Zebra Technologies demonstrated a Generative Artificial Intelligence (GenAI) large language model (LLM) running on Zebra handheld mobile computers and tablets without needing connectivity to the cloud.
This breakthrough empowers Zebra partners and customers to unlock exciting productivity gains that will shape the future of work across industries from retail to warehouse and logistics to hospitality and healthcare. On-device execution of GenAI LLMs has the potential to empower front-line workers with new capabilities so they can deliver new outcomes for their end customers.
On-device AI can offer additional personalization as well as enhanced privacy and security as data remains on the device. It also drives faster performance and lower costs as GenAI searches on the cloud can be expensive.
A whitepaper published by Qualcomm Technologies suggests that GenAI-based search cost per query is estimated to increase by ten times compared to traditional search methods. By removing the need to utilise the cloud, costs can be reduced.
"Zebra’s devices are powerful platforms boasting cutting-edge software and AI models," said Christanto Suryadarma, Southeast Asia (SEA) sales vice president, Zebra Technologies Asia Pacific.
He added that through collaborative efforts with our partner ecosystem, we're propelling novel technologies like GenAI forward and applying its capabilities to diverse domains such as voice AI, computer vision, and deep learning-powered machine vision software to effectively tackle customer challenges and elevate our overall value proposition.
Potential use cases for LLMs include improving associate effectiveness by enhancing their product and customer service knowledge, acting as an efficient internal communications tool by answering employee queries on things like store policies, collecting and analysing feedback from associates to identify areas of improvement, enhancing productivity and increasing job satisfaction levels.
LLMs also have the potential to elevate the customer experience by powering personalized shopping assistants that could provide product recommendations, integrating shopping experiences across in-store, online, and mobile platforms as well as potentially enabling fully voice-activated shopping.
