The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
717 episodes - English - Latest episode: about 1 month ago - ★★★★★ - 323 ratingsMachine learning and artificial intelligence are dramatically changing the way businesses operate and people live. The TWIML AI Podcast brings the top minds and ideas from the world of ML and AI to a broad and influential community of ML/AI researchers, data scientists, engineers and tech-savvy business and IT leaders. Hosted by Sam Charrington, a sought after industry analyst, speaker, commentator and thought leader. Technologies covered include machine learning, artificial intelligence, deep learning, natural language processing, neural networks, analytics, computer science, data science and more.
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Episodes
Trends in Natural Language Processing with Sameer Singh - #445
January 07, 2021 22:10 - 1 hourToday we continue the 2020 AI Rewind series, joined by friend of the show Sameer Singh, an Assistant Professor in the Department of Computer Science at UC Irvine. We last spoke with Sameer at our Natural Language Processing office hours back at TWIMLfest, and was the perfect person to help us break down 2020 in NLP. Sameer tackles the review in 4 main categories, Massive Language Modeling, Fundamental Problems with Language Models, Practical Vulnerabilities with Language Models, and Evaluat...
Trends in Computer Vision with Pavan Turaga - #444
January 04, 2021 22:33 - 1 hourAI Rewind continues today as we’re joined by Pavan Turaga, Associate Professor in both the Departments of Arts, Media, and Engineering & Electrical Engineering, and the Interim Director of the School of Arts, Media, and Engineering at Arizona State University. Pavan, who joined us back in June to talk through his work from CVPR ‘20, Invariance, Geometry and Deep Neural Networks, is back to walk us through the trends he’s seen in Computer Vision last year. We explore the revival of physics-ba...
Trends in Reinforcement Learning with Pablo Samuel Castro - #443
December 30, 2020 18:51 - 1 hourToday we kick off our annual AI Rewind series joined by friend of the show Pablo Samuel Castro, a Staff Research Software Developer at Google Brain. Pablo joined us earlier this year for a discussion about Music & AI, and his Geometric Perspective on Reinforcement Learning, as well our RL office hours during the inaugural TWIMLfest. In today’s conversation, we explore some of the latest and greatest RL advancements coming out of the major conferences this year, broken down into a few major t...
MOReL: Model-Based Offline Reinforcement Learning with Aravind Rajeswaran - #442
December 28, 2020 21:19 - 38 minutesToday we close out our NeurIPS series joined by Aravind Rajeswaran, a PhD Student in machine learning and robotics at the University of Washington. At NeurIPS, Aravind presented his paper MOReL: Model-Based Offline Reinforcement Learning. In our conversation, we explore model-based reinforcement learning, and if models are a “prerequisite” to achieve something analogous to transfer learning. We also dig into MOReL and the recent progress in offline reinforcement learning, the differences in ...
Machine Learning as a Software Engineering Enterprise with Charles Isbell - #441
December 23, 2020 22:03 - 46 minutesAs we continue our NeurIPS 2020 series, we’re joined by friend-of-the-show Charles Isbell, Dean, John P. Imlay, Jr. Chair, and professor at the Georgia Tech College of Computing. This year Charles gave an Invited Talk at this year’s conference, You Can’t Escape Hyperparameters and Latent Variables: Machine Learning as a Software Engineering Enterprise. In our conversation, we explore the success of the Georgia Tech Online Masters program in CS, which now has over 11k students enrolled, and t...
Natural Graph Networks with Taco Cohen - #440
December 21, 2020 20:02 - 58 minutesToday we kick off our NeurIPS 2020 series joined by Taco Cohen, a Machine Learning Researcher at Qualcomm Technologies. In our conversation with Taco, we discuss his current research in equivariant networks and video compression using generative models, as well as his paper “Natural Graph Networks,” which explores the concept of “naturality, a generalization of equivariance” which suggests that weaker constraints will allow for a “wider class of architectures.” We also discuss some of Taco’...
