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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Trends in Machine Learning & Deep Learning with Zack Lipton - #334
30 december 2019 · 1 uur 20 min
Today we kick off our 2019 AI Rewind Series joined by Zack Lipton, Professor at CMU. Lees meer
You might remember Zack from our conversation earlier this year, “Fairwashing” and the Folly of ML Solutionism. In today's conversation, Zack recaps advancements across the vast fields of Machine Learning and Deep Learning, including trends, tools, research papers and more.
We want to hear from you! Send your thoughts on the year that was 2019 below in the comments, or via Twitter @samcharrington or @twimlai.
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FaciesNet & Machine Learning Applications in Energy with Mohamed Sidahmed - #333
27 december 2019 · 40 min
Today we close out our 2019 NeurIPS series with Mohamed Sidahmed, Machine Learning and Artificial Intelligence R&D Manager at Shell. In our conversation, we discuss two papers Mohamed and his team submitted to the conference this year, Accelerating Least Squares Imaging Using Deep Learning Techniques, and FaciesNet: Machine Learning Applications for Facies Classification in Well Logs. The show notes for this episode can be found at twimlai.com/talk/333/, where you’ll find links to both of these papers! Lees meer
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Machine Learning: A New Approach to Drug Discovery with Daphne Koller - #332
26 december 2019 · 43 min
Today we’re joined by Daphne Koller, co-Founder and former co-CEO of Coursera and Founder and CEO of Insitro. In our conversation, discuss the current landscape of pharmaceutical drugs and drug discovery, including the current pricing of drugs, and an overview of Insitro’s goal of using ML as a “compass” in drug discovery. We also explore how Insitro functions as a company, their focus on the biology of drug discovery and the landscape of ML techniques being used, Daphne’s thoughts on AutoML, and Lees meer
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Sensory Prediction Error Signals in the Neocortex with Blake Richards - #331
24 december 2019 · 40 min
Today we continue our 2019 NeurIPS coverage, this time around joined by Blake Richards, Assistant Professor at McGill University and a Core Faculty Member at Mila. Blake was an invited speaker at the Neuro-AI Workshop, and presented his research on “Sensory Prediction Error Signals in the Neocortex.” In our conversation, we discuss a series of recent studies on two-photon calcium imaging. We talk predictive coding, hierarchical inference, and Blake’s recent work on memory systems for reinforcement lea Lees meer
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How to Know with Celeste Kidd - #330
23 december 2019 · 53 min
Today we’re joined by Celeste Kidd, Assistant Professor at UC Berkeley, to discuss her invited talk “How to Know” which details her lab’s research about the core cognitive systems people use to guide their learning about the world. We explore why people are curious about some things but not others, and how past experiences and existing knowledge shape future interests, why people believe what they believe, and how these beliefs are influenced, and how machine learning figures into the equation. Lees meer
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Using Deep Learning to Predict Wildfires with Feng Yan - #329
20 december 2019 · 51 min
Today we’re joined by Feng Yan, Assistant Professor at the University of Nevada, Reno to discuss ALERTWildfire, a camera-based network infrastructure that captures satellite imagery of wildfires. In our conversation, Feng details the development of the machine learning models and surrounding infrastructure. We also talk through problem formulation, challenges with using camera and satellite data in this use case, and how he has combined the use of IaaS and FaaS tools for cost-effectiveness and scalability Lees meer
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Advancing Machine Learning at Capital One with Dave Castillo - #328
19 december 2019 · 47 min
Today we’re joined by Dave Castillo, Managing VP for ML at Capital One and head of their Center for Machine Learning. In our conversation, we explore Capital One’s transition from “lab-based” ML to enterprise-wide adoption and support of ML, surprising ML use cases, their current platform ecosystem, their design vision in building this into a larger, all-encompassing platform, pain points in building this platform, and much more. Lees meer
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Helping Fish Farmers Feed the World with Deep Learning w/ Bryton Shang - #327
17 december 2019 · 38 min
Today we’re joined by Bryton Shang, Founder & CEO at Aquabyte, a company focused on the application of computer vision to various fish farming use cases. In our conversation, we discuss how Bryton identified the various problems associated with mass fish farming, challenges developing computer algorithms that can measure the height and weight of fish, assess issues like sea lice, and how they’re developing interesting new features such as facial recognition for fish! Lees meer
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Metaflow, a Human-Centric Framework for Data Science with Ville Tuulos - #326
13 december 2019 · 56 min
Today we kick off our re:Invent 2019 series with Ville Tuulos, Machine Learning Infrastructure Manager at Netflix. At re:Invent, Netflix announced the open-sourcing of Metaflow, their “human-centric framework for data science.” In our conversation, we discuss all things Metaflow, including features, user experience, tooling, supported libraries, and much more. Lees meer
If you’re interested in checking out a Metaflow democast with Villa, reach out at twimlai.com/contact!
