Podcasts about deep learning indaba

Quelques 700 chercheuses et chercheurs venus de toutes l'Afrique, de la Côte d'Ivoire au Cameroun en passant par l'Algérie, se réunissent cette semaine à Dakar, au Sénégal, à l'occasion du Deep Learning Indaba, à l'Université Amadou Mahtar Mbow. Ces scientifiques planchent sur une nouvelle intelligence artificielle capable de résoudre des problèmes agricoles, environnementaux, énergétiques et éducatifs, le tout avec un enthousiasme communicatif.

Comment l'intelligence artificielle, IA, peut-elle contribuer au développement de l'Afrique ? C'est l'une des questions-clé que se posent depuis hier (dimanche), à Dakar, les quelque 700 spécialistes qui participent au « Deep Learning Indaba » 2024, le forum annuel des développeurs africains de cette technologie révolutionnaire. Dans l'agriculture, l'éducation et la santé, l'intelligence artificielle peut permettre de grandes avancées sur le continent. Mais à certaines conditions. Le chercheur camerounais Paulin Melatagia enseigne à la faculté des sciences de l'université de Yaoundé 1. RFI : en quoi l'intelligence artificielle peut-elle permettre une agriculture de précision ?Paulin Melatagia : L'intelligence artificielle, avec tout l'ensemble des outils aujourd'hui qu'elle arrive à mobiliser, est très utilisée dans l'agriculture, notamment pour tout ce qui est prédiction des invasions, par exemple la prédiction des invasions des criquets à partir d'images satellitaires. On peut également utiliser l'intelligence artificielle pour la détection des maladies des plantes. Il suffit aujourd'hui, avec certaines applications qui sont déployées sur des téléphones portables, scanner des feuilles, et à partir de ces images-là, de détecter un certain nombre de maladies sur les plantes. On peut également, grâce à l'intelligence artificielle, prédire des inondations à partir d'images satellitaires ou même d'images qui sont connectées avec des drones. Je pourrais également ajouter, comme autre exemple, l'arrosage intelligent grâce à l'internet des objets qui permet de mesurer l'humidité, la température et la luminosité dans un champ et ensuite de déclencher, voilà, le système d'arrosage.Dans le domaine de la santé maintenant, en quoi l'intelligence artificielle peut-elle aider le médecin à détecter des maladies ?Oui, l'intelligence artificielle peut être utilisée, notamment à partir de tout ce qui est imagerie médicale, pour identifier ou prédire des pathologies. À ce moment, il s'agit d'une aide au médecin ou une aide à la décision du médecin qui, à partir des IRM et des images de radiographie ou d'échographie, va les passer à une intelligence artificielle et obtiendra des résultats qu'il pourra ou non confirmer grâce à son expertise. Dans le même temps, on peut avoir des intelligences artificielles qui sont utilisées par des patients, qui vont pouvoir faire des pré diagnostics sur la base d'une collecte d'informations personnelles, par exemple la température, une image de la peau, une image des yeux, du nez, et cetera, et donc obtenir un diagnostic, un pré diagnostic pardon qui va être confirmé plus tard par un médecin expérimenté.Dans le domaine de l'éducation, pour les apprenants et les élèves qui ne parlent ni français ni anglais, qui ne parlent que leur langue locale, qu'est-ce que l'intelligence artificielle apporte de nouveau ?Ce que l'intelligence artificielle apporte de nouveau, c'est que, aujourd'hui, nous avons beaucoup de langues qui sont dites peu dotées, notamment en Afrique, peu dotées parce qu'il n'y a pas suffisamment de matière. On n'a pas suffisamment de données numériques pour pouvoir générer des intelligences artificielles du même niveau que les IA que l'on a en français et en anglais. Et donc les intelligences artificielles qui sont développées sur les langues africaines, notamment, permettent ce qu'on appelle la reconnaissance de la parole. On a donc des apprenants qui peuvent s'exprimer dans leur langue maternelle et les IA sont capables de faire de la traduction automatique ou même de comprendre ce qu'a dit l'apprenant. Un exemple, un élève dans une salle de classe peut poser une question dans sa langue maternelle sur un sujet, l'IA va traduire, ou alors va comprendre ce qui a été dit, et aller chercher une réponse, ramener la réponse à l'apprenant, qui va donc améliorer sa compréhension sur le sujet.Alors pour développer l'intelligence artificielle en Afrique, il faut des centres de données, est-ce qu'il y a beaucoup de pays africains équipés de tels centres ?Non, les centres de données pour le moment, on en retrouve très peu en Afrique malheureusement, avec des moteurs de calcul qui sont basés en Afrique. Pour le moment, la grande majorité des intelligences artificielles qui sont conçues par les Africains ou même qui sont conçues sur les données africaines le sont dans des centres de données qui sont hébergés en dehors de l'Afrique.Et quels sont les pays où commence à se développer des centres de données sur le continent ?On a par exemple le Sénégal qui a des centres de données, mais qui en plus a acquis un supercalculateur il y a quelques années. En Afrique du Sud, au Kenya, au Maroc, on retrouve également de grands centres de données qui ont déjà été mis en place. Dans les pays comme le Cameroun, on a quelques centres de données qui appartiennent à des entreprises privées, aussi on a un centre de données qui appartient à une société d'État. Mais ces centres de données-là ne sont pas encore exploités pour produire de l'intelligence artificielle.Alors l'intelligence artificielle, ça ne marche évidemment que si on est équipé d'un téléphone mobile et que si on a accès à Internet, est ce qu'il n'y a pas blocage de ce côté-là ?Oui, effectivement, il y a des blocages. Si on s'en tient au dernier rapport de l'association interprofessionnelle GSMA sur l'Afrique, le taux de pénétration de la téléphonie mobile est de l'ordre de quatre-vingt-dix-sept pour 100, soit quasiment un téléphone par personne. Cependant, on a que 70% des téléphones qui sont des smartphones et on sait bien que, pour accéder à des solutions d'intelligence artificielle, le smartphone est l'outil le plus adapté. En tout cas, sur le continent africain, on a également la problématique de la connexion internet. Le même rapport indique que l'on est aujourd'hui à 30% de la population africaine qui utilise Internet. Ces chiffres-là sont très faibles, mais ils ont doublé en 10 ans, ce qui permet de penser que, dans les années à venir, ce nombre-là va encore augmenter considérablement.À lire aussiIntelligence artificielle en Afrique: l'IA change la donne chez les communicants [2/3]

