb and Josh welcome Cassie Kozyrkov, Google's First Chief Decision Scientist, for a conversation about the limitations of data and the need to put a face on technology. Cassie is now CEO of Data Scientific and helped shape the technology all around us, and this far-ranging discussion of conversational AI examines the composition of the technologies that go into artificial intelligence, the ways we can use technology to help people make better quality decisions, and why we should look for opportunities to automate "thunking" moments.

Kevin est Senior Data Scientist et formateur sur les métiers de la data. Il est surtout l'un des plus gros influenceurs data en France, avec +7K abonnés sur LinkedIn et 1K abonnés sur TikTok. Dans cet épisode, je me mets dans la peau d'un étudiant ou d'un profil en reconversion et lui pose les questions essentielles afin de lancer sa carrière en data.On aborde :

Nesse episódio, trouxemos duas pessoas maravilhosas, o ⁠Guga Moser⁠ e a Dani Sitko, para falar um pouco sobre o que rolou no tão comentado Web Summit.Vamos ouvir que foi destaque, o que teve de bom e o que deu pra aprender em um evento desse porte. E aí bora ouvir o que rolou? Aproveita e se conecta com a gente lá na comunidade do telegram e conta pra gente o que vocês acharam. Referências: Cassie Kozyrkov - https://youtu.be/gjDRDrOrH94 https://kozyrkov.medium.com/whats-different-about-today-s-ai-380569e3b0cd Web Summit Newspaper

This episode focuses on AI and more specifically, generative AI. Many people will have recently seen the trending discussions and thought pieces on #ChatGPT.To find out what it all means for legal professionals, I spoke with Jonny Badrock, Senior Director for Data Services at SYKE.We explore the immediate applications of generative AI for legal teams, consider its current limitations and then cast our eyes forward to discuss what it might mean in the medium and long term.Further readingOpenAI ChatGPTOn the Dangers of Stochastic Parrots: Can Language Models Be Too Big?

In this podcast, Sharon Mandell describes how AI helps her team at Juniper and Juniper Networks'  IT customers to deliver better experiences.  Links to information discussed in the podcast. 2022 Juniper Networks AI Report: https://juni.pr/3CyRdyuAssessing AI Security Risk: https://www.microsoft.com/security/blog/2021/12/09/best-practices-for-ai-security-risk-management/Cassie Kozyrkov's AI Lectures: https://www.youtube.com/playlist?list=PLRKtJ4IpxJpB_2ei8-5eWU31EZ6uSj9_sBill Schmarzo's Big Data MBA Series: https://www.youtube.com/playlist?list=PLaQqEd_Tx4Ep1bOIFEzDJNXI9r64rjhXLEthical Machines by Reid Blackman (Book): https://www.reidblackman.com/ethical-machines/A Beginner Guide on Synthetic Data: https://towardsdatascience.com/synthetic-data-key-benefits-types-generation-methods-and-challenges-11b0ad304b55The Real Promise of Synthetic Data: https://news.mit.edu/2020/real-promise-synthetic-data-1016Bio.Sharon Mandell is the Senior Vice President and Chief Information Officer leading Juniper's global information technology team. In this role, she leads the ongoing enhancement of the company's IT infrastructure and applications architectures to support the growth objectives of the company. She and her team are also responsible for showcasing Juniper's use of its technologies to the world. Prior to joining Juniper in 2020, Mandell was the Chief Information Officer for TIBCO Software and previously developed her leadership strategy at Harmonic, Black Arrow (now Cadent), Knight Ridder and the Tribune Company. Throughout her career, Mandell developed a level of expertise in cyber security and compliance, enterprise architecture and road mapping, data and analytics, digital transformation and customer service. She is passionate about supporting women in STEM careers and in her free time Mandell serves on various arts and education related boards. She also proudly serves on the computer science advisory board at Temple University. Mandell holds a bachelor's degree in computer science from Temple University and an MBA from the University of Chicago Booth School of Business.https://www.linkedin.com/in/sharon-mandell-juniper/ @sharonomink

How do the world's most influential technology companies think about decision-making? Google's Chief Decision Scientist, Cassie Kozyrkov, joins your host, Dr. Joe Sweeney, Executive Director of the Alliance for Decision Education, to talk about the science of decision-making in data-driven organizations, the pitfalls and possibilities for incorporating AI into the decision-making process, and how computer programming is like a cross between LEGOs and magic spells. Cassie and Joe discuss her journey from logging gemstones in Microsoft Excel as a child to founding the field of decision intelligence at Google, and the profound impact that Decision Education will have on our children's futures. Cassie also shares critical advice about asking ourselves the right question, in order to make the most rational decision.

