10

PTLs and Subcommittee Chair Update

SuperAI superBlueprint

SuperAI SuperBlueprint - InfiniEdge AI - Confluence

10

PoC Document

Autonomous Agents Network Blueprint PoC Document - Akraino - Confluence

10

InfiniEdge AI
R3.2

10

ONE summit CFP

ONE Summit Japan | LF Events
CFP Draft
Physical AI Blueprints and Workstreams in the LF Edge Akraino and InfiniEdge AI Projects

The convergence of AI and edge computing is transforming a wide range of industries, driving unprecedented levels of automation, efficiency, and real-time decision-making. This presentation focuses on the emergence of Physical AI through rapid evolution of Edge AI.

We will showcase how LF Edge projects, specifically Akraino and InfiniEdge AI, enable Edge AI use cases by providing robust and comprehensive open-source reference stacks, from infrastructure to application layer.

Edge AI has been growing due to IoT, and is now accelerating due to robotics, drones, and automated vehicles, driven by demand for low latency processing, local inference compute, and data privacy. Ultra-low latency is especially needed for safety and human interaction.

Bringing AI capabilities closer to users and data is a paradigm shift. Edge AI enables real-time inference, reduces network traffic, and enhances data security, allowing applications in manufacturing, healthcare, smart cities, and autonomous vehicles, among others, to operate with greater autonomy and responsiveness.

Within Edge AI, Physical AI is emerging as a transformative domain. Physical AI refers to AI systems that directly interact with the physical world by perceiving the environment through sensors, processing information, and executing actions through actuators. This encompasses a wide range of applications, from robotic automation and predictive maintenance in industrial settings to intelligent surveillance and environmental monitoring. The ability of AI at the edge to directly influence and control physical processes opens new frontiers for innovation, enabling more adaptive, resilient, and intelligent systems.

The Akraino and InfiniEdge AI projects provide open-source reference stacks that address end-to-end requirements for Physical AI at the edge.

This presentation will offer a detailed overview of how these projects work in concert to tackle the challenges and unlock the opportunities presented by Edge AI. Attendees will gain valuable insights into leveraging these open-source technologies to accelerate their Edge AI and Physical AI initiatives and contribute to the evolution of intelligent edge computing.

SL No.

Voting Member

Member Company

Y/N/A

1

@Ike Alisson

Alicon

2

@Jeff Brower

Signalogic

3

@Haruhisa Fukano

Fujitsu

4

@Yin Ding

Google

5

@thorking

Infortrend

6

@Vijay pal

PalC Networks

7

@Sujata Tibrewala

ByteDance 

8

@zhuguanyu

Huawei

9

10

11

12

13

14

15

16

17

18

19

20