Bongani Bingwa speaks to Bataung Qhotsokoane, Editor at iAfrikan about the upcoming Deep Learning Indaba and what to expect.See omnystudio.com/listener for privacy information.

Big tech's power over language, means power over people. Bridget Todd talks to AI community leaders paving the way for open voice tech in their own languages and dialects.In this episode: AI builders and researchers in the US, Kenya and New Zealand who say the languages computers learn to recognize today will be the ones that survive tomorrow — as long as communities and local startups can defend their data rights from big AI companies.Halcyon Lawrence was a researcher of information design at Towson University in Maryland (via Trinidad and Tobago) who did everything Alexa told her to for a year.*Keoni Mahelona is a leader of Indigenous data rights and chief technology officer of Te Hiku Media, a Māori community media network with 21 local radio stations in New Zealand. Kathleen Siminyu is an AI grassroots community leader in Kenya and a machine learning fellow with Mozilla's Common Voice working on Kiswahili voice projects. IRL: Online Life is Real Life is an original podcast from Mozilla, the non-profit behind Firefox. In Season 7, host Bridget Todd talks to AI builders that put people ahead of profit.*Sadly, following the recording of this episode, Dr. Halcyon Lawrence passed away. We are glad to have met her and pay tribute to her legacy as a researcher and educator. Thank you, Halcyon. 