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Single Headed Attention RNN: Stop Thinking With Your Head with Stephen Merity - #325
12 december 2019 · 59 min
Today we’re joined by Stephen Merity, an independent researcher focused on NLP and Deep Learning. In our conversation, we discuss Stephens latest paper, Single Headed Attention RNN: Stop Thinking With Your Head, detailing his primary motivations behind the paper, the decision to use SHA-RNNs for this research, how he built and trained the model, his approach to benchmarking, and finally his goals for the research in the broader research community. Lees meer
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Automated Model Tuning with SigOpt - #324
9 december 2019 · 46 min
In this TWIML Democast, we're joined by SigOpt Co-Founder and CEO Scott Clark. Scott details the SigOpt platform, and gives us a live demo! Lees meer
This episode is best consumed by watching the corresponding video demo, which you can find at twimlai.com/talk/324.
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Automated Machine Learning with Erez Barak - #323
6 december 2019 · 43 min
Today we’re joined by Erez Barak, Partner Group Manager of Azure ML at Microsoft. In our conversation, Erez gives us a full breakdown of his AutoML philosophy, and his take on the AutoML space, its role, and its importance. We also discuss the application of AutoML as a contributor to the end-to-end data science process, which Erez breaks down into 3 key areas; Featurization, Learner/Model Selection, and Tuning/Optimizing Hyperparameters. We also discuss post-deployment AutoML use cases, and much more! Lees meer
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Responsible AI in Practice with Sarah Bird - #322
4 december 2019 · 38 min
Today we continue our Azure ML at Microsoft Ignite series joined by Sarah Bird, Principal Program Manager at Microsoft. At Ignite, Microsoft released new tools focused on responsible machine learning, which fall under the umbrella of the Azure ML 'Machine Learning Interpretability Toolkit.’ In our conversation, Sarah walks us this toolkit, detailing use cases and the user experience. We also discuss her work in differential privacy, and in the broader ML community, in particular, the MLSys conference. Lees meer
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Enterprise Readiness, MLOps and Lifecycle Management with Jordan Edwards - #321
2 december 2019 · 39 min
Today we’re joined by Jordan Edwards, Principal Program Manager for MLOps on Azure ML at Microsoft. In our conversation, Jordan details how Azure ML accelerates model lifecycle management with MLOps, which enables data scientists to collaborate with IT teams to increase the pace of model development and deployment. We discuss various problems associated with generalizing ML at scale at Microsoft, what exactly MLOps is, the “four phases” along the journey of customer implementation of MLOps, and much m Lees meer
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DevOps for ML with Dotscience - #320
26 november 2019 · 47 min
Today we’re joined by Luke Marsden, Founder and CEO of Dotscience. Luke walks us through the Dotscience platform and their manifesto on DevOps for ML. Lees meer
Thanks to Luke and Dotscience for their sponsorship of this Democast and their continued support of TWIML.
