Google Cloud Platform Podcast

Melanie and Mark celebrate their 150th episode this week with a high-energy interview of mutual friend, KF, at Strange Loop. KF gives her perspective on Strange Loop, working remotely, and distributed systems. She compliments Strange Loop for the diversity it has achieved as the conference has grown. She laments the lack of introductory material for distributed systems learners, saying it’s not as complicated as everyone thinks but needs more educational material for beginners! In general, she believes everyone could benefit from some code study, especially if you can find a good mentor. KF also gives us some great tips for working remotely and staying effective and social.

Today, Melanie brings you another great interview from her time at Deep Learning Indaba in South Africa. She was joined by Yabebal Fantaye and Jessica Phalafala for an in-depth look at the deep learning research that's going on in the continent.

At the African Institute for Mathematical Sciences, the aim is to gather together minds from all over Africa and the world to not only learn but to use their distinct perspectives to contribute to research that furthers the sciences. Our guests are both part of this initiative, using their specialized skills to expand the abilities of the group and stretch the boundaries of machine learning, mathematics, and other sciences.

Yabebal elaborates on the importance of AIMS and Deep Learning Indaba, noting that the more people can connect with each other, the more confidence they will gain. Jessica points out how this research in Africa can do more than just advance science. By focusing on African problems and solutions, machine learning research can help increase the GDP and economic standards of a continent thought to be "behind".

Jessica Phalafala is a PhD Applied Mathematics student at Stellenbosch University and currently affiliated with the African Institute for Mathematical Sciences. In her mid-twenties, she finds herself with four qualifications all obtained with distinction, including a Master of Science in Pure Mathematics degree from the University of the Witwatersrand. Jessica is interested in using her functional analysis background together with a number of newly developed skills to contribute towards developing rigorous mathematical theory to support some existing deep learning methods and algorithms for her PhD research. Outside of research she takes great interest in fast-tracking the level of accessibility of higher education in South Africa as co-founder of the Sego Sa Lesedi Foundation, a platform created to inform underprivileged high school learners of career and funding opportunities in science as well as provide them with mentorship as they transition into undergraduate studies.

Dr. Fantaye is an AIMS-ARETE Research Chair based in South Africa. His research is in applying artificial intelligence and advanced statistical methods to cosmological data sets in order to understand the nature of the universe and to satellite images of the Earth in order to find alternative ways to monitor African development progress. Dr. Fantaye is a fellow of the World Economic Forum Young Scientists community, and a fellow and a Chair of the Next Einstein Forum Community of Scientists.

• A Kubernetes FAQ for the C-suite blog
• BigQuery and surrogate keys: a practical approach blog
• Adding custom intelligence to Gmail with serverless on GCP blog
• Announcing Cloud Tasks, a task queue service for App Engine flex and second generation runtimes blog
• Unity and DeepMind partner to advance AI research blog

• African Institute for Mathematical Sciences site
• Provable approximation properties for deep neural networks research
• Next Einstein Initiative site
• Square Kilometer Array (SKA) site
• University of the Witwatersrand site
• Council of Scientific and Industrial Research (CSIR) site
• South African National Space Agency (SANSA) site
• National Astrophysics and Space Science Programme (NASSP)site
• IndabaX site
• Coursera site
• Andrej Karpathy research
• Andrej Karpathy Blog blog

If I'm using the Cluster Autoscaler for Kubernetes (or GKE), how can I prevent it from removing specific nodes from the cluster when scaling down?

• How can I prevent Cluster Autoscaler from scaling down a particular node? github
• What types of pods can prevent CA from removing a node? github

Mark will definitely be at Kubecon in December and will probably be at Unite L.A. this month.

Melanie is speaking at Monktoberfest Oct 4th in Portland, Maine and will be at CAMLIS the following week.

Today, Melanie brings you another great interview from her time at Deep Learning Indaba in South Africa. She was joined by Yabebal Fantaye and Jessica Phalafala for an in-depth look at the deep learning research that’s going on in the continent.

At the African Institute for Mathematical Sciences, the aim is to gather together minds from all over Africa and the world to not only learn but to use their distinct perspectives to contribute to research that furthers the sciences. Our guests are both part of this initiative, using their specialized skills to expand the abilities of the group and stretch the boundaries of machine learning, mathematics, and other sciences.

Yabebal elaborates on the importance of AIMS and Deep Learning Indaba, noting that the more people can connect with each other, the more confidence they will gain. Jessica points out how this research in Africa can do more than just advance science. By focusing on African problems and solutions, machine learning research can help increase the GDP and economic standards of a continent thought to be “behind”.