University of Pretoria's Vukosi Marivate, the holder of the ABSA Chair of Data Science, has been chosen for the 2023 World Economic Forum's Young Global Leaders Programme. Prof Maravati wears many hats, including heading a Data Science for Social Impact research group focusing on Artificial Intelligence and languages, especially African languages. He is the Chief Technology Officer at Lelapa.ai, a start-up with Big Tech investors. Prof Marivate also helped launch the Deep Learning Indaba that brings the African AI community together. He has received recognition for his Covid-19 ZA Dashboard, which is still the only source of aggregated data on Covid-19 in South Africa. He told BizNews why he moved back to South Africa from the US and how he wants to solve some of the African continent's significant challenges with machine learning.  Learn more about your ad choices. Visit megaphone.fm/adchoices

Deep Learning Indaba is an organization that empowers and builds communities around Artificial Intelligence and Machine Learning across Africa. Benjamin Rosman dives into how Deep Learning Indaba is impacting these communities.

If any company is at the top of most people's minds when it comes to AI, it's DeepMind. They have been at the forefront of many major breakthroughs including AlphaGo, the first AI to beat a human Go world champion and AlphaFold, which revolutionized protein structure prediction. Our guest on this week's episode, Shakir Mohamed, joined DeepMind in the early days and has been an instrumental part of their success ever since. Shakir is a Senior Staff Scientist at DeepMind, an Associate Fellow at the Leverhulme Centre for the Future of Intelligence, and a Honorary Professor of University College London. Shakir is also a founder and trustee of the Deep Learning Indaba, a grassroots organization aiming to build pan-African capacity and leadership in AI. Pieter and Shakir discuss his career journey of coming to DeepMind, his professional accomplishments like using ML to solve the problem of nowcasting (short-term weather predictions), and his personal work of growing AI's global inclusion with orgs like Deep Learning Indaba. SUBSCRIBE TO THE ROBOT BRAINS PODCAST TODAY | Visit therobotbrains.ai and follow us on YouTube at TheRobotBrainsPodcast, Twitter @therobotbrains, and Instagram @therobotbrains.| Host: Pieter Abbeel | Executive Producers: Alice Patel & Henry Tobias Jones | Production: Fresh Air Production See acast.com/privacy for privacy and opt-out information.