Head to https://twimlai.com/democast/dotscience to watch the full democast!
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Building an Autonomous Knowledge Graph with Mike Tung - #319
21 november 2019 · 44 min
Today we’re joined by Mike Tung, Founder, and CEO of Diffbot. In our conversation, we discuss Diffbot’s Knowledge Graph, including how it differs from more mainstream use cases like Google Search and MSFT Bing. We also discuss the developer experience with the knowledge graph and other tools, like Extraction API and Crawlbot, challenges like knowledge fusion, balancing being a research company that is also commercially viable, and how they approach their role in the research community. Lees meer
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The Next Generation of Self-Driving Engineers with Aaron Ma - Talk #318
18 november 2019 · 48 min
Today we’re joined by our youngest guest ever (by far), Aaron Ma, an 11-year-old middle school student and machine learning engineer in training. Aaron has completed over 80(!) Coursera courses and is the recipient of 3 Udacity nano-degrees. In our conversation, we discuss Aaron’s research interests in reinforcement learning and self-driving cars, his journey from programmer to ML engineer, his experiences participating in kaggle competitions, and how he balances his passion for ML with day-to-day life. Lees meer
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Spiking Neural Networks: A Primer with Terrence Sejnowski - #317
14 november 2019 · 50 min
On today’s episode, we’re joined by Terrence Sejnowski, to discuss the ins and outs of spiking neural networks, including brain architecture, the relationship between neuroscience and machine learning, and ways to make NN’s more efficient through spiking. Terry also gives us some insight into hardware used in this field, characterizes the major research problems currently being undertaken, and the future of spiking networks. Lees meer
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Bridging the Patient-Physician Gap with ML and Expert Systems w/ Xavier Amatriain - #316
11 november 2019 · 39 min
Today we’re joined by return guest Xavier Amatriain, Co-founder and CTO of Curai, whose goal is to make healthcare accessible and scaleable while bringing down costs. In our conversation, we touch on the shortcomings of traditional primary care, and how Curai fills that role, and some of the unique challenges his team faces in applying ML in the healthcare space. We also discuss the use of expert systems, how they train them, and how NLP projects like BERT and GPT-2 fit into what they’re building. Lees meer
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What Does it Mean for a Machine to "Understand"? with Thomas Dietterich - #315
7 november 2019 · 38 min
Today we have the pleasure of being joined by Tom Dietterich, Distinguished Professor Emeritus at Oregon State University. Tom recently wrote a blog post titled "What does it mean for a machine to “understand”, and in our conversation, he goes into great detail on his thoughts. We cover a lot of ground, including Tom’s position in the debate, his thoughts on the role of systems like deep learning in potentially getting us to AGI, the “hype engine” around AI advancements, and so much more. Lees meer
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Scaling TensorFlow at LinkedIn with Jonathan Hung - #314
4 november 2019 · 35 min
Today we’re joined by Jonathan Hung, Sr. Software Engineer at LinkedIn. Jonathan presented at TensorFlow world last week, titled Scaling TensorFlow at LinkedIn. In our conversation, we discuss their motivation for using TensorFlow on their pre-existing Hadoop clusters infrastructure, TonY, or TensorFlow on Yard, LinkedIn’s framework that natively runs deep learning jobs on Hadoop, and its relationship with Pro-ML, LinkedIn’s internal AI Platform, and their foray into using Kubernetes for research. Lees meer
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Machine Learning at GitHub with Omoju Miller - #313
31 oktober 2019 · 44 min
Today we’re joined by Omoju Miller, a Sr. machine learning engineer at GitHub. In our conversation, we discuss: Lees meer
• Her dissertation, Hiphopathy, A Socio-Curricular Study of Introductory Computer Science,
• Her work as an inaugural member of the Github machine learning team
• Her two presentations at Tensorflow World, “Why is machine learning seeing exponential growth in its communities” and “Automating your developer workflow on GitHub with Tensorflow.” -