If the terms “Artificial Intelligence,” “Machine Learning,” and “Deep Learning” have you uttering "Oofda", this episode is for you. Tim Bornholdt chats with Indico Data's Slater Victoroff about these emerging technologies and best use-cases for the future.   **SHOW LINKS** Indico Data | https://indicodata.ai/  Slater on Twitter | https://twitter.com/sl8rv  Slater.website | https://www.slater.website/  The Toaster Project | http://www.thetoasterproject.org/  Cassie Kozyrkov, Chief Decision Scientist at Google, on LinkedIn | https://www.linkedin.com/in/kozyrkov/ Rate and review the show on Apple Podcasts | https://constantvariables.co/review  Connect with The Jed Mahonis Group on LinkedIn | https://linkedin.com/company/the-jed-mahonis-group  Show notes | https://constantvariables.co Chat with The Jed Mahonis Group about your app dev questions | https://jmg.mn Are you an iOS, Android or Rails developer? Connect with us | careers@jmg.mn 

Some would say that, given the breadth and depth of data that is available to businesses these days, a surefire path to business value is to load up a department with smart data scientists, task them with developing a solid machine learning strategy, and then execute that strategy. The people who've said that might take issue with this episode. Cassie Kozyrkov joined the show to discuss decision-making: what it is, how we often frame decisions too narrowly, and the different roles data can play to support the process. And much, much more! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page. 

Decisions are what create our life and dictate our futures. All our decisions have infinite compounding effects that shape the world. With that in mind, it is vital for us to make intelligent decisions when it matters. Chief Decision Scientist at Google and a leader in the field of Decision Intelligence, Cassie Kozyrkov, unravels the process of decision-making and what role data science and the concepts that underlie play. Cassie explains the importance of humans - the decision-makers - in the safe, reliable, effective, and responsible production of artificial intelligence. She emphasizes how we can use our innate analytical decision-making to better ourselves and society for the future.Support the show (http://www.patreon.com/barrykibrick)

We're baaaaaaack…! Shorter show name, a rebrand, some minor formatting and structural updates, but still "Moe Kiss with a couple of guys who listeners can't keep straight." On this episode, we talk for a little bit about what we've been doing while we were on hiatus and then dive into a topic that only Cassie Kozyrkov has dared to deeply explore before: the distinction between analysts, statisticians, data engineers, ML engineers...and data charlatans. Well, really just the first two. But, Cassie('s content) has made numerous appearances on the show, so it seemed like high time that we dug into some of her ideas. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.  

1 — Which do you think is most critical to scale?! Vote here!Tech was dominant on the Davos Agenda — but what was striking was how many real examples there are of enterprises scaling AI programs.2 — Want to build an effective Enterprise Data Strategy?! Use Krishna Cheriath’s “Iceberg Approach”. Everyone acknowledges that data is a vital enterprise resource/asset, yet most companies do not have an effective EDS and CDOs/CDAOs struggle to articulate an effective EDS to align leaders across business, technology and analytics.3– 3 Ways To Get Value out of External Data by McKinsey3a. Establish a dedicated team for external-data sourcing3b. Develop relationships with data marketplaces and aggregators3c. Prepare the data architecture for new external-data streams4 — Ladies in Data, AI and Analytics You Should Follow!Priyanka Vergadia on #31DaysofMLDale Markowitz on How to use AI to translate videos.Can AI be creative?! Cassie Kozyrkov answers...And a special thanks to Ryan Anderson, the host of the "Digital Native" Podcast: We talked about The Future of Data, The Value of Emotions in Decision Making…and the Pre-Mortem…see the episode @ https://www.youtube.com/watch?v=zy7sPJGCyEg&feature=emb_title

