Retail DX with original smart shopping cart (SSC) (Mr. Nagata, Retail AI)

Mr. Nagata gave a lecture on the ecosystem that Retail AI wants to realize. This ecosystem has two axes. In the first axis, "shopping experience of the new age", we convert and analyze information from customer experiences obtained from smart shopping carts and signage into AI, and then use that information. It is a composition that repeats the cycle of using one axis, "innovating the distribution system", and returning the results of using the data to the site and returning it to the customer.

The first axis was the introduction of smart shopping carts and signage.

The introduction of the smart shopping cart, which cuts the waiting time at the checkout counter in half, not only cuts the cost of the checkout operation, which is the most costly, but also makes it easier for customers to shop, increasing the frequency of visits and contributing to an increase in sales. did. He also explained that using the signage attached to the cart makes it possible to visualize the data of "unplanned purchases" that account for 80 % of all shopping.

Mr. Nagata also said that there are three resources that promote retail DX. It is 1. Operation-driven: Repeated improvements so that new technologies will permeate on-site, 2. Retrofit: adapting the new system in a way that suits the times, and 3. Open innovation: In order to promote the DX conversion of the entire distribution, he enthusiastically talked about the importance of sharing know-how and improving the industry.

In Retail AI, Miyawaka City is designated as a retail town, and we are focusing on the realization of real retail DX by preparing an environment that allows us to implement the PDCA cycle from technology development to demonstration experiments and PoC. Mr. Nagata said that he would like to bring about innovation while repeatedly verifying in the real field and improve people's lives.

Utilization of AI and Deep Learning in the Retail Industry -The Front Line and Overseas Cases- (Mr. Nakane from NVIDIA)

NVIDIA offers a variety of solutions, but this time Mr. Nakane introduced the NVIDIA Accelerated AI Platform, which is specialized for the retail industry.

This platform is divided into three layers, and among the third from the bottom is the "application framework" layer, which is specialized for the retail industry, "METROPOLIS" that enables video analysis, and "OMNIVERSE" that supports the metaverse. ” and so on.

Leveraging this platform, whether developing in-house or leveraging NVIDIA's ecosystem of partners, retail-specific application frameworks can be leveraged to provide retail end customers with greater agility. Mr. Nakane said that it is possible to provide various solutions with

In addition, the utilization of AI is roughly divided into four areas (intelligent store, intelligent QSR, intelligent supply chain, and omni-channel management). He also talked in detail about the use cases of AI in overseas companies (Carrefour, Wal-Mart, Kroger, etc.) in each area and its effects.

Coordinator who supports the “first step” in utilizing AI (Mr. Macnica Nomoto)

Macnica provided a detailed explanation of the use cases of AI in the retail industry, how AI works, and the knowledge and preparation required when actually implementing AI.

In many cases, it is a use case that utilizes "images acquired from cameras" and "AI" to solve various problems facing the retail industry, such as predicting the number of people entering stores, detecting congestion, and detecting intrusions. As a mechanism for this AI image analysis, a large amount of information is input, AI analyzes it, and the information is output as data.

The flow of image analysis using AI involves the "learning" and "inference" phases, which require a lot of hardware and software. If you were to prepare all of this from scratch, you would have to think about how to select vendors and equipment and acquire the knowledge to use them. We talked about how Macnica can provide the shortest route to an environment that would normally require a lot of effort to prepare, so that retailers can focus on their main business and work that creates added value.