Using AI to Diagnose and Treat Neurological Disorders with Archana Venkataraman - #312
28 oktober 2019 · 47 min
Today we’re joined by Archana Venkataraman, John C. Malone Assistant Professor of Electrical and Computer Engineering at Johns Hopkins University. Archana’s research at the Neural Systems Analysis Laboratory focuses on developing tools, frameworks, and algorithms to better understand, and treat neurological and psychiatric disorders, including autism, epilepsy, and others. We explore her work applying machine learning to these problems, including biomarker discovery, disorder severity prediction and mor Lees meer
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Deep Learning for Earthquake Aftershock Patterns with Phoebe DeVries & Brendan Meade - #311
25 oktober 2019 · 36 min
Today we are joined by Phoebe DeVries, Postdoctoral Fellow in the Department of Earth and Planetary Sciences at Harvard and Brendan Meade, Professor of Earth and Planetary Sciences at Harvard. Phoebe and Brendan’s work is focused on discovering as much as possible about earthquakes before they happen, and by measuring how the earth’s surface moves, predicting future movement location, as seen in their paper: ‘Deep learning of aftershock patterns following large earthquakes'. Lees meer
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Live from TWIMLcon! Operationalizing Responsible AI - #310
22 oktober 2019 · 31 min
An often forgotten about topic garnered high praise at TWIMLcon this month: operationalizing responsible and ethical AI. This important topic was combined with an impressive panel of speakers, including: Rachel Thomas, Director, Center for Applied Data Ethics at the USF Data Institute, Guillaume Saint-Jacques, Head of Computational Science at LinkedIn, and Parinaz Sobahni, Director of Machine Learning at Georgian Partners, moderated by Khari Johnson, Senior AI Staff Writer at VentureBeat. Lees meer
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Live from TWIMLcon! Scaling ML in the Traditional Enterprise - #309
18 oktober 2019 · 34 min
Machine learning and AI is finding a place in the traditional enterprise - although the path to get there is different. In this episode, our panel analyzes the state and future of larger, more established brands. Hear from Amr Awadallah, Founder and Global CTO of Cloudera, Pallav Agrawal, Director of Data Science at Levi Strauss & Co., and Jürgen Weichenberger, Data Science Senior Principal & Global AI Lead at Accenture, moderated by Josh Bloom, Professor at UC Berkeley. Lees meer
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Live from TWIMLcon! Culture & Organization for Effective ML at Scale (Panel) - #308
15 oktober 2019 · 28 min
TWIMLcon brought together so many in the ML/AI community to discuss the unique challenges to building and scaling machine learning platforms. In this episode, hear about changing the way companies think about machine learning from a diverse set of panelists including Pardis Noorzad, Data Science Manager at Twitter, Eric Colson, Chief Algorithms Officer Emeritus at Stitch Fix, and Jennifer Prendki, Founder & CEO at Alectio, moderated by Maribel Lopez, Founder & Principal Analyst at Lopez Research. Lees meer
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Live from TWIMLcon! Use-Case Driven ML Platforms with Franziska Bell - #307
10 oktober 2019 · 32 min
Today we're Franziska Bell, Ph.D., the Director of Data Science Platforms at Uber, who joined Sam on stage at TWIMLcon last week. Fran provided a look into the cutting edge data science available company-wide at the push of a button. Since joining Uber, Fran has developed a portfolio of platforms, ranging from forecasting to conversational AI. Hear how use cases can strategically guide platform development, the evolving relationship between her team and Michelangelo (Uber’s ML Platform) and much more! Lees meer
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Live from TWIMLcon! Operationalizing ML at Scale with Hussein Mehanna - #306
8 oktober 2019 · 34 min
The live interviews from TWIMLcon continue with Hussein Mehanna, Head of ML and AI at Cruise. From his start at Facebook to his current work at Cruise, Hussein has seen first hand what it takes to scale and sustain machine learning programs. Hear him discuss the challenges (and joys) of working in the industry, his insight into analyzing scale when innovation is happening in parallel with development, his experiences at Facebook, Google, and Cruise, and his predictions for the future of ML platforms! Lees meer