AAI for Good, a global summit hosted by XPRIZE and ITU, about machine translation and cognitive code switching. Today’s episode explores the concept of Cosmo-uBuntu, an approach to technological innovation that addresses issues of global justice and helps us better understand personhood in AI praxis. Hosted by S. Ama Wray, an associate professor at UC Irvine and co-founder of AI for Africa, with guests Vukosi Marivate, Jose Cossa and Jackie Berry, highlight the cultural and individual differences in direct interaction with different technology interfaces based on the cultural reading practices of non-Western and African peoples, with thoughts on how these works can reverse the trend toward exclusively Anglophone digital futures in Africana worlds while conducting proactive restoration of African epistemologies.Dr. S. Ama Wray, is a self-described Performance Architect and is an Associate Professor of Dance at the University of California, Irvine. Through dance methods she innovates across disciplinary lines, collaborating widely with practitioners from music, new media, health, visual art and theater. She is one of the co-Founders of AI 4 Afrika, inspired by AI for Good, and also the Africana Institute for Creativity Recognition and Elevation. In 2018 she received the 2018 Emerging Scholar Award from the African Diaspora SIG of the Comparative International Education Society. Her research into improvisation through the lens of West African performance, specifically Ewe, is burgeoning into a new interdisciplinary field, an integrative study of the optimization of human performance. The outcomes include Embodiology® an inclusive movement and mind method, optimizing creativity, empathy and wellbeing. As a consequence of COVID-19 she has created online wellness practice - Embodying Resilience - to maintain vitality and create community. Her creative praxis as relates to digital domains began in the U.K as recipient of the 2003 National Endowment for Science Technology and the Arts Fellowship, producing the prize-winning Texterritory. Integrating a cellphone performance platform it transforms audiences into co-creators in live performance settings. As founding Artistic Director of JazzXchange Wray continues to elevate jazz music in the concert dance setting, collaborating with artists including: Wynton Marsalis, Bobby McFerrin, Nicole Mitchell, Gary Crosby, OBE, Zoe Rahman and Julian Joseph, OBE. Her academic writing on Embodiology® and also Jazz Dance have been published by Oxford Books, Routledge and Florida University Press.Dr. Vukosi Marivate is the ABSA UP Chair of Data Science at the University of Pretoria. 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. 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 a founder of the Deep Learning Indaba, the largest Machine Learning/Artificial Intelligence workshop on the African continent, aiming to strengthen African Machine Learning.José Cossa, Ph.D., is a Mozambican scholar, writer/author, researcher, poet, blogger, “Twitterer”, podcaster, entrepreneur, and an Associate Professor in the College of Education at Pennsylvania State University. Most recently, Cossa served as a Visiting Associate Professor in the Graduate School of Education at the American University in Cairo and a Senior Lecturer at Vanderbilt University’s Peabody College. Cossa holds a Ph.D. in Cultural and Educational Policy Studies with a depth area in Comparative and International Education from Loyola University Chicago. He is the author of the book Power, Politics, and Higher Education: International Regimes, Local Governments, and Educational Autonomy, the recipient of the 2012 Joyce Cain Award for Distinguished Research on People of African Descent, awarded by the Comparative and International Education Society (CIES), and a member of the MacArthur Foundation 100&Change Panel of Judges for two consecutive competitions (Inaugural Challenge and 2019/2020). Cossa’s research focus is on power dynamics in negotiation over educational policy; unveiling issues inherent in the promise of modernity and working towards decolonizing, de-bordering, de-peripheralizing, and de-centering the world; higher education policy and administration; system transfer; international development; and, global and social justice. In addition, Cossa is currently engaging in a new (exterior to modernity) theorizing, i.e., Cosmo-uBuntu, to offer alternative theoretical grounding to research, analysis, and practice.Dr. Jackie Berry is a Cognitive Scientist studying visual perception, human-computer interaction, and expertise. Dr. Berry was a Fulbright U.S. Scholar at the American University in Cairo for the 2019-2020 academic year where she served as a teacher and researcher. Her work focused on TetLag which is the brief performance dip caused by switching to a different, but familiar, computer interface. Jackie holds a Bachelor of Science in Psychology, a Master of Science in Human Factors Psychology, a Master of Business Administration, and a Doctorate in Cognitive Psychology. She was the first person at Rensselaer Polytechnic Institute to collect online research data and the first African-American to graduate with a Doctorate in Cognitive Psychology from the State University of New York at the University in Albany. Her major research projects include developing a new model of geometric feature detection for English letter recognition, studying task switching in older adults, and investigating attentional capture during visual search. During her Fulbright U.S. Scholar award year Dr. Berry investigated whether Arabic-English biliterates might be better able to switch between different interfaces and configurations for the same task because they must regularly alternate between different orientations of text in reading, writing, and technology use in their daily lives. She wishes to continue this research with other “bidirectional biliterates” such as biliterate speakers of Hebrew and Chinese.Links:xprize.org/blog See acast.com/privacy for privacy and opt-out information.

In this special #TWIMLfest edition of the podcast, we’re joined by Shakir Mohamed, a Senior Research Scientist at DeepMind. Shakir is also a leader of Deep Learning Indaba, a non-profit organization whose mission is to Strengthen African Machine Learning and Artificial Intelligence. In our conversation with Shakir, we discuss his recent paper ‘Decolonial AI,’ the distinction between decolonizing AI and ethical AI, while also exploring the origin of the Indaba, the phases of community, and much more. The complete show notes for this episode can be found at twimlai.com/go/418.

