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
Machine Learning for Security and Security for Machine Learning with Nicole Nichols - TWiML Talk #252
April 16, 2019 17:01 - 41 minutesToday we’re joined by Nicole Nichols, a senior research scientist at the Pacific Northwest National Lab. We discuss her recent presentation at GTC, which was titled “Machine Learning for Security, and Security for Machine Learning.” We explore two use cases, insider threat detection, and software fuzz testing, discussing the effectiveness of standard and bidirectional RNN language models for detecting malicious activity, the augmentation of software fuzzing techniques using deep learning, and...
Domain Adaptation and Generative Models for Single Cell Genomics with Gerald Quon - TWiML Talk #251
April 15, 2019 19:48 - 32 minutesToday we’re joined by Gerald Quon, assistant professor at UC Davis. Gerald presented his work on Deep Domain Adaptation and Generative Models for Single Cell Genomics at GTC this year, which explores single cell genomics as a means of disease identification for treatment. In our conversation, we discuss how he uses deep learning to generate novel insights across diseases, the different types of data that was used, and the development of ‘nested’ Generative Models for single cell measurement.
Mapping Dark Matter with Bayesian Neural Networks w/ Yashar Hezaveh - TWiML Talk #250
April 11, 2019 19:01 - 34 minutesToday we’re joined by Yashar Hezaveh, Assistant Professor at the University of Montreal. Yashar and I caught up to discuss his work on gravitational lensing, which is the bending of light from distant sources due to the effects of gravity. In our conversation, Yashar and I discuss how ML can be applied to undistort images, the intertwined roles of simulation and ML in generating images, incorporating other techniques such as domain transfer or GANs, and how he assesses the results of this pro...
Deep Learning for Population Genetic Inference with Dan Schrider - TWiML Talk #249
April 09, 2019 03:39 - 49 minutesToday we’re joined by Dan Schrider, assistant professor in the department of genetics at UNC Chapel Hill. My discussion with Dan starts with an overview of population genomics, looking into his application of ML in the field. We then dig into Dan’s paper “The Unreasonable Effectiveness of Convolutional Neural Networks in Population Genetic Inference,” which examines the idea that CNNs are capable of outperforming expert-derived statistical methods for some key problems in the field.
Empathy in AI with Rob Walker - TWiML Talk #248
April 05, 2019 18:31 - 40 minutesToday we’re joined by Rob Walker, Vice President of Decision Management at Pegasystems. Rob joined us back in episode 127 to discuss “Hyperpersonalizing the customer experience.” Today, he’s back for a discussion about the role of empathy in AI systems. In our conversation, we dig into the role empathy plays in consumer-facing human-AI interactions, the differences between empathy and ethics, and a few examples of ways empathy should be considered when enterprise AI systems.
Benchmarking Custom Computer Vision Services at Urban Outfitters with Tom Szumowski - TWiML Talk #247
April 03, 2019 21:24 - 50 minutesToday we’re joined by Tom Szumowski, Data Scientist at URBN, parent company of Urban Outfitters and other consumer fashion brands. Tom and I caught up to discuss his project “Exploring Custom Vision Services for Automated Fashion Product Attribution.” We look at the process Tom and his team took to build custom attribution models, and the results of their evaluation of various custom vision APIs for this purpose, with a focus on the various roadblocks and lessons he and his team encountered a...
Pragmatic Quantum Machine Learning with Peter Wittek - TWiML Talk #245
April 01, 2019 21:27 - 1 hourToday we’re joined by Peter Wittek, Assistant Professor at the University of Toronto working on quantum-enhanced machine learning and the application of high-performance learning algorithms. In our conversation, we discuss the current state of quantum computing, a look ahead to what the next 20 years of quantum computing might hold, and how current quantum computers are flawed. We then dive into our discussion on quantum machine learning, and Peter’s new course on the topic, which debuted i...