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Live from TWIMLcon! Encoding Company Culture in Applied AI Systems - #305
4 oktober 2019 · 32 min
In this episode, Sam is joined by Deepak Agarwal, VP of Engineering at LinkedIn, who graced the stage at TWIMLcon: AI Platforms for a keynote interview. Deepak shares the impact that standardizing processes and tools have on a company’s culture and productivity levels, and best practices to increasing ML ROI. He also details the Pro-ML initiative for delivering machine learning systems at scale, specifically looking at aligning improvement of tooling and infrastructure with the pace of innovation and more Lees meer
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Live from TWIMLcon! Overcoming the Barriers to Deep Learning in Production with Andrew Ng - #304
1 oktober 2019 · 34 min
Earlier today, Andrew Ng joined us onstage at TWIMLcon - as the Founder and CEO of Landing AI and founding lead of Google Brain, Andrew is no stranger to knowing what it takes for AI and machine learning to be successful. Hear about the work that Landing AI is doing to help organizations adopt modern AI, his experience in overcoming challenges for large companies, how enterprises can get the most value for their ML investment as well as addressing the ‘essential complexity’ of software engineering. Lees meer
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The Future of Mixed-Autonomy Traffic with Alexandre Bayen - #303
27 september 2019 · 44 min
Today we are joined by Alexandre Bayen, Director of the Institute for Transportation Studies and Professor at UC Berkeley. Alex's current research is in mixed-autonomy traffic to understand how the growing automation in self-driving vehicles can be used to improve mobility and flow of traffic. At the AWS re:Invent conference last year, Alex presented on the future of mixed-autonomy traffic and the two major revolutions he predicts will take place in the next 10-15 years. Lees meer
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Deep Reinforcement Learning for Logistics at Instadeep with Karim Beguir - #302
25 september 2019 · 44 min
Today we are joined by Karim Beguir, Co-Founder and CEO of InstaDeep, a company focusing on building advanced decision-making systems for the enterprise. In this episode, we focus on logistical problems that require decision-making in complex environments using deep learning and reinforcement learning. Karim explains the InstaDeep process and mindset, where they get their data sets, the efficiency of RL, heuristic vs learnability approaches and how explainability fits into the model. Lees meer
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Deep Learning with Structured Data w/ Mark Ryan - #301
19 september 2019 · 40 min
Today we're joined by Mark Ryan, author of the upcoming book Deep Learning with Structured Data. Working on the support team at IBM Data and AI, he saw a lack of general structured data sets people could apply their models to. Using the streetcar network in Toronto, Mark gathered an open data set that started the research for his latest book. In this episode, Mark shares the benefits of applying deep learning to structured data, details of his experience with a range of data sets, and details his new book. Lees meer
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Time Series Clustering for Monitoring Fueling Infrastructure Performance with Kalai Ramea - #300
18 september 2019 · 30 min
Today we're joined by Kalai Ramea, Data Scientist at PARC, a Xerox Company. In this episode we discuss her journey buying a hydrogen car and the subsequent journey and paper that followed assessing fueling stations. In her next paper, Kalai looked at fuel consumption at hydrogen stations and used temporal clustering to identify signatures of usage over time. As the number of fueling stations is planned to increase dramatically in the future, building reliability on their performance is crucial. Lees meer
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Swarm AI for Event Outcome Prediction with Gregg Willcox - TWIML Talk #299
13 september 2019 · 41 min
Today we're joined by Gregg Willcox, Director of Research and Development at Unanimous AI. Inspired by the natural phenomenon called 'swarming', which uses the collective intelligence of a group to produce more accurate results than an individual alone, ‘Swarm AI’ was born. A game-like platform that channels the convictions of individuals to come to a consensus and using a behavioral neural network trained on people’s behavior called ‘Conviction’, to further amplify the results. Lees meer