In episode one of season five we talk about Bit by Bit, take a listener question on machine learning gatherings on the African continent (Deep Learning INDABA!DSA!) and hear an interview with Daphne Koller recorded at ODSC West

On the podcast today, we have two more fascinating interviews from Melanie’s time at Deep Learning Indaba! Mark helps host this episode as we speak with Karim Beguir and Muthoni Wanyoike about their company, Instadeep, the wonderful Indaba conference, and the growing AI community in Africa. Instadeep helps large enterprises understand how AI can benefit them. Karim stresses that it is possible to build advanced AI and machine learning programs in Africa because of the growing community of passionate developers and mentors for the new generation. Muthoni tells us about Nairobi Women in Machine Learning and Data Science, a community she is heavily involved with in Nairobi. The group runs workshops and classes for AI developers and encourages volunteers to participate by sharing their knowledge and skills. Karim Beguir Karim Beguir helps companies get a grip on the latest AI advancements and how to implement them. A graduate of France’s Ecole Polytechnique and former Program Fellow at NYU’s Courant Institute, Karim has a passion for teaching and using applied mathematics. This led him to co-found InstaDeep, an AI startup that was nominated at the MWC17 for the Top 20 global startup list made by PCMAG. Karim uses TensorFlow to develop Deep Learning and Reinforcement Learning products. Karim is also the founder of the TensorFlow Tunis Meetup. He regularly organises educational events and workshops to share his experience with the community. Karim is on a mission to democratize AI and make it accessible to a wide audience. Muthoni Wanyoike Muthoni Wanyoike is the team lead at Instadeep in Kenya. She is Passionate about bridging the skills gap in AI in Africa and does this by co-organizing the Nairobi Women in Machine Learning community. The community enables learning, mentorship, networking, and job opportunities for people interested in working in AI. She is experienced in research, data analytics, community and project management, and community growth hacking. Cool things of the week Is there life on other planets? Google Cloud is working with NASA’s Frontier Development Lab to find out blog In this Codelab, you will learn about StarCraft II Learning Environment project and to train your first Deep Reinforcement Learning agent. You will also get familiar some of the concepts and frameworks to get to train a machine learning agent. site A new course to teach people about fairness in ML blog Serverless from the ground up: Building a simple microservice with Cloud Functions (Part 1) blog Superposition Podcast from Deep Learning Indaba with Omoju Miller and Nando de Freitas tweet and video Interview Instadeep site Nairobi Women in Machine Learning and Data Science site Neural Information Processing Systems site Google Launchpad Accelerator site TensorFlow site Google Assistant site Cloud AutoML site Hackathon Lagos site Deep Learning Book book Ranked Reward: Enabling Self-Play Reinforcement Learning for Combinatorial Optimization research paper Lessons learned on building a tech community blog Kenya Open Data Initiative site R for Data Science GitHub site and book TWIML Presents Deep Learning Indaba site Question of the week If I want to create a GKE cluster with a specific major kubernetes version (or even just the latest) using the command line tools, how do I do that? GCloud container clusters create site Specifying cluster version site Where can you find us next? Our guests will be at Indaba 2019 in Kenya. Mark will be at KubeCon in December. Melanie will be at SOCML in November.

In this episode of our Deep Learning Indaba Series, we’re joined by Osonde Osoba, Engineer at RAND Corporation and Professor at the Pardee RAND Graduate School. Osonde and I spoke on the heels of the Indaba, where he presented on AI Ethics and Policy. We discuss his framework-based approach for evaluating ethical issues, such as applying the ethical principles laid out in the Belmont Report, and how to build an intuition for where ethical flashpoints may exist in these discussions. We then shift gears to Osonde’s own model development research and end up in a really interesting discussion about the application of machine learning to strategic decisions and game theory, including the use of fuzzy cognitive map models. The complete show notes for this episode can be found at twimlai.com/talk/192. For more info on the Deep Learning Indaba series, visit twimlai.com/indaba2018.

In this episode of our Deep Learning Indaba Series, we’re joined by Herman Kamper, Lecturer in the electrical and electronics engineering department at Stellenbosch University in SA and a co-organizer of the Indaba. Herman and I discuss his work on limited- and zero-resource speech recognition, how those differ from regular speech recognition, and the tension between linguistic and statistical methods in this space. We dive into the specifics of the methods being used and developed in Herman’s lab as well, including how phoneme data is used for segmenting and processing speech data. The full show notes for this episode can be found at https://twimlai.com/talk/191. For more on the Deep Learning Indaba series, visit https://twimlai.com/indaba2018.  

