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Happy Halloween! Today, Jon Foust and Brian Dorsey chat with Maria Laura Scuri of FACEIT about ways they are reducing toxicity in gaming. FACEIT is a competitive gaming platform that helps connect gamers and game competition and tournament organizers. In order to do this well, FACEIT has put a lot of energy into finding ways to keep the experience positive for everyone. Because gaming toxicity can involve anything from verbal jabs to throwing a game, FACEIT uses a combination of data collecting programs and input from players to help identify toxic behavior. In identifying this behavior, FACEIT has to consider not only the literal words spoken or actions made, but the context around them. Is that player being rude to strangers or is he egging on a friend? The answer to this question could change the behavior from unacceptable to friendly banter. Using their own machine learning model, interactions are then given a score to determine how toxic the player was in that match. The toxicity scores along with their program, Minerva, determine if any bans should be put on a player. FACEIT focuses on punishing player behavior, rather than the player themselves, in an effort to help players learn from the experience and change the way they interact with others in the future. Maria’s advice to other companies looking to help reduce toxicity on their platforms is to know the context of the toxic event. Know how toxicity can express itself on your platform and find ways to deal with all of them. She also suggests tackling the issues of toxicity in small portions and celebrating the small wins! Her final piece of advice is to focus on criticizing the behavior of the rather than attacking them personally. Maria Laura Scuri Maria is the Director of Business Intelligence at FACEIT, the leading competitive platform for online multiplayer games with over 15 million s. She ed FACEIT as part of the core team in 2013 as an intern assisting with everything from customer to event management. Her ion for data, machine learning, and artificial intelligence saw her quickly rise through the ranks to her current position, leading the Business Intelligence and Data Science teams. Maria works side by side with some of the biggest tech companies in the world including Google Cloud. She is the main lead on a number of projects including the inception of an Artificial Intelligence to fight toxicity on the platform. Maria is responsible for implementing best practices around data visualization and tools that allow the FACEIT team to thrive, as well as sourcing and training new talent. Maria is a huge video games fan. You can find her on League of Legends as “FACEIT Lulu” and on Steam as “Sephariel”. Cool things of the week What can Google Cloud do for you? New trainings for business professionals blog Leave no database behind with Cloud SQL for SQL Server blog How to orchestrate Cloud Dataprep jobs using Cloud Composer blog Updates make Cloud AI platform faster and more flexible blog Use GKE usage metering to combat over-provisioning bterview FACEIT site FACEIT blog FACEIT on Medium site Steam site Perspective API site BigQuery site Looker site Cloud Datalab site Jupyter Notebook site Cloud AI Platform site TensorFlow site Google Cloud Data Labeling site Google Translation site] Dealing with CS:GO Free to Play and Addressing Toxicity in Matches blog Revealing Minerva and addressing toxicity and abusive behaviour in matches blog One of Europe’s Largest Gaming Platforms is Tackling Toxicity with Machine Learning blog FACEIT And Google Partner To Use AI To Tackle In Game Toxicity article FACEIT implement Minerva, an AI to punish toxicity in CSGO blog FACEIT Takes On Toxicity With Machine Learning article Exploring Cyberbullying and Other Toxic Behavior in Team Competition Online Games whitepaper Toxic Behavior in Online Games whitepaper A Look at Gaming Culture and Gaming Related Problems: From a Gamer’s Perspective whitepaper An Analysis of (Bad) Behavior in Online Video Games whitepaper Toxicity detection in multiplayer online games whitepaper Jon’s gaming info steam BattleNet: Syntax#11906 Question of the week When I SSH into my VM via different methods (Cloud Console, GCloud, terminal/command prompt) I get a different name… What can I do to make that static? OS Where can you find us next? FACEIT will be at Next London and GDC Brian will be at Super Computing in Denver. Jon will be at AnimeNYC, Kubecon in November and Google Kirkland and Montreal in December.

We’re sad to say goodbye to Mark Mandel this week but excited to bring you an interview he and guest host Robert Martin did with Björn Lindberg of Massive Entertainment. The gaming studio is located in Sweden and owned by Ubisoft. Their most recent game, The Division 2, is a “looter shooter” game that was released in March. It can be played solo or s can be matched up to play with or against others. To keep the game running smoothly, Massive employs a micro-service architecture to divide and conquer the trials of creating and running such a large, intense game. The Division 2 was launched with Google Cloud, a process Björn says was a bit easier than launching on physical hardware. Autoscaling in the cloud has created a simpler, more trustworthy gaming process as well, and by connecting to data centers in multiple regions, they’re able to decrease latency. Björn Lindberg Björn Lindberg, to the best of my knowledge is working as On-Line technical director at Massive Entertainment a Ubisoft owned and operated game studio in Malmö Sweden. He does design and implementation of on-line backend systems for large AAA on-line games such as The Division series of games and World in Conflict. Interview Massive Entertainment site The Division 2 site Ubisoft site Terraform site Grafana site Compute Engine site Thank You Mark! Thank you Mark for everything you’ve done to make this podcast a success! We’ll miss you!

