AI Technologies , Generative AI , Large Language Models
Applying AI Generative Models to Understand Customers
Edmund Situmorang on How AI Models Are Transforming LogisticsThe advancement of AI generative language models has brought machines closer to humans. It gives us a deeper understanding of complex information structures on the web.
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We live in an age where AI is capable of defining, understanding and generating a language. It can construct sentences for dialog with humans, based on the huge amount of data that has been collected over the years.
Edmund Situmorang, group CTO at Asian Bulk Logistics, is thinking about ways to use AI generative language models to understand internal and external stakeholders within the logistics sector. He's making this a top priority for the global organization this year.
"ChatGPT and generative language models are definitely a game changer," Situmorang says. He speaks about applying this for sentiment analysis on social media data.
"In logistics, it can be used to understand the complaints of the customer. It is also about looking deeper and understanding what those sentiments are about. In the future, a machine will understand what we are talking about," Situmorang says.
Cybersecurity Use Case
Organizations hire penetration testers to identify vulnerabilities in systems. Often, the problem is tracked down to weak passwords and the carelessness of an employee or third party. NLP models can now be applied to do this assessment.
"The No. 1 problem [with cybersecurity] is people. Normally, I would hire experts to assess people and how they do things. A machine can do that now," Situmorang says.
NLP models can understand complex structures of information stored on servers. They can help identify the source of this information, which would be immensely helpful to penetration or security testers.
In this video interview with Information Security Media Group, Situmorang discusses:
- Digital transformation of logistics companies;
- Potential business apps for generative AI and ChatGPT;
- Use cases for cybersecurity.
Situmorang has over 15 years of senior management experience in multiple businesses across verticals and horizontal streams. He has served in financial services industries such as banking, insure-tech and fintech. He is passionate about strategy and technology, and his technical areas of expertise are blockchain, AI, machine learning, metaverse, data science, IoT and digital transformation.