In our last (but not least!) interview from NEXT, Mark and Melanie talked with Sivan Aldor-Noiman and Erik Andrejko about Wellio, an awesome new platform that combines AI and healthy eating. Wellio was developed as a way to not only educate users on the importance of proper nutrition for well-being but to give them their own personal nutritionist.

The data scientists at Wellio started from scratch (pun intended) to create their own food-related database and then began training models so the data could be organized and personalized. Using a combination of human power and machine learning techniques, Wellio learns your preferences, allergies, diets, etc. and will make healthy decisions for you based on these key facts. It chooses recipes, populates a grocery list, and even has the ingredients delivered to your door in time for dinner!

Sivan heads Data Science for Wellio, an early stage startup in the FoodTech space that is helping people eat better. In Wellio, her team delivers models that help inspire, empower and adapt to people's eating needs, cooking abilities and health constraints. She began her career in the Israeli military serving as an instructor for an anti-tank missile unit (please don't think Rambo, think more like a classroom teacher). Sivan then transitioned to school and received her undergraduate degree in Industrial Engineering and a Master in Statistics from the Technion, Israel Institute of Technology. She moved to the U.S. to complete a Ph.D. degree in Statistics from The Wharton School, University of Pennsylvania. In her previous job, Sivan ended up leading several Data Science teams and learned that she really liked leading technical people since she got to learn a lot from them. Ultimately, she missed the smaller company mentality, so she is back in the startup world. Sivan was once asked to define herself so here goes: "I am an enthusiastic disagreeable giver and a constant empirical driven learner".

Erik has spent his career making a positive impact on the world through mathematics. He is a co-founder and Chief Technology Officer of Wellio - an early stage startup applying AI to the intersection of food and human health. Previously, Erik lead the data science and research organization at The Climate Corporation, which applies data science to solve challenging problems in numerous domains including climatology, agronomic modeling and geospatial applications. When not analyzing interesting datasets, Erik can often be found riding up some incline on a bicycle or cooking.

• Summary of Google Cloud Next Tokyo site
• Deep Learning Indaba GCP Credit Awards site
• Data Studio and Dataprep are now generally available blog
  • DS: BI analyze more than 500 other data sources via more than 100 partner-built connectors and used by over a million people globally
  • DP: new look, team collab and more analytics features blog
• Announcing general availability of Cloud Memorystore for Redis blog
• Coursera Advanced Machine Learning with TensorFlow with GCP blog
  • Webinar on October 9th at 9AM PST to learn more
• Simplifying ML predictions with Google Cloud Functions blog
• 50 Best Cloud Security Podcasts site
  • GCP Podcast Episode #100: Vint Cerf: past, present, and future of the internet podcast

• Wellio site
• GKE site
• Cloud Storage site
• Pub/Sub site
• Cloud Composer site
• Cloud ML Engine site
• Stackdriver site
• Cloud Functions site
• TensorFlow site
• Keras site
• Scikit Learn site
• Cloud TPU site
• Cloud AutoML site
• Cloud Vision site
• DevOps201 for Application Developers video
• Cloud Firestore site
• Day 3 Keynote: Made Here Together video
• Spinnaker site
• Contact Wellio email

Is Inbox going away?

• Inbox is signing off: find your favorite features in the new Gmail blog
• 5 ways the new Gmail can help you get more done blog

We'll both be at Strangeloop.

Mark will probably be at Unite L.A. in October.

Melanie speaking at Monktoberfest Oct 4th in Portland, Maine.

In our last (but not least!) interview from NEXT, Mark and Melanie talked with Sivan Aldor-Noiman and Erik Andrejko about Wellio, an awesome new platform that combines AI and healthy eating. Wellio was developed as a way to not only educate users on the importance of proper nutrition for well-being but to give them their own personal nutritionist.

The data scientists at Wellio started from scratch (pun intended) to create their own food-related database and then began training models so the data could be organized and personalized. Using a combination of human power and machine learning techniques, Wellio learns your preferences, allergies, diets, etc. and will make healthy decisions for you based on these key facts. It chooses recipes, populates a grocery list, and even has the ingredients delivered to your door in time for dinner!

This week we are bringing you a couple of interviews from last week's Deep Learning Indaba conference. Dr. Vukosi Marivate, Andrea Bohmert and Yasin(i) Musa Ayami talk about the burgeoning machine learning community, research, companies and AI investment landscape in Africa. While Mark is at Google Cloud Next in Tokyo, Melanie is joined by special guest co-hosts Nyalleng Moorosi and Willie Brink.