Gabi Ferrara and Jon Foust are back today and ed by fellow Googler Manuel Lima. In this episode, Manuel tells us all about data visualization, what it means, why it’s important, and the best ways to do it effectively. For Google and its mission, data visualization is especially necessary in faciliatating the accesibility of information. It “makes the invisible visible” because of the way it can decode meaningful data patterns. Working across multiple G products, Manuel and his team build advanced visualization models that go beyond graphs and bar charts to things like sophisticated time lines that aid in the progression from data to usable knowledge. They have also created guidelines for things like what kind of graphical language to use, what type of charts s might need, and more. These guidelines, originally used only internally, have now been adjusted and released for use by developers outside Google with the help of the Material.io team. The guidelines are based around the six data visualazation prinles that help s get started. They can be employed to plan and inspire an entire project or to evaluate a specific data visualation chart. Some of the most important principles are to be honest and to lend a helping hand. You can read more in their Medium article, Six Principles for Deg Any Chart. Manuel Lima A Fellow of the Royal Society of Arts and nominated by Creativity magazine as “one of the 50 most creative and influential minds of 2009,” Manuel Lima is the founder of VisualComplexity.com, Design Lead at Google, and a regular teacher of data visualization at Parsons School of Design. Manuel is a leading voice on information visualization and has spoken at numerous conferences, universities, and festivals around the world, including TED, Lift, OFFF, Eyeo, Ars Electronica, IxDA Interaction, Harvard, Yale, MIT, Columbia, the Royal College of Art, NYU Tisch School of the Arts, ENSAD Paris, the University of Amsterdam, and MediaLab-Prado Madrid. He has also been featured in various publications and media outlets, such as Wired, the New York Times, Science, Nature, Businessweek, Fast Company, Forbes, The Guardian, BBC, CNN, Design Observer, Creative Review, Eye, Grafik, étapes, and El País. His first book, Visual Complexity: Mapping Patterns of Information, has been translated into French, Chinese, and Japanese. His latest, The Book of Circles: Visualizing Spheres of Knowledge, covers 1,000 hundred years of humanity’s long-lasting obsession with all things circular. With more than twelve years of experience deg digital products, Manuel has worked for Codecademy, Microsoft, Nokia, R/GA, and Kontrapunkt. He holds a BFA in Industrial Design and a MFA in Design & Technology from Parsons School of Design. During the course of his MFA program, Manuel worked for Siemens Corporate Research Center, the American Museum of Moving Image, and Parsons Institute for Information Mapping in research projects for the National Geospatial-Intelligence Agency. Cool things of the week Compute Engine or Kubernetes Engine? New trainings teach you the basics of architecting on Google Cloud blog Stadia comes next month site Google Cloud named a Leader in the 2019 Gartner Magic Quadrant for Full Life Cycle API Management for the fourth consecutive time blog Google Hardware Event Pixel 4 is here to help blog Meet the new Google Pixel Buds blog Nest Mini brings twice the bass and an upgraded Assistant blog More affordable and portable: let’s Pixelbook Go bterview Material.io site Data Visualization Guides site Six Principles for Deg Any Chart article Google’s six rules for great data design article BigQuery site Stackdriver site Google Analytics site Question of the week What are the most common products used in cloud gaming? Cloud Spanner for storing player authentication and inventory or long-term state storage site Redis is used in Open Match VM’s have been the most commonly used product for game servers but there has been a shift to Kubernetes Pub/Sub Where can you find us next? Gabi will be at Full Stack Europe. Jon will be at Kubecon in November to run a workshop on Open Match. Sound Effect Attribution “Small Group Laugh 6” by Tim.Kahn of Freesound.org “Jingle Romantic” by Jay_You of Freesound.org

Today on the podcast, Gabi Ferrara and Jon Foust share a great interview with Laura Ham, Community Solution Engineer at SeMI Technologies. At SeMI Technologies, Laura works with their project Weaviate, an open-source knowledge graph program that allows s to do a contextualized search based on inputted data. However, unlike traditional databases, Weaviate attaches meanings and links within the data. Laura details what knowledge graphs are and how they can be useful for both small and large projects. Explaining that ontology is the meaning of words, she tells us how Weaviate is able to use this concept to make more specific data entries and links, allowing s to perform better and more informative searches. Weaviate is able to do this with the help of Kubernetes. Later, Laura tells Gabi and Jon the ways Weaviate helps developers and s with thorough documentation, assistance with troubleshooting, and from solution engineers. Laura Ham Laura is the Community Solution Engineer at SeMI Technologies, where she takes care of building and ing a community around their open source software product, Weaviate. She also takes care of the developer and experience within the business, which means she writes documentation to both developers and s, as well as researches and evaluates new software implementations on experience. She has a -centered approach in the work that she develops and designs. Laura is a full-time graduate student in Human Computer Interaction and Design with a special focus on Innovation and Entrepreneurship at EIT Digital Master School. Here, she learns about how to develop and design technology from a perspective, and how to apply this with an entrepreneurial mindset. Cool things of the week Use G Suite to make documents (and other tools) more accessible to people with disabilities blog 4 steps to stop data exfiltration with Google Cloud blog Using Colab to get more out of BigQuery blog Updates to AutoML Vision Edge, Auto ML Video, & AutoML Intelligence API bterview SeMI Technologies site Weaviate site Weaviate GitHub github Weaviate documentation site GraphQL API github Kubernetes site GKE site Cloud BigTable site SeMI Technologies Meetups site Question of the week When will Python 2 reach the end of its life, and what does that mean for G? Python Google Cloud Client Libraries only Python 3 github Countdown to end of life site Where can you find us next? Gabi will be at Full Stack Europe. Jon will be at his twin’s wedding! Then Kubecon in November to run a workshop on Open Match. SeMI Technologies will be hosting meetups in NYC on October 24th, the Bay Area on October 25th, and Amsterdam on November 7th. Sound Effect Attribution “Small Group Laugh 6” by Tim.Kahn of Freesound.org “Small Group Laugh 2” by Tim.Kahn of Freesound.org “02 Storm Orage” by ArnaudCoutancier of Freesound.org “Harry Potter Theme”, a clunky midi file rendition of music originally composed by John Williams. Purchase the soundtrack on Amazon

