A large number of AI solution service providers participated in the 2023 International Artificial Intelligence Competition. Amidst the exhibition of various image analysis, recognition, and detection technologies used in computer vision, a trend toward no-code development was also gaining traction among AI developers.

We met with CEO Duwon Jeong of AltoAir, a no-code edge AI development platform service company that supports end-to-end embedded AI development.

Edge AI development faces increasing development costs.

The edge AI development process involves the following stages: field data collection, data labeling, AI model training, AI model lightweighting, and AI model deployment, and it takes 3 to 4 months to complete a single project. If issues such as decreased accuracy, insufficient memory, slow processing speed, or labeling issues arise during the project stage, the project must return to the previous stage and redesign, which leads to increased development time and costs.

AltoAir CEO Jeong Du-won cited three reasons why AI models return to the design stage: △ difficulty in predicting the memory usage of the design model, △ hardware constraints used in model design, and △ lack of know-how to confirm optimization of AI models in terms of accuracy and processing speed.

In particular, edge AI generally has limitations in processing power, memory, and storage capacity, so the AI model process necessarily involves developing a model that is 'fit' and optimized for these limitations. This optimization process involves numerous trials and errors, and repeated redesigns and modifications.

CEO Jeong emphasized that because computational load, processing speed, and memory usage are trade-offs, finding the right balance and appropriate load distribution between software and hardware is paramount. Consequently, individual developers designing AI models on their own inevitably invest excessive time, energy, and resources in a single model training session.

AltoAir Launches No-Code Edge AI Development Platform

AltoAir Corporation ambitiously presented its no-code edge AI development platform, Tiny Boom, at this year's International Artificial Intelligence Competition.

Most companies offer AI solution services for each technology and often provide customized technical responses to customers. On the other hand, through an AI development platform, the entire process from data collection to AI model training and lightweighting, and AI model deployment can be executed in one stop using an intuitive UI/UX.

CEO Jeong Du-won, who developed Tiny Boom, emphasized, “This is a product that allows even companies with no AI capabilities to develop edge AI models with simple UI operations,” and “It can reduce development time by more than 1/10 of the existing time, and it can also realize the effect of improving the efficiency of AI expert engineer resources.”

The types of AI models that can be developed through TinyBoom include image data analysis models, such as image classification and object recognition, and time-series data analysis models, such as signal classification and anomaly detection. CEO Jeong added that examples include supplying the AI model to quality inspection processes at steel manufacturing companies and medical image interpretation.

CEO Jeong emphasized, “Tinyboom is a solution specialized in the development of edge AI models that are relatively inexpensive enough to operate on microcontrollers (MCUs) and can operate on low-power processors,” and added, “In the second half of 2023, we plan to provide a ‘HW-NAS’ function to minimize the edge AI development cycle by applying technology that finds the optimal balance between HW and SW.”