Ask the Experts: Is On-Device AI Going to Prove to Be Hype or Helpful?
I sat down with engineers from Google Cloud and Qualcomm to break down the benefits of this new approach to AI so you can decide for yourself.
Your frontline workers need AI, and they need it now.
They need guidance. They need information. And it’s getting harder to find a co-worker or manager that can provide these things. Everyone’s busy.
In fact, in Zebra’s latest Global Shopper Study, 85% of the retail associates surveyed said they believe AI will help them be more productive, and 78% said AI/machine learning would boost efficiency and customer service. Three-quarters said the same for generative AI (GenAI).
That’s why we’ve been working with people like Rouzbeh Aminpour from Google Cloud, Art Miller from Qualcomm Technologies, Inc. and dozens of engineers from all three companies to develop, refine and implement on-device AI – or edge AI – tools with frontline worker feedback.
Your frontline workers don’t need a stochastic parrot, and you don’t need yet another complicated digital transformation project that may or may not prove capable of making things easier. They just need an assistant that has all the answers and empowers them, by their side (or in their ear) as they execute workflows. That’s what will make it easier for you to help customers, care for patients, make decisions, get orders out the door or find the goods, supplies, and equipment needed to do all the above.
Imagine if nurses have an AI assistant on their clinical mobile device to provide timely, relevant information and training exactly when they need it while caring for patients. This Just-In-Time information (or assistance) approach can enhance decision-making and improve patient outcomes without compromising safety or regulatory compliance. The same is true for retail and warehouse associates, delivery drivers, first responders, factory workers, and so many others.
Though some of your frontline workers may not yet realize (or believe) they need AI’s help, the reality is they are facing too many challenges that can’t be solved without AI playing some part.
That said, it shouldn’t be hard to onboard AI, and once up and running, you shouldn’t fear that AI assistant is going to bail on you in your moment of need. Your frontline workers shouldn’t have to worry that they’ll lose access to their assistant – their only source of information – if they lose a wireless signal.
That’s the other reason we’ve been exploring what AI workloads we can run at the far-edge (mobile) and local edge (on-prem) that work in tandem with the cloud.
The truth is you don’t need everything in your tech stack to be cloud-based – or on-prem, for that matter. There are some workflow-supportive technology tools that can fully live at the mobile edge, locally on the device. As model training frameworks evolve, chipsets incorporate more powerful neural processing capabilities and the models themselves become more efficient, it will become increasingly possible to process more at the edge to drive productivity right at the point of activity.
That’s why you should take 30 minutes to listen to the conversation I had with Rouzbeh and Art on the podcast:
We know on-device AI may feel like a nascent idea. Earlier this year, we showed GenAI running on edge devices without cloud connectivity for the first time publicly at the Google Cloud Next 2024 event. Plus, I know you may still be trying to compute GenAI’s potential value to your frontline workers and business in general, regardless of where the AI model lives.
So, as you’re thinking through all this and trying to decide how GenAI may be helpful to you and your frontline workers, I want to ensure you’re considering how helpful on-device AI (or edge AI) can be. I want you to fully understand what we’re talking about here: how on-device AI works, how complicated it’s going to be to put into practice, and how else you’ll be able to leverage it in the future beyond the chatbot type experience you’re thinking of offering workers today.
So, watch the video above, download the MP3 below, or keep scrolling to the bottom of the page to read the full transcript. Then reach out if you have questions. We’re happy to help you think through how best to leverage Generative AI because we really do believe that this will be tremendously helpful to you, your frontline workers, and even your customers for years to come.
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Tom Bianculli
Tom Bianculli serves as the Chief Technology Officer of Zebra Technologies. In this role, he is responsible for the exploration of emerging opportunities, coordinating with product teams on advanced product development and Internet of Things (IoT) initiatives. The Chief Technology Office is comprised of engineering, business, customer research and design functions.
Tom began his career in the tech industry at Symbol Technologies, Inc. (later acquired by Motorola) in 1994 as part of the data capture solutions business. In the following years, he held positions of increased responsibility including architectural and director of engineering roles.
Tom has been granted over 20 U.S. patents and is a Zebra Distinguished Innovator and Science Advisory Board associate. He was recently named one of the Top 100 Leaders in Technology 2021 by Technology Magazine.
Tom holds bachelor of science and master of science degrees in electrical engineering from Polytechnic University, NYU and serves on the board of directors for the School of Engineering at the New York Institute of Technology.