Productionizing Time-Series Workloads at Siemens Energy with Edgar Bahilo Rodriguez - #439
December 18, 2020 20:13 - 41 minutesToday we close out our re:Invent series joined by Edgar Bahilo Rodriguez, Lead Data Scientist in the industrial applications division of Siemens Energy. Edgar spoke at this year's re:Invent conference about Productionizing R Workloads, and the resurrection of R for machine learning and productionalization. In our conversation with Edgar, we explore the fundamentals of building a strong machine learning infrastructure, and how they’re breaking down applications and using mixed technologies to...
ML Feature Store at Intuit with Srivathsan Canchi - #438
December 16, 2020 20:14 - 41 minutesToday we continue our re:Invent series with Srivathsan Canchi, Head of Engineering for the Machine Learning Platform team at Intuit. As we teased earlier this week, one of the major announcements coming from AWS at re:Invent was the release of the SageMaker Feature Store. To our pleasant surprise, we came to learn that our friends at Intuit are the original architects of this offering and partnered with AWS to productize it at a much broader scale. In our conversation with Srivathsan, we ex...
re:Invent Roundup 2020 with Swami Sivasubramanian - #437
December 14, 2020 20:41 - 48 minutesToday we’re kicking off our annual re:invent series joined by Swami Sivasubramanian, VP of Artificial Intelligence, at AWS. During re:Invent last week, Amazon made a ton of announcements on the machine learning front, including quite a few advancements to SageMaker. In this roundup conversation, we discuss the motivation for hosting the first-ever machine learning keynote at the conference, a bunch of details surrounding tools like Pipelines for workflow management, Clarify for bias detectio...
Predictive Disease Risk Modeling at 23andMe with Subarna Sinha - #436
December 11, 2020 21:35 - 39 minutesToday we’re joined by Subarna Sinha, Machine Learning Engineering Leader at 23andMe. 23andMe handles a massive amount of genomic data every year from its core ancestry business but also uses that data for disease prediction, which is the core use case we discuss in our conversation. Subarna talks us through an initial use case of creating an evaluation of polygenic scores, and how that led them to build an ML pipeline and platform. We talk through the tools and tech stack used for the opera...
Scaling Video AI at RTL with Daan Odijk - #435
December 09, 2020 19:25 - 40 minutesToday we’re joined by Daan Odijk, Data Science Manager at RTL. In our conversation with Daan, we explore the RTL MLOps journey, and their need to put platform infrastructure in place for ad optimization and forecasting, personalization, and content understanding use cases. Daan walks us through some of the challenges on both the modeling and engineering sides of building the platform, as well as the inherent challenges of video applications. Finally, we discuss the current state of their pl...
Benchmarking ML with MLPerf w/ Peter Mattson - #434
December 07, 2020 20:40 - 46 minutes - 106 MBToday we’re joined by Peter Mattson, General Chair at MLPerf, a Staff Engineer at Google, and President of MLCommons. In our conversation with Peter, we discuss MLCommons and MLPerf, the former an open engineering group with the goal of accelerating machine learning innovation, and the latter a set of standardized Machine Learning speed benchmarks used to measure things like model training speed, throughput speed for inference. We explore the target user for the MLPerf benchmarks, the ...
Benchmarking ML with MLCommons w/ Peter Mattson - #434
December 07, 2020 20:40 - 46 minutesToday we’re joined by Peter Mattson, General Chair at MLPerf, a Staff Engineer at Google, and President of MLCommons. In our conversation with Peter, we discuss MLCommons and MLPerf, the former an open engineering group with the goal of accelerating machine learning innovation, and the latter a set of standardized Machine Learning speed benchmarks used to measure things like model training speed, throughput speed for inference. We explore the target user for the MLPerf benchmarks, the nee...
Deep Learning for NLP: From the Trenches with Charlene Chambliss - #433
December 03, 2020 20:43 - 45 minutesToday we’re joined by Charlene Chambliss, Machine Learning Engineer at Primer AI. Charlene, who we also had the pleasure of hosting at NLP Office Hours during TWIMLfest, is back to share some of the work she’s been doing with NLP. In our conversation, we explore her experiences working with newer NLP models and tools like BERT and HuggingFace, as well as whats she’s learned along the way with word embeddings, labeling tasks, debugging, and more. We also focus on a few of her projects, like ...