*Bonus Episode* A Quantum Machine Learning Algorithm Takedown with Ewin Tang - TWiML Talk #246
April 01, 2019 18:40 - 40 minutesIn this special bonus episode of the podcast, I’m joined by Ewin Tang, a PhD student in the Theoretical Computer Science group at the University of Washington. In our conversation, Ewin and I dig into her paper “A quantum-inspired classical algorithm for recommendation systems,” which took the quantum computing community by storm last summer. We haven’t called out a Nerd-Alert interview in a long time, but this interview inspired us to dust off that designation, so get your notepad ready!
Supporting TensorFlow at Airbnb with Alfredo Luque - TWiML Talk #244
March 28, 2019 19:38 - 40 minutesToday we're joined by Alfredo Luque, a software engineer on the machine infrastructure team at Airbnb. If you’re interested in AI Platforms and ML infrastructure, you probably remember my interview with Airbnb’s Atul Kale, in which we discussed their Bighead platform. In my conversation with Alfredo, we dig a bit deeper into Bighead’s support for TensorFlow, discuss a recent image categorization challenge they solved with the framework, and explore what the new 2.0 release means for their us...
Mining the Vatican Secret Archives with TensorFlow w/ Elena Nieddu - TWiML Talk #243
March 27, 2019 16:20 - 43 minutesToday we’re joined by Elena Nieddu, Phd Student at Roma Tre University, who presented on her project “In Codice Ratio” at the TF Dev Summit. In our conversation, Elena provides an overview of the project, which aims to annotate and transcribe Vatican secret archive documents via machine learning. We discuss the many challenges associated with transcribing this vast archive of handwritten documents, including overcoming the high cost of data annotation.
Exploring TensorFlow 2.0 with Paige Bailey - TWiML Talk #242
March 25, 2019 21:01 - 39 minutesToday we're joined by Paige Bailey, TensorFlow developer advocate at Google, to discuss the TensorFlow 2.0 alpha release. Paige and I talk through the latest TensorFlow updates, including the evolution of the TensorFlow APIs and the role of eager mode, tf.keras and tf.function, the evolution of TensorFlow for Swift and its inclusion in the new fast.ai course, new updates to TFX (or TensorFlow Extended), Google’s end-to-end ML platform, the emphasis on community collaboration with TF 2.0, and ...
Privacy-Preserving Decentralized Data Science with Andrew Trask - TWiML Talk #241
March 21, 2019 16:27 - 33 minutesToday we’re joined by Andrew Trask, PhD student at the University of Oxford and Leader of the OpenMined Project, an open-source community focused on researching, developing, and promoting tools for secure, privacy-preserving, value-aligned artificial intelligence. We dig into why OpenMined is important, exploring some of the basic research and technologies supporting Private, Decentralized Data Science, including ideas such as Differential Privacy,and Secure Multi-Party Computation.
The Unreasonable Effectiveness of the Forget Gate with Jos Van Der Westhuizen - TWiML Talk #240
March 18, 2019 19:31 - 32 minutesToday we’re joined by Jos Van Der Westhuizen, PhD student in Engineering at Cambridge University. Jos’ research focuses on applying LSTMs, or Long Short-Term Memory neural networks, to biological data for various tasks. In our conversation, we discuss his paper "The unreasonable effectiveness of the forget gate," in which he explores the various “gates” that make up an LSTM module and the general impact of getting rid of gates on the computational intensity of training the networks.
Building a Recommendation Agent for The North Face with Andrew Guldman - TWiML Talk #239
March 14, 2019 16:42 - 47 minutesToday we’re joined by Andrew Guldman, VP of Product Engineering and R&D at Fluid to discuss Fluid XPS, a user experience built to help the casual shopper decide on the best product choices during online retail interactions. We specifically discuss its origins as a product to assist outerwear retailer The North Face. In our conversation, we discuss their use of heat-sink algorithms and graph databases, challenges associated with staying on top of a constantly changing landscape, and more!