Vukosi and Yasin(i) share how Deep Learning Indaba is playing an important role to recognize and grow machine learning research and companies on the African continent. We also discuss Yasin(i)'s prototyped app, Tukuka, and how it won the Maathai Award which is given to individuals who are a positive force for change. Tukuka is being built to aid economically disadvantaged women in Zambia get access to financial resources that are currently unavailable. Andrea rounds up the interviews by giving us a VC perspective on the AI start-up landscape in Africa and how that compares to other parts of the world. As Nyalleng says at the end, AI is happening in Africa and has great potential for impact.

Willie Brink is a senior lecturer of Applied Mathematics in the Department of Mathematical Sciences at Stellenbosch University, South Africa. He teaches various courses in Applied Mathematics and Computer Science, at all levels, and his research interests fall mainly in the broad fields of computer vision and machine learning. He has worked on multi-view geometry, visual odometry, recognition and tracking, probabilistic graphical models, as well as deep learning. Recent research directions include visual knowledge representation and reasoning. Willie is also one of the founders and organisers of the Deep Learning Indaba, an exciting initiative working to celebrate and strengthen machine learning and artificial intelligence research in Africa, and to promote diversity and transformation in these fields.

Nyalleng is a Software Engineer and Researcher with the Google AI team in Ghana. Before joining Google, Nyalleng was a senior Data Science researcher at South Africa's national science lab, Council for Scientific and Industrial Research (CSIR), with the Modeling and Digital Sciences Unit. In her capacity at CSIR, she works on projects ranging from: rhino poaching prevention with park rangers, working with news outlets to understand social media sentiments, and searching for Biomarkers in African cancer proteomes. Before getting into ML research at CSIR, she was a computer science lecturer at Fort Hare University and a software engineer at Thomson Reuters. Moorosi is an active member of Women in Machine Learning, Black in Artificial Intelligence, and an organising member of the Deep Learning Indaba - a yearly workshop that gathers African researchers in one space to share ideas and grow machine learning and artificial intelligence capabilities.

Dr. Vukosi Marivate holds a PhD in Computer Science (Rutgers University) and MSc & BSc in Electrical Engineering (Wits University). He has recently started at the University of Pretoria as the ABSA Chair of Data Science. Vukosi works on developing Machine Learning/Artificial Intelligence methods to extract insights from data. A large part of his work over the last few years has been in the intersection of Machine Learning and Natural Language Processing (due to the abundance of text data and need to extract insights). As part of his vision for the ABSA Data Science chair, Vukosi is interested in Data Science for Social Impact, using local challenges as a springboard for research. In this area Vukosi has worked on projects in science, energy, public safety and utilities. Vukosi is an organizer of the Deep Learning Indaba, the largest Machine Learning/Artificial Intelligence workshop on the African continent, aiming to strengthen African Machine Learning. He is passionate about developing young talent, supervising MSc and PhD students, and mentoring budding Data Scientists.

Yasin(i) Musa Ayami is Team Lead at TsogoloTech and a certified Oracle Associate. Mr. Ayami recently graduated with a Master's Degree in Information Technology at the prestigious Durban University of Technology (DUT) were his study mainly focused on Computer Vision and Machine Learning. Prior to him enrolling for his Master's Degree, Mr Ayami served as an Intern Software Engineer at DUT's App Factory where he also served as Team Lead before deciding to further his studies. He also worked as a Part-Time Student Instructor at the DUT. In 2017, he co-founded TsogoloTech. His vision has always been to leverage technology for social good.

Andrea Bohmert is a Co-Managing Partner at Knife Capital. Before joining Knife Capital, she was the Founder and Co-Managing Partner of Hasso Plattner Ventures Africa. Passionate about strategizing how to scale businesses and meeting the entrepreneurs responsible for creating them, she has been actively involved in numerous initiatives aiming to accelerate the African entrepreneurial ecosystem.

