<description>&lt;p&gt;Sponsor: BePresent - https://www.bepresentapp.com/&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;In this episode of AI in NYC, hosts Rob May, Ryan Eppley, and Anna Kirk sit down with David Justus, VP of Applied AI at Panasonic, to explore one of the most underappreciated frontiers in artificial intelligence: edge AI. David breaks down how Panasonic is deploying AI in internet-constrained environments — from in-flight entertainment systems on transatlantic flights to manufacturing floors and stadium video processing — where sending data to the cloud simply isn't an option.&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;The conversation takes a fascinating geopolitical turn as David contrasts how the US, China, and Japan are each taking radically different approaches to generative AI. While the US doubles down on closed, AGI-focused ecosystems and China pushes open-weight models, Japan is quietly building sovereign, domain-specialized AI — including the recently released Rakuten V3 model that outperforms GPT-4o on Japanese-specific tasks. David argues that the US approach may not be great for edge computing and could be starting to show cracks.&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;David also shares insights from Panasonic's research lab, including new work on using diffusion models for document understanding, and explains why the last six months have been a true inflection point for running meaningful AI on small, resource-constrained devices. Whether you're building products, leading an AI team, or just trying to understand where the industry is heading beyond the data center, this episode is packed with perspective you won't hear anywhere else.&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;David Justus brings a background in applied mathematics and computer science, with experience spanning finance, creative industries, and consulting for companies like Verizon, Nike, and Mayo Clinic before joining Panasonic's global applied AI team two years ago.&lt;/p&gt;</description>

AI in NYC Show

AI in NYC Team

EP 22: Edge AI, Privacy & Japan's Different Approach ft. David Justus, VP of Applied AI @ Panasonic

APR 21, 202641 MIN
AI in NYC Show

EP 22: Edge AI, Privacy & Japan's Different Approach ft. David Justus, VP of Applied AI @ Panasonic

APR 21, 202641 MIN

Description

Sponsor: BePresent - https://www.bepresentapp.com/In this episode of AI in NYC, hosts Rob May, Ryan Eppley, and Anna Kirk sit down with David Justus, VP of Applied AI at Panasonic, to explore one of the most underappreciated frontiers in artificial intelligence: edge AI. David breaks down how Panasonic is deploying AI in internet-constrained environments — from in-flight entertainment systems on transatlantic flights to manufacturing floors and stadium video processing — where sending data to the cloud simply isn't an option.The conversation takes a fascinating geopolitical turn as David contrasts how the US, China, and Japan are each taking radically different approaches to generative AI. While the US doubles down on closed, AGI-focused ecosystems and China pushes open-weight models, Japan is quietly building sovereign, domain-specialized AI — including the recently released Rakuten V3 model that outperforms GPT-4o on Japanese-specific tasks. David argues that the US approach may not be great for edge computing and could be starting to show cracks.David also shares insights from Panasonic's research lab, including new work on using diffusion models for document understanding, and explains why the last six months have been a true inflection point for running meaningful AI on small, resource-constrained devices. Whether you're building products, leading an AI team, or just trying to understand where the industry is heading beyond the data center, this episode is packed with perspective you won't hear anywhere else.David Justus brings a background in applied mathematics and computer science, with experience spanning finance, creative industries, and consulting for companies like Verizon, Nike, and Mayo Clinic before joining Panasonic's global applied AI team two years ago.