Active Learning for Materials Design with Kevin Tran - TWiML Talk #238
March 11, 2019 18:28 - 33 minutesToday we’re joined by Kevin Tran, PhD student at Carnegie Mellon University. In our conversation, we explore the challenges surrounding the creation of renewable energy fuel cells, which is discussed in his recent Nature paper “Active learning across intermetallics to guide discovery of electrocatalysts for CO2 reduction and H2 evolution.” The AI Conference is returning to New York in April and we have one FREE conference pass for a lucky listener! Visit twimlai.com/ainygiveaway to enter!
Deep Learning in Optics with Aydogan Ozcan - TWiML Talk #237
March 07, 2019 19:08 - 42 minutesToday we’re joined by Aydogan Ozcan, Professor of Electrical and Computer Engineering at UCLA, exploring his group's research into the intersection of deep learning and optics, holography and computational imaging. We specifically look at a really interesting project to create all-optical neural networks which work based on diffraction, where the printed pixels of the network are analogous to neurons. We also explore practical applications for their research and other areas of interest.
Scaling Machine Learning on Graphs at LinkedIn with Hema Raghavan and Scott Meyer - TWiML Talk #236
March 04, 2019 17:00 - 46 minutesToday we’re joined by Hema Raghavan and Scott Meyer of LinkedIn to discuss the graph database and machine learning systems that power LinkedIn features such as “People You May Know” and second-degree connections. Hema shares her insight into the motivations for LinkedIn’s use of graph-based models and some of the challenges surrounding using graphical models at LinkedIn’s scale, while Scott details his work on the software used at the company to support its biggest graph databases.
Safer Exploration in Deep Reinforcement Learning using Action Priors with Sicelukwanda Zwane - TWiML Talk #235
March 01, 2019 17:00 - 53 minutesToday we conclude our Black in AI series with Sicelukwanda Zwane, a masters student at the University of Witwatersrand and graduate research assistant at the CSIR, who presented on “Safer Exploration in Deep Reinforcement Learning using Action Priors” at the workshop. In our conversation, we discuss what “safer exploration” means in this sense, the difference between this work and other techniques like imitation learning, and how this fits in with the goal of “lifelong learning.”
Dissecting the Controversy around OpenAI's New Language Model - TWiML Talk #234
February 25, 2019 17:58 - 1 hourIn the inaugural TWiML Live, Sam Charrington is joined by Amanda Askell (OpenAI), Anima Anandkumar (NVIDIA/CalTech), Miles Brundage (OpenAI), Robert Munro (Lilt), and Stephen Merity to discuss the controversial recent release of the OpenAI GPT-2 Language Model. We cover the basics like what language models are and why they’re important, and why this announcement caused such a stir, and dig deep into why the lack of a full release of the model raised concerns for so many.
Human-Centered Design with Mira Lane - TWiML Talk #233
February 22, 2019 15:26 - 46 minutesToday we present the final episode in our AI for the Benefit of Society series, in which we’re joined by Mira Lane, Partner Director for Ethics and Society at Microsoft. Mira and I focus our conversation on the role of culture and human-centered design in AI. We discuss how Mira defines human-centered design, its connections to culture and responsible innovation, and how these ideas can be scalably implemented across large engineering organizations.
Fairness in Machine Learning with Hanna Wallach - TWiML Talk #232
February 18, 2019 23:06 - 48 minutesToday we’re joined by Hanna Wallach, a Principal Researcher at Microsoft Research. Hanna and I really dig into how bias and a lack of interpretability and transparency show up across ML. We discuss the role that human biases, even those that are inadvertent, play in tainting data, and whether deployment of “fair” ML models can actually be achieved in practice, and much more. Hanna points us to a TON of resources to further explore the topic of fairness in ML, which you’ll find at twimlai.com...