• AlphaGo Movie site
• WiML: Women in Machine Learning site
• Deep Learning Indaba Poster Sessions site
• Neural Information Processing Systems site

• Deep Learning Indaba site
• Deep Learning Indaba GitHub site
• Deep Learning Indaba Tutorials site
• Deep Learning Indaba 2018 Slides site
• Deep Learning Indaba 2017 Presentations videos
• Deep Learning Indaba X site
• Yasin(i) Musa Ayami on GitHub site and LinkedIn site
• Deep Learning Indaba Award Winners site and tweet
• Maathai Award site
• Xamarin site
• SuperPosition at The Deep Learning Indaba with Dr. Vukosi Marivate podcast
• Knife Capital site
• Investing in AI by Andrea Bohmert article
• 10 Defining Moments that shaped the 2016 SA startup ecosystem article
• Data Science Africa site
• International Data Week site
• Google Cloud Platform Credits award winners tweet

The co-hosts weigh in on our question of the week: What have you taken away from this week and will take forward?

Mark and Melanie will be at Strangeloop.

Willie will be teaching Machine Learning at Stellenbosch University this summer.

Nyalleng will be at the Women in Machine Learning Workshop and the Neural Information Processing Systems Conference in Montreal in December.

This week we are bringing you a couple of interviews from last week’s Deep Learning Indaba conference. Dr. Vukosi Marivate, Andrea Bohmert and Yasin(i) Musa Ayami talk about the burgeoning machine learning community, research, companies and AI investment landscape in Africa. While Mark is at Google Cloud Next in Tokyo, Melanie is joined by special guest co-hosts Nyalleng Moorosi and Willie Brink.

Vukosi and Yasin(i) share how Deep Learning Indaba is playing an important role to recognize and grow machine learning research and companies on the African continent. We also discuss Yasin(i)’s prototyped app, Tukuka, and how it won the Maathai Award which is given to individuals who are a positive force for change. Tukuka is being built to aid economically disadvantaged women in Zambia get access to financial resources that are currently unavailable. Andrea rounds up the interviews by giving us a VC perspective on the AI start-up landscape in Africa and how that compares to other parts of the world. As Nyalleng says at the end, AI is happening in Africa and has great potential for impact.

Jeff Dean, the lead of Google AI, is on the podcast this week to talk with Melanie and Mark about AI and machine learning research, his upcoming talk at Deep Learning Indaba and his educational pursuit of parallel processing and computer systems was how his career path got him into AI. We covered topics from his team's work with TPUs and TensorFlow, the impact computer vision and speech recognition is having on AI advancements and how simulations are being used to help advance science in areas like quantum chemistry. We also discussed his passion for the development of AI talent in the content of Africa and the opening of Google AI Ghana. It's a full episode where we cover a lot of ground. One piece of advice he left us with, "the way to do interesting things is to partner with people who know things you don't."

Listen for the end of the podcast where our colleague, Gabe Weiss, helps us answer the question of the week about how to get data from IoT core to display in real time on a web front end.

Jeff Dean joined Google in 1999 and is currently a Google Senior Fellow, leading Google AI and related research efforts. His teams are working on systems for speech recognition, computer vision, language understanding, and various other machine learning tasks. He has co-designed/implemented many generations of Google's crawling, indexing, and query serving systems, and co-designed/implemented major pieces of Google's initial advertising and AdSense for Content systems. He is also a co-designer and co-implementor of Google's distributed computing infrastructure, including the MapReduce, BigTable and Spanner systems, protocol buffers, the open-source TensorFlow system for machine learning, and a variety of internal and external libraries and developer tools.

Jeff received a Ph.D. in Computer Science from the University of Washington in 1996, working with Craig Chambers on whole-program optimization techniques for object-oriented languages. He received a B.S. in computer science & economics from the University of Minnesota in 1990. He is a member of the National Academy of Engineering, and of the American Academy of Arts and Sciences, a Fellow of the Association for Computing Machinery (ACM), a Fellow of the American Association for the Advancement of Sciences (AAAS), and a winner of the ACM Prize in Computing.

• Google Dataset Search is in beta site
• Expanding our Public Datasets for geospatial and ML-based analytics blog
  • Zip Code Tabulation Area (ZCTA) site
• Google AI and Kaggle Inclusive Images Challenge site
• We are rated in the top 100 technology podcasts on iTunes site
• What makes TPUs fine-tuned for deep learning? blog

