ABSTRACTOur guest this episode is Glenn Jocher, CEO and founder of Ultralytics, the company that brought you YOLO v5 and v8. Gil and Glenn discuss how to build an open-source community on Github, the history of YOLO and even particle physics. They also talk about the progress of AI, diffusion and transformer models and the importance of simulated synthetic data today. The first episode of season 2 is full of stimulating conversation to understand the applications of YOLO and the impact of...

ABSTRACT Gil Elbaz speaks with Tadas Baltrusaitis, who recently released the seminal paper DigiFace 1M: 1 Million Digital Face Images for Face Recognition. Tadas is a true believer in synthetic data and shares his deep knowledge of the subject along with  insights on the current state of the field and what CV engineers need to know. Join Gil as they discuss morphable models, multimodal learning, domain gaps, edge cases and more TOPICS & TIMESTAMPS 0:00 Introduction 2:06 Getting...

Host Gil Elbaz welcomes Andrew J. Davison, the father of SLAM. Andrew and Gil dive right into how SLAM has evolved and how it started. They speak about Spatial AI and what it means along with a discussion about global belief propagation. Of course, they talk about robotics, how it's impacted by new technologies like NeRF and what is the current state-of-the-art. Timestamps and Topics [00:00:00] Intro [00:02:07] Early Research Leading to SLAM [00:04:49] Why SLAM [00:08:20] Computer Vision...

Gil Elbaz hosts Or Litany, a senior research scientist at Nvidia. They discuss the impact of 3D on computer vision and where it’s going in the near future. As well, they talk about the impact of industry on academia and vice versa. Or speaks about the future of 3D generative models, NeRF and how multi-modal models are changing computer vision. Together, Gil and Or explore the best ways to succeed in the field of AI. TOPICS & TIMESTAMPS [0:34] Intro [2:01] Starting his journey  [5:03]...

In this episode of Unboxing AI, I host Michael J. Black from the Max Planck Institute. We speak about body models, his journeys in industry and academia, representing all human body types and the age of the avatar. Michael explains about the early days of computer vision, his experiences commercializing body models through his startup, Body Labs, and how the metaverse and our avatars will revolutionize our everyday lives. Episode transcript and more at UnboxingAI.show TOPICS &...

In this episode of Unboxing AI, meet Vijay Badrinarayanan, the VP of AI at Wayve, and learn about Wayve’s end-to-end machine learning approach to self-driving. Along the way, Vijay shares what it was like working for Magic Leap in the early days, and relates the research journey that led to SegNet. TOPICS & TIMESTAMPS 00:47 Guest Intro 02:38 Academia & Classic Computer Vision 08:56 PostDoc @ Cambridge - Road scene segmentation 18:42 Technical Challenges Faced During Early Deep...

In this episode of Unboxing AI, I host Idan Bassuk, the VP A.I. at Aidoc, to chat about computer vision, NLP, and AI explainability in the medical field. During the episode, Idan discusses the challenges that should interest anyone who’s building an AI team for scale. For example: what type of roles does he have on his team? Is it engineering first or data first? Does the real world of production resemble the rich academic research in the medical space? TOPICS & TIMESTAMPS 1:52 - Going...

Listen in as Prof. Lihi Zelnik-Manor shares insights from a career that bridges from academia to industry. Lihi walks us through the history of the computer vision development community to the interplay between the industry and academia today. Lihi Zelnik-Manor is an Professor in the Faculty of Electrical and Computer Engineering at the Technion and former General Manager of Alibaba DAMO Israel Lab. Prof. Zelnik-Manor holds a PhD and MSc (with honors) in Computer Science from the Weizmann...

Are you up to solving a machine learning problem? If so, start on Kaggle. Anthony Goldbloom, co-founder and CEO of Kaggle, joins us to talk about what it takes to found a machine learning community.  We answer the question of what happens when you cross a domain expert with a pragmatic problem solver. Anthony talks about the future of AI and computer vision, how important it is to learn through doing and what he is looking forward to in the next year.