AI for Healthcare with Peter Lee - TWiML Talk #231
February 18, 2019 02:06 - 56 minutesIn this episode, we’re joined by Peter Lee, Corporate Vice President at Microsoft Research responsible for the company’s healthcare initiatives. Peter and I met back at Microsoft Ignite, where he gave me some really interesting takes on AI development in China, which is linked in the show notes. This conversation centers around impact areas Peter sees for AI in healthcare, namely diagnostics and therapeutics, tools, and the future of precision medicine.
An Optimized Recurrent Unit for Ultra-Low Power Acoustic Event Detection with Justice Amoh Jr. - TWiML Talk #230
February 11, 2019 21:43 - 45 minutesToday, we're joined by Justice Amoh Jr., a Ph.D. student at Dartmouth’s Thayer School of Engineering. Justice presented his work on “An Optimized Recurrent Unit for Ultra-Low Power Acoustic Event Detection.” In our conversation, we discuss his goal of bringing low cost, high-efficiency wearables to market for monitoring asthma. We explore the challenges of using classical machine learning models on microcontrollers, and how he went about developing models optimized for constrained hardware e...
Pathologies of Neural Models and Interpretability with Alvin Grissom II - TWiML Talk #229
February 11, 2019 17:49 - 32 minutesToday, we continue our Black in AI series with Alvin Grissom II, Assistant Professor of Computer Science at Ursinus College. In our conversation, we dive into the paper he presented at the workshop, “Pathologies of Neural Models Make Interpretations Difficult.” We talk through some of the “pathological behaviors” he identified in the paper, how we can better understand the overconfidence of trained deep learning models in certain settings, and how we can improve model training with entropy re...
AI for Earth with Lucas Joppa - TWiML Talk #228
February 08, 2019 16:00 - 56 minutesToday we’re joined by Lucas Joppa, Chief Environmental Officer at Microsoft and Zach Parisa, Co-founder and president of Silvia Terra, a Microsoft AI for Earth grantee. In our conversation, we explore the ways that ML & AI can be used to advance our understanding of forests and other ecosystems, supporting conservation efforts. We discuss how Silvia Terra uses computer vision and data from a wide array of sensors, combined with AI, to yield more detailed estimates of the various species in o...
AI for Accessibility with Wendy Chisholm - TWiML Talk #227
February 06, 2019 16:00 - 50 minutesToday we’re joined by Wendy Chisholm, a principal accessibility architect at Microsoft, and one of the chief proponents of the AI for Accessibility program, which extends grants to AI-powered accessibility projects the areas of Employment, Daily Life, and Communication & Connection. In our conversation, we discuss the intersection of AI and accessibility, the lasting impact that innovation in AI can have for people with disabilities and society as a whole, and the importance of projects in th...
AI for Humanitarian Action with Justin Spelhaug - TWiML Talk #226
February 04, 2019 16:00 - 58 minutesToday we're joined by Justin Spelhaug, General Manager of Technology for Social Impact at Microsoft. In our conversation, we discuss the company’s efforts in AI for Humanitarian Action, covering Microsoft’s overall approach to technology for social impact, how his group helps mission-driven organizations best leverage technologies like AI, and how AI is being used at places like the World Bank, Operation Smile, and Mission Measurement to create greater impact.
Teaching AI to Preschoolers with Randi Williams - TWiML Talk #225
January 31, 2019 05:58 - 43 minutesToday, in the first episode of our Black in AI series, we’re joined by Randi Williams, PhD student at the MIT Media Lab. At the Black in AI workshop Randi presented her research on Popbots: A Early Childhood AI Curriculum, which is geared towards teaching preschoolers the fundamentals of artificial intelligence. In our conversation, we discuss the origins of the project, the three AI concepts that are taught in the program, and the goals that Randi hopes to accomplish with her work.
