Decolonizing AI with Shakir Mohamed - #418
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.
14 Loka 202054min
Spatial Analysis for Real-Time Video Processing with Adina Trufinescu
Today we’re joined by Adina Trufinescu, Principal Program Manager at Microsoft, to discuss some of the computer vision updates announced at Ignite 2020. We focus on the technical innovations that went into their recently announced spatial analysis software, and the software’s use cases including the movement of people within spaces, distance measurements (social distancing), and more. We also discuss the ‘responsible AI guidelines’ put in place to curb bad actors potentially using this software for surveillance, what techniques are being used to do object detection and image classification, and the challenges to productizing this research. The complete show notes for this episode can be found at twimlai.com/go/417.
8 Loka 202039min
How Deep Learning has Revolutionized OCR with Cha Zhang - #416
Today we’re joined by Cha Zhang, a Partner Engineering Manager at Microsoft Cloud & AI. Cha’s work at MSFT is focused on exploring ways that new technologies can be applied to optical character recognition, or OCR, pushing the boundaries of what has been seen as an otherwise ‘solved’ problem. In our conversation with Cha, we explore some of the traditional challenges of doing OCR in the wild, and what are the ways in which deep learning algorithms are being applied to transform these solutions. We also discuss the difficulties of using an end to end pipeline for OCR work, if there is a semi-supervised framing that could be used for OCR, the role of techniques like neural architecture search, how advances in NLP could influence the advancement of OCR problems, and much more. The complete show notes for this episode can be found at twimlai.com/go/416.
5 Loka 202057min
Machine Learning for Food Delivery at Global Scale - #415
In this special edition of the show, we discuss the various ways in which machine learning plays a role in helping businesses overcome their challenges in the food delivery space. A few weeks ago Sam had the opportunity to moderate a panel at the Prosus AI Marketplace virtual event with Sandor Caetano of iFood, Dale Vaz of Swiggy, Nicolas Guenon of Delivery Hero, and Euro Beinat of Prosus. In this conversation, panelists describe the application of machine learning to a variety of business use cases, including how they deliver recommendations, the unique ways they handle the logistics of deliveries, and fraud and abuse prevention. The complete show notes for this episode can be found at twimlai.com/go/415.
2 Loka 202057min
Open Source at Qualcomm AI Research with Jeff Gehlhaar and Zahra Koochak - #414
Today we're joined by Jeff Gehlhaar, VP of Technology at Qualcomm, and Zahra Koochak, Staff Machine Learning Engineer at Qualcomm AI Research. If you haven’t had a chance to listen to our first interview with Jeff, I encourage you to check it out here! In this conversation, we catch up with Jeff and Zahra to get an update on what the company has up to since our last conversation, including the Snapdragon 865 chipset and Hexagon Neural Network Direct. We also discuss open-source projects like the AI efficiency toolkit and Tensor Virtual Machine compiler, and how these projects fit in the broader Qualcomm ecosystem. Finally, we talk through their vision for on-device federated learning. The complete show notes for this page can be found at twimlai.com/go/414.
30 Syys 202042min
Visualizing Climate Impact with GANs w/ Sasha Luccioni - #413
Today we’re joined by Sasha Luccioni, a Postdoctoral Researcher at the MILA Institute, and moderator of our upcoming TWIMLfest Panel, ‘Machine Learning in the Fight Against Climate Change.’ We were first introduced to Sasha’s work through her paper on ‘Visualizing The Consequences Of Climate Change Using Cycle-consistent Adversarial Networks’, and we’re excited to pick her brain about the ways ML is currently being leveraged to help the environment. In our conversation, we explore the use of GANs to visualize the consequences of climate change, the evolution of different approaches she used, and the challenges of training GANs using an end-to-end pipeline. Finally, we talk through Sasha’s goals for the aforementioned panel, which is scheduled for Friday, October 23rd at 1 pm PT. Register for all of the great TWIMLfest sessions at twimlfest.com! The complete show notes for this episode can be found at twimlai.com/go/413.
28 Syys 202041min
ML-Powered Language Learning at Duolingo with Burr Settles - #412
Today we’re joined by Burr Settles, Research Director at Duolingo. Most would acknowledge that one of the most effective ways to learn is one on one with a tutor, and Duolingo’s main goal is to replicate that at scale. In our conversation with Burr, we dig how the business model has changed over time, the properties that make a good tutor, and how those features translate to the AI tutor they’ve built. We also discuss the Duolingo English Test, and the challenges they’ve faced with maintaining the platform while adding languages and courses. Check out the complete show notes for this episode at twimlai.com/go/412.
24 Syys 202055min
Bridging The Gap Between Machine Learning and the Life Sciences with Artur Yakimovich - #411
Today we’re joined by Artur Yakimovich, Co-Founder at Artificial Intelligence for Life Sciences and a visiting scientist in the Lab for Molecular Cell Biology at University College London. In our conversation with Artur, we explore the gulf that exists between life science researchers and the tools and applications used by computer scientists. While Artur’s background is in viral chemistry, he has since transitioned to a career in computational biology to “see where chemistry stopped, and biology started.” We discuss his work in that middle ground, looking at quite a few of his recent work applying deep learning and advanced neural networks like capsule networks to his research problems. Finally, we discuss his efforts building the Artificial Intelligence for Life Sciences community, a non-profit organization he founded to bring scientists from different fields together to share ideas and solve interdisciplinary problems. Check out the complete show notes at twimlai.com/go/411.
21 Syys 202040min