>> VIEW SHOW NOTES + RESOURCESChristina Stathopoulos is an Analytical Consultant at Google who uses data and visualization to help her clients drive decisions about marketing, expansion, and more. She holds adjunct faculty positions at two top universities in Madrid, where she teaches analytics courses for MBA programs. Alongside her corporate and academic work, she is a wildly popular speaker supporting women in STEM and emerging technologies. So basically, Christina is bonafide analytics rockstar using best-in-class data presentation and visualization practices to fuel her meteoric speaking career. In This Episode, You’ll Learn…Christina’s unique and winding path towards becoming a world-renowned analytics speakerThe profound impact effective data visualization and presentation had on her careerThe four guiding “maxims” of conversation she uses to deliver every talkHer favorite data visualization tools vs. what she recommends for othersAn inside look into her rigorous presentation preparation processThe simple and ingenious way she presents complex technical informationHer invaluable advice on what aspiring women in tech speakers should and should not doWhy the analytics industry still has work to do in representing women in tech speakersThe surprising advice she would give her past self before her first presentationPeople, Blogs, and Resources MentionedChristina’s keynote for the Smart Future World Expo 2019 in IstanbulGoogle Data StudioGrice’s maxims of conversationData is Ugly RedditThe Women in Analytics ConferenceThree Women in Tech Speakers to Watch: Kate Strachnya, Cassie Kozyrkov, Allie K. Miller Talk Like TED by Carmine GalloEverybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are by Seth Stephens-DavidowitzHow to Keep Up with Christina Stathopoulos:Christina’s LinkedIn, Twitter, and Instagram profilesHer LinkedIn #BookAWeekChallenge

In this episode, Sarah Bowen and Merle Van Den Akker talk to Rory Sutherland. The conversation takes many interesting twists and turns including: How does innovative thinking and knowledge accumulation differ in business compared to academia? What is the problem with data (particularly big data)? Why did it take a pandemic for people to start working from home? Listen to the episode to discover what is it that connects cryptic crosswords, a keen interest in true crime, evolutionary, and behavioural science!Links mentioned:Rory’s reading listThe books that sold Rory on behavioural science“The Economic Naturalist” by Robert Frank: https://www.amazon.co.uk/dp/B0054ZBXFM/ref=cm_sw_em_r_mt_dp_jvXGFbM69XH6A“The Darwin Economy” by Robert Frank: https://www.amazon.co.uk/dp/0691153191/ref=cm_sw_r_tw_dp_x_FwXGFbVC3ZAZW“The Mating Mind” by Geoffrey Miller: https://www.amazon.co.uk/dp/0099288249/ref=cm_sw_r_tw_dp_x_KxXGFbKZX06RW“Spent: Sex, Evolution, and Consumer Behaviour” by Geoffrey Miller: https://www.amazon.co.uk/Spent-Sex-Evolution-Consumer-Behavior/dp/0143117238Innovation:“How innovation works” by Matt Ridley: https://www.amazon.co.uk/dp/B07XZ6Z8ZH/ref=cm_sw_r_tw_dp_x_GyXGFbW3490GWTrue Crime and the Golden State Killer:“I’ll Be Gone in the Dark” by Michelle McNamara: https://www.amazon.co.uk/dp/B0792LVP7T/ref=cm_sw_r_tw_dp_x_4BXGFb888R69XOther linksSoviet innovation methodology TRIZ: https://en.wikipedia.org/wiki/TRIZWhy the hell does a kangaroo jump? https://www.sciencemag.org/news/2019/02/when-did-kangaroos-start-hopFollow @quaesita (Cassie Kozyrkov, Head of Decision Intelligence @ Google) on twitter: https://twitter.com/quaesita Finding Rory Sutherland:Rory’s twitter (@rorysutherland): https://twitter.com/rorysutherlandNudgestock (@nudgestuck)Watch the 2020 event on YouTube: https://www.youtube.com/watch?v=ObFrZImxYeIhttps://nudgestock.co.uk/ Questioning Behaviour Socials: Facebook: @QBpodcast (https://www.facebook.com/QBPodcast) Insta: @questioningbehaviour (https://www.instagram.com/questioning...)Twitter: @QB_podcast (https://twitter.com/QB_Podcast) LinkedIn: @Questioning Behaviour (https://www.linkedin.com/groups/8928118/) Music: Derek Clegg “You’re the Dummy” https://derekclegg.bandcamp.com/

Proving that innovation is more than just a lucky idea, Matt Mullen curated his vast experience while at Macy's, VISA, Epicor Software and ProShip to graciously teach us about all things innovation, entrepreneurialism and intrepreneurislism. Matt's masterclass includes a clear, growth-based definition of innovation, the impact of organizational structure, creating a plan toward profit, 3 levers to yield growth, the discipline needed to evaluate business ideas, the importance of storytelling and much more. So much more that we kept recording...and recording, resulting in two episodes! Stay tuned for the final portion of Matt's interview dropping next Thursday. In the meantime, Matt suggests to continue your education around machine learning and AI with the help of Cassie Kozyrkov, Google's Chief Decision Scientist. Warning - the article includes super cute cat photos. Fun Fact: Matt may have invented the in-mall kiosk.

