INEEJI CEO Jaesik Choi: “We must provide AI solutions that are safe and reliable for workers.”

At the 2024 AMWC (Autonomous Manufacturing World Congress) held at COEX in Seoul on June 11, iNEEJi CEO Jaesik Choi gave the first keynote speech, presenting on 'DX: Crisis and Opportunity, Not a Choice but a Necessity.'

CEO Choi first opened the lecture by focusing on the continuous growth of generative AI. He said, “ChatGPT is just the beginning,” and said, “Among Gartner’s top 10 strategic technology trends for 2024, we are focusing on three topics: industrial cloud platform, platform engineering, and AI trust risk security management (AI TRiSM).”

AI technology is a field that is attracting attention across industries, with venture capital investment in generative AI solutions exceeding $1.7 billion over the past three years. In particular, new technologies such as △generative AI △pre-trained generative transformer (GPT) △large-scale language model (LLM) △research-augmented generation (RAG) are leading the AI ​​industry.

CEO Choi said, “Domestic AI-related technology in the manufacturing sector is at a low level compared to the global level,” and “AI utilization in primary and secondary industries such as steel and petrochemicals is relatively slow, and there is a rapid shift toward tertiary industries that are closely related to customers, such as distribution and bio.”

He continued, “If we look at the status of AI utilization by industry, the larger the company, the more likely it is to introduce technologies developed through collaboration with external parties rather than purchasing or renting commercial products and services that use AI.” He explained, “Companies leading the global ICT market are releasing various products equipped with AI developed in-house, and integrated management of energy and environment using AI is emerging as the most important keyword because it is effective in saving energy.”

CEO Choi, who introduced the S-curve of industrial change, predicted that autonomous manufacturing through AI, like the steam engine in the 4th industrial revolution, will be a decisive breakthrough that will enable numerous other technological advancements.

CEO Choi, who mentioned the change in the autonomous manufacturing paradigm through AI, said, “Data science is becoming more advanced as a process that goes beyond information and optimizes it depending on the difficulty of analysis and the value of data,” and predicted, “While the industrial field has focused on production optimization through AI so far, AI standardization and advancement will be achieved through operational optimization.”

Then, CEO Choi asked a question. “Would you be able to ride in a self-driving car with your family using AI technology from the Large Language Model (LLM)?” CEO Choi said, “It’s easy to say to make a product and use it, but when you think of your family, it has to be safe and reliable beyond just good.”

He continued, “It is easy to use solutions using AI technology in industrial settings, but workers who use the equipment in the field for long periods of time must have a sense of safety and reliability.”

CEO Choi said that what INEEJI does is develop AI technology and apply it on-site based on reliability. CEO Choi, who introduced a case of optimizing the manufacturing process through the application of INEEJI’s AI technology, previously mentioned the effect of applying AI technology at the lighthouse factory.

CEO Choi said, “AI-related technologies are being applied and operated in 68 cases (47%) of 145 lighthouse factories around the world,” and explained, “They are being introduced in various fields such as automatic control, optical inspection, and machine learning process analysis, and through this, they are having the effect of increasing overall equipment and assembly efficiency and reducing energy consumption.”

Next, CEO Choi introduced INEEJI’s customer cases, saying, “We have provided successful AI solutions in condensing gas line (CGL), cement calcination process preheating room, and oil refinery process RHDS (residue oil hydrodesulfurization),” adding, “In addition to improving quality competitiveness, energy cost reduction, quality stabilization, and process optimization have been improved.”