Our guests Matthew Tamsett and Ravi Upreti Gabi Ferrara and Aja Hammerly to talk about data science and their project, Qubit. Qubit helps web companies by measuring different experiences, analyzing that information, and using it to improve the website. They also use the collected data along with ML to predict things, such as which products s will prefer, in order to provide a customized website experience. Matthew talks a little about his time at CERN and his transition from working in academia to industry. It’s actually fairly common for physicists to branch out into data science and high performance computing, Matthew explains. Later, Ravi and Matthew talk G shop with us, explaining how they moved Qubit to G and why. Using PubSub, BigQuery, and BigQuery ML, they can provide their customers with real-time solutions, which allows for more reactive personalization. Data can be analyzed and updates can be created and pushed much faster with G. Autoscaling and cloud management services provided by G have given the data scientists at Qubit back their sleep! Matthew Tamsett Matthew was trained in experimental particle physics at Royal Holloway University of London, and did his Ph.D. on the use of leptonic triggers for the detection of super symmetric signals at the ATLAS detector at CERN. Following this, he completed three post doctoral positions at CERN and on the neutrino experiment NOvA at Louisiana Tech University, Brookhaven National Laboratory, New York, and the University of Sussex UK, culminating in a EU Marie Curie fellowship. During this time, Matt co-authored many papers including playing a minor part in the discovery of the Higgs Boson. Since leaving academia in 2016, he’s worked at Qubit as a data scientist and later as lead data scientist where he lead a team working to improve the online shopping experience via the use of personalization, statistics and predictive modeling. Ravi Upreti Ravi has been working with Qubit for almost 4 years now and leads the platform engineering team there. He learned distributed computing, parallel algorithms and extreme computing at Edinburgh University. His four year stint at Ocado helped developed a strong domain knowledge for e-commerce, along with deep technical knowledge. Now it has all come together, as he gets to apply all these learnings to Qubit, at scale. Cool things of the week A developer goes to a DevOps conference blog Cloud Build brings advanced CI/CD capabilities to GitHub blog Cloud Build called out in Forrester Wave twitter 6 strategies for scaling your serverless applications bterview Qubit site Qubit Blog blog Pub/Sub site BigQuery site BigQuery ML site Cloud Datastore site Cloud Memorystore site Cloud Bigtable site Cloud SQL site Cloud AutoML site Goodbye Hadoop. Building a streaming data processing pipeline on Google Cloud blog Question of the week How do you deploy a Windows container on GKE? Where can you find us next? Gabi will be at the Google Cloud Summit in Sao Paulo, Brazil. Aja will be at Cloud Next London. Sound Effect Attribution “Small Group Laugh 6” by Tim.Kahn of Freesound.org

Mark Mandel and Jon Foust return this week to host Jesse Houston, CEO of Phoenix Labs. Jesse goes into detail about their online, multiplayer game Dauntless, a hunting action game that brings friends together from every platform to fight giant monsters. s can even switch platforms, say from Xbox to Playstation, and pick up right where they left off. Later in the show, Jesse describes the hurdles of building such a huge game and how Phoenix Labs overcame them. Late nights and holiday hours helped them create “no downtime deploys”, so s can continue to play even as the game updates. Because big projects sometimes come with big problems, Jesse also emphasized the importance of developing crisis management skills to help get through tough times. We talk more specifically about what it takes to build and run Dauntless, from G products such as GKE, Bigtable, and BigQuery, to tricks with scaling and management. In the future, Dauntless will be available on the Switch, new expansions will be released, and more. Jesse Houston Jesse Houston is a games industry veteran with over 18 years experience in the gaming space. Houston fell in love with games at an early age and found his footing in the games industry by applying to a QA position in a local paper. Previously, Houston has held lead producer roles at both Riot Games on League of Legends, and BioWare on the Mass Effect series. He also served as Production Director at Ubisoft, overseeing Technical Project Management, Pipeline Planning, Development and Design, among other responsibilities. Houston formed Phoenix Labs with Sean Bender and Robin Mayne to create deep multiplayer games that bring players together. Cool things of the week Virtual display devices for Compute Engine are now GA blog Container-native load balancing on GKE are now GA blog How to deploy a Windows container on Google Compute Engine blog Agones 1.0 site Interview Phoenix Labs site Dauntless site Dauntless Updates site Dauntless on Twitter twitter Cloud Bigtable site Kubernetes site BigQuery site GKE site Redis site Introducing Google Customer Reliability Engineering blog Cloud SQL site Question of the week What is the difference between vs Standard network? Where can you find us next? Jesse will be speaking at the Montreal International Game Summit. You can see Phoenix Labs at many other gaming conferences, including Pax, TwitchCon, and GDC. Mark is taking some vacation time, then he’ll be at Kubecon. Jon will also be at Kubecon, as well as taking some personal time to attend several weddings. Sound Effect Attribution “Fantasy Orchestra” by BigManJoe of Freesound.org

Conversational AI is our topic this week as your hosts Mark Mirchandani and Priyanka Vergadia are ed by Cathy Pearl and Jessica Dene Earley-Cha. Cathy explains what conversation AI is, describing it as people teaching computers to communicate the way humans do, rather than forcing humans to communicate like computers. Later, we talk best practices in design and development, including how a good conversation design and sample dialogues before building can create a better product. This prep work helps anticipate the ways different s could respond to the same question and how the program should react. In multi-modal programming, planning is also important. Our guests suggest starting with the spoken portions of the design and then planning visual components that would augment the experience. Working together as a team is one of the most important parts of the planning process. We also talk best use-cases for conversation AI. Does performing this task via voice make the experience better? Does it make the task easier or more accessible? If so, that could be a great application. In the future, the conversation may be a silent communication with the help of MIT’s Alter Ego. Cathy Pearl Cathy Pearl is head of conversation design outreach and author of the O’Reilly book, “Deg Voice Interfaces”. She’s been creating Voice Interfaces for 20 years and has worked on everything from programming NASA helicopter pilot simulators to a conversational app in which Esquire’s style columnist advises what to wear on a first date. She earned an MS in Computer Science from Indiana University and a BS in Cognitive Science from UC San Diego. You can find Cathy on Twitter, or check out her latest Medium article “A Conversation With My 35-year-old Chatbot”. Jessica Dene Earley-Cha Jessica Dene Earley-Cha is a Developer Advocate for Actions on Google. She loves to connect with developers and explore VUI (voice interface) to add another dimension to how s interact with technology. Jessica is part of the leadership team for @WomenInVoice. You’ll find her either spending time with her dog, collecting strawberry knick knack or biking around town. Stay up-to-date on her ventures on Twitter. Cool things of the week How Google and Mayo Clinic will transform the future of healthcare blog Announcing the general availability of 6 and 12 TB VMs for SAP HANA instances on Google Cloud Platform blog Understanding your G Costs site and videos Coupon code for qwiklabs is: 1q-costs-626 Interview G Podcast Episode 188: Conversation AI with Priyanka Vergadia podcast Google’s Conversation Design Best Practices site Actions on Google site Interactive Canvas docs Dialogflow site Deconstructing Chatbots videos Behind the Actions videos Assistant On Air videos MIT’s Alter Ego site Google Developers on Medium site Actions Codelabs site Actions Code Samples site Actions on Google Twitter site Google Assistant Dev on Reddit site Cathy’s Book: Deg Voice Interfaces site How We Talk: The Inner Workings of Conversation site Talk: The Science of Conversation site Question of the week How to integrate Dialogflow with BigQuery Where can you find us next? Cathy will be at Project Voice. Mark will be on vacation soon! Priyanka will be at GOTO Berlin, Codemotion Milan, and GOTO Copenhagen