In today's episode, we will be talking with our good friend, Ted Sfikas. He is the North American Director of Tealium’s Solution Consultants organization, a team that works with Tealium's customers to build strategic solutions and that work with the Universal Data Hub and automate the Data Supply Chain. He has over 17 years of experience with a number of leading organizations within Digital Marketing, Social platforms, SaaS-based telephony and messaging firms, ITSM portfolios and automated Quality Assurance technologies. Ted will be sharing how Tealium can help businesses get ready for compliance with CCPA among other things. You can connect with Ted in the following ways: LinkedIn: https://www.linkedin.com/in/tedsfikas Website: www.tealium.com. Ted also mentioned a person we should know: Cassie Kozyrkov, Head of Decision Intelligence at Google (Twitter: @quaesita). At Tech & Main, we want to be YOUR technology partner. Let our 20+ years of expertise help you achieve the outcomes that are best for your business: cybersecurity, cloud, SD-WAN and data center. We have engineers and project managers available to assist you. Call our office at 678-575-8515, email us at info@techandmain.com or visit us at www.techandmain.com. Thanks for listening! --- Send in a voice message: https://anchor.fm/techandmain/message

Today's podcast is on AI. Stripping away the jargon in machine learning and AI to take a look at what’s easy, what’s hard, how to spot opportunities, and what you need to know to avoid the biggest threats in AI. Cassie Kozyrkov is Chief Decision Scientist at Google Cloud and shares her view and experience.

In this episode of the Data Show, I speak with Cassie Kozyrkov, technical director and chief decision scientist at Google Cloud. She describes “decision intelligence” as an interdisciplinary field concerned with all aspects of decision-making, and which combines data science with the behavioral sciences. Most recently she has been focused on developing best practices that […]

Top Articles is Hacker Noon's way of highlighting the best from the community of contributing authors. "Why Businesses Fail At Machine Learning" by Cassie Kozyrkov Cassie is Chief Decision Scientist at Google, where they've coined the term "Decision Intelligence Engineering", which is a service offered by Google designed to assist businesses in assessing their applied machine learning needs. This article is from June 2018. Cassy explores the idea that when businesses attempt to utilize applied machine learning, they have a habit of attempting to reinvent the wheel Cassie Kozyrkov - https://hackernoon.com/@kozyrkov The Article - https://hackernoon.com/why-businesses-fail-at-machine-learning-fbff41c4d5db

