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The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

Sam Charrington

153
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361
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The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

Sam Charrington

153
Followers
361
Plays
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About Us

Machine 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, deep learning, computer science, data science and more.

Latest Episodes

Computer Vision for Remote AR with Flora Tasse

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.

40 MIN2 d ago
Comments
Computer Vision for Remote AR with Flora Tasse

Deep Learning for Automatic Basketball Video Production with Julian Quiroga

Today we're Julian Quiroga, a Computer Vision Team Lead at Genius Sports, to discuss his recent paper “As Seen on TV: Automatic Basketball Video Production using Gaussian-based Actionness and Game States Recognition.” We explore camera setups and angles, detection and localization of figures on the court (players, refs, and of course, the ball), and the role that deep learning plays in the process. We also break down how this work applies to different sports, and the ways that he is looking to improve i

42 MIN5 d ago
Comments
Deep Learning for Automatic Basketball Video Production with Julian Quiroga

How External Auditing is Changing the Facial Recognition Landscape with Deb Raji

Today we’re taking a break from our CVPR coverage to bring you this interview with Deb Raji, a Technology Fellow at the AI Now Institute. Recently there have been quite a few major news stories in the AI community, including the self-imposed moratorium on facial recognition tech from Amazon, IBM and Microsoft. In our conversation with Deb, we dig into these stories, discussing the origins of Deb’s work on the Gender Shades project, the harms of facial recognition, and much more.

81 MIN1 w ago
Comments
How External Auditing is Changing the Facial Recognition Landscape with Deb Raji

AI for High-Stakes Decision Making with Hima Lakkaraju

Today we’re joined by Hima Lakkaraju, an Assistant Professor at Harvard University. At CVPR, Hima was a keynote speaker at the Fair, Data-Efficient and Trusted Computer Vision Workshop, where she spoke on Understanding the Perils of Black Box Explanations. Hima talks us through her presentation, which focuses on the unreliability of explainability techniques that center perturbations, such as LIME or SHAP, as well as how attacks on these models can be carried out, and what they look like.

45 MIN1 w ago
Comments
AI for High-Stakes Decision Making with Hima Lakkaraju

Invariance, Geometry and Deep Neural Networks with Pavan Turaga

We continue our CVPR coverage with today’s guest, Pavan Turaga, Associate Professor at Arizona State University. Pavan gave a keynote presentation at the Differential Geometry in CV and ML Workshop, speaking on Revisiting Invariants with Geometry and Deep Learning. We go in-depth on Pavan’s research on integrating physics-based principles into computer vision. We also discuss the context of the term “invariant,” and Pavan contextualizes this work in relation to Hinton’s similar Capsule Network res

47 MIN2 w ago
Comments
Invariance, Geometry and Deep Neural Networks with Pavan Turaga

Channel Gating for Cheaper and More Accurate Neural Nets with Babak Ehteshami Bejnordi

Today we’re joined by Babak Ehteshami Bejnordi, a Research Scientist at Qualcomm. Babak is currently focused on conditional computation, which is the main driver for today’s conversation. We dig into a few papers in great detail including one from this year’s CVPR conference, Conditional Channel Gated Networks for Task-Aware Continual Learning, covering how gates are used to drive efficiency and accuracy, while decreasing model size, how this research manifests into actual products, and more!

55 MIN2 w ago
Comments
Channel Gating for Cheaper and More Accurate Neural Nets with Babak Ehteshami Bejnordi

Building an ML-Forward Commerce Platform at Square with Marsal Gavalda - #384

Today we’re joined by Marsal Gavalda, head of machine learning for the Commerce platform at Square, where he manages the development of machine learning for various tools and platforms, including marketing, appointments, and above all, risk management. We explore how they manage their vast portfolio of projects, and how having an ML and technology focus at the outset of the company has contributed to their success, tips and best practices for internal democratization of ML, and much more.

51 MIN3 w ago
Comments
Building an ML-Forward Commerce Platform at Square with Marsal Gavalda - #384

Cell Exploration with ML at the Allen Institute w/ Jianxu Chen

Today we’re joined by Jianxu Chen, a scientist at the Allen Institute for Cell Science. At the latest GTC conference, Jianxu presented his work on the Allen Cell Explorer Toolkit, an open-source project that allows users to do 3D segmentation of intracellular structures in fluorescence microscope images at high resolutions, making the images more accessible for data analysis. We discuss three of the major components of the toolkit: the cell image analyzer, the image generator, and the image visualizer

43 MIN3 w ago
Comments
Cell Exploration with ML at the Allen Institute w/ Jianxu Chen

Neural Arithmetic Units & Experiences as an Independent ML Researcher with Andreas Madsen

Today we’re joined by Andreas Madsen, an independent researcher based in Denmark. While we caught up with Andreas to discuss his ICLR spotlight paper, “Neural Arithmetic Units,” we also spend time exploring his experience as an independent researcher, discussing the difficulties of working with limited resources, the importance of finding peers to collaborate with, and tempering expectations of getting papers accepted to conferences -- something that might take a few tries to get right.

30 MINJUN 12
Comments
Neural Arithmetic Units & Experiences as an Independent ML Researcher with Andreas Madsen

2020: A Critical Inflection Point for Responsible AI with Rumman Chowdhury

Today we’re joined by Rumman Chowdhury, Managing Director and Global Lead of Responsible AI at Accenture. In our conversation with Rumman, we explored questions like: • Why is now such a critical inflection point in the application of responsible AI? • How should engineers and practitioners think about AI ethics and responsible AI? • Why is AI ethics inherently personal and how can you define your own personal approach? • Is the implementation of AI governance necessarily authoritarian?

