Digital Transformation: what should companies look for in AI platforms?

Digital transformation is one of the most trending keywords in recent years, primarily due to the COVID-19 pandemic that has accelerated the digital transformation among enterprise operations. What is the definition of digital transformation? Taiwan's top research and technology development organization ITRI AI collaborative platform Aldea considers a company that is embracing digital transformation when it begins to apply new technologies to its existing data and information and replace manual handling. Business models, customer experience, and operations processes that combine with internet applications in terms of equipment and services are also part of the equation and can quickly run into problems as well.

In the article originally posted on CENS' sister media platform, Economic Daily News, Aldea invited Advantech WISE-AIFS Senior Sales Manager Chen Ling-hsuan to share helpful applications in the pursuit of digital transformation.

What would be the challenges that companies will face implementing digital transformation in the general industry?

As Advantech is an industrial computer manufacturer with a very high market share, the company is in the best position to understand the many challenges and needs among manufacturers. With the rapid changes in the world's industrial sectors after 2020, human resources are even more insufficient, even when industries are just in the first stages of digitalization. However, with upgrades applied, the data collection is still reliant on human resources. Therefore, Advantech has looked to offer a solution to help manufacturers use artificial intelligence, such as systematically scaling key functions such as training and deployment models for a smoother transition.

It is also because of this that AI needs to learn the knowledge required for industrial upgrading, and it needs to cooperate with the industry through the integration of software and hardware to facilitate implementation in the industry. Therefore, a one-stop AI-based platform - WISE-AIFS was developed to address these issues.

Chen also offered suggestions for companies when deciding what AI tools to invest in.

How do companies decide whether an AI platform is suitable for them?

Chen suggested five factors to look at:

Highly efficient, and ability to access computational resources:

The AI platform will create hundreds of thousands of data, so the platform's ability to offer an accessible user interface is important, making it easy for users to oversee CPU, GPU, and database management efficiently.

Easy to Integrate with Various Datasets:

Data collection is a crucial part of the digital transformation process, Chen says, so the platform must be capable of collecting vast OT data, IT data, and scenario-based data.

Must be cost-saving and provide smooth development procedures:

The platform must include mainstream AI structures, development interfaces, and algorithms, as well as provide model development and version control features.

Labor-efficient with long-distance modularization:

The platform must be compatible with various systems and equipment; therefore, features like long-distance modularization for development purposes, such as Windows, Linux, and Docker, are a must.

One-stop management of entire product life cycles:

An AI platform intended for industrialized applications must factor in automated model training and deployment, as well as re-training and re-deployment.