The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
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799 afleveringen, van nieuw naar oud
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Exploring Dark Energy & Star Formation w/ ML with Viviana Acquaviva - TWiML Talk #184
26 september 2018 · 40 min
In today’s episode of our Strata Data series, we’re joined by Viviana Acquaviva, Associate Professor at City Tech, the New York City College of Technology. In our conversation, we discuss an ongoing project she’s a part of called the “Hobby-Eberly Telescope Dark Energy eXperiment,” her motivation for undertaking this project, how she gets her data, the models she uses, and how she evaluates their performance. Lees meer
The complete show notes can be found at https://twimlai.com/talk/184.
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Document Vectors in the Wild with James Dreiss - TWiML Talk #183
24 september 2018 · 41 min
In this episode of our Strata Data series we’re joined by James Dreiss, Senior Data Scientist at international news syndicate Reuters. James and I sat down to discuss his talk from the conference “Document vectors in the wild, building a content recommendation system,” in which he details how Reuters implemented document vectors to recommend content to users of their new “infinite scroll” page layout. Lees meer
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Applied Machine Learning for Publishers with Naveed Ahmad - TWiML Talk #182
20 september 2018 · 40 min
In today’s episode we’re joined by Naveed Ahmad, Senior Director of data engineering and machine learning at Hearst Newspapers. In our conversation, we discuss into the role of ML at Hearst, including their motivations for implementing it and some of their early projects, the challenges of data acquisition within a large organization, and the benefits they enjoy from using Google’s BigQuery as their data warehouse. Lees meer
For the complete show notes for this episode, visit https://twimlai.com/talk/182.
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Anticipating Superintelligence with Nick Bostrom - TWiML Talk #181
17 september 2018 · 45 min
In this episode, we’re joined by Nick Bostrom, professor at the University of Oxford and head of the Future of Humanity Institute, a multidisciplinary institute focused on answering big-picture questions for humanity with regards to AI safety and ethics. In our conversation, we discuss the risks associated with Artificial General Intelligence, advanced AI systems Nick refers to as superintelligence, openness in AI development and more! The notes for this episode can be found at https://twimlai.com/talk/18 Lees meer
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Can We Train an AI to Understand Body Language? with Hanbyul Joo - TWIML Talk #180
13 september 2018 · 52 min
In this episode, we’re joined by Hanbyul Joo, a PhD student at CMU. Lees meer
Han is working on what is called the “Panoptic Studio,” a multi-dimension motion capture studio used to capture human body behavior and body language. His work focuses on understanding how humans interact and behave so that we can teach AI-based systems to react to humans more naturally. We also discuss his CVPR best student paper award winner “Total Capture: A 3D Deformation Model for Tracking Faces, Hands, and Bodies.”
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Biological Particle Identification and Tracking with Jay Newby - TWiML Talk #179
10 september 2018 · 46 min
In today’s episode we’re joined by Jay Newby, Assistant Professor in the Department of Mathematical and Statistical Sciences at the University of Alberta. Lees meer
Jay joins us to discuss his work applying deep learning to biology, including his paper “Deep neural networks automate detection for tracking of submicron scale particles in 2D and 3D.” He gives us an overview of particle tracking and a look at how he combines neural networks with physics-based particle filter models.
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AI for Content Creation with Debajyoti Ray - TWiML Talk #178
6 september 2018 · 55 min
In today’s episode we’re joined by Debajyoti Ray, Founder and CEO of RivetAI, a startup producing AI-powered tools for storytellers and filmmakers. Lees meer
Deb and I discuss some of what he’s learned in the journey to apply AI to content creation, including how Rivet approaches the use of machine learning to automate creative processes, the company’s use hierarchical LSTM models and autoencoders, and the tech stack that they’ve put in place to support the business.