This week, Jon Foust and Michelle Casbon bring you another fascinating interview from our time at Next! Michelle and special guest Amanda were able to catch up with Paco Nathan of Derwen AI to talk about his experience at Next and learn what Derwen is doing to advance AI. Paco and Derwen have been working extensively on ways developer relations can be enhanced by machine learning. Along with O’Reilly Media, Derwen just completed three surveys, called ABC (AI, Big Data, and Cloud), to look at the adoption of AI and the cloud around the world. The particular interest in these studies is a comparison between countries who have been using AI, Big Data, and Cloud for years and countries who are just beginning to get involved. One of the most interesting things they learned is how much budget companies are allocating to machine learning projects. They also noticed that more and more large enterprises are moving, at least partially, to the cloud. One of the challenges Paco noticed was the difference between machine learning projects in testing versus how they act once they go live. Here, developers come across bias, ethical, and safety issues. Good data governance polices can help minimize these problems. Developing good data governance policies is complex, especially with security issues, but it’s an important conversation to have. In the process of computing the survey data, Paco discovered many big companies spend a lot of time with this issue and even employ checklists of requirements before projects can be made live. In his research, Paco also discovered that about 54% of companies are non-starters. Usually, their problems stem from tech debt and issues with company personnel who do not recognize the need for machine learning. The companies working toward integrating machine learning tend to have issues finding good staff. Berkeley is working to solve this problem by requiring data science classes of all students. But as Paco says, data science is a team sport that works well with a team of people from different disciplines. Paco is an advocate of mentoring, to help the next generation of data scientists learn and grow, and of unbundling corporate decision making to help advance AI. Amanda, Michelle, and Paco wrap up their discussion with a look toward how to change ML biases. People tend to blame ML for bias outcomes, but models are subject to data we feed in. Humans have to make decisions to work around that by looking at things from a different perspective and taking steps to avoid as much bias as we can. ML and humans can work together to find these biases and help remove them. Paco Nathan Paco Nathan is the Managing Parter at Derwen. He has 35+ years tech industry experience, ranging from Bell Labs to early-stage start-ups. Paco is also the Co-chair Rev. Advisor for Amplify Partners, Recognai, Primer AI, and Data Spartan. He was formerly the Director of Community Evangelism for Databricks and Apache Spark. Cool things of the week CERN recreated the Higgs discovery on GCP video To discover the Higgs yourself, check out the CERN open data portal site Fun facts from Michelle’s visit: Seven total, four main experiments ATLAS (largest, general-purpose) site CMS (prettiest, general-purpose) site ALICE (heavy-ion) site LHCb (interactions of b-hadrons, matter/antimatter asymmetry) site The French/Swiss border runs across the CERN property Streetview of CERN control center site CERN is the birthplace of the web Where the protons come from site Watch Particle Fever movie Interview Derwen, Inc. site Derwen, Inc. Blog blog Cloud Programming Simplified: A Berkeley View on Serverless Computing paper Apache Spark site Google Cloud Storage site Datastore site Kubeflow site Quicksilver site O’Reilly Media site Google Knowledge Graph site Jupyter site JupyterCon site The Economics of Artificial Intelligence site “Why Do Businesses Fail At Machine Learning?” by Cassie Kozyrkov video The Gutenberg Galaxy site Programmed Inequality site Question of the week Stadia Connect occurred last Thursday. What are some of the biggest announcements that came out of it? Where can you find us next? Jon is in New York for Games for Change. Michelle and Mark Mirchandani are back in San Francisco. Brian & Aja are at home in Seattle. Gabi is in Brazil. Sound Effect Attribution “Crowd laugh.wav” by tom_woysky of Freesound.org