• Jeff Dean on Google AI profile
• Deep Learning Indaba site
• Google AI site
• Google AI in Ghana blog
• Google Brain site
• Google Cloud site
• DeepMind site
• Cloud TPU site
• Google I/O Effective ML with Cloud TPUs video
• Liquid cooling system article
• DAWNBench Results site
• Waymo (Alphabet's Autonomous Car) site
• DeepMind AlphaGo site
• Open AI Dota 2 blog
• Moustapha Cisse profile
• Sanjay Ghemawat profile
• Neural Information Processing Systems Conference site
• Previous Podcasts
  • GCP Podcast Episode 117: Cloud AI with Dr. Fei-Fei Li podcast
  • GCP Podcast Episode 136: Robotics, Navigation, and Reinforcement Learning with Raia Hadsell podcast
  • TWiML & AI Systems and Software for ML at Scale with Jeff Dean podcast
• Additional Resources
  • arXiv.org site
  • Chris Olah blog
  • Distill Journal site
  • Google's Machine Learning Crash Course site
  • Deep Learning by Ian Goodfellow, Yoshua Bengio and Aaron Courville book and site
  • NAE Grand Challenges for Engineering site
  • Senior Thesis Parallel Implementations of Neural Network Training: Two Back-Propagation Approaches by Jeff Dean paper and tweet
  • Machine Learning for Systems and Systems for Machine Learning slides

How do I get data from IoT core to display in real time on a web front end?

• Building IoT Applications on Google Cloud video
• MQTT site
• Cloud Pub/Sub site
• Cloud Functions site
• Cloud Firestore site

Melanie is at Deep Learning Indaba and Mark is at Tokyo NEXT. We'll both be at Strangeloop end of the month.

Gabe will be at Cloud Next London and the IoT World Congress.

Jeff Dean, the lead of Google AI, is on the podcast this week to talk with Melanie and Mark about AI and machine learning research, his upcoming talk at Deep Learning Indaba and his educational pursuit of parallel processing and computer systems was how his career path got him into AI. We covered topics from his team’s work with TPUs and TensorFlow, the impact computer vision and speech recognition is having on AI advancements and how simulations are being used to help advance science in areas like quantum chemistry. We also discussed his passion for the development of AI talent in the content of Africa and the opening of Google AI Ghana. It’s a full episode where we cover a lot of ground. One piece of advice he left us with, “the way to do interesting things is to partner with people who know things you don’t.”

Listen for the end of the podcast where our colleague, Gabe Weiss, helps us answer the question of the week about how to get data from IoT core to display in real time on a web front end.

Our guest today is Dr. Mario Lassnig, a software engineer working on the ATLAS Experiment at CERN! Melanie and Mark put on their physics hats as they learn all about what it takes to manage the petabytes of data involved in such a large research project.

Dr. Mario Lassnig has been working as a Software Engineer at the European Organisation for Nuclear Research (CERN) since 2006. Within the ATLAS Experiment, he is responsible for all aspects of its large-scale distributed data, including management, storage, network, and access. He is also one of the principal developers of the Rucio system for scientific data management. In his previous life, he developed mobile navigation software for multi-modal transportation in Vienna at Seibersdorf Research, as well as cryptographic smart-card applications for access control at the University of Klagenfurt. He holds a Master's degree in Computer Science from the University of Klagenfurt, and a doctoral degree in Computer Science from the University of Innsbruck.

• The Machines Can Do the Work, a Story of Kubernetes Testing, CI, and Automating the Contributor Experience blog
  • Google Cloud grants $9M in credits for the operation of the Kubernetes project blog
• Improving job searches for veterans with Google Cloud's Talent Solution blog
• Unity For Beginners… From a Beginner blog
  • GCP Podcast Episode 134: Connected Games with Unity and Google Cloud with Brett Bibby and Micah Baker podcast
• Neural Information Processing Systems Conference site

• Rucio - Scientific Data Management site
• CERN site
• ATLAS site
• Google Cloud Storage site
• Google Compute Engine site
• G Suite site
• GKE On-Prem site
• Rucio on GitHub site
• University of Oslo site
• University of Innsbruck site
• Brookhaven National Laboratory site
• University of Texas at Arlington site
• Square Kilometer Array site
• DUNE site
• LIGO Lab site
• Scientific Computing with Google Cloud Platform: Experiences from the Trenches in Particle Physics and Earth Sciences video
• GCP Podcast Episode 122: Project Jupyter with Jessica Forde, Yuvi Panda and Chris Holdgraf podcast
• Rucio Workshop site
• ACM/IEEE Supercomputing 2018 site

I am not familiar with Docker or Kubernetes - where can I get started?

• Docker

  • Docker's official "Getting Started" guide
  • Katacoda's free, interactive Docker course

• Kubernetes

  • You should totally read this comic and interactive tutorial
  • Katacoda's free, interactive Kubernetes course

Melanie will be at Deep Learning Indaba.

Mark will be at Tokyo NEXT.

We'll both be at Strange Loop.