61 MINJUN 9
Comments
2020: A Critical Inflection Point for Responsible AI with Rumman Chowdhury

Latest Episodes

Computer Vision for Remote AR with Flora Tasse

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.

40 MIN2 d ago
Comments
Computer Vision for Remote AR with Flora Tasse

Deep Learning for Automatic Basketball Video Production with Julian Quiroga

Today we're Julian Quiroga, a Computer Vision Team Lead at Genius Sports, to discuss his recent paper “As Seen on TV: Automatic Basketball Video Production using Gaussian-based Actionness and Game States Recognition.” We explore camera setups and angles, detection and localization of figures on the court (players, refs, and of course, the ball), and the role that deep learning plays in the process. We also break down how this work applies to different sports, and the ways that he is looking to improve i

42 MIN5 d ago
Comments
Deep Learning for Automatic Basketball Video Production with Julian Quiroga

How External Auditing is Changing the Facial Recognition Landscape with Deb Raji

Today we’re taking a break from our CVPR coverage to bring you this interview with Deb Raji, a Technology Fellow at the AI Now Institute. Recently there have been quite a few major news stories in the AI community, including the self-imposed moratorium on facial recognition tech from Amazon, IBM and Microsoft. In our conversation with Deb, we dig into these stories, discussing the origins of Deb’s work on the Gender Shades project, the harms of facial recognition, and much more.

81 MIN1 w ago
Comments
How External Auditing is Changing the Facial Recognition Landscape with Deb Raji

AI for High-Stakes Decision Making with Hima Lakkaraju

Today we’re joined by Hima Lakkaraju, an Assistant Professor at Harvard University. At CVPR, Hima was a keynote speaker at the Fair, Data-Efficient and Trusted Computer Vision Workshop, where she spoke on Understanding the Perils of Black Box Explanations. Hima talks us through her presentation, which focuses on the unreliability of explainability techniques that center perturbations, such as LIME or SHAP, as well as how attacks on these models can be carried out, and what they look like.

45 MIN1 w ago
Comments
AI for High-Stakes Decision Making with Hima Lakkaraju

Invariance, Geometry and Deep Neural Networks with Pavan Turaga

We continue our CVPR coverage with today’s guest, Pavan Turaga, Associate Professor at Arizona State University. Pavan gave a keynote presentation at the Differential Geometry in CV and ML Workshop, speaking on Revisiting Invariants with Geometry and Deep Learning. We go in-depth on Pavan’s research on integrating physics-based principles into computer vision. We also discuss the context of the term “invariant,” and Pavan contextualizes this work in relation to Hinton’s similar Capsule Network res

47 MIN2 w ago
Comments
Invariance, Geometry and Deep Neural Networks with Pavan Turaga

Channel Gating for Cheaper and More Accurate Neural Nets with Babak Ehteshami Bejnordi

Today we’re joined by Babak Ehteshami Bejnordi, a Research Scientist at Qualcomm. Babak is currently focused on conditional computation, which is the main driver for today’s conversation. We dig into a few papers in great detail including one from this year’s CVPR conference, Conditional Channel Gated Networks for Task-Aware Continual Learning, covering how gates are used to drive efficiency and accuracy, while decreasing model size, how this research manifests into actual products, and more!

55 MIN2 w ago
Comments
Channel Gating for Cheaper and More Accurate Neural Nets with Babak Ehteshami Bejnordi

Building an ML-Forward Commerce Platform at Square with Marsal Gavalda - #384

Today we’re joined by Marsal Gavalda, head of machine learning for the Commerce platform at Square, where he manages the development of machine learning for various tools and platforms, including marketing, appointments, and above all, risk management. We explore how they manage their vast portfolio of projects, and how having an ML and technology focus at the outset of the company has contributed to their success, tips and best practices for internal democratization of ML, and much more.

51 MIN3 w ago
Comments
Building an ML-Forward Commerce Platform at Square with Marsal Gavalda - #384

Cell Exploration with ML at the Allen Institute w/ Jianxu Chen

Today we’re joined by Jianxu Chen, a scientist at the Allen Institute for Cell Science. At the latest GTC conference, Jianxu presented his work on the Allen Cell Explorer Toolkit, an open-source project that allows users to do 3D segmentation of intracellular structures in fluorescence microscope images at high resolutions, making the images more accessible for data analysis. We discuss three of the major components of the toolkit: the cell image analyzer, the image generator, and the image visualizer

43 MIN3 w ago
Comments
Cell Exploration with ML at the Allen Institute w/ Jianxu Chen

Neural Arithmetic Units & Experiences as an Independent ML Researcher with Andreas Madsen

Today we’re joined by Andreas Madsen, an independent researcher based in Denmark. While we caught up with Andreas to discuss his ICLR spotlight paper, “Neural Arithmetic Units,” we also spend time exploring his experience as an independent researcher, discussing the difficulties of working with limited resources, the importance of finding peers to collaborate with, and tempering expectations of getting papers accepted to conferences -- something that might take a few tries to get right.

30 MINJUN 12
Comments
Neural Arithmetic Units & Experiences as an Independent ML Researcher with Andreas Madsen

2020: A Critical Inflection Point for Responsible AI with Rumman Chowdhury

Today we’re joined by Rumman Chowdhury, Managing Director and Global Lead of Responsible AI at Accenture. In our conversation with Rumman, we explored questions like: • Why is now such a critical inflection point in the application of responsible AI? • How should engineers and practitioners think about AI ethics and responsible AI? • Why is AI ethics inherently personal and how can you define your own personal approach? • Is the implementation of AI governance necessarily authoritarian?

61 MINJUN 9
Comments
2020: A Critical Inflection Point for Responsible AI with Rumman Chowdhury

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