T-Mobile U.S. recently revealed that the company is testing to discover whether humanoid robots could respond faster and rely less on onboard computers by running some of their AI at its network edge.
In a newly published blog, CTO John Saw explained T-Mobile is working with robotics company Figure AI to test if its systems can run on nearby computing infrastructure without slowing the machines’ responsiveness.
The systems involve controlling robots’ movement, and interpreting visual information and language instructions.
Saw wrote shifting some processing off the robots could reduce battery use, computing demands, heat, weight and cost. It could also let them run more capable AI without needing more hardware or power.
AWS
T-Mobile is working with AWS on the first deployments of Kinetic Edge, the operator’s distributed computing infrastructure for physical AI.
They are using T-Mobile’s 5G-Advanced network and distributed edge along with AWS’ cloud orchestration and AI services to push “deterministic connectivity, compute and intelligence closer to where machines operate”, Saw wrote.
He explained reliable connections and localised computing could help businesses take physical AI beyond individual demonstrations, highlighting developers are putting vision and reasoning models at the network edge to make robots, cameras and sensors less dependent on a distant cloud.
“This early work is helping us explore the capabilities that could make physical AI possible at scale, while opening the door to entirely new applications and opportunities”.
Machines require consistent connectivity when moving, sufficient uplink capacity to send sensor data, low latency and wide-area coverage, Saw wrote. Wi-Fi and satellite have a role, but he argued advanced terrestrial wireless networks are better suited to meeting the needs.
Human interaction
Saw noted employing people to assist robots would become challenging when thousands of machines are involved: T-Mobile is working with Serve Robotics to evaluate the feasibility of conducting monitoring at the edge to assess which problems can be solved by humans and which need more AI input.
The executive also highlighted work with Nvidia, Nokia and a growing group of developers to run physical AI applications across distributed edge networks, along with the recent completion of an AI-RAN call involving the vendors.
Saw explained T-Mobile is working with the city of San Jose in the state of California and specialist companies to develop a way to create an overview of traffic using edge AI to combine the views of separate 5G cameras.
They are testing if AI can connect occurrences at different junctions and if providing a big-picture could help people spot traffic patterns sooner.
The operator is also exploring “how AI and network workloads can share accelerated computing infrastructure” through partnerships with Nvidia, Nokia and Ericsson.
Saw said T-Mobile must develop ways to deliver “data and workloads” to “where intelligence needs to run”, whether it be on devices, the edge or cloud. He said the direction “is becoming clearer” and T-Mobile’s network would “be the connective tissue” between the layers.
Source: Mobile World Live
Image Credit: T-Mobile
Source: Tahawul Tech