Holistic Optimization of the LinkedIn News Feed - TWiML Talk #224
January 28, 2019 16:28 - 48 minutesToday we’re joined by Tim Jurka, Head of Feed AI at LinkedIn. In our conversation, Tim describes the holistic optimization of the feed and we discuss some of the interesting technical and business challenges associated with trying to do this. We talk through some of the specific techniques used at LinkedIn like Multi-arm Bandits and Content Embeddings, and also jump into a really interesting discussion about organizing for machine learning at scale.
AI at the Edge at Qualcomm with Gary Brotman - TWiML Talk #223
January 24, 2019 16:50 - 51 minutesToday we’re joined by Gary Brotman, Senior Director of Product Management at Qualcomm Technologies, Inc. Gary, who got his start in AI through music, now leads strategy and product planning for the company’s AI and ML technologies, including those that make up the Qualcomm Snapdragon mobile platforms. In our conversation, we discuss AI on mobile devices and at the edge, including popular use cases, and explore some of the various acceleration technologies offered by Qualcomm and others that ...
AI Innovation at CES - TWiML Talk #222
January 21, 2019 19:18 - 2 minutesA few weeks ago, I made the trek to Las Vegas for the world’s biggest electronics conference, CES. In this special visual only episode, we’re going to check out some of the interesting examples of machine learning and AI that I found at the event. Check out the video at https://twimlai.com/ces2019, and be sure to hit the like and subscribe buttons and let us know how you like the show via a comment! For the show notes, visit https://twimlai.com/talk/222.
Self-Tuning Services via Real-Time Machine Learning with Vladimir Bychkovsky - TWiML Talk #221
January 17, 2019 19:34 - 46 minutesToday we’re joined by Vladimir Bychkovsky, Engineering Manager at Facebook, to discuss Spiral, a system they’ve developed for self-tuning high-performance infrastructure services at scale, using real-time machine learning. In our conversation, we explore how the system works, how it was developed, and how infrastructure teams at Facebook can use it to replace hand-tuned parameters set using heuristics with services that automatically optimize themselves in minutes rather than in weeks.
Building a Recommender System from Scratch at 20th Century Fox with JJ Espinoza - TWiML Talk #220
January 14, 2019 20:15 - 34 minutesToday we’re joined by JJ Espinoza, former Director of Data Science at 20th Century Fox. In this talk we dig into JJ and his team’s experience building and deploying a content recommendation system from the ground up. In our conversation, we explore the design of a couple of key components of their system, the first of which processes movie scripts to make recommendations about which movies the studio should make, and the second processes trailers to determine which should be recommended to u...
Legal and Policy Implications of Model Interpretability with Solon Barocas - TWiML Talk #219
January 10, 2019 18:22 - 46 minutesToday we’re joined by Solon Barocas, Assistant Professor of Information Science at Cornell University. Solon and I caught up to discuss his work on model interpretability and the legal and policy implications of the use of machine learning models. In our conversation, we explore the gap between law, policy, and ML, and how to build the bridge between them, including formalizing ethical frameworks for machine learning. We also look at his paper ”The Intuitive Appeal of Explainable Machines.”
Trends in Computer Vision with Siddha Ganju - TWiML Talk #218
January 07, 2019 21:00 - 32 minutesIn the final episode of our AI Rewind series, we’re excited to have Siddha Ganju back on the show. Siddha, who is now an autonomous vehicles solutions architect at Nvidia shares her thoughts on trends in Computer Vision in 2018 and beyond. We cover her favorite CV papers of the year in areas such as neural architecture search, learning from simulation, application of CV to augmented reality, and more, as well as a bevy of tools and open source projects.
Trends in Reinforcement Learning with Simon Osindero - TWiML Talk #217
January 03, 2019 18:26 - 52 minutesIn this episode of our AI Rewind series, we introduce a new friend of the show, Simon Osindero, Staff Research Scientist at DeepMind. We discuss trends in Deep Reinforcement Learning in 2018 and beyond. We’ve packed a bunch into this show, as Simon walks us through many of the important papers and developments seen this year in areas like Imitation Learning, Unsupervised RL, Meta-learning, and more. The complete show notes for this episode can be found at https://twimlai.com/talk/217.