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Deep Reinforcement Learning Primer and Research Frontiers with Kamyar Azizzadenesheli - TWiML Talk #177
30 augustus 2018 · 1 uur 35 min
Today we’re joined by Kamyar Azizzadenesheli, PhD student at the University of California, Irvine, who joins us to review the core elements of RL, along with a pair of his RL-related papers: “Efficient Exploration through Bayesian Deep Q-Networks” and “Sample-Efficient Deep RL with Generative Adversarial Tree Search.” Lees meer
To skip the Deep Reinforcement Learning primer conversation and jump to the research discussion, skip to the 34:30 mark of the episode. Show notes at https://twimlai.com/talk/177
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OpenAI Five with Christy Dennison - TWiML Talk #176
27 augustus 2018 · 48 min
Today we’re joined by Christy Dennison, Machine Learning Engineer at OpenAI, who has been working on OpenAI’s efforts to build an AI-powered agent to play the DOTA 2 video game. In our conversation we overview of DOTA 2 gameplay and the recent OpenAI Five benchmark, we dig into the underlying technology used to create OpenAI Five, including their use of deep reinforcement learning, LSTM recurrent neural networks, and entity embeddings, plus some tricks and techniques they use to train the models. Lees meer
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How ML Keeps Shelves Stocked at Home Depot with Pat Woowong - TWiML Talk #175
23 augustus 2018 · 45 min
Today we’re joined by Pat Woowong, principal engineer in the applied machine intelligence group at The Home Depot. Lees meer
We discuss a project that Pat recently presented at the Google Cloud Next conference which used machine learning to predict shelf-out scenarios within stores. We dig into the motivation for this system and how the team went about building it, their use of kubernetes to support future growth in the platform, and much more.
For complete show notes, visit https://twimlai.com/talk/175.
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Contextual Modeling for Language and Vision with Nasrin Mostafazadeh - TWiML Talk #174
20 augustus 2018 · 49 min
Today we’re joined by Nasrin Mostafazadeh, Senior AI Research Scientist at New York-based Elemental Cognition. Lees meer
Our conversation focuses on Nasrin’s work in event-centric contextual modeling in language and vision including her work on the Story Cloze Test, a reasoning framework for evaluating story understanding and generation. We explore the details of this task, some of the challenges it presents and approaches for solving it.
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ML for Understanding Satellite Imagery at Scale with Kyle Story - TWiML Talk #173
16 augustus 2018 · 56 min
Today we’re joined by Kyle Story, computer vision engineer at Descartes Labs. Lees meer
Kyle and I caught up after his recent talk at the Google Cloud Next Conference titled “How Computers See the Earth: A Machine Learning Approach to Understanding Satellite Imagery at Scale.” We discuss some of the interesting computer vision problems he’s worked on at Descartes, and the key challenges they’ve had to overcome in scaling them.
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Generating Ground-Level Images From Overhead Imagery Using GANs with Yi Zhu - TWiML Talk #172
13 augustus 2018 · 38 min
Today we’re joined by Yi Zhu, a PhD candidate at UC Merced focused on geospatial image analysis. In our conversation, Yi and I take a look at his recent paper “What Is It Like Down There? Generating Dense Ground-Level Views and Image Features From Overhead Imagery Using Conditional Generative Adversarial Networks.” We discuss the goal of this research and how he uses conditional GANs to generate artificial ground-level images. Lees meer
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Vision Systems for Planetary Landers and Drones with Larry Matthies - TWiML Talk #171
9 augustus 2018 · 44 min
Today we’re joined by Larry Matthies, Sr. Research Scientist and head of computer vision in the mobility and robotics division at JPL. In our conversation, we discuss two talks he gave at CVPR a few weeks back, his work on vision systems for the first iteration of Mars rovers in 2004 and the future of planetary landing projects. Lees meer
For the complete show notes, visit https://twimlai.com/talk/171.
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Learning Semantically Meaningful and Actionable Representations with Ashutosh Saxena - TWiML Talk #170
6 augustus 2018 · 46 min
In this episode i'm joined by Ashutosh Saxena, a veteran of Andrew Ng’s Stanford Machine Learning Group, and co-founder and CEO of Caspar.ai. Ashutosh and I discuss his RoboBrain project, a computational system that creates semantically meaningful and actionable representations of the objects, actions and observations that a robot experiences in its environment, and allows these to be shared and queried by other robots to learn new actions. Lees meer
For complete show notes, visit https://twimlai.com/talk/170.
