Quantum Machine Learning: The Next Frontier? with Iordanis Kerenidis - #397
Today we're joined by Iordanis Kerenidis, Research Director CNRS Paris and Head of Quantum Algorithms at QC Ware. Iordanis was an ICML main conference Keynote speaker on the topic of Quantum ML, and we focus our conversation on his presentation, exploring the prospects and challenges of quantum machine learning, as well as the field’s history, evolution, and future. We’ll also discuss the foundations of quantum computing, and some of the challenges to consider for breaking into the field.
4 Elo 20201h
ML and Epidemiology with Elaine Nsoesie - #396
Today we continue our ICML series with Elaine Nsoesie, assistant professor at Boston University. In our conversation, we discuss the different ways that machine learning applications can be used to address global health issues, including infectious disease surveillance, and tracking search data for changes in health behavior in African countries. We also discuss COVID-19 epidemiology and the importance of recognizing how the disease is affecting people of different races and economic backgrounds.
30 Heinä 202046min
Language (Technology) Is Power: Exploring the Inherent Complexity of NLP Systems with Hal Daumé III - #395
Today we’re joined by Hal Daume III, professor at the University of Maryland and Co-Chair of the 2020 ICML Conference. We had the pleasure of catching up with Hal ahead of this year's ICML to discuss his research at the intersection of bias, fairness, NLP, and the effects language has on machine learning models, exploring language in two categories as they appear in machine learning models and systems: (1) How we use language to interact with the world, and (2) how we “do” language.
27 Heinä 20201h 2min
Graph ML Research at Twitter with Michael Bronstein - #394
Today we’re excited to be joined by return guest Michael Bronstein, Head of Graph Machine Learning at Twitter. In our conversation, we discuss the evolution of the graph machine learning space, his new role at Twitter, and some of the research challenges he’s faced, including scalability and working with dynamic graphs. Michael also dives into his work on differential graph modules for graph CNNs, and the various applications of this work.
23 Heinä 202055min
Panel: The Great ML Language (Un)Debate! - #393
Today we’re excited to bring ‘The Great ML Language (Un)Debate’ to the podcast! In the latest edition of our series of live discussions, we brought together experts and enthusiasts to discuss both popular and emerging programming languages for machine learning, along with the strengths, weaknesses, and approaches offered by Clojure, JavaScript, Julia, Probabilistic Programming, Python, R, Scala, and Swift. We round out the session with an audience Q&A (58:28).
20 Heinä 20201h 34min
What the Data Tells Us About COVID-19 with Eric Topol - #392
Today we’re joined by Eric Topol, Director & Founder of the Scripps Research Translational Institute, and author of the book Deep Medicine. We caught up with Eric to talk through what we’ve learned about the coronavirus since it's emergence, and the role of tech in understanding and preventing the spread of the disease. We also explore the broader opportunity for medical applications of AI, the promise of personalized medicine, and how techniques like federated learning can offer more privacy in healthc
16 Heinä 202042min
The Case for Hardware-ML Model Co-design with Diana Marculescu - #391
Today we’re joined by Diana Marculescu, Professor of Electrical and Computer Engineering at UT Austin. We caught up with Diana to discuss her work on hardware-aware machine learning. In particular, we explore her keynote, “Putting the “Machine” Back in Machine Learning: The Case for Hardware-ML Model Co-design” from CVPR 2020. We explore how her research group is focusing on making models more efficient so that they run better on current hardware systems, and how they plan on achieving true co
13 Heinä 202045min
Computer Vision for Remote AR with Flora Tasse - #390
Today we conclude our CVPR coverage joined by Flora Tasse, Head of Computer Vision & AI Research at Streem. Flora, a keynote speaker at the AR/VR workshop, walks us through some of the interesting use cases at the intersection of AI, CV, and AR technologies, her current work and the origin of her company Selerio, which was eventually acquired by Streem, the difficulties associated with building 3D mesh environments, extracting metadata from those environments, the challenges of pose estimation and more.
9 Heinä 202040min