On the podcast this week, we have a great interview with Google Developer Advocate, Dale Markowitz. Aja Hammerly and Jon Foust are your hosts, as we talk about machine learning, its best use cases, and how developers can break into machine learning and data science. Dale talks about natural language processing as well, explaining that it’s basically the intersection of machine learning and text processing. It can be used for anything from aggregating and sorting Twitter posts about your company to sentiment analysis. For developers looking to enter the machine learning space, Dale suggests starting with non life-threatening applications, such as labeling pictures. Next, consider the possible mistakes the application can make ahead of time to help mitigate issues. To help prevent the introduction of bias into the model, Dale suggests introducing it to as many different types of project-appropriate data sets as possible. It’s also important to continually monitor your model. Later in the show, we talk Google shop, learning about all the new features in Google Translate and AutoML. Dale Markowitz Dale Markowitz is an Applied AI Engineer and Developer Advocate for ML on Google Cloud. Before that she was a software engineer in Google Research and an engineer at the online dating site OkCupid. Cool things of the week Build a dev workflow with Cloud Code on a Pixelbook blog Feminism & Agile blog New homepage and improved collaboration features for AI Hub bterview TensorFlow site Natural Language API site AutoML Natural Language site Content Classification site Sentiment Analysis site Analyzing Entities site Translation API site AutoML Translate site Google Translate Glossary Documentation docs Google News Lab site AI Platform’s Data Labeling Service docs Question of the week How many different ways can you run a container on G? GKE Cloud Run App Engine Flexible Environmnet Compute Engine VM as a computer Where can you find us next? Dale will be at DevFest Minneapolis, DevFest Madison, and London NEXT. Jon will be at the internal Google Game Summit and visiting Montreal. Aja will be holding down the fort at home. Sound Effect Attribution “Mystery Peak2” by FoolBoyMedia of Freesound.org “Collect Point 00” by LittleRobotSoundFactory of Freesound.org “Cinematic Piano” by Ellary of Freesound.org

Michelle Casbon is back in the host seat with Mark Mirchandani this week as we talk data science with Devoted Health Director of Data Science, Chris Albon. Chris talks with us about what it takes to be a data scientist at Devoted Health and how Devoted Health and machine learning are advancing the healthcare field. Later, Chris talks about the future of Devoted Health and how they plan to grow. They’re hiring! At Devoted Health, they emphasize knowledge, ing a culture of not just machine learning but people learning as well. Questions are encouraged and assumptions are discouraged in a field where a tiny mistake can change the care a person receives. Because of this, their team not only have a strong data science background, they also learn the specific nuances of the healthcare system in America, combined with knowledge of the legal and privacy regulations in that space. How did Chris go from Political Science Ph.D. to non-profit data science wizard? Listen in to find out his storied past. Chris Albon Chris Albon is the Director of Data Science at Devoted Health, using data science and machine learning to help fix America’s health care system. Previously, he was Chief Data Scientist at the Kenyan startup BRCK, cofounded the anti-fake news company New Knowledge, created the data science podcast Partially Derivative, led the data team at the humanitarian non-profit Ushahidi’s, and was the director of the low-resource technology governance project at FrontlineSMS. Chris also wrote Machine Learning For Python Cookbook (O’Reilly 2018) and created Machine Learning Flashcards. He earned a Ph.D. in Political Science from the University of California, Davis researching the quantitative impact of civil wars on health care systems. Chris earned a B.A. from the University of Miami, where he triple majored in political science, international studies, and religious studies. Cool things of the week How Itaú Unibanco built a CI/CD pipeline for ML using Kubeflow blog Why TPUs are so high-performance BFloat16: The secret to high performance on Cloud TPUs blog TPU Codelabs site Benchmarking TPU, GPU, and U Platforms for Deep Learning paper Machine Learning Flashcards site Interview Devoted Health site Devoted Health is hiring! site Ushahidi site FrontlineSMS site New Knowledge site Joel Grus: Fizz Buzz in TensorFlow site Snowflake site Periscope Data site Airflow site Kubernetes site Chris Albon’s Website site Partially Derivative podcast Partially Derivative Back Episodes podcast Question of the week Chris Albon To paraphrase: A computer program is said to learn if its performance at specific tasks improves with experience. To find out more, including the definition of a partial derivative, buy a pack of Chris’s flashcards. Who knows, they might help you land your next job. Where can you find us next? Michelle is planning the ML for Developers track for QCon SF on Nov. 13. Mark is staying in San Francisco and just launched two Beyond Your Bill videos: Organizing your G resources and Managing billing permissions. Sound Effect Attribution “Small Group Laugh 5” by Tim.Kahn of Freesound.org “Crowd Laugh” by Tom_Woysky of Freesound.org “Transformers Type SFX 2” by HykenFreak of Freesound.org “Approx 800 Laugh” by LoneMonk of Freesound.org “Bad Beep” by RicherLandTV of Freesound.org “C-ClassicalSuspense” by DuckSingle of Freesound.org

