Distilling Transformers and Diffusion Models for Robust Edge Use Cases with Fatih Porikli - #738

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Here We Woe Again: Jenna Ortega, Creators Al Gough & Miles Millar 31:46

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BE WARNED! This podcast will contain spoilers for Wednesday Season 2, episodes 1-4. Join host Caitlin Reilly each week as she takes you deep into the twisted world of Wednesday with an amazing group of guests! And producer Thing will be helping out to make sure everything goes to plan - well, mostly, anyway... In this episode: Jenna Ortega peels back the layers on the new tension between Wednesday and Enid. And that terrifying vision! Plus… Series showrunners Al Gough and Miles Millar reveal why they made Morticia Addams such a central character in this season, and what it means for Wednesday. Whether you’re a normie or an outcast, the Wednesday Season 2 Official Woecast will be the place for all things Nevermore! For more juicy details about Wednesday Season 2, head over to Tudum.com to get all of the latest updates. 1:15 Preparing for Season 2 3:25 Evolving Wednesday’s look for Season 2 4:12 Addams clan expands for Season 2 6:12 Joanna Lumley joining the cast 7:38 Wednesday and Enid's Friendship 9:00 Wednesday’s Vision 10:50 Jenna is a Producer 13:45 Al and Miles introduction 14:03 Wednesday takes down a Serial Killer 15:05 Intergenerational Relationships & the Addams Women 17:48 Catherine Zeta-Jones as Morticia in Season 2 20:48 Wednesday and Enid’s relationship 24:04 Steve Buscemi joining the cast 26:19 Wednesday’s popular! 27:45 Boy with the Clockwork Heart stop motion sequence…

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Today, we're joined by Fatih Porikli, senior director of technology at Qualcomm AI Research for an in-depth look at several of Qualcomm's accepted papers and demos featured at this year’s CVPR conference. We start with “DiMA: Distilling Multi-modal Large Language Models for Autonomous Driving,” an end-to-end autonomous driving system that incorporates distilling large language models for structured scene understanding and safe planning motion in critical "long-tail" scenarios. We explore how DiMA utilizes LLMs' world knowledge and efficient transformer-based models to significantly reduce collision rates and trajectory errors. We then discuss “SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation,” a diffusion-distilled approach that combines generative models with metric depth estimation to produce sharp, accurate monocular depth maps. Additionally, Fatih also shares a look at Qualcomm’s on-device demos, including text-to-3D mesh generation, real-time image-to-video and video-to-video generation, and a multi-modal visual question-answering assistant.

The complete show notes for this episode can be found at https://twimlai.com/go/738.

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Distilling Transformers and Diffusion Models for Robust Edge Use Cases with Fatih Porikli - #738

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

1,753 subscribers

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The complete show notes for this episode can be found at https://twimlai.com/go/738.

762 قسمت

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Closing the Loop Between AI Training and Inference with Lin Qiao - #742 1:01:11

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In this episode, we're joined by Lin Qiao, CEO and co-founder of Fireworks AI. Drawing on key lessons from her time building PyTorch, Lin shares her perspective on the modern generative AI development lifecycle. She explains why aligning training and inference systems is essential for creating a seamless, fast-moving production pipeline, preventing the friction that often stalls deployment. We explore the strategic shift from treating models as commodities to viewing them as core product assets. Lin details how post-training methods, like reinforcement fine-tuning (RFT), allow teams to leverage their own proprietary data to continuously improve these assets. Lin also breaks down the complex challenge of what she calls "3D optimization"—balancing cost, latency, and quality—and emphasizes the role of clear evaluation criteria to guide this process, moving beyond unreliable methods like "vibe checking." Finally, we discuss the path toward the future of AI development: designing a closed-loop system for automated model improvement, a vision made more attainable by the exciting convergence of open and closed-source model capabilities. The complete show notes for this episode can be found at https://twimlai.com/go/742 .…

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Distilling Transformers and Diffusion Models for Robust Edge Use Cases with Fatih Porikli - #738