Feature Stores for Accelerating AI Development - #432
November 30, 2020 22:40 - 56 minutesIn this special episode of the podcast, we're joined by Kevin Stumpf, Co-Founder and CTO of Tecton, Willem Pienaar, an engineering lead at Gojek and founder of the Feast Project, and Maxime Beauchemin, Founder & CEO of Preset, for a discussion on Feature Stores for Accelerating AI Development. In this panel discussion, Sam and our guests explored how organizations can increase value and decrease time-to-market for machine learning using feature stores, MLOps, and open source. We also discuss...
An Exploration of Coded Bias with Shalini Kantayya, Deb Raji and Meredith Broussard - #431
November 27, 2020 21:41 - 1 hourIn this special edition of the podcast, we're joined by Shalini Kantayya, the director of Coded Bias, and Deb Raji and Meredith Broussard, who both contributed to the film. In this panel discussion, Sam and our guests explored the societal implications of the biases embedded within AI algorithms. The conversation discussed examples of AI systems with disparate impact across industries and communities, what can be done to mitigate this disparity, and opportunities to get involved. Our paneli...
Common Sense as an Algorithmic Framework with Dileep George - #430
November 23, 2020 21:18 - 47 minutesToday we’re joined by Dileep George, Founder and the CTO of Vicarious. Dileep, who was also a co-founder of Numenta, works at the intersection of AI research and neuroscience, and famously pioneered the hierarchical temporal memory. In our conversation, we explore the importance of mimicking the brain when looking to achieve artificial general intelligence, the nuance of “language understanding” and how all the tasks that fall underneath it are all interconnected, with or without language. ...
Scaling Enterprise ML in 2020: Still Hard! with Sushil Thomas - #429
November 19, 2020 21:21 - 46 minutesToday we’re joined by Sushil Thomas, VP of Engineering for Machine Learning at Cloudera. Over the summer, I had the pleasure of hosting Sushil and a handful of business leaders across industries at the Cloudera Virtual Roundtable. In this conversation with Sushil, we recap the roundtable, exploring some of the topics discussed and insights gained from those conversations. Sushil gives us a look at how COVID19 has impacted business throughout the year, and how the pandemic is shaping enterpri...
Enabling Clinical Automation: From Research to Deployment with Devin Singh - #428
November 16, 2020 22:20 - 43 minutesToday we’re joined by Devin Singh, a Physician Lead for Clinical Artificial Intelligence & Machine Learning in Pediatric Emergency Medicine at the Hospital for Sick Children (SickKids) in Toronto, and Founder and CEO of HeroAI. In our conversation with Devin, we discuss some of the interesting ways that Devin is deploying machine learning within the SickKids hospital, the current structure of academic research, including how much research and publications are currently being incentivized, ho...
Pixels to Concepts with Backpropagation w/ Roland Memisevic - #427
November 12, 2020 18:29 - 34 minutesToday we’re joined by Roland Memisevic, return podcast guest and Co-Founder & CEO of Twenty Billion Neurons. We last spoke to Roland in 2018, and just earlier this year TwentyBN made a sharp pivot to a surprising use case, a companion app called Fitness Ally, an interactive, personalized fitness coach on your phone. In our conversation with Roland, we explore the progress TwentyBN has made on their goal of training deep neural networks to understand physical movement and exercise. We also...
Fighting Global Health Disparities with AI w/ Jon Wang - #426
November 09, 2020 19:19 - 35 minutesToday we’re joined by Jon Wang, a medical student at UCSF, and former Gates Scholar and AI researcher at the Bill and Melinda Gates Foundation. In our conversation with Jon, we explore a few of the different ways he’s attacking various public health issues, including improving the electronic health records system through automating clinical order sets, and exploring how the lack of literature and AI talent in the non-profit and healthcare spaces, and bad data have further marginalized unders...
