Applying RL to Real-World Robotics with Abhishek Gupta - #466

Applying RL to Real-World Robotics with Abhishek Gupta - #466

Today we’re joined by Abhishek Gupta, a PhD Student at UC Berkeley. Abhishek, a member of the BAIR Lab, joined us to talk about his recent robotics and reinforcement learning research and interests, which focus on applying RL to real-world robotics applications. We explore the concept of reward supervision, and how to get robots to learn these reward functions from videos, and the rationale behind supervised experts in these experiments. We also discuss the use of simulation for experiments, data collection, and the path to scalable robotic learning. Finally, we discuss gradient surgery vs gradient sledgehammering, and his ecological RL paper, which focuses on the “phenomena that exist in the real world” and how humans and robotics systems interface in those situations. The complete show notes for this episode can be found at https://twimlai.com/go/466.

Jaksot(778)

Invariance, Geometry and Deep Neural Networks with Pavan Turaga - #386

Invariance, Geometry and Deep Neural Networks with Pavan Turaga - #386

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

25 Kesä 202046min

Channel Gating for Cheaper and More Accurate Neural Nets with Babak Ehteshami Bejnordi - #385

Channel Gating for Cheaper and More Accurate Neural Nets with Babak Ehteshami Bejnordi - #385

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!

22 Kesä 202055min

Machine Learning Commerce at Square with Marsal Gavalda - #384

Machine Learning Commerce 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.

18 Kesä 202051min

Cell Exploration with ML at the Allen Institute w/ Jianxu Chen - #383

Cell Exploration with ML at the Allen Institute w/ Jianxu Chen - #383

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

15 Kesä 202044min

Neural Arithmetic Units & Experiences as an Independent ML Researcher with Andreas Madsen - #382

Neural Arithmetic Units & Experiences as an Independent ML Researcher with Andreas Madsen - #382

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.

11 Kesä 202031min

2020: A Critical Inflection Point for Responsible AI with Rumman Chowdhury - #381

2020: A Critical Inflection Point for Responsible AI with Rumman Chowdhury - #381

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?

8 Kesä 20201h 1min

Panel: Advancing Your Data Science Career During the Pandemic - #380

Panel: Advancing Your Data Science Career During the Pandemic - #380

Today we’re joined by Ana Maria Echeverri, Caroline Chavier, Hilary Mason, and Jacqueline Nolis, our guests for the recent Advancing Your Data Science Career During the Pandemic panel. In this conversation, we explore ways that Data Scientists and ML/AI practitioners can continue to advance their careers despite current challenges. Our panelists provide concrete tips, advice, and direction for those just starting out, those affected by layoffs, and those just wanting to move forward in their careers.

4 Kesä 20201h 7min

On George Floyd, Empathy, and the Road Ahead

On George Floyd, Empathy, and the Road Ahead

Visit twimlai.com/blacklivesmatter for resources to support organizations pushing for social equity like Black Lives Matter, and groups offering relief for those jailed for exercising their rights to peaceful protest.

2 Kesä 20206min

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