Google’s own Billy Jacobson s hosts Mark Mandel and Mark Mirchandani this week to dive deeper into Cloud Bigtable. Bigtable is Google’s petabyte scale, fully managed, NoSQL database. Billy elaborates on what projects Bigtable works best with, like time-series data analytics, and why it’s such a great tool. It offers huge scalability with the benefits of a managed system, and it’s flexible and easily customized so s can turn on and off the pieces they need. Later, we learn about other programs that are compatible with Bigtable, such as JanusGraph, Open TSDB, and GeoMesa. Bigtable also s the API for HBase, an open-source project similar to Bigtable. Because of this, it’s easy for HBase s to move to Bigtable, and the Bigtable community has access to many open source libraries. Billy also talks more about the nine clients available, and when customers might want to use Bigtable instead of, or in conjunction with, other Google services such as Spanner and BigQuery. Billy Jacobson Billy Jacobson is a developer programs engineer focusing on Cloud Bigtable. Cool things of the week Introducing Cloud Run Button: Click-to-deploy your git repos to Google Cloud blog Firebase Unity Solutions: Update game behavior without deploying with Remote Config btroducing the BigQuery Terraform module blog Macy’s uses Google Cloud to streamline retail operations bterview Cloud Bigtable site G Podcast Episode 18: Bigtable with Ian Lewis podcast BigQuery site Bigtable Documentation docs Codelab: Introduction to Cloud Bigtable site Key Visualizer docs Bigtable Replication Documentation docs Bigtable and HBase Documentation docs HBase site JanusGraph site Open TSDB site GeoMesa site Bigtable Client Libraries docs Cloud Spanner site Managing IoT Storage with Google’s Cloud Platform (Google I/O’19) video Cloud Datastore site Cloud Firestore site Mapping the invisible: Street View cars add air pollution sensors site Breathing Easy with Bigtable article Question of the week If I have an organization, how do I break down my billing data by folder? Where can you find us next? Mark Mirch is working around town but will be headed to LA soon. Mark Mandel will be at Pax Dev, Pax West, Kubecon, and the GDC Online Games Technology Summit.

Mark Mirchandani is back this week with guest host Gabe Weiss to learn about HerdX. Our guests, Ron Hicks and Austin Adams, describe how this idea came about, the mechanics of the system, and how it could change the world of livestock. HerdX is an environmentally friendly, humane way to improve the system of livestock management and sales. It uses monitoring systems to follow animals as they move about the field, then employs algorithms to identify any problems that may need attention. This allows for treatment of specific animals, rather than mass treatment of both healthy and unhealthy livestock. When pitted against humans, HerdX’s AI system could pinpoint the problem livestock much faster and more accurately than people. Once problem livestock are found, the rancher can use that information to devise and implement a treatment plan. Consumers benefit from HerdX as well, through better quality meat and better transparency of rancher practices. The players in the supply chain are recorded and meat is monitored through the entire process, from farm, to feed lot, to the dinner table. Because bad animals can be removed or cured and the supply chain is run much more efficiently, meat spoilage and food poisoning can be mitigated. Ron Hicks As the CEO & Founder of HerdX, Inc., a global AgTech company based in the Texas Hill Country, Ron is filling the void in ag data with IoT devices designed for livestock herds. In a nutshell, HerdX is using tags, water, and data to connect farmers around the world with families around the dinner table. Before his time with HerdX, Ron had a number of immensely successful career paths and achievements as a serial entrepreneur, inventor, and a strong visionary who loves disruptive technologies that can change the world. He was distinguished with Business Week’s top industrial design award in Medical Technologies, which recognized him along with other leaders and companies throughout the world, including BMW, Sony, Logitech, and Ford Motor Company. Ron is also a dynamic speaker who is ionate about solving problems rather than just talking about them and has spoken at conferences as a keynote speaker at Google headquarters in the United States and Singapore. He was also the keynote speaker at Texas Governor Rick Perry’s program titled “Technology Excellence for Rural America” which served as a springboard for the formation of HerdX. Austin Adams Austin Adams holds over a decade of experience in leading innovative software teams. At his previous employer Adams took multiple greenfield projects from initial scoping, to research and development, to proof of concept, and ultimately to market-leading products. Adams is an early adopter, leader, and contributor to the Kubernetes open source platform. He has used Kubernetes to create automation systems to help drive more than a billion dollars of product sales. Cool things of the week Press play: Find and listen to podcast episodes on Search blog Japanese researchers build robotic tail to keep elderly upright site Shining a light on your costs: New billing features from Google Cloud bterview HerdX site New Zealand Innovator of the Year Awards site Question of the week How do I connect an IoT device to a trigger event in the cloud? Cloud IoT step-by-step: Cloud to device communication blog Cloud IoT Core site Gabe’s blog blog Where can you find us next? Mark will be hanging out locally and working on training content. Gabe will be at Next London. Sound Effect Attribution “radio t3 SW bleep.wav” by ERH of Freesound.org

On the show today, we speak with Developer Advocate and fellow Googler, Sherol Chen about machine learning and AI. Jon Foust and Aja Hammerly learn about the history and impact of AI and ML on technology and gaming. What does it mean to be human? What can machines do better than humans, and what can humans do better than machines? These are the large questions that we aim to solve in order to understand and use AI. Sherol goes on to explain the types of deep learning machines can achieve, from neural networks to decision trees. Sherol also went into depth about the potential social impact of AI as it assists doctors parsing through medical records and plans agricultural endeavors to maximize food production and safety. Sherol also elaborates on the ethical responsibilities we must realize when developing AI projects. For developers looking to build a new AI project, Sherol outlines the pros and cons of using existing tools like Cloud Speech-to-Text, AutoML and AutoML Tables. Sherol Chen Sherol advocates for Machine Learning for Google Cloud, and works in Research at Google Brain for Machine Learning in Music and Creativity for the Magenta team. She’s taught Artificial Intelligence at Stanford and around the world in six different countries. Her PhD work is in Computer Science, researching storytelling and Artificial Intelligence at the Expressive Intelligence Studio. Cool things of the week AMD EPYC processors come to Google—and to Google Cloud blog Kaggle Petfinder Dataset site Streaming data from Cloud Storage into BigQuery using Cloud Functions blog App Engine Standard Ruby site Thagomizer bterview AutoML Tables site AutoML Tables Promo Video video Can Machines Think? article AI Impact Challenge site NeurIPS site ICLR site ICML site Machine Learning Crash Course site TensorFlow site Project Magenta site Cloud Speech-to-Text site Cloud AutoML site Sherol’s Blog blog Question of the week You mentioned that you can run App Engine + Rails, how do you handle migrations? Where can you find us next? Jon will be at PAX Dev and PAX West, the internal game summit at Google in Sunnyvale, and taking some personal time to travel to Montreal. Aja will be hanging around at home, on the internet, and at Seattle.rb. Sound Effect Attribution “Coins 1.wav” by ProjectsU012 of Freesound.org “Wedding Bells.wav” by Maurice_J_K of Freesound.org “Small Group Laugh.wav” by Tim.Kahn of Freesound.org