Accessibility and Computer Vision - #425
November 05, 2020 22:46 - 1 hourDigital imagery is pervasive today. More than a billion images per day are produced and uploaded to social media sites, with many more embedded within websites, apps, digital documents, and eBooks. Engaging with digital imagery has become fundamental to participating in contemporary society, including education, the professions, e-commerce, civics, entertainment, and social interactions. However, most digital images remain inaccessible to the 39 million people worldwide who are blind. AI and...
NLP for Equity Investing with Frank Zhao - #424
November 02, 2020 17:00 - 44 minutesToday we’re joined by Frank Zhao, Senior Director of Quantamental Research at S&P Global Market Intelligence. In our conversation with Frank, we explore how he came to work at the intersection of ML and finance, and how he navigates the relationship between data science and domain expertise. We also discuss the rise of data science in the investment management space, examining the largely under-explored technique of using unstructured data to gain insights into equity investing, and the edge...
The Future of Education and AI with Salman Khan - 423
October 28, 2020 05:47 - 47 minutes - 43.7 MBIn the final #TWIMLfest Keynote Interview, we’re joined by Salman Khan, Founder of Khan Academy. In our conversation with Sal, we explore the amazing origin story of the academy, and how coronavirus is shaping the future of education and remote and distance learning, for better and for worse. We also explore Sal’s perspective on machine learning and AI being used broadly in education, the potential of injecting a platform like Khan Academy with ML and AI for course recommendations, and if ...
The Future of Education and AI with Salman Khan - #423
October 28, 2020 05:47 - 47 minutesIn the final #TWIMLfest Keynote Interview, we’re joined by Salman Khan, Founder of Khan Academy. In our conversation with Sal, we explore the amazing origin story of the academy, and how coronavirus is shaping the future of education and remote and distance learning, for better and for worse. We also explore Sal’s perspective on machine learning and AI being used broadly in education, the potential of injecting a platform like Khan Academy with ML and AI for course recommendations, and if th...
Why AI Innovation and Social Impact Go Hand in Hand with Milind Tambe - #422
October 23, 2020 05:36 - 35 minutesIn this special #TWIMLfest Keynote episode, we’re joined by Milind Tambe, Director of AI for Social Good at Google Research India, and Director of the Center for Research in Computation and Society (CRCS) at Harvard University. In our conversation, we explore Milind’s various research interests, most of which fall under the umbrella of AI for Social Impact, including his work in public health, both stateside and abroad, his conservation work in South Asia and Africa, and his thoughts on the ...
What's Next for Fast.ai? w/ Jeremy Howard - #421
October 21, 2020 18:55 - 1 hourIn this special #TWIMLfest episode of the podcast, we’re joined by Jeremy Howard, Founder of Fast.ai. In our conversation with Jeremy, we discuss his career path, including his journey through the consulting world and how those experiences led him down the path to ML education, his thoughts on the current state of the machine learning adoption cycle, and if we’re at maximum capacity for deep learning use and capability. Of course, we dig into the newest version of the fast.ai framework and ...
Feature Stores for MLOps with Mike del Balso - #420
October 19, 2020 15:02 - 45 minutesToday we’re joined by Mike del Balso, co-Founder and CEO of Tecton. Mike, who you might remember from our last conversation on the podcast, was a foundational member of the Uber team that created their ML platform, Michelangelo. Since his departure from the company in 2018, he has been busy building up Tecton, and their enterprise feature store. In our conversation, Mike walks us through why he chose to focus on the feature store aspects of the machine learning platform, the journey, pers...
Exploring Causality and Community with Suzana Ilić - #419
October 16, 2020 08:00 - 54 minutesIn this special #TWIMLfest episode, we’re joined by Suzana Ilić, a computational linguist at Causaly and founder of Machine Learning Tokyo (MLT). Suzana joined us as a keynote speaker to discuss the origins of the MLT community, but we cover a lot of ground in this conversation. We briefly discuss Suzana’s work at Causaly, touching on her experiences transitioning from linguist and domain expert to working with causal modeling, balancing her role as both product manager and leader of the dev...