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AI Innovation for Clinical Decision Support with Joe Connor - TWiML Talk #169
2 augustus 2018 · 42 min
In this episode I speak with Joe Connor, Founder of Experto Crede. Lees meer
In our conversation, we explore his experiences bringing AI powered healthcare projects to market in collaboration with the UK National Health Service and its clinicians, some of the various challenges he’s run into when applying ML and AI in healthcare, as well as some of his successes. We also discuss data protections, especially GDPR, potential ways to include clinicians in the building of applications.
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Dynamic Visual Localization and Segmentation with Laura Leal-Taixé -TWiML Talk #168
30 juli 2018 · 45 min
In this episode I'm joined by Laura Leal-Taixé, Professor at the Technical University of Munich where she leads the Dynamic Vision and Learning Group. Lees meer
In our conversation, we discuss several of her recent projects including work on image-based localization techniques that fuse traditional model-based computer vision approaches with a data-driven approach based on deep learning, her paper on one-shot video object segmentation and the broader vision for her research.
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Conversational AI for the Intelligent Workplace with Gillian McCann - TWiML Talk #167
26 juli 2018 · 37 min
In this episode I'm joined by Gillian McCann, Head of Cloud Engineering and AI at Workgrid Software. In our conversation, which focuses on Workgrid’s use of cloud-based AI services, Gillian details some of the underlying systems that make Workgrid tick, their engineering pipeline & how they build high quality systems that incorporate external APIs and her view on factors that contribute to misunderstandings and impatience on the part of users of AI-based products. Lees meer
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Computer Vision and Intelligent Agents for Wildlife Conservation with Jason Holmberg - TWiML Talk #166
22 juli 2018 · 48 min
In this episode, I'm joined by Jason Holmberg, Executive Director and Director of Engineering at WildMe. Jason and I discuss Wildme's pair of open source computer vision based conservation projects, Wildbook and Whaleshark.org, Jason kicks us off with the interesting story of how Wildbook came to be, the eventual expansion of the project and the evolution of these projects’ use of computer vision and deep learning. Lees meer
For the complete show notes, visit twimlai.com/talk/166
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Pragmatic Deep Learning for Medical Imagery with Prashant Warier - TWiML Talk #165
19 juli 2018 · 37 min
In this episode I'm joined by Prashant Warier, CEO and Co-Founder of Qure.ai. We discuss the company’s work building products for interpreting head CT scans and chest x-rays. We look at knowledge gained in bringing a commercial product to market, including what the gap between academic research papers and commercially viable software, the challenge of data acquisition and more. We also touch on the application of transfer learning. Lees meer
For the complete show notes, visit https://twimlai.com/talk/165.
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Taskonomy: Disentangling Transfer Learning for Perception (CVPR 2018 Best Paper Winner) with Amir Zamir - TWiML Talk #164
16 juli 2018 · 48 min
In this episode I'm joined by Amir Zamir, Postdoctoral researcher at both Stanford & UC Berkeley, who joins us fresh off of winning the 2018 CVPR Best Paper Award for co-authoring "Taskonomy: Disentangling Task Transfer Learning." In our conversation, we discuss the nature and consequences of the relationships that Amir and his team discovered, and how they can be used to build more effective visual systems with machine learning. Lees meer
https://twimlai.com/talk/164
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Predicting Metabolic Pathway Dynamics w/ Machine Learning with Zak Costello - TWiML Talk #163
11 juli 2018 · 40 min
In today’s episode I’m joined by Zak Costello, post-doctoral fellow at the Joint BioEnergy Institute to discuss his recent paper, “A machine learning approach to predict metabolic pathway dynamics from time-series multiomics data.” Zak gives us an overview of synthetic biology and the use of ML techniques to optimize metabolic reactions for engineering biofuels at scale. Lees meer
Visit twimlai.com/talk/163 for the complete show notes.