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Rebooting AI: What's Missing, What's Next with Gary Marcus - TWIML Talk #298
10 september 2019 · 48 min
Today we're joined by Gary Marcus, CEO and Founder at Robust.AI, well-known scientist, bestselling author, professor and entrepreneur. Hear Gary discuss his latest book, ‘Rebooting AI: Building Artificial Intelligence We Can Trust’, an extensive look into the current gaps, pitfalls and areas for improvement in the field of machine learning and AI. In this episode, Gary provides insight into what we should be talking and thinking about to make even greater (and safer) strides in AI. Lees meer
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DeepQB: Deep Learning to Quantify Quarterback Decision-Making with Brian Burke - TWIML Talk #297
5 september 2019 · 51 min
Today we're joined by Brian Burke, Analytics Specialist with the Stats & Information Group at ESPN. A former Navy pilot and lifelong football fan, Brian saw the correlation between fighter pilots and quarterbacks in the quick decisions both roles make on a regular basis. In this episode, we discuss his paper: “DeepQB: Deep Learning with Player Tracking to Quantify Quarterback Decision-Making & Performance”, what it means for football, and his excitement for machine learning in sports. Lees meer
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Measuring Performance Under Pressure Using ML with Lotte Bransen - TWIML Talk #296
3 september 2019 · 35 min
Today we're joined by Lotte Bransen, a Scientific Researcher at SciSports. With a background in mathematics, econometrics, and soccer, Lotte has honed her research on analytics of the game and its players, using trained models to understand the impact of mental pressure on a player’s performance. In this episode, Lotte discusses her paper, ‘Choke or Shine? Quantifying Soccer Players' Abilities to Perform Under Mental Pressure’ and the implications of her research in the world of sports. Lees meer
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Managing Deep Learning Experiments with Lukas Biewald - TWIML Talk #295
29 augustus 2019 · 42 min
Today we're joined by Lukas Biewald, CEO and Co-Founder of Weights & Biases. Lukas founded the company after seeing a need for reproducibility in deep learning experiments. In this episode, we discuss his experiment tracking tool, how it works, the components that make it unique, and the collaborative culture that Lukas promotes. Listen in to how he got his start in deep learning and experiment tracking, the current Weights & Biases success strategy, and what his team is working on today. Lees meer
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Re-Architecting Data Science at iRobot with Angela Bassa - TWIML Talk #294
26 augustus 2019 · 49 min
Today we’re joined by Angela Bassa, Director of Data Science at iRobot. In our conversation, Angela and I discuss: Lees meer
• iRobot's re-architecture, and a look at the evolution of iRobot.
• Where iRobot gets its data from and how they taxonomize data science.
• The platforms and processes that have been put into place to support delivering models in production.
•The role of DevOps in bringing these various platforms together, and much more!
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Disentangled Representations & Google Research Football with Olivier Bachem - TWIML Talk #293
22 augustus 2019 · 43 min
Today we’re joined by Olivier Bachem, a research scientist at Google AI on the Brain team. Lees meer
Olivier joins us to discuss his work on Google’s research football project, their foray into building a novel reinforcement learning environment. Olivier and Sam discuss what makes this environment different than other available RL environments, such as OpenAI Gym and PyGame, what other techniques they explored while using this environment, and what’s on the horizon for their team and Football RLE.
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Neural Network Quantization and Compression with Tijmen Blankevoort - TWIML Talk #292
19 augustus 2019 · 50 min
Today we’re joined by Tijmen Blankevoort, a staff engineer at Qualcomm, who leads their compression and quantization research teams. In our conversation with Tijmen we discuss: Lees meer
• The ins and outs of compression and quantization of ML models, specifically NNs,
• How much models can actually be compressed, and the best way to achieve compression,
• We also look at a few recent papers including “Lottery Hypothesis."