In this episode of our Deep Learning Indaba series, we’re joined by Naila Murray, Senior Research Scientist and Group Lead in the computer vision group at Naver Labs Europe. Naila presented at the Indaba on computer vision, and in this discussion we explore her work on visual attention, including why visual attention is important and the trajectory of work in the field over time. We also discuss her paper “Generalized Max Pooling,” and her recent research interest in learning representations with deep learning. For the complete show notes, visit twimlai.com/talk/190.

Last month, at The Deep Learning Indaba, we had the opportunity to sit down with senior data scientist at Github, Omoju Miller, and Principal Scientist at DeepMind and Professor of Computer Science at University of Oxford, Nando de Freitas. We got to talk ‘Turning Points of AI’: where we’ve been, where are we now and what can be envisaged for the future of computer intelligence. Resources: You can find out more about the Deep Learning Indaba here: http://www.deeplearningindaba.com. Follow Omoju’s blog here: http://omojumiller.com. And check out Nando’s online lectures here: https://www.youtube.com/user/ProfNand... And follow all of us on twitter: @superpositionZA, @omojumiller, @NandoDF. Music by Faresa Mpephu. Soundcloud@faresa-mphephu.

In this, the first episode of the Deep Learning Indaba series, we’re joined by Sara Hooker, AI Resident at Google Brain. I had the pleasure of speaking with Sara in the run-up to the Indaba about her work on interpretability in deep neural networks. We discuss what interpretability means and when it’s important, and explore some nuances like the distinction between interpreting model decisions vs model function. We also dig into her paper Evaluating Feature Importance Estimates and look at the relationship between this work and interpretability approaches like LIME. We also talk a bit about Google, in particular, the relationship between Brain and the rest of the Google AI landscape and the significance of the recently announced Google AI Lab in Accra, Ghana, being led by friend of the show Moustapha Cisse. And, of course, we chat a bit about the Indaba as well. For the complete show notes for this episode, visit twimlai.com/talk/189. For more information on the Deep Learning Indaba series, visit twimlai.com/indaba2018. 

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 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. Yabebal Fantaye 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. Cool things of the week 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 Interview 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 Question of the week 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 Where can you find us next? 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.

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 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 Moorosi 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 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 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 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. What are you looking forward to this week? AlphaGo Movie site WiML: Women in Machine Learning site Deep Learning Indaba Poster Sessions site Neural Information Processing Systems site Interview 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 Question of the week The co-hosts weigh in on our question of the week: What have you taken away from this week and will take forward? Where can you find us next? 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.

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 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. Cool things of the week 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 Interview 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 Question of the week 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 Where can you find us next? 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.

Hello Super Positioners, Today we bring to your ears Dr Vukosi Marivate, one of the co-organisers of the Deep Learning Indaba. Listen to his fascinating perspective from the intersection of data science, public policy and Mama Africa. Resources: Dr Vukosi Marivate's Website: www.vima.co.za Computational Social Science Workshop, UCT: https://compsocialscience.github.io/summer-institute/2018/capetown/ The Deep Learning Indaba: http://www.deeplearningindaba.com/ Data Science Africa: http://www.datascienceafrica.org/ This podcast was made in collaboration with The African Perspective (TAP) Magazine. Take a look at their YouTube channel: https://www.youtube.com/channel/UCdLXfy1kpSNTg2xAKycTUtA. Music by Faresa Mpephu: https://soundcloud.com/faresa-mphephu. Thank you for the support.

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 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. Cool things of the week 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 Interview 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 Question of the week 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 Where can you find us next? Melanie will be at Deep Learning Indaba. Mark will be at Tokyo NEXT. We’ll both be at Strange Loop.