Jon Foust s Mark Mirchandani this week as we meet up with Alim Karim from NetApp and Technical Director in OCTO Dean Hildebrand of Google. NetApp has been in data management for 20 years, focusing on providing on-prem, high-performance storage solutions for large industry clients. Their recent partnership with Google Cloud has allowed them to expand their services, offering the same great data management and storage in the cloud. Dean and Alim elaborate on the best uses for NetApp, explaining that lifting and shifting an existing project to the cloud is only one way NetApp can be useful. New projects can be built right in Google Cloud with NetApp as well. Our guests discuss the other pros of the NetApp service, including faster data retrieval, better monitoring, and predictability. We also talk about how NetApp takes customer into consideration to make sure their service is the best it can be for every client. What’s in store for the future of NetApp? Listen in to find out! Alim Karim Alim Karim is a Product Manager in the Cloud Data Services BU at NetApp. He started his career as a software developer and ed NetApp in 2011. At NetApp Alim has held several customer-facing positions and is ionate about solving business problems with technology. He holds an undergraduate degree in Computer Science and an MBA from Queen’s University. Dean Hildebrand Dean Hildebrand is a Technical Director in the Office of the CTO (OCTO) at Google Cloud focusing on enterprise and HPC storage systems. He has authored over 100 scientific publications and patents, and been the technical program chair and sat on the program committee of numerous conferences. He received a B.Sc. degree in computer science from the University of British Columbia in 1998 and M.S. and PhD. degrees in computer science from the University of Michigan in 2003 and 2007, respectively. Cool things of the week Google Cloud Game Servers site VMware Cloud Foundation comes to Google Cloud blog Using G NuGet Packages in Unity article Interview NetApp on Google Cloud site Cloud Volumes Service site BigQuery site TensorFlow site Google Cloud Storage site Anthos site Question of the week How do I authenticate my Google Kubernetes Engine cluster in a CI/CD pipeline? Where can you find us next? Our guests will be at Google Cloud Summit Seattle and Next London. Jon will be at PAX Dev, doing some Google Game stuff in Sunnyvale, and taking some personal time to travel to Montreal. After Austin, Mark will be staying local to work on some stuff, and he’s about to launch the next few episodes of Stack Doctor. Sound Effect Attribution “Small Audience Laughs.wav” by Oniwe of Freesound.org “MysteryPeak1.wav” by FoolBoyMedia of Freesound.org “Small Group Laugh.wav” by TimKahn of Freesound.org

The podcast today is all about conversational AI and Dialogflow with our Google guest, Priyanka Vergadia. Priyanka explains to Mark Mirchandani and Brian Dorsey that conversational AI includes anything with a conversational component, such as chatbots, in anything from apps, to websites, to messenger programs. If it uses natural language understanding and processing to help humans and machines communicate, it can be classified as conversational AI. These programs work as translators so humans and computers can chat seamlessly. We discuss how people interact with conversational AI, maybe without even realizing it. From asking Google Home to set your alarm to getting customer service at your favorite online store, AI is probably working behind the scenes to help. Priyanka also tells us all about Google’s natural language understanding and processing program, Dialogflow. Designed to simplify the process, Dialogflow allows you to input a simple idea like asking for coffee, and watch as the program automatically includes many of the different ways people would naturally ask for coffee. Coffee would be great right now! Listen in to find out the best (and worst) use cases and practices for this powerful tool! Priyanka Vergadia Priyanka Vergadia is a Developer Advocate at Google. She worked directly with customers for 1.5 years prior to recently ing Google Cloud Developer Relations team. She loves architecting cloud solutions and enjoys building conversational experiences. Her interest in Conversational AI led to the Deconstructing Chatbots YouTube series. Priyanka is currently starring in a new show called “Get Cooking in Cloud” where she will be sharing recipes to cook various business solutions on Google Cloud. Cool things of the week Least privilege for Cloud Functions using Cloud IAM blog Brick by brick: Learn G by setting up a kid-controllable Minecraft server blog Containerizing in the real world … of Minecraft btroducing the What-If Tool for Cloud AI Platform models bterview Chatbot Fail site Dialogflow site and docs Deconstructing Chatbots videos Codelab: Build your first Chatbot with Dialogflow site Question of the week How do you run a recurring python script? Where can you find us next? Priyanka will be at Codemotion Milan in October and GOTO Copenhagen in November. Brian will be at the office in Seattle, thinking about Compute Engine. Mark will be in Austin and the Bay Area working on new training content! Sound Effect Attribution “Small Group Laugh Set.wav” by Tim Kahn of Freesound.org “Whip Crack 01.wav” by CGEffex of Freesound.org

Jon Foust and Mark Mirchandani are ed by Adé Mochtar to discuss the IT learning platform, Instruqt and how they create and manage the platform with the help of Google Cloud. Sandeep of Google stops in with the info on the Instruqt arcade games we saw at Google Next ‘19. Instruqt’s main philosophy is that people learn best by doing, and their courses encourage immersion right off the bat. Developers are asked coding questions and allowed to work in sandbox environments to fully expose them to the subject. Instruqt checks the student’s work as they continue through the program to ensure the material is being properly learned. But learning should be fun, too! By putting developer challenges on old-style arcade machines, developers can test their coding skills, learn new things, and have fun at the same time. At conferences, this has been a great way to engage their target audience. Google Cloud games were run on the Instruqt platform at Next ‘19, and conference attendees came back day after day to try to get on the high score leaderboard. It was a super fun way to get people using Google Cloud technologies! Adé Mochtar Adé is Co-Founder and CTO of Instruqt, a hands-on learning platform for IT technology. Before starting Instruqt, he was an engineer and consultant in Cloud and DevOps-related topics. A big part of that job was to educate organizations on how to adopt new technology. With Instruqt, he tries to achieve the same but on a larger scale. His mission is to make learning DevOps and Cloud more effective and fun. At Instruqt, Adé mainly focuses on back-end and infrastructure engineering using Terraform, Go, and (probably too much) Bash. Cool things of the week Step up your interviewing game with Byteboard blog Gartner names Google Cloud a leader in its IaaS Magic Quadrant blog Real-time bikeshare information in Google Maps rolls out to 24 cities blog Run Visual Studio Code in Cloud Shell bterview Instruqt site Instruqt on Slack site Kubernetes site Cloud Functions site Hashi Corp site Instruqt Arcade at Next ‘19 video Google Developer Advocate - Sandeep Dinesh on Instruqt video Go site React site Terraform site GKE site Cloud SQL site Cloud Build site Firebase site Question of the week I want to be more familiar with Google Cloud, how do I navigate the space for material? Learn more with Qwiklabs and Coursera. Get Certified. Where can you find us next? Instruqt arcade games will be at GopherCon and Cloud Summits! Jon will be speaking at Pax Dev and Pax West. Mark will be hanging on the East Coast, then meeting with customers in Austin. Sound Effect Attribution “Red Arrows Flyby.wav” by Figowitz of Freesound.org “crowd laugh.wav” by Tom_Woysky of Freesound.org “Alien_Scream.wav” by Syna-Max of Freesound.org “Laser Gun7.wav” by Burkay of Freesound.org “Scratch2.mp3” by Feveran of Freesound.org “BumbleBeeShort.mp3” by CGEffex of Freesound.org “ComedyRimshot.wav” by XTRgamr of Freesound.org

