Meta Tech Podcast

72: Multimodal AI for Ray-Ban Meta glasses


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In this episode of the Meta Tech Podcast, host Pascal sits down with Shane, a research scientist at Meta, to explore the cutting-edge research behind Ray-Ban Meta glasses. Shane shares insights from his seven-year journey at Meta, where he focuses on computer vision and multimodal AI within the Wearables AI organization.

Tune in to learn how Shane's team is pioneering foundational models for Ray-Ban Meta glasses, tackling unique challenges, and pushing the boundaries of AI-driven innovation. Discover how multimodal AI is transforming user experiences and get a glimpse into the future of wearable technology. Whether you're an engineer, a tech enthusiast, or simply curious about the latest advancements, there is something for everyone in this episode. 

Got feedback? Send it to us on Threads (https://threads.net/@metatechpod), Instagram (https://instagram.com/metatechpod) and don’t forget to follow our host Pascal (https://mastodon.social/@passy, https://threads.net/@passy_). Fancy working with us? Check out https://www.metacareers.com/.

Links

  • AnyMAL: An Efficient and Scalable Any-Modality Augmented Language Model - https://arxiv.org/abs/2309.16058 

  • Be My Eyes Programme: https://www.forbes.com/sites/stevenaquino/2024/10/11/inside-the-be-my-eyes-meta-collaboration-and-the-allure-to--impact-humanity/ 

  • Meta Open Source on Threads: https://www.threads.net/@metaopensource 

  • CacheLib: https://cachelib.org/ 

  • Meta’s AI-Powered Ray-Bans Are Life-Enhancing for the Blind - Wall Street Journal: https://www.wsj.com/tech/ai/metas-ai-powered-ray-bans-are-life-enhancing-for-the-blind-3ae38026 

Timestamps

  • Intro 0:06

  • OSS News 0:56

  • Introduction Shane 1:30

  • The role of research scientist over time 3:03

  • What's Multimodal AI? 5:45

  • Applying Multimodal AI in Meta's products 7:21

  • Acoustic modalities beyond speech 9:17

  • AnyMAL 12:23

  • Encoder zoos 13:53

  • 0-shot performance 16:25

  • Iterating on models 17:28

  • LLM parameter size 19:29

  • How do we process a request from the glasses? 21:53

  • Processing moving images 23:44

  • Scaling to billions of users 26:01

  • Where lies the optimisation potential? 28:12

  • Incorporating feedback 29:08

  • Open-source influence 31:30

  • Be My Eyes Programme 33:57

  • Working with industry experts at Meta 36:18

  • Outro 38:55

...more
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