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Machine Learning to Discover Physics and Engineering Principles with Nathan Kutz - TWiML Talk #162
9 juli 2018 · 43 min
In this episode, I’m joined by Nathan Kutz, Professor of applied mathematics, electrical engineering and physics at the University of Washington to discuss his research into the use of machine learning to help discover the fundamental governing equations for physical and engineering systems from time series measurements. Lees meer
For complete show notes visit twimlai.com/talk/162
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Automating Complex Internal Processes w/ AI with Alexander Chukovski - TWiML Talk #161
5 juli 2018 · 40 min
In this episode, I'm joined by Alexander Chukovski, Director of Data Services at Munich, Germany based career platform, Experteer. In our conversation, we explore Alex’s journey to implement machine learning at Experteer, the Experteer NLP pipeline and how it’s evolved, Alex’s work with deep learning based ML models, including models like VDCNN and Facebook’s FastText offering and a few recent papers that look at transfer learning for NLP. Lees meer
Check out the complete show notes at twimlai.com/talk/161
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Designing Better Sequence Models with RNNs with Adji Bousso Dieng - TWiML Talk #160
2 juli 2018 · 38 min
In this episode, I'm joined by Adji Bousso Dieng, PhD Student in the Department of Statistics at Columbia University to discuss two of her recent papers, “Noisin: Unbiased Regularization for Recurrent Neural Networks” and “TopicRNN: A Recurrent Neural Network with Long-Range Semantic Dependency.” We dive into the details behind both of these papers and learn a ton along the way. Lees meer
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Love Love: AI and ML in Tennis with Stephanie Kovalchik - TWiML Talk #159
29 juni 2018 · 47 min
In the final show in our AI in Sports series, I’m joined by Stephanie Kovalchik, Research Fellow at Victoria University and Senior Sports Scientist at Tennis Australia. In our conversation we discuss Tennis Australia's use of data to develop a player rating system based on ability and probability, some of the interesting products her Game Insight Group is developing, including a win forecasting algorithm, and a statistic that measures a given player’s workload during a match. Lees meer
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Growth Hacking Sports w/ Machine Learning with Noah Gift - TWiML Talk #158
28 juni 2018 · 51 min
In this episode of our AI in Sports series I'm joined by Noah Gift, Founder and Consulting CTO at Pragmatic Labs and professor at UC Davis. Noah and I discuss some of his recent work in using social media to predict which players hold the most on-court value, and how this work could lead to more complete approaches to player valuation. Lees meer
Check out the show notes at twimlai.com/talk/158
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Fine-Grained Player Prediction in Sports with Jennifer Hobbs - TWiML Talk #157
27 juni 2018 · 43 min
In this episode of our AI in Sports series, I'm joined by Jennifer Hobbs, Senior Data Scientist at STATS, a collector and distributor of sports data, to discuss the STATS data pipeline and how they collect and store different types of data for easy consumption and application. We also look into a paper she co-authored, Mythbusting Set-Pieces in Soccer, which was presented at the MIT Sloan Conference this year. Lees meer
https://twimlai.com/talk/157
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Targeted Ticket Sales Using Azure ML with the Trail Blazers w/ Mike Schumacher & Chenhui Hu - TWiML Talk #156
26 juni 2018 · 37 min
In today’s episode of our AI in Sports series I'm joined by Mike Schumacher, director of business analytics for the Portland Trail Blazers, and Chenhui Hu, a data scientist at Microsoft to discuss how the Blazers are using machine learning to produce better-targeted sales campaigns, for both single-game and season-ticket buyers. Lees meer
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AI for Athlete Optimization with Sinead Flahive - TWiML Talk #155
25 juni 2018 · 40 min
This week we’re excited to kick off a series of shows on AI in sports. In this episode I'm joined by Sinead Flahive, data scientist at Dublin, Ireland based Kitman Labs to discuss Kitman’s Athlete Optimization System, which allows sports trainers and coaches to collect and analyze data for player performance optimization and injury reduction. Enjoy! Lees meer
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Omni-Channel Customer Experiences with Vince Jeffs - TWiML Talk #154
21 juni 2018 · 43 min