Trends in Natural Language Processing with Sebastian Ruder - TWiML Talk #216
December 31, 2018 16:53 - 52 minutesIn this episode of our AI Rewind series, we’ve brought back recent guest Sebastian Ruder, PhD Student at the National University of Ireland and Research Scientist at Aylien, to discuss trends in Natural Language Processing in 2018 and beyond. In our conversation we cover a bunch of interesting papers spanning topics such as pre-trained language models, common sense inference datasets and large document reasoning and more, and talk through Sebastian’s predictions for the new year.
Trends in Machine Learning with Anima Anandkumar - TWiML Talk #215
December 27, 2018 15:48 - 51 minutesIn this episode of our AI Rewind series, we’re back with Anima Anandkumar, Bren Professor at Caltech and now Director of Machine Learning Research at NVIDIA. Anima joins us to discuss her take on trends in the broader Machine Learning field in 2018 and beyond. In our conversation, we cover not only technical breakthroughs in the field but also those around inclusivity and diversity. For this episode's complete show notes, visit twimlai.com/talk/215.
Trends in Deep Learning with Jeremy Howard - TWiML Talk #214
December 24, 2018 16:43 - 1 hourIn this episode of our AI Rewind series, we’re bringing back one of your favorite guests of the year, Jeremy Howard, founder and researcher at Fast.ai. Jeremy joins us to discuss trends in Deep Learning in 2018 and beyond. We cover many of the papers, tools and techniques that have contributed to making deep learning more accessible than ever to so many developers and data scientists.
Training Large-Scale Deep Nets with RL with Nando de Freitas - TWiML Talk #213
December 20, 2018 17:34 - 55 minutesToday we close out both our NeurIPS series joined by Nando de Freitas, Team Lead & Principal Scientist at Deepmind. In our conversation, we explore his interest in understanding the brain and working towards artificial general intelligence. In particular, we dig into a couple of his team’s NeurIPS papers: “Playing hard exploration games by watching YouTube,” and “One-Shot high-fidelity imitation: Training large-scale deep nets with RL.”
Making Algorithms Trustworthy with David Spiegelhalter - TWiML Talk #212
December 20, 2018 01:00 - 23 minutesToday we’re joined by David Spiegelhalter, Chair of Winton Center for Risk and Evidence Communication at Cambridge University and President of the Royal Statistical Society. David, an invited speaker at NeurIPS, presented on “Making Algorithms Trustworthy: What Can Statistical Science Contribute to Transparency, Explanation and Validation?”. In our conversation, we explore the nuanced difference between being trusted and being trustworthy, and its implications for those building AI systems.
Designing Computer Systems for Software with Kunle Olukotun - TWiML Talk #211
December 18, 2018 00:38 - 55 minutesToday we’re joined by Kunle Olukotun, Professor in the department of EE and CS at Stanford University, and Chief Technologist at Sambanova Systems. Kunle was an invited speaker at NeurIPS this year, presenting on “Designing Computer Systems for Software 2.0.” In our conversation, we discuss various aspects of designing hardware systems for machine and deep learning, touching on multicore processor design, domain specific languages, and graph-based hardware. This was a fun one!
Operationalizing Ethical AI with Kathryn Hume - TWiML Talk #210
December 14, 2018 17:49 - 53 minutesToday we conclude our Trust in AI series with this conversation with Kathryn Hume, VP of Strategy at Integrate AI. We discuss her newly released white paper “Responsible AI in the Consumer Enterprise,” which details a framework for ethical AI deployment in e-commerce companies and other consumer-facing enterprises. We look at the structure of the ethical framework she proposes, and some of the many questions that need to be considered when deploying AI in an ethical manner.