Decolonizing AI with Shakir Mohamed - #418
October 14, 2020 04:59 - 54 minutesIn 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 mu...
Spatial Analysis for Real-Time Video Processing with Adina Trufinescu
October 08, 2020 18:06 - 39 minutesToday 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 so...
How Deep Learning has Revolutionized OCR with Cha Zhang - #416
October 05, 2020 16:02 - 57 minutesToday 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 soluti...
Machine Learning for Food Delivery at Global Scale - #415
October 02, 2020 18:40 - 57 minutesIn 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 ...
Open Source at Qualcomm AI Research with Jeff Gehlhaar and Zahra Koochak - #414
September 30, 2020 13:29 - 42 minutesToday 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 ...
Visualizing Climate Impact with GANs w/ Sasha Luccioni - #413
September 28, 2020 20:57 - 41 minutesToday 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 o...
ML-Powered Language Learning at Duolingo with Burr Settles - #412
September 24, 2020 17:59 - 55 minutesToday 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 maintaini...
Bridging The Gap Between Machine Learning and the Life Sciences with Artur Yakimovich - #411
September 21, 2020 18:43 - 40 minutesToday 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 b...
Understanding Cultural Style Trends with Computer Vision w/ Kavita Bala - #410
September 17, 2020 18:33 - 38 minutesToday we’re joined by Kavita Bala, the Dean of Computing and Information Science at Cornell University. Kavita, whose research explores the overlap of computer vision and computer graphics, joined us to discuss a few of her projects, including GrokStyle, a startup that was recently acquired by Facebook and is currently being deployed across their Marketplace features. We also talk about StreetStyle/GeoStyle, projects focused on using social media data to find style clusters across the globe...
That's a VIBE: ML for Human Pose and Shape Estimation with Nikos Athanasiou, Muhammed Kocabas, Michael Black - #409
September 14, 2020 20:37 - 43 minutesToday we’re joined by Nikos Athanasiou, Muhammed Kocabas, Ph.D. students, and Michael Black, Director of the Max Planck Institute for Intelligent Systems. We caught up with the group to explore their paper VIBE: Video Inference for Human Body Pose and Shape Estimation, which they submitted to CVPR 2020. In our conversation, we explore the problem that they’re trying to solve through an adversarial learning framework, the datasets (AMASS) that they’re building upon, the core elements that se...
3D Deep Learning with PyTorch 3D w/ Georgia Gkioxari - #408
September 10, 2020 17:50 - 35 minutesToday we’re joined by Georgia Gkioxari, a research scientist at Facebook AI Research. Georgia was hand-picked by the TWIML community to discuss her work on the recently released open-source library PyTorch3D. In our conversation, Georgia describes her experiences as a computer vision researcher prior to the 2012 deep learning explosion, and how the entire landscape has changed since then. Georgia walks us through the user experience of PyTorch3D, while also detailing who the target audien...
What are the Implications of Algorithmic Thinking? with Michael I. Jordan - #407
September 07, 2020 11:43 - 56 minutesToday we’re joined by the legendary Michael I. Jordan, Distinguished Professor in the Departments of EECS and Statistics at UC Berkeley. Michael was gracious enough to connect us all the way from Italy after being named IEEE’s 2020 John von Neumann Medal recipient. In our conversation with Michael, we explore his career path, and how his influence from other fields like philosophy shaped his path. We spend quite a bit of time discussing his current exploration into the intersection of ec...
Beyond Accuracy: Behavioral Testing of NLP Models with Sameer Singh - #406
September 03, 2020 19:10 - 41 minutesToday we’re joined by Sameer Singh, an assistant professor in the department of computer science at UC Irvine. Sameer’s work centers on large-scale and interpretable machine learning applied to information extraction and natural language processing. We caught up with Sameer right after he was awarded the best paper award at ACL 2020 for his work on Beyond Accuracy: Behavioral Testing of NLP Models with CheckList. In our conversation, we explore CheckLists, the task-agnostic methodology for...
