Google Cloud Platform Podcast

Our guests Matthew Tamsett and Ravi Upreti join Gabi Ferrara and Aja Hammerly to talk about data science and their project, Qubit. Qubit helps web companies by measuring different user 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 users 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 GCP shop with us, explaining how they moved Qubit to GCP 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 GCP. Autoscaling and cloud management services provided by GCP 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 blog

Interview

• 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. Users 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 users 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 GCP 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 Premium 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 joined 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 users 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, "Designing Voice User Interfaces". She's been creating Voice User 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 user interface) to add another dimension to how users 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 GCP Costs site and videos
  • Coupon code for qwiklabs is: 1q-costs-626

Interview

• GCP 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: Designing Voice User 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 blog

Interview

• 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 GCP?

• GKE
• Cloud Run
• App Engine Flexible Environment
• 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, supporting 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 members 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 CPU 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 GCP 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 joins 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 user 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 users 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 supports the API for HBase, an open-source project similar to Bigtable. Because of this, it's easy for HBase users 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 blog
• Introducing the BigQuery Terraform module blog
• Macy's uses Google Cloud to streamline retail operations blog

Interview

• Cloud Bigtable site
• GCP 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 passionate 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 blog

Interview

• 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 blog

Interview

• 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 joins 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 feedback 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 joined NetApp in 2011. At NetApp Alim has held several customer-facing positions and is passionate 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 GCP 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 support 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 joining 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
• Containerizing in the real world … of Minecraft blog
• Introducing the What-If Tool for Cloud AI Platform models blog

Interview

• 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