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Identifying New Materials with NLP with Anubhav Jain - TWIML Talk #291
15 augustus 2019 · 40 min
Today we are joined by Anubhav Jain, Staff Scientist & Chemist at Lawrence Berkeley National Lab. We discuss his latest paper, ‘Unsupervised word embeddings capture latent knowledge from materials science literature’. Anubhav explains the design of a system that takes the literature and uses natural language processing to conceptualize complex material science concepts. He also discusses scientific literature mining and how the method can recommend materials for functional applications in the future. Lees meer
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The Problem with Black Boxes with Cynthia Rudin - TWIML Talk #290
14 augustus 2019 · 48 min
Today we are joined by Cynthia Rudin, Professor of Computer Science, Electrical and Computer Engineering, and Statistical Science at Duke University. In this episode we discuss her paper, ‘Please Stop Explaining Black Box Models for High Stakes Decisions’, and how interpretable models make for more comprehensible decisions - extremely important when dealing with human lives. Cynthia explains black box and interpretable models, their development, use cases, and her future plans in the field. Lees meer
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Human-Robot Interaction and Empathy with Kate Darling - TWIML Talk #289
8 augustus 2019 · 44 min
Today we’re joined by Dr. Kate Darling, Research Specialist at the MIT Media Lab. Kate’s focus is on robot ethics, the social implication of how people treat robots and the purposeful design of robots in our daily lives. We discuss measuring empathy, the impact of robot treatment on kids behavior, the correlation between animals and robots, and why 'effective' robots aren’t always humanoid. Kate combines a wealth of knowledge with an analytical mind that questions the why and how of human-robot intera Lees meer
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Automated ML for RNA Design with Danny Stoll - TWIML Talk #288
5 augustus 2019 · 37 min
Today we’re joined by Danny Stoll, Research Assistant at the University of Freiburg. Danny’s current research can be encapsulated in his latest paper, ‘Learning to Design RNA’. In this episode, Danny explains the design process through reverse engineering and how his team’s deep learning algorithm is applied to train and design sequences. We discuss transfer learning, multitask learning, ablation studies, hyperparameter optimization and the difference between chemical and statistical based approac Lees meer
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Developing a brain atlas using deep learning with Theofanis Karayannis - TWIML Talk #287
1 augustus 2019 · 37 min
Today we’re joined by Theofanis Karayannis, Assistant Professor at the Brain Research Institute of the University of Zurich. Theo’s research is focused on brain circuit development and uses Deep Learning methods to segment the brain regions, then detect the connections around each region. He then looks at the distribution of connections that make neurological decisions in both animals and humans every day. From the way images of the brain are collected to genetic trackability, this episode has it all. Lees meer
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Environmental Impact of Large-Scale NLP Model Training with Emma Strubell - TWIML Talk #286
29 juli 2019 · 37 min
Today we’re joined by Emma Strubell, currently a visiting scientist at Facebook AI Research. Emma’s focus is bringing state of the art NLP systems to practitioners by developing efficient and robust machine learning models. Her paper, Energy and Policy Considerations for Deep Learning in NLP, reviews carbon emissions of training neural networks despite an increase in accuracy. In this episode, we discuss Emma’s research methods, how companies are reacting to environmental concerns, and how we can do b Lees meer
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“Fairwashing” and the Folly of ML Solutionism with Zachary Lipton - TWIML Talk #285
25 juli 2019 · 1 uur 15 min
Today we’re joined by Zachary Lipton, Assistant Professor in the Tepper School of Business. With a theme of data interpretation, Zachary’s research is focused on machine learning in healthcare, with the goal of assisting physicians through the diagnosis and treatment process. We discuss supervised learning in the medical field, robustness under distribution shifts, ethics in machine learning systems across industries, the concept of ‘fairwashing, and more. Lees meer