How Machine Learning Powers On-Demand Logistics at Doordash with Gary Ren - #405
August 31, 2020 20:27 - 43 minutesToday we’re joined by Gary Ren, a machine learning engineer for the logistics team at DoorDash. In our conversation, we explore how machine learning powers the entire logistics ecosystem. We discuss the stages of their “marketplace,” and how using ML for optimized route planning and matching affects consumers, dashers, and merchants. We also talk through how they use traditional mathematics, classical machine learning, potential use cases for reinforcement learning frameworks, and challenge...
Machine Learning as a Software Engineering Discipline with Dillon Erb - #404
August 27, 2020 19:23 - 44 minutesToday we’re joined by Dillon Erb, Co-founder & CEO of Paperspace. We’ve followed Paperspace since their origins offering GPU-enabled compute resources to data scientists and machine learning developers, to the release of their Jupyter-based Gradient service. Our conversation with Dillon centered on the challenges that organizations face building and scaling repeatable machine learning workflows, and how they’ve done this in their own platform by applying time-tested software engineering prac...
AI and the Responsible Data Economy with Dawn Song - #403
August 24, 2020 20:02 - 53 minutesToday we’re joined by Professor of Computer Science at UC Berkeley, Dawn Song. Dawn’s research is centered at the intersection of AI, deep learning, security, and privacy. She’s currently focused on bringing these disciplines together with her startup, Oasis Labs. In our conversation, we explore their goals of building a ‘platform for a responsible data economy,’ which would combine techniques like differential privacy, blockchain, and homomorphic encryption. The platform would give consume...
Relational, Object-Centric Agents for Completing Simulated Household Tasks with Wilka Carvalho - #402
August 20, 2020 17:52 - 41 minutesToday we’re joined by Wilka Carvalho, a PhD student at the University of Michigan, Ann Arbor. In our conversation, we focus on his paper ‘ROMA: A Relational, Object-Model Learning Agent for Sample-Efficient Reinforcement Learning.’ In the paper, Wilka explores the challenge of object interaction tasks, focusing on every day, in-home functions. We discuss how he’s addressing the challenge of ‘object-interaction’ tasks, the biggest obstacles he’s run into along the way.
Model Explainability Forum - #401
August 17, 2020 19:28 - 1 hourToday we bring you the latest Discussion Series: The Model Explainability Forum. Our group of experts and researchers explore the current state of explainability and discuss the key emerging ideas shaping the field. Each guest shares their unique perspective and contributions to thinking about model explainability in a practical way. We explore concepts like stakeholder-driven explainability, adversarial attacks on explainability methods, counterfactual explanations, legal and policy implicat...
What NLP Tells Us About COVID-19 and Mental Health with Johannes Eichstaedt - #400
August 13, 2020 15:31 - 58 minutesToday we’re joined by Johannes Eichstaedt, an Assistant Professor of Psychology at Stanford University. In our conversation, we explore how Johannes applies his physics background to a career as a computational social scientist, some of the major patterns in the data that emerged over the first few months of lockdown, including mental health, social norms, and political patterns. We also explore how Johannes built the process, and the techniques he’s using to collect, sift through, and unders...
Human-AI Collaboration for Creativity with Devi Parikh - #399
August 10, 2020 19:24 - 44 minutesToday we’re joined by Devi Parikh, Associate Professor at the School of Interactive Computing at Georgia Tech, and research scientist at Facebook AI Research (FAIR). In our conversation, we touch on Devi’s definition of creativity, explore multiple ways that AI could impact the creative process for artists, and help humans become more creative. We investigate tools like casual creator for preference prediction, neuro-symbolic generative art, and visual journaling.
Neural Augmentation for Wireless Communication with Max Welling - #398
August 06, 2020 19:12 - 48 minutesToday we’re joined by Max Welling, Vice President of Technologies at Qualcomm Netherlands, and Professor at the University of Amsterdam. In our conversation, we explore Max’s work in neural augmentation, and how it’s being deployed. We also discuss his work with federated learning and incorporating the technology on devices to give users more control over the privacy of their personal data. Max also shares his thoughts on quantum mechanics and the future of quantum neural networks for chip de...