The AI Retail Assistant Manager: Extend AI and inference at the edge to empower associates
26Summary: In this video, Mike Ensor, Tech Lead for Google Distributed Cloud, explores how retailers can leverage inference at the edge to enhance their operations and customer experiences. Learn how retailers can leverage the power of cloud infrastructure, AI, and edge hardware powered by Intel Xeon processors with Google Distributed Cloud to optimize operations and enhance the customer experience.
Challenge: Retail associates face a significant challenge in accessing and utilizing information efficiently while in a retail setting, hindering their ability to make quick, informed decisions. Enabling use cases such as fixing a point of sale terminal, answering customer questions accurately, and expanding knowledge on new or bespoke products can be daunting. Navigating complex digitized manuals and relying on generic training materials often proves cumbersome, especially when immediate answers are needed for customer interactions or problem-solving. This lack of readily available, contextualized guidance, unreliable connectivity can slow productivity and can lead to missed opportunities,
Solution: The video presents three types of AI and ML applications that can be implemented using existing AI, cloud infrastructure and edge CPUs by Intel Xeon processors:
Google Cloud infrastructure extends to the edge.: Build applications on the cloud leveraging the latest in open source and cloud software and extend them directly to your location without compromising on latency, connectivity, or data residency.
Inference at the edge: Run applications to solve use cases such as store analytics, transaction processing, and associate enablement directly from your store locations cost efficiently and quickly with CPUs by Intel Xeon processors.
AI Agents: Enable AI agents to provide employees with quick access to solve challenges, provide high bar customer experiences, and leverage company documents and procedures quickly and on-site.
Results: Implementing these AI solutions enables retailers to gain real-time insights into customer behavior, like peak hours, popular areas, and demographics. They can also personalized customer experiences through tailored content and assistance and improve employee efficiency with AI-powered assistance and access to knowledge. Retailers can also gain the ability to process data locally even without compromising on latency, connectivity, data residency, or cost.
Highlights and Key Takeaways from the video:
→Extend AI and cloud infrastructure to enable retail associates with ownership, problem solving, and product knowledge to create delightful customer experiences..
→AI and ML solutions can be deployed at the edge to ensure low latency, compliance, and cost-effectiveness.
→Google Distributed Cloud can be combined with existing investments to achieve digital transformation.
→Inference at the edge enabled with CPUs powered by Intel Xeon processors deliver high performance and cost efficiency.
→AI-powered solutions can enhance employee performance by providing instant answers to questions in multiple languages.
→The future of retail is powered by AI and it can transform data collected into contextualized experiences that are specific to individual customers.
𝗚𝗼𝗼𝗴𝗹𝗲 𝗖𝗹𝗼𝘂𝗱 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝘀 𝘂𝘀𝗲𝗱: Google Distributed Cloud, powered by Intel Xeon processors
𝗟𝗲𝗮𝗿𝗻 𝗺𝗼𝗿𝗲 → https://goo.gle/4aUy5sMhttps://goo.gle/4aUy5sM