Happy Holidays, everyone! Melanie and Mark wrap up a great year by reminiscing about some of their favorite episodes! We also talk about the big news of the year, our favorite articles, and what’s coming up for the GCP Podcast in 2019. Cool things of the week Kubernetes and GKE for developers: a year of Cloud Console blog Reducing gender bias in Google Translate blog Cloud Security Command Center is now in beta and ready to use blog Main content Podcast accomplishments! We have awesome new intro and outro music, new website, new YouTube videos! We hit 1 million and then 2 million downloads! Mark and the podcast are celebrating their three year anniversary! Top 10 most downloaded episodes of all time! GCP Podcast Episode 111: Google Cloud Platform with Sam Ramji podcast GCP Podcast Episode 112: Percy.io with Mike Fotinakis podcast GCP Podcast Episode 146: Google AI with Jeff Dean podcast GCP Podcast Episode 127: SRE vs Devops with Liz Fong-Jones and Seth Vargo podcast GCP Podcast Episode 128: Decision Intelligence with Cassie Kozyrkov podcast GCP Podcast Episode 113: Open Source TensorFlow with Yifei Feng podcast GCP Podcast Episode 88: Kubernetes 1.7 with Tim Hockin podcast GCP Podcast Episode 108: Launchpad Studio with Malika Cantor and Peter Norvig podcast GCP Podcast Episode 130: Data Science with Juliet Hougland and Michelle Casbon podcast GCP Podcast Episode 125: Open Source at Google Cloud Platform with Sarah Novotny podcast Top 10 most downloaded episodes for 2018! Exact same list except Tim Hockin is not #7. Following episodes go up a number and we added to #10 spot. GCP Podcast Episode 122: Project Jupyter with Jessica Forde, Yuvi Panda and Chris Holdgraf podcast Mark’s favorite episodes GCP Podcast Episode 129: Developer Relations with Mandy Waite podcast GCP Podcast Episode 121: Kontributing to Kubernetes with Paris Pittman and Garrett Rodrigues podcast GCP Podcast Episode 131: Actions on Google with Mandy Chan podcast GCP Podcast Episode 148: Wellio with Sivan Aldor-Noiman and Erik Andrejko podcast GCP Podcast Episode 110: CPU Vulnerability with Matt Linton and Paul Turner podcast GCP Podcast Episode 125: Open Source at Google Cloud Platform with Sarah Novotny podcast GCP Podcast Episode 140: Container Security with Maya Kaczorowski podcast Melanie’s favorite episodes GCP Podcast Episode 117: Cloud AI Fei-Fei Li was the Chief Scientist of AI/ML at Google podcast GCP Podcast Episode 114: ML Bias & Fairness with Timnit Gebru and Margaret Mitchell podcast GCP Podcast Episode 141: Accessibility in Tech podcast GCP Podcast Episode 136: Robotics with Raia podcast GCP Podcast Episode 150: Strange Loop, Remote Working, and Distributed Systems with KF podcast DL Indaba GCP Podcast Episode 147: DL Indaba: AI Investments in Africa podcast GCP Podcast Episode 149: Deep Learning Research in Africa with Yabebal Fantaye & Jessica Phalafala podcast GCP Podcast Episode 152: AI Corporations and Communities in Africa with Karim Beguir & Muthoni Wanyoike podcast GCP Podcast Episode 157: NeurIPS and AI Research with Anima Anandkumar podcast Favorite announcements, products, and more at Google Cloud Unity and Google Cloud Strategic Alliance blog Open Match blog Cloud TPU site Google Dataset Search is in beta site No tricks, just treats: Globally scaling the Halloween multiplayer Doodle with Open Match on Google Cloud blog GKE On-Prem site Open Source - Knative release, Skaffold, Istio updates, gVisor, etc. Google in Ghana blog Cloud NEXT blog GCP Podcast Episode 137: Next Day 1 podcast GCP Podcast Episode 138: Next Day 2 podcast GCP Podcast Episode 139: Next Day 3 podcast Unity and DeepMind partner to advance AI research blog Introducing PyTorch across Google Cloud blog Question of the week What were your personal highlights for 2018? Mark Agones Introducing Agones: Open-source, multiplayer, dedicated game-server hosting built on Kubernetes blog github The new website Having Melanie join me on the podcast Melanie Bringing Francesc back Meeting Grace GCP Podcast Episode 142: Agones With Mark Mandel and Cyril Tovena podcast Where can you find us next? It’s the holidays! Special thanks! Thank you guests Thank you Jennifer Thank you HD Interactive: James, Trae, Sabrina, and Sean Thank you Greg Thank you Neil, Chuck, and Shana Thank you MBooth for the website overhaul and social media support Thank you Francesc Thank you listeners!

“We as humans have a fundamental malfunction, seeing human properties in computers.” As Chief Decision Scientist at Google, Cassie Kozyrkov guides teams in data-driven decision process and AI strategy. She personally trained over 15,000 Googlers. We talked about how humans and machines make decisions. Key takeaway: “A decision is a decision, no matter if it's done by a human or a machine.” Also, check out Cassie's posts on Medium. Nobody can explain machine learning better. Must read!

“We as humans have a fundamental malfunction, seeing human properties in computers.” As Chief Decision Scientist at Google, Cassie Kozyrkov guides teams in data-driven decision process and AI strategy. She personally trained over 15,000 Googlers. We talked about how humans and machines make decisions. Key takeaway: “A decision is a decision, no matter if it’s done by a human or a machine.” Also, check out Cassie’s posts on Medium. Nobody can explain machine learning better. Must read!

In this episode of DataFramed, Hugo speaks with Cassie Kozyrkov, Chief Decision Scientist at Google Cloud. Cassie and Hugo will be talking about data science, decision making and decision intelligence, which Cassie thinks of as data science plus plus, augmented with the social and managerial sciences. They’ll talk about the different and evolving models for how the fruits of data science work can be used to inform robust decision making, along with pros and cons of all the models for embedding data scientists in organizations relative to the decision function. They’ll tackle head on why so many organizations fail at using data to robustly inform decision making, along with best practices for working with data, such as not verifying your results on the data that inspired your models. As Cassie says, “Split your damn data”.Links from the showFROM THE INTERVIEWCassie on Twitter Is data science a bubble? (By Cassie Kozyrkov, Hackernoon)Incompetence, delegation, and population (By Cassie Kozyrkov, Hackernoon)Populations — You’re doing it wrong (By Cassie Kozyrkov, Hackernoon)What on earth is data science? (By Cassie Kozyrkov, Hackernoon)FROM THE SEGMENTSProbability Distributions and their Stories (with Justin Bois at ~19:45)Justin's Website at CaltechProbability distributions and their stories (By Justin Bois)Machines that Multi-Task (with Friederike Schüür of Fast Forward Labs ~43:45)Sebastian’s Ruder’s Overview of Multi-Task Learning in Deep Neural NetworksMulti-Task Learning for NLP, also by Sebastian RuderGANs for Fake Celebrity Images (Karras et al, Nvidia)Adversarial Multi-Task Learning for Text Classification (Liu et al., arXiv.org)Original music and sounds by The Sticks.