Blockchain takes the spotlight as new host Carter Morgan s veteran Mark Mandel in a fascinating interview with Allen Day. Allen is a developer advocate with Google, specializing in streaming analytics for blockchain, biomedical, and agricultural applications. This week Allen reveals how blockchain and cryptocurrencies can be applied to a variety of applications like distributed file storage and video services. We also discuss the hype and merits of blockchain + projects that Allen has worked on to analyze cryptocurrency transactions using Google Cloud’s big data platforms. The results may just surprise you. Allen Day Allen Day is a developer advocate with Google in Singapore. He specializes in streaming analytics for blockchain, biomedical, and agricultural applications. Allen studied at the UCLA Geffen School of Medicine and earned his PhD in Human Genetics. Allen’s blockchain work is focused on interoperability between smart contract platforms and cloud platforms. He created Google Cloud’s blockchain public datasets program, which allows non-specialist engineers and data scientists to search and analyze public blockchain data. Cool things of the week Blockchain.com, scaling and saving with Cloud Spanner blog Cloud TPU Pods break AI training records blog Cloud Memorystore adds import-export and Redis 4.0 blog To run or not to run a database on Kubernetes: What to consider blog Google to acquire Elastifile bterview Blockchain site Bitcoin site Coinbase site Ethereum site $24 million iced tea company says it’s pivoting to the blockchain, and its stock jumps 200% news article Blockchain ETL project on GitHub site BigQuery site Kubernetes site Cloud Composer site Pub/Sub site Bigtable site Tensorflow site Bitcoin in BigQuery: blockchain analytics on public data blog BigQuery public blockchain datasets on G site Ethereum in BigQuery: how we built this dataset blog Ethereum in BigQuery: a Public Dataset for smart contract analytics btroducing six new cryptocurrencies in BigQuery Public Datasets—and how to analyze them blog Building hybrid blockchain/cloud applications with Ethereum and Google Cloud blog Bitcoin in BigQuery: blockchain analytics on public data blog Unchained Podcast podcast Off the Chain Podcast podcast Question of the week What are the four (or six?) types of VMs that exist on Google Cloud Platform? blog and docs Where can you find us next? Mark Mandel is going to Tokyo Next, Open Source in Gaming Day , and the North American Open Source Summit, as well as Pax Dev and Pax West. Carter will be at the Edinburgh Fringe Festival and working on new videos. Allen will be at Strike Two Summit (Amsterdam), Singularity Festival (Heraklion), and Ethereum Devcon (Osaka). Sound Effect Attribution “mysterypeak1.wav” by FoolBoyMedia of Freesound.org “crowd laugh.wav” by Tom_Woysky of Freesound.org

This week on the podcast, Yuri Litvinovich of Scotiabank was able to Mark Mirchandani and Michelle Casbon to talk about migration from on-prem and their partnership with Google Cloud. Mark Mandel stops in with some cool things of the week and the question of the week, too! With Yuri’s help, Scotiabank is working to become a modern financial services technology company. Their transition from working mostly on-prem to working in the cloud was exciting for him as he discovered how much cheaper, faster, and more secure large enterprise projects can be in the public cloud. Three years ago, Scotiabank’s CEO began encouraging this shift to keep the company up-to-date, with funds allocated to moving all their thousands of applications and products to a more efficient system. To accomplish this, Yuri turned to Kubernetes to make use of containers. Because they are light and homogenous in different environments, the modernization at Scotiabank went much more smoothly with Kubernetes and GKE. They also use a mix of managed systems like BigQuery, Dataflow, and Pub/Sub, as well as made-from-scratch applications that help the Google products to be compatible with Scotiabank’s existing software. Yuri believes this was a key to their success in the migration from on-prem to the cloud. In the process of migration, Yuri experienced some pushback from developers who were concerned about the move. He encouraged them not to “lift and shift” their projects, but to completely re-build them with cloud dev ops principles in mind. Yuri’s goal was to convince developers that doing this would result in projects that were much easier, cheaper, and more secure in the long run. By outlining the benefits and goals of migration and sharing success stories of other businesses who have transferred to Kubernetes and the cloud, Scotiabank was able to help convince developers of the importance of it. Yuri also encourages trust and cooperation between teams. Yuri Litvinovich Yuri is a Senior Cloud Engineer and Kubernetes Tech Lead at Scotiabank. He’s currently part of Platform Organization (PLATO) within Scotiabank, which performs enterprise modernization program to transform the Bank into a modern technology company in financial services. Yuri has extensive experience in Cloud technologies, Kubernetes, DevOps, Site Reliability Engineering, Automation, CI/CD, Linux, networking, and system istration. His pursuit of excellence led him to work on implementing cutting-edge technologies in both startups, and large enterprise environments making them vital part of organization’s digital transformation journey. Cool things of the week Introducing Deep Learning Containers: Consistent and portable environments blog How to implement document tagging with AutoML blog Analyze BigQuery data with Kaggle Kernels notebooks blog G Podcast Episode 84: Kaggle with Wendy Kan podcast Introducing the Jenkins GKE Plugin—deploy software to your Kubernetes clusters bterview Scotiabank site Kubernetes site Kubernetes Engine site Cloud SQL site BigQuery site Dataflow site Pub/Sub site Stackdriver site Anthos site GKE On-Prem site Istio site Autoscaling Streaming Applications in Cloud Dataflow with Scotiabank video Google Cloud Next ‘19: Day 2 Product Innovation Keynote video Kubeflow site Question of the week Rather than using the standard Cloud Shell image - what if I want to add my own “by default” installed tooling? Where can you find us next? Mark Mirch is working on This Week in Cloud. Mark Mandel is going to Tokyo Next, Open Source in Gaming Day , and the North American Open Source Summit. Sound Effect Attribution “crowd laugh.wav” by tom_woysky of Freesound.org