Approaches to Fairness in Machine Learning with Richard Zemel - TWiML Talk #209
December 12, 2018 22:29 - 45 minutesToday we continue our exploration of Trust in AI with this interview with Richard Zemel, Professor in the department of Computer Science at the University of Toronto and Research Director at Vector Institute. In our conversation, Rich describes some of his work on fairness in machine learning algorithms, including how he defines both group and individual fairness and his group’s recent NeurIPS poster, “Predict Responsibly: Improving Fairness and Accuracy by Learning to Defer.”
Trust and AI with Parinaz Sobhani - TWiML Talk #208
December 11, 2018 16:53 - 46 minutesIn today’s episode we’re joined by Parinaz Sobhani, Director of Machine Learning at Georgian Partners. In our conversation, Parinaz and I discuss some of the main issues falling under the “trust” umbrella, such as transparency, fairness and accountability. We also explore some of the trust-related projects she and her team at Georgian are working on, as well as some of the interesting trust and privacy papers coming out of the NeurIPS conference.
Unbiased Learning from Biased User Feedback with Thorsten Joachims - TWiML Talk #207
December 07, 2018 19:04 - 40 minutesIn the final episode of our re:Invent series, we're joined by Thorsten Joachims, Professor in the Department of Computer Science at Cornell University. We discuss his presentation “Unbiased Learning from Biased User Feedback,” looking at some of the inherent and introduced biases in recommender systems, and the ways to avoid them. We also discuss how inference techniques can be used to make learning algorithms more robust to bias, and how these can be enabled with the correct type of logging ...
Language Parsing and Character Mining with Jinho Choi - TWiML Talk #206
December 05, 2018 22:31 - 47 minutesToday we’re joined by Jinho Choi, assistant professor of computer science at Emory University. Jinho presented at the conference on ELIT, their cloud-based NLP platform. In our conversation, we discuss some of the key NLP challenges that Jinho and his group are tackling, including language parsing and character mining. We also discuss their vision for ELIT, which is to make it easy for researchers to develop, access, and deploying cutting-edge NLP tools models on the cloud.
re:Invent Roundup Roundtable 2018 with Dave McCrory and Val Bercovici - TWiML Talk #205
December 03, 2018 19:36 - 1 hourI’m excited to present our second annual re:Invent Roundtable Roundup. This year I’m joined by Dave McCrory, VP of Software Engineering at Wise.io at GE Digital, and Val Bercovici, Founder and CEO of Pencil Data. If you missed the news coming out of re:Invent, we cover all of AWS’ most important ML and AI announcements, including SageMaker Ground Truth, Reinforcement Learning, DeepRacer, Inferentia and Elastic Inference, ML Marketplace and much more. For the show notes visit https://twimlai....
Knowledge Graphs and Expert Augmentation with Marisa Boston - TWiML Talk #204
November 29, 2018 23:34 - 46 minutesToday we’re joined by Marisa Boston, Director of Cognitive Technology in KPMG’s Cognitive Automation Lab. We caught up to discuss some of the ways that KPMG is using AI to build tools that help augment the knowledge of their teams of professionals. We discuss knowledge graphs and how they can be used to map out and relate various concepts and how they use these in conjunction with NLP tools to create insight engines. We also look at tools that curate and contextualize news and other text-base...
ML/DL for Non-Stationary Time Series Analysis in Financial Markets and Beyond with Stuart Reid - TWiML Talk #203
November 26, 2018 21:59 - 58 minutesToday, we’re joined by Stuart Reid, Chief Scientist at NMRQL Research. NMRQL is an investment management firm that uses ML algorithms to make adaptive, unbiased, scalable, and testable trading decisions for its funds. In our conversation, Stuart and I dig into the way NMRQL uses ML and DL models to support the firm’s investment decisions. We focus on techniques for modeling non-stationary time-series, stationary vs non-stationary time-series, and challenges of building models using financial...