This week we learn about how Mercari is handling migrating from an on-prem monolithic infrastructure to cloud microservices architecture with GKE. Terry and Taichi share with Melanie and Mark what drove the decision for the change, the challenges and what the team has learned from the transition. The real value for this change has been about making the platform more scalable as they grow to meet the needs of their millions of daily active users. It’s another great interview we captured out of Google NEXT. Taichi Nakashima Taichi is a tech lead for the microservices platform at Mercari. Prior to Mercari, he was a backend engineer at Rakuten, building internal Platform as a Service. Mercari chose microservice architecture as their next development platform, and built two teams to proceed with the migration. One is the microservice platform team that is building a platform that can deploy any microservices, and the other is the microservice development team that are focusing on migrating the current monolithic API to microservices. Mercari use GKE as a platform and GCP as the main infrastructure for microservices. Tonghui (Terry) Li Tonghui joined Mercari in April 2018 and is responsible for migrating the monolithic backend API to a microservice architecture. Prior to Mercari, he was a tech lead of Indeed, working on different components of the job search engine including Title Normalization, Location system, Job Search API, and more. Cool things of the week How to call the Cloud AutoML API from a web app site GCPPodcast Episode 108: Launchpad Studio with Malika Cantor and Peter Norvig site Who is this street artist? Building a graffiti artist classifier using AutoML blog Datastore Transactions, Batches and Perf! video and twitter Deploy only what you trust: introducing Binary Authorization for Google Kubernetes Engine blog Interview Mercari site Microservices on GKE at Mercari site Continuous Delivery for Microservices with Spinnaker at Mercari site Microservices site GKE site Terraform site Spinnaker site GKE On-Prem site GKE On-Prem - Managing Across Hybrid IT Environments with Open Architectures (Cloud Next ‘18) video Mercari on GitHub site BigQuery site Mercari Engineering Blog blog kubectl site Google Cloud AutoML site Photo credit: Taichi Nakashima Question of the week How do I use my existing identity management system with Google Cloud Platform? site and blog Where can you find us next? Mark is at Pax Dev and Pax West. Find him and say hi. In September, Mark will be at Tokyo NEXT and Melanie will be at Deep Learning Indaba. You can find both of us at Strangeloop.

Mark and Melanie are your hosts again this week as we talk with Steren Giannini and Stewart Reichling discussing what’s new with App Engine. Particularly its new second generation runtime, allowing headless Chrome, and better language support! And automatic scalability to make your life easier, too. App Engine also has an interesting way of inspiring new Google products. Tune in to learn more! Steren Giannini Steren Giannini is a Product Manager on Google Cloud Platform (GCP). He graduated from École Centrale Lyon, France and then was CTO of a startup that created mobile and multi-device solutions. After joining Google, Steren launched Stackdriver Error Reporting and now focuses on GCP’s serverless offering. Recently, Steren has been working on upgrading App Engine’s auto scaling system and bringing Node.js to App Engine standard environment. Stewart Reichling Stewart Reichling is a Product Manager on Google Cloud Platform (GCP). He is a graduate of Georgia Institute of Technology and has worked across Strategy, Marketing and Product Management at Google. He currently works on bringing new runtimes (Python, Node.js, +more to come!) to App Engine and Cloud Functions. Cool things of the week Robot dance party: How we created an entire animated short at Next ‘18 blog What’s happening in BigQuery: integrated machine learning, maps, and more blog Protecting against the new “L1TF” speculative vulnerabilities blog Interview App Engine site Deploying Node.js on App Engine standard environment video Introducing headless Chrome support in Cloud Functions and App Engine blog Node 8 site Python 3.7.0 site App Engine PHP 7.2 Runtime Environment Beta site Headless Chrome site GCPPodcast Episode 23: Humble Bundle with Andy Oxfeld podcast Google Cloud Datastore site App Engine Task Queue site Ubuntu site gVisor site Open-sourcing gVisor, a sandboxed container runtime blog App Engine Documentation site gcloud app deploy site To send feedback, email stewartr@google.com or steren@google.com App Engine Google Group forum Operating Serverless Apps with Google Stackdriver video App Engine’s new auto scaling system - scheduler blog Question of the week What does it mean when the recommendation is to update your image? Getting Image Vulnerabilities site Updating Managed Instance Groups site Node Images site Where can you find us next? Melanie will be at Deep Learning Indaba and Strangeloop. Mark will be at Pax Dev and Pax West starting August 28th. In September, he’ll be at Tokyo NEXT and Strangeloop.