Happy Independence Day to our American listeners! Mark Mandel is back today as he and Gabi Ferrara interview Bill Creekbaum of Informatica to learn how they work with Google Cloud for a better big data experience. Mark Mirchandani is hanging around the studio as well, bringing some cool things of the week and helping with the question of the week! Informatica provides data managing products that offer complete solutions focusing on metadata management, integration, governance, security, data quality, and discoverability. Bill’s job at Informatica is to ensure these products really take advantage of the strengths of Google Cloud Platform. One such example is a product that allows customers to design in Informatica and push their projects to Cloud Dataproc. Informatica also offers similar capabilities in BigQuery. When moving data from on-prem to the cloud, customers can use Informatica and Google Cloud together for a seamless transition, cost savings, and easier data control. Together, Informatica and Google Cloud can also facilitate the acquisition of high quality data. To have better, more trustworthy output, data inputed needs to be safe to access, have few or no duplicates and null values, and be complete. To achieve this, developers usually use a combination of the Informatica tools Intelligent Cloud Services, Enterprise Data Catalog, and Big Data Management, and the Google tools BigQuery, Cloud Storage, Analytics, Dataproc, and Pub/Sub. Bill’s closing advice for companies comes in three parts: take stock of the data you’ve got, set goals, and develop a well-rounded team. Bill Creekbaum Bill Creekbaum is Sr. Director of Product Management for Cloud, Big Data, and Analytic Ecosystems at Informatica. He is focused on delivering market leading unified data management platforms and services that help customers take advantage of their greatest assets, data. Bill has been in product management and product marketing for more than 20 years and for the past 10 has been focused on successfully delivering SaaS and Cloud Applications to the market. Prior to ing Informatica, Bill has worked at SnapLogic, GoodData, Oracle, Microsoft, Mindjet, and more. See more of Bill’s experience on LinkedIn. Cool things of the week Google Cloud + Chronicle: The security moonshot s Google Cloud blog G Podcast Episode 135: VirusTotal with Emi Martinez podcast Introducing Equiano, a subsea cable from Portugal to South Africa blog Kubernetes 1.15: Extensibility and Continuous Improvement blog Future of CRDs: Structural Schemas blog See how your code actually executes with Stackdriver Profiler, now GA bterview Informatica site Informatica for G site BigQuery site Cloud Storage site Cloud Dataproc site Intelligent Cloud Services site Enterprise Data Catalog site Big Data Management site Google Analytics site Pub/Sub site Google Cloud & Informatica: Accelerate your Data-Driven Digital Transformation webinar Informatica for Google BigQuery data sheet Informatica Intelligent Cloud Services for Google BigQuery site Question of the week If I want to have my App Engine Application serve any subdomain on my custom domain, how do I do that? Where can you find us next? Gabi is done traveling. Mark Mirch’ is working on Stack Chat. Mark Mandel is going to Tokyo Next, Open Source in Gaming Day , and the North American Open Source Summit. Sound Effect Attribution “small group laugh 6.flac” by tim.kahn of Freesound.org “Chewing, Carrot, A” by Inspector J of Freesound.org “Testtone1000hz” by Jobro of Freesound.org

On this episode, our hosts Mark Mirchandani and Gabi Ferrara dive into Google Cloud Platform UX with guest and Google Product Designer Michael Kleinerman. Michael’s path to Product Designer started with “ancient” tech deg with Flash and 3D motion graphics and progressed from there through interaction designer to his place now with Google. His experience has helped him appreciate the many different kinds of designers needed for projects and how they have to work together for a good product. At Google, Michael’s team builds design systems that create a balance between what Google uses and what the products built on Google use. He adopted Material Design, which offers guidelines for patterns and components of design, to Google Cloud. Material Design spans across multiple devices and screen sizes to help simplify design across devices. When Cloud reached the enterprise space, where components can be more complex, Michael’s team worked to adjust Cloud using Material Design so that features like tables would work correctly. Accessibility is also a top priority for Cloud and the design team. To begin the process of deg for accessibility, the team finds the top three or so reasons that a would come to their product and ensures those are accessible to all. The next step is to create easier usability in the second tier features of the product, and then all features beyond. Using a screen reader, they go through the product to see if it’s usable, and really try to make the experience better. The team also makes sure there are a lot of guidance pages as well. The goal in product design is to make things simple and consistent for everyone. Michael Kleinerman Michael is a Product Designer at Google. He worked on Android and YouTube in the Bay Area before ing Cloud in NYC, where he started by leading the UX for Firestore until it launched in both Firebase and G. This work evolved into his current role on the core platform team, responsible for the design direction of the main design system used by producer teams to build and launch products on G. Cool things of the week Committed use discounts at a glance blog Networking in depth blog Chatbots with Dialog Flow blog and video Turn it up to eleven: Java 11 runtime comes to App Engine blog App Engine second generation runtimes now get double the memory; plus Go 1.12 and PHP 7.3 now generally available bterview Material.io site Material Design site Firebase site Cloud Firestore site Question of the week How do I work with my containers locally and then get them into the cloud? Where can you find us next? Gabi is done traveling. Mark Mirch’ is filming for customers in the Bay area. Everyone else is just laying low for now! Sound Effect Attribution “alert.wav” by danielnieto7 of Freesound.org “cell phone vibraion.wav” by MrAuralization of Freesound.org “laugh crowd 2.wav” by MrAuralizationFunWithSound of Freesound.org

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 G 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