In this, the final episode of our PegaWorld series I’m joined by Vince Jeffs, Senior Director of Product Strategy for AI and Decisioning at Pegasystems. Vince and I had a great talk about the role AI and advanced analytics will play in defining future customer experiences. We do this in the context provided by one of his presentations from the conference, which explores four technology scenarios from Pegasystems’ innovation labs. These look at a connected car experience, the use of deep learning for diagnostics, dynamic notifications, and continuously optimized marketing. We also get into an interesting discussion about how much is too much when it comes to hyperpersonalized experiences, and how businesses can manage this challenge. The notes for this show can be found at twimlai.com/talk/154. For more information on the Pegaworld series, visit twimlai.com/pegaworld2018. Lees meer
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Workforce Intelligence for Automation & Productivity with Michael Kempe - TWiML Talk #153
20 juni 2018 · 36 min
In this episode of our PegaWorld series, I’m joined by Michael Kempe, chief operating officer at global share registry and financial services provider Link Market Services. In the interview, Michael and I dig into Link’s use of workforce intelligence software to allow it to track and analyze the performance of its workforce and business processes. Michael and I discuss some of the initial challenges associated with implementing this type of system, including skepticism amongst employees, and how it ultimately sets the stage for the Link’s broader use of machine learning, AI and so called “robotic process automation” to increase workforce productivity. The notes for this show can be found at twimlai.com/talk/153. For more information on our PegaWorld series, visit twimlai.com/pegaworld2018. Lees meer
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Data Platforms for Decision Automation at Scotiabank with Jim Saleh - TWiML Talk #152
19 juni 2018 · 33 min
In this show, part of our PegaWorld 18 series, I'm joined by Jim Saleh, Senior Director of process and decision automation at Scotiabank. Jim is tasked with helping the bank transition from a world where customer interactions are based on historical analytics to one where they’re based on real-time decisioning and automation. In our conversation we discuss what’s required to deliver real-time decisioning, starting from the ground up with the data platform. In this vein we explore topics like data lakes, data warehouses, integration, and more, and the effort required to take advantage of these. The notes for this show can be found at twimlai.com/talk/152. For more info on our PegaWorld 2018 series, visit twimlai.com/pegaworld2018. Lees meer
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Towards the Self-Driving Enterprise with Kirk Borne - TWiML Talk #151
18 juni 2018 · 41 min
In this show, the first of our PegaWorld 18 series, I'm joined by Kirk Borne, Principal Data Scientist at management consulting firm Booz Allen Hamilton. In our conversation, Kirk shares his views on automation as it applies to enterprises and their customers. We discuss his experiences evangelizing data science within the context of a large organization, and the role of AI in helping organizations achieve automation. Along the way Kirk, shares a great analogy for intelligent automation, comparing it to an autonomous vehicle . We covered a ton of ground in this chat, which I think you’ll get a kick out of. The notes for this show can be found at twimlai.com/talk/151. For more info about our PegaWorld 2018 Series, visit twimlai.com/pegaworld2018. Lees meer
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How a Global Energy Company Adopts ML & AI with Nicholas Osborn - TWiML Talk #150
14 juni 2018 · 46 min
On today’s show I’m excited to share this interview with Nick Osborn, a longtime listener of the show and Leader of the Global Machine Learning Project Management Office at AES Corporation, a Fortune 200 power company. Nick and I met at my AI Summit a few weeks back, and after a brief chat about some of the things he was up to at AES, I knew I needed to get him on the show! In this interview, Nick and I explore how AES is implementing machine learning across multiple domains at the company. We dig into several examples falling under the Natural Language, Computer Vision, and Cognitive Assets categories he’s established for his projects. Along the way we cover some of the key podcast episodes that helped Nick discover potentially applicable ML techniques, and how those are helping his team broaden the use of machine learning at AES. This was a fun and informative conversation that has a lot to offer. Thanks, Nick! The notes for this episode can be found at twimlai.com/talk/150. Lees meer
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Problem Formulation for Machine Learning with Romer Rosales - TWiML Talk #149
11 juni 2018 · 50 min