Mark Mandel is in the guest seat today as Melanie and our old pal Francesc interview Cyril Tovena of Ubisoft and Mark about Agones. We discuss dedicated game servers and their importance in game performance, how Agones can make hosting and scaling dedicated game servers easier to manage, and the future of Agones. Cyril and Mark elaborate on Ubisoft’s relationship with Google and how it’s progressing the world of gaming. Listen in! Mark Mandel Mark Mandel is a Developer Advocate for Games for Google Cloud Platform, founder of the open source, multiplayer dedicated game server scaling project Agones, and one half of the Google Cloud Platform Podcast. Hailing from Australia, Mark built his career developing backend systems for over 15 years, writing open source software, and building infrastructure in the cloud. Cyril Tovena Cyril Tovena is a Technical Lead for the online group for Ubisoft Montreal, helping game productions to build online features in the last four years. Cyril started his career eight years ago, building web services in London. He is currently designing and implementing scalable microservices in the cloud. Cool things of the week Introducing App Engine Second Generation runtimes and Python 3.7 blog Cloud Functions serverless platform is generally available blog GOTO 2018 • The Robustness of Go • Francesc Campoy video Simple backup and replay of streaming events using Cloud Pub/Sub, Cloud Storage, and Cloud Dataflow blog Calling Java developers: Spring Cloud GCP 1.0 is now generally available blog Interview Agones Github site Agones on Twitter twitter Agones: Scaling Multiplayer Dedicated Game Servers with Kubernetes talk from NEXT 2018 video Ubisoft site Kubernetes site GKE site Go site dep site Agones Contributing Guide site Developing, Testing, and Building Agones site Agones Slack Channel site Agones Google Group site Question of the week Francesc answers our question of the week, “Should you do ML in Go?”. Short answer? Probably not. Python may be the better choice. If you do want to experiment with Go and ML, try Gonum, Gorgonia, or TensorFlow for Go. Where can you find us next? Francesc will be at GopherCon, GoSF, and Velocity. Melanie will be at Deep Learning Indaba and Strangeloop. Mark will be at Pax Dev and Pax West starting August 28th. In September, he’ll be at Tokyo NEXT and Strangeloop.

On this episode of the podcast we continue a conversation we started with Haben Girma, an advocate for equal rights for people with disabilities, regarding the value of tech accessibility. Melanie and Mark talk with her about common challenges and best practices when considering accessibility in technology design and development. Bottom line - we need one solution that works for all. Haben Girma The first Deafblind person to graduate from Harvard Law School, Haben Girma advocates for equal opportunities for people with disabilities. President Obama named her a White House Champion of Change, and Forbes recognized her in Forbes 30 Under 30. Haben travels the world consulting and public speaking, teaching clients the benefits of fully accessible products and services. Haben is a talented storyteller who helps people frame difference as an asset. She resisted society’s low expectations, choosing to create her own pioneering story. Because of her disability rights advocacy she has been honored by President Obama, President Clinton, and many others. Haben is also writing a memoir that will be published by Grand Central Publishing in 2019. Learn more at habengirma.com. Cool things of the week Istio reaches 1.0: ready for prod blog Google for Nigeria: Making the internet more useful for more people blog GCPPodcast Episode 17: The Cloud In Africa with Hiren Patel and Dale Humby podcast Access Google Cloud services, right from IntelliJ IDEA blog Interview Haben Girma’s website site Haben Girma’s presentation at NEXT video GCPPodcast Episode 100: Vint Cerf: past, present, and future of the internet podcast Web Content Accessibility Guidelines (WCAG) site Android Accessibility Guidelines site Apple Developer Accessibility Guidelines site Black in AI site Google Accessibility site San Francisco Lighthouse for the Blind site National Federation of the Blind site National Association of the Deaf site Question of the week How do I perform large scale mutations in BigQuery? blog and site Where can you find us next? Mark will be at Pax Dev and Pax West starting August 28th. In September, he’ll be at Tokyo NEXT. Melanie is at Def Con, Black Hat, and BSides Las Vegas. In September, she will be at Deep Learning Indaba.