What is decision intelligence? How does it tie into the world of data science? And what does Google have to do with it all? Click on the above SoundCloud link and find out! Welcome to episode #11 of DataHack Radio, where we were joined by Google Cloud's Chief Decision Scientist, Cassie Kozyrkov! Cassie is a well-known speaker in the data science sphere, and often pens down her thoughts in articulate fashion in this field. She takes us on a journey into her life at Google and how she went from being a Statistician at Google to her current role.

Chief decision scientist Cassie Kozyrkov berättar om sin resa på Google i att försöka hitta tillämpningar baserade på de senaste forskningsrönen inom AI och hur deras process går till. Hon förklarar bland annat hur man använder AI för Google Search, där man bland annat får sin sökmening kompletterad helt automatiskt. Cassie Kozyrkov beskriver hur man ska lyckas tillämpa AI, och mer specifikt maskininlärning, och hon menar att det är en utmaning och konst i sig. Hon berättar att det finns två sidor, nämligen en affärssida och en tekniksida av maskininlärning. Hon beskriver hur ett team ska byggas och vilka kompetenser det bör ingå i varje team för att man ska lyckas med att bygga AI-system som gör nytta. Dessutom avslöjar Cassie Kozyrkov Googles strategi, där de gått över från "mobile first" till "AI first", och hur de internt försöker utbilda alla inom grunderna för AI – inklusive HR, jurister, och ingenjörer. Läs mer: https://ai-podden.se/

Chief Decision Scientist, Cassie Kozyrkov joins Mark and Melanie this week to explain data science, analytics, machine learning and statistical inference, in relation to decision intelligence. Cassie Kozyrkov As Chief Decision Scientist at Google Cloud, Cassie advises leadership teams on decision process, AI strategy, and building data-driven organizations. She works to democratize statistical thinking and machine learning so that everyone - Google, its customers, the world! - can harness the beauty and power of data. She is the innovator behind the practice of Decision Intelligence Engineering at Google and she has personally trained over 15,000 Googlers in machine learning, statistics, and data-driven decision-making. Before her current role, she served in Google’s Office of the CTO as Chief Data Scientist. Prior to joining Google, Cassie worked as a data scientist and consultant. She holds degrees in mathematical statistics, economics, psychology, and cognitive neuroscience. When she’s not working, you’re most likely to find Cassie at the theater, in an art museum, exploring the world, or curled up with a good novel. Cool things of the week Cloud ML Engine adds Cloud TPU support for training blog docs Google Kubernetes Engine 1.10 is generally available and ready for the enterprise blog Introducing ultramem Google Compute Engine machine types blog Increase performance while reducing costs with the new App Engine scheduler blog docs Interview Decision Intelligence wikipedia Redhat Summit Keynote youtube Data Analytics wikipedia Statistical Analysis wikipedia Machine Learning wikipedia Deep Learning wikipedia There are several other episodes that provide insights into data science: #31 TensorFlow with Eli Bixby podcast #84 Kaggle with Wendy Kan podcast #109 Cloud AutoML Vision with Amy Unruh and Sara Robinson podcast #113 Open Source TensorFlow with Yifei Feng podcast #122 Project Jupyter with Jessica Forde, Yuvi Panda and Chris Holdgraf podcast As well as case studies on real world problems: #91 The Future of Media with Machine Learning with Amit Pande podcast #115 Google Play Marketing with Dom Elliott and Stewart Bryson podcast Question of the week How can I secure my Google Cloud Platoform acoount using a YubiKey? Securing your Cloud Platform Account with Security Keys docs Encrypting Google Application Default and gcloud credentials with GPG SmardCard blog Where can you find us next? Mark will be speaking at the Monthly SF Game Development Community, presenting on You Can’t Just Add More Servers on May the 30th in San Francisco. Melanie is speaking at a joint WiMLDS and PyLadies event “Paths to Data Science” on June 26th. More details to come.