In this episode, i'm joined by Romer Rosales, Director of AI at LinkedIn. We begin with a discussion of graphical models and approximate probability inference, and he helps me make an important connection in the way I think about that topic. We then review some of the applications of machine learning at LinkedIn, and how what Romer calls their ‘holistic approach’ guides the evolution of ML projects at LinkedIn. This leads us into a really interesting discussion about problem formulation and selecting the right objective function for a given problem. We then talk through some of the tools they’ve built to scale their data science efforts, including large-scale constrained optimization solvers, online hyperparameter optimization and more. This was a really fun conversation, that I’m sure you’ll enjoy! The notes for this show can be found at twimlai.com/talk/149. Lees meer
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AI for Materials Discovery with Greg Mulholland - TWiML Talk #148
7 juni 2018 · 42 min
In this episode I’m joined by Greg Mulholland, Founder and CEO of Citrine Informatics, which is applying AI to the discovery and development of new materials. Greg and I start out with an exploration of some of the challenges of the status quo in materials science, and what’s to be gained by introducing machine learning into this process. We discuss how limitations in materials manifest themselves, and Greg shares a few examples from the company’s work optimizing battery components and solar cells. We dig into the role and sources of data used in applying ML in materials, and some of the unique challenges to collecting it, and discuss the pipeline and algorithms Citrine uses to deliver its service. This was a fun conversation that spans physics, chemistry, and of course machine learning, and I hope you enjoy it. The notes for this show can be found at twimlai.com/talk/148. Lees meer
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Data Innovation & AI at Capital One with Adam Wenchel - TWiML Talk #147
4 juni 2018 · 45 min
In this episode I’m joined by Adam Wenchel, vice president of AI and Data Innovation at Capital One, to discuss how Machine Learning & AI are being integrated into their day-to-day practices, and how those advances benefit the customer. In our conversation, we look into a few of the many applications of AI at the bank, including fraud detection, money laundering, customer service, and automating back office processes. Adam describes some of the challenges of applying ML in financial services and how Capital One maintains consistent portfolio management practices across the organization. We also discuss how the bank has organized to scale their machine learning efforts, and the steps they’ve taken to overcome the talent shortage in the space. The notes for this show can be found at twimlai.com/talk/147. Lees meer
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Deep Gradient Compression for Distributed Training with Song Han - TWiML Talk #146
31 mei 2018 · 46 min
On today’s show I chat with Song Han, assistant professor in MIT’s EECS department, about his research on Deep Gradient Compression. In our conversation, we explore the challenge of distributed training for deep neural networks and the idea of compressing the gradient exchange to allow it to be done more efficiently. Song details the evolution of distributed training systems based on this idea, and provides a few examples of centralized and decentralized distributed training architectures such as Uber’s Horovod, as well as the approaches native to Pytorch and Tensorflow. Song also addresses potential issues that arise when considering distributed training, such as loss of accuracy and generalizability, and much more. The notes for this show can be found at twimlai.com/talk/146. Lees meer
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Masked Autoregressive Flow for Density Estimation with George Papamakarios - TWiML Talk #145
28 mei 2018 · 35 min
In this episode, University of Edinburgh Phd student George Papamakarios and I discuss his paper “Masked Autoregressive Flow for Density Estimation.” George walks us through the idea of Masked Autoregressive Flow, which uses neural networks to produce estimates of probability densities from a set of input examples. We discuss some of the related work that’s laid the groundwork for his research, including Inverse Autoregressive Flow, Real NVP and Masked Auto-encoders. We also look at the properties of probability density networks and discuss some of the challenges associated with this effort. The notes for this show can be found at twimlai.com/talk/145. Lees meer
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Training Data for Computer Vision at Figure Eight with Qazaleh Mirsharif - TWiML Talk #144
25 mei 2018 · 22 min
For today’s show, the last in our TrainAI series, I'm joined by Qazaleh Mirsharif, a machine learning scientist working on computer vision at Figure Eight. Qazaleh and I caught up at the TrainAI conference to discuss a couple of the projects she’s worked on in that field, namely her research into the classification of retinal images and her work on parking sign detection from Google Street View images. The former, which attempted to diagnose diseases like diabetic retinopathy using retinal scan images, is similar to the work I spoke with Ryan Poplin about on TWiML Talk #122. In my conversation with Qazaleh we focus on how she built her datasets for each of these projects and some of the key lessons she’s learned along the way. The notes for this show can be found at twimlai.com/talk/144. For series details, visit twimlai.com/trainai2018. Lees meer
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Agile Data Science with Sarah Aerni - TWiML Talk #143
24 mei 2018 · 38 min
Today we continue our TrainAI series with Sarah Aerni, Director of Data Science at Salesforce Einstein. Sarah and I sat down at the TrainAI conference to discuss her talk “Notes from the Field: The Platform, People, and Processes of Agile Data Science.” Sarah and I dig into the concept of agile data science, exploring what it means to her and how she’s seen it done at Salesforce and other places she’s worked. We also dig into the notion of machine learning platforms, which is also a keen area of interest for me. We discuss some of the common elements we’ve seen in ML platforms, and when it makes sense for an organization to start building one. The notes for this show can be found at twimlai.com/talk/143. For more details on the TrainAI series, visit twimlai.com/trainai2018 Lees meer
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Tensor Operations for Machine Learning with Anima Anandkumar - TWiML Talk #142
23 mei 2018 · 34 min
In this episode of our TrainAI series, I sit down with Anima Anandkumar, Bren Professor at Caltech and Principal Scientist with Amazon Web Services. Anima joined me to discuss the research coming out of her “Tensorlab” at CalTech. In our conversation, we review the application of tensor operations to machine learning and discuss how an example problem–document categorization–might be approached using 3 dimensional tensors to discover topics and relationships between topics. We touch on multidimensionality, expectation maximization, and Amazon products Sagemaker and Comprehend. Anima also goes into how to tensorize neural networks and apply our understanding of tensor algebra to do perform better architecture searches. The notes for this show can be found at twimlai.com/talk/142. For series info, visit twimlai.com/trainai2018 Lees meer
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Deep Learning for Live-Cell Imaging with David Van Valen - TWiML Talk #141
22 mei 2018 · 37 min
In today’s show, I sit down with David Van Valen, assistant professor of Bioengineering & Biology at Caltech. David joined me after his talk at the Figure Eight TrainAI conference to chat about his research using image recognition and segmentation techniques in biological settings. In particular, we discuss his use of deep learning to automate the analysis of individual cells in live-cell imaging experiments. We had a really interesting discussion around the various practicalities he’s learned about training deep neural networks for image analysis, and he shares some great insights into which of the techniques from the deep learning research have worked for him and which haven’t. If you’re a fan of our Nerd Alert shows, you’ll really like this one. Enjoy! The notes for this show can be found at twimlai.com/talk/141. For more information on this series, visit twimlai.com/trainai2018. Lees meer
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Checking in with the Master w/ Garry Kasparov - TWiML Talk #140
21 mei 2018 · 33 min
In this episode I’m joined by legendary chess champion, author, and fellow at the Oxford Martin School, Garry Kasparov. Garry and I sat down after his keynote at the Figure Eight Train AI conference in San Francisco last week. Garry and I discuss his bouts with the chess-playing computer Deep Blue–which became the first computer system to defeat a reigning world champion in their 1997 rematch–and how that experience has helped shaped his thinking on artificially intelligent systems. We explore his perspective on the evolution of AI, the ways in which chess and Deep Blue differ from Go and Alpha Go, and the significance of DeepMind’s Alpha Go Zero. We also talk through his views on the relationship between humans and machines, and how he expects it to change over time. The notes for this show can be found at twimlai.com/talk/140. For more information on this series, visit twimlai.com/trainai2018. Lees meer
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Exploring AI-Generated Music with Taryn Southern - TWiML Talk #139
17 mei 2018 · 33 min
In this episode I’m joined by Taryn Southern - a singer, digital storyteller and Youtuber, whose upcoming album I AM AI will be produced completely with AI based tools. Taryn and I explore all aspects of what it means to create music with modern AI-based tools, and the different processes she’s used to create her singles Break Free, Voices in My Head, and more. She also provides a rundown of the many tools she’s used in this space, including Google Magenta, Watson Beat, AMPer, Landr and more. This was a super fun interview that I think you’ll get a kick out of. The notes for this show can be found at twimlai.com/talk/139 Lees meer
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Practical Deep Learning with Rachel Thomas - TWiML Talk #138
14 mei 2018 · 44 min
In this episode, i'm joined by Rachel Thomas, founder and researcher at Fast AI. If you’re not familiar with Fast AI, the company offers a series of courses including Practical Deep Learning for Coders, Cutting Edge Deep Learning for Coders and Rachel’s Computational Linear Algebra course. The courses are designed to make deep learning more accessible to those without the extensive math backgrounds some other courses assume. Rachel and I cover a lot of ground in this conversation, starting with the philosophy and goals behind the Fast AI courses. We also cover Fast AI’s recent decision to switch to their courses from Tensorflow to Pytorch, the reasons for this, and the lessons they’ve learned in the process. We discuss the role of the Fast AI deep learning library as well, and how it was recently used to held their team achieve top results on a popular industry benchmark of training time and training cost by a factor of more than ten. The notes for this show can be found at twimlai.com/talk/138 Lees meer
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Kinds of Intelligence w/ Jose Hernandez-Orallo - TWiML Talk #137
10 mei 2018 · 44 min
In this episode, I'm joined by Jose Hernandez-Orallo, professor in the department of information systems and computing at Universitat Politècnica de València and fellow at the Leverhulme Centre for the Future of Intelligence, working on the Kinds of Intelligence Project. Jose and I caught up at NIPS last year after the Kinds of Intelligence Symposium that he helped organize there. In our conversation, we discuss the three main themes of the symposium: understanding and identifying the main types of intelligence, including non-human intelligence, developing better ways to test and measure these intelligences, and understanding how and where research efforts should focus to best benefit society. The notes for this show can be found at twimlai.com/talk/137. Lees meer
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Taming arXiv with Natural Language Processing w/ John Bohannon - TWiML Talk #136
7 mei 2018 · 54 min
In this episode i'm joined by John Bohannan, Director of Science at AI startup Primer. As you all may know, a few weeks ago we released my interview with Google legend Jeff Dean, which, by the way, you should definitely check if you haven’t already. Anyway, in that interview, Jeff mentions the recent explosion of machine learning papers on arXiv, which I responded to jokingly by asking whether Google had already developed the AI system to help them summarize and track all of them. While Jeff didn’t have anything specific to offer, a listener reached out and let me know that John was in fact already working on this problem. In our conversation, John and I discuss his work on Primer Science, a tool that harvests content uploaded to arxiv, sorts it into natural topics using unsupervised learning, then gives relevant summaries of the activity happening in different innovation areas. We spend a good amount of time on the inner workings of Primer Science, including their data pipeline and some of the tools they use, how they determine “ground truth” for training their models, and the use of heuristics to supplement NLP in their processing. The notes for this show can be found at twimlai.com/talk/136 Lees meer
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Epsilon Software for Private Machine Learning with Chang Liu - TWiML Talk #135
4 mei 2018 · 47 min
In this episode, our final episode in the Differential Privacy series, I speak with Chang Liu, applied research scientist at Georgian Partners, a venture capital firm that invests in growth stage business software companies in the US and Canada. Chang joined me to discuss Georgian’s new offering, Epsilon, a software product that embodies the research, development and lessons learned helps in helping their portfolio companies deliver differentially private machine learning solutions to their customers. In our conversation, Chang discusses some of the projects that led to the creation of Epsilon, including differentially private machine learning projects at BlueCore, Work Fusion and Integrate.ai. We explore some of the unique challenges of productizing differentially private ML, including business, people and technology issues. Finally, Chang provides some great pointers for those who’d like to further explore this field. The notes for this show can be found